Transition Towards a Sustainable Biobased Economy [64] 9781788015912

Table of contents :
Cover
Half Title
Green Chemistry Series
Transition Towards a Sustainable Biobased Economy
Copyright
Contents
1. Introduction: Tackling Uncertainty in the Biobased Economy Through Science
1.1 Introduction
1.2 Proposed Framework of Analysis: Science–Policy and Science–Market Bridges for Reducing Uncertainty
1.2.1 Techno-economic Uncertainty
1.2.2 Environmental and Social Uncertainty
1.2.3 Mapping and Bridging Uncertainty in the Biobased Economy
1.3 Uncertainty Map and Book Structure
1.4 Conclusions
Acknowledgements
References
2. Upstream Environmental Assessment
2.1 Introduction
2.1.1 Sugar Sources – Sugar Beet
2.1.1.1 Environmental Sustainability of Sugar Beet
2.1.2.1 Environmental Sustainability of Maize
2.1.2 Sugar Sources – Maize
2.2 Life Cycle Assessment of Fermentable Sugars
2.2.1 Maize and Stover Processing
2.2.2 Sugar Beet Processing
2.2.3 Selected Environmental Impact Categories
2.2.4 Allocation
2.3 Results and Discussion
2.4 Conclusions
References
3. Downstream Environmental Assessment
3.1 Introduction
3.2 Literature Review
3.2.1 Industrial Best Practice Indicators
3.3 Methodology
3.3.1 Selection Criteria for LCA Complementary Efficiency Indicators
3.3.2 Conventional LCA Indicators
3.3.3 Novel and Existing Efficiency and Circular Metrics
3.3.3.1 Product Renewability
3.3.3.2 Process Material Circularity
3.3.3.3 Energy Intensity
3.3.4 LCA of STAR-ProBio Case Studies
3.3.5 Goal, Scope and Functional Unit
3.3.6 Process Description
3.3.7 Scenario Description
3.3.8 Packaging Films
3.3.8.1 Mulch Films
3.3.8.2 Polymer Resins
3.3.8.3 Assumptions and Other Considerations
3.4 Result Interpretations: Gate-to-gate Impact and Resource Efficiency
3.4.1 Sensitivity Study: The Impact of Resource Efficiency and Waste Minimisation Strategies
3.4.1.1 Limitations of the Proposed Sustainability Analysis Methods
3.5 Conclusion
Acknowledgements
References
4. Techno-economic Sustainability Assessment: Methodological Approaches for Biobased Products
4.1 Introduction
4.1.1 Techno-economic Sustainability Analysis
4.2 Techno-economy Sustainability Analysis Methodology for Renewable Feedstock Resources Used for Biobased Products
4.2.1 Natural Renewable Resources – Introduction
4.2.1.1 Natural Renewable Resources and Resource Use Efficiency
4.2.1.2 Techno-economic Sustainability Assessment in Relation to Biomass
4.2.2 Objectives
4.2.3 Methodological Approach to Resource Use in TESA
4.2.3.1 Supply Chain and Life Cycle Material Flow Scheme
4.2.3.2 Biomass Resources
4.2.3.3 Abiotic Resources
4.2.3.4 TEA approach in the Sustainability Aspects
4.2.4 Recapitulation
4.3 Techno-economy Sustainability and Analysis Methodology for Conversion Routes of Renewable Feedstock Resources to Biobased Products
4.3.1 Methodology Development
Step 1: Identification of International Standards, Initiatives and Legi
Step 2: Literature Review on Techno-economic Sustainability Studies for
Step 3: Identification of Gaps on Techno-economic & Sustainability Ind
Step 4: Development of Principles, Criteria and Indicators for Techno-
4.3.2 System Boundaries
4.3.3 Scope of the Techno-economic & Sustainability Assessment
4.3.4 TESA Principle, Criteria & Indicators
4.4 Techno-economy Sustainability Analysis Methodology for Alternative EoL Options for Post-consumer Biobased Products
4.4.1 Methodology
4.4.2 TESA Criteria for Alternative EoL Options for Post-consumer/Post-consumer/Post-industrial Biobased Products
Acknowledgements
References
5. Market Assessment
5.1 Introduction
5.2 Sustainability Transition Towards a Biobased Economy
5.2.1 Sustainability Transition in Sociotechnical Regimes
5.2.2 Quality Infrastructure and Sustainability Assessment Schemes
5.2.3 User Acceptance
5.2.4 User Acceptance in Transition Processes
5.3 Importance of Sustainability Criteria and Research Gaps
5.3.1 Fundamental Characteristics of Relevance for Consumers of Sustainable Biobased Products
5.3.2 Environmental Topics of Relevance for Consumers of Sustainable Biobased Зкщвгсеы
5.3.3 Social and Economic Criteria of Relevance for Consumers of Sustainable Biobased Зкщвгсеы
5.3.4 Research Gaps Regarding Sustainability Assessment Schemes for Biobased Products
5.4 Research Methodology
5.5 End Consumers’ and Professionals’ Sustainability Preferences
5.5.1 Propensity to Buy Biobased Products and Importance of Specific Kinds of Information for the Buying Decisions
5.5.2 Preferences Regarding Environmental Aspects
5.5.3 Preferences Regarding Social and Economic Aspects
5.6 Relevance of Sustainability Certification
5.7 Additional Important Factors for Buying Decisions
5.8 Market Assessment for Specific Products
5.9 Conclusions and Outlook
References
6. Social Assessment
6.1 Introduction
6.2 Methodology
6.2.1 Main Features
6.2.2 Measurement Challenges
6.3 S-LCA Applied to Bio-based Products: A General Framework
6.3.1 Stakeholder Engagement in Social Sustainability Studies
6.4 Results and Discussion
6.4.1 Stakeholder Identification and Classification
6.4.2 Stakeholders Mapping According to Their Power and Interest
6.4.3 Stakeholders Validation of Social Impact Categories, Subcategories and Indicators
6.5 Conclusions
Acknowledgements
References
7. Indirect Land Use Change and Bio-based Products
7.1 Traditional and Novel Uses of Land
7.2 Direct and Indirect Land Use Changes
7.3 Evidence of iLUC Effects
7.4 Consequences and Magnitude of the LUC
7.5 Assessment of LUC Impacts
7.5.1 LUC Impacts and the Time Dimension
7.5.2 Food vs. Fuel Debate
7.6 iLUC Assessment and Related Uncertainties
7.6.1 Economic Equilibrium Models
7.6.2 Causal Descriptive Models
7.6.3 Uncertainties Related to Existing Models
7.6.4 The Renewable Energy Directive RED II: An Example of Normative Framework
7.7 The STAR-ProBio Approach: The SydiLUC Model
7.8 Conclusion
Acknowledgements
References
8. Conclusions
Acknowledgements
References
Subject Index

Citation preview

Transition Towards a Sustainable Biobased Economy

Green Chemistry Series Editor-in-chief: James H. Clark, Department of Chemistry, University of York, UK

Series editors: George A. Kraus, Iowa State University, USA Andrzej Stankiewicz, Delft University of Technology, The Netherlands Peter Siedl, Federal University of Rio de Janeiro, Brazil

Titles in the series: 1: 2: 3: 4: 5: 6: 7: 8: 9:

The Future of Glycerol: New Uses of a Versatile Raw Material Alternative Solvents for Green Chemistry Eco-Friendly Synthesis of Fine Chemicals Sustainable Solutions for Modern Economies Chemical Reactions and Processes under Flow Conditions Radical Reactions in Aqueous Media Aqueous Microwave Chemistry The Future of Glycerol: 2nd Edition Transportation Biofuels: Novel Pathways for the Production of Ethanol, Biogas and Biodiesel 10: Alternatives to Conventional Food Processing 11: Green Trends in Insect Control 12: A Handbook of Applied Biopolymer Technology: Synthesis, Degradation and Applications 13: Challenges in Green Analytical Chemistry 14: Advanced Oil Crop Biorefineries 15: Enantioselective Homogeneous Supported Catalysis 16: Natural Polymers Volume 1: Composites 17: Natural Polymers Volume 2: Nanocomposites 18: Integrated Forest Biorefineries 19: Sustainable Preparation of Metal Nanoparticles: Methods and Applications 20: Alternative Solvents for Green Chemistry: 2nd Edition 21: Natural Product Extraction: Principles and Applications 22: Element Recovery and Sustainability 23: Green Materials for Sustainable Water Remediation and Treatment 24: The Economic Utilisation of Food Co-Products 25: Biomass for Sustainable Applications: Pollution Remediation and Energy 26: From C-H to C-C Bonds: Cross-Dehydrogenative-Coupling 27: Renewable Resources for Biorefineries

28: Transition Metal Catalysis in Aerobic Alcohol Oxidation 29: Green Materials from Plant Oils 30: Polyhydroxyalkanoates (PHAs) Based Blends, Composites and Nanocomposites 31: Ball Milling Towards Green Synthesis: Applications, Projects, Challenges 32: Porous Carbon Materials from Sustainable Precursors 33: Heterogeneous Catalysis for Today’s Challenges: Synthesis, Characterization and Applications 34: Chemical Biotechnology and Bioengineering 35: Microwave-Assisted Polymerization 36: Ionic Liquids in the Biorefinery Concept: Challenges and Perspectives 37: Starch-based Blends, Composites and Nanocomposites 38: Sustainable Catalysis: With Non-endangered Metals, Part 1 39: Sustainable Catalysis: With Non-endangered Metals, Part 2 40: Sustainable Catalysis: Without Metals or Other Endangered Elements, Part 1 41: Sustainable Catalysis: Without Metals or Other Endangered Elements, Part 2 42: Green Photo-active Nanomaterials 43: Commercializing Biobased Products: Opportunities, Challenges, Benefits, and Risks 44: Biomass Sugars for Non-Fuel Applications 45: White Biotechnology for Sustainable Chemistry 46: Green and Sustainable Medicinal Chemistry: Methods, Tools and Strategies for the 21st Century Pharmaceutical Industry 47: Alternative Energy Sources for Green Chemistry 48: High Pressure Technologies in Biomass Conversion 49: Sustainable Solvents: Perspectives from Research, Business and International Policy 50: Fast Pyrolysis of Biomass: Advances in Science and Technology 51: Catalyst-free Organic Synthesis 52: Hazardous Reagent Substitution: A Pharmaceutical Perspective 53: Alternatives to Conventional Food Processing: 2nd Edition 54: Sustainable Synthesis of Pharmaceuticals: Using Transition Metal Complexes as Catalysts 55: Intensification of Biobased Processes 56: Sustainable Catalysis for Biorefineries 57: Supercritical and Other High-pressure Solvent Systems: For Extraction, Reaction and Material Processing 58: Biobased Aerogels: Polysaccharide and Protein-based Materials

59: Rubber Recycling: Challenges and Developments 60: Green Chemistry for Surface Coatings, Inks and Adhesives: Sustainable Applications 61: Green Synthetic Processes and Procedures 62: Resource Recovery from Wastes: Towards a Circular Economy 63: Flow Chemistry: Integrated Approaches for Practical Applications 64: Transition Towards a Sustainable Biobased Economy

How to obtain future titles on publication: A standing order plan is available for this series. A standing order will bring delivery of each new volume immediately on publication.

For further information please contact: Book Sales Department, Royal Society of Chemistry, Thomas Graham House, Science Park, Milton Road, Cambridge, CB4 0WF, UK Telephone: þ44 (0)1223 420066, Fax: þ44 (0)1223 420247 Email: [email protected] Visit our website at www.rsc.org/books

Transition Towards a Sustainable Biobased Economy Edited by

Piergiuseppe Morone Unitelma Sapienza University of Rome, Italy Email: [email protected] and

James H. Clark University of York, UK Email: [email protected]

Green Chemistry Series No. 64 Print ISBN: 978-1-78801-591-2 PDF ISBN: 978-1-83916-027-1 EPUB ISBN: 978-1-83916-028-8 Print ISSN: 1757-7039 Electronic ISSN: 1757-7047 A catalogue record for this book is available from the British Library r The Royal Society of Chemistry 2020 All rights reserved Apart from fair dealing for the purposes of research for non-commercial purposes or for private study, criticism or review, as permitted under the Copyright, Designs and Patents Act 1988 and the Copyright and Related Rights Regulations 2003, this publication may not be reproduced, stored or transmitted, in any form or by any means, without the prior permission in writing of The Royal Society of Chemistry or the copyright owner, or in the case of reproduction in accordance with the terms of licences issued by the Copyright Licensing Agency in the UK, or in accordance with the terms of the licences issued by the appropriate Reproduction Rights Organization outside the UK. Enquiries concerning reproduction outside the terms stated here should be sent to The Royal Society of Chemistry at the address printed on this page. Whilst this material has been produced with all due care, The Royal Society of Chemistry cannot be held responsible or liable for its accuracy and completeness, nor for any consequences arising from any errors or the use of the information contained in this publication. The publication of advertisements does not constitute any endorsement by The Royal Society of Chemistry or Authors of any products advertised. The views and opinions advanced by contributors do not necessarily reflect those of The Royal Society of Chemistry which shall not be liable for any resulting loss or damage arising as a result of reliance upon this material. The Royal Society of Chemistry is a charity, registered in England and Wales, Number 207890, and a company incorporated in England by Royal Charter (Registered No. RC000524), registered office: Burlington House, Piccadilly, London W1J 0BA, UK, Telephone: þ44 (0) 20 7437 8656. For further information see our web site at www.rsc.org Printed in the United Kingdom by CPI Group (UK) Ltd, Croydon, CR0 4YY, UK

Contents Chapter 1 Introduction: Tackling Uncertainty in the Biobased Economy Through Science P. Morone and F. Govoni 1.1 1.2

Introduction Proposed Framework of Analysis: Science–Policy and Science–Market Bridges for Reducing Uncertainty 1.2.1 Techno-economic Uncertainty 1.2.2 Environmental and Social Uncertainty 1.2.3 Mapping and Bridging Uncertainty in the Biobased Economy 1.3 Uncertainty Map and Book Structure 1.4 Conclusions Acknowledgements References Chapter 2 Upstream Environmental Assessment I. Camara-Salim, G. Feijoo and M. T. Moreira 2.1

2.2

Introduction 2.1.1 Sugar Sources – Sugar Beet 2.1.2 Sugar Sources – Maize Life Cycle Assessment of Fermentable Sugars 2.2.1 Maize and Stover Processing 2.2.2 Sugar Beet Processing 2.2.3 Selected Environmental Impact Categories 2.2.4 Allocation

Green Chemistry Series No. 64 Transition Towards a Sustainable Biobased Economy Edited by Piergiuseppe Morone and James H. Clark r The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

vii

1

1 3 4 5 6 7 9 10 10 12

12 16 22 28 29 30 32 32

viii

2.3 Results and Discussion 2.4 Conclusions Acknowledgements References

33 38 39 39

Chapter 3 Downstream Environmental Assessment K. Lokesh, J. Clark and A. Mathuru

44

3.1 3.2

Introduction Literature Review 3.2.1 Industrial Best Practice Indicators 3.3 Methodology 3.3.1 Selection Criteria for LCA Complementary Efficiency Indicators 3.3.2 Conventional LCA Indicators 3.3.3 Novel and Existing Efficiency and Circular Metrics 3.3.4 LCA of STAR-ProBio Case Studies 3.3.5 Goal, Scope and Functional Unit 3.3.6 Process Description 3.3.7 Scenario Description 3.3.8 Packaging Films 3.4 Result Interpretations: Gate-to-gate Impact and Resource Efficiency 3.4.1 Sensitivity Study: The Impact of Resource Efficiency and Waste Minimisation Strategies 3.5 Conclusion Acknowledgements References Chapter 4 Techno-economic Sustainability Assessment: Methodological Approaches for Biobased Products D. Briassoulis, A. Koutinas, J. Go!aszewski, A. Pikasi, D. Ladakis, M. Hiskakis and M. Tsakona 4.1 4.2

Introduction 4.1.1 Techno-economic Sustainability Analysis Techno-economy Sustainability Analysis Methodology for Renewable Feedstock Resources Used for Biobased Products 4.2.1 Natural Renewable Resources – Introduction 4.2.2 Objectives

44 45 47 50 50 51 52 58 60 61 61 61 68

73 75 76 76

80

80 80

83 83 88

Contents

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4.2.3

Methodological Approach to Resource Use in TESA 4.2.4 Recapitulation 4.3 Techno-economy Sustainability and Analysis Methodology for Conversion Routes of Renewable Feedstock Resources to Biobased Products 4.3.1 Methodology Development 4.3.2 System Boundaries 4.3.3 Scope of the Techno-economic & Sustainability Assessment 4.3.4 TESA Principle, Criteria & Indicators 4.4 Techno-economy Sustainability Analysis Methodology for Alternative EoL Options for Post-consumer Biobased Products 4.4.1 Methodology 4.4.2 TESA Criteria for Alternative EoL Options for Post-consumer/Post-industrial Biobased Products Acknowledgements References

Chapter 5 Market Assessment L. Ladu and S. Wurster 5.1 5.2

5.3

Introduction Sustainability Transition Towards a Biobased Economy 5.2.1 Sustainability Transition in Sociotechnical Regimes 5.2.2 Quality Infrastructure and Sustainability Assessment Schemes 5.2.3 User Acceptance 5.2.4 User Acceptance in Transition Processes Importance of Sustainability Criteria and Research Gaps 5.3.1 Fundamental Characteristics of Relevance for Consumers of Sustainable Biobased Products 5.3.2 Environmental Topics of Relevance for Consumers of Sustainable Biobased Products

88 97

98 98 104 105 105

109 109

113 123 124

133

133 134 134 137 138 139 139

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141

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Contents

5.3.3

Social and Economic Criteria of Relevance for Consumers of Sustainable Biobased Products 5.3.4 Research Gaps Regarding Sustainability Assessment Schemes for Biobased Products 5.4 Research Methodology 5.5 End Consumers’ and Professionals’ Sustainability Preferences 5.5.1 Propensity to Buy Biobased Products and Importance of Specific Kinds of Information for the Buying Decisions 5.5.2 Preferences Regarding Environmental Aspects 5.5.3 Preferences Regarding Social and Economic Aspects 5.6 Relevance of Sustainability Certification 5.7 Additional Important Factors for Buying Decisions 5.8 Market Assessment for Specific Products 5.9 Conclusions and Outlook Acknowledgements References

Chapter 6 Social Assessment E. Imbert and P. M. Falcone 6.1 6.2

Introduction Methodology 6.2.1 Main Features 6.2.2 Measurement Challenges 6.3 S-LCA Applied to Bio-based Products: A General Framework 6.3.1 Stakeholder Engagement in Social Sustainability Studies 6.4 Results and Discussion 6.4.1 Stakeholder Identification and Classification 6.4.2 Stakeholders Mapping According to Their Power and Interest 6.4.3 Stakeholders Validation of Social Impact Categories, Subcategories and Indicators 6.5 Conclusions Acknowledgements References

142 144 145 147

147 150 151 154 155 156 159 161 161

166

166 168 168 170 171 174 175 175 176 180 184 185 185

Contents

xi

Chapter 7 Indirect Land Use Change and Bio-based Products D. Marazza, E. Merloni and E. Balugani 7.1 7.2 7.3 7.4 7.5

Traditional and Novel Uses of Land Direct and Indirect Land Use Changes Evidence of iLUC Effects Consequences and Magnitude of the LUC Assessment of LUC Impacts 7.5.1 LUC Impacts and the Time Dimension 7.5.2 Food vs. Fuel Debate 7.6 iLUC Assessment and Related Uncertainties 7.6.1 Economic Equilibrium Models 7.6.2 Causal Descriptive Models 7.6.3 Uncertainties Related to Existing Models 7.6.4 The Renewable Energy Directive RED II: An Example of Normative Framework 7.7 The STAR-ProBio Approach: The SydiLUC Model 7.8 Conclusion Acknowledgements References Chapter 8 Conclusions J. H. Clark Acknowledgements References Subject Index

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192 193 197 199 202 202 204 205 206 208 210 212 215 218 219 219 223

225 225 226

CHAPTER 1

Introduction: Tackling Uncertainty in the Biobased Economy Through Science P. MORONE* AND F. GOVONI Unitelma Sapienza University of Rome, Bioeconomy in Transition Research Group, Viale Regina Elena 295, 00161, Rome, Italy *Email: [email protected]

1.1 Introduction Europe is confronted by the depletion of natural resources due to, among other issues, their unsustainable use, increased global competitiveness, the global population growth rate, and other challenging environmental and economic issues.1 Promoting the sustainable growth of dynamic bioeconomy sectors will contribute to the transition from a fossil fuel-based society to an innovative, resource-efficient and competitive one. Biobased products represent a great opportunity to reconcile sustainable long-term growth with environmental protection through the wise and forethoughtful use of renewable resources for industrial purposes. However, managing those resources in a sustainable manner implies the addressing of major social, economic and environmental challenges and facing the potential risks associated with direct and indirect land use change as well as competition with the food industry.2 Bearing this in mind, to steer the transition process along the desired sustainable pathway, specific policy and strategies should be designed to define a supportive regulatory structure.3 Green Chemistry Series No. 64 Transition Towards a Sustainable Biobased Economy Edited by Piergiuseppe Morone and James H. Clark r The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

1

2

Chapter 1

To this aim, several sectoral policies and strategies have been developed in order to support the establishment of a comprehensive and effective policy framework for a biobased economy in Europe. In this sense, we can recall: the Common Agricultural Policy; the 2013 EU Forest Strategy; the Common Fisheries Policy; the Blue Growth Agenda; and the European Innovation Partnership for Agriculture. Along with sectoral policies, the European Union has also adopted a series of horizontal policies affecting different value chains of the bioeconomy and supporting the transition toward a resource-efficient and low carbon economy. To this end, the following can be mentioned: the Europe 2020 strategy; the Lisbon Agenda; European Circular Economy Package; the COP21 Paris Agreement; the 2030 Climate and Energy Policy; the Lead Market Initiative; the European Bioeconomy Strategy and Action Plan; the Innovation Europe Flagship Initiative. In addition to strategies and policies, regulatory tools like standards and certification schemes can further support the establishment of a sustainable bioeconomy. Standards and certifications play a central role in promoting innovation activities by reducing perceived uncertainty and prompting the market uptake of new products. The role of standards is especially relevant in markets characterised by a high degree of uncertainty – such as the biobased market – stemming from the technological domain as well as social and environmental realms.4 In this respect, the development of comprehensive sustainability schemes and assessment tools for biobased products represents a first fundamental step towards the design of such standards and certification schemes, contributing to a clear and evidence-based view of environmental, economic and social impacts of biobased products and assisting policy makers in shaping their policy agenda. In this regard, the identification of new and effective ways of bridging the gap between scientists and policy makers is crucial to encourage the development, implementation and an effective management of the evidence-informed regulatory frameworks,5 reducing in turn the uncertainty associated with the development of a radically new economic model. Bearing this in mind, this book presents research results obtained within the Horizon 2020 project STAR-ProBio, aimed at promoting the development of sustainability schemes (including standards, labels and certifications) for the assessment of biobased products, which are considered fundamental to the establishment of a cutting-edge sustainable bioeconomy. The book is a collection of six chapters (plus an introductory and a concluding chapter), which cover a range of issues spanning from upstream and downstream environmental assessment, techno-economic assessment, social assessment, to crosscutting issues such as indirect land use change (iLUC) and end-of-life options. In this introductory chapter we propose an overarching framework of analysis to grasp the impact that sustainability schemes and sustainability assessment tools can play in reducing uncertainty and promoting the transition towards a bioeconomy – making sense of the research conducted in the following six chapters as pieces of a complex puzzle which need to be considered unitarily in order to achieve the desired goal.

Introduction: Tackling Uncertainty in the Biobased Economy Through Science

3

The remainder of this introduction is organised as follows: a theoretical discussion, reviewing the concept of uncertainty associated with the bioeconomy, is provided in Section 1.2; in Section 1.3, the proposed uncertainty map is offered to the reader as a red thread linking the six main chapters composing the book; Section 1.4 presents concluding remarks.

1.2 Proposed Framework of Analysis: Science–Policy and Science–Market Bridges for Reducing Uncertainty Uncertainty is a major challenge for new economic activities as well as for already established businesses aiming to explore new opportunities. In the presence of a high degree of uncertainty, entrepreneurs might be reluctant from investing financial resources while policy makers could be discouraged from promoting a transition whose societal and environmental impacts are not clear. Hence, it is no surprise that economists have repeatedly attempted to tackle the issue of uncertainty in transition processes. Building on the traditional definition first proposed by Frank Knight,6 uncertainty can be understood as risk that is not possible to calculate. In this sense, uncertainty differs from risk as the latter refers to a situation where the probability of the alternative outcomes (or alternative states of the world) is either known ex ante or can be reliably estimated. Conversely, uncertainty entails the impossibility of specifying numerical probabilities for specific events. Beyond uncertainty, more often than not, obtaining knowledge about all alternative outcomes is problematic. Under this condition, economists introduced two further notions – namely ambiguity and ignorance. Following Dosi and Egidi,7 we shall refer to these four types of uncertainty (i.e. risk, uncertainty, ambiguity and ignorance) as substantive uncertainty. Another layer can be added when introducing procedural uncertainty – that uncertainty associated with the lack of cognitive competences needed to make the best possible use of the available information. In other words, under procedural uncertainty decision makers are constrained in their computational and cognitive capabilities. As argued in Morone and Tartiu,8 complex innovation systems – such as the one involving a transition to a biobased economy – are largely characterised by both substantive and procedural forms of uncertainty. For the sake of clarity, in the context of a transition to a biobased economy, we shall reduce these areas of uncertainty to two domains of analysis. Uncertainty associated with a new biobased socio-technological regime stems from unknown internal costs and benefits (techno-economic uncertainty) as much as from unknown external costs and benefits (e.g. environmental and social uncertainty). These two domains of uncertainty affect, in turn, the market structure and the policy action. On the one hand, a high degree of techno-economic uncertainty might prevent investors from endowing the needed resources and putting innovative

4

Chapter 1

activities on hold. This undermines the market potential development of the new economic activity and might ultimately prevent the transition from occurring. High degree of environmental and social uncertainty, on the other hand, would pose a constraint to policy actions aiming at stimulating the transition – since investing taxpayers’ money into a policy action whose social and environmental benefits are not fully proofed might turn to be a rather unpopular policy initiative.

1.2.1

Techno-economic Uncertainty

Following Maijer et al.,9 and elaborating on their proposed framework, we shall maintain that techno-economic uncertainty stems from the following internal sources: 1. Technical uncertainty: this source of uncertainty stems directly from the lack of knowledge on the production process associated with the new technology. Typically, this refers to poor information available on the cost structure of the new technology, the availability of several concurring technological options (hence the lack of a technologically dominant design) and the stakeholders’ perception of technology (based on their knowledge, previous experiences, expectations, risk aversion, etc.). Further, uncertainty about the relation between the technology and the infrastructure within which the new technology will be integrated is also relevant. Thus, this source of uncertainty may hinder a proper assessment of the innovation and consequently postpone the innovation decision or even encourage its abandonment. 2. Resource uncertainty: this source of uncertainty refers typically to the lack of financial and human resources. However, in the context of the biobased economy transition, the role of feedstock availability becomes extremely relevant. In this regard, interlinkages across different levels of the value chain become crucial involving, for instance, the cascading use of resources. 3. Functionality uncertainty: this source of uncertainty is associated with products characteristics. The biobased economy is not only about producing the same products in different ways, but mostly producing new products in different ways and using different inputs. This implies a growing uncertainty related to products functionality associated with, among other things, the quality of feedstocks, the reliability of production processes, the chemical and mechanical properties of new materials, consumers’ acceptance of new product designs, etc. These three sources of uncertainty involve two typologies of actors: producers and consumers and propagate into the locus of their interaction – i.e. the market. Hence, techno-economic uncertainty impacts on market uncertainty.

Introduction: Tackling Uncertainty in the Biobased Economy Through Science

1.2.2

5

Environmental and Social Uncertainty

External sources of uncertainty refer to the lack of knowledge on the impact that the new socio-technological regime will have on social welfare through environmental and social externalities. In this sense, environmental and social uncertainty stems from the following external sources: 1. Environmental uncertainty: this source of uncertainty relates to the lack of knowledge on the overall impact of the new process or product on the environment. Albeit the transition out of a fossil-based economy into a biobased one is undertaken with the specific aim of reducing the impact on the environment, the superiority in terms of environmental sustainability of biobased products with respect to conventional ones is not straightforward and has to be rigorously proved. This relates to the high complexity associated with the new biobased regime, which involves a plethora of variables and the associated web of causal relations (often involving complex feedback effects, revers causality and simultaneity) on a global scale. Moreover, the environmental impact should be always assessed looking at both upstream (i.e. the use of alternative feedstocks and processes) and downstream (i.e. end biobased products and their fossil-based commercial equivalents) stages of the value chain taking into consideration alternative end-of-life routes. 2. Social uncertainty: this source of uncertainty relates to the lack of knowledge on the impact that the new biobased regime has on societal challenges including, among others: green jobs creation, labour conditions, rural area development, social inclusion and food security. Again, uncertainty stems from the complexity of the system and the multitude of variables involved. As an exemplification, the unforeseen food crops vs. energy crops debate has cast a shadow on the biofuel sector among researchers, analysts and policy makers as well as the general public. 3. Health uncertainty: this source of uncertainty has two dimensions. On the one hand, it relates to the impact that the new biobased production system has on workers operating in possibly contaminated environments (e.g. those operating on waste valorisation plants or dealing with potentially toxic chemicals); on the other hand, it relates to the impact that consumables, produced for instance with secondary raw materials, might have on consumers health (e.g. food packaging, cutlery, diapers, cosmetics, etc.). These three sources of uncertainty involve two typologies of actors: policy makers and consumers and propagate into the policy domain where they interact in the form of principal and agent. Hence, environmental and social uncertainty impacts on policy uncertainty as it poses a hurdle to the deployment of proactive policies in support of the transition.

6

1.2.3

Chapter 1

Mapping and Bridging Uncertainty in the Biobased Economy

Building on the framework developed above, Table 1.1 summarises domains, sources and actors associated with uncertainty in the biobased economy. This mapping exercise allowed us identifying four domains within which uncertainty arises. Our next step will aim at establishing cross-links among these domains and defining possible bridges to curb uncertainty. As discussed above, techno-economic uncertainty impacts upon market uncertainty. Hence, reducing techno-economic uncertainty might, in turn, impact positively upon market uncertainty. Specifically, performing a scientifically sound assessment of production costs and revenues (associated with alternative production functions as well as alternative feedstock) would allow producers to be more confident in the real chances of being competitive in the emerging market, and to assess their chances of success in the medium and long run. Moreover, this would affect consumers who are interested in products functionality and price and would perceive price signals as indicators of market stability. This suggests that, developing scientifically robust methodologies, considering the whole life cycle of new products as well as the entire value chain, will allow curbing market uncertainty and, eventually, stimulate the market uptake of new biobased products. Similarly, environmental and social uncertainty can be addressed by means of analytically rigorous environmental and social impact assessment. This involves processes to identify, predict and evaluate the impacts of new products and processes upon the environment (including all possible sources of positive and negative externalities) and key social indicators. In turn, a rigorous assessment of such impacts might prove to be a rather powerful tool to support science-based policy decision and, therefore, reduce policy uncertainty. As it seems, the first two domains of uncertainty produce effects in terms of uncertainty related to the market stability and its potential size (the need to set new and complex value chains, which require long-term perspectives), as well as the uncertainty associated with the overarching policy framework. Table 1.1

Domains, sources and actors associated with uncertainty in the biobased economy.

Domains of analysis

Sources of uncertainty

Involved actors

Domains of impact

Producers and Market uncertainty Technical uncertainty consumers Resource uncertainty Functionality uncertainty Policy makers and Policy uncertainty Environmental and Environmental consumers/citizens social uncertainty uncertainty Social uncertainty Health uncertainty Techno-economic uncertainty

Introduction: Tackling Uncertainty in the Biobased Economy Through Science

Figure 1.1

7

Uncertainty map.

Figure 1.1 summarises these links and the proposed establishment of science-policy and science-market bridges as a way of reducing uncertainty and promoting the transition to a biobased economy. Market and policy domains are characterised by the existence of selfreinforcing links. Indeed, stable and harmonised policies would accelerate the market uptake of biobased products. In turn, a fast-growing market could trigger the policy interest and stimulate the adoption of supportive actions. By the same coin, this virtuous circle could revert into a vicious one, impeding the transition.

1.3 Uncertainty Map and Book Structure Building on the conceptual framework developed in Section 1.2, we shall now look into the specific content of this book, assessing the contribution of each chapter in reducing market and policy uncertainty acting through the environmental and social domain and the techno-economic domain. Moving from the assumption that biobased products’ sustainability needs to be proofed, the chapters of this book provide a scientifically-based harmonised approach for environmental, social and economic sustainability assessments. This serves the purpose of reducing techno-economic uncertainty by assessing internal costs and benefits occurring through the whole value chains associated with new biobased products, as well as reducing environmental and social uncertainty by assessing external costs and benefits associated with the introduction of such new products in the market. In turn, this leads to the reduction of market and policy uncertainty by the definition of specific tools able to bridge science-policy and sciencemarket realms.

8

Chapter 1

Chapters 2 and 3 deal with upstream and downstream environmental assessment. Specifically, Chapter 2 provides an overview regarding the upstream activities that constitute forest and agricultural biomass production systems and primary processing (previous to downstream activities), paying special attention to the determination of their environmental assessment. The analysis is focused on the assessment of alternative feedstocks potential on selected biobased products. Chapter 3 focuses on how selected key sustainability characteristics can be quantitatively and qualitatively captured through use of life cycle analysis (LCA) and novel non-LCA based methodologies, covering a biobased product from their ‘‘manufacturing’’ to ‘‘end-of life’’ phases. Uncertainty domain of analysis: environmental and social uncertainty Uncertainty domain of impact: policy uncertainty Chapter 4 presents a techno-economic sustainability analysis methodology for resource efficiency and the utilisation of renewable feedstocks for the production of biobased products. This includes the conversion routes of renewable feedstock resources to biobased products and development of technoeconomic sustainability analysis methodology encompassing bioeconomy and circular economy aspects. It includes the definition of alternative end-of-life routes for biobased products and development of the techno-economic sustainability analysis methodology for each major end-of-life route. Finally, it defines techno-economic sustainability indicators for biobased products from alternative feedstocks through their end-of-life procedures. Uncertainty domain of analysis: techno-economic uncertainty Uncertainty domain of impact: market uncertainty Chapter 5 looks closely at market dynamics providing an overview of the results of a foresight activity aimed at identifying the demand for new sustainability criteria that are easily understood by different consumer groups (end consumers, businesses and public procurers) and relevant to their needs. In this regard, this chapter attempts to lays a bridge between market needs – exemplified by consumer demand for new sustainability criteria, and research trajectories in providing such criteria. Uncertainty domain of analysis: techno-economic uncertainty and environmental and social uncertainty Uncertainty domain of impact: market uncertainty Chapter 6 provides an overview of a Social Life Cycle Assessment (S-LCA) tailored to biobased products. As the authors maintain, despite being an emerging methodology, it offers a way to assess a product’s socio-economic impacts, including human health related aspects, throughout the value chain, which represents a key issue in the specific case of biobased products.

Introduction: Tackling Uncertainty in the Biobased Economy Through Science

9

It also provides key indications to policy makers concerned with the social impacts of a complex and pervasive transition out of a fossil-based society. Uncertainty domain of analysis: environmental and social uncertainty Uncertainty domain of impact: policy uncertainty Chapter 7 provides insights on those mechanisms which may lead to undesired land use changes associated to the expansion of biobased products and which may result in adverse environmental and social impacts. Main findings in the literature are summarised and differences of biofuel vs. biobased products cases are shown in this chapter. It also shows how production routes can be associated to specific factors whose values proved sensitive to the land market and to subsequent land conversions. A novel risk approach to anticipate and counteract adverse effects is illustrated. Uncertainty domain of analysis: environmental and social uncertainty Uncertainty domain of impact: policy uncertainty

1.4 Conclusions In this introductory chapter we propose a framework of analysis to grasp the impact that sustainability schemes and sustainability assessment tools can play in reducing uncertainty and promoting the transition towards a biobased economy. The six main chapters composing this book will provide scientific insights on how such schemes can be developed in a way that sustainability is assessed along the whole supply chain and in a circular perspective. Moving from the assumption that a biobased economy is not a sustainable one by definition, this book will provide the reader with a comprehensive, albeit preliminary, set of methodologies and scientifically sound tools for sustainability assessment, paving the way to evidence-informed policy actions. We suggest a framework of analysis where uncertainty is associated with two domains (the techno-economic domain and the environmental and social domain), which impact respectively on market uncertainty and policy uncertainty. The uncertainty mapping exercise served the purpose of providing an overarching umbrella where solutions to promote the transition towards a biobased economy can be identified in a way that bridges environmental and social sustainability as well as techno-economic sustainability with market-related issues and policy interventions. The ongoing work undertaken as part of the STAR-ProBio project has, ultimately, the ambitious objective of developing two appropriate tools as viable ways of reducing market and policy uncertainty acting through the environmental and social domain and the techno-economic domain. Specifically, the research presented in this book is preparatory to the development of a fit-for-purpose sustainability assessment blueprint (the SAT-ProBio), which comprises a thoroughly selected list of indicators, both qualitative and quantitative, to assess biobased products’ sustainability. The selection of such

10

Chapter 1

indicators is based on the complementary methodologies presented in the six chapters composing this book. The SAT-ProBio also serves the purpose of allowing comparisons between conventional and biobased counterparts. In this way, the blueprint becomes a valuable tool for supporting evidenceinformed policy interventions and for creating a level playing field. Once identified, the effectiveness of such policy intervention(s) can be evaluated against other policy actions aimed at boosting the transition to a circular biobased economy. To this aim, STAR-ProBio is also developing a user-friendly policy tool for assessing the impact of alternative policies (the SyD-ProBio). Specifically, a system dynamic model is being developed to assess different policy scenarios and provide policy recommendations for fostering the market development of biobased products. This serves the purpose of capturing the main drivers of the emerging biobased economy and providing support in fine-tuning policy interventions. The SAT-ProBio and the SyD-ProBio are tightly linked to each other. Specifically, echoing the mentioned nexus between market and policy domains, the indicators selected to shape the SAT-ProBio feed into the SyD-ProBio structure (in the form of key variables). In turn, the SyD-ProBio provides a flexible tool to assess the impact of alternative policy scenarios upon market penetration of biobased products. All in all, both tools provide an attempt to overcome uncertainty by means of scientifically sound approaches. At the same time, the ‘user-friendly’ nature of such tools allows creating an interface between science and policy making as well as between science and market operators including all relevant stakeholders (e.g. producers, consumer associations, trade associations, etc.).

Acknowledgements The authors are very grateful to the STAR-ProBio project (Sustainability Transition Assessment and Research of Bio-based Products) for their financial support. The project is funded by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 727740, Work Programme BB-01-2016: Sustainability schemes for the bio-based economy.

References 1. P. Morone, The times they are a-changing: making the transition toward a sustainable economy, Biofuel. Bioprod. Bioref., 2016, 10, 369–377. 2. L. Ladu and K. Blind, Overview of policies, standards and certifications supporting the European bio-based economy, Curr. Opin. Green Sustainable Chem., 2017, 8, 30–35. 3. L. Ladu and R. Quitzow, Bio-based economy: Policy framework and foresight thinking, in Food Waste Reduction and Valorisation: Sustainability Assessment and Policy Analysis, ed. P. Morone, F. Papendiek and V. E. Tartiu, Springer, 2017.

Introduction: Tackling Uncertainty in the Biobased Economy Through Science

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4. K. Blind, S. S. Petersen and C. A. F. Riillo, The impact of standards and regulation on innovation in uncertain markets, Res. Policy, 2017, 46(1), 249–264. 5. K. Bultitude, P. Rodari and E. Weitkamp, Bridging the gap between science and policy: the importance of mutual respect, trust and the role of mediators, Jcom, 2012, 11(03), C01. 6. F. H. Knight, Risk, Uncertainty, and Profit, Houghton Mifflin, Boston, MA, USA, 1921. 7. G. Dosi and M. Egidi, Substantive and procedural uncertainty, J. Evol. Econ., 1991, 1, 145–198. 8. P. Morone and V. E. Tartiu, Addressing Uncertainty in Complex Systems— The case of bio-based products derived from urban bio-waste valorisation, in Uncertainty Management in Simulation-Optimization of Complex Systems: Algorithms and Applications, ed. C. Meloni and G. Dellino, Operations Research/Computer Science Interfaces Series, Springer, Berlin, Germany, vol. 59, ISBN 978-1-4899-7546-1, 2015. 9. I. S. M. Meijer, M. P. Hekkert, J. Faber and R. E. Smits, Perceived uncertainties regarding socio-technological transformations: towards a framework, Int. J. Foresight Innov. Policy, 2006, 2(2), 214–240.

CHAPTER 2

Upstream Environmental Assessment I. CAMARA-SALIM,* G. FEIJOO AND M. T. MOREIRA Santiago de Compostela University, CRETUS Institute, Department of ´mez de Marzoa, s/n, 15705 ´a de Lope Go Chemical Engineering, Ru ˜ a, Spain Santiago de Compostela, A Corun *Email: [email protected]

2.1 Introduction In Europe, total biomass production is estimated at 1500 Mt (dry matter), of which 65% comes from agriculture and 35% from forestry. These values account not only for the harvestable biomass but also for the one essential in the support of the ecosystem. In terms of the major components of biomass in Europe, the highest percentages correspond to sugar and starch (carbohydrates) and cellulosic raw materials, with Germany and France being the main suppliers of agricultural biomass in Europe. Most of this biomass is used in the feed and food industry (62%), followed by the biofuels (19%) and bioproducts sectors (19%). Although these percentages are significant, it must be taken into account that there is a gap in the data on the share of biomass used for the production of biofuels and biotechnological products, so that assumptions taken may be under or overestimated.1 Regarding biobased products, a plethora of feedstocks can provide a sugar intermediate as a platform chemical for the production of this type of material (Figure 2.1). They include edible crops, i.e. sugar crops (e.g. sugar beet and sugarcane) and starch crops (wheat and maize), residues from agricultural activities, including lignocellulosic crops (e.g. maize stover and wheat straw) and Green Chemistry Series No. 64 Transition Towards a Sustainable Biobased Economy Edited by Piergiuseppe Morone and James H. Clark r The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

12

Upstream Environmental Assessment

Figure 2.1

13

General flow diagram of paths for fermentable sugars.

residues from industrial side stream (e.g. sugar beet pulp, molasses and bagasse). Depending on the quality of the raw material considered, these carbohydrate sources are mainly used for food and feed supply or as an intermediate platform for the production of biofuels (e.g. bioethanol and biogas). While it is clear that the technological way to convert edible crops into sugars (e.g. glucose and sucrose) is considered fully developed, there is no comparable level for lignocellulosic crops. Although significant progress has been made in this field, it remains a challenge to carry out hydrolysis of the raw material and overcome the limitations imposed by the recalcitrant nature of lignin, as well as to increase sugar production yields throughout the supply chain to ensure a process with a high level of efficiency and sustainability.2 Life Cycle Assessment (LCA) has been extensively used to assess the environmental burdens of agricultural cropping systems. Most of these studies focuses on agriculture for food and feed ingredients.3–7 Although scarce, studies have been found that aim to evaluate the environmental sustainability of fermentable sugars for the production of bioproducts, as shown in Table 2.1. The majority of the encountered literature focuses on biofuels and highlights the final product life cycle as a functional unit, such as bioethanol.8–10 In fact, the justification for the technological and environmental feasibility of biofuel production is largely behind this type of study, with the evaluation of bioethanol production standing out among all the publications. Owing to techno-economic downsides, the upstream unit processes are hitherto considered as bottlenecks of biorefineries. Therefore, by selecting those fermentable sugar options with the best environmental profile, it is possible to improve the environmental impacts associated with the biorefinery concept. Table 2.1 shows the LCA studies in which sugar production is evaluated in greater detail, considering its production as a functional unit.

14 Table 2.1 Life cycle assessment studies of fermentable sugars. Acronyms: FD – Fossil Depletion, CC – Climate Change, AC – Acidification, EP – Eutrophication, NPV – Net Present Value, WD – Water Depletion, ALOP – Agricultural Land Occupation, HT – Human Toxicity, NREU – Non-Renewable Energy Use, OD – Ozone Depletion, PM – Particulate Matter, IR – Ionising Radiation, POF – Photochemical Oxidant Formation. Impact categories

Feedstocks

Main processes involved

Functional unit

– Sugarcane – Sugar beet – Maize

– Agriculture – Sugar extraction – Milling and Enzymatic hydrolysis

1 tonne of saccharide

– – – – –

– Hardwood mill residuals – Low value hardwood

– Forestry operations – Supercritical water pretreatment – Enzymatic hydrolysis

kg fermentable sugar

– FD – WD – CC

Thomas et al. (2012)61

– Poplar

– – – – – – –

kg of sugars

– CC – FD

TAO et al. (2014)62

– – – –

– Diluted acid pre-treatment (DAP) – Ammonia fibre expansion

kg Fermentable Sugar

– FD – CC

Adom et al. (2014)36

Source Renouf et al. (2008)18

Chapter 2

Maize stover Switchgrass Poplar Miscanthus

Ammonia fibre expansion Diluted acid Liquid hot water Soaking aqueous ammonia Ammonia recycle percolation Steam explosion Enzymatic hydrolysis

FD AC CC EP WD

– Agriculture – Milling and enzymatic hydrolysis

kg of starch and glucose

– – – – – – –

CC OD PM IR POF AC WD

Vercalsteren and Boonen (2015)59

– Maize stover

– – – – – –

kg of fermentable sugars

– – – –

CC EP WD AC

Prasad et al. (2016)29

– Softwood

kg dry mass sugar

– OD

– Harvest residues

– Mild bisulfite (MBS) pretreatment – Enzymatic hydrolysis

– Sugar beet

– Sugar extraction

kg of hexose equivalent – CC

Vargas-Ramirez et al. (2017)64

– Spruce – Maize

– – – – –

kg C6 sugars

Moncada et al. (2018)60

Agriculture Milling Steam explosion Diluted acid Orgonosolv Liquid hot water

Agriculture Forestry operations Milling Organosolv Anaerobic digestion

Nwaneshiudu et al. (2016)63

Upstream Environmental Assessment

– Wheat, maize and potato

POF – AC – EP – HT – PM – – – – – –

NPV CC WD ALO HT NREU

15

16

Chapter 2

As observed in Table 2.1, it is not easy to make a comparison between the different studies, largely due to the different life cycle impact assessment methods used. Starting from this premise, this study will address the study of the agricultural and pre-processing stages of fermentable sugars from different potential feedstocks, such as sugar beet, maize and maize stover. These raw materials were chosen taking into account their availability in Europe and their carbohydrate content. The following sections describe the specificities of sugar beet and maize cultivation and present a literature review on the LCA studies of these two crops to understand the current scope of research in this field.

2.1.1

Sugar Sources – Sugar Beet

Sugar beet is an important crop for the production of sugar (i.e. sucrose), accounting for 36% of the world sugar supply. Its importance increased in the Napoleonic period due to the disruption of the sugar cane market from the colonies to Europe. From the twentieth century onwards, sugar beet cultivation went from being a very labour-intensive activity to an extensive system with the use of specific machinery that enabled higher yields to be achieved. Although sugar beet is grown all over the world, its cultivation is associated with temperate climates. In continental Europe, sugar beet crops are usually grown in spring until late autumn or early winter, when processing for sugar starts. In Mediterranean areas, sugar beet is sown in autumn and harvested in summer.11 Modern sugar beet is scientifically known as Beta vulgaris ssp. vulgaris. Thanks to photosynthesis, the plant begins to form sugar and store it within its root, the wet weight composition of which is associated with sucrose, pulp and molasses in percentages of 14%, 5.5%, 3.7%, respectively.12 The amount of sugar produced by the plant varies according to geographic and climatic conditions, soil type, fertilisers, harvest date and storage time. After harvesting there is a gradual loss of sugar content, so factory processing must be carried out afterwards in order not to lose product yield.11 Sugar beet accounts for 36% of the world sugar supply.13 Considering that sugar production has been primarily associated with the food sector, sugar beet has not been considered as an important raw material for bioproducts. However, changes in dietary habits and competition with other sugars (e.g. sugar cane sucrose) are pushing sucrose consumption in Europe to reach a tipping point. Natural and artificial sweetener options are gaining market weight, with the use of high-fructose corn syrup (HFCS) as a source of low-cost sugars that have been incorporated into a multitude of foods. On the other hand, in economic terms, European export policies facilitate the entry into the market of sugar from sugar cane. Considering the possibility that the market for sugar derived from sugar beet may find a less niche market, it may be time to look for alternatives to sucrose products. Therefore, the overall supply chain needs to be assessed, taking into account not only sucrose as the raw

Upstream Environmental Assessment

Figure 2.2

17

Multiple uses of sugar beet.

material, but also the use of by-products such as leaves and branches of the plant as well as those derived from sugar beet processing (i.e. molasses and sugar beet pulp).14 Figure 2.2 summarises the many possible applications of sugar beet as raw material. In relative percentages, Europe is the world’s largest producer of sugar beet, with France, Germany, Poland and the United Kingdom being the largest producers (Figure 2.3a). France and Germany together account for more than 50% and 20% of the European and world sugar beet production, respectively (Figure 2.3b). The average yield in Europe in 2017 was 70 150 kg ha 1 with more than 1.5 million ha of harvested area. Belgium showed the highest yield (95 114 kg ha 1) and Germany the largest area (406 700 ha). Globally, 4 894 026 ha was used for sugar beet cultivation, with an average yield of 61 506 kg ha 1, with the largest area harvested in the Russian Federation (around 1 million ha) and Chile with the highest yield, with 108 069 kg ha 1.15

2.1.1.1

Environmental Sustainability of Sugar Beet

Understanding the root and fate of environmental impacts related to agricultural activities is a challenging task. There is a wide and complex range of variables, for example, the numerous pre-harvest tillage activities, the use of fertilisers, the need for irrigation, plant protection and land use. It is considered that, in order to carry out sustainability analysis of processes and

18

Chapter 2 (a)

40 35

Million tonnes

30 25 20 15 10 5 0 France

Germany

Poland

United Kingdom

Rest of Europe

(b)

Russia France Germany United States Rest of the world

Figure 2.3

(a) Main sugar beet producers in Europe. Total sugar beet produced in Europe: 131 million tonnes (FAOSTAT, 2017) and (b) Share of world’s sugar beet producers. Total worldwide sugar beet produced: 301 million tonnes (FAOSTAT, 2017).

products, the LCA methodology emerges as one of the most efficient tools in the identification of environmental impacts since it exhaustively analyses all the processes that are linked to the life cycle of a process or product. In this way, it is necessary to gather extensive information from each of the stages involved, but in return, the management of this information can be visualised in the form of global environmental impacts, which can help define strategies to develop in decision making. In this section, the literature on LCA of sugar beet cultivation and processing are reviewed, pointing out the main outcomes of these studies. The geographical coverage, functional unit, system boundaries, impact categories and type of allocation are presented in Table 2.2. A significant number of LCA studies related to sugar beet cultivation and processing have

Authors and year

Geographical coverage

Purpose of LCA study

Functional unit (FU) Foreground input data

Brentrup et al. Germany (2001)16

1 tonne of To compare the extractable sugar impact of three different nitrogen fertilisers Bennett et al. United Kingdom Environmental 50 tonnes of sugar (2004)17 beet and Germany assessment of genetically modified sugar beet, tolerant to herbicides Renouf et al. USA, United UK sugar beet as sugar kg monosaccharide (2008)18 Kingdom and producers for from sugar beet Australia fermentation

Field activities, pest CC, OD, AET, AC, — control, field emissions EP, SS, PM and HH

Foteinis et al. Greece (2011)20

To understand if substituting sugar processing plants to biofuel plants is sustainable To assess the Product 1 tonne of white sugar Carbon Footprint (PCF) of EU beet sugar

Field activities, fertilisers, CC pest control, field emissions, transport of crop, crop processing

Mass, Economic, Energy, System expansion

19

Sugar production in Sweden from 1995 until 2015

Europe

Field activities, fertilisers, CC, EP, AC and SS — pest control, field emissions

System Field activities, fertilisers, FD, AC, EP, WD expansion pest control, field emissions, transport of crop, crop processing — 50 000 ha of arable Field activities, fertilisers, CC, EP, FCU land in southern pest control, field Sweden emissions, transport of crop, crop processing 35 Gcal of bioethanol Field activities, fertilisers, AD, CC, OD, HT, — FET, MET, TET, from sugar beet pest control, field POF, AC, EP emissions, transport of crop, crop processing

Ness (2011)19 Sweden

Klenk et al. (2012)21

Impact categories Allocation

Upstream Environmental Assessment

Table 2.2 Summary of the literature review on LCA of sugar beet feedstock. Acronyms: AC – Acidification, AD – Abiotic Depletion, AET – Aquatic Ecotoxicity, ALO – Agricultural Land Occupation, BES – Biodiversity and Ecosystem Services, CC-Climate Change, CED – Cumulative Energy Demand, EP – Eutrophication, ET – Ecotoxicity, FCU – Field Chemical Use, FD – Fossil Depletion, FE – Freshwater Eutrophication, FET – Freshwater Ecotoxicity, HT – Human Toxicity, IR – Ionising Radiation, LU – Land Use, ME – Marine Eutrophication, MET – Marine Ecotoxicity, OD – Ozone Depletion, POF – Photochemical Oxidant Formation, PM – Particulate Matter, SS – Summer Smog, TE – Terrestrial Eutrophication, TET – Terrestrial Ecotoxicity, WD – Water Depletion.

20

Table 2.2

(Continued)

Authors and year

Geographical coverage

˜ oz et al. Mun (2014)10

France

Soheili-Fard Iran and KouchakiPenchah (2015)7 Maravı´c et al. Serbia (2015)22

Europe

Alexiades et al. (2018)24

California

Functional unit (FU) Foreground input data

Impact categories Allocation

To comprehend the 1 kg ethanol from Field activities, fertilisers, CC, POF, AC, FE, Economic ME, ALO, BES sugar beet in pest control, field environmental France emissions, transport of impacts of crop, crop processing bioethanol and to compare with its fossil counterpart Sugar beet cultivation 1 tonne of sugar beet Field activities, fertilisers, CC, AD, FD, AC, — EP, OD, HT, considering three pest control, field FET, MET, TET, emissions farm levels (Large, POF medium and small) 1 mg of beet sugar Crop processing CC, CED Economic Economic and environmental assessment of improving the purification process of a sugar processing plant in Serbia 1 tonne of white beet Field activities, fertilisers, CC, OD, HT, PM, System LCA methodological IR, POF, AC, EP, expansion, sugar pest control, field improvements for ET, LU, WD, AD mass, energy emissions, transport of fair environment crop, crop processing report in the EU sugar beet industry — 1 MJ ethanol Field activities, fertilisers, CC Environmental pest control, field performance of emissions, transport of biofuels from sugar crop, crop processing beet in California

Chapter 2

Spoerri and ¨gi Ka (2016)23

Purpose of LCA study

Upstream Environmental Assessment

21

been published. Studies available from 2000 to date were considered as selection criteria, attempting to gather useful information on sugar beet cultivation in different countries of the world. The aim is to provide an overview of the environmental sustainability of this crop system. An LCA study compared the impacts of three different fertilisers (urea, calcium ammonium nitrate and urea ammonium nitrate) used in sugar beet cultivation in Germany.16 Environmental impacts increased when urea fertiliser was applied. Differences in results are mainly due to ammonia volatilisation, which varies according to each type of fertiliser. Moreover, acidification and eutrophication were the impact categories that most contributed to the overall environmental burdens of the system studied. Another investigation17 explored the use of a genetically modified sugar beet with high herbicide tolerance. The results showed that the cultivation of genetically modified (GM) sugar beet could reduce environmental impacts due to higher production yields and indirect impacts associated with the transport of herbicides. However, this study did not consider risk assessment related to genetic modification. An LCA analysis18 compared three types of feedstocks for the production of sugars, i.e. Australian sugarcane, US Maize and UK sugar beet. The recoverable sugars from maize amounts to 60% (wt), compared to sugarcane and sugar beet (15% wt). Nevertheless, sugarcane provides high crop yield and consequently, the highest sugar yield per hectare. Although sugar beet cultivation does not require intensive fertilisation, it does demand greater use of pesticides. When introducing the impact associated with the by-products associated with each crop into the analysis, it is necessary to assign environmental burdens and evaluate the benefits obtained by valuing these flows. The by-product bagasse from sugarcane processing can provide energy, reducing greenhouse gases (GHG) emissions, whereas alternative uses of by-products of sugar beet, such as pulp and molasses, may lessen eutrophication impacts. It is interesting to assess how sugar production can affect the ecological quality of the productive area. In Sweden, a substantial decrease in biodiversity due to the replacement of native lands by arable areas from 1995 to 2015 was evidenced.19 Sweden has no organic beet cultivation and the ease of importing organic sugar from other regions prevents organic production from being established. In Northern Greece, an LCA study20 assessed the environmental consequences of transforming sugar beet facilities into bioethanol plants. It was found that, with the same amount of sugar beet, the results were better for bioethanol production than for sugar plants, with a total reduction of more than 30% in the environmental burdens. A review of different carbon footprint methodologies as well as a comparison of the sugar beet industry carbon footprint with its main substitutes, namely sugarcane, starch-based glucose and fructose syrups, were investigated for the EU.21 The results from a cradle-to-gate assessment revealed that sugar cultivation and processing stages account for 32% and 64% of total global warming impacts, respectively. The remaining 4% of the impacts are due to the transportation phase. Steam production from sugar beet

22

Chapter 2

processing accounts for up to 50% of the global GHG emissions. In terms of GHG impacts from sugar beet cultivation, NO2 emissions, production of nitrogen fertiliser and the use of diesel represent the most relevant impacts, with shares of 40%, 29% and 23%, respectively. This study also highlighted the difficulty of comparing different carbon footprint (PCF) studies of similar products due to different methodological choices. In an additional processing step, a comparative analysis of various biomasses for bioethanol production was carried out.10 As expected, biomass ethanol has less impact on GHGs, but if land use is taken into account, petrochemical ethanol has less impact. Only when land use is not considered was ethanol production from sugar beet in France the best compared to wheat in France, maize in the United States and sugar cane in Brazil. The threat of climate change and the depletion of fossil resources are the two fundamental drivers in the transition from fossil fuels to biomass; however, this change must carefully consider wider range of environmental impacts affecting ecosystems integrity and their consequences in the future. Sugar beet has been analysed in other countries where production does not represent a major volume.7 Interestingly, no substantial difference was found between different types and sizes of the harvested plant in Iran, with machinery and electricity being identified as the main environmental burdens, followed by the use of fertilisers and pesticides. In Serbia, the environmental profile of a sugar processing plant was assessed,22 identifying sugar beet cultivation and the use of natural gas as the main activities associated with environmental burdens. A broader study of 11 sugar companies in 18 countries identified that the agricultural cropping stage plays an important role in environmental impacts.23 In contrast, the impacts of transporting the sugar beet from the plots to the processing plant are irrelevant in comparison to the cultivation and processing phases. Another study evaluated the environmental profile of sugar beet bioethanol production in California.24 The results indicated that optimisation of by-products from the crop processing phase, such as biochar, can reduce the environmental burden by applying it as a soil amendment.

2.1.2

Sugar Sources – Maize

Along with rice and wheat, maize (Zea mays ssp.) is considered one of the ‘‘big three’’,25 providing almost 30% of the calories present in food for people in developing countries, while in the developed countries maize is mainly used as feed. Originating from North and Central America, maize is considered a starch crop due to its high carbohydrate content. It is classified as a summer crop as it needs optimal temperatures between 20 and 24 1C. Despite these conditions, it is cultivated almost everywhere in the world, except in the polar areas. Normally the sowing season begins in spring and is harvested in autumn. However, the sowing and harvesting periods depend on the type of maize, whether maize silage or grain. It also depends on the grain maturity class and geoclimatic circumstances. For instance, in the north-western regions of

Upstream Environmental Assessment

23

Europe, where there are fewer summer hours, maize production is better suited to silage because the crop does not need to be fully matured, while the warmer regions of Europe produce mainly grain maize. Nitrogen fertilisation is fundamental in maize cultivation. In addition, the practice of irrigation is common in the Mediterranean region, contrary to central and north of Europe where maize is mostly rainfed.26,27 In many countries, especially in the tropics, maize is grown mainly on a small scale as a means of subsistence. Large maize-producing countries use hybrid maize breeding, intensive fertilisation and mechanical operations with high diesel consumption.28 In addition to food and feed, maize can have a plethora of uses, including the production of starch, sweeteners, beverages, biofuels and bioproducts.26 Maize stover, which is a residue of maize crops, is composed of leaves, husks, stalks and cobs.29 It is rich as a soil amendment and can also be used as animal feed. In addition, it has a high lignocellulose content, which makes it possible to produce biofuels and bioproducts from this waste. Figure 2.4 represents a general description of the many choices of products made from maize. In the last decade, world production has grown steadily from about 792 million tonnes in 2007, 850 million tonnes in 2010 and 1.13 billion tonnes in 2017.15 Currently, the average global yield is approximately 5.5 tonnes ha 1, with a total of up to 200 million hectares of arable land used for maize cultivation in the world. China is the country that uses the most arable land for maize (21.5% of the global land use). Maize production in Europe is very modest, representing only 5.7% and 4% of the global production quantity and harvested area, respectively.15 As shown in Figure 2.5a, the largest

Figure 2.4

Multiple uses of maize.

24

Chapter 2 (a) 20 18 16 Million tonnes

14 12 10 8 6 4 2 0 Romania

France

Hungary

Italy

Rest of Europe

(b)

United states China Brazil Argentina Rest of the world

Figure 2.5

(a) Main maize grain producers in Europe. Total maize produced in Europe: 64 million tonnes (FAOSTAT, 2017) and (b) Share of major’s grain maize producers. Total worldwide maize produced: 1.13 billion tonnes (FAOSTAT, 2017).

producers in Europe are Romania and France, followed by Hungary and Italy. In the world, the United States and China are by far the largest producers, accounting for more than 50% of the total production (Figure 2.5b).

2.1.2.1

Environmental Sustainability of Maize

This section gathers literature on LCA of maize cultivation and processing, summarising main outcomes of these studies. The geographical coverage, functional unit, system boundaries, impact categories and type of allocation are presented in Table 2.3. Many LCA studies related to the use of maize biomass could be identified. Table 2.3 presents a summary of the most

Authors and year

Geographical coverage Purpose of LCA study

Buratti et al. (2008)30

General

Renouf et al. (2008)18

US

Kim et al. (2009)18

US

Murphy and Kendall (2013)32

US

Tsiropoulos Europe et al. (2013)33 Jayasundara Ontario, et al. (2014)34 Canada

Functional unit (FU) Foreground input data

Impact categories

Allocation

1 MJ ethanol

25

System expansion, Field activities, fertilisers, CC, OD, HT, mass, energy PM, IR, ET, pest control, field and economic AC, EP, LU, emissions, transport of AD, FD crop, crop processing, transport of product US maize cultivation as kg monosaccharide Field activities, fertilisers, FD, AC, EP, WD System expansion sugar producers for from maize pest control, field fermentation emissions, transport of crop, crop processing 1 kg of grain and 1 kg Field activities, fertilisers, FD, CC, AC, EP System expansion, Comparison of two of stover pest control, field mass cropping systems: emissions maize grain with and without stover collection Energy, economic, 1 ha of corn and Field activities, fertilisers, FD, AC, EP Comparison of three subdivision stover production pest control, field allocation methods used for maize and emissions, transport of crop stover European glucose pro1 kg of glucose Crop processing CC, NREU Subdivision duction from maize economic, mass and system expansion Economic and Field activities, fertilisers, CC, FD Environmental burdens 1 mg of grain and system 1 Mg of stover pest control, field of maize and stover expansion emissions production in Ontario Environmental burdens of producing bioethanol from maize

Upstream Environmental Assessment

Table 2.3 Summary of the literature review on LCA of maize feedstock. Acronyms: AC – Acidification, AD – Abiotic Depletion, AET – Aquatic Ecotoxicity, CC-Climate Change, CED – Cumulative Energy Demand, EP – Eutrophication, ET – Ecotoxicity, FD – Fossil Depletion, FE – Freshwater Eutrophication, FET – Freshwater Ecotoxicity, HT – Human Toxicity, IR – Ionising Radiation, LU – Land Use, ME – Marine Eutrophication, MET – Marine Ecotoxicity, OD – Ozone Depletion, POF – Photochemical Oxidant Formation, PM – Particulate Matter, TE – Terrestrial Eutrophication, TET – Terrestrial Ecotoxicity, WD – Water Depletion.

26

Table 2.3

(Continued)

Authors and year

Geographical coverage Purpose of LCA study

Bacenetti et al. Northern (2014)35 Italy Adom et al. (2014)36

General

Noya et al. (2015)37

Italy

Boone et al. (2016)38

Belgium

Liang et al. (2018)39

China

Functional unit (FU) Foreground input data

1 m3 of methane Environmental profile of two crop systems from maize grain for methane production Process simulation and 1 kg of sugar from maize stover environmental impacts of lignocellulosic crops to produce sugars Environmental profile 1 tonne of maize of different types of grain maize grain

Impact categories

Field activities, fertilisers, OD, HT, FET, MET, TET, pest control, field POF, CC, AC, emissions, transport of AD, EP crop, crop processing Crop processing FD, CC

Allocation —

—

Field activities, fertilisers, CC, OD, AC, FE, Mass and economic pest control, field ME, HT, POF, emissions TET, FET, MET, WD, FD Field activities, fertilisers, OD, POF, PM, — pest control, field CC, AC, FE, emissions ME

To account for dynamic 1 kg of maize grain in production maize system, instead of averages in the region of Flanders To assess the 1 mg of maize grain Field activities, fertilisers, AD, FD, WD, LU, CC, AC, environmental profile pest control, field EP, HT, AET, of Chinas farm system emissions, transport of TET crop

—

Chapter 2

Upstream Environmental Assessment

27

representative references according to a time horizon of 10 years and a wide range of countries. An LCA study30 on a generic bioethanol production from maize showed that maize cultivation is responsible for more than 60% of the environmental impacts. It also indicated that the choice of allocation methods had a great influence on the results. The system expansion approach was the most recommended allocation method if comprehensive system information and sufficient data to identify the impacts of products and by-products were available. Fermentable sugar production from maize in the US, sugar cane in Australia and sugar beet in UK were compared.18 The outcomes confirmed that maize-based saccharide has the worst performance on many environmental indicators, mainly due to the low sugar yield per hectare of this crop. Another LCA study in the US compared two cropping systems, maize cultivation with and without stover collection.31 The production of maize grain alone performed worse than the cultivation with stover collection. In addition, the removal of stover reduces nitrogen-based emissions. However, it deteriorates soil quality due to the depletion of organic carbon. An LCA study32 comparing three different allocation methods for maize and maize stover in the US demonstrated that economic and subdivision allocation methods have much less impact for stover than energy allocation. It is important to consider that the allocation choices are driven by the purpose of the study and the quality of data. If, for instance, market prices for stover are well established, consideration can be given to using the economic allocation. It is therefore preferable to use different allocation methods for stover production. The environmental profile of glucose from maize production was investigated for Europe.33 Since the milling industry is known for its valuable by-products, the effects of allocation were also made using subdivision, economic, mass and system expansion approaches. In terms of glucose production, as regards the energy-related indicator, the choice of different allocation methods did not show significant changes in the results, as opposed to the results for GHG emissions, which were sensitive to allocation methods. The outcomes for by-products using different allocation types had greater discrepancies compared to glucose production. When analysing the time scale of the crop between 2006–2011,34 the activities that most affect energy intensity for maize grain production are grain drying and the use of nitrogenous agrochemicals. Therefore, more sustainable ways of drying the grain and the use of maize hybrids could potentially reduce the amount of energy used. In Northern Italy, an LCA work35 stressed that the method chosen to account for nitrogen-related emissions is very important as it has a great influence on the results. Nitrogen fertilisation is one of the most impactful activities in maize cultivation, mainly related to the impact categories of eutrophication and acidification. In addition, it is recommended to use methods that take into account site-specific parameters.

28

Chapter 2

The environmental profile of sugar production from lignocellulosic crops was evaluated,36 considering as raw materials maize stover, switchgrass, poplar and Miscanthus (silvergrass). The outcomes show that, by using the diluted acid pre-treatment method (DAP), maize stover is the best-case scenario, consuming less energy. The authors noted the difficulty of comparing the results with other studies, due to the few references that focus on the environmental sustainability of sugar production from lignocellulosic biomass. In Northern Italy, different classes of maize were compared using the LCA methodology.37 The results vary substantially according to the class of maize, mostly because they present very different yields, and some require lower fertiliser application. This study provides information for decision making about the type of maize that should be considered when aiming to reduce the environmental impacts of an agricultural process. A different LCA approach investigated the dynamics of farm systems in Flanders, Belgium.38 Fifteen scenarios and site-specific local data were considered. An interesting consideration is that policy options are important for improving the environmental profile of maize production systems. Another point is that genetic improvement of maize can improve the overall environmental sustainability of the cropping system, as higher yields are expected. China is also a major producer of maize, the second largest in the world. However, this country faces a significant reduction in arable land. An LCA work of agricultural systems in China39 analysed wheat and maize crop rotation, applying standardisation and weighting steps in the assessment, taking into consideration human and ecosystem health and the use of natural resources. The outcomes showed that special attention needs to be given to lower the levels of eutrophication and toxicity of water bodies in China. The normalisation stage was performed in terms of per capita values for China and the globe. It highlighted that very different results were identified by comparing the normalisation factors of China with the global ones. For instance, for land use indicator, the values for China and the world were 2.79 and 0.47 person equivalent per t of grain, respectively.

2.2 Life Cycle Assessment of Fermentable Sugars Beyond the bibliographic review of the different LCAs on sugar production, this section aims to provide its own results, revisiting the data published in the bibliography, but establishing a comparison between the fermentable sugars of maize, maize stover and sugar beet. The functional unit considered is 1 kg of fermentable sugars from maize, maize stover and sugar beet. To this end, bibliographic data, databases and data from industrial partners were assessed. This LCA is a ‘‘cradle-to-gate’’ assessment, whose system boundary considers agricultural activities, feedstock transportation, feedstock processing and transportation to the factory. The following sections describe in more detail the system boundaries for each raw material. Table 2.4 shows the scenarios and sources considered for the life cycle inventory phase.

Upstream Environmental Assessment

29

Table 2.4

Life cycle inventories sources of sugar beet, maize and maize stover for agriculture and processing phases. Acronyms: UK – United Kingdom, FR – France, DE – Germany, US – United States, IT – Italy, BE – Belgium.

Scenarios

Description

Agriculture A1 A2 A3 A4 A5 A6

(A) Sugar beet (UK) Sugar beet (FR) Sugar beet (DE) Maize (US), considering 50% stover removal Maize (US), not considering stover removal Maize (IT), very low yield, considering total stover removal Maize (IT), very high yield, considering total stover removal Maize (BE), considering 50% stover removal

A7 A8

Processing (P) P1 Beet sugar. By-products: lime fertiliser and beet pulp P2 Beet sugar. By-products: molasse and beet pulp P3 Maize sugar. By-products: maize gluten feed, meal and oil P4 Maize sugar. By-products: maize gluten feed, meal and germ P5 Maize stover sugar

2.2.1

Sources Renouf et al.18 ˜oz et al.10 Mun Ecoinvent65 Renouf et al.18 A4 et al.18 Noya et al.37 Noya et al.37 Boone et al.38 Renouf et al.18 Maravı´c et al.22 Renouf et al.18 Moncada et al.60 Confidential data from industrial partner

Maize and Stover Processing

The production of glucose from maize is mainly done through a wet milling process, as the objective is to separate the main parts of this plant into starch and gluten. Wet mills generate a variety of valuable by-products, namely maize germ, maize oil, maize gluten feed, maize gluten meal, steepwater, etc. The quantity and quality of each product will depend on the producer and the consumer demand. Unlike dry milling, the wet milling process requires more energy and water. Its primary energy sources are mainly coal and natural gas.40 The production process begins with the cleaning of the maize grain and its dry milling to separate the germ from the kernel. The germ-free grain then undergoes a wet milling process to separate the starch from the gluten. On a dry weight basis, maize kernel can yield approximately 65% starch.41 The generated by-product gluten is sold as maize gluten meal and the fibre is blended with steepwater to produce maize gluten feed. Finally, the starch undergoes an enzymatic hydrolysis process to be converted into glucose. Enzymatic hydrolysis comprises the processes of liquefaction and saccharification. Liquefaction using water and heat will break the starch molecules, dissolving the starch in water. With the addition of amylase, starch is converted into dextrins. The solution is cooled and saccharification takes place. The enzyme glucoamylase will then convert dextrin to glucose.41 Figure 2.6 depicts a generic flow of maize processing into glucose.

30

Chapter 2

Figure 2.6

General scheme conversion of maize into bioproducts.

Maize stover can also be used as biomass to produce fermentable sugars. However, because of its recalcitrant nature, this biomass needs pretreatment steps before undertaking an enzymatic hydrolysis in order to facilitate the separation of the carbohydrate fraction from other components of the stover, such as lignin. Stover is a promising feedstock to be used in the biorefinery route, since it is an abundant residue from agricultural activities, has low cost and does not compete with food and feed markets. To date, stover has been mainly used as a soil conditioner and as animal feed. The stover is produced at a ratio of about 1 to 1 to maize grain.29 However, it is important that a fraction of the stover is kept in the soil to preserve soil quality and avoid nutrient losses in the field. Assuming that 50% of the stover would be removed from maize fields, about half billion and more than 32 million tonnes of stover would be available worldwide and in Europe, respectively.15 The stover biomass consists of approximately 38%, 26% and 19% of cellulose, hemicellulose and lignin, respectively. Its composition may vary slightly depending on the time of growth and geoclimatic conditions.29 In this study, maize stover is subjected to steam explosion with the objective of facilitating the enzymatic hydrolysis, transforming hemicellulose and cellulose into total sugars, composed mainly of glucose (B59%), xylose (B33%) and other sugars (B8%).

2.2.2

Sugar Beet Processing

The sugar industry is a consolidated technology in the market, which benefits from advanced research and development in this field. After harvesting and storage, the sugar beet is transported to the sugar processing plant, which is usually located near the cultivation area. At the factory, the sugar beet is washed and sliced into very small strips, named cosettes. Sugar extraction is done by diffusion using hot water, generating raw juice for further processing and beet pulp as a by-product. Impurities are removed

Upstream Environmental Assessment

Figure 2.7

31

General scheme conversion of sugar beet into bioproducts.

from the raw juice by the addition of lime and carbon dioxide to obtain a purer sucrose stream. Furthermore, the evaporation stage increases the concentration of sugar in the juice, representing on average between 50 and 60% of the sugar content. Sugars are then crystallised, and the crystals are separated by centrifugation. Molasses is produced as a by-product in the final stages of crystallisation and centrifugation, provided that no crystals are formed.42 The sucrose production for biorefineries does not require pre-treatment and hydrolysis processes and is easily converted to glucose and fructose in the fermentation stage. Figure 2.7 describes the conversion pathways from sugar beet to sugar and their subsequent applications in bioproducts. The residues and/or by-products from the cultivation and processing of sugar beet are sugar beet pulp (SBP), molasses, lime-based fertiliser, glue and the upper part of sugar beet (i.e. leaves and branches). A further step in the processing of sugar beet for the production of beverages or biofuels generates vinasse as a by-product.14,43 Unlike the formation of sucrose from sugar beet processing, the use of by-products (i.e. leaves and SBP) as raw material for further fermentation requires pre-treatment and hydrolysis steps as it is necessary to break down cellulose, hemicellulose, lignin and pectin into fermentable sugars.44 SBP and sugar beet leaves show high potential as feedstocks to be used on the route to sustainable biorefineries. To date, the use of SBP has been used primarily for animal feed, as dry pellet and silage. As total sugar beet production is 131 and 301 million tonnes in Europe and worldwide respectively,15 and the processing of 1 tonne of sugar beet can produce 70 kg of dried SBP,14 it can be assumed that annually around 9 and 21 million tonnes of SBP can be produced in Europe and worldwide, respectively. As far as sugar beet leaves are concerned, they represent up to 50% of the total biomass weight (wet basis)45 and sugar beet cultivation generates about 120 million tonnes of leaves in Europe each year. Sugar beet leaves are also a

32

Chapter 2

rich source of lignocellulose, and are composed of cellulose (13–18%), hemicellulose (11–17%), pectin (14–18%) and lignin (5–6%).46 SBP, also known as sugar beet bagasse, is an abundant by-product of sugar processing. It is insoluble in water and rich in polysaccharides. SBP is composed of approximately 22–24% cellulose, 30% hemicellulose, 15–25% pectin and 5.9% lignin.14,42 Acid or enzymatic hydrolysis of SBP yields a combination of glucose, fructose, xylose, mannose, galactose, arabinose and galacturonic acid. It is important to note that dry beet pulp has a low density, which makes it difficult to transport. Therefore, they are often pressed into granules to be transported.47 The other by-product of the sugar beet process, molasses, is formed in the final stages of crystallisation and centrifugation and is a potential feedstock for biofuels. The amount of molasses produced in sugar processing represents approximately 5% of the weight of sugar beet. This study only considers the transformation of beet root into sugars. However, further research on the processing of SBP into sugars should be encouraged with the aim of enhancing the value of these residues into the biorefinery route.

2.2.3

Selected Environmental Impact Categories

The life cycle inventory stage generates an extended list of elementary flows that are difficult to describe and communicate. However, the life cycle impact assessment (LCIA) phase will support the translation of these values into environmental indicators. In this context, caution is required when selecting LCIA methods because the results vary depending on the method chosen. The selected environmental indicators for impact assessment in this study are: 1) climate change48 (CC; unit – kg CO2 eq.), 2) particulate matter49 (PM; unit – deaths), 3) human toxicity, cancer50 (HT; unit – CTUh), 4) acidification (AC; unit – Mol H1 eq.), 5) freshwater eutrophication (FE; unit – kg P eq.),51,52 6) terrestrial eutrophication51,52 (TE; unit – kg N eq.), 7) water scarcity (WD; unit – m3 water deprived eq.), 8) fossil resource depletion53,54 (AD; unit – MJ) and 9) land use, soil quality index (LU; unit – Pt).55 These impact categories were chosen as recommended in the Product Environmental Footprint (PEF) guide56 and the International Reference Lice Cycle Data System (ILCD).57

2.2.4

Allocation

As aforementioned, sugar production, whether from starch or sugar crops, generates many valuable by-products. Therefore, it is important to allocate the environmental burdens of these by-products in order to have a fair outcome. Caution is needed when it comes to allocation, since the results of the environmental impact are different depending on the allocation method. Moreover, it is not straightforward to use system expansion allocation method as recommended by ISO 14040/4458 and the PEF guide.56 Economic allocation was considered here because important by-products are generated

Upstream Environmental Assessment Table 2.5

33

Mass and economic values for maize grain, maize stover and sugar beet.

Maize agriculture

Maize grain and stover yield (tonne ha 1)

Maize grain and stover price (h kg 1)

A4 A6 A7 A8

9.10; 9.10a 6.71; 8.57b 14.78; 17.67b 10.28; 10.28a

0.120c; 0.036d 0.178; 0.051d 0.178; 0.051d 0.184; 0.054d

(US) (IT) (IT) (BE)

Maize processing (P3)

Mass (kg kg

Maize Maize Maize Maize

0.027 0.268 0.080 1

oil gluten feed gluten meal sugar

Maize processing (P4)

Mass (kg kg

Maize Maize Maize Maize

0.105 0.290 0.091 1

germ gluten feed gluten meal sugar

Sugar beet processing (P1)

Mass (kg kg

Beet pulp Calcium carbonate Beet sugar

0.651 0.295 1

Sugar beet processing (P2)

Mass (kg kg

Beet pulp Molasses Beet sugar

0.340 0.390 1

1

maize grain)

Price (h kg 1) 0.910e 0.158 f 0.632 f 0.300 f

1

beet sugar)

Price (h kg 1) 0.270 f 0.158 f 0.632 f 0.300 f

1

maize grain)

Price (h kg 1) 0.156g 0.100e 0.423h

1

maize grain)

Price (h kg 1) 0.156g 0.105g 0.423h

a

Maize stover yield is assumed to be the same as grain (1-1). 50% of the stover is assumed to be removed from the field. b 100% of the maize stover is removed. c Source: US Department of Agriculture (USDA).66 d The price of maize stover is assumed to be 30% of the grain according to literature.37 e Source: Agri-footprint.67 f Source: Moncada et al.60 g Source: Maravı´c et al.22 h Source: European Commision.68

in the process. Energy allocation was not selected, as this assessment focuses on fermentation sugars that will be used for the production of bioproducts and not for energy production, such as biofuels. Table 2.5 shows the prices and quantities considered for the different scenarios.

2.3 Results and Discussion The environmental results of this assessment showed that upstream processes present a wide variety of case studies, mainly due to agricultural activities. Each type of agriculture has a unique profile, depending on many variables, such as geoclimatic conditions. Table 2.6 shows the average values and standard deviations of the sugar production of these three feedstocks.

34

Chapter 2

Table 2.6

Environmental impacts of 1 kg of sugar production from maize grain, sugar beet and maize stover. Average and standard deviation values.

Impact categories

Sugar beet

CC (kg CO2 eq.) PM (Deaths) HT (CTUh) AC (Mol H1 eq.) FE (kg P eq.) TE (Mol N eq.) WD (m3 water deprived eq.) FD (MJ) LU (Pt)

0.86  0.20 0.67  0.18 0.68  0.12 (1.87  1.75)
10 7 (9.44  6.06)
10 8 (8.00  4.15)
10 8 (6.56  2.12)
10 9 (6.71  4.13)
10 9 (6.60  3.09)
10 9 3 3 (0.022  0.026)
10 (0.014  0.007)
10 (0.011  0.005)
10 3 (1.58  0.51)
10 4 (1.42  0.77)
10 4 (2.14  0.58)
10 4 0.09  0.12 0.06  0.03 0.04  0.02 0.008  0.004 5.45  7.11 4.01  4.82

Maize grain

9.95  2.01 43  15

Maize stover

6.53  1.96 48  29

8.86  1.40 24  22

Comparaive profile (%)

100

80

60

40

20

0

CC

PM

HT

AC

Sugar beet

Figure 2.8

EF Maize grain

ET

LU

WD

FD

Maize stover

Comparative profile of the production of 1 kg of sugar from sugar beet, maize grain and maize stover (average values of the different scenarios).

In terms of absolute values, sugar beet performs the worst for CC, PM, AC, ET and FD. These results can also be explained by the fact that, unlike maize, residues from sugar beet cultivation, such as sugar beet leaves, were considered completely left in the field and no allocation was performed. Sugar production has higher impact on WD, HT and LU for maize grain and EP for maize stover. The absolute results can be better visualised in Figure 2.8. In addition, Figures 2.9, 2.10 and 2.11 show to what extent the results in the initial phases may differ from each scenario for sugar beet, maize grain and maize stover, respectively. There are few LCA studies on the production of fermentable sugars, making comparison of results difficult. In addition, the different methods used to calculate the environmental impact categories further complicate the comparison of the results with other papers. However, Vercalsteren and Boonen (2015)59 performed an LCA of glucose production from first-generation

Upstream Environmental Assessment

35

100

Comparative profile (%)

80

60

40

20

0

CC

PM Sc1 (A1P1)

Figure 2.9

HT

AC

Sc2 (A1P2)

EF

Sc3 (A2P1)

ET

Sc4 (A2P2)

LU Sc5 (A3P1)

WD

FD

Sc6 (A3P2)

Comparative environmental profiles to produce sugars from sugar beet (functional unit: 1 kg of fermentable sugars).

100

Comparative profile (%)

80

60

40

20

0

CC

PM

Sc7 (A4P3) Sc8 (A4P4)

Figure 2.10

HT

Sc9 (A5P3) Sc10 (A5P4)

AC

EF

Sc11 (A6P3) Sc12 (A6P4)

ET

LU

WD

FD

Sc13 (A7P3) Sc14 (A7P4) Sc15 (A8P3) Sc16 (A8P4)

Comparative environmental profiles to produce sugars from maize grain (functional unit: 1 kg of fermentable sugars).

feedstocks (potato, maize and wheat) with similar methods used in this present study. The results for the production of 1 kg of glucose showed an average of 0.80 kg CO2 eq. for CC, 0.011 mol H1 eq. for AC, 310 4 kg P eq. for FE and 0.048 Mol N eq. for TE. These results are within the range of the present study, given the high standard deviation of the mean values observed in Table 2.6. An LCA work36 on second-generation raw materials, one of which was maize stover, reported a result of 8.6 MJ kg 1 of sugar from maize stover. However, they considered the diluted acid pre-treatment (DAP) and not steam explosion as the pre-treatment method. Another study,60 who

36

Chapter 2 100

Comparative profile (%)

80 60 40 20 0 CC

PM

HT

AC

EF

ET

LU

WD

FD

-20 Sc17 (A8P5)

Figure 2.11

Sc18 (A7P5)

Sc19 (A6P5)

Sc20 (A4P5)

Comparative environmental profiles to produce sugars from maize stover (functional unit: 1 kg of fermentable sugars).

compared first with second-generation feedstocks, found that 9.01 MJ and 0.79 kg CO2 eq. per kg of sugar from maize grain were produced. Moreover, three different edible feedstocks to be used as fermentable sugars were investigated,18 showing environmental impacts of about 6 MJ and 1 kg CO2 eq. per kg of sugar from maize grain, and 5.25 MJ and 0.61 kg CO2 eq. per kg of sugar from sugar beet. Nevertheless, they used system expansion in the assessment to allocate the environmental impacts of the by-products. When performing a hotspot analysis, comparing the differences in terms of the agricultural and processing phases, it can be observed that agricultural activities are the main contributors to the global environmental impacts for the production of fermentable sugars from maize grains and sugar beet, as shown in Figures 2.12a and b. However, in the case of maize stover (Figure 2.12c), agricultural activities are not as representative, compared to the first-generation crops, sugar beet and maize grain. This is mainly due to the economic value of the maize stover, which is much lower than maize grain. The results of water depletion are greater for the processing phase in the case of maize grain and maize stover, since no irrigation is performed in the agricultural phase for this scenario. In general, the results show that the cultivation of raw materials contributes greatly to the environmental impact of sugar production. Therefore, since agricultural data have a substantial influence on the final results, it is important to take into account reliable agricultural data when performing LCA of fermentable sugars. Moreover, even if sugar producers are not involved in the agricultural process, the option to buy raw materials that are less harmful to the environment would reduce their overall environmental impact.

(a)

(b) 100%

80%

80%

60%

60% 40%

40%

20% 20% 0% CC

0% CC

PM

HT

AC

EF

Agriculture

ET

LU

WD

FD

PM

HT

AC

EF

ET

LU

WD

FD

-20%

Processing

Agriculture

Upstream Environmental Assessment

100%

Processing

(c) 100% 80% 60% 40% 20% 0% CC

PM

HT

AC

EF

ET

LU

WD

FD

-20% Agriculture

(a) Hotspots analysis for the case study A4P3 – Maize grain (Scenario 9); (b) Hotspots analysis for the case study A1P1 – Sugar beet (Scenario 1) and (c) Hotspots analysis for the case study A4P5 – Maize stover (Scenario 20).

37

Figure 2.12

Processing

38

Chapter 2

100%

80%

60%

Transport Seed Agricultural machinery

40%

Pesticides Fertilisation Field emissions

20%

0% CC

PM

HT

AC

EF

ET

LU

WD

FD

-20%

Figure 2.13

Hotspots analysis for the agriculture activities (case study in the US – A4).

Figure 2.13 identifies the processes of greatest environmental contribution to agriculture in the United States (A4, Table 2.4). It clearly shows that field emissions, fertilisation and transport contribute significantly to global environmental impacts. With respect to the FD, transport is responsible for more than half of this category of environmental impact and fertilisation contributes greatly to WD, since although irrigation is not applied in this agricultural case, a considerable amount of water is required in the production of fertilisers.

2.4 Conclusions Environmental concerns are leading to increased research involving the use of renewable biomass for bioproduct production. In addition, since edible biomass biofuels address the problem of competition with food and feed, and given that the population is growing, there is a bias in favour of the use of agricultural and industrial processing residues. However, the technology to process second-generation raw materials is in its initial stage due to the recalcitrant nature of lignocellulose. The environmental impacts of sugar production from three raw materials (sugar beet, maize grain and maize stover) were investigated through the LCA methodology. In total, 20 scenarios were analysed, and the results showed great variation for each case study, mainly due to agricultural activities that have unique conditions, depending on many variables, such as those associated with crop management and geoclimatic conditions. If the results are made in terms of mean values, it can be observed that beet production has the highest environmental impacts in five of the environmental impact categories (CC, PM, AC, TE and FD), while maize grain contributes more for HT and WD, and maize stover is the worst for FE. The greater impact related to sugar beet can be explained by the fact that,

Upstream Environmental Assessment

39

unlike maize grain and sugar cane, the allocation of residues in the agricultural phase of sugar beet was not considered, attributing all environmental impacts of agricultural activities to the beet root. The results from hotspots analysis also showed that agricultural activities contribute greatly to the production of sugar from sugar beet and grain maize and, to a lesser extent, from maize stover. This can be explained by the low economic value of maize stover. Economic allocation was performed in this study and it should be borne in mind that the results may vary depending on the allocation methods chosen. Owing to the great contribution of agriculture to the global environmental impacts, sugar producers must be aware that the choices of raw materials to produce sugars will greatly affect their overall environmental performance. In general, when environmental research is carried out only for agriculture for all scenarios under investigation, field emissions, transport processes and fertilisation contribute greatly to environmental impacts. The LCA methodology proved to be an important tool for analysing the environmental burdens of sugar production. However, more research is needed in the selection and processing of raw materials, especially from second-generation feedstocks, to drive the transition to bioeconomy.

Acknowledgements This contribution was supported by the European project STARProBio (Grant Agreement Number 727740). The authors belong to the Galician Competitive Research Group GRC2013-032 and to the CRETUS Strategic Partnership (AGRUP2015/02), co-funded by Xunta de Galicia and FEDER (EU).

References 1. A. Camia, et al. Biomass Production, Supply, Uses and Flows in the European Union, Luxembourg, DOI: 10.2760/181536, 2018. 2. C. T. De Matos, J. C. Garcia, J.-P. Aurambout, B. Kavalov and S. Manfredi Environmental Sustainability Assessment of Bioeconomy Products and Processes – Progress Report 1, DOI: 10.2788/708144, 2015. `s, Data strategy for en3. A. Avadı´, L. Nitschelm, M. Corson and F. Verte vironmental assessment of agricultural regions via LCA: case study of a French catchment, Int. J. Life Cycle Assess., 2016, 21, 476–491. ˜o, Potential mitigation of the environmental im4. K. Benis and P. Ferra pacts of food systems through urban and peri-urban agriculture (UPA) – a life cycle assessment approach, J. Cleaner Prod., 2017, 140, 784–795. 5. G. A. Blengini and M. Busto, The life cycle of rice: LCA of alternative agrifood chain management systems in Vercelli (Italy), J. Environ. Manage., 2009, 90, 1512–1522. 6. V. Fantin, S. Righi, I. Rondini and P. Masoni, Environmental assessment of wheat and maize production in an Italian farmers’ cooperative, J. Cleaner Prod., 2017, 140, 631–643.

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7. F. Soheili-Fard and H. Kouchaki-Penchah, Assessing environmental burdens of sugar beet production in East Azerbaijan province of I.R. Iran based on farms size levels, Int. J. Farming Allied Sci., 2015, 4, 489–495. 8. S. Bernesson, D. Nilsson and P. A. Hansson, A limited LCA comparing large- and small-scale production of ethanol for heavy engines under Swedish conditions, Biomass Bioenergy, 2006, 30, 46–57. 9. E. Gnansounou, A. Dauriat, L. Panichelli and J. Villegas, Energy and greenhouse gas balances of biofuels: Biases induced by LCA modelling choices, J. Sci. Ind. Res., 2008, 67, 885–897. ˜oz, et al., Life cycle assessment of bio-based ethanol produced from 10. I. Mun different agricultural feedstocks, Int. J. Life Cycle Assess., 2014, 19, 109–119. 11. A. P. Draycott Sugar Beet. Blackwell Publishing, Blackwell Publishing, DOI: 10.1002/9780470751114, 2006. 12. FAO, Sugar Beet White Sugar. Agribusiness Handbooks, 2009. 13. Y. Zhang, et al., Characterization of A- and B-type starch granules in Chinese wheat cultivars, J. Integr. Agric., 2016, 15, 2203–2214. 14. J. Tomaszewska, et al., Products of sugar beet processing as raw materials for chemicals and biodegradable polymers, RSC Adv., 2018, 8, 3161–3177. 15. FAOSTAT. Crop statistics, 2017. Available at: http://www.fao.org/faostat/ en/#data. (Accessed: 10th January 2019). 16. F. Brentrup, J. Kusters, H. Kuhlmann and J. Lammel, Application of the Life Cycle Assessment methodology to agricultural production: an example of sugar beet production with different forms of nitrogen fertilisers, Eur. J. Agron., 2001, 14, 221–233. 17. R. Bennett, R. Phipps, A. Strange and P. Grey, Environmental and human health impacts of growing genetically modified herbicidetolerant sugar beet: A life-cycle assessment, Plant Biotechnol. J., 2004, 2, 273–278. 18. M. A. Renouf, M. K. Wegener and L. K. Nielsen, An environmental life cycle assessment comparing Australian sugarcane with US corn and UK sugar beet as producers of sugars for fermentation, Biomass Bioenergy, 2008, 32, 1144–1155. 19. B. Ness, An Intergrated Sustainability Assessment of the Swedish Sugar Production System from a Life-Cycle Perspective: 2003-2015, Interdisciplinary Description Complex Syst., 2011, 9, 23–38. 20. S. Foteinis, V. Kouloumpis and T. Tsoutsos, Life cycle analysis for bioethanol production from sugar beet crops in Greece, Energy Policy, 2011, 39, 4834–4841. 21. I. Klenk, B. Landquist and O. R. de Imana, The Product Carbon Footprint of EU beet sugar, Sugar Industry J., 2012, 137, 169–177. 22. N. Maravı´c, et al., Economic analysis and LCA of an advanced industrialscale raw sugar juice purification procedure, Food Bioprod. Process., 2015, 5, 19–26. ¨gi Case study European Sugar: important insights for 23. A. Spoerri and T. Ka environmental footprinting, in LCA Food 2016 – 10th International Conference on Life Cycle Assessment of Food 2016, 2016, pp. 1–9.

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24. A. Alexiades, A. Kendall, K. S. Winans and S. R. Kaffka, Sugar beet ethanol (Beta vulgaris L.): A promising low-carbon pathway for ethanol production in California, J. Cleaner Prod., 2018, 172, 3907–3917. 25. I. Batey, The Diversity of Uses for Cereal Grains, in Cereal Grains, Elsevier Ltd, 2017, pp. 41–53. ´mez-barbero and E. Rodrı´guez-cerezo, Framework 26. J. Kathage, M. Go for Assessing the Socio-economic Impacts of Bt Maize Cultivation, DOI: 10.2788/739670, 2016. ¨delsheim and G. Smets, Baseline Information on Agricultural 27. P. L. J. Ru Practices in the EU Maize (Zea mays L.), 2011. 28. E. Ofori and N. Kyei-baffour in Agrometeorology and Maize Production, 2006, pp. 1–19. 29. A. Prasad, M. Sotenko, T. Blenkinsopp and S. R. Coles, Life cycle assessment of lignocellulosic biomass pretreatment methods in biofuel production, Int. J. Life Cycle Assess., 2016, 21, 44–50. 30. C. Buratti, M. Barbanera and F. Fantozzi, Environmental Balance of Bioethanol from Corn Grain: Evaluation of Different Procedures of Co-products Allocation, in 16th European Biomass Conference & Exhibition, 2–6 June 2008, Valencia, Spain, 2008. 31. S. Kim, B. E. Dale and R. Jenkins, Life cycle assessment of corn grain and corn stover in the United States, Int. J. Life Cycle Assess., 2009, 14, 160–174. 32. C. W. Murphy and A. Kendall, Life cycle inventory development for corn and stover production systems under different allocation methods, Biomass Bioenergy, 2013, 58, 67–75. 33. I. Tsiropoulos, B. Cok and M. K. Patel, Energy and greenhouse gas assessment of European glucose production from corn-a multiple allocation approach for a key ingredient of the bio-based economy, J. Cleaner Prod., 2013, 43, 182–190. 34. S. Jayasundara, C. Wagner-Riddle, G. Dias and K. A. Kariyapperuma, Energy and greenhouse gas intensity of corn (Zea mays L.) production in Ontario: A regional assessment, Can. J. Soil Sci., 2014, 94, 77–95. 35. J. Bacenetti, A. Fusi, M. Negri, R. Guidetti and M. Fiala, Environmental assessment of two different crop systems in terms of biomethane potential production, Sci. Total Environ, 2014, 466–467, 1066–1077. 36. F. Adom, J. B. Dunn and J. Han GREET Pretreatment Module, 2014. ´lez-Garcı´a, J. Bacenetti, L. Arroja and M. T. Moreira, 37. I. Noya, S. Gonza Comparative life cycle assessment of three representative feed cereals production in the Po Valley (Italy), J. Cleaner Prod., 2015, 99, 250–265. 38. L. Boone, et al., Environmental life cycle assessment of grain maize production: An analysis of factors causing variability, Sci. Total Environ, 2016, 553, 551–564. 39. L. Liang, et al., Life Cycle Assessment of China’s agroecosystems, Ecol. Indic., 2018, 88, 341–350. 40. R. P. Anex & and A. L. Ogletree Life-Cycle Assessment of Energy-based Impacts of a Biobased Process for Producing 1, 3-Propanediol, in Feedstocks for the Future, 2006, pp. 222–238.

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41. E. C. Ramirez, D. B. Johnston, A. J. Mcaloon, W. Yee and V. Singh, Engineering process and cost model for a conventional corn wet milling facility, Ind. Crops Prod., 2007, 7, 91–97. 42. R. Duraisam, K. Salelgn and A. K. Berekete, Production of Beet Sugar and Bio-ethanol from Sugar beet and it Bagasse: A Review, Int. J. Eng. Trends Technol., 2017, 43, 222–233. 43. G. Vaccari, E. Tamburini, G. Sgualdino, K. Urbaniec and J. Klemesˇ, Overview of the environmental problems in beet sugar processing: Possible solutions, J. Cleaner Prod., 2005, 13, 499–507. 44. A. B. Dı´az, C. Marzo, I. Caro, I. de Ory and A. Blandino, Valorization of exhausted sugar beet cossettes by successive hydrolysis and two fermentations for the production of bio-products, Bioresour. Technol., 2017, 225, 225–233. 45. N. Aramrueang, S. M. Zicari and R. Zhang, Response Surface Optimization of Enzymatic Hydrolysis of Sugar Beet Leaves into Fermentable Sugars for Bioethanol Production, Adv. Biosci. Biotechnol., 2017, 8, 51–67. 46. M. Modelska, et al., Concept for recycling waste biomass from the sugar industry for chemical and biotechnological purposes, Molecules, 2017, 22, 1–26. 47. A. A. M. Habeeb, A. E. Gad, A. A. EL-Tarabany, M. M. Mustafa and M. A. A. Atta, Using of Sugar Beet Pulp By-Product in Farm Animals Feeding, Int. J. Sci. Res. Sci. Technol., 2017, 3, 107–120. 48. IPCC, Anthropogenic and Natural Radiative Forcing, DOI: 10.1017/ CBO9781107415324.018, 2013. 49. P. Fantke, et al. Health impacts of fine particulate matter, in Global Guidance for Life Cycle Impact Assessment Indicators, vol. 166, 2016. 50. R. K. Rosenbaum, et al., USEtox – The UNEP-SETAC toxicity model: Recommended characterisation factors for human toxicity and freshwater ecotoxicity in life cycle impact assessment, Int. J. Life Cycle Assess., 2008, 13, 532–546. 51. M. Posch, et al., The role of atmospheric dispersion models and ecosystem sensitivity in the determination of characterisation factors for acidifying and eutrophying emissions in LCIA, Int. J. Life Cycle Assess., 2008, 13, 477–486. ¨la ¨, M. Posch, M. Johansson and J. P. Hettelingh, Country52. J. Seppa dependent characterisation factors for acidification and terrestrial eutrophication based on accumulated exceedance as an impact category indicator, Int. J. Life Cycle Assess., 2006, 11, 403–416. ´e, et al. Handbook on Life Cycle Assessment. Operational Guide 53. J. B. Guine to the ISO Standards, 2002. ´e and G. Huppes Abiotic Resource 54. L. Van Oers, A. De Koning, J. B. Guine Depletion in LCA. Improving Characterisation Factors for Abiotic Resource Depletion as Recommended in the New Dutch LCA Handbook, Aviation Week and Space Technology, New York, 2002. 55. U. Bos, R. Horn, T. Beck, Lindner, P. Jan and M. Fischer LANCA – Characterization Factors for Life Cycle Impact Assessment – v2.0, 2016.

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56. European Commission, PEFCR Guidance Document – Guidance for the Development of Product Environmental Footprint Category Rules (PEFCRs), version 6.3, 2017. 57. S. Fazio, et al. Supporting Information to the Characterisation Factors of Recommended EF Life Cycle Impact Assessment Method New Models and Differences with ILCD, DOI: 10.2760/671368, 2018. 58. ISO14040, ISO 14040-Environmental Management – Life Cycle Assessment – Principles and Framework. ISO 14040, vol. 3, 2006. 59. A. Vercalsteren & and K. Boonen Life Cycle Assessment Study of Starch Products for the European Starch Industry Association (AAF): Sector Study, 2015. 60. J. Moncada, I. Vural Gursel, W. J. J. Huijgen, J. W. Dijkstra and A. Ramı´rez, Techno-economic and ex-ante environmental assessment of C6 sugars production from spruce and corn. Comparison of organosolv and wet milling technologies, J. Cleaner Prod., 2018, 170, 610–624. 61. V. M. Thomas, D. G. Choi, D. Luo & and M. Realff A supercritical Water Approach to Cellulosic Sugars: Lifecycle Energy, Greenhouse Gas and Water Implications, 2012, pp. 1–11. 62. L. Tao, E. C. D. Tan, A. Aden and R. T. Elander, Techno-Economic Analysis and Life-Cycle Assessment of Lignocellulosic Biomass to Sugars Using Various Pretreatment Technologies, Biological Conversion of Biomass for Fuels and Chemicals: Explorations from Natural Utilization Systems, 2014, 358–380. 63. I. C. Nwaneshiudu, I. Ganguly, F. Pierobon, T. Bowers and I. Eastin, Environmental assessment of mild bisulfite pretreatment of forest residues into fermentable sugars for biofuel production, Biotechnol. Biofuels, 2016, 1–10. 64. J. M. Vargas-Ramirez, D. P. Wiesenborn, D. G. Ripplinger and S. W. Pryor, Carbon footprint of industrial-beet sugars stored as raw thick juice for use as a fermentation feedstock, J. Cleaner Prod., 2017, 162, 1418–1429. 65. Ecoinvent databases, 2015. Available at: http://www.ecoinvent.org/ database. 66. USDA, United States Department of Agriculture, National Agricultural Statistics Service, Prices Received for Corn by month – United States, 2019. Available at: https://www.nass.usda.gov/Charts_and_Maps/Agricultural_ Prices/pricecn.php#skipnav. (Accessed: 4th April 2019). 67. B. Durlinger, E. Koukouna, R. Broekema, M. Van Paassen & J. Scholten Agri-footprint 4.0, 2017. 68. European Commission, EU Sugar Market Observatory, 2019. Available at: https://ec.europa.eu/agriculture/sites/agriculture/files/market-observatory/ sugar/doc/price-reporting_en.pdf. (Accessed: 5th April 2019).

CHAPTER 3

Downstream Environmental Assessment K. LOKESH,* J. CLARK AND A. MATHURU Green Chemistry Centre of Excellence, Department of Chemistry, University of York, Heslington, York YO10 5DD, United Kingdom *Email: [email protected]

3.1 Introduction Biobased products have been identified as one of the most promising pathways for our transition from a linear economy to a resilient, circular, biobased economy,1 directly contributing to 14 (out of the 17) UN sustainable development goals. A large number of diverse biobased solutions are not available as greener alternatives to commercially prevalent petro-derived products. It is, however, crucial to only make way for solutions drawn from responsible and sustainably-sound innovation. The sustainability performance and trade-off characteristics of a given biobased value chain or product must be evaluated to fully comprehend its impacts, from a ‘‘cradle-grave’’ perspective, prior its promotion in the commercial market. A number of legislations and CEN mandates, to systematically evaluate and release biobased products, exist in Europe (including CEN/M/430 on bio-polymers and bio-lubricants, M/491 on bio-solvents and bio-surfactants, M/492 for the development of horizontal standards for biobased products, and M/547 on algae and algae-based products or intermediates2) which provide guidelines on the minimum biobased content of the products, its functional capabilities and their environmental impact. This chapter is dedicated to delivering approaches to complement the existing methodology by proposing Green Chemistry Series No. 64 Transition Towards a Sustainable Biobased Economy Edited by Piergiuseppe Morone and James H. Clark r The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

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approaches to address the need for resource efficiency and the subsequent minimisation of waste. Here we propose methodologies that incorporate the definition of resource efficiency into the established and industrially employed principles of green chemistry that complement other main environmental impact assessment methods, such as life cycle impact assessment (LCA). To demonstrate the proposed methodology, we adopt LCA, a robust tool for impact-led environmental analysis. Guidance on undertaking sustainability evaluations of products and supply chains, published by regulatory authorities such as the International Standards Organisation (via ISO14044: Environmental management: LCA) and other initiatives such as the European Commission’s International Reference Life Cycle Data System (ILCD) Handbook and SMGP-PEF (Single Market for Green Products-Product Environmental Footprint) are available for further reference.3–5 Resource efficiency has been identified as crucial in our journey towards a full-fledged, fully functional circular economy6–8 as it promotes alternative utilisation of any and every product and residue, upholding its resource value and minimising wastage as disposal onto a landfill. It is, therefore, essential to use this concept as a base for any environmental analysis of existing and novel value chains, to shed light on key characteristics such as resource efficiency and unique waste utilisation characteristics, that are seldom captured in life cycle studies.9–11 In this study, novel methodologies that qualitatively or quantitatively highlight these characteristics have been adopted or developed to complement the life cycle study. In this chapter we aim to expand on these methodologies and demonstrate their functionality by employing them in a comparative LCA of a selection of biobased case studies and their fossil-derived commercial counterparts. Owing to the emphasis of the proposed methodology on process design (particularly its resource economy and circularity characteristics), the environmental evaluation will focus on stages between ‘‘pre-processing factory gate’’ to distribution to consumer’’ stages (otherwise termed as downstream processes). Please refer to Chapter 2 for upstream-related processes (cradlefactory gate), specification and associated LCA.

3.2 Literature Review The bioenergy sector that is constantly under the sustainability radar was studied in greater detail for the identification of gaps in the existing methods of impact assessment and reporting, the outcomes of which have been presented in D1.1 of STAR-ProBio research.12 Moving from voluntary assessment and reporting, the Renewable Energy Directive (RED) (2009/28/EC) set mandatory greenhouse gas emissions reporting along with other key sustainability indicators as criteria for biofuels and biomass consumption which include land use, biodiversity loss, water use and quality, etc. Upon maturation of these selection criteria, the incorporation of resource efficiency measures was recommended to be implemented by the EEA report, 2013, to reduce the overall above-mentioned impacts of biomass consumption, for example, via

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the use of agricultural and forestry residue for bioenergy production. Since the recommendation, many studies have adopted the resource efficiency measures and within the publication by European Commission ‘‘Roadmap to Resource efficiency Europe’’ that applies to domestic, construction, bioenergy and other sectors, the need for responsible consumption of resources has been stressed upon.6–8,13,14 International Sustainability and Carbon Certification (ISCC 202: Sustainability requirement) also provides elaborate sustainability criteria for the production, harvesting and use of biomass and bioproducts, which is applicable to the entire supply chain.15 RSB (Roundtable on Sustainable Biomaterials RSB-STD-01-010)12 standards for certification of biomaterials and biofuels, besides specifying sustainability criteria and indicators for all of the supply chain, explicitly capture the importance of cascading use of end-oflife (EoL) products, by-products and residues generated by a wide variety of sectors.16 ISO 13065:2015 specifies the sustainability criteria for bioenergy candidates to enable their comparability flexibly either across the entire supply chain or specific bioenergy production processes.17 The Renewable Obligation Sustainability criteria in the UK, which follows the criteria implemented by EU-RED, is also applied to all biomaterials (bio-liquids, solids and gaseous fuels). Some of the key criteria covered by most of the standards and certification procedures include GHG emissions, water quality and use, hazardous waste, air quality, land use and biodiversity loss. With respect to the CEN standards, EN16751:2015: Biobased products: Sustainability criteria, provides guidance to the economic operators and other relevant stakeholders to incorporate the practice of reporting and communication of the various sustainability aspects of a biobased value chain. EN16751 also directs the operators to EN16760: Biobased products: LCA, for use of abovesuggested environmental criteria and impact indicators. However, the suggested impact indicators only very broadly address the environmental impact. The scope of EN16751 provides guidance on undertaking impact assessment and reporting on biobased products covering stages from feedstock acquisition up to the feedstock ‘‘pre-processing’’ phase (conversion of raw biomass to primary feedstock). There was a leap from this stage onto the final product production, lacking any coverage on guidance or regulation of the specific resource consumption (particularly abiotic resources and ecological impacts). For a more elaborate review and analysis of all international and national standards on biomaterials and biobased value chains, refer to the suggested literature.12 The findings from a comprehensive evaluation of more than 45 certification labels, schemes and initiatives associated with biobased products were undertaken and presented under the first published report of this research12 which includes the identification of potential gaps in criteria and indicators. Some of the aspects the schemes lacked in coverage included (but are not limited to) secondary resource efficiency; functionality (output service quality); land use efficiency; and EoL characteristics. These identified indicators were then compared to those recommended by policy makers for industrial and/or commercial application, the PEFCR (Product Environmental Footprint Category rules) guidance5 and the EN 16751 standard.18

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A good convergence between practice (in peer-reviewed LCA studies) and recommendation (in standards and norms) was identified for some indicators including climate change, resources depletion and acidification. However, methodologies relevant to EoL management such as waste minimisation and secondary material utilisation were lacking. However, the PEFCR guidance notes provide unique approaches to the management and treatment (for the allocation of impacts and credits) of domestic and packaging materials based on the suggested average packaging datasets in the event of lack of primary data. In particular, the suggested single EoL formula, the ‘‘Circular footprint formula’’, captures the complexities within the EoL processes in general, following the potential routes of material and energy flow within a circularised production process. Among a variety of waste management approaches that can be adopted for any biobased product at the different stages of its life processes (reuse by consumers, recovery and reuse by manufacturers with uncompromised secondary material quality), the circular footprint methodology addresses only the following approaches: recycling, energy recovery and disposal. Moreover, very limited coverage on the balance and allocation of EoL impacts and credits to product and processes have been based on the assumptions of market dynamics, such as the demand, supply and use of scrap material, thus providing credits for cascading use by secondary industries (PEFCR). The one key parameter that links an economic operator with sustainable strategies is product design. Designing products responsibly towards a highquality secondary application (at the EoL phase) or the same application must be appropriately credited. Under practical material recycling scenarios, a quality of the recycled material which expresses their potential for application to similar or higher quality application must be captured. This aspect is currently lacking within the PEF’s circular footprint formula.

3.2.1

Industrial Best Practice Indicators

 BASF Eco-efficiency Indicators BASF eco-efficiency indicators are globally-known success stories in industrial sustainability reporting and practice. BASF eco-efficiency indicators were employed for the quantification of environmental and economic impacts of chemical products and processes across their life cycle19 drawing from ISO14044 for LCA and ISO14045 for Eco-efficiency assessment.20 A typical list of indicators within BASF eco-efficiency analysis include a) b) c) d) e) f)

Raw material consumption Water consumption Human toxicity potential Land use Acidification Ozone depletion

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g) Photochemical Ozone creation h) Climate change  Dow’s chemical index Dow Chemical Company strives to improve its performance in terms of the environment, health and safety, through a ten year evolution of their commitment and this led to the development of the globally-known Sustainable Chemical Index (SCI).21 This strategy was undertaken mainly to boost the sales of the products based on sustainable chemistry by 10%, thereby leading to sustainable long-term commercial growth. The principles of sustainable product and process development include renewability and recyclability of materials, material transformation efficiency, life cycle benefits, value chain and logistical risks, end-of-life issues, and a social commitment to health and safety. The new Sustainable Chemistry Index is made of 19 sustainability criteria that were developed as part of Dow’s 2025 Sustainability goals.21 Measuring progress in sustainable product manufacturing is complicated due to the prevalence of multiple issues and indicators across the life cycles of products. Dow Chemical Company developed and implemented an assessment process for the use of sustainable chemistry concepts by their supply chain actors, to encourage and track more sustainable practices and products. This annual sustainability check focussed on four broad themes: product risks, addressing world challenges through products and operations, strategy and recognition, and value chain engagement. This process has been credited with promoting dialogue, actions, and improvements by business units, and serves as a key mechanism for raising sustainability awareness in the company.18 This new SCI addresses a variety of sustainability criteria; in addition to which, adherence to the principles of circular economy has become a crucial aspect.  Green chemistry metrics The prevalence of stand-alone, mass-based green chemistry metrics in the chemical industry, including atom economy (AE), reaction mass efficiency (RME), process mass intensity (PMI) and E-factor, has been well-known for more than 25 years.22,23 However, a similar study also suggested that their use must be integrated with LCA to quantify the environmental impacts of the production processes and the products from a life cycle perspective.23 Besides, this combined approach may help provide a level playing field for the comparison of biobased and petro-based products and processes. Some of the key principles of green chemistry, relevant to the resource efficiency and process toxicity that we wish to address in this study, require an ideal process to: ’

’ ’

Utilise material and energy efficiency to provide the most optimal product yield Reduce the amount of waste that is generated from the process Avoid the use of toxic and/or hazardous chemical substances

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Keep material and energy consumption to a minimum Product design must undergo natural degradation when reaching its EoL.

In view of the principles listed above, a set of green chemistry metrics that are conventionally used have been listed below: ’ ’ ’ ’ ’ ’

Process Mass Intensity Reaction mass efficiency Atom Economy Solvent intensity E-factor Effective mass yield

Sustainability indicators that may be applied to the different stages of product maturity (conceptual stage; process chemistry stage; process design stage; pilot stage and commercial production stage) have been demonstrated by many more authors.6,12,21,24–27 Ruiz-Mercado et al. (2011) undertook a review of a mix of environmental, economic and social indicators which roughly amounted to 75þ sustainability indicators. The extensive coverage of metrics under this study is evidence of the wide range of sustainability evaluation combinations that are available to the economic operators. The combinations suggested in the study, in addition to the LCA indicators, also contain resource efficiency and circular indicators. Some of the indicators suggested in the literature addressed EoL options and some were an amalgamation of both green and fiscal parameters (for example, recycling mass fraction, disposal mass fraction, renewability index, water intensity). While appreciating the wide array of sustainability indicators that have been made available, it is essential to comprehend the potential for double counting when utilising these methods with LCA, which subsequently leads to inaccurate results. Moreover, the target stakeholders, who may be policy makers, SMEs or consumers tend to demand a standard approach that employs ‘‘practical’’ indicators that can be easily applied and interpreted in an industrial set-up for systematised sustainable development. Under such conditions, it is essential for assessors, sustainability tool developers to strategically set selection criteria for the identification of the most promising sustainable indicators that are ‘‘fit-for-purpose’’.  Portfolio Sustainability Assessment (PSA) methodology The World Business Council for Sustainable Development (WBCSD) launched the Portfolio Sustainability Assessment (PSA)28 which led to the development of a consistent framework composed of key indicators for voluntary use by chemical sector at a global level. The indicators within the PSA methodology emphasise ‘the toxicity profile and exposure hazard across the entire life cycle of the chemical, anticipated regulatory trends, environmental impacts, traceability and market transparency’ followed by the capability of the framework to potentially

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contribute to the UN’s sustainable development goals. A systematised scoring system is used to assess and identify high-risk products and product groups, eliminate these risks, and eventually, greening the portfolio. The aim of this methodology, as proposed by WBCSD, is as follows: ’

’ ’

Novel approaches to inform and engage external stakeholders and enable effective decision-making Ease of understanding, implementation and execution Balance between a very simplistic and a very complex approach

 Material circularity indicators – Ellen MacArthur Foundation Material circularity indicators is a ‘‘single score’’ metric developed by the Ellen MacArthur foundation to help businesses embed principles of material circularity into process design and their supply chain.29 There are subindicators for the core indicators listed to capture the intrinsic dynamics (i.e. the sub-processes) prevalent in such supply chains. There are also some key complementary indicators that address some high-risk elements and hotspots embedded in these processes including energy intensity, toxic outputs, market price volatility of materials used and material scarcity. For further information on the material circularity indicators, please refer to the suggested reference.29

3.3 Methodology 3.3.1

Selection Criteria for LCA Complementary Efficiency Indicators

Some guiding principles drawn from the thorough consultation of the published literature3,5–7,12,15–17,19,21,22,24–31 provided a set of selection criteria to identify additional indicators that not only address the principles of resource efficiency but also highlight the ‘‘clean/green production attributes’’ of a given process that will aid the chosen LCA. These selection criteria have been indicated below  First line indicators prior to a comprehensive LCA The key sustainability characteristics of a products (or product groups) that are linked to the principles of circular economy must be quantified to explicitly highlight any environmental and/or resource hotspots, particularly in the case of potentially high-risk candidates. Therefore, the indicators proposed must demonstrate these crucial attributes identifying the suitability of the candidates to be considered for a more elaborate, data and effort-intensive assessments such as LCA.  Easier implementation and interpretation For the successful adoption and use of the suggested indicators, ‘‘easy to use and interpret’’ resource efficiency indicators are an essential. The

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outcome of such an assessment does not require specialist knowledge to communicate the outcomes internally among the value chain actors and externally to the end-users (consumers).  Cross-functionality The detailed literature review presented earlier has demonstrated the prevalence of 75 þ indicators to measure the environmental performance of a product or a process.8,27,32 We need a set of cross-functional indicators that can be applied to different product categories to help interpret complex life cycle inventory data into simplified impact hot-spot indicators. This simplified data must have the capability to be embedded into LCA and into the other pillars of sustainability such as the techno-economic pillar, for optimisation and financial feasibility evaluation and, if possible, within the social sphere to communicate the commercial consumer level performance of the product.  Adherence to the impending sustainable development targets The suggested set of indicators must be able to address the existing and prospective EU sustainability targets. The Europe 2020 strategy emphasises that overall GHG emissions must be lowered to 20% compared to 1990 levels and that the energy efficiency of all processes must be increased by an additional 20% within its climate change and energy objective.33 Within the ‘‘Roadmap to a resource efficient Europe’’ (2011),7 there is an explicit indication that stakeholders (businesses and consumers) will be rewarded with the right incentives when opting for the most resource-efficient products and services that provide clear information on their environmental credentials and market price values and that appropriate measures will be taken to purge the commercial market of the least efficiency products. There is currently a lack of dedicated methodologies to assess the feasibility of recycling materials, particularly within the CEN standard EN16751 for biobased products. Based on the selection criteria presented above, this chapter proposes a primary environmental impact assessment method, LCA. The chosen LCA approach is complimented by a set of novel hybridised indicators that were developed exclusively for this study by combining the existing methods for green production with that addressing resource efficiency characteristics. The following sections will elaborate further on the choice of LCA and the hybridised indicators, the rationale for their choice, their definition and information on how to apply them to the different cycle stages and interpret their quantifications drawn from utilising these indicators.

3.3.2

Conventional LCA Indicators

The main method of environmental impact assessment that was chosen and employed in this chapter was life cycle assessment (LCA). The LCA impact categories, chosen for this study were drawn from a mix of methods, exclusively for this study, to ensure that the impact assessment methods are aligned with

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environmental compliance system for industrial manufacturing, developed by the European Commission called ‘‘Single Market for Green products – Product Environmental Footprint (SMGP-PEF)’’ guidance.5 It is essential to note that among the LCA impact categories demonstrated in Chapter 2, only those most relevant indicators that assess product manufacturing and process dynamics have been adopted for downstream assessment:  Acidification – measured as mol H1 eq. (Model: Accumulated Exceedance34)  Climate change: Global warming potential – measured as kg of CO2 eq. (Model: Bern model, over a 100 year time horizon35)  Particulate matter: Air quality – measured as Disease incidence (Model: PM method suggested by UNEP36)  Eutrophication: Terrestrial Eutrophication – measured as mol N-eq. (Model: Accumulated Exceedance model34) and Freshwater Eutrophication – measured as kg P-eq. (Model: EUTREND in ReCiPe 200837)  Human Health: Human Toxicity, Cancer – measured as kg CTUh (Model: USEtox38)  Mineral and Fossil resources: Fossil resource depletion – measured as MJ (Model: CML 2002)  Water Scarcity: water availability – measured as m3water deprived-eq. (Model: Available WAter REmaining [AWARE]39)

3.3.3

Novel and Existing Efficiency and Circular Metrics

A list of novel metrics was adopted to address the principles of clean and green production in addition to highlighting the resource efficiency characteristics embedded within the process design. This approach encourages the creation of linkages between LCA and circular thinking in linear processes and help optimise and improve the degree of circularity in partially circular processes. The importance of capturing the material and waste hotspots and potential strategies to circularise or recover, finite resources, particularly, fossil-derived energy, rare earth metals or even fresh water is crucial to re-design a process towards a sustainable long-term pathway. Rare earth metals, in particular, are essential to attaining transition to a low-carbon economy if it were to need the transformation the energy and transport infrastructure with ‘‘smart’’ technology. However, the vulnerability of the availability of these materials to countries, industries, supply chains and individuals at a global level appears a rather ‘‘high-risk’’ scenario considering around 64% of the rare earth metals are generated from one country.40 Similarly, freshwater depletion is only recently being addressed within LCA via categorisation of freshwater consumption based on the source and quality, as green, blue and grey, a technique also called water footprinting. In a circular economy no material is treated as dispensable and any kind of loss or leakage of material and energy from the system is reported and analysed, thereby closing that window of wastage. Metrics that can capture the flow of materials either in linear or circular routes can be quantified

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and assessed for environmental impact by linking the data obtained with LCA impact categories. These indicators have been presented below as ‘‘standalone’’, however, the outcomes of analysis via these hybridised indicators can be interpreted to the unit suggested for LCA of products and processes, the functional unit of study. Details regarding the choice of case studies and functional unit of analysis that were used to demonstrate the functionality of these indicators have been presented in section 3.3.5.  Hazardous chemical use Hazardous chemical use is a ‘‘qualitative’’ parameter that ‘‘flags up’’ the use of substances within a product’s inventory (including solvents, catalysts, additives or other chemicals) that can be classified as hazardous by EU-REACH (Registration, Evaluation, Authorisation and Restriction of Chemicals). This was undertaken via the comparison of the product’s life cycle inventory with that of the known global databases for hazardous chemicals, mainly SINLIST41 and SUBSPORT42 which also cover the lists of chemicals of concern captured by the EU-REACH And US-EPA. The presence of such substances is flagged up by use of an ‘‘amber flag’’ highlighting the requirement to identify a relatively greener substitute. SINLIST, supported by SUBSPORT, is instrumental in providing details on a greener substitute to the identified substance of concern. A schematic representation of the process flow for the identification of hazardous substances (substances that are carcinogenic, mutagenic and reprotoxic (CMR), persistent bioaccumulative toxic (PBT) and potential endocrine disruptors) in the product’s material inventory has been presented in Figure 3.1. This indicator may be applied to all life cycle stages involving synthesis, formulation and reprocessing that employ solvents, catalysts or additives that may be suspected to containing substance of concern. Ideally, the processes that are assessed for sustainability must avoid or find a suitable greener alternative to any substance of high concern listed in the SINLIST and SUBSPORT owing to their potential to cause harm to humans and the environment. Though, this environmental indicator is responsible only for highlighting the presence of potential substances of concern; it is not within the scope of this indicator to provide explicit thresholds providing minimum and maximum measures for such substances. This indicator is

Figure 3.1

Process flow for the identification and indication of presence of any substances of concern.

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mainly informative and the setting of thresholds for such substances is at the discretion of the local, national and/or international regulatory authorities and policy makers (e.g. UNEP, ECHA, US-EPA).  Feedstock intensity Feedstock intensity is a ratio of the total amount of the key raw material that is required to produce a unit mass of the analysed biobased product (eqn (3.1)). It is measured as kg of feedstock required per unit mass (kg) of the targeted desired main product and useful co-product. For the LCA of case studies in this chapter, this indicator was modified to calculate the kilograms of feedstock required to produce a functional unit of the main product. The purpose of this indicator was to assess the efficiency of the feedstock transformation technology, leading to the measuring the material intensity of the overall process. Feedstock intensity ¼

Mraw:mat Mmain:prod þ Mco:prod

(3:1)

Mmain.prod ¼ Total mass of target products synthesised in a process (kg) Mmain.prod ¼ Total mass of useful co-products synthesised in a process (kg) Mraw.mat ¼ Total mass of main feedstock fed into the process (kg) The feedstock intensity is a quantitative indicator. In terms of performance interpretation, these indicators are best used in a comparative manner, for example, for comparison between biobased products or between biobased and fossil-derived products. The feedstock intensity of any product that is analysed must ideally be 1 kg per kg of the target product. However, interpreting this methodology to provide quantification for a functional unit of the product studies, these quantifications may deviate from that suggested above. In such cases, the feedstock intensity may desirably be lower than or equal to that calculated for the baseline candidate studied in parallel. NOTE: In the case of consideration of a product that is a complex mixture of ‘final formulation’ substances, the Mmain.prod in the empirical expression may refer to the active ingredient or the dry matter content drawn from the main biobased feedstock.  Waste Factor Waste factor addresses one of the main principles of circular economy, waste generated in a production process (eqn (3.2)). Waste  factor ¼

MTotW MProd þ Mco:prod

(3:2)

MTotW ¼ Total mass of waste generated from the production process (kg) Mco.prod ¼ Total mass of useful co-products generated (kg) MProd ¼ Total mass of target product generated from the process (kg)

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Waste ratio is defined as a ratio of the total mass of solid, liquid or gaseous waste (which may include feedstock, solvents and catalysts) generated as a process waste or lost from the system via leaks or spills, to the total mass of target main products and co-products. This metric is measured as kg of waste generated per kg of useful product (target and co-product) synthesised. Similar to feedstock intensity, for the purpose of uniformity in this chapter, this indictor is presented as kg of waste generated per functional unit of study. Ideally, a waste factor of ‘‘zero’’ is preferred indicating that all the starting material has been transformed into a final product. This may not be the case in a practical scenario and therefore, in such cases or when comparing a biobased case study with a commercial or petro-derived case study, a relatively lower waste factor is preferred.

3.3.3.1

Product Renewability

The nature of the key materials that are utilised in the synthesis of a product must be highlighted, irrespective of whether they are purely or partially bio-derived (eqn (3.3)). Consumers and other relevant stakeholders observe the use of bio-derived raw materials as a sign of adherence to the principles of bioeconomy, and therefore, appropriate credit must be provided to the process design. Measured as a percentage of the product in question, the following indicator has been suggested as a measure of the renewability (biobased) of the product.   MBio feed þ MBio Comp inp  100 Product Renewability ¼ (3:3) Mnet feed þ Mnet Comp inp MBio_feed ¼ Net mass (upon deduction of losses during feedstock transformation to product) of bio-derived main feedstock incorporated into the product (kg) Mall_feed ¼ Net mass of all main feedstock incorporated into the product (kg) MBio_Comp_inp ¼ Net Mass of bio-derived material incorporated into final formulation (compositional inputs) (kg) Mall_Comp_inp ¼ Mass of all the material incorporated into final formulation (compositional inputs, for example, polymer additives (kg)) Measured as a percent of the product, the indicator should result in a figure between 0 to 100 with ‘‘0’’ representing no renewability and ‘‘100’’ representing the ideal scenario of 100% renewability. This metric is a useful first-hand evaluation of the nature of the product prior to the more elaborate experimental sample assessment and quantification of the biobased content, that is suggested in the CEN/TC 16751:2014.18 Unlike the metrics suggested above, the quantifications associated to this metric remain constant, irrespective of which unit the outcomes are interpreted to.

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3.3.3.2

Process Material Circularity

Process material efficiency is defined as the summation of all the net mass of process auxiliaries used in the process including a deduction of that particular auxiliary that has been recovered and reused (eqn (3.4)). It is essential to highlight the responsible material circularisation strategies in a process that has been designed to recover, re-process and reuse some or all of the process auxiliaries. An approach to measure this circularity has been presented in eqn (3.4).   n P Mrec:Pro:aux MPro:aux  100 Process material circularity ¼ i ¼ 1 (3:4) n MPro.aux ¼ Net mass of a specific process auxiliaries (deducting losses during use) used in the production (kg) Mre.Pro.aux ¼ Net mass of a process auxiliaries (deducting losses during recovery, reprocessing, if any) that have been circularised (kg) n ¼ Total number of all the process materials used in a specific stage i ¼ List of process auxiliaries used in the product synthesis at a given stage Measured as a percentage, similar to product renewability, the quantitative outcome must fall between 0 to 100, with 0 representing the process no circularity of process materials and 100 representing all the employed process auxiliaries being 100% recovered and reused. For the purpose of uniformity and to avoid double counting, it is recommended to calculate this parameter based on the net mass of the components.

3.3.3.3

Energy Intensity

Energy intensity is defined as a ratio of total amount of energy (fossil-derived, renewable and internally derived energy) to the total amount of products and co-products generated within the process (eqn (3.5)). All the energy invested (electricity, heat and other forms of energy) is made accountable using this expression since, in accordance to the principles of green chemistry, a conversion process must be optimised to consume lowest amounts of energy for optimal product yield. Electricity inputs, within LCA, are multiplied by a factor of 3 to reflect the primary energy invested for the desired distribution of electricity to the final destination. This factor, 3, is considered a sufficient approximation of typical efficiency of primary energy conversion to electricity, in the context of this indicator. Energy intensity ¼ ðEFosD þ ERenD þ EIntD Þ  3 MProd þ MCo:prod EFosD ¼ Fossil-derived energy used (kWh) ERenD ¼ Renewable energy used (kWh)

(3:5)

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EIntD ¼ Internally derived energy used (kWh) MProd ¼ Total mass of target product generated (kg) MCo.prod ¼ Total mass of co-product generated (kg) The quantitative figure of this parameter is variable with the goal of analysis. When applied to an independent process evaluation, the quantification is measured as kWh energy required per kg of products. When applying this method in combination with an LCA study, for the purpose of coherence, the outcomes will be interpreted to ‘‘kWh of energy required per functional unit’’. For the purpose of robust interpretation, this metric is best utilised for the comparison of energy intensity of two biobased candidates or between biobased and fossil-derived candidates. It is essential to note that the proposed set of non-LCA, hybridised indicators need to be examined for robustness and relevance to the nature of this research the keywords for which are biobased products, circular economy, bioeconomy and sustainability framework. To evaluate the effectiveness of these indicators in achieving the purpose of their development, an environmental performance evaluation that employs the proposed set of indicators, in combination with the established methodologies of LCA is required. Prior to the initiation of these studies, suitable biobased products and appropriate fossil-derived counterparts have been identified based on the work ‘‘D1.3: Identification of case studies and stakeholders’’,43 the main purpose of which was to provide exemplary candidates to evaluate, develop and refine the chosen sustainability assessment methodologies upon. In the upcoming segments, a brief introduction to the selected case studies have been provided, which is then followed by an elaborate description of the production process, LCA. This LCA employs the selected list of LCA and hybridised indicators to demonstrate their efficacy in communicating the needed information and issues encountered due to unforeseen factors. Bockstaller and Girardin (2003) suggest a range of approaches which may be used to validate environmental indicators that have been developed.44 They include design validation, output validation and end-use validation. Design validation is an iterative method development which involves peer review and comparison with other similar methodologies. Output validation involves the comparison of quantitative or qualitative outputs with those of the prevalent environmental methods, for example, through use of probability tests. End-use validation entails the ‘‘fit-for-purpose’’ nature of the proposed methodology. In accordance to the suggested approaches, this report will undertake a ‘‘fit-for-purpose’’ evaluation examining the effectiveness of the proposed hybridised, non-LCA indicators through the use of dedicated pre-chosen biobased case studies. The environmental impact quantifications resulting from both the biobased and petro-derived case studies using the chosen LCA and the hybridised indicators will be subjected to further assessments to demonstrate their sensitivities to changes in processes and sub-processes. Nevertheless, due to the niche nature of the biobased products that are currently in the market and in the pipeline, the methodology was developed only with the data that was made available as a

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part of the project. This highlights the need for further improvements required to refine the methods suggested over time, thereby adding some uncertainties that have been mentioned later in this chapter.

3.3.4

LCA of STAR-ProBio Case Studies

For the purpose of demonstration and validation of the selected LCA and hybridised indicators, three case studies that were previously identified in D1.3 will be employed in this study. This case study selection also involved identification of suitable fossil-derived commercial products to enable a comparative environmental evaluation applying the newly conceived methodology. These case studies are presented in Table 3.1. These case studies were selected based on their promising nature as biobased alternatives to the conventional candidates, technology maturity, relevance to the main goal of this research (towards the development of sustainability assessment framework for biobased products), comparability with commercially available fossil-derived counterparts, and availability of data appropriate for a comprehensive LCA evaluation. Polylactic acid (PLA) is a biobased aliphatic polymer that is processed via polymerisation of lactic acid, sourced from maize sugars. It is popularly identified as one of the most promising alternatives to petroleum-derived plastics. Currently demonstrating an annual growth rate of 18.2%,45 PLA is expected to reach a market share worth $50.1 billion by 2020. Finding application in a number of different sectors including packaging, agriculture, automobile and textiles, PLA is transforming into a versatile biobased biodegradable polymer that is blended with biobased or fossil-derived co-polymers to boost the rate of biodegradability in managed EoL scenarios.46–48 For this study, PLA is transformed into BoPLA (Biaxially oriented PLA) that is used in the production of packaging films for horticultural produce. Synthesised commercially from maize starch, it is expected to replace BoPP (Biaxially oriented polypropylene) in the current race to reach the proposed bioeconomy targets. The current market share for BoPLA films is unknown, owing to the novel nature of the product. Table 3.1

List of case studies selected to test the effectiveness of the environmental impact assessment methodologies (from cradle-gate).

Biobased case study

Conventional case study Applications 100% biobased Packaging films

Functional unit

1 piece of packaging film which is 350 mm 250 mm with a thickness of 0.025 mm Film required to mulch PLA þ biobased Linear low-density Partially biobased Agricultural mulch 1 ha of agricultural land co-polymer polyethylene films (LLDPE) Polystyrene (PS) 100% biobased resin 1 kg of the resin Biobased for end-product Polybutylene synthesis succinate (PBS) Biaxially oriented Biaxially oriented PLA (BoPLA) Polypropylene (BoPP)

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However, its promising functionality, gradual increase in annual production capacity and its acting as an acclaimed direct contribution to circular economy makes it an ideal candidate for the comparative sustainability assessment evaluation that we aim to undertake in chapter. The fossil-derived competitor that BoPLA is weighed against in this study is BoPP packaging films. Despite lacking the ability to be heat sealable, requiring an external coating of heat sealant to improve its functionality, this versatile polymer has a current market worth $13 billion with a growing annual growth rate of 6% between 2017 and 2021. BoPP is currently the most prevalent commercial choice of plastic for packaging fresh produce – vegetables and fruits.49 The second case study focusses on agricultural mulch. Linear low-density polyethylene (LLDPE)-based mulch film has global application to date which is foreseen to have an annual growth rate of 5.1% for 2017–2021.49 Synthesised from petro-derivatives, LLDPE mulch film is also known for its challenges in terms of removal (from the fields) and collection at the EoL, resulting contamination and long-term agronomical impacts from reduction of soil porosity, microbial activity, contamination with partially degraded polymer compounds and effects on the overall soil quality. The PLA-based mulch film, considered to be the biobased alternative to the conventional candidate, and is synthesised from a combination of bio-derived polymers but is only partially biobased. As mentioned earlier, the biodegradability of the 100% biobased PLA is complemented by blending with readily biodegradable (partially biobased) co-polymers rendering the product a sustainable EoL option, 90–95% biodegradability.50 The market share of PLA-based mulch film, analysed in this study, is currently unknown, owing to the novel nature of the product and the confidential nature of the product’s performance in the market. In the current race within the EU to reach bioeconomy targets, the market for biodegradable mulch films is steadily increasing and is foreseen to secure a global market worth $72 million at an annual growth rate of 8.5%.51 Polybutylene succinate (PBS) is commercially synthesised at an expected production capacity of roughly 1 million tonnes per annum, with wide applicability through formulations into products such as agricultural mulch, plastic containers, slow-release (fertiliser and pesticide) capsules, biodegradable fishing lines, pharmaceutical products etc., and is a key driver in the gradually increasing production installations across the globe.52 In terms of the resin’s EoL performance, the products are primarily designed for biodegradability, recycling or incineration, based on the nature and the formulation of the end product. The versatility of this novel polymer, however, can only be evaluated through a comparative analysis with a resin that shares similar properties. The petro-derived product that fulfils this purpose and finding global commercial application is polystyrene resin. Polystyrene products, in general, are non-biodegradable in nature and limited numbers of recycling facilities available. There is a prevalence of mixed information on whether polystyrene is recyclable. There are very limited numbers of facilities that recycle polystyrene, the evidence for which is very limited.

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This petro-derived resin, however, is not recycled as much as it is produced and consumed globally, and is disposed of in landfill at its EoL. With a market share worth $28 billion, polystyrene is widely applied in a number of sectors including packaging, insulation and electronics and is foreseen to reach an annual growth rate of 4.5% by 2021. Amidst this growth, the market is expected to gradually lean towards the biobased alternative to keep up with the global race to switch to biobased, greener products from the conventional petro-based products.

3.3.5

Goal, Scope and Functional Unit

The goal of this study was to test the effectiveness of the proposed environmental impact assessment through the comparative environmental sustainability of the biobased case studies with that of their fossil-derived competitors. The scope of analysis, therefore, focusses on the downstream impact assessment, encompassing the life cycle stages between ‘‘manufacturing’’ and ‘‘distribution to consumers’’. Environmental impact assessment of stages encompassing product consumption and EoL management is currently under progress and, therefore, falls outside the scope of this part of the chapter. For the purpose of this study, the environmental evaluation of the manufacturing, formulation and consumption stages are assumed to take place within Europe in the current time period. The functionality of the packaging film is to ensure the protection of horticulture produce from damage and pest attack during transportation and its shelf life between packaging and consumption by consumer. For 100% biobased BoPLA, the required packaging film is 1 piece measuring 350 mm250 mm with a thickness of 0.025 mm. In the case of the baseline candidate, BoPP, product specifications of the film is a thickness of 0.025 mm and dimensions of 350 mm250 mm was assumed. The functional unit of analysis for partially biobased PLA-based mulch film is that required to mulch 1 ha of agricultural land for a period of one crop rotation. The mulch film synthesised from PLA (45%) and a co-polymer with UV-stabilisers and carbon black (remaining fraction)53 is assumed to be 0.012 mm thick with a density of 1.4 g cm3, leading to an overall requirement of 152 kg of PLA/co-polymer film per hectare of agricultural land. The baseline case for this biobased product encompasses the environmental impact assessment of LLDPE-based mulch film with an average thickness of 0.025 mm and a density of 0.918 g cm3 requiring 185 kg of mulch film for a hectare of agricultural land. PLA-based mulch film was designed to be relatively thinner than the LLDPE mulch film to ensure its complete biodegradability, while the latter was designed for easier removal and baling at its EoL. The functional unit of analysis for third and final case study, 100% biobased polybutylene succinate (bio-PBS) resin, is the production of 1 kg of the polymer. PBS production and its associated infrastructure is still in its infancy at a global level, amidst is promising prospects from sharing functional characteristics with that of polystyrene resin. This led to data unavailability and

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confidentiality concerns for the associated end product in the market. This led to our study opting for polymer production as the case study for the environmental impact assessment. The scope of analysis will, therefore, be the quantification of the environmental impacts of producing 1 kg of 100% biobased PBS resin, from ‘‘manufacturing’’ to the refinery ‘‘factory gate’’.

3.3.6

Process Description

Within this report, the environmental impact assessment has been undertaken for the following stages: Conversion of primary feedstock (glucose) to polymers, and refining and formulation, including transportation and distribution of goods (intermediates, raw formulations and end-products) to the different facilities and consumers.

3.3.7

Scenario Description

For the purpose of environmental impact assessment for the biobased case studies, certain scenarios have been defined. The main feedstock that acts as the starting material in this study, glucose, is synthesised from three different biomass products –starch-rich maize kernels, lignocellulose-rich maize stover and lignocellulose- and pectin-rich sugar beet pulp. However, the system boundary set for downstream impact assessment indicates that glucose (sourced from the three different feedstocks) as the starting material for the production of these biobased products is drawn from fermentation processes. The geographical sources of these feedstocks, cultivation approaches, harvest and distribution to pre-treatment plants, biomass transformation technology, relevant inventory, description of process and sub-processes have been captured in Chapter 2.

3.3.8

Packaging Films

A schematic representation of the processes and sub-processes involved in the production of packaging films sourced from both biobased and fossilderived feedstock and the associated system boundary that has been analysed within this report has been presented in Figure 3.2. The 100% biobased PLA is assumed to be sourced from raw biomass of varying resource value such as maize (starchy, food-based), maize stover (lignocellulosic, agricultural residue) and sugar beet pulp (pectin-rich, industrial residue). The main substrate, glucose, is initially sterilised in combination with an optimised mixture of nutrients. The sterilised nutrient broth is then inoculated with a suitable industrial strain of Lactobacillus sp. or Bacillus sp. leading to fermentation at the desired temperature and pH to produce the building-block monomer lactic acid. It is industrial practice to ensure optimum conditions to maximise lactic acid production. Therefore, the unreacted lactic acid monomers resulting from the ‘‘polymerisation’’ step are designed to be recovered and recirculated back into the process.

62 Life Cycle processes and the system boundary for the exemplary environmental evaluation of the 100% bio-derived BoPLA and fossil-derived BoPP based packaging films.

Chapter 3

Figure 3.2

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63

During the downstream processes, the calcium lactate is subjected to reactive distillation, acidification, followed by a second stage of purification leading to the formation of L-lactic acid. Fractionated lactic acid (from the fermentation broth and the spent cells which are assumed to be sent off to an on-site anaerobic digester) is then purified and crystallised, before being prepared for polymerisation to produce PLA oligomers. These PLA oligomers are assumed to be thermally cracked and re-polymerised via a ring-opening method to produce a high molecular mass PLA resin which is then pelletised for blending and extrusion into BoPLA packaging films. BoPP has been chosen as the baseline candidate against which the environmental performance of BoPLA will be weighed. The inventory associated with polypropylene, available in the Ecoinvent 3.5 database, was adopted and modified to suit the assumptions, processes and sub-processes employed for the BoPP film production within this study. For disaggregated information required for the quantification of the hybridised indicators, published literature by PlasticsEurope54 was consulted. The processes and sub-processes that were captured within the scope of this report are as follows: Assumptions related to transportation, distribution of intermediates and finished products and formulation (extrusion), BoPLA based assumptions was employed.

3.3.8.1

Mulch Films

The PLA-based mulch film adopted for this study was assumed to made of 70% plant-based co-polyester synthesised from 100% biobased PLA and 55% biobased polybutylene adipate terephthalate (PBAT), designed to be fully biodegradable at its EoL. The process of their production and the system boundary of this analysis has been presented in Figure 3.3. The inventory for the production of PLA was adopted from the NatureWorks INGEOs PLA eco-profile that is available within the Ecoinvent 3.5 database.55 The inventory for the PBAT co-polyester was adopted from the published industrial reports and patents56,57 and is an aliphatic-aromatic co-polyester synthesised from 100% biobased 1,4 butanediol (bio 1,4-BDO) and petro-derived adipic acid and terephthalic acid. For the production of biobased bio 1,4-BDO, glucose, sourced from sugar beet pulp (pectin-rich, industrial residue) (please refer to Chapter 2 for process descriptions), was assumed to be fermented using an industrial engineered strain of E. coli, under fed-batch conditions at a pH of 7. After the fermentation process, 1,4-BDO was fractionated, purified, concentrated through evaporation, followed by another step purification (via column distillation). The refined bio 1,4-BDO was pelletised before transportation to the formulating facility. Similar to the case of PLA, the fermentation and other organic waste generated from the process were assumed to be transferred to an on-site anaerobic digester (AD) facility to be transformed into a source of biogas. Organic waste that cannot be sent to the AD was assumed to be treated appropriately before being sent to landfill.

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Figure 3.3

Life Cycle processes and the system boundary for the exemplary environmental evaluation of the partially bio-derived PLA and fossil-derived LLDPE-based mulch films. Chapter 3

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In the case of the baseline candidate, LLDPE mulch films are assumed to be synthesised from 100% virgin petro-derived polymers. The data inventory for the production of LLDPE resin was adopted from that available in the Ecoinvent 3.5 database. The material and energy input for the production of mulch films were adopted from published literature11,58,59 and modified to the technical specifications of our chosen functional unit.

3.3.8.2

Polymer Resins

Polybutylene succinate (PBS) is a polyester which was conventionally synthesised from non-renewable resources, until recent advances in renewable materials sector led to the development of 100% biobased compostable PBS. Polybutylene succinate (bio-PBS) is synthesised from the combination of biobased succinic acid, 1,4-butanediol and a third monomer which in most cases is a dicarboxylic acid.60–63 A schematic representing their production and the system boundary of the LCA has been presented in Figure 3.4. The versatile chemical and mechanical properties of the PBS were determined to be comparable to polystyrene (PS), polypropylene (PP) and low-density polyethylene (LDPE). The production route associated to the synthesis of 100% bio 1,4-BDO was elaborated under sub-section mulch films. The production process for the synthesis of 100% biobased succinic acid (bio-SA) is as follows. Glucose, sourced from the different feedstock mentioned earlier, was subjected to fermentation using dedicated industrially engineered microbial strains to produce succinic acid, which upon fractionation from the fermentation broth and spent cells underwent subsequent stages of downstream processes to ensure, high-quality succinic acid was produced. These steps included a series of repeated column purification, evaporation and crystallisation. It is essential to note that the inorganic acids used in the treatment of columns, the fermentation broth and waste heat from the refining phase were recovered and reused internally. The inventory data for the production of 100% biobased succinic acid was acquired from the industry partners an literature review.9,64–66 Both 100% bio-SA and 100% bio-1,4 BDO were mixed at a molar ratio of 1.3 : 1 and steam-melted in a mixing tank. The melted mixture was then subjected to esterification at specific temperatures and pressured with sufficient residence time for the esters to be formed. Unreacted 1,4-BDO was recovered and reused to ensure no feedstock was wasted. A recovery efficiency of 99.5% was assumed for this purpose. The ester was then extracted and polymerised in the presence of a catalyst (titanium tetrabutoxide) and at specific temperatures and pressure for an optimised yield of high-molecular-weight 100% biobased PBS. The extracted PBS was then assumed to be pelletised and stored for transportation to the end-product formulation facility. The data inventory for the pelletisation of the PBS resin was based on the average figures for the data obtained from peer-reviewed published literature.9,61,65 In the case of the baseline candidate, polystyrene (PS) resin, the data inventory and the methods of production of polystyrene from petro-chemical

66 Life Cycle processes and the system boundary for the exemplary environmental evaluation of the 100% bio-derived Polybutylene succinate (PBS) resin and fossil-derived polystyrene (PS) resin.

Chapter 3

Figure 3.4

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67

sources was adopted and modified from the eco-profile for PS production,65 which is available in the Ecoinvent 3.5 database that was used in the LCA evaluation of the case studies within SIMAPRO software. Some modifications were made where the starting material for the production of PS was assumed to be ethyl benzene leading to the production of styrene which is then polymerised to produce polystyrene resin.

3.3.8.3

Assumptions and Other Considerations

 Allocation methods: The starting material for the production of PLA, bio 1,4-BDO and the biobased succinic acid was assumed to be glucose sourced from the different biomass (feedstock). The impacts associated with their production in the upstream processes were subjected to economic allocation based on the market performance of the products and by-products of the biomass production. This information was sourced from the work that was undertaken and reported as a part of Chapter 2. To ensure coherence in the flow of analysis and to avoid double counting, no allocations of impacts were made within the downstream impact assessment (this study).  Recovery and reuse of resources: For transparency within this report, the materials (process outputs) that have been circularised have been distinguished individually in the process inventory for the production of the biobased case studies in the suggested reference.67  Transformation efficiencies: The efficiency of extraction of L-lactic acid from the fermentation broth was assumed to be at an industrial average of 95%. The polymerisation and transformation of L-lactic acid to PLA resin is assumed to occur at an efficiency of 98%. Unreacted monomers were extracted and subjected to another round of polymerisation. Undesirable meso-lactide formed in the process was assumed to be removed and disposed of in landfill. Wastage of PLA resin from loss on factory floor was assumed to be about 0.5%. The re-processable nature of the PLA resin facilitates the recirculation of any waste resulting from the refining and formulation phase at an assumed efficiency of 90%. Similar assumptions have been adopted for the synthesis of PLA and the co-polyester blend involved in the mulch film production. The transformations of the intermediates to PBS, however, have been assumed to be at an industrial average of 97%. The losses of PBS resin encountered during packaging and transportation have been omitted as it falls outside the scope of analysis.  Out of scope: Temperatures, pressures, pH and other technical details have not been captured within this report as they fall outside the scope. For these details, please refer to the result of techno-economic evaluation of these case studies in D4.1 resulting from the STAR-ProBio project. Water scarcity has been reported only for freshwater that was directly integrated into the process. Water used for cooling purposed has not been considered. Product use and disposal have been excluded from this report

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mainly because the use phase will appropriately fit with the end-of-life assessment that will be captured as a part of the planned work.  Transportation: In terms of the transportation processes, the pelletised intermediates from the refinery were assumed to be freighted to the endproducer located at a distance of 250 km using a 7.5 ton low-sulphur diesel truck. From the end-product producers, the packaging films (unit of 500 000 pieces) were assumed to be distributed to the regional warehouse located at a distance of 150 km, and finally the product reaching the retailer located at a distance of 10 km. A single packaging film wrapped fresh fruit or vegetable was assumed to be bought and transported by a consumer in a small petrol vehicle over a distance of 5 km.

3.4 Result Interpretations: Gate-to-gate Impact and Resource Efficiency The outcomes of the life cycle impact and the resource efficiency evaluation undertaken for the biobased and fossil-derived case studies have been presented in Tables 3.2, 3.3 and 3.4. BoPLA Packaging Film: BoPLA packaging films delivered minimum GHG savings of about 50%, of which 20% of the savings were delivered through recovery and recirculation of materials, including process consumables and unreacted components. Some process level emissions consisting of leakages and wastage of inorganic acids, catalysts, and unrecoverable reactants, depending on their fate, lead to an increase in eutrophication potential. Emissions to the air resulting from energy use (electricity and natural gas) contribute to acidification, however, BoPLA provides significant savings relative to that of the conventional BoPP packaging films. No substances of very high concern were identified when comparing the product’s inventory against the hazardous substances databases, SINLIST and SUBSPORT, as proposed in the ‘‘hazardous chemical use’’ in section 3.3.3. BoPLA is 100% biobased, including the polymer additive that was used to improve film properties and functionality. Evaluation of the process characteristics (process auxiliary recovery and reuse) demonstrated a process material circularity of about 85%. Feedstock intensity for both the BoPLA and BoPP packaging film was determined to be more or less similar, through BoPLA consumed relatively lower quantities of feedstock to produce a functional unit of analysis. The energy-intensive downstream processes, and the waste generated from the purification and extrusion stages, were determined to contribute to relatively greater waste factor and energy intensity impacts compared to BoPP packaging. The biggest contributor of waste was the fermentation process which comprised the aqueous contaminants not suitable for anaerobic digestion. This waste was assumed to enter wastewater treatment and landfill routes. It is essential to note that the life cycle emissions associated with the production of glucose have been taken into account, though the LCA in this chapter has been undertaken only from the manufacturing phase to the distribution to the consumer phase.

BoPLA Life Cycle impact indicators Global warming potential (GWP100) Respiratory inorganics Human Toxicity, Cancer Acidification, Terrestrial and freshwater Freshwater Eutrophication Water scarcity Fossil resource depletion Hybridised Indicators Presence of hazardous chemicals Feedstock intensity Waste factor Process material circularity Renewability Energy intensity

Maize derived 3

4.4610 1.67109 2.10107 1.35104 5.23106 6.2104 0.234

BoPLA Maizestover derived 3

2.410 6.051010 1.55107 3.57105 4.50106 6.11104 0.162

BoPLA Sugarbeet pulp derived 3

2.710 9.841010 1.60107 1.26104 4.99106 5.51104 0.176

BoPP

Units

Petroleum derived 3

8.110 5.58109 3.52107 6.11104 3.52106 1.54102 0.397

BoPLA Biobased

BoPP Petroleum derived

Non-hazardous chemical present 7.5103 2.2103 85 100 7.2103

Non-hazardous chemical present 7.77103 1.35103 No data 0 5.14103

per functional unit kg CO2 eq. Deaths CTUh mol H1 eq. kg P eq. m3 deprived MJ

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Table 3.2 Life cycle impact and resource efficiency performance of the biobased BoPLA packaging (per film) in comparison to the fossilderived BoPP packaging (per film).ab

— kg of feedstock kg of waste % % kWh of energy required

a

FU ¼ Functional unit (1 packaging film that is 350 mm250 mm with a thickness of 0.05 mm). Mass of BoPLA film: 5.58 g; Mass of BoPP film ¼ 4.67 g.

b

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70 Table 3.3 Life cycle impact and resource efficiency performance of the biobased PLA mulch film (per ha of mulched land) in comparison to the fossil-derived LLDPE mulch film (per ha of mulched land).a,b

Life Cycle impact indicators Global warming potential (GWP100) Respiratory inorganics Human Toxicity, Cancer Acidification, Terrestrial and freshwater Freshwater Eutrophication Water scarcity Fossil resource depletion Hybridised Indicators Presence of hazardous chemicals Feedstock intensity Waste factor Process material circularity Renewability Energy intensity

PLA-based Mulch PLA-based Mulch PLA-based Mulch LLDPE-based Mulch Units Maize stover Sugarbeet pulp Maize derived derived derived Petroleum derived per functional unit 352.42 2.87105 8.20106 3.89

292.47 2.52105 7.90106 3.31

304 3.08105 8.01106 3.68

574 3.09105 1.67106 4.08

kgCO2 eq. Deaths CTUh mol H1 eq.

0.126 4.86 1.66103

0.106 3.51 1.63103

0.102 3.84 1.50103

0.144 18.72 1.76103

kg P eq. m3 deprived MJ equivalent

PLA-based Mulch Bio- derived

LLDPE based Mulch Petroleum derived

Units per functional unit

Non-hazardous chemical present 2.20102 17.26 78 70 2.03103

Non-hazardous chemical present 2.08102 8.12 No data 0 2.96103

— kg of feedstock required kg of waste % % kWh of energy required

a

FU ¼ Functional unit (1 ha of mulched agricultural land). Mass of PLA-based mulch film: 152 kg/functional unit; Mass of LLDPE film ¼ 185 kg/functional unit.

b

Chapter 3

PBS resin Maize stover derived

PBS resin Sugar beet pulp derived

PS resin

Life Cycle impact indicators

PBS resin Maize based derived

Petroleum derived

Units per functional unita

Global warming potential (GWP100) Respiratory inorganics Human Toxicity, Cancer Acidification, Terrestrial and freshwater Freshwater Eutrophication Water scarcity Fossil resource depletion

2.15 2.4107 3.36108 7.8103 1.24103 0.554 19.4

1.94 1.24107 2.16108 5.41103 1.05103 0.557 7.8

1.98 1.17107 2.87108 5.24103 1.16103 0.575 12.6

2.96 3.29107 5.46108 1.42102 1.73103 2.6 45

kg CO2 eq. Deaths CTUh mol H1 eq. kg P eq. m3 deprived MJ equivalent

Hybridised Indicators Presence of hazardous chemicals Feedstock intensity Waste factor Process material circularity Renewability Energy intensity

PBS resin Bio-derived

Polystyrene resin Petroleum derived

Units per functional unita

Non-hazardous chemical present 1.03 0.30 48 100 0.523

Non-hazardous chemical present 1.05 0.16 No data 0 0.704

—

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Table 3.4 Life cycle impact and resource efficiency performance of the biobased PBS resin (1 kg) in comparison to the fossil-derived polystyrene resin (1 kg).

kg of feedstock required kg of waste % % kWh of energy required

a

FU ¼ Functional unit (1 kg of resin).

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Agricultural Mulch film: Based on the process specification modelled for the proposed functional unit of mulch films, PLA-based mulch film delivered GHG savings in the range 35–50%, compared to the LLDPE mulch film. It is essential to note that the PLA film is only partially (70%) biobased as the components that are used in the preparation of the co-polymer (Ecoflexs F blend), adipic acid and terephthalic acid, are petro-chemically sourced. Adipic acid, in particular, is GHG intense, contributing nearly 40% of the overall process emissions, followed by the purified terephthalic acid that contributed nearly 20%. In terms of conventional impact categories, the PLA-based mulch films performed relatively better than the LLDPE mulch films, in terms of the all the LCA impact categories as presented in Table 3.3. When focussing on the resource efficiency and circularity performance, no significant difference was observed for the amount of feedstock required to produce a functional unit worth of mulch films in both the biobased and fossil-derived case study. The waste resulting from the production of the PLA-based mulch films, however, was determined to be relatively higher (þ113%) compared to that generated from LLDPE mulch film production. The waste was attributable to post-fermentation water, solvents and other undesirable contaminants and unreacted monomers and extrusion waste that resulted from the production process. Transformation of fermentation waste (spent cells and the fermentation broth) into biogas via an on-site AD facility happens to be an established industrial process to reduce a process’s energy intensity. An assessment of the environmental impacts associated with this particular scenario would be an intriguing aspect to explore and is also a recommendation for future work. Polymer resin: The overall GHG emissions associated to the production of 100% biobased PBS resin (1 kg) was determined to be relatively lower (roughly 25–35%) compared to that of the conventional candidate. Similar to the case studies presented above, effective process water recovery and reuse was instrumental in reducing the overall water requirement. The fossil resource depletion associate to the biobased candidate is also attributable to the use of energy sources for the energy generation and the use of natural gas to generate steam employed in the succinic acid production stages, which again was determined to be 50–80% lower than that required for equivalent processes in polystyrene production process. From the resource efficiency and circularity perspective, the amount of feedstock required to produce 1 kg of PBS resin was more or less equal to that required for the production of 1 kg of polystyrene resin. These quantifications may vary when accounting for the efficiency of the transformation of feedstock to products during the formulation phase (which falls out of scope for this study). In terms of waste generated, the fermentation and downstream processes associated to the production of bio-SA and bio 1,4-BDO were determined to be 90% relatively waste-intense. Further techno-economic optimisation and subsequent technology maturity will help reduce waste generation. Biobased PBS is 100% renewable. Nevertheless, preparation of composites or blends with fossil-derived assemblies may have an impact on this quantification.

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73

Sensitivity Study: The Impact of Resource Efficiency and Waste Minimisation Strategies

The overall impact of employing the principles of resource efficiency on the environmental performance of production pathways used to synthesise these biobased candidates was explored further setting the following sensitivity scenario. The aim of this sensitivity study was to evaluate and quantify the overall life cycle impacts of biobased products with and without the incorporation of resource efficiency and circularity (RE&C) strategies for the same set of impact categories. The biobased product synthesis with embedded resource efficiency and waste reduction strategies was assessed for environmental performance earlier. These quantified impacts will set the benchmark for the proposed scenario. For our sensitivity study, the energy and materials circularity and waste reduction strategies embedded within the production processes and sub-processes will be omitted. The outcomes will be compared with that of the benchmark, providing a clear picture of the impact and credits associated with employing resource efficiency and material circularity principles (for example, energy use and materials wasted). It is essential to note that this sensitivity study is undertaken only for the averaged impact quantifications of the biobased products and not for the fossil-based case studies, firstly due to this being not within the scope of our analysis and secondly due to the lack of data within the published literature for the fossil-based candidates. The LCA of this sensitivity scenario resulted in the outcome that has been presented in Figure 3.5. In the benchmark production process for L-Lactic acid (entering the production of both BoPLA packaging film and PLA mulch film), methanol, which is used to convert lactic acid monomers to methyl lactate, is assumed

Figure 3.5

Variation in environmental impact associated to the three biobased case studies subjected to a sensitivity study (with and without resource efficiency and circularity characteristics).

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to be recovered and reused. For this sensitivity study, the energy demand of this step and the recovered and reused fraction of methanol was omitted and instead, it was assumed as a waste that was disposed through the liquid waste stream. Recovery and reuse of unreacted components from the L-lactic acid production step were also omitted. Elimination of any waste reduction approaches employed within the PLA packaging film production process is demonstrated by the þ26–33% increase in the waste factor. A significant increase in GWP100 (þ18–25% for the biobased case studies) was observed from a combination of the solid waste generated (from the fermentation process) going to landfill, the need for additional quantities of raw feedstock to make up for the loss of monomers and the need for additional methanol within the process. Any savings in energy consumption stemming from the cancellation of the RE&C approaches were nullified by the additional demand for energy from an additional need for glucose and other process materials (þ6–30%). This added energy requirement, particularly in the case of BoPLA films, caused an increase in emissions to air through the burning of a fossil fuel (natural gas), thereby leading to relatively increased acidification potential (þ24%). During bio-SA production, the process was designed to recover, re-process and reuse fermentation water leading to a quantified water consumption of only 14.05 kg, saving 115.2 kg of through the use of reverse osmosis. For the sensitivity study, the energy demand for water recovery was deducted and the water savings were omitted. The loss of invested process water, due to the lack of its recovery, reprocessing and reuse step in the original assessment, lead to an increase in the overall process water requirement (þ8–16%). In the case of PLA mulch films, fermentation waste sent to landfill and loss of inorganic solvents through the waste streams resulted in an increase in eutrophication potential.

3.4.1.1

Limitations of the Proposed Sustainability Analysis Methods

Based on the experience of employing the hybridised environmental indicators to the case studies, some benefits and limitations have been identified. The hybridised indicators were instrumental in identifying and assessing the circular, resource efficiency characteristics of the processes associated to the production of the selected case studies. In addition to fulfilling the purpose that has been elaborate in the section 3.1, the flexibility of these indicators has also been demonstrated where the quantifications of their environmental impact have been presented for the functional unit of each of the case studies. Such an approach to result presentation, besides complying with the standards for life cycle impact assessment communication, also provides an opportunity for a convenient and coherent interpretation of the same. Similar to the LCA indicators that are applicable to both biobased and fossil-derived products without the need for major modifications, the hybridised indicators provide a level playing field to enable the comparison of both the biobased products with that of their fossil-derived counterparts.

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The hybridised indicators, however, need further refinement. A combination of the scope of our study and lack of data provided no opportunity to assess the performance of these indicators when applied to second-life products or products belonging to other product groups and sectors within the biobased sector. This is also recommended as a potential area to explore in our future work. Another key requirement for the successful application of the hybridised indicators (similar to LCA indicators) is data availability. Availability of the product’s life cycle inventory that provides crucial information of material and energy flow, including internal strategies for augmented resource efficiency through recovery and reuse or recycling approaches and loss of resources as production waste or leakages, is crucial. It is essential to note that these indicators quantify parameters that are only related to the process that is studied. They can be applied to the appropriate life cycle stages spanning from ‘‘cradle-grave’’. However, these indicators rely heavily on the transparency of the economic operators and the documentation provided (life cycle inventory), to quantify the sustainability characteristics (for example, hazardous chemical use). This dependency undermines the accuracy and proficiency of these indicators, in the event of a lack of primary (industrial) data. Finally, similar to LCA, the scope of evaluation must be clearly defined to avoid potential double counting. With regards to the hazardous chemical use, though the current indicator provides an indication of the whether a substance of high concern is present or absent, further developments which will highlight potential toxicity or hazard status of any detected restricted substances is required. This is also a recommendation for future work for further method development.

3.5 Conclusion This study was dedicated to the identification and development of environmental impact indicators that could contribute to the evaluation of the environmental performance of biobased products, independently or in comparison with that of petro-derived counterparts. Upon extensive literature review and careful assessment, a set of LCA indicators, which needed to be complemented with a set of hybridised indicators that address the resource-efficient nature of a given technology route, were identified. The robustness of the selected LCA and hybridised indicators were evaluated through a comparative LCA of promising biobased case studies and their fossil-derived commercial equivalents, from ‘‘manufacturing to distribution to consumer’’ stages. During the result interpretation phase, the LCA indicators were instrumental in highlighting the resource and energy hotspots, toxicity to environment and human health, in addition to the quantification of impacts from minimisation of resource use. The hybridised indicators were determined to be instrumental in directly quantifying resource consumption and wastage, embedded resource circularity, renewable nature of the product and the process inventory, use of any substances that are restricted/facing potential restriction. The hybridised indicators were primarily used to assess the technology routes and the

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outcomes were not influenced by the choice of feedstock or other relevant parameters. Therefore, their applicability to the end-of-life management options associated with biobased products (including disassembly and reuse, recycling, incineration with or without energy recovery, composting, anaerobic digestion) would be a valuable study. A dedicated research to adopt these hybridised indicators towards developing a method for the endof-life impact assessment is currently being undertaken. Additionally, environmental evaluation of products and processes from other sectors using the proposed methodology (for example, pharmaceuticals, fine chemicals, automotive, agriculture) to understand the potential and limitations for their horizontal applicability is also a recommendation for future work.

Acknowledgements This research is a part of the findings of the project STAR-ProBio which is European Union’s Horizon 2020 funded, under grant agreement No. 727740, work programme BB-01-2016: Sustainability schemes for the biobased economy. I would also like to convey my special thanks to our partners from the Agricultural University of Athens, Quantis Sarl and University of Santiago Compostela who made significant contributions to this part of our research.

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9. H. Moussa and S. Young, PhD Thesis, University of Waterloo, 2014. 10. S. Papong, P. Malakul, R. Trungkavashirakun, P. Wenunun, T. Chom-in, M. Nithitanakul and E. Sarobol, J. Cleaner Prod., 2014, 65, 539–550. 11. F. Razza and A. K. Cerutti, in Soil Degradable Bioplastics for a Sustainable Modern Agriculture, ed. M. Malinconico, Springer Berlin Heidelberg, Berlin, Heidelberg, 2017, pp. 169–185. 12. S. Majer, D. Moosman, S. Wurster and L. Ladu, Report on identified environmental, social and economic criteria/indicators/requirements and related ‘Gap Analysis’, 2017. ¨ppen, B. Kauertz, A. Detzel, F. Wellenreuther, 13. H. Fehrenback, S. Ko E. Brietmayer, R. Essel, M. Carus, S. Kay, B. Wern, F. Baur, K. Bienge and J. Von Geibler, Biomass Cascades: Increasing Resource Efficiency by Cascading Use of Biomass- From Theory to Practice, German Environmental Agency, Heidelberg, Germany, 2017. 14. A. Tukker, J. Cleaner Prod., 2015, 97, 76–91. 15. ISCC202 Sustainability Requirements V3.0, International Sustainability and Carbon Certification, 2016. 16. Roundtable on Sustainable Biomaterials, RSB standards for the certification of biofuels and biomaterials based on end-of-life products, byproducts an residues, Switzerland, 2017. 17. International Organization for Standardization, Environmental management – Eco-effcieincy assessment of product systems – Principles, requirements and guidelines, 2012, ISO 14045:2012. 18. CEN European Committee for Standardization, Bio-based product. Sustainable criteria, European Committee for Standardization, 2016, BS EN 16751:2016. 19. BASF, Eco-Efficiency Analysis, https://www.basf.com/en/company/ sustainability/management-and-instruments/quantifying-sustainability/ eco-efficiency-analysis.html, (accessed 6 September 2018). 20. International organisation of Standardisation, 2012. 21. R. K. Helling, S. E. Hunter, E. Ocampo and H. Zhang, ACS Sustainable Chem. Eng., 2018, 6, 2250–2255. 22. R. A. Sheldon, Green Chem., 2017, 19, 18–43. 23. R. A. Sheldon, Catal. Today, 2011, 167, 3–13. 24. R. G. G. Caiado, R. de Freitas Dias, L. V. Mattos, O. L. G. Quelhas and W. Leal Filho, J. Cleaner Prod., 2017, 165, 890–904. 25. A. Azapagic and S. Perdan, Process Saf. Environ. Prot., 2000, 78, 243–261. 26. L. Schneider, V. Bach and M. Finkbeiner, in Special Types of Life Cycle Assessment, ed. M. Finkbeiner, Springer Netherlands, Dordrecht, 2016, pp. 179–218. 27. G. J. Ruiz-Mercado, R. L. Smith and M. A. Gonzalez, Ind. Eng. Chem. Res., 2012, 51, 2309–2328. 28. World Business Council for Sustainable Development, Chemical Industry Methodology for Portfolio Sustainability Assessment (PSA), 2018. 29. Ellen Macarthur Foundation, Circularity Indicators, https://www. ellenmacarthurfoundation.org/resources/apply/circularity-indicators, (accessed 17 December 2018).

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CHAPTER 4

Techno-economic Sustainability Assessment: Methodological Approaches for Biobased Products D. BRIASSOULIS,*a A. KOUTINAS,b J. GOŁASZEWSKI,c A. PIKASI,a D. LADAKIS,b M. HISKAKISa AND M. TSAKONAb a

Department of Natural Resources & Agricultural Engineering, Agricultural University of Athens, 75, Iera Odos Str., 11855 Athens, Greece; b Department of Food Science & Human Nutrition, Agricultural University of Athens, 75, Iera Odos Str., 11855 Athens, Greece; c Centre for Bioeconomy and Renewable Energies, University of Warmia and Mazury in Olsztyn, Poland *Email: [email protected]

4.1 Introduction 4.1.1

Techno-economic Sustainability Analysis

Sustainable development is defined as ‘‘the ability of humanity to ensure that it meets the needs of the present without compromising the ability of future generations to meet their own needs. Sustainable development is not a fixed state of harmony, but rather a process of change in which the exploitation of resources, the direction of investments, the orientation of technological

Green Chemistry Series No. 64 Transition Towards a Sustainable Biobased Economy Edited by Piergiuseppe Morone and James H. Clark r The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

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development and institutional changes are made consistent with future as well as present needs’’.1 The complete sustainability of a system (e.g. of a process or a product) consists of three pillars of sustainability: economic, social, and environmental pillars. A system is unsustainable as a whole, if any one pillar is weak.2 However, a theoretically rigorous description of the three sustainability pillars is missing.3 The glossary entries for the three pillars of sustainability appear to be incorrect as they represent goals hard to be achieved:1 Environmental sustainability: ‘‘The ability of the environment to support a defined level of environmental quality and natural resource extraction rates indefinitely’’. Symptoms of an environmentally unsustainable system include major forest fires, icebergs melting and collapsing, marine litter, etc. Economic sustainability: ‘‘The ability of an economy to support a defined level of economic production indefinitely’’. A major characteristic symptom of an economically unsustainable system is the Great Recession of 2008. Social sustainability: ‘‘The ability of a social system, such as a country, family, or organisation, to function at a defined level of social well-being and harmony indefinitely’’. Symptoms of a socially unsustainable system include wars, endemic poverty, low education rates, widespread injustice, etc. Optimisation of economics and high efficiency are required for the overall production process of biobased products to be competitive to that of fossil feedstock based products, combined with minimisation of negative environmental impact.4 While analysing the different alternative scenarios of resources and processing routes used for the production of biobased products and the alternative End-of-Life (EoL) options for post-consumer and post-industrial biobased products, the critical parameters that affect the applicability of each scenario need to be assessed. The scope of this chapter is to define the relevant criteria and indicators that can be used to evaluate the techno-economic dimension of the sustainability of the alternative scenarios for the three stages of the biobased products life cycle (resources, processing, EoL). Before proceeding, the key terms are clarified. Techno-Economic Assessment: or Techno-economic analysis (abbreviated TEA) is a methodology framework to analyse the technical and economic performance of a process, product or service.5 TEA in principle is a costbenefit comparison using different methods. These assessments are used for tasks such as to evaluate the economic feasibility of a specific project, investigate cash flows (e.g. financing problems) over the lifetime, evaluate the likelihood of different technology scales and applications, and compare the economic quality of different technology applications providing the same service.6 TEA is used widely as an integral cost-benefit comparison tool for commercial project development to determine life cycle costs of a project but also for research and development of new products. TEA is one of the most important activities during the development phase of new products or

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services. This analysis differs greatly between an existing product in the market, where real data exist, and a conceptual new product, where the data have to be estimated. In the first case a detailed process flow diagram of the system can be constructed and the variability of some of the parameters (feedstock availability, market, resources, etc.) can be accurately estimated. In the case of a new process the analysis depends of the readiness level. At least advanced laboratory and early scale-up data have to be available in order to construct a process flow diagram scenario and use simulation tools to estimate the inputs, outputs and resources utilisation. In most cases, only a stochastic model can account for the risk factors that will allow the economic funding of the project described by the scenario analysed. The variability of the inputs and outputs in such a model are represented as probabilistic functions. The standard deviation of this function represents the uncertainty (risk) and decreases if more data are made available (by increasing the readiness level).8 Specifically, for biobased products, TEA aims at providing a quantitative and qualitative analysis of the impact of technological advances and the economy-of-scale on the financial viability of the conversion of biomass and processing to materials and products, their use and their EoL routes. Sustainability: The most widely quoted definition of sustainability and sustainable development is that of the World Commission on Environment and Development (WCED, Brundtland Commission) of the United Nations (UN): ‘Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs’.9 The standard ISO 26000:2010 defines sustainable development as the development that meets the needs of the present without compromising the ability of future generations to meet their own needs.10 Sustainable development is about integrating the goals of a high quality of life, health and prosperity with social justice and maintaining the Earth’s capacity to support life in all its diversity. These social, economic and environmental goals are interdependent and mutually reinforcing. Sustainable development can be treated as a way of expressing the broader expectations of society as a whole. Furthermore, EN 16751:2016 defines sustainability as the goal of sustainable development.11 While using (environmental) Life Cycle Analysis (LCA) to measure the environmental dimension of sustainability is widespread, similar approaches for the economic (Life Cycle Costing, LCC) and the social (S-LCA) dimensions of sustainability have still limited application worldwide and techno-economic sustainability analysis has been very recently introduced in limited research projects.12,13 The UNEP/SETAC Life Cycle initiative has provided a definition on life cycle sustainability assessment (LCSA) that refers to the evaluation of all environmental, social and economic negative impacts and benefits in decision-making processes towards more sustainable products throughout their life cycle.14 Notwithstanding, a clear definition on techno-economic sustainability analysis is not available.

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Techno-Economic Sustainability Assessment or Techno-economic sustainability analysis (abbreviated TESA): A comprehensive approach on the definition of techno-economic sustainability analysis is provided by Gargalo et al. who describe their proposed framework for techno-economic and environmental sustainability analysis as ‘a step-by-step framework whose purpose is to identify the best potential alternative(s) that would sustainably create value with the least potential risk of economic and environmental impact’.7 The techno-economic sustainability analysis, depending on its specific scope, compares the technical and economic sustainability aspect of two existing or optimised systems or alternatives. Therefore, the techno-economic sustainability analysis of biobased products uses the results of techno-economic analysis and optimisation to compare the profitability (with a broad sense that includes all involved stakeholders) and viability of the products in question. This techno-economic sustainability analysis in interaction with the environmental sustainability analysis and the social sustainability analysis complete the sustainability analysis for a specific biobased product case. The techno-economic sustainability analysis should respond to two questions: – Technical feasibility and sustainability of resources – Economic profitability with a very broad definition that includes all stakeholders like the consumers and the community and society in addition to the traditional businesses (that in any case will not operate unless they are profitable). It is evident that there is a significant overlapping between the technoeconomic, environmental and social aspects particularly in the community and the society profitability concepts. Finally, it has to be emphasised that the sustainability analysis intends to compare cases and not to provide thresholds. This modular chapter presents a techno-economic sustainability assessment methodology for the biobased products. The TESA of a biobased product applies to the alternative scenarios of the three stages of the whole life cycle of the product from the resources, to processing and the EoL routes.

4.2 Techno-economy Sustainability Analysis Methodology for Renewable Feedstock Resources Used for Biobased Products 4.2.1

Natural Renewable Resources – Introduction

The economic growth is a process of increasing market value of the goods and services over time. Nowadays, the crucial prerequisite for the process is to develop economy of biobased resources through integration of the economic, environmental and social issues from the life cycle perspective into a consistent policy framework. Assuming that natural resources are finite and limited, the

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improvement of resource efficiency is set up at the top priorities globally, in the EU and in the national programmes dedicated to resource use and bioeconomy.15–17 The programmes assume undertaking significant efforts oriented on sustainable development of new resource efficient biobased products. It is anticipated that in the short to medium terms a resource efficient aspect of bioeconomy will amplify improved productivity, economic growth and new jobs, environmental benefits and resilience, and macroeconomic stability.11 The biobased products origin is in biological resources. They are composed of biotic resources (living and organic materials) regenerated naturally or by agricultural, forestry, fishing and aquaculture practices with simultaneous exploitation of other biotic and abiotic resources such as land area, air, water, fossils and minerals. The importance of sustainable and productive agriculture is strongly expressed among the 17 Sustainable Development Goals and 169 associated targets, including target 2.4 ‘‘By 2030, ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production, that help maintain ecosystems, that strengthen capacity for adaptation to climate change, extreme weather, drought, flooding and other disasters and that progressively improve land and soil quality’’ and indicator 2.4.1 ‘‘Proportion of agricultural area under productive and sustainable agriculture’’.18 The available indicators and statistics for the bioeconomy sectors present resource use data associated with the acreage and harvested volume of main raw materials used for making marketable bio-products. They include the primary and secondary feedstocks converted to consumables such as food, feeds and industrial products.19,20 It can be assumed that such the feedstocks represent the volume of extracted resources and are produced by efficient techno-economic activities. The key question arises: is there any potential for new products from the same volume of feedstock? The scenarios developed for resource management assume that such opportunity requires a transition of the present economic paradigm of a positive correlation between increased production of goods and services and resource use into a paradigm which will focus on the improvement of resource efficiency by minimisation of waste generation at any stage of supply chains and the maximisation of the conversion of by-products to marketable products. All the activities should be accompanied with a more efficient processing of biomass together with rational waste management at all stages of supply chain including EoL options returning nutrients to the environment. Those activities are needed to maintain life support systems related to water and energy use, biodiversity, and competition for land area dedicated to primary biomass production. It means that economic growth should be decoupled from resource use and resource use from environmental impact.8 Such a concept entails several challenges and risks, including feedstock supply reliability and fragmented supply chain with mostly local and small-scale landowners (farmers, foresters). The process of improvement the feedstock supply reliability and guarantee the quality of biobased products is associated with a stronger horizontal and vertical integration of supply chains by certifications of

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environmental benefits and providing sustainability standards that integrate the efficiency of resource use with biobased products.

4.2.1.1

Natural Renewable Resources and Resource Use Efficiency

The main drivers for global natural resource depletion are growing population, income and structural changes in standards of living and diets. According to the UN population projections, by 2050 the world population will reach about 9.8 billion people, roughly 1/4 more than the present figure that accounts for about 7.6 billion people.21 Besides, it is predicted that by 2030 the aspiration of now-developing countries for improving standard of living will contribute to the 3-fold increase in the global middle-class consumption level.10,22 This demographic tendency and anticipated improvement in standard of living will be accompanied by growing global demand for natural renewable and non-renewable resources. First of all, the increase in world population correlates with growing demand for food, energy and industrial products. Those commodities entail the use of natural resources. The indices for the growing consumption of food and industrial products and also economic output for the 20th century were increased concomitantly. The amount of primary materials extracted from the Earth amounted to 70 billion tonnes in 2010 and over the last four decades it has shown an over-3-fold increase.23 The use of fossil fuels has increased by 12, fishing catches by 35, water use by 9, extraction of material resources by 8 and minerals by 23 times during this period. At the same time, there was a 23-fold increase of economic output.11 Further, when we assume that by 2050 the arable land in developing countries will decrease by 6% and in developed countries will increase by 15% and the impact of extreme climate conditions to the economy may be more frequent we can also assume that in order to keep economy growing, the agricultural and industrial production should be more intensive and productive.24 But intensive production requires not only better use of existing land and practices but also higher inputs of energy and other production means (machinery, equipment, fertilisers, pesticides, etc.). Nowadays, the pivotal requirement for smart economic activities to change this tendency is a continuous improvement in management of natural resources. The set of sustainability indicators of natural resource use specific to biobased production was proposed by Go"aszewski et al.25 The indicators were related to the productivity of material, energy, water and land area use in association with ecosystem provisioning and regulating services and discussed in the context of eco-efficiency as resource productivity and resource specific impact intensity. Biomass is a renewable material that can be continually replenished.26 Primary or secondary material that is used to produce a product composes the raw material feedstock.5 The availability of cost-effective biomass feedstock, even if renewable, is not unlimited. It leads to the potential competition between different biomass-based economy sectors. Natural resources used for biomass production, such as soil and water in aquifers, and certain biomass

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resources, such as forests, animals and fish, are called ‘‘critical zone renewable resources’’ and other resources associated with renewable energy (solar, wind, waves), water and air comprise ‘‘non-critical zone renewable resources’’.27 While renewable resources are naturally renewed within short periods of time, they can be used to exhaustion depending on the degree and type of exploitation.28 Globally, the use of natural resources has more than tripled since 1970 and the key impacts caused by resource extraction and processing are 90% biodiversity loss and water stress.29 The biomass flows in the EU-28 economy is shown in Figure 4.1. The biggest supply sector of biomass per dry matter content basis is agriculture (65%, including crops 69%, crop residues 14% and grazed biomass 17%) followed by forestry (34%, including primary biomass 68%, by- and co-products 24% and other uses 4%) and fishery sector (1%). Currently, the aquaculture origin biomass is of a marginal amount (less than 1%). At the same time 62% of biomass is used for feed and food, 19% for bioenergy and 19% for biomaterials.30 Resource efficiency improvement is related to rational exploitation and use of natural biotic and abiotic resources. It means that raw materials, energy, water and land area should be exploited in a way which will reconcile production, energy and cost efficiency with regeneration of exploited resources. In order to attain the above assumptions the economic activities should be considered on a life cycle basis, including efficient and maximally productive resource use and extending the use of renewable resources and additional conversions to other products at any stage of supply chain. Those activities should be accompanied with assessment of internal life cycle assessment costs as well as costs imputed to environmental externalities and social impacts.

4.2.1.2

Techno-economic Sustainability Assessment in Relation to Biomass-based Resources

In order to predict the bioeconomy growth in the context of sustainability the first step is to introduce an understandable approach for the estimation of technicalities related to the fabrication of biobased goods and services in relation to economic evaluation and environmental impacts. The concept of TEA is not new but its practice is generally associated with the assessment of selected stages of the entire value chain such as biomass production, raw material feedstock, or bioenergy generation.31–35 TEA in the framework of sustainability assessment of biobased products begins and ends with the natural world of human life and human economic activities, i.e. the ecosystems (natural capital36) and ecosystem services (natural resources37), followed by economic activities (beneficiaries38) and socio-economic implications related to improvement in the quality of ecosystems (management, conservation39). Ecosystem management links economic activities and associated impacts to ecosystems with Earth system processes including the planet’s natural cycles of carbon, water, nitrogen, and phosphorus flows.40 Hence, the resource use in TEA in the sustainability context can be seen as an ecosystem-based approach

Methodological Approaches for Biobased Products

Figure 4.1

The Sankey biomass diagram – towards a cross-set integration of biomass.23 r European Union 2017. Source: http://dx.doi.org/10.2760/22906.

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undertaken at the phase of product design which combine technical and economic evaluation of the sustainable value chain for biobased products by links of the extraction of biomass having desirable chemical composition with the final biobased product and EoL options. The approach integrates the TEA of the entire supply chain and EoL options with environmental impacts (LCA) and extends it into economic (Life Cycle Costing, LCC) and social (SocialLCA, S-LCA) life cycle impact analysis. Therefore, TEA in sustainability assessment of biobased products entails three main stages: 1) modelling life cycle potential allocations of resources along the entire supply chain and EoL options; 2) techno-economic assessment (TEA), and 3) environmental (LCA), cost (LCC) and social (S-LCA) life cycle analyses.

4.2.2

Objectives

The aim of the study is to present the methodological approach to TESA regarding renewable resource use for biobased products. TEA entails the resources use at the upstream, midstream and downstream stages of biobased product supply chain and EoL options in relation to economic evaluation and environmental impacts. It comprises an inventory of alternative feedstock resources, the collection and analysis of data on alternative feedstock resources for biobased products including the extraction of raw material feedstock – protein, oil, starch, simple sugars, and fibre (industrial crops: coand by-products, waste streams), primary agricultural production (food) and the associated agri-food industries co- and by-products and waste streams.

4.2.3 Methodological Approach to Resource Use in TESA 4.2.3.1 Supply Chain and Life Cycle Material Flow Scheme Supply chain integrates activities involved in the process of sourcing, preprocessing, conversion and logistics and finishes when the product reaches the final user. Those activities seen in business terms compose the value chain. The concept of value chain was originally developed by Porter.41 Kaplinsky and Morris define the value chain as ‘‘the full range of activities which are required to bring a product or service from conception, through the different phases of production (involving a combination of physical transformation and the input of various producer services), delivery to final customers, and final disposal after use’’.42 From the standardisation point of view, the supply chain of biobased products is defined as the linked set of resources and processing that begins with the production of raw material and extends through the manufacturing, processing, handling and delivery of products to the purchaser.5 Taking this meaning of supply chain into consideration the scheme of the life cycle renewable feedstock resources flow assumed for TEA is shown in Figure 4.2. It entails resource use in a set of unit processes including sets of downstream, midstream and upstream processes, i.e. biomass production, harvesting, acquisition and handling, processing to

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Figure 4.2

The scheme of material flow along the supply chain of biobased products.33

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Table 4.1

The list of EU-based value chains.

36

No Sector

Value chain

1

Chemicals

2

Disposable food packaging Cutlery Agriculture

Cellulose to bio-solventsGlycerine to liquid epoxy resin adhesivesLignin to carbon nanofibres Starch to bioplastic food packagingStarch to beverage bottles

3 4

Simple sugars or starch to single use cutlery Starch to biobased mulch filmsStarch to clips, binders and seeding potsPolysaccharides to crop health inducersSolid biomass to fine chemicals 5 Fabrication Starch to bioplastics for fabrication 6 Automotive Vegetable fats to bio-lubricantsCellulose to car interior panels 7 Textiles Starch to carpetsCellulose to fabricRubber to single use gloves 8 Food packaging Cellulose to plastic cups 9 Construction Waste biomass to insulation materialWaste biomass to wood-plastic compositesSimple sugars to PVC pipes 10 Animal husbandry Plant-based chemicals to fine chemicals

raw material feedstock, processing to intermediates, conversion to platform chemicals, chemical derivatives up to the final marketable product and its delivery to customer. The processes require inputs of raw materials, land area, water, and energy. The integral part of the approach is composed by unit processes associated with co-product or by-product and/or biowaste usage by conversion to secondary material or EoL processing including wastewater treatment and energy recovery. A variety of biobased value chains have been identified within the EU and the examples are presented in Table 4.1.43–45 Those examples provide a spectrum of innovative biobased products which are manufactured with performance and at the cost evaluated in the process of TEA. Nowadays, this standard approach can be completed with evaluation of GHG emissions. However, sustainability assessment requires a broader insight into life cycle environmental impact followed by socioeconomic consequences, considering resource flow along the entire supply chain and intended EoL options. By using the basal inventory data of TEA, the estimation of environmental impacts can be based on the life cycle analysis (LCA) that is well regulated by standards (ISO 14040:2006, ISO 14044:2006, CEN/EN 16760:2015) and specific guidelines (PEFCR v.6.2:2018). Regarding the following criteria, feedstock variability, multi-regional supply chain, variety of EoL options, gaps in sustainability schemes, EU feedstock preference, multi-sector application and potential for growth were selected for the most promising biobased value chains: solid biomass to biobased chemicals, starch to biobased plastics, solid biomass to fibres and insulation materials and oil biomass to biobased lubricants.46 Figure 4.3 develops an exemplary supply chain ‘‘starch to biobased mulch film’’. The starch is derived from maize feedstock and the following processes provide starch, unrefined dextrose, lactic acid, lactide, polylactic acid and the final biobased product.

Methodological Approaches for Biobased Products

Figure 4.3

The exemplary supply chain for production of biobased mulch film from maize starch.33

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In order to support the future bioeconomy policy and decision-making at the EU level research was conducted on environmental impact assessments of innovative biobased products and their petrochemical counterparts.47 The outputs were based on the sixteen environmental impact categories (excluding land use changes) plus the inclusion of EoL stage. Seven cradle-to-grave case studies on biobased plastics produced from agricultural feedstock, i.e. beverage bottles, single use cups, single use cutlery, packaging films, horticultural clips, much films and carrier bags, were selected from the 17th innovative biobased products. The obtained results clearly indicate that on average the main environmental impacts were associated with the stage of manufacture and the use of energy and chemicals (over 50%) and biomass production (about 10%). The impact of EoL stage was highly differentiated and dependent on the way the biobased product was treated to have a positive or negative contribution to the overall assessment. Up to now there is no clear indications in the literature on specific socio-economic impacts of innovative biobased products. However, TEA in the context of sustainability assessment of biobased products should be based on the supply chain from biomass to end user and intendent EoL options in order to provide conformity assessment including chain of custody and tracking sustainability (e.g. mass balance).

4.2.3.2

Biomass Resources

The primary biomass resources origin from plants (phytomass) and are classified into two groups: – gymnosperms (non-flowering plants: softwood), e.g. pine, spruce, fir; – angiosperms (flowering plants), divided further into: – monocots: – perennial grasses, e.g. Miscanthus, sorghum, sugar cane; – herbaceous species, e.g. cereals such as wheat, corn; – dicots: – flowering non-perennial, e.g. soybean, alfalfa, hemp, flax; – perennial such as hardwoods, e.g. poplar, willow. In the study all plant resources are considered the agricultural, forestry or aquaculture raw material feedstocks. For the sake of conversions they can be grouped according to the main chemical platform of a given biomass: simple sugars, starch, vegetable oils, fibres; lignocellulose and protein. Besides, coproducts, by-products and biowaste streams from plant production will contribute to the balance of raw material. In the context of value chain primary biomass resources are directly exploited from the ecosystems and compose the TEA input. The statistics related to biomass production provide the basis for calculation of the volumes of raw material feedstock, coproducts, by-products and residues. The secondary biomass resources origin is from animals (zoomass). Livestock and aquaculture animals use primary feedstock for feed to

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Figure 4.4

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The generic scheme for classification of resources of biomass and residues as potential material inputs or outputs of TEA.33

produce food but at the same time the production and processing generate numerous by-products and residues with the potential for further conversions to other biobased products. The statistics related to heads, production and animal products processing provide the basis for calculation of the volumes of co-products, by-products and residues. The processing and post-use residue and biowaste streams compose the tertiary biomass. The classification of primary, secondary and tertiary biomass and associated residues in a hierarchy to the process of photosynthesis is presented in Figure 4.4. In TEA of biobased products, primary biomass and residues compose the key resource input. The improvements in efficiency of biomass production and raw material feedstock processing contribute not only to the overall profitability through TEA-based techno-economic indicators but also to reduction of negative impact on interrelated biobased sectors (competition for land area and biomass) and social implications (feed security) through sustainability assessment by environmental and socio-economic indicators.

4.2.3.3

Abiotic Resources

The biomass production and conversion to biobased products require input of abiotic resources. In TEA they are associated with non-renewable material use (fossil fuels, minerals), use of renewable non-biobased energy, depletion of water and exploitation of land area. The abiotic resource uses cause the main environmental impacts and associated socio-economic consequences.

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TEA simulations oriented on the saving, mitigation or reduction of nonrenewable resource use as well as on the increase of renewable energy use can provide the most desirable extension to sustainability aspects as the generalisation of TEA into sustainability assessment.

4.2.3.4

TEA approach in the Sustainability Aspects

The life cycle-oriented TEA of resource use for sustainable biobased products comprises three levels: 1. Biobased product-oriented process modelling that sets up a series of processes along supply chain and EoL options; it enables comparison of different configuration of processes. Assuming material flow along the supply chain (see Figures 4.2 and 4.3) and boundaries related to the life cycle assessment the generic model for resource use along the biobased value chain assumes following stages (Figure 4.5): – biomass production or acquisition (procurement); – upstream (pre-treatment to raw material feedstock); – manufacturing (conversion); – downstream (refining, formulation to final product, packaging, distribution); – use/consumption; – EoL management. The life cycle model cradle to cradle combines ecosystem provisioning services. 2. Engineering design process that sets up a series of steps that create functional processes and products in such a way that they can be manufactured regarding numerous aspects for consideration including operating parameters, materials requirements, design life, packaging and others; this level implements different concepts and assumptions on the basis of current knowledge (literature and research and development data) and provides indications on potential technical and economic problems. Regarding renewable resources use, TEA involves functional processes related to: – applied technology and technical equipment; – material inputs (raw material use for biobased processing and renewable energy, water) and outputs (products, co-products, byproducts, biowaste and emissions); – EoL treatment with engineering the fate of each output from each stage of value chain; – labour engagement. Figure 4.6 provides exemplary insight into numerous potential options of TEA to configure the optimal pathway from the feedstock to final product(s) and engineering the EoL options. In general, plantbased raw material feedstocks compose the processing basis for sugar, lignin and vegetable oil chemical routes.

Methodological Approaches for Biobased Products

Figure 4.5

The generic model of life cycle oriented renewable resources flow along the value chain.33

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96 The differentiated pathways from raw material feedstock through sugar, lignin and vegetable oil chemical routes to biobased products.33

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Figure 4.6

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The technology and technical equipment related to the final biobased products can involve very differentiated pathways of resource use in processing regarding the feedstock production, acquisition, pre-treatment options, dedicated routes and processing to the 1st product (e.g. to C6 sugar-based ethanol via microbial fermentation) or to the 2nd product (e.g. to ethanol-based polymers via downstream catalysis) or to the 3rd product (e.g. to polyethylenebased plastic bag). 3. Economic evaluation by identification and valuation of inputs and outputs in the context of the cost-benefit analysis (CBA) expressed in monetary terms as profitability and sensitivity analyses; this level is related to the previous one through the physical balance of resource use in terms of mass, energy and water flow. The aspect of sustainability imposes cost-effectiveness analysis (CEA) expressed as the ratio where denominator is a gain in a sustainability aspect. The use of renewable resources, mostly as raw material feedstock, compose the main input in the fabrication of biobased products but the structure of the costs (capital, operating) strongly depends on the final product (bioenergy, biomaterials, biochemicals). In TEA the capital costs entail the costs of purchase, installation, engineering and construction and finance-related, while operating costs are associated directly with the input of raw materials (feedstock, energy, chemicals, minerals), energy, water and labour, as well as other inputs related to logistics (e.g. transport, distance to the site), upstream processing (e.g. formulation, packaging) and waste treatment. The operating costs for resource use can be significantly reduced by recirculation of media (water, energy) and cascade processing to other valuable products (e.g. the ‘‘zero waste’’ concept). The data collected in TEA can contribute directly to the LCA, LCC and S-LCA and one of the commonly integrated evaluations of environmental impacts are emissions of greenhouse gases that can be also expressed in monetary terms. The important part of economic evaluation associated with resource use is sensitivity and risk analysis, i.e. the simulation analysis to predict the outcomes of decision given the change of biomass volume and composition, distance related transport, etc.

4.2.4

Recapitulation

The TEA is going to be an integral part of any research and investing activities associated with the development of new biobased goods or services. In the three levels approach combining process modelling, engineering design and economic evaluation TEA provides numerous parameters for techno-economic evaluation. The renewable resource use is a sensitive factor of TEA and a specific relation of resource use with sustainability assessment is to be developed. At the core of an effective TEA there is reliable information gathered from different sources including research and development

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outputs, relevant literature, and market-specific information. In such the cases TEA enables: – economic viability; – simulations and optimisation of unit processes and the whole production process; – detection and elimination of bottlenecks; – continuous validation and verification of the process modelling, engineering design and economic evaluation; – scaling-up to a commercial scale facility; – decision on investment, future research, and policy making. The natural process of ongoing TEA development is to entail sustainability assessment including the focus on the key input category – the uses of renewable natural resources and valuation of their impact to environmental, economic and social well-being. It is justifiable because TEA data can be used not only for assessment of techno-economic parameters required for decision on profitability and investment, but also for evaluation of environmental (LCA) and socio-economic (LCC, S-LCA) sustainability aspects. Nowadays, there is no unique methodological approach on how to integrate TEA with sustainability assessment. Instead the current methodologies that assume sustainability aspects rely mostly on separately executed TEA and LCA. The above-mentioned approach that provides indications on integration of TEA with sustainability aspects coincides with the idea to the complex evaluation of sustainability of biobased products.33

4.3 Techno-economy Sustainability and Analysis Methodology for Conversion Routes of Renewable Feedstock Resources to Biobased Products 4.3.1

Methodology Development

The techno-economic sustainability analysis (TESA) methodology for the process stage leading to the production of biobased products has been developed based on four preliminary inventory analysis steps, followed by two TESA methodological stages for the development of techno-economic sustainability principles, criteria, and indicators. The aim of this methodological framework is to ensure the development of optimal and sustainable conversion routes for the production of biobased products using renewable resources. Future sustainable processes should allow for process improvement and optimisation based on alternative renewable feedstock evaluation and efficient processing, valorisation of waste and by-product streams and recirculation of used biobased products from the EoL alternative stages into the manufacturing stage in line with the principles of circular economy.

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Step 1: Identification of International Standards, Initiatives and Legislations on Sustainability Aspects for the Production of Biofuels, Bioenergy and Biomass A comprehensive review of existing sustainability evaluation methodologies for the production of bioenergy, biomass and biofuels has provided a list of currently used principles, criteria and indicators for these sectors. In this way, the frequency that sustainability criteria are used could be assessed. Furthermore, any differences in the aforementioned sectors have been identified. This analysis was exploited in order to set the basis for the development of the methodological framework for the production of biobased products from any crude renewable feedstock. The analysis was initiated with the identification of sustainability frameworks that are relevant to the analysis, followed by detailed analysis of the selected relevant frameworks in order to describe the sustainability criteria and indicators used. In reaction to the concerns on the sustainability of biofuels and bioenergy production, governments and organisations around the world have initiated policy developments that aim to secure the sustainable production of biomass, biofuels and bioenergy taking into consideration both environmental and social sustainability criteria. Certification schemes are envisaged to play an important role in demonstrating compliance with such sustainability criteria. One of the first countries to have such an operational system is the UK, where the Renewable Transport Fuel Obligation requires biofuel suppliers to report on the sustainability and greenhouse gas performance of their biofuels. The Netherlands Programme Sustainable Biomass has been developed to gain experience in the production and certification of sustainable biomass in order to strengthen the framework towards sustainable biomass production, based on practical experiences.48 The programme contained a subsidy fund and a supporting programme operated from 2008 until 2013. The project portfolio included projects from the Global Sustainable Biomass tenders, the Sustainable Biomass Import tenders and relevant projects from the Daey Ouwens Fund. The programme clustered the knowledge from the biomass project portfolio and has filled the knowledge gaps with supplementary research.37 More recently, sustainability criteria for biofuels produced in EU have been developed in the Renewable Energy Directive (RED) 2009/28/EC.49 In addition, the European Standard EN 16214:2012 entitled ‘‘Sustainability criteria for the production of biofuels and bioliquids for energy applications – Principles, criteria, indicators and verifiers’’ specifies requirements relevant for the provision of evidence by economic operators that the production, cultivation and harvesting of biomass for biofuels and bioliquids production is in accordance with legal or other requirements. It defines procedures, criteria and indicators providing the required evidence for:  production of raw material in areas for nature protection purposes  harvesting of raw material from non-natural highly biodiverse grasslands  cultivation and harvesting on peatland

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In the bioenergy sector, the ISO 13065:2015 entitled ‘‘Sustainability criteria for bioenergy’’ specifies principles, criteria and indicators for the bioenergy supply chain to facilitate assessment of environmental, social and economic sustainability aspects. It is applicable to the whole supply chain, parts of a supply chain or a single process in the supply chain. Furthermore, it applies to all forms of bioenergy, irrespective of raw material, geographical location, technology or end use. ISO 13065:2015 does not establish thresholds or limits and does not describe specific bioenergy processes and production methods. Compliance with ISO 13065:2015 does not determine the sustainability of processes or products. Moreover, it is intended to facilitate comparability of various bioenergy processes or products and to facilitate comparability of bioenergy and other energy options. Concerning biobased products, the EN 16751:2016 ‘‘Bio-based products – sustainability criteria’’ has recently introduced horizontal sustainability criteria applicable to the biobased fraction of all biobased products, excluding food, feed and energy, covering all three pillars of sustainability.50 If the product is partly biobased, this European Standard can only be used for the biobased fraction since it does not address the non-biobased fraction of a product. This European Standard sets a framework to provide information on management of sustainability aspects and cannot be used to make claims that operations or products are sustainable since it does not establish thresholds or limits. This European Standard can be used either to provide sustainability information on biomass production or to provide sustainability information on the supply chain for the biobased fraction of the biobased product. The Roundtable on Sustainable Biofuels, a multi-stakeholders initiative of the UNEP in cooperation with the Ecole Polytechnique Federale de Lausanne, has developed a set of global sustainability standards for biofuels.51 Since 2011, the Principles and Criteria recommended by the Roundtable on Sustainable Biofuels are implemented through a third-party certification system including biofuels, biobased chemicals and bioplastics among others. Therefore, the name of this initiative has changed into Roundtable on Sustainable Biomaterials.40 In 2011 the Global Bioenergy Partnership conducted a report including 24 sustainability indicators for bioenergy.52 Methodology sheets were presented in this report with the intention to provide policy-makers and other stakeholders with a tool providing information on the development of national bioenergy policies and programmes, monitoring the impact of these policies and programmes, as well as interpreting and responding to the environmental, social and economic impacts of bioenergy production and use. Sustainable principles, criteria and indicators have also been introduced by The Roundtable for Responsible Soy Production,53 The International Sustainability and Carbon Certification54 and other initiatives. The review of international standards and global initiatives and frameworks revealed that techno-economic sustainability aspects for the production of biofuels, bioenergy, biomass and biobased products have not received significant attention and are not addressed sufficiently within the existing

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frameworks. Only very recently has economic sustainability been introduced in ISO 13065:2015 and EN 16751:2016 with the criteria of fair business practices and financial risk management. Yet, the procedures described focus mainly on business aspects as the economic sustainability is limited to efficient use of assorted company assets in order to prolong its profitable operation. Moreover, emphasis is given to fair business practices in order to combat fraudulent, deceptive or dishonest consumer or commercial business practices. As an overall conclusion, the techno-economic sustainability of the manufacturing process is not well addressed as it does not cover the evaluation of alternative feedstocks, the valorisation of waste and by-product streams and the recirculation of used biobased products.

Step 2: Literature Review on Techno-economic Sustainability Studies for the Production of Biofuels, Bioenergy, Biomass and Biobased Products The literature review focused mainly on the identification of relevant literaturecited studies on the processing stage leading to the production of bioenergy, biomass, biofuels and biobased products sectors with emphasis given on the principles, criteria and indicators used in each study to assess the technoeconomic and/or sustainability aspects of the processing stage. The studies focusing on the evaluation of upstream stages of the aforementioned supply chains were not taken into consideration. The studies that focused on the evaluation of the whole supply chain were included in the assessment. There is a wide range of literature-cited publications focusing on the economic viability of bioenergy production as well as biofuels and biomass production. The economic viability of the relevant value chains has been evaluated considering both microeconomic and macroeconomic sustainability55–57 as well as technical sustainability. In the case of microeconomic sustainability, emphasis is given on business profitability and the analysis performed is either product oriented (comparing different products) or process oriented (comparing different processes producing the same product or assessing the sustainability of a process and its improvements over time).58 Common profitability criteria and indicators that have been reported in all the aforementioned sectors are net present value (NPV), internal rate of return (IRR), production cost, investment cost and operating cost.44,59–80 Additional parameters considered payback period (PBP), gross profit and net profit, among others.46 Table 4.2 presents the techno-economic viability and profitability indicators used in the evaluated literature-cited publications. It is found that cost of production, elsewhere mentioned as total production cost or product costs, is the most cited techno-economic indicator among the studied sectors. In addition, some publications introduce alternative indicators such as development of GDP/GNI, inflation, income diversification, impacts from eco-friendly investments, cost/ benefit ratio, life cycle costing and minimum fuel selling price53,59–61 The macroeconomic indicators presented in the literature-cited publications are total value added in the economy45,47,62,63 as well as trade

102 Table 4.2

Chapter 4 Techno-economic viability and profitability indicators used in the bioenergy, biomass and biofuels sectors.

Indicators

Units

Principle – ECONOMIC PILLAR – Economic/ financial viability, cost efficiency, profitability Net present value

—

Internal rate of return/Expected rate of returnReturn of Investment

h

Cost of production/Total production cost/ Product costs:

h

Benefit per cost: total revenue to total production cost Payback period/Time of return of investment: the time required to recover the cost of investment Degree to which the applied technology and operational aspects are proven, flexibility to changes in demand and supply, product diversification Gross profit: the venture’s revenues minus the cost of production Net profit: level of profit taking into account taxes and depreciation over a period of years Investment costs – CAPEX/Investment cost per product unit: Funds used by a company to acquire, upgrade, and maintain physical assets such as property, buildings, an industrial plant, technology or equipment (www.investopedia.com) Operational costs – OPEX: Operating expenses represent the other day-to-day expenses necessary to keep the business running. These are short-term costs and are used up in the same accounting period in which they were purchased (www.investopedia.com) Minimum selling price: Relevant costing as a standalone refers to analysing the cost of a business decision based only on the expenses that are relevant in the present time. The minimum pricing is essentially the break even point for that given sale. Any pricing above the absolute minimum results in profits Value added/Total value added to the economy – annual basis: The total value added to the local economy is comprised of the following values; labour income plus taxed profit at an annual basis per bioenergy plant

h

Sectors applied Bioenergy Biomass Biofuels Bioenergy Biofuels Biomass Bioenergy Biofuels Biomass Bioenergy Biofuels Biomass Biomass

References 44, 47–50, 55, 63, 90, 91 44, 48–53 44, 48, 52–56 50, 55, 92–101 78, 83

time

Bioenergy 44, 48, 102 Biomass

—

Bioenergy 44, 45, 48–50, 103

h/year

Bioenergy 45

Bioenergy 45, 63 Biomass h/product Bioenergy 45, 57, 58, unit Biomass 104 h/year

h/product Biomass unit

57, 58

h

Biofuels

58

h

Bioenergy, 45,47,62,63 biomass

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balances, foreign investments, changes in overall productivity, business opportunities, long-term profitability, energy diversity, product durability, and research and development efforts.44,46,61 The evaluation of technical process sustainability focus on aspects such as technological maturity, degree to which the applied technology and operational aspects are proven, flexibility to changes in demand and supply, continuity and predictability of performance, and potential power generation among others.44,45

Step 3: Identification of Gaps on Techno-economic & Sustainability Indicators The evaluation of literature-cited publications showed that the vast majority of the published studies focus on the upstream stage alone or the whole supply chain. In addition, most of the evaluated studies focus mainly on techno-economic aspects missing to address sustainability aspects of the processing stage leading to the production of biobased products. Important gaps in the methodology employed to assess the profitability of biobased products is that the currently employed criteria and indicators reflect the linear utilisation and processing of resources neglecting to address significant aspects of circular economy principles,64–66,81 such as valorisation of waste and by-products and recirculation of used biobased products from the alternative EoL stages into the manufacturing stage. Linear value chains do not exploit recirculation of used products, which should be evaluated when circular economy principles are applied. Furthermore, the effect of alternative feedstock selection and processing, including the potential for biorefinery development, is not addressed in current methodologies. It is widely accepted that cascading principles should be applied in the circular economy era.65,82 Furthermore, the effective exploitation of unavoidable organic wastes is imperative in order to minimise the environmental burden caused by their current management practices and at the same time provide an important renewable feedstock for the production of biobased products. Conventional processes for the production of biobased chemicals and polymers mainly rely on either direct utilisation of agricultural crops or end products and co-products utilisation from the primary processing industry (e.g. sugar and molasses production from sugar beet processing, glucose syrup from corn refining).67 Valorisation of waste and by-product streams as well as recirculation of used biobased products will facilitate the transition to the bioeconomy era68 enhancing also socio-economic growth with environmental benefits and technological advances in the biobased production sector.65,70,71 External economic and technical risk aspects related to the processing stage for the production of biobased products and the degree they may influence the economic feasibility of process implementation have not been adequately addressed. Such risks are related to feedstock availability, infrastructure, technological maturity, market alternatives and uncertainties involved in cost estimation.83,84

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In most cases, the incorporation of external social and environmental impact costs to the techno-economic production cost has not been taken into consideration. This means that the production of biobased products would, in most cases, not be cost-competitive with conventional counterparts derived from fossil raw materials. The term ‘‘environmental prices’’ addresses the welfare expenditure that is associated with the release of 1 kg of any pollutant to the environment. Thus, it is necessary to account for externally attributed environmental costs in order to compare the production of biobased products with their commercial counterpart considering both the production cost and the cost associated to environmental impacts. Many of the world’s most challenging environmental externalities are broadly spread, inflicting costs in terms of lost biodiversity and damaged ecosystems, depletion of terrestrial and marine species, and emissions that harm human health and generate climate change. Some are truly global, such as greenhouse gas emissions. Most of the profound tools for estimating external costs have been developed for the energy and transportation sectors. Some of these models observed most frequently in the literature are the ExternE,85 which refer to the energy sector and are an approach of calculating environmental external costs, as well as the Tellus model,86 the EPS 2000 model,87 and the ECON model.88 Average values of environmental prices are provided for the EU28 considering monetary values for emissions of different pollutants, environmental themes (e.g. climate change) and impacts of environmental pollution (e.g. damage to human health).89

Step 4: Development of Principles, Criteria and Indicators for Techno-economic Sustainability Assessment of the Processing Stage The set of criteria that have been used for the selection of the list of technoeconomic sustainability indicators are the following (in decreasing importance):  Completeness: through the participatory process, completeness requires that all the relevant parameters are captured  Operationality: the set of indicators should be measured on an appropriate scale, while ensuring both data and information availability  Non-redundancy: within each category group, sustainability indicators should not measure the same variable/parameter  Homogeneity: within each category group, an agreement about the set of indicators to be used can be reached  Address the gaps identified in the current methodologies and literaturecited publications on techno-economic evaluation of relevant processes

4.3.2

System Boundaries

The system boundaries considered in the techno-economic sustainability assessment of the conversion stage in the value chain for the production of biobased products included mainly the manufacturing and downstream

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stages. These stages include refining of crude biomass resources, chemical or biochemical conversion into chemical intermediates, separation and purification of chemical intermediate, polymerisation (if applicable in the production of biobased polymers) and end-product formulation.

4.3.3

Scope of the Techno-economic & Sustainability Assessment

The scope of the techno-economic sustainability assessment of the conversion stage is to evaluate both process profitability and efficiency and how these could be improved within a specific time frame. The techno-economic evaluation of a current process and its potential improvement could be evaluated using similar indicators among the next four cases: – Technological improvements: The implementation of novel processing advances leading to more efficient production of biobased products in the existing processing line. – Feedstock selection (the case of biorefinery development): Alternative feedstocks should be evaluated in order to select the one that leads to the most profitable and sustainable process for the production of a specific biobased product. The type of feedstock, the potential refining technologies for the production of value-added co-products, its regional availability and the technology used to convert the feedstock into the final biobased product should be also addressed. – Valorisation of wastes and by-product stream: Conventional value chains lead to the production of various side stream with no or low economic benefit. Valorisation of by-product or waste streams should be considered in order to improve process profitability and provide new market alternatives. – Recirculation of used biobased products: In the circular economy era, sustainable production of biobased products will be combined with recirculation of used biobased products via case-specific EoL scenarios. Material, chemical and energy recycling should be evaluated in order to assess profitability and techno-economic sustainability improvement as compared to current processing schemes.

4.3.4

TESA Principle, Criteria & Indicators

Based on the literature review presented above and the identified gaps, the following techno-economic principle, criteria and indicators are proposed for the evaluation of TESA. The methodology presented below should be applied in two stages: – Stage 1: Report the techno-economic data of an implemented process leading to the production of a specific biobased product from a specific feedstock. An appropriate reference product should be used for comparison purposes.

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– Stage 2: Assess the techno-economic sustainability of alternative nonimplemented processes producing the same biobased product using the same or alternative feedstocks. A sensitivity and systems engineering analysis should be carried out to evaluate the improvements that could be achieved via alternative feedstocks or processes. This approach will facilitate the transition to the circular (bio)economy era. A distinction should be made between drop-in and functional biobased products using specific or multiple feedstocks. In the first case, the reference product will be the petrochemical product, while in the second case the reference product could be the conventional biobased product. The appropriate reference product should be used for comparison purposes. It is important to note that the economic operator will select the principle, criteria and indicators for the evaluation of the techno-economic improvement achieved for the production of a specific biobased product using mainly the metrics presented in indicators 1.1, 1.2 and 1.3. Furthermore, the metrics are indicative and the economic operator should describe the reason why specific metrics have been selected. For example, if only process improvement should be evaluated then only criterion 1.1 and indicators 1.1, 1.2 and 1.3 should be used. If a biorefinery concept is compared against a conventional single-product process, then only criterion 2 should be used.

Principle 1: Sustainable Manufacturing – Techno-economically Sound Manufacturing This principle is proposed to assess the techno-economic viability and profitability of a current process or a processing route under evaluation. External environmental costs should be also taken into consideration. Special emphasis is given on the assessment of process improvement, biorefinery development, side stream valorisation and risk analysis on the techno-economic efficiency, process profitability and sustainability of the process under evaluation. A reference product should be used. Criterion 1: Techno-economic Efficiency and Process Profitability Based on Process Improvements Indicator 1.1. Describe techno-economic data for the production of the biobased product based on the current process. Indicative metrics are:  Fixed Capital Investment per kg product for the specific plant capacity  Cost of Manufacture per kg product for the specific plant capacity  Discounted Payback Period or Return on Investment Indicator 1.2. Perform a TEA to evaluate the production of the same biobased product via process improvements using the same feedstock as the current process. The methodology of TEA should be based on sensitivity analysis taking into consideration the variability caused by the most

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influential process and market parameters (e.g. conversion yield, energy integration etc.). A reference product should be also considered. Indicative metrics are the following:  Variation of Fixed Capital Investment at different plant capacities  Variation of Cost of Manufacture at different plant capacities  Discounted Cash Flow Analysis for the estimation of the Minimum Selling Price (associated with zero NPV at the end of the useful lifetime of plant operation) or the estimation of the selling price to achieve the same Discounted Payback Period reported in Indicator 1.1  Optimum Plant Capacity leading to minimum Cost of Manufacture  Variation of Minimum Feedstock Capacity Requirement that corresponds to zero NPV at the end of the useful lifetime of plant operation or Feedstock Capacity Requirement that corresponds to currently achieved techno-economic metrics (e.g. discounted payback period). These metrics could be estimated at the optimum plant capacity  The ratio of Feedstock Capacity Requirement to Feedstock Availability in the region  Assessment of the incorporation of the external environmental costs (e.g. pollutant emissions, climate change) on the Cost of Manufacture using the most appropriate methodologies/models. As an example, Bijleveld et al.89 have reported environmental prices for various pollutants, environmental themes and environmental impacts for EU28  Estimate the Total Value Added (expressed as the value of sales less the cost of raw materials, utilities and services purchased) for the biobased product derived from either the current process or the improved processes Indicator 1.3. Risk Assessments – describe procedures taken to identify economic and technical risks related to feedstock supply, regional feedstock availability, infrastructure and application-technical aspects in the implemented process. A sensitivity analysis and systems engineering approach will be followed:  Describe the measures taken to address and limit the associated risks  Assess and document Risk Aspects to describe the effect of different variables Criterion 2: Techno-economic Efficiency and Process Profitability Based on the Utilisation of Alternative Crude Renewable Feedstock and Biorefinery Development Indicator 2.1. The economic operator shall provide information on the measures taken to increase uptake of crude biomass resources as feedstocks. Indicator 2.2. The economic operator shall perform a sensitivity analysis using the following indicative parameters:

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 The metrics presented in Indicator 1.2  Comparison with the respective metrics derived from the reference product and/or the current process producing the same biobased product (Indicator 1.1)  The Fraction of Revenue for Feedstock Functionality – the ratio of the monetary value of the biobased products (h of product sales per kg feedstock) to the unitary monetary value of the crude resource (h per kg feedstock) Indicator 2.3. Risk Assessments – describe procedures taken to identify economic and technical risks related to feedstock supply, regional feedstock availability, infrastructure and application-technical aspects in the implemented process. A sensitivity analysis and systems engineering approach will be followed:  Describe the measures taken to address and limit the associated risks  Assess and document Risk Aspects to describe the effect of different variables Criterion 3: Enhance Valorisation of By-product and Waste Streams Produced by the Current Process Indicator 3.1. The economic operator shall provide information on the measures taken to enhance the value added through the valorisation of by-product and waste streams produced by the current process. Indicator 3.2. Provide quantitative data demonstrating the value added to the current process through the valorisation of waste and by-product streams. This could be achieved by estimating the following metrics:  The metrics presented in Indicators 1.2  Comparison with the respective metrics derived from the current process (Indicator 1.1.1)  The monetary value (h) derived from the marketable products produced from 1 kg by-product streams to the monetary value (h) derived by selling 1 kg of by-product streams as animal feed or using this for energy generation Indicator 3.3. Risk Assessments – describe procedures taken to identify economic and technical risks related to feedstock supply, regional feedstock availability, infrastructure and application-technical aspects in the implemented process. A sensitivity analysis and systems engineering approach will be followed:  Describe the measures taken to address and limit the associated risks  Assess and document Risk Aspects to describe the effect of different variables

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Criterion 4: Enhance Techno-economic Efficiency and Process Profitability via Recirculation of Used Biobased Products in the Manufacturing Stage. Techno-economically sound recirculation of used biobased products from the EoL stage into the manufacturing stage requires the development of appropriate technologies and practices to allow optimal recirculation and reuse of used biobased products. This concept applies circular economy principles aiming to create added value towards the improvement of techno-economic efficiency and process profitability. Indicator 4.1. The economic operator shall provide information on the measures taken to increase uptake of recycled used biobased products in existing industrial plants through different means of recirculation (e.g. material or chemical recycling). Indicator 4.2. The efficiency of recirculation should be evaluated via the following metrics:  The metrics presented in Indicators 1.2 when recirculation is applied  Comparison with the respective metrics derived from the current process (Indicator 1.1) where recirculation is not applied  Economic Recircularity of biobased products defined as the monetary value of recirculated used biobased products plus the monetary value of raw materials used for the production of 1 kg biobased product divided by the monetary value of the raw materials required to produce 1 kg of the biobased product in the current process Indicator 4.3. Risk Assessments – describe procedures taken to identify economic and technical risks related to feedstock supply, regional feedstock availability, infrastructure and application-technical aspects in the implemented process. A sensitivity analysis and systems engineering approach will be followed:  Describe the measures taken to address and limit the associated risks  Assess and document Risk Aspects to describe the effect of different variables

4.4 Techno-economy Sustainability Analysis Methodology for Alternative EoL Options for Post-consumer Biobased Products 4.4.1

Methodology

The development of the techno-economic sustainability analysis (TESA) methodology for the post-consumer and post-industrial stage of biobased products has been based on three preliminary inventory analysis steps,

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followed by the development of techno-economic sustainability principles, criteria, and indicators. The aim of the TESA methodological framework is to ensure that optimal alternative EoL routes, allowing for their recirculation as valuable resources in line with the concept of the circular bioeconomy. The following steps describe the development and the validation of the methodology: Step 1: Analysis of policies, action plans and regulations concerning the sustainability aspects of the EoL routes as they are related to circular economy (CE) and bioeconomy The concept and the basic principles of the CE were analysed by focusing on the gaps related to the linkage between the CE concepts and sustainable development. One problem identified was that the CE focuses on EoL activities (i.e. reduce, reuse and recycle) directly related to economic prosperity and environmental quality, while the social impacts and enabling roles of key stakeholders (consumers and business models) are missing.105 Furthermore, while important components of the value chain such as recovery or recycling and consumption or use are presented as dominant features of the CE concept, key components such as manufacturing and distribution, are in most cases absent.89 The missing links in the CE and the gaps in between the value chains have been identified by stakeholders, organisations and scientists and reported in scientific publications and project reports and actions of various organisations. Political actions dealing with the EoL fragmentation issue include an initiative of the European Commission that has proposed new rules for waste management including more closely harmonised rules on the use of extended producer responsibility (EPR)106,107 and the similar momentum that has been built in the US for introduction of EPR for packaging.89,90 The need for regulation of the CE at European level has led to new concepts and strategies: the CE Action Plan108 the Circular Economy Package (CEP)90 and the Bioeconomy Strategy,109 by the European Commission and in a similar way the ‘Sustainable Materials Management’ (SMM) by EPA in US.110 Despite the regulations, the standards and certification schemes developed in support of the growth of both the biobased products market and the CE, a major gap still exists in incorporating the EoL routes and resource efficiency in the products design. This has led to the consideration of how the integrated design and engineering of biobased products, from the selection of alternative renewable resources to the selection of alternative processing routes can affect resources efficiency in addition to functionality. The integration of prioritised or targeted EoL routes into the (bio)-based products design has been recognised to be a crucial issue. The clarification of the goals of the Bioeconomy and the CE and the identification of the gaps and weaknesses related to the EoL stage, allowed for analysing the parameters that should be carefully evaluated in the framework of the TESA of alternative EoL options of biobased plastics.89

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Step 2: Analysis of the EoL options of biobased and conventional fossilbased post-consumer products focusing on the EU and USA statistics and the corresponding legislative developments for plastics The provisions of the regulatory framework gaps and weaknesses identified in the previous step, have been used as key drivers for developing the inventory of alternative EoL routes for biobased plastics. Statistical data, relevant standards and regulations, and scientific literature on the alternative End-of-Use recirculation routes of biobased plastics were among the main sources on which the EoL options have been identified.89 The EoL options inventory89 represents a prerequisite for the development of a sustainability methodological framework for the assessment of each EoL of post-industrial and post-consumer biobased products (plastics), providing the data needed for developing the sustainability criteria of the various alternative EoL options. The basic terminology used relevant to the alternative EoL routes of biobased products was defined in accordance with the CEP.90 The waste management hierarchy defined according to the EU and the US was followed for the consecutive prioritisation of the alternative EoL options: reuse, material recycling (mechanical and chemical) and organic recycling (industrial aerobic composting and anaerobic digestion).89 The option of a single dedicated EoL route incorporated into the design concerns specific biobased products (e.g. mulch films biodegradable in soil, chain saw oils etc.). Step 3: Analysis of techno-economic parameters pertaining to the sustainability of the alternative EoL options of biobased and conventional fossil-based products based on a literature review Based on an extended literature review, key points of the processes pertaining to the different EoL options were examined by stressing out the weaknesses and the strengths of each process as well as the critical factors that influence the sustainability performance and in relation to different materials.89 Furthermore, special attention and emphasis was given in the techno-economic factors such as technical feasibility related to the characteristics of the materials and the potential of being treated by the specific EoL option. Economic factors were identified that must be taken into consideration for each EoL option and that influence the sustainability performance from the stage of the entrance to the treatment facility, such as the availability of the specific post-consumer plastics to be treated, to the exit of the treatment facility where the economic evaluation of the output is considered. The possibility and the prerequisite of the recirculation of the recovered material through the value chain cycle was examined and highlighted as a major key factor influencing the sustainability of the different alternative EoL options. A literature review has been carried out to gather information for a wide range of biobased plastics as well as conventional ones to be used as reference materials for comparison purposes, depending on the cases analysed. The limiting factors for each EoL alternative option, the gaps and the trends were identified. The inventory analysis of techno-economic parameters pertaining to the sustainability of

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the alternative EoL options of biobased and conventional products allowed for further analysing the identified crucial parameters and determining the techno-economic sustainability principles, criteria and indicators of each EoL option in the next two TESA methodological steps. Step 3 was actually integrated with step 2 interactively in the performed inventory analysis89 and elements from both are combined in the next methodology steps. Step 4: A set of principles, criteria and indicators for techno-economic sustainability assessment of the alternative routes of the EoL stage has been proposed based on the outcomes of steps 1–3 and relevant scientific sources. Based on the techno-economical sustainability principles and the technical and economic analysis conducted in steps 1 through 3 to identify constraints, opportunities and particularities of the EoL options for biobased products, a set of criteria and associated indicators was developed to cover the possible techno-economic sustainability aspects of the EoL phase of these products. These criteria and indicators may be used as a toolkit by the interested party to respond to the particular scope of the TESA of alternative EoL routes for a particular biobased product. Step 5: The proposed EoL sustainability principles, criteria and indicators are assessed/evaluated using the selected case studies and the TESA methodology for EoL options will be refined and finalised (in progress). This step is intended to provide a validation and optimisation of the TESA criteria and indicators developed in step 4 through selected case studies. The TESA for the EoL of post-consumer and post-industrial biobased products is applied in two stages following the prioritised alternative EoL routes according to the hierarchy of the Circular Economy Package (CEP): reuse, material recovery (mechanical and chemical recycling), organic recycling (aerobic composting and anaerobic digestion) while energy recovery is a complementary route (i.e. not an independent option) applied only for non-recyclable non-biodegradable biobased products: Stage 1.1 – Materials recovery: Report the TESA data of an established materials recycling reference scenario process resulting in the production of recyclates or monomers from a specific post-consumer, post-industrial biobased product. An equivalent reference product should be used for comparison purposes. In the case of drop-in biobased products, the conventional fossil-based products will be selected as reference materials. In the case of biodegradable biobased products a conventional biobased product (equivalent in terms of applications and/or properties) should be used as reference material. Stage 1.2 – Organic recycling: Report the TESA data of an established organic recycling reference scenario process resulting in the production of compost and possibly biogas from a specific post-consumer, post-industrial nonrecyclable biobased product entering the facility together with biowaste. An equivalent reference conventional biodegradable product (biowaste) should be used for comparison purposes.

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Stage 2: The TESA analysis of new processes or products not yet commercialised (i.e. TESA analysis based on pilot-scale or experimental data and hypothetical scenarios) requires the use of a stochastic approach to account for the inherent uncertainty. In stage 2, the TESA indicators of such a system are represented by functions instead of deterministic values of a commercial application. Upon the progress of the developmental work the uncertainty decreases and the standard deviation of all the stochastic parameters decreases accordingly. The standard deviation is a measurement of the uncertainty.

4.4.2

TESA Criteria for Alternative EoL Options for Post-consumer/Post-industrial Biobased Products

Principle 2: Sustainable Alternative EoL Routes – Techno-economically sound EoL options This principle focuses on the assessment of alternative EoL options for a post-consumer or post-industrial product including technical processability, economic viability, combined environmental and techno-economic resources efficiency and impact on sustainability. The assessment should be compared against a reference product and depending on the scope of the analysis should also compare alternative EoL options. Criterion 2.1: Technical Feasibility for Material Recovery and Organic Recycling Based on Existing Processes and Possible Improvements Biodegradability. The nature and the intrinsic properties of the materials, particularly their biodegradability, is a determinant factor for the route they will be directed as well as for the treatment they will be subjected to at their EoL stage. For example, the post-consumer and post-industrial plastics that are recyclable but non-biodegradable, the so-called drop-ins, can be recycled through the existing recycling streams of their conventional counterparts in the case of mechanical and chemical recycling.111,112 In the case of biodegradable products, there are limitations that must be considered when these materials are to be treated by mechanical or chemical recycling.113 Furthermore, only the non-recyclable biobased post-consumer and post-industrial products that are biodegradable under industrial aerobic composting and/or anaerobic digestion conditions can be considered suitable for the organic recycling EoL option. Non-recyclable non-biodegradable biobased plastics should be routed to energy recovery in the form of SRF. Proposed indicator: Indicator 2.1.1. Main characteristics of the post-consumer and postindustrial product that distinguish the possible mechanical and chemical recycling or organic recycling routes and affect significantly the processability of the stream. Indicative qualitative metrics are:  Drop-ins  Biodegradability

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Sorting efficiency. The sorting process is a critical step for the material recovery as well as organic recycling EoL options. First of all, in the case of mechanical recycling biobased plastics may be collected separately into mono-streams and if the efficiency achieved is high, it may turn the mechanical recycling as the most attractive EoL option for the post-industrial and post-consumer biobased plastics.114 In the case of chemical recycling, separate collection of post-consumer biobased plastics, or biobased plastics of high purity sorted out from mixed plastics would allow for the chemical depolymerisation processes to be applied to pure raw materials and recover high added value monomers of high quality and price.115 Similarly, when aerobic composting is to be considered, the sorting efficiency of biobased compostable plastics from mixed plastics waste streams is a critical requirement for the smooth operation of the composting facilities. The role of sorting in the anaerobic digestion treatment option is crucial as well, as the feedstock for the anaerobic digestion (AD) should be of high quality, collected separately, or separated from the total volume of the wastes, in order to ensure stable operation of the digester.116 The following indicator is proposed: Indicator 2.1.2. Sorting efficiency of the collected post-consumer specific biobased plastic from different collection and sorting schemes. Indicative metrics are:  Separate collection  Food contact materials  Sorting efficiency Mechanical Recycling Processability. The technical feasibility of the mechanical recycling process depends on several factors. First of all, the possibility of severe thermal degradation during mechanical recycling is a key factor that must be considered. Thermal stability is a first prerequisite for any polymer, conventional or biobased, to be recyclable.117 Furthermore, the uniformity of the mono stream or the sorted post-consumer biobased plastic stream affects the processing efficiency or recyclability of the plastic waste. Thus, the presence of polymers not compatible with the main polymer processed and/or foreign materials result in contamination of the stream possibly introducing processing problems and degraded quality of the recyclate.118 Other physical limiting factors may determine the recyclability of specific biobased plastics, among them is the presence of contaminants in the plastic waste stream. The above considerations can be assessed with the proposed indicator: Indicator 2.1.3. Mechanical recyclability of the sorted post-consumer specific biobased products. Indicative metrics are:  Degradation of selected mechanical properties  Limiting physical characteristics

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 Presence of contaminants  Compatibility with other polymers Chemical Recycling Processability. Concerning chemical recycling, the technical feasibility of the process can be evaluated by the depolymerisation efficiency as measure. The efficiency in terms of conversion yield in high value-added monomers and/or chemicals recovered is crucial factor. A depolymerisation process that is not efficient cannot result in high recovery rates or high-quality monomers/chemicals. Such a process needs further improvement that can be achieved, for example, by both the design and production of innovative depolymerisation catalysts or the development of chemically recyclable polymers designed for this targeted EoL route.99 Proposed indicator: Indicator 2.1.4. Technical feasibility for the chemical recycling of the sorted post-consumer specific biobased products. Indicative metrics are:  Depolymerisation efficiency Compostability. The technical feasibility of organic recycling is connected with the conformity of biobased plastics to the compostability and/or biodegradability requirements defined by standard specifications published by several organisations, so as to be accepted for industrial composting and/or AD. The situation is more clear in the case of industrial composting compared to that of anaerobic digestion for which (although several standard test methods have been developed to determine the degree of biodegradation of plastics under anaerobic conditions representative of AD plants) the lack of standard specifications, represents a major barrier for its development.89 Proposed indicator: Indicator 2.1.5. Technical feasibility for the aerobic composting and anaerobic digestion of the sorted non-recyclable post-consumer specific biobased biodegradable products. Indicative metrics are:  Compliance with standards for compostability under industrial aerobic composting conditions  Compliance with standards for biodegradability under anaerobic digestion conditions Criterion 2.2: Economic Viability of Material Recovery and Organic Recycling Based on Existing Processes Infrastructures for Materials Recovery. The availability of mechanical recycling facilities in the region that accept biobased plastics, and/or the distance of available infrastructures, turns mechanical recycling into a first priority alternative EoL route for biobased products, or not.8 In the

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case of chemical recycling, the establishment of the feasibility of large scale operations in a way that chemical recycling becomes a valuable alternative recycling route in the near future should be supported by research and development activities as strongly recommended by stakeholders.119 Proposed indicator: Indicator 2.2.1. Availability of recycling facilities for mechanical and chemical recycling of post-consumer/post-industrial products. Indicative qualitative metrics:  Availability of mechanical and/or chemical recycling facilities Infrastructures for Organic Recycling. A basic prerequisite for considering organic recycling and/or anaerobic digestion as suitable EoL options for biobased products is the infrastructures availability. The availability of industrial composting facilities and AD facilities that accept biobased plastics in the region and/or the distance of available infrastructures, turn these options, or not, into attractive alternative EoL routes. Proposed indicator: Indicator 2.2.2. Availability of aerobic composting and anaerobic digestion facilities for the organic recycling of non-recyclable post-consumer/ post-industrial biodegradable products. Indicative qualitative metrics:  Availability of industrial aerobic composting and/or AD facilities Availability of Biobased Plastic Waste for Materials Recovery. One of the key factors for the economic viability of mechanical recycling and/or chemical recycling is the requirement that sufficient commercial mono stream biobased plastic quantities are available and their supply is constant to cover the investments required.120 Proposed indicator: Indicator 2.2.3. Availability of collected and sorted recyclable industrial/ post-consumer biobased products. Indicative metrics:  Availability of post-consumer biobased products Availability of Biobased Plastic Waste for Organic Recycling. A guaranteed long-term supply of biowaste feedstock, including biobased compostable plastics, is necessary before the establishment of an aerobic composting or AD plant. Especially for closed or contained composting systems, it is important that they operate near or at their maximum design capacity so as to be economically viable. Likewise, the organic feedstock inputs to AD facilities are required to be guaranteed. Proposed indicator:

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Indicator 2.2.4. Availability of collected and sorted non-recyclable post-industrial and post-consumer compostable biobased products along with biowaste feedstock. Indicative metrics:  Availability of post-consumer compostable biobased products and biowaste feedstock Recovered materials quality. It is crucial that the final products are characterised in terms of their quality. Several standards define the required general characteristics and some optional degradation characteristics of conventional plastic recyclates, applicable also to their biobased nonbiodegradable counterparts.121 No standards exist for biodegradable biobased plastic recyclates. In the case of chemical recycling, the nature of the feedstock defines the subsequent chemical recycling processes and finally the quality of the monomers/oligomers that is economically feasible to produce. Pure polymers streams result in high value products by chemical depolymerisation processes (original monomers recovery), while, thermochemical recycling processes, such as pyrolysis (thermal decomposition), end up in products characterised by low quality, as they consist of mixtures of various hydrocarbons.122 Proposed indicators: Indicator 2.2.5. Post-consumer and post-industrial recycled product quality characterisation. Indicative qualitative metrics:  Commercial recyclates quality characterisation  Second-generation commercial monomers/oligomers characterisation

quality

Organic recycling products quality. The quality of the final products of organic recycling (namely compost, digestate and biogas respectively), has a strong impact on the economic viability of the relevant EoL treatments. Meeting the requirements of the relevant specifications is a critical issue for the marketing of a final organic recycling product. For example, the European Fertiliser Regulation harmonised quality standards for the compost and AD products in the EU internal fertilisers market promote the competitiveness of the recycled organic fertilisers and soil improvers.123–125 In the case of AD the production and quality of biogas generated should meet the relevant specifications (e.g. ISO 20675:2018).126 Proposed indicators: Indicator 2.2.6. Compost quality from aerobic composting and AD of non-recyclable post-consumer and post-industrial biodegradable biobased products and biowaste. Indicative qualitative metrics:  Compost produced from industrial aerobic composting and AD from biowaste together with biodegradable biobased product meets the relevant specifications of the European Fertiliser Regulation

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 Biogas produced from AD of biodegradable biobased product meets the relevant specifications for quality of biogas Market of Recovered Biobased Materials. The market price for a specific quality of biobased recyclates is a crucial factor of the economic viability of mechanical recycling. Mechanical recycling may be feasible but not economically viable if the prices obtained do not support its operation as a first priority option for EoL of biobased products.104 The market price for a specific quality of second-generation biobased monomers or oligomers is a crucial factor of the economic viability of chemical recycling. Proposed indicators: Indicator 2.2.7. Market value of post-consumer and post-industrial recycled products. Indicative metrics are:  Relative value of biobased recyclates and biobased monomers and oligomers Market of Final Products of Organic Recycling. Ensuring successful industrial composting and/or AD plant development and operation with strong impact on the economic viability of the organic recycling of non-recyclable biobased plastics along with biowaste, requires availability of markets for the end products. There is a trend in several Member States to shift from composting to AD or to combined AD and composting treatments because the municipalities are able to negotiate lower gate fees to biowaste operators thanks to increased competition in the biowaste treatment sector and the lower price for digestate. As result, biowaste operators are forced to generate revenue through other options, such as the sale of electricity from biogas production.127 Proposed indicators: Indicator 2.2.8. Market of non-recyclable post-consumer and postindustrial biodegradable biobased products. Indicative metrics:  Value of compost from industrial aerobic composting or AD of biowaste and biobased biodegradable products  Value of biogas from AD of biowaste and biobased biodegradable products Estimated Financial Feasibility. The financial feasibility of the EoL options is based on the economic data and can be described in terms of the profitability of the processes. It is noteworthy, that for all EoL alternatives, the existence of relevant data is very limited for biobased post-consumer/postindustrial products. An extrapolation can be made from available data for conventional plastics, in the case of mechanical recycling. No data are available for chemical recycling even for conventional plastics as these processes have not been commercialised yet. For organic recycling the financial data available for composting and AD of biowaste are also directly

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applicable for biobased products except for the gate fee. Proposed indicators to describe the profitability of the processes: Indicator 2.2.9. Estimated financial feasibility of mechanical recycling, chemical recycling and organic recycling of post-consumer and postindustrial biobased products. Indicative metrics:  Return on Investment (ROI)  Net Present Value (NPV) Criterion 2.3: Common environmental and techno-economic criteria of material recovery and organic recycling Material Mass Recovery Efficiency. The higher the recyclate mass or the higher the mass of pure monomer or oligomer or chemicals produced from the initial mass of the sorted post-consumer plastic entering the mechanical or chemical recycling facility, respectively, is, the higher the material recovery and recirculation potential is achieved.128 Proposed indicators: Indicator 2.3.1. Mass recovery efficiency through the mechanical and chemical recycling. Indicative metrics:  Recyclate or monomer or oligomer or chemical mass recovery efficiency Organic Mass and Biogas Recovery Efficiency. The percentage of the compostable biobased plastics actually composted and/or the percentage of anaerobically digestible biobased plastics converted into biomass is small. The biogas obtained describes the efficiency of recovery of the sorted postconsumer biodegradable biobased plastic mass entering the AD facilities together with biowaste. Proposed indicators: Indicator 2.3.2. Biogas mass recovery efficiency under AD conditions The Additives Impact on Sustainability Of Materials Recovery. The nature and efficiency of additives and of reagents used for the manufacturing and the reprocessing of the biobased plastics, and in chemical recycling, respectively, affect the overall sustainability of materials recovery. Some additives used in plastics manufacturing are degraded during use and so the post-consumer plastics may have a different additives synthesis from the original material.129,130 The efficiency and nature of the additives used with reprocessing may have an additional impact on the techno-economic and environmental impact sustainability of mechanical recycling. Using environmentally benign and efficient reagents would also contribute to the environmental and techno-economic sustainability of the chemical recycling process. Proposed indicators:

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Indicator 2.3.3. Impact of additives and reagents used with mechanical and chemical recycling of post-consumer and post-industrial products on sustainability. Indicative metrics:  Nature and impact of additives used during manufacturing  Nature and impact of additives used with mechanical recycling  Nature, and impact of reagents used with depolymerisation The Additives Impact on Sustainability of Organic Recycling. The efficiency and nature of the additives used in both the composting process and the AD, with emphasis placed on the use of environmentally benign additives that are natural substances or compostable/digestible biobased compounds may affect the techno-economic and environmental sustainability of the process.131,132 Proposed indicators: Indicator 2.3.4. Impact of the additives and reagents used with aerobic composting and AD of non-recyclable post-consumer/post-industrial biodegradable biobased products on sustainability. Indicative metrics:  Nature and impact of additives used with biobased products under aerobic industrial composting and AD conditions Resources Utilisation Efficiency. The overall environmental and economic sustainability of the alternative materials recovery and recycling processes is affected significantly by the efficiency of the used for the processes and their renewability and/or recirculation. ergy used may be derived from renewable and/or conventional while the water used may partially come from a closed recycling the waste water.133 Proposed indicators:

technoorganic utilities The ensources loop of

Indicator 2.3.5. Utilisation efficiency of the resources used for the mechanical reprocessing, chemical depolymerisation and organic recycling of postconsumer/post-industrial products. Indicative metrics:    

Total water consumption efficiency Waste water recirculation Total energy consumption efficiency Renewable energy use/total energy consumption

Waste – Emissions Impact on Sustainability of Materials Recovery. The wastes and the air emissions produced during the mechanical and/or chemical recycling processes have important impacts on their techno-economic and environmental sustainability. Waste streams in mechanical and chemical recycling usually include solid waste and air, possibly harmful, emissions and also waste water mainly in the case of mechanical recycling.134,135 Proposed indicators:

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Indicator 2.3.6. Impact of the waste – emissions associated with the mechanical reprocessing and chemical depolymerisation of post-consumer/post-industrial products on sustainability. Indicative metrics:  Hazardous VOCs emitted  Hazardous non-volatile compounds released to the environment  LCA related emissions Waste – Emissions Impact on Sustainability of Organic Recycling. Waste streams generated from aerobic composting, such as leachate, residuals, odous, air emissions and in AD anaerobic digestion effluents (ADEs) may have important techno-economic and environmental sustainability impact. Proposed indicators: Indicator 2.3.7. Impact of the waste – emissions associated with the aerobic composting and AD of non-recyclable post-consumer and post-industrial biodegradable biobased products on sustainability. Indicative metrics:  Specific gas emissions  Residuals, solid waste  Leachate or anaerobic digestion effluents

Principle 3: Techno-economically Sound Recirculation Potential of Recycled Post-consumer and Post-industrial Biobased Products Through Alternative EoL Routes Techno-economically sound recirculation of mechanically and chemically recycled post-consumer and post-industrial biobased products back into the plastic conversion manufacturing of end products and the polymer processing stages, respectively, depends on the recirculation potential of the specific biobased products (described below) and also on the manufacturing technoeconomic recirculation processing efficiency (described in Principle 2). Recirculation of non-recyclable biodegradable biobased products may be achieved through the use of compost as organic fertiliser for biomass (resources) production, replacing chemical fertilisers. The possibility of the recycled post-consumer and post-industrial biobased products to recirculate from the stage of the EoU/EoL back into the manufacturing and processing stages or even to the initial parts of the value chains comprises the recirculation potential that in general integrates criteria related to the EoL stage described in Principle 3. The reason that the recirculation potential is presented as an additional separate techno-economic sustainability principle (3), even though it contains elements of the techno-economic sustainability criteria of the alternative EoL options (principle 2), is the identification of a gap between product design, materials supply, marketing and manufacturing, on one hand, and the return flow of recycled and recovered materials, on the other hand. This fragmentation has been recognised as a major missing link in the

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circular economy. In an effort to integrate the fragmented cycle and allow for the circular economy to develop, new rules have been proposed by the European Commission including ‘‘more closely harmonised rules on the use of extended producer responsibility (EPR)’’.90 The inclusion of the specific principle 3 on recirculation of the recycled and recovered materials along with associated techno-economic criteria and indicators aims at ensuring the restoration of the fragmented connection between the EoL stage and the produced secondary materials with the biobased products value chains. Material characteristics, standards and traceability schemes can play a significant role in this direction. Criterion 3.1: Recirculation Potential of Mechanically and Chemically Recycled Post-consumer and Post-industrial Biobased Products Recirculation Potential of Recovered Materials. The physical and chemical characteristics of specific post-consumer and post-industrial products have strong impacts on their recirculation potential. In mechanical recycling, the maximum number of reprocessing cycles before the material becomes non-recyclable depends on the specific material and the reprocessing conditions. The deterioration (degradation) of the properties of a biobased or conventional polymer in most cases is gradual, analogous to the reprocessing cycles and characteristic for the specific product.136 In chemical recycling the recirculation potential through the recovery of monomers or oligomers depends on the characteristics of the specific product (e.g. biobased composites, industrial off grade PLA and medical grade PLA resins, PET or Bio-PET).137–139 Proposed indicators: Indicator 3.1.1. Maximum number of possible mechanical reprocessing cycles of the post-consumer/post-industrial product. Indicative metrics:  Number of reprocessing cycles Indicator 3.1.2. Recirculation potential of specific post-consumer/post-industrial products through mechanical and chemical recycling reprocessing. Indicative qualitative metrics:  Mechanical and Chemical recirculation potential for specific biobased products Characterisation of Reprocessed Materials. The mechanically reprocessed and chemically depolymerised post-consumer and post-industrial products are characterised according to standards for their quality and their potential to close the loop of the recirculation back to their useful life cycle stages. The establishment of relevant standards is an issue of essential importance, as the European plastics recycling industry lacks uniform standards and certification schemes which would strengthen the secondary raw materials market. Consumers hardly rely on constant supplies of high-quality products, due to the differentiation of quantities and qualities of reprocessed

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materials because of the standards variation. Moreover, chemical recycling needs to be conceptualised in the legislation so that the produced material’s quality and recirculation potential are clearly defined as well as distinguished from energy recovery.141 Proposed indicators: Indicator 3.1.3. Characterisation of mechanically reprocessed and chemically depolymerised post-consumer and post-industrial products according to relevant standards. Indicative qualitative metrics:  Characterisation of mechanically reprocessed material  Relative purity of recovered monomers or oligomers Traceability Schemes of Secondary Market. Traceability schemes may be required by legislation, international standards or end users in order to allow better product control or to locate and withdraw unwanted material and/or defective products from the secondary market.142 Such schemes enhance the confidence between the producers and end users as far as the use of the reprocessed or recovered materials are concerned, ensuring their recirculation potential back to the useful life cycle stage. Proposed indicators: Indicator 3.1.4. Is the mechanically reprocessed and chemically depolymerised post-consumer and post-industrial product recorded by means of a traceability scheme? Indicative qualitative metrics:  Traceability of mechanically reprocessed material and recovered monomers or oligomers Criterion 3.2: Recirculation potential of organically recycled post-consumer and post-industrial biodegradable biobased products Recirculation Potential of Compost. The final compost product, from the organic recycling of non-recyclable post-consumer and post-industrial biodegradable biobased products, may be characterised and used as organic fertiliser, or soil improvement compound. The compost enhances the biomass production and CO2 absorption, replacing the corresponding chemical fertilisers. Proposed indicators: Indicator 3.2.1. Recirculation potential of the compost produced through organic recycling of non-recyclable post-consumer and post-industrial biodegradable biobased products. Indicative metrics are:  Compost potential as organic fertiliser

Acknowledgements This work was funded by STAR-ProBio project, European Union’s Horizon 2020 research and innovation programme: Grant Agreement Number 727740. http://www.star-probio.eu/.

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84. C. L. Gargalo, A. Carvalho, K. V. Gernaey and G. Sin, A framework for techno-economic & environmental sustainability analysis by risk assessment for conceptual process evaluation, Biochem. Eng. J., 2016, 116, 146. 85. ExternE, Externalities of Energy Methodology, European Commission, ETSU, Metroeconomica, UK, vol. 2, 1995. 86. Tellus Packaging Study, 2019 https://p2infohouse.org/ref/01/00047/710.htm. 87. J. Jantzen and R. Pesˇic, Assessment of the economic value of environmental degradation in Serbia, Final report, 2004. 88. Environmental Priority Strategies (EPS), IVL, 2017. https://www.ivl.se/ english/startpage/pages/our-focus-areas/environmental-engineering-andsustainable-production/lca/eps.html. 89. S. B. M. Bijleveld, L. Graaff, E. Schep, A. Schroten, R. Vergeer, and S. Ahdour, Environmental Prices Handbook EU28 Version – Methods and Numbers for Valuation of Environmental Impacts, Publication code: 18.7N54.125, CE Delft, Delft, 2018. 90. M. A. F. D. Moraes, A. M. Nassar, P. Moura, R. L. V. Leal and L. A. B. Cortez, Jet biofuels in Brazil: Sustainability challenges, Renew. Sustain. Energy Rev., 2014, 40, 716. 91. J. C. Sacramento-Rivero, F. Navarro-Pineda and L. E. Vilchiz-Bravo, Evaluating the sustainability of biorefineries at the conceptual design stage, Chem. Eng. Res. Des., 2016, 107, 167. 92. O. Arodudu, K. Helming, H. Wiggering and A. Voinov, Towards a more holistic sustainability assessment framework for agro-bioenergy systems — A review, Environmental Impact Assessment Review, 2017, 62, 61. 93. J. M. Pinazo, M. E. Domine, V. Parvulescu and F. Petru, Sustainability metrics for succinic acid production: A comparison between biomassbased and petrochemical routes, Catal. Today, 2015, 239, 17. 94. S. Safarian and R. Unnthorsson, An assessment of the sustainability of lignocellulosic bioethanol production from wastes in Iceland, Energies, 2018, 11(6), 1493. 95. J. R. Ziolkowska, Evaluating sustainability of biofuels feedstocks: A multi-objective framework for supporting decision making, Biomass Bioenergy, 2013, 59, 425. 96. F. Delrue, et al., An economic, sustainability, and energetic model of biodiesel production from microalgae, Bioresour. Technol., 2012, 111, 191. ´, 97. E. E. Silva Lora, J. C. Escobar Palacio, M. H. Rocha, M. L. Grillo Reno O. J. Venturini and O. A. del Olmo, Issues to consider, existing tools and constraints in biofuels sustainability assessments, Energy, 2011, 36(4), 2097. 98. A. Caldeira-Pires, S. M. da Luz, S. Palma-Rojas, T. Rodrigues, V. C. Silverio, F. Vilela, P. Barbosa, A. M. Alves and A. CaldeiraPires, et al., Sustainability of the biorefinery industry for fuel production, Energies, 2013, 6(1), 329.

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99. J. M. Pinazo, M. E. Domine, V. Parvulescu and F. Petru, Sustainability metrics for succinic acid production: A comparison between biomassbased and petrochemical routes, Catal. Today, 2015, 239, 17. 100. F. Delrue, P.-A. Setier, C. Sahut, L. Cournac, A. Roubaud, G. Peltier and A.-K. Fromenta, An economic, sustainability, and energetic model of biodiesel production from microalgae, Bioresour. Technol, 2012, 111, 191. 101. S2BIOM, Consistent Cross-Sectoral Sustainability Criteria & Indicators, Iinas, 2015. ´jo, J. Luiz de Medeiros, L. Yokoyama and 102. O. de Queiroz Fernandes Arau ´rio Vaz Morgado, Metrics for sustainability analysis of postC. do Rosa combustion abatement of CO2 emissions: Microalgae mediated routes and CCS (carbon capture and storage), Energy, 2015, 92, 556. ¨htinen, T. Myllyviita, P. Leskinen and S. K. Pitka ¨nen, A systematic 103. K. La literature review on indicators to assess local sustainability of forest energy production, Renew. Sustain. Energy Rev., 2014, 40, 1202. 104. L. B. Oliveira, M. S. M. de Araujo, L. P. Rosa, M. Barata and E. L. La Rovere, Analysis of the sustainability of using wastes in the Brazilian power industry, Renew. Sustain. Energy Rev., 2008, 12(3), 883. 105. D. Briassoulis, A. Pikasi and M. Hiskakis, End-of-waste life: Inventory of alternative end-of use recirculation routes of bio-based plastics in the European Union context, Crit. Rev. Environ. Sci. Technol., 2019, 1–58. 106. A European Strategy for Plastics in a Circular Economy, Communication from the Commission to the EP&C, the European Economic and Social Committee and the Committee of the Regions Brussels, COM(2018) 28 final, 2018. 107. Directive (EU) 2018/851 of the EP&C Amending Directive 2008/98/EC on waste, European Parliament and Council, OJ L 150, 2018. 108. Closing the loop – An EU action plan for the Circular Economy, Communication from the Commission to the EP&C, the European Economic and Social Committee and the Committee of the Regions, COM/2015/0614 final, 2015. 109. A sustainable Bioeconomy for Europe, strengthening the connection between economy, society and the environment-Updated Bioeconomy Strategy, Directorate-General for Research and Innovation, European Union, 2018. ISBN 978-92-79-94145-0. 110. Sustainable Materials Management Program Strategic Plan, Fiscal Year 2017–2022, EPA, 2015. 111. European Bioplastics, Frequently Asked Questions On Bioplastics, 2017. 112. Biobased Plastics in a Circular Economy, Policy suggestions for biobased and biobased biodegradable plastics, Report, Delft, CE Delft, 2017. 113. Lepitreb, Separate Recycling Streams for Biodegradable Plastics – A hot waste legislation topic in Europe, Bioplastics News, 2017, https:// bioplasticsnews.com/bioplastics/.

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114. Plastics Recyclers Europe, Study on an increased mechanical recycling target for plastics, Final Report, 2013. 115. J. M. Garcıa, Catalyst: Design Challenges for the Future of Plastics Recycling, Chem, 2016, 1, 813. ¨m and H. Kang, Source Separation of 116. T. Al Seadi, N. Owen, H. Hellstro MSW, International Energy Agency (IEA), IEA Bioenergy, Technical Brochure, 2013, ISBN 978-1-910154-01-4. 117. S. M. Al-Salem, P. Lettieri and J. Baeyens, Recycling and recovery routes of plastic solid waste (PSW): A review, Waste Manage., 2009, 29, 2625. 118. N. Singh, D. Hui, R. Singh, I. P. S. Ahuja, L. Feo and F. Fraternali, Recycling of plastic solid waste: A state of art review and future applications, Composites 2017, Part B 115, 409. 119. European Bioplastics e.V., Recycling And Recovery: End-of-Life Options for Bioplastics, Position of European Bioplastics, 2017. 120. M. van den Oever, K. Molenveld, M. van der Zee and H. Bos, Bio-based and biodegradable plastics – Facts and Figures, Wageningen Food and Biobased Research, Report. 121. EN 15347:2007, Plastics, Recycled Plastics. Characterization of plastics waste, CEN, 2007. 122. T. T. Sharobem, Tertiary Recycling of Waste Plastics: An Assessment of Pyrolysis by Microwave Radiation, Columbia University, 2010. 123. EurProposal for a Regulation on the making available on the market of CE marked fertilising products and amending Regulations (EC) No 1069/2009 and (EC) No 1107/2009, Brussels, COM(2016) 157 final 2016/ 0084 (COD), 2016. 124. European Bioplastics, Position of European Bioplastics concerning Fertilizer Regulation: Biodegradable Mulch Film, 2016, http://ec. europa.eu/transparency/regdoc/?fuseaction=feedbackattachment&fb_ id=72FDC5F4-0A1D-B942-A363D85479EE9DEF. 125. IFOAM EU: New European Fertiliser Regulation by 2022; 2018; last accessed 10/7/2019, https://www.ifoam-eu.org/en/news/2018/11/21/ new-european-fertiliser-regulation-2022. 126. ISO 20675:2018, Biogas—Biogas Production, Conditioning, Upgrading and Utilization—Terms, Definitions and Classification Scheme, International Organization for Standardization, 2018. 127. JRC European Commission, Technical report for End-of-waste criteria on Biodegradable waste subject to biological treatment, Third Working Document, Seville, Spain, 2012. 128. European Commission DG ENV, Plastic Waste In The Environment, Revised final report, 2011. 129. J. N. Hahladakis, C. A. Velis, R. Weber, E. Iacovidou and P. Purnell, An overview of chemical additives present in plastics: Migration, release, fate and environmental impact during their use, disposal and recycling, J. Hazard. Mater., 2018, 344, 179. 130. S. V. Sankar and S. A. Kumar, Chapter 2.2. Recent trends and future of polymer additives in macromolecular recycling technology: a brief

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overview, in Recycling of Polymers: Methods, Characterization and Applications, ed. R. Francis, John Wiley & Sons, USA, ch. 2, 2016. J. Gabhane, S. P. William, R. Bidyadhar, P. Bhilawe, D. Anand, A. N. Vaidya and S. R. Wate, Additives aided composting of green waste: Effects on organic matter degradation, compost maturity, and quality of the finished compost, Bioresour. Technol., 2012, 114, 382. ´lez, M. E. Sa ´nchez and X. Go ´mez, Enhancing Anaerobic J. Gonza Digestion: The Effect of Carbon Conductive Materials, J. Carbon Res., 2018, 4, 59. J. Nakatani and M. Hirao, Multicriteria Design of Plastic Recycling Based on Quality Information and Environmental Impacts, J. Ind. Ecol., 2011, 15(2), 228–244. Q. Xiang, S. Mitra, M. Xanthos and S. K. Dey, Evolution and Kinetics of Volatile Organic Compounds Generated during Low-Temperature Polymer Degradation, J. Air Waste Manage. Assoc., 2002, 52, 95. ˜o, J. A. Conesa, J. Molto ´ and R. Font, Emissions from the N. Ortun pyrolysis and combustion of different wastes, 7th International Symposium on Feedstock Recycling of Polymeric Materials (7th ISFR 2013), New Delhi, India, 2013. B. Luijsterburg and H. Goossens, Assessment of plastic packaging waste: material origin, methods, properties, Resour. Conserv. Recycl., 2014, 85, 88. ¨rquist, Separation for regeneration – Chemical recycling of cotton S. Bjo and polyester textiles, MSc Theses, The Swedish School of Textiles, 2017. B. Anneaux, J. Campanelli and E. Foley, A Novel Method for Chemical Recycling of PLA Under Mild Conditions, White Paper, Zeus Industrial Products, Inc., Orangeburg, SC, www.zeusinc.com, 2018. DEMETO project, Modular, Scalable and High-Performance Depolymerization by Microwave Technology, Horizon 2020 grant no. 768573, 2017. https://www.demeto.eu/. Plastic Recyclers Europe, Recyclers Certification, 2019, last accessed May 2019, https://www.plasticsrecyclers.eu/recyclers-certification. Plastics Recyclers Europe, Chemical recycling, 2019, last accessed May 2019 https://www.plasticsrecyclers.eu/chemical-recycling. British Standards Institution 2019, Environmental-Management-andSustainability, Recycling, 2019, last accessed May 2019, https://shop. bsigroup.com/Browse-By-Subject/Environmental-Management-andSustainability/Recycling/.

CHAPTER 5

Market Assessment L. LADU* AND S. WURSTER ¨t Berlin, Germany Technische Universita *Email: [email protected]

5.1 Introduction The beginning of the 21st century is shaped by the competition of different co-existing economic models: the still dominant fossil-based economy as well as the emerging biobased economy and the circular economy. The occurrence of biobased and circular economic concepts reflect the need for a paradigm shift towards sustainability.1 In the EU market, the bioeconomy is regarded as the region’s ‘‘response to key environmental challenges the world is facing’’.2 Central goals of the bioeconomy are ‘‘to reduce the dependence on natural resources, transform manufacturing, promote sustainable production of renewable resources from land, fisheries and aquaculture and their conversion into food, feed, fibre, biobased products and bio-energy, while growing new jobs and industries’’.2 Investigation into strategies to promote this paradigm shift has been limited. This chapter is specifically dedicated to the European market for biobased products, defined by CEN as products wholly or partly derived from biomass, such as plants, trees or animals.3 In November 2017, the BBP-EG (Biobased Product Expert Group) published its guiding principles and recommendations for the further development of the biobased products sector, including various research activities and measures to stimulate the transition towards biobased products.4 The report concludes with eight recommendations for policy reforms to stimulate the growth of the sector. A key item is related to the sustainability impact assessment of biobased products. More specifically, Green Chemistry Series No. 64 Transition Towards a Sustainable Biobased Economy Edited by Piergiuseppe Morone and James H. Clark r The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

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recommendation 4 is ‘‘Develop and implement robust methodologies, criteria, standards and certification schemes for assessing sustainability impact of biobased products’’. Two other recommendations (recommendations 6 and 7) are closely linked with this suggestion: ‘‘Implement market stimulation measures to enable a more competitive sustainable bioeconomy’’ and ‘‘Invest in the development of tools (standards and labels) enabling biobased products to be better evaluated by purchasers’’. This chapter addresses important aspects related to the market acceptance of biobased products that should be further elaborated. A specific goal is to identify preferences of consumer groups (end consumers, businesses and public procurers) regarding sustainability assessment schemes. Priority is given to the identification of relevant sustainability factors that consumer groups consider to be important and therefore determine their buying decisions. On this basis, findings on the sustainability preferences, awareness and willingness to buy biobased products of consumers are provided based on the application of different foresight methods. Foresight can help identify key factors for increasing social acceptance and therefore unlock market potentials.5 Insights into the perception of these products by society (end consumers, businesses and procurement professionals) and on the role of communicating sustainability (including the link to certification and labelling) are given. In summary, this chapter aims to deepen the understanding of consumer groups’ sustainability preferences and provide guidance on how the criteria that they use to assess the sustainability of biobased products can be most effectively communicated. This chapter is organised as follows: the next section provides information on the transition towards sustainability and a post fossil-based society. This is followed by a literature review on market acceptance factors and assessment schemes. Afterwards, the central sections of this chapter provide findings of the foresight analysis on certification schemes and market preferences, followed by a summary and implications for research and practice.

5.2 Sustainability Transition Towards a Biobased Economy This chapter is dedicated to the transition to a biobased economy in the sociotechnical regime. It relies on three groups of concepts: i) sustainability transition in sociotechnical regimes, ii) quality infrastructure and sustainability assessment schemes and iii) user acceptance as a basis for the analysis of the user acceptance in transition processes.

5.2.1

Sustainability Transition in Sociotechnical Regimes

A sociotechnical (ST) regime refers to a ‘‘semi-coherent set of rules carried by different social groups’’, which provides ‘‘orientation and co-ordination to the activities of relevant actor groups’’ and ‘‘account[s] for the stability of

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ST-configurations’’. With regard to the life cycle of a specific technology and ‘‘in evolutionary terms’’, ST-regimes function as ‘‘selection and retention mechanism[s]’’ while ST stability is ‘‘of a dynamic kind, meaning that innovation still occurs but of an incremental nature’’.6 Seven dimensions of sociotechnical regimes can be distinguished: technology, user practices and application domains (markets), symbolic meaning of technology, infrastructure, industry structure, policy and techno-scientific knowledge.6 This chapter pays specific attention to the transition in the user practices and application domains (markets) dimension, which influences the industry structure. A transition is defined as a fundamental change in a societal (sub)system resulting from a co-evolution of economic, technological, institutional, cultural and ecological developments.7 Transitions are long term phenomena (25–50 years), highly complex and involve a variety of stakeholder groups.7 The transition towards a sustainable and post fossil-based society is an emerging subject of academic research comprising various disciplines, including innovation studies, evolutionary economics, institutional theory and complexity theory, and addresses questions of fundamental societal change7 and related literature). Promoting innovation-driven economies towards sustainability plays a crucial role in the transition away from a fossil-based society.8 According to the European Commission, the biobased economy, also known as the ‘‘bioeconomy’’, refers to ‘‘the production of renewable biological resources and the conversion of these resources and waste streams into value-added products, such as food, feed, biobased products and bioenergy’’.9 The shift to a biobased economy is a central goal of the European Union. Key documents manifesting this objective include, for example, the European Bioeconomy Strategy, which aims to ‘‘pave the way to a more innovative, resource efficient and competitive society that reconciles food security with the sustainable use of renewable resources for industrial purposes, while ensuring environmental protection’’.10 Developed in 2012 and updated in 2018, the strategy represents the primary policy framework of the European bioeconomy,11 and aimed to establish a sustainable European bioeconomy that contributes to achieving the 2030 Agenda, its Sustainable Development Goals (SDGs), as well as the Paris Agreement. Implementing a successful transition and reaching a paradigm shift are ambitious goals because they are by definition embedded in complex processes.7 Transition dynamics can be visualised by multi-phase concepts and S-shaped curves.7 As shown in Figure 5.1, such curves include four phases: (1) Pre-development: small changes take place in a system but are not (yet) obvious; (2) Take-off: structural changes gain momentum, the transition starts; (3) Acceleration: structural changes gain speed and become visible; and (4) Stabilisation: a new state of dynamic equilibrium is reached.7 The S-curve suggests an easy flowing process. However, transitions may also consist of periods of slow progress in which obstacles occur and slow down the process (see Figure 5.2a). In addition, there is no guarantee that a transition will be successful and result in a new stable equilibrium (see Figure 5.2b).

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Transition process.

Figure 5.2

Delayed transition process (a) and example for an unfinished transition process (b).

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Figure 5.1

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The success of a transition process depends on many factors, which influence each stakeholder’s response to the changes in the ST regime from the fossil-based economy to a sustainable biobased economy. For this reason, stimulating stakeholders’ behaviour to reach the desired change by appropriate measures is of key importance.

5.2.2

Quality Infrastructure and Sustainability Assessment Schemes

The quality infrastructure, defined in Box 5.1, is a critical element in promoting and sustaining economic development and environmental and social well-being.12 It plays an important role in transition processes.

Box 5.1 Key definitions in the context of sustainability assessment schemes. Quality infrastructure

‘‘the system comprising the organisations (public and private) together with the policies, relevant legal and regulatory frameworks and practices needed to support and enhance the quality, safety and environmental soundness of goods, services and processes’’12 Note: ‘‘It relies on: metrology, standardisation, accreditation, conformity assessment, and market surveillance’’12 Conformity the ‘‘rules, procedures and management for carrying out assessment system conformity assessment’’18 Certification system a type of conformity assessment system; a ‘‘set of procedures and resources for carrying out the certification process as per the certification scheme labelling to the issue of a certificate’’19 (the source added ‘‘. . . of competence including maintenance’’) Certification scheme a ‘‘certification system related to specified products, to which the same specified requirements, specific rules and procedures apply’’20 Sustainability a certification scheme which includes a third-party certification verification of the sustainability criteria stipulated in the scheme system documents21 Note: The whole certification process is usually based on accreditation standards (e.g., ISO 19011 or ISO 17065)20 consisting of two separate processes of evaluation and certification. As a result of the certification process, a label on a product shows compliance with the respective certification scheme22 Sustainability a system related to specified products to which the same assessment scheme specified requirements, specific rules and procedures apply, which does not necessarily lead to certification Note: Since sustainability certification schemes belong to sustainability assessment schemes, this term can also be used synonymously for these certification schemes

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Influencing the shape of the S-curve shown in Figure 5.1, specific quality infrastructure instruments can support the diffusion of innovation,13,14 for the purposes of standardisation and regulation. Likewise, quality infrastructure instruments such as standards, eco-labels and regulation can promote innovation itself.13–17 Conformity assessment and its specific variant certification, which are the focus of this chapter, are other important quality infrastructure instruments (see Box 5.1). Our specific focus is on sustainability-related conformity assessment and certification schemes, which, as described in Box 5.1, provide not only assessments, but also the opportunity to be awarded a certificate following a successful evaluation.

5.2.3

User Acceptance

The research on sustainability preferences and acceptance factors for biobased products aims to support the development of sustainability assessment schemes for these products. Although certification can provide a suitable means to prove sustainability, there is currently a research gap regarding appropriate sustainability assessment schemes for biobased products.22 In this context, we define the user acceptance of a biobased product as the demonstrable willingness within a user group to employ this product for the tasks it is designed to support (derived from Dillon and Morris,23 who created this definition for information technology – ‘‘information technology’’ was replaced by ‘‘biobased product’’). This chapter pays particular attention to the identification and assessment of consumer preferences in order to support the transition toward a sustainable biobased economy by stimulating market demand. Specifically, we aim to support the creation of assessment criteria sets for sustainability certification in its three pillars (comprising environmental, social and economic aspects) to facilitate the market’s transition towards biobased products as indicated in Figure 5.3.

Figure 5.3

Three pillars approach and the intended effect on the user’s side.

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Figure 5.4

5.2.4

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Technology acceptance model.

User Acceptance in Transition Processes

Our research covers acceptance factors but also additional topics that influence consumers’ buying decisions, such as performance, trust and confidence; details will be provided in Sections 5.3 to 5.5. Our analysis of acceptance factors relies on well-established theories. Highly valued among marketing scholars and practitioners, the Theory of Reasoned Action (TRA)24 explains the relationship between attitudes and behaviours within human action and provides important insights into influencing factors of buying processes. Besides building the foundation for the Theory of Planned Behaviour and the Reasoned Action Approach, the TRA is also able to explain green behaviour. For example, a positive relationship between people’s interest in environmental issues and their willingness to pay more for renewable and sustainable energy was found.25,26 However, product characteristics are under-represented in these models. The Technology Acceptance Model (TAM)27,28 extends the scope of the TRA by also considering product characteristics. Figure 5.4 highlights the importance of product attributes, issues of trust and benefits expected as well as the perceived usefulness and perceived ease of use of a product. Likewise, consumers increasingly value health and sustainability in regards to biobased products and the importance of trust attributes is rising. Regulatory framework conditions have been identified as important factors influencing the innovation activities of companies, industries and whole economies while standardisation can serve as a catalyst for innovation.13,14 Likewise, quality seals can be used to address the interest in information on health aspects and sustainability and promote trust.15,29 For this reason, certification can shorten a transition process, in particular by leading to an earlier beginning of the stabilisation stage and, more importantly, optimise the likelihood of a successful outcome (see Figure 5.5).

5.3 Importance of Sustainability Criteria and Research Gaps As shown in Figures 5.3 and 5.5, the acceptance of biobased products is influenced by criteria in the environmental, social and economic

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Figure 5.5 Table 5.1

Influence of certification on transition processes. General characteristics of relevance for consumers of biobased products.

Characteristics and selected sources

Characteristics and selected sources

Quality31 on sustainable consumption,32 for green products Functionality and performance29,30,35

Price31 for biobased products30,33,34 Product life expectancy34 Life cycle cost36

sustainability pillars as well as additional criteria. This section gives insight into existing sustainability preferences and specific acceptance factors for biobased products. Regarding relevant attributes of sustainable biobased products, the state of the art in research provides various items, as shown in the following subsections.

5.3.1

Fundamental Characteristics of Relevance for Consumers of Sustainable Biobased Products

‘‘Making a product that’s good for our planet is important, but, for consumers, it’s not enough’’.30 Table 5.1 presents general characteristics that not only sustainable biobased products but also products in general should have. Table 5.1 shows the significance of these fundamental items, which are typically even more important for consumers of sustainable products than the fulfilment of specific sustainability criteria. For example, at least two studies identified the quality of the product as the most important

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aspect in a buying decision and found functionality and performance more important than independence from fossil content for corporate consumers.31,32 Two items presented in Table 5.1, namely, product life expectancy and life cycle cost, require specific attention because their importance depends significantly on the particular kind of product under consideration. Product life expectancy is, for example, less important for a cosmetic product than for a building product. Nevertheless, this does not question the importance of ensuring that cremes and shampoos, to continue the example, can be used within an appropriate period. Another important characteristic of various specific products, for example in the building sector, is the life cycle cost (LCC). The LCC is a method for evaluating all relevant costs over a projects, products or a measures lifecycle.38 It takes into account: initial costs (including capital investment costs, purchase, and installation costs); future costs (including energy costs, operating costs, maintenance costs, capital replacement costs, financing costs); and any resale, salvage, or disposal cost over the lifetime of the project, product, or measure.38 Due to its narrowed scope, LCC is not discussed as frequently in the literature as the other items in Table 5.1. The importance of LCC for products in general was shown for consumers in the United States.36

5.3.2

Environmental Topics of Relevance for Consumers of Sustainable Biobased Products

Relevant environmental product characteristics for consumers cover the whole product life cycle, starting with the criterion ‘‘sustainable yields’’ on sustainable biomass as shown in Table 5.2, which refers to the protection of the regeneration capacity of the acreage.39 Emphasis is also put on the end of life stage of the products, addressed by criteria such as biodegradability, compostability, cascade use and circularity. Biodegradability is important for end consumers of biobased products and in business-tobusiness (B2B) markets while compostability is important in B2B Table 5.2

Environmental topics of relevance for consumers of biobased products.

Characteristics and selected sources

Characteristics and selected sources

Sustainable yields39 Savings in CO2 emissions34,35 Reduced human toxicity34,35 Appropriate packaging34,35 Biodegradability40 Compostability40

Cascade use39 Circular usability29,31,39 Energy efficiency34,35 Additional product characteristics when comparing them with fossil counterparts35,40

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markets. Cascade use means to use the biomass first for what achieves the highest value.39 Circular usability29,31,39 extends the concept of cascade use. It refers to the key concept of the circular economy, which is based on three principles: ‘‘1. waste does not exist, as products are designed for a cycle of disassembly and reuse; 2. consumables should be returned to the biosphere without harm after a cascading sequence of uses, contributing to its restoration, while durables are designed to maximise their reuse or upgrade; and 3. renewable energy should be used to fuel the process’’.3,39 Besides the production and end of life stage items, the use stage is important as well, starting with considerations on appropriate packaging as well as savings in CO2 emissions and consumers’ interest in reduced human toxicity. In addition, product characteristics when comparing biobased products with fossil counterparts are a key product characteristic in B2B markets.35,40 Based on considerations on material efficiency, the European Union is also looking into the measurement and promotion of durable and repairable energy-related products under the Ecodesign framework. However, only a small proportion of products covered by the Ecodesign Directive are relevant to the bioeconomy – such products are mostly casing of electrical and electronic appliances.41 Besides the environmental factors discussed above, the life cycle assessment represents another important method to assess the environmental impact of a product. Life cycle assessments (LCAs) are ‘‘compilation(s) and evaluation(s) of the inputs, outputs and the potential environmental impacts of a product system throughout its life cycle’’.42 Their foundations are laid by the two general standards ISO 14040 and 14044, while EN 16760 describes how to handle the specificities of the biobased part of a biobased product in an LCA. Environmental Product Declarations (EPDs) are a famous direct application of LCAs. The experts interviewed by the authors during the preparation of this research stressed that many biobased products perform better than traditional alternative products over their entire life cycle, mostly in terms of important environmental impact categories (for example, end of life options and GHG emissions). However, the consumer interest in the application of LCA in the assessment of biobased products has not yet been investigated.

5.3.3

Social and Economic Criteria of Relevance for Consumers of Sustainable Biobased Products

A key social aspect in the product context refers to the working conditions in the products’ value chain. The International Labour Organisation’s (ILO) Core Labour Standards, the UN Global Compact and the OECD Guidelines for Multi-National Enterprises provide key social standards that should be observed by production sites along the supply chains.43 Additional social considerations of consumption are often closely connected with economic topics. As shown in Table 5.3, our literature review identified ten relevant

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Social and economic criteria of relevance for consumers of biobased products.

Characteristics and selected sources

Characteristics and selected sources

Food security39 Safe drinking water30 Health care30 Fair wages and safe working conditions30 Jobs and economic opportunity30

Living conditions of the world’s poor34 Equal opportunities34 Economic viability34 Economic growth34 Diversity39

items in this context. In particular, the importance of food security was highlighted: ‘‘Food first: ensure the primacy of food security’’.29 Other topics are the living conditions of the world’s poor and equal opportunities for all regarding social issues and economic viability as well as economic growth to secure human well-being.34 Consumers regard it as important that companies care for safe drinking water, health care, fair wages and safe working conditions, and jobs and economic opportunity.30 However, a link to certification is not made. This applies also to the item ‘‘economic growth’’, defined as growth that secures human well-being, and the item ‘‘diversity’’,32 which relates to the output, scale, processes and technique of production.37 It is important to notice that the importance of the several characteristics varies between different categories of biobased products.35,40,44 For procurement professionals, a supportive regulatory environment and certainty about future regulation regarding biobased products are also important.35,40 Concerning public procurement, the acceptance of biobased products in green public procurement schemes will depend on an aboveaverage performance along multiple environmental criteria. In this regard, a political decision to promote biobased products via public procurement might be needed.40 A recent study21 analysed 45 certification schemes for social factors, which are used in current eco-labels and certification schemes. Along with various environmental factors, social factors included in certification schemes were, for example: ‘‘respect to human rights’’, ‘‘no child labour’’, ‘‘the working conditions of the employees meet at least minimum standards’’, ‘‘the payment of employees meet at least minimum standards’’, ‘‘biomass production does not impair food security’’, ‘‘no GMO’’, ‘‘not tested on animals’’, and ‘‘no slash-and-burn to get acreage’’. However, the acceptance of these factors has not yet been analysed. This is only one example for an existing research gap regarding sustainability assessment schemes consumers’ preferences. The following section describes this gap in more detail.

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Research Gaps Regarding Sustainability Assessment Schemes for Biobased Products

The current state of research addresses sustainability assessment schemes for biobased products insufficiently.45 Detailed analyses of the existing research gap regarding sustainability assessment schemes consumers’ preferences unveiled the importance of four specific issues which require further research: 1. The research clearly shows the importance of information, trust and expected product benefit in buying decisions. However, more insight into the nature of suitable information on sustainable biobased products is needed. Of specific interest in this context is the role of certificates to provide this information and to raise trust. 2. Although information on the importance of sustainability criteria in general exists, more information on its relevance to decisions to buy biobased products is needed. This refers, for example, to sustainable consumption,31 and to green products without focussing on biobased products.32 Regarding the four social criteria30 indicated in Table 5.3, gaps exist as well. A key issue is that that source does not refer to biobased products specifically. The consumers of their survey stressed the importance of the four social criteria in Table 5.3. However, these criteria have yet to be linked to pertinent information for consumers’ buying decisions, in particular regarding biobased products. This need for specific insight also refers, for example, to the importance of LCC, whose importance was shown in a consumer study36 but only for consumers in the United States and without considering biobased products specifically. 3. Due to the importance of product performance and functionality, it is to be explored whether a performance criterion should be included in sustainability certification and, if so, for which biobased products it should apply. 4. The importance of the price highlights the need for efficient assessment solutions, which consider only those aspects that are really needed. This requires a detailed analysis of the relevance of the various environmental, social, economic and additional factors for the consumers. The examples show that specific analyses are needed to learn more on the importance of specific product information in markets for biobased products and their relevance for sustainability assessment schemes and certification. To address the various research gaps, this chapter assesses individuals’ and professionals’ sustainability preferences to suggest suitable assessment criteria and additional building blocks for such a scheme.

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5.4 Research Methodology The aim of our research is to gain deeper insight into i) the importance of sustainability information and certification in buying decisions, ii) the relevance of product characteristics, particularly, with regards to the three sustainability pillars, and iii) appropriate characteristics of sustainability assessment schemes to support decisions to buy biobased products such as mandatory and voluntary elements. For this reason, a survey was conducted. Survey research is ‘‘a specific type of field study that involves the collection of data from a sample of elements drawn from a well-defined population through the use of a questionnaire’’.46 Our research included six steps as shown in Figure 5.6: a literature review, summarised in section 5.3, an initial focus group event, the implementation of the survey and its analysis, evaluation and validation and, finally, the development of a summary and conclusion. Our survey had two target groups: end users and professionals. Regarding end users, a specific focus was put on Early Adopters. The concept of ‘Early Adopters’ is part of the Diffusion of Innovations theory of Everett Rogers.47 This theory explains the diffusion of new ideas, products etc. as well as different adopter groups and the time in which they adopt the innovations. Figure 5.7 shows the different adopter groups and their activities in the life cycle of a product. As pictured in Figure 5.7, Early Adopters are the first adopters after the innovators. They play an important role in convincing other groups to adopt the innovative product, idea or similar. Two typical characteristics of Early Adopters are that they are young and well-educated (see for example the two sources on the adoption of green and environmentally friendly products48,49 as well as related sources). Taking this into consideration, contacting university students in different European member states provided attractive opportunities to reach (potential) Early Adopters. For this reason, working with this consumer group was a key part in the survey’s dissemination strategy. Representatives of the group of

Figure 5.6

Research steps to identify consumers’ sustainability preferences.

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Figure 5.7

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Diffusion of innovations curve.

professionals were selected directly and individually, following the practice of two expert surveys.35,40 The selected experts included representatives of the following target groups: public procurers, businesses, certification bodies, and other institutions such as NGOs and researchers in relevant fields. Specific considerations were put on professionals entrusted with buying decisions (procurement professionals) due to their specific role on the demand side of biobased products and the importance of getting insight into their acceptance factors. As mentioned in the description of Figure 5.6, the creation of our survey built on two preliminary activities: the literature review and focus group activities. The discussions with the focus group enabled us to collect views on sustainability preferences from the following stakeholder groups: industry, public procurers, consumer representatives, and laboratories. The results were used for the survey preparation and led to questionnaires with five main topics:  awareness and willingness to buy biobased products  importance of sustainability information and certification in buying decisions  relevant product characteristics, in particular in the three sustainability pillars  characteristics of sustainability assessment schemes  additional factors to support decisions to buy biobased products The survey targeted five European regions in particular: Germany, Italy, Spain, the Netherlands, and Belgium. It was created with the LimeSurvey tool for web-based surveys and was available in English, German, Italian and Spanish. The consumer version was also available in French to address additional consumers interested in the survey.

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In line with the goal to focus on potential Early Adopters, students at multiple well-known European Universities were contacted via central mailing lists with invitations to participate in the survey. From a demographic point of view, it was therefore expected that most participants reached by this measure would be 21- to 30-years-old. As an additional measure of voluntary sampling, invitations to participate in the survey were published on the internet and in the newsletters of student organisations as well as distributed via social media. The participants of the survey among the professional group were invited individually. The survey was available for eleven weeks in summer 2018 and provided 1088 responses: 744 from end consumers and 344 from professionals (including 85 procurement professionals). Most of the participants of the end consumer survey were from Italy (39%), Germany (31%) and Spain (24%). The majority of the 344 professionals came from Germany (41%) and the Netherlands (18%). Professionals of various other countries, including representatives of organisations working on the EU level, made up the rest of the sample (28%). Sections 5.5 to 5.8 provide detailed information on the implementation and results of the survey, consisting of a brief overview of the literature, end consumers’ and professionals’ sustainability preferences, relevance of sustainability certification, additional factors for buying decisions and the market assessment for specific products.

5.5 End Consumers’ and Professionals’ Sustainability Preferences Addressing the research gaps described in section 5.3, our survey addressed the following topics of end consumers’ and professionals’ sustainability preferences:  The propensity to buy biobased products and the importance of specific information for the buying decisions  Preferences regarding environmental aspects  Preferences regarding social and economic aspects The results are presented in the following:

5.5.1

Propensity to Buy Biobased Products and Importance of Specific Kinds of Information for the Buying Decisions

The consumption behaviour of private households (end consumers) and professional buyers is different in many respects. For example, there are various products used for industrial applications which are not demanded by private households.

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Regarding the products which are relevant for both target groups, the buying decisions of end consumers and professionals are also embedded in different contexts. An important factor is that the buying decisions of professionals not only depend on individual preferences but also on the procurement rules of their employers (also including rules of public procurement). These rules are often shaped by regulatory framework conditions. Section 5.8 will describe various needs for more supportive framework conditions for facilitating the procurement processes to buy biobased products. In regards to the individual propensity to purchasing biobased products, Figure 5.8 shows that most of the end consumers (75%) are inclined or even very inclined to purchase biobased products. The willingness to buy biobased products is even higher when particular products were discussed (such as personal care products). When the awareness of biobased products and the willingness to buy them were assessed, the end consumers’ willingness to buy these products exceeds the awareness of them in all cases, except for paper products. However, the price of the products is always a decisive factor as well. Specific results on these aspects will be presented in detail in sections 5.7 and 5.8. Section 5.8 will also show that the willingness to buy biobased products varies between 86% for personal care products and 27% for lubricants on the end consumers’ side. On the side of the professionals, it ranged from 84% for personal care products to 11% for electronic equipment with biobased casing. The high percentage rates for the willingness to buy biobased personal care products do not only stress the interest in these products, they are also an indicator for a basic interest in biobased products in general in both target groups. This positive result also provided us with useful framework conditions to discuss specific aspects related to these products with the

Figure 5.8

Propensity of the end consumers to purchase biobased products.

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Figure 5.9

Importance of information on biobased products for different stakeholder groups.

Figure 5.10

Word cloud of the interest categories of the end consumers (left side) and the professionals (right side) in addition to the three sustainability pillars in general.

participants. The majority of all target groups regard information related to all three sustainability pillars as relevant for their buying decisions. However, as Figure 5.9 shows, environmental aspects are the most influential factor. In response to the optional open question to indicate additional information of relevance, participants provided various statements. Topics of key interest are shown in Figure 5.10. Instead of additional topics, it was noted in many cases that the participants mentioned topics that specified the three sustainability pillars and that were also discussed in detail in later parts of the survey. Interestingly, there are clear differences between the most-mentioned items of both user groups. While health is a key issue for end consumers, followed by the functionality and origin of the biobased products, the top topics of the professionals are the specific environmental issue end of life

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and the price. However, the biggest share of answers is inhomogeneous: the category ‘‘other’’ includes, for example, information on comparisons with alternative products, the availability of the product (i.e. where and how easily the products can be bought) as well as the need for appropriate definitions of biobased products. An unanswered question is whether the statements refer to biobased products in general or, as the term ‘‘health’’ might indicate, whether participants had specific products in mind when answering this question.

5.5.2

Preferences Regarding Environmental Aspects

The next set of questions discussed relevant environmental, social and economic product characteristics. Figure 5.11 provides an overview on the importance of environmental issues in decisions to purchase a biobased product. As shown in Figure 5.11, important information for assessing the environmental sustainability performance of biobased products includes their recyclability, the type and origin of their raw material, the percentage of their biobased content and their biodegradability. Various participants used the optional open question to specify additional environmental issues.

Figure 5.11

Information decisions.

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These include in particular energy issues, which are addressed in a specific product-related section of the survey, but also, for example, regional origin and transportation, thereby extending the scope of the item ‘‘type and origin of raw material’’ by highlighting regionality.

5.5.3

Preferences Regarding Social and Economic Aspects

With regard to the social dimension, the survey included seven items: 1. influence of the product on people’s health, 2. respect for human rights in the production of the material and the product, 3. no child labour, 4. not tested on animals, 5. the working conditions and the payment of the employees meet at least minimum standards, 6. implementation of an occupational health and safety plan for the production of the product and 7. contribution to the economic well-being of local communities by the producer.y Although ‘‘child labour’’ could be included in the broader category of ‘‘Respect of human rights. . .’’ and is also covered by the ILO international labour standards,z it was decided to present this item separately because of its specific relevance to protect the weakest members of today’s societies. Another issue considered by the human rights item was food security. Food security is addressed by the Universal Declaration of Human Rights (UDHR) in Article 25: (1) ‘‘Everyone has the right to a standard of living adequate for the health and well-being of himself and of his family, including food. . .’’. The Renewable Energy Directive (RED)’s, sustainability criteria for bioenergy described earlier does not address food security (although food security is mentioned in its article 23). Therefore, it was decided to keep food security under human rights in general. For both the professional and end consumer groups, information on the absence of child labour, respect for human rights and people’s health are the most important social acceptance factors (Figure 5.12). The top-ranked item for end consumers is the influence of the product on people’s health. In line with our expectations, all target groups ranked ‘‘no child labour’’ higher than ‘‘human rights. . .’’, highlighting the relevance of this specific item in the sustainability assessment context. Likewise, ‘‘no child labour’’ was ranked higher than ‘‘working conductions and payment of the employees meet at least minimum standards’’. To address the relation between child labour and the two other categories, a sustainability assessment criterion ‘‘Fulfilment of key human rights principles and international labour standards (ILO) in the sourcing of raw materials and the production of the products, for example, forbidding child labour’’ might provide a solution. A similar approach is used by the Roundtable on Sustainable Biomaterials (RSB) that includes the principle y

This item in the survey was listed under the economic pillar of sustainability, but addresses both the social pillar and the economic pillar. In the analyses of the results, this item is treated under the social pillar as suggested by participating experts. z International Labour Organisation (ILO)’s conventions and recommendations.

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Figure 5.12

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Information on social issues influencing purchasing decisions.

‘‘human and labour rights’’.50 The survey results suggest to follow that example. Additional issues proposed by the participants in the optional open question include food security in the assessment and a suggestion to analyse social issues on each product life cycle stage, meaning to conduct social LCAs. A targeted discussion on food security and the work of FAOy led to the reconsideration of this item separately in sustainability certification. An indicator for food security could be that the amount of feedstock sourced from countries with undernutrition does not exceed specific thresholds. As Figure 5.12 shows, various social issues besides ‘‘influence of the product on people’s health’’ (e.g. ‘‘no child labour’’ and ‘‘respect of human rights. . .’’) were also ranked very high. This can be regarded as an indicator of an ethical consumption behaviour, a conscious and deliberate choice due to personal and moral beliefs.51 A comparison of our findings with studies on decisions to buy organic food52–54 showed the importance of health issues in both decisions. More specifically, the highest awareness and willingness to buy biobased products was observed for personal care products in our study. Besides this, the

y

See, for example, http://www.fao.org/economic/ess/ess-fs/en/ for further information.

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influence of the product on people’s health was top-ranked among the consumers of our survey and on the second rank among the professionals. An interesting result of the participants’ ranking of environmental information in our survey is that ‘‘No use of genetically modified organisms’’ (GMO) is ranked as a relatively low priority despite this criterion being regarded as very important for food and communicated on the packages of various food products. The result indicates that, depending on the specific application field, stakeholders have different views regarding the use of these organisms. While there is much scepticism and opposition regarding GMO-containing food, non-food applications may be acceptable for large parts of the target groups. A case study on food packaging41 provided additional insight: if biobased packaging is used for organic food products, it is important that not only the food but also the packaging is GMO-free. While analyses in the food sector refer to animal welfare (e.g. Rupesh and Velmurugan53), in particular regarding the production of meat, our survey included the item ‘‘not tested on animals’’. This item is relatively low ranked, which may be a result of the fact that only a fraction of biobased products can be tested on animals, e.g. cosmetic products. The economic dimension was analysed by two items. For professionals, fair business practices of the company are more important than the fair land use rights practices in the production of feedstock. As Figure 5.13 shows, the ranking by the end consumers has the opposite order. An interpretation may be that professionals are aware of the need to consider business practices as a whole in their buying decisions while end consumers paid specific

Figure 5.13

Information on economic issues influencing purchasing decisions.

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attention to an item whose wording suggests a close relation to the material of the products. In response to an optional open question regarding additional economic issues, both end consumers and professionals referred to fair wages and the price of the product. The fact that fair wages, which can be linked to several pillars, were mentioned again highlights the importance of this topic for buying decisions. The existence of issues that are linked with more than one sustainability pillar also shows the importance of considering the various assessment items beyond the boundaries of the three sustainability pillars individually.

5.6 Relevance of Sustainability Certification The survey also analysed the benefit of sustainability certification and detailed features of possible sustainability certification schemes for biobased products. First, a set of questions referring to general certification issues was posed. The introductory question was: ‘‘Would you regard sustainability certification for biobased products as beneficial for your buying decisions?’’ As Figure 5.14 shows, over 75% of each group of respondents answered positively. This percentage was highest in the end consumer group, within which 84% gave a positive answer. Another key question was which topics the different target groups believed should be mandatorily and voluntarily considered in such a scheme. With a positive response ranging from 87 to 91% of all participants, the majority of all groups suggest that the inclusion of information on environmental issues should be mandatory in the certification of biobased products. However, as

Figure 5.14

Importance of sustainability certification for the purchasing decisions.

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Figure 5.15

Compulsory nature certification.

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shown in Figure 5.15, support for mandatory certification is less strong for social issues (56 to 62%) and economic issues (39 to 46%). While the majority of participants believe that economic issues should not be mandatorily considered in the certificate, end consumers suggested mandatory certification of economic issues slightly more frequently than procurement professionals. Regarding economic issues, for which the majority of participants do not believe should be a mandatory consideration for sustainability certification, participants suggested voluntary certification (34% of the end consumers, 41% of the professionals in total and 35% of the procurement professionals) or separate certification (20% of the end consumers, 19% of the professionals in total and 22% of the procurement professionals).

5.7 Additional Important Factors for Buying Decisions In the context of green products, the quality of a product was identified as the most important consideration in a buying decision.31,32 In the same way, the importance of functionality and performance in the evaluation of biobased and sustainable products was stressed.29,30 Likewise, the state of the art in research highlights the importance of the price of a product as a key purchasing factor. For example, a study31 involving 25 633 telephone and faceto-face interviews in EU27 member states on sustainable consumption, found that the majority of buyers regard the price of a product as more important than its environmental impact. Likewise, the importance of this

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issue based on an EU-wide survey on green products involving 26 568 persons in EU27 countries and Croatia was reported.32 Regarding biobased products, the importance of this factor was emphasised as well.29,30,33,34 However, the importance of these topics in the given context has not yet been investigated. In particular, there is no information on how much more the target groups would be willing to pay for certified biobased products. There is also no information whether people are willing to pay more for products performing better from an environmental and social point of view, and if so, to what extent. In addition, the importance of analysing LCC was stressed.36 Additional issues which drew our attention were the importance of the brand name30 in the specific buying decisions to buy biobased products as well as the energy consumption of these products.40 For this reason, the survey for our different target groups included six items to analyse the additional topics functionality and performance of the product and better performance than alternative fossil-based products, price, energy consumption, brand name and specific brand name for biobased products. Specifying financial issues, the survey among processionals not only included the item ‘‘price’’ but also the more complex item ‘‘LCC’’. In summary, the three most important additional factors influencing end consumers’ decisions to purchase biobased products are: 1. price, 2. Functionality and performance of the product and 3. better performance than alternative fossil-based products. These three factors are depicted in Figure 5.16. For professionals, this ranking was: 1. Functionality and performance of the product, 2. price and 3. LCC (which was not discussed with end consumers due to the complexity of this aspect and its relevance for selected products only). The survey also discussed the participants’ willingness to pay for certified biobased products and, if so, how much more than for a non-certified product. In response to the question ‘‘Imagine a biobased product with a logo indicating that the issues important for your buying decision are considered. How much would you be willing to pay extra?’’, consumers, the largest group surveyed, would be willing to pay 2.5% or more for a certified product. Regarding further factors that could support decisions to buy biobased products and their market in general, professionals were asked how European policymakers could promote the acceptance of biobased products. Nine aspects were identified: 1. appropriate information, communication (in general) and awareness increase, 2. public procurement, 3. taxation and subsidies, 4. labels and certificates, 5. legislation including bans, 6. standards, 7. ensuring environmental friendliness, 8. comparisons with fossilbased products and 9. harmonisation of definitions.

5.8 Market Assessment for Specific Products To obtain a deeper understanding of the willingness to buy biobased products of which the participants are aware of, two questions on a) the awareness of biobased products and b) the willingness to buy them were

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Figure 5.16

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Information on additional characteristics influencing purchasing decisions.

used. Due to the focus on specific buying decisions, only consumers and procurement professionals were considered in this analysis. Figure 5.17 visualizes the result for these groups. As shown in Figure 5.17, personal care, cleaning, and paper products are the best-known products of which end consumers and procurement professionals are aware of variants with biobased contents while lubricants and electronic equipment with biobased contents were the least known products. The willingness of consumers to buy biobased products is the highest for the best-known products together with children’s products, the latter of which exhibits a significant discrepancy between the willingness to buy biobased products and the awareness of such products. Lubricants as well as

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Figure 5.17

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Awareness of various biobased products and buying intentions.

construction and building material are the products for which there is the least willingness to buy biobased products. Compared with the results on the general willingness to purchase biobased products with 75% of the end consumers being inclined and very inclined to make such purchases, their willingness to buy biobased personal care products even reached 84%. Among the procurement professionals, the

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willingness to buy biobased products is however still significantly lower than their awareness of these products. These findings also have implications on the question of how much more end consumers and procurement professionals would pay for certified biobased products. Future research must analyse how certificates can stimulate the willingness to buy specific types of products and to what extent the willingness to pay extra for such certificates may vary.

5.9 Conclusions and Outlook The bioeconomy is an important emerging phenomenon of the 21st century. However, various challenges regarding the initiation of the transition towards this new socio-economic paradigm exist.1 This chapter was dedicated to the market assessment of these products to support producers and decision makers in the identification and implementation of appropriate market stimulation measures. Specifically, this focussed on BBP-EG’s4 fourth recommendation to ‘‘develop and implement robust methodologies, criteria, standards and certification schemes for assessing sustainability impact of biobased products’’. The analyses of the specific consumer preferences led to eight conclusions: 1. End consumers are inclined to buy biobased products. There is specific demand for biobased products that address personal care. In line with this, there is much interest in information on a product’s influence on health. 2. The majority of all stakeholder groups regard information on all sustainability pillars as relevant for their decisions on buying biobased products; information on environmental issues, in general, is regarded as the most important. 3. The importance of sustainability certification for biobased products was clearly expressed: 80% of professionals and 84% of end consumers answered ‘‘yes’’ to the question ‘‘Would you regard sustainability certification for biobased products as beneficial for your buying decisions?’’ 4. Most participants believe that the consideration of environmental and social issues should be mandatory for sustainability certification while consideration of economic issues should be voluntary. 5. For end consumers, the three most important environmental issues influencing the decision to purchase a biobased product are: 1. biodegradability, 2. recyclability and 3. type and origin or raw material. For professionals, this ranking is: 1. recyclability, 2. type and origin of raw material and 3. percentage of biobased content. 6. For end consumers, the three most important social issues influencing the decision to purchase a biobased product are: 1. the influence of the product on people’s health, 2. no child labour and 3. respect of human

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rights in the production of the material and the product and for professionals. For professionals, this ranking is: 1. no child labour, 2. the influence of the product on people’s health and 3. respect for human rights in the production of the material and the product. 7. For end consumers, the three most important additional product characteristics, which may influence one’s decision to purchase a biobased product are: 1. price, 2. functionality or performance of the product and 3. better performance than alternative fossil-based product. For professionals, this ranking is: 1. functionality and performance of the product, 2. price and 3. LCC. 8. Among procurement professionals, the willingness to buy biobased products is still significantly lower than their awareness of these products. The 8th item of the list above demonstrates the need for specific action. Based on input by our stakeholders, regulatory frameworks should be further developed to encourage the adoption of biobased products. In addition, the willingness to pay for certified biobased products was analysed among end consumers. A field experiment designed to elicit consumers’ willingness to pay (WTP) will be carried will further the results. Here, end consumers’ preferences will be assessed through a case study and by the comparison of WTP for a biobased product carrying a proposed certification scheme against an identical biobased product without that label and a conventional product of the same kind. The experiment will be based on an incentivecompatible experiment design, in which every participant can achieve the best outcome for themselves by acting according to their true preferences. This experimental methodology will provide an estimation of the end consumers’ attitude towards new certified biobased products with a minimum risk of overestimating their real willingness to pay and will allow underpinning the real premium assigned by end consumers to self-certification and mandatory certification schemes. This experiment, which is not only focussed on the green premium but also on the willingness to pay for certified biobased products, will be the first of its kind in the area of study. The results will be published by the STAR-ProBio project at the end of 2019. In summary, our findings on sustainability criteria support the prediction of BBMG GlobeScan and SustainAbility:30 ‘‘Brands will win by embedding sustainability and social purpose into every business strategy, product design and stakeholder relationship’’ regarding the design of biobased product and stakeholder relations. However, an appropriate communication of these characteristics will be important. As our analyses have shown, labelling and certification can play an important role in pursuing this goal. Based on our findings, our recommendation for further research is threefold: 1. The survey described in this chapter aimed to support the creation of a sustainability scheme to promote the market uptake of biobased

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products, which shall be completed in spring 2020. We suggest further research to analyse the success and impact of that scheme in the future regarding the various types of biobased products and the different stakeholder groups. 2. We also suggest continuous research on the further development of the bio- and circular economy as a whole. The high variety of biobased products in terms of their feedstock (e.g. fresh biomass, residues of the food sector and product waste in the after use stage), their functionalities and use stage, as well as their end-of-life options constitutes a fascinating environment for manifold scientific activities in this context. 3. The suggested analyses of the bioeconomy also include comparisons with other transitions of the past and the present, in particular with the IT field regarding the emergence of the internet and the digital society. Multi-disciplinary research from scientists of various fields is suggested to deepen the insight in the transition topic and its multiple dimensions. In addition, it is suggested to conduct more comparative analyses on both the market for organic food products and the market for biobased products.

Acknowledgements The authors are very grateful to the STAR-ProBio project (Sustainability Transition Assessment and Research of Bio-based Products) for their financial support. The project is funded by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 727740, Work Programme BB-01-2016: Sustainability schemes for the biobased economy. Duration: 36 months (May 2017 – April 2020).

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Standardisation in a Sustainable Bio-Based Economy in the EU, Sustainability, 2018, 10(7), 2455. A. Dillon and M. G. Morris User acceptance of new information technology: theories and models, in Annual Review of Information Science and Technology, ed. M. Williams, Information Today, Medford NJ, 1996, pp. 3–32. I. Ajzen and M. Fishbein, Understanding Attitudes and Predicting Social Behavior, Prentice Hall, 1980. H.-K. Bang, A. E. Ellinger, J. Hadjimarcou and P. A. Traichal, Consumer concern, knowledge, belief, and attitude toward renewable energy: An application of the reasoned action theory, Psychol. Mark., 2000, 17(6), 449–468. ¨rling, Psychological deA. Hansla, A. Gamble, A. Juliusson and T. Ga terminants of attitude towards and willingness to pay for green electricity, Energy Policy, 2008, 36(2), 768–774. F. D. Davis, A technology acceptance model for empirically testing new end-user information systems – theory and results, PhD thesis, Massachusetts Inst. of Technology, 1985. F. D. Davis, R. Bagozzi and P. R. Warshaw, User Acceptance of Computer Technology: A Comparison of Two Theoretical Models, Manage. Sci., 1989, 35(8), 982–1003. ¨ring, C. M. Baum, O. K. Butkowski and M. Kircher Kriterien fu ¨r S. Bro ¨konomie, in Bioo¨konomie fu ¨r Einsteiger, ed. den Erfolg der Bioo J. Pietzsch, 2017. BBMG GlobeScan and SustainAbility, Re:Thinking Consumption- Consumers and the Future of Sustainability, 2012. The Gallup Organisation at the request of the Directorate-General for the Environment. Flash EB No 256 Europeans’ attitudes towards the issue of sustainable consumption and production. 2009. TNS Political & Social at the request of the European Commission – Directorate-General for Environment, FLASH EUROBAROMETER 367, Attitudes of Europeans Towards Building the single market for green products, http://ec.europa.eu/environment/eurobarometers_en.htm, 2012. D. Whitson, H. E. Ozkaya and J. Roxas, Changes in consumer segments and preferences to green labeling, Int. J. Consum. Stud., 2014, 38, 458– 466. ¨hm, Sustainability seen from the perspective of D. Hanss and G. Bo consumers, Int. J. Consum. Stud., 2012, 36, 678–687. J. Peukert and R. Quitzow, Acceptance of bio-based products on business-to-business markets and public procurement: expert survey results, Biofuels, Bioprod. Biorefin., 2017, 11, 92–109. K. B. Sheehan, The many Shades of Greenwashing: Using Consumer Input for Policy Decisions Regarding Green Advertisements, in Communicating Sustainability for the Green Economy, ed. L. R. Kahle and E. Gurel-Atay, 2015, pp. 43–55.

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37. Vertech Group. Life Cycle Cost Assessment. CloseWEEE-WP8-DEL-D8.1VTG-20150631-v02.doc, https://ec.europa.eu/research/participants/ documents/downloadPublic?documentIds=080166e5a0aca20f&appId= PPGMS, 2014. 38. S. Fuller Guidance on Life-Cycle Cost Analysis. Required by Executive Order 13123, Department of Energy, Federal Energy Management Program, Washington, DC, 2005. 39. SCAR, 4th Foresight Exercise Sustainable Agriculture, Forestry and Fisheries in the Bioeconomy – A Challenge for Europe, http://ec.europa. eu/research/scar/pdf/feg4-draft-15_may_2015.pdf, 2015. 40. Open-Bio, Deliverable N1 9.2 Acceptance factors for bio-based products and related information systems. http://www.biobasedeconomy.eu/app/ uploads/sites/2/2017/07/Acceptance-factors-for-bio-based-products-andrelated-information-systems.pdf, 2015. 41. STAR-ProBio, STAR-ProBio Deliverable D9.2, Recommendations for Standards and criteria for eco-labels for bio-based products, Available from Internet: www.star-probio.eu, 2018. 42. ISO, ISO 14044 Environmental Management – Life Cycle Assessment – Requirements and Guidelines, 2006. 43. ILO/ITC, International Instruments and Corporate Social Responsibility A Booklet to Accompany Training on Promoting labour standards through Corporate Social Responsibility, https://www.ilo.org/wcmsp5/ groups/public/—ed_emp/—emp_ent/—multi/documents/ instructionalmaterial/wcms_227866.pdf, 2007. 44. M. G. Luchs, R. Walker Naylor, J. R. Irwin and R. Raghunathan, The Sustainability Liability: Potential Negative Effects of Ethicality on Product Preference, J. Marketing, 2010, 74, 18–31. ¨n, 45. S. Majer, S. Wurster, D. Moosmann, L. Ladu, B. Sumfleth and D. Thra Gaps and Research Demand for Sustainability Certification and Standardisation in a Sustainable Bio-Based Economy in the EU, Sustainability, 2018, 10(7), 2455. 46. P. S. Visser, J. A. Krosnick and P. J. Lavrakas Survey Research, in Handbook of Research Methods in Social and Personality Psychology, ed. H. T. Reis and C. M. Judd, Cambridge University Press, New York, NY, US, 2000, pp. 223–252. 47. E. M. Rogers, Diffusion of Innovations, Free Press, New York, 2003. 48. D. Mulvaney and P. Robbins, Green Food: An A-to-Z Guide, SAGE Publications, Inc., 2011. 49. S. Hardmana, E. Shiub and R. Steinberger-Wilckensa, Comparing highend and low-end early adopters of battery electric vehicles, Transp. Res. Part A- Policy, 2016, 88(2016), 40–57. 50. RSB, RSB Principles and Criteria. http://rsb.org/wp-content/uploads/ 2017/03/RSB-STD-01-001_Principles_and_Criteria.pdf, 2017. 51. M. Carrigan, I. Szmigin and J. Wright, Shopping for a better world? An interpretive study of the potential for ethical consumption within the older market, J. Consum. Mark., 2004, 21, 401–417.

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52. Grand View Research, Organic Foods And Beverages Market Analysis By Product (Fruits & Vegetables, Meat, Fish & Poultry, Dairy Products, Frozen & Processed Food), Organic Beverages (Non-Dairy, Coffee & Tea, Beer & Wine), And Segment Forecasts, 2018–2025, 2017. 53. M. M. Rupesh and R. Velmurugan, Consumer’s attitude towards organic food products, Discovery, 2013, 3(7), 15–18. 54. M. C. T. R. Vidigal, A. A. Simiqueli, P. H. P. Souza, D. F. Balbino and L. A. Minim, Food technology neophobia and consumer attitudes toward foods produced by new and conventional technologies: A case study in Brazil, LWT-Food Sci. Technol., 2015, 60(2), 832–840.

CHAPTER 6

Social Assessment E. IMBERT* AND P. M. FALCONE Unitelma Sapienza – University of Rome, Department of Law and Economics, Viale Regina Elena 295, 00161, Roma, Italy *Email: [email protected]

6.1 Introduction There is a major consensus on the existence of a strong relationship between climate change and Greenhouse Gas (GHG) Emissions.1–4 Within this context, technological breakthroughs can play a key role in reducing carbon emissions, boosting the development of green economies.5 However, innovations have had only partial success in reducing negative impacts on the environment while simultaneously providing positive societal and economic effects. The sustainability of new technologies and products needs to be proven, even when they utilize renewable feedstocks and especially if supported by tailored policy actions.6 In general, when assessing a product’s sustainability, socio-economic aspects have been neglected in comparison to environmental aspects.7 However, in recent years several factors have contributed to increased attention being paid to the social dimension. At the global policy level, these are represented by the targets set by the United Nations (UN) Sustainable Development Goals (SDGs), since six out of the 17 SDGs are particularly focused on social issuesy.8 Moreover, three relevant examples at the European level are the European growth agenda, calling for more sustainable and equitable production systems,9 the EU strategy for Corporate Social Responsibility10 and EU Procurement Directives y

Goals n. 1, 4, 5, 8, 10 and 11.

Green Chemistry Series No. 64 Transition Towards a Sustainable Biobased Economy Edited by Piergiuseppe Morone and James H. Clark r The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

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where, despite environmental considerations being most frequently prominent, more consideration was given to socio-economic aspects.11 At the same time, there has also been great interest in the business world evidenced by a huge expansion in new business models focused on social sustainability. In this respect, social economy enterprises represent 10% of all businesses in the EU, employing more than 11 million peoplez. Meanwhile, consumers in general, have been becoming increasingly aware of important socio-economic issues and thus, more demanding in their buying decisionmaking process.12,13 As a consequence there has been a proliferation of labels, though not all with a life cycle perspective. This perspective, encompassing the whole life cycle of a product (i.e. extraction and processing of raw materials, manufacturing, distribution, product use, recycling and disposal) is instead considered to be crucial14,15 also with regards to meeting SDGsy. Moreover, in the specific case of bio-based products and related sustainability challenges, a life cycle perspective becomes particularly relevant. For example, there must be an assurance that sustainable sourcing of raw materials has been achieved avoiding competition with food and feed production, as well as verification of whether an appropriate and sustainable end of life has been considered.16 Notably, a S-LCA integrated with an environmental life cycle assessment (E-LCA) and life cycle costing (LCC), i.e. a life cycle sustainability assessment (LCSA), can be used as a decision-support tool17 thanks to the identification of risks, positive and negative impacts and potential improvement opportunities.18 It should be noted, however, that it is not possible to consider an excessively high number of criteria19,20 in assessing social sustainability, in order to avoid placing a heavy burden especially on producer companies that need to provide primary data. A selection must be made upstream. Against this backdrop and building on previous studies,7,21 the present chapter extends the research on the structuring of a general S-LCA framework for biobased products, aiming to further deepen our knowledge on the most relevant social impact categories, subcategories, and indicators associated with these kinds of products. Specifically, the selection of social topics and associated indicators is based on a recent review of the literature that was validated and integrated through a participatory approach, engaging a broad number of stakeholders via four interactive workshops. The framework presents a selected set of socio-economic criteria to be met, with the final aim of supporting and improving future decision-making processes to support sustainable bio-based products. Indeed, the selection of adequate criteria can support the design of sustainability schemes (e.g. standards, labels, certifications, etc.) that also embrace social aspects, and that can be useful to a broad variety of actors, including policymakers, industry and consumers.22,23

z

https://ec.europa.eu/growth/sectors/social-economy_en See the project ‘Linking the UN Sustainable Development Goals to life cycle impact pathway ´ Sustainability. https://www.lifecycleinitiative. frameworks’, led by LCA 2.-0 Consultants and PRe org/new-project-linking-the-un-sustainable-development-goals-to-life-cycle-impact-pathwayframeworks/

y

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The chapter is organized as follows. Section 6.2 provides an overview of the main challenges related to the S-LCA methodology and its application. In Section 6.3 the proposed social assessment framework for bio-based products is presented. Section 6.4 describes and discusses the results. Finally, in Section 6.5 conclusions are made and future directions for research are suggested.

6.2 Methodology 6.2.1

Main Features

S-LCA is a relatively new methodology compared to E-LCA and LCC and is therefore being continuously updated.24 It can be applied at both the product or service levels, the economic sectors and to systems.25 In particular, it can be also used for comparing similar products (e.g. when composed of different feedstocks), systems or different scenarios in order to identify those which are most sustainable.8 A key methodological reference framework for S-LCA is represented by the UNEP/SETAC guidelines,26 complementing the ISO 14040:2006 and 14044:2006 standards referring to the E-LCA. Indeed, a S-LCA is based on the same steps followed by an E-LCA, i.e. i) goal and scope definition, ii) life cycle inventory, iii) life cycle impact assessment and iv) interpretation. The guidelines, defining a S-LCA as an assessment technique that aims to evaluate the social and socio-economic aspects of products and their potential positive and negative impacts along their life cycle,27 presented a broad list of social themes of interest to be assessed, i.e. subcategories, with the final aim of avoiding an analysis based on limited topics for social marketing objectives.28 The guidelines were then later complemented by the methodological sheets29 that identified a set of indicators that can be used for each of the subcategories identified in the guidelines. The UNEP-SETAC guidelines (2009)26 describe the subcategories as related to impact categories and stakeholder categories, which represent all social groups of actors affected throughout production and consumption processes. Grießhammer et al.30 agreed to introduce four groups of stakeholders: workforce, local community, society and consumers. In the guidelines, an additional group of stakeholders, i.e. value chain actors, was also proposed. Social impact categories are identified in S-LCA to categorize the ways in which stakeholders can be impacted within a particular area of protection (AoP).31 Social impact categories are, essentially, related to different stakeholder groups and can be categorized into midpoints and endpoints. While the endpoint category aims to represent the final damages caused to an AoP, the midpoint category seeks to cover a particular issue that stands somewhere between the inventory indicators and the final damage to the AoP.26 Since impact categories represent groupings of S-LCA results related to issues of major relevance, they can be distinguished by several subcategories representing specific impacts on stakeholders. In this context, the afore mentioned ‘‘Methodological Sheets for Subcategories in Social Life Cycle

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29

Assessment’’ provides a selection of socio-economic topics and potential associated indicators, defined according to international agreements (e.g. UN declaration of human rights, convention on workers’ rights, etc.) and organized by stakeholder categories (i.e. workers, local community, society, consumers, and value chain actors)z. Indeed, appropriate indicators, which act as the bridge linking data to subcategories and impact categories, must be selected.32 In this regard, well defined indicators are extremely important in guiding the data collection process33 since indicators can be quantitative, qualitative or semi qualitative.34 The former are indicators indented to assess impacts that can also be detected without taking into account the experiences of relevant stakeholders – e.g. wages, working hours, etc. The latter are indicators that look at ‘inner qualities’ – e.g. experiences or feelings of the stakeholders. Although the presence of subjective indicators would improve the strengths of the S-LCA,35 it is often the case that objective indicators are solely considered while performing S-LCA. This is mainly due to the lack of available data. In particular, from a practical viewpoint, the inclusion of subjective indicators requires an appraisal of the experience of a specifically impacted stakeholder.36 Moreover, the use of subjective indicators poses several challenges with reference to the functional unit, which is the amount of product function which acts generally as a reference for all the calculations needed to assess the impacts.37 Furthermore, considering that a number of indicators identified by the guidelines and methodological sheets refer in part to the organizational rather than to the product level, a new approach known as the Social Organizational LCA (SOLCA) has been recently proposed with the aim of complementing the product-focused approach with an organizational perspective.38 As it seems, data collection on well-being represent one of the more challenging tasks in performing S-LCA, and the use of subjective indicators is likely to make it more difficult.23 Robustness and reliability of S-LCA findings depend largely on the theoretical soundness in defining the impacts’ pathway established among indicators, subcategories and impact categories.36 In this context, according to the UNEP-SETAC guidelines, there are two types of social and socio-economic impact categories: Type I and Type II. ‘‘Type I impact categories aggregate the results for the subcategories within a theme of interest to a stakeholder, Type II impact categories model the results for the subcategories that have a causal relationship defined on the criteria’’ (2009, p. 71). Figure 6.1 depicts the characteristics of the two types of social impact categories. Type I social impact categories employed in S-LCA does not incorporate causal relationships and the indicators are assessed with a scoring system. They represent social issues of interest concerning impacted stakeholders and, as proposed by Benoit-Norris39 may cover health and safety, human rights, working conditions, socio-economic repercussions, cultural heritage z

For instance, if we consider ‘‘working conditions’’ of the stakeholder category ‘‘workers’’ as an impact category, possible subcategories could be ‘‘fair salary, hours of work, etc’’.

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Figure 6.1

Characteristics of Type I and II impact pathways.33

and governance. The information can be grouped to express one endpoint category that can be human well-being or fairness of relationships.26 Type II social impact categories are based on the causal relationships from indicators to mid and endpoint impact categories. As proposed by Weidema,40 the social impact pathways to the endpoints human well-being is based upon the midpoints health, autonomy, safety, security, equal opportunities, etc. With the publication of UNEP-SETAC guidelines, there has been a proliferation of contributions incorporating Type I characterization models.40,41 Type II models gained momentum a few years later.42–45 Over the years, a wide number of S-LCA studies have been published,43,44,46–48 many of which have used the guidelines as a reference framework. However, a standardized methodology has not yet been fully achieved and several operational challenges are still faced by practitioners and scholars.49,50

6.2.2

Measurement Challenges

Currently, the selection of subcategories and associated indicators, availability and meaningfulness of data and the choice of the impact assessment method represent the main critical elements of a S-LCA.51 In particular, the impact assessment stage is considered to be extremely challenging52 and Type I approach has remained the most used53 especially given that Type II does not work for all subcategories and therefore introduces more challenges. To date, there has been two principal databases in use, i.e. the Product Social Impact Life Cycle Assessment (PSILCA) database, developed by Green Delta,54 and the Social Hotspot Database developed by the New Earth.55 Both databases provide information on social risks.56 However, a hotspot analysis carried out at the national, regional or sector level represents solely the first step, since the final objective is to understand the positive and negative impacts of specific products and processes. Accordingly, these macro-scale assessments need to be complemented through case studies using site

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57

specific data. This is, however, a very challenging outcome to be achieved since primary data are extremely difficult to collect. Furthermore, there is no general consensus on how the collection of primary data should be carried out. In this respect, an increased sharing of questionnaires and surveys used for gathering data may lead to significant benefits.32 Performing an S-LCA practically is therefore extremely challenging. According to Traverso et al.,58 an important step towards the objective is represented by Fontes et al.59 who in their Handbook for Product Social Impact Assessment developed a practical methodology to assess the positive and negative impacts of products on three stakeholder categories, i.e. workers, consumers and local communities based on 19 social topics and their related indicators. In the latest version of the handbook the impact assessment is based on a qualitative approach which refines social topics and performance indicators, as well as adding a new stakeholder category, i.e. small-scale entrepreneurs.56 Moreover, it is underlined that a preliminary identification of hotspots using, for instance, the Social Hotspot Database39,55 can be useful even before performing a single case study. For example, if some value chain phases occur within the EU then it would probably not be necessary to consider the absence of child labour.58 Based on the methodological gaps that have been overviewed in this paragraph, a revision process of the guidelines led by the Social Local Community Alliance, and supported by the European Commission in cooperation with UN Environment and the Life Cycle Initiative has been set in motion to include methodological advancements and boost harmonization, include know-how gained from recently published studies and integrate the SOLCA approach.60

6.3 S-LCA Applied to Bio-based Products: A General Framework Bio-based products are defined as products that are wholly or partly derived from materials of biological origin and include a wide variety of products such as bioplastics (CEN/BT/WG 209). These types of products have been included among the six priority action lines on which the EC industrial strategy should be focused.61,62 As mentioned, considering that on the one hand, there is a great need to have precise information on socio-economic impacts of specific bio-based products and, on the other hand, there is the necessity to avoid a heavy burden on producer companies providing the primary data, the number of considered social topics needs to be limited. Consequently, a selection of the most relevant social topics to be assessed was undertaken. As a first step, the selection process was based on a review of the literature that included: i) relevant international frameworks, European projects and standards related to social sustainability and bio-based products (Table 6.1) ii) S-LCA peer-reviewed studies (Table 6.2) iii) S-LCA peer-reviewed studies specifically referring to bio-based products (Table 6.3). As a second step: (i) a stakeholder analysis for identifying and categorizing stakeholders according to their power and interest with regards to bio-based

172 Table 6.1

Chapter 6 Reference frameworks related to social sustainability.

Title

Brief description

UNEP-SETAC guidelines 2009

A framework for Social LCA, which has been adapted from the ISO standardized Environmental LCA Framework (ISO 14040:2006 and 14044:2006).

Global Reporting Initiative (GRI) standards

Consists of global standards for sustainability reporting, developed by an international independent organization, with a network-based structure and a Collaborating Centre of the United Nations Environment Programme (https://www.globalreporting.org/standards/). The standards, can be utilized by any organization that aims to present its impacts on the three pillars of sustainability.

Handbook for Product Social Impact Assessment56

Proposes a methodology based on a set a social topics associated with four stakeholder groups (workers, local communities, small-scale entrepreneurs and users) using a scale based approach.

Raw materials scoreboard 2018

Consists of a set of indicators specifically related to raw materials including those on social sustainability.

EN 16751:2015

Identifies sustainability criteria of bio-based products. With reference to social criteria: (i) labour rights (including labour rights, working and living conditions), land use rights and land use change, water use rights (including waterscarce areas) and local development.

Prosuite (Prospective Sustainability Assessment of Technologies) project59

Proposes a new methodology for assessing the sustainability impact of new technologies, including impacts on social well-being. It has been applied to biorefineries.

BioSTEP project (Promoting stakeholder engagement and public awareness for a participative governance of the European bioeconomy)a

Besides identifying the economic and environmental impacts of the bioeconomy, one of project tasks was also aimed at identifying its social dimension.

S2Biom project (Delivery of sustainable supply of non-food biomass to support a ‘‘resourceefficient’’ Bioeconomy in Europe)b

Proposes sustainability criteria and indicators for non-food biomass and includes the social dimension.

The Global-Bio-Pact project (Global Assessment of Biomass and Bioproduct Impacts on Socio-economics and Sustainability)c

Proposes a set of criteria and indicators for assessing socio-economic impacts of biomass production and several conversion chains.

a

See Deliverable 2.2 Summary report on the social, economic and environmental impacts of the bioeconomy, at http://www.bio-step.eu/results/. b See D5.4 Sustainability Criteria & indicators at https://www.s2biom.eu/en/publications-reports/ s2biom.html. c See Socio-Economic Impacts of Biomass Feedstock Production at https://www.globalbiopact.eu/ publications.html.

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Summary of the selected S-LCA related peer-reviewed studies utilized for identifying the list of social topics.

Authors

Brief description

Aparcana and Salhofer, 201342 Sureau et al., 201824

A test of S-LCA framework, developed by the authors, on three Peruvian recycling systems. A review of a broad range of criteria and indicators used by different existing S-LCA frameworks and how they were selected. Identification of the main social impacts emerging from the literature related to the mining sector, comparing them with general social criteria suggested by general frameworks for the social sustainability assessment, such as GRI standards and UNEP-SETAC guidelines. Present a methodological framework, by applying a S-LCA to a specific case study conducted on a jar of honey.

Mancini and Sala, 201857

D’Eusanio et al., 201846

Table 6.3

Summary of selected S-LCA related peer-reviewed studies on bio-based products utilized for identifying the list of social topics.

Authors Macombe et al., 2013

Brief description 63

Manik et al., 201364

Ekener-Petersen et al., 201476

Rafiaani et al., 201837 Falcone and Imbert, 20187 Siebert et al., 201815 Falcone et al., 201921

Investigation of the S-LCA methodology by focussing on biodiesel production, comparing different raw materials. Identification of social criteria that should be used to assess the sustainability of biofuels and potential hotspots within palm oil biodiesel in a province of Indonesia. Identification of potential hotspots and compares socioeconomic impacts of four types of vehicle fuels, i.e. two bio-based (biodiesel and bioethanol) and two fossil-fuel (diesel and petrol) utilized in the EU, with particular attention to Northern Europe and Sweden. A proposal of a systemic approach for a social sustainability impact assessment tailored to the biobased economy. Investigation of the social dimension of bio-based products, specifically focussing on the identification of criteria and indicators related to the consumer stakeholder category. Presentation of a set of social indices and indicators applicable to wood-based production systems in Germany. A proposal of a set of social criteria and indicators tailored to bio-based products, based on a participatory stakeholder involvement.

products development and (ii) the validation, through a participatory approach engaging the identified stakeholders, of the list of social impact categories, subcategories and indicators was undertaken.

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Chapter 6

Stakeholder Engagement in Social Sustainability Studies

The relationship between sustainable innovations and the role of stakeholders (i.e. workers, consumers, society, local community and value chain actors), in shaping such an innovation pattern has gained momentum in the scientific literature over the last few years.65–67 Notably, attention has been paid to stakeholder engagement practices for defining the most relevant aspects to be included in a sustainable innovation assessment.68,69 It should be noted that in comparison to the environmental assessment based on highly technical criteria, a social assessment may involve a broad spectrum of aspects affecting stakeholders both directly and indirectly. These may include human rights, working conditions, health and safety issues, equity, social responsibility, job creation and participation in society, social capital, access to basic needs and resources and happiness.70 Accordingly, the consideration of stakeholder perspectives when formulating the most relevant aspects included in a social sustainability assessment becomes even more important. According to Lelea et al.71 it is indeed necessary to implement a broad approach requiring not only the integration of scientific disciplines but also non-academic perspectives. In this vein, the involvement of stakeholders in initiatives associated with evaluation and assessment frameworks is driven by several motivations, including: i) the promotion of social learning; ii) the inclusion of multiple perspectives that improve understanding of problems and choice of solutions; and iii) the prevention or reduction of possible future social issues.72 It is worth noting that stakeholder engagement is also recognized as a good practice in the S-LCA literature.73 Despite stakeholders appearing mainly as the target of impacts, or as users (practitioners) and endusers (e.g. consumers and policymakers) of an S-LCA, it has been stressed that they can also play a crucial role in the decision-making process, being also active actors in the definition of relevant impact categories and indicators.74 In fact, several scholars have highlighted the role of stakeholders in validating, complementing and selecting the main topics and related indicators that are generally identified in a preliminary step through the review of literature, international conventions, policy documents, standards and assessment tools.24 Moreover, since social indicators are context-dependent, the participation of a wide range of stakeholders helps to adapt indicators to the real context more effectively than if merely based on expert opinions.74 This ensures a final set of higher quality indicators that brings together different perspectives, reflecting heterogeneous stakeholder values. In their review of scientifically published life cycle studies of bio-based products, Martin et al.75 reported that most of the reviewed studies gathered input from stakeholders to identify the most relevant topics and indicators, with specific reference also being made to social indicators. Indeed, stakeholder engagement practices have gained increased attention also in social life cycle studies specifically related to bio-based products.37,76 With regards to contextspecific SLCAs, several scholars41,77 suggest the integration of top–down,

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universally-recognized, social sustainability aspects with bottom–up, contextspecific, social aspects, drawing on the interests and preferences of the affected stakeholders.7 Therefore, they recommend taking into consideration topics (i.e. impact categories) and associated indicators which are legitimate and relevant to a wide variety of representatives of different institutions and organizations such as trade unions, employer associations, NGOs and policymakers.15 It should be noted that most of the studies mentioned in this section often used different techniques to involve stakeholders. In general, there are several ways for involving stakeholders, including online consultations, questionnaires and face to face interviews. However, stakeholder participation in more interactive contexts allows sharing broader perspectives,78 making the participatory approach particularly relevant.74,79 These considerations lead us to decide involving stakeholders by using the interactive workshops technique for validating the main social topics retrieved by literature review. An interactive workshop is defined as a structured set of facilitated activities for groups of participants who work together to explore a problem and find solutions over a specific period of time in one location.80 In this respect, the methodology through which stakeholders are identified and selected is essential in order to ensure the involvement of a wide spectrum of actors with different experiences, as well as the overall robustness of the validation exercise.71 Therefore, the following section will provide a description of how stakeholders were identified and then mapped.

6.4 Results and Discussion It is widely recognized in the S-LCA literature that social impacts may affect different stakeholder categories which represent all social groups of actors affected throughout the life cycle of a product. A stakeholder category is defined as a cluster of stakeholders that are expected to have shared interests due to their similar relationship to the investigated product systems.26 As mentioned in the previous section, different categories of stakeholders may also be involved in the decision-making processes related to an S-LCA and therefore engaged in a participatory process, cooperating with practitioners. For this purpose, drawing on the existing literature71,81,82 a stakeholder analysis has been undertaken in order to:  identify and define the characteristics of key stakeholders;  assess each stakeholder’s relative interest and power in bio-based products development;  ensure that all stakeholder categories are adequately represented by our participatory approach.

6.4.1

Stakeholder Identification and Classification

Workshop participants were identified through an extensive process that included: i) identifying bio-based products value chains; ii) defining the actors

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involved in each identified value chain; iii) associating all actors with the previously-mentioned categories of stakeholders, i.e. workers, consumers, local community, general society and value chain actors. Subsequently, in order to identify a first set of potential participants names, we focused on the grey literature reviewing government, industry and civil society organizations (CSOs) reports. The preliminary information gathered from the reports was further complemented by formal and informal meetings and webinars with key informants including, among others, experts involved in other EU projects concerned with the bioeconomy and representatives from clusters on Industrial Biotechnology and Green Chemistry. In fact, the collaboration with key informants allowed us to gain more exhaustive information and, consequently, to come up with an initial list of potential participants to the workshops. This preliminary list was augmented by means of snowballing methodology, as the identified participants were asked to recommend other suitable participants to be involved. A final list of 50 participants was compiled, encompassing a broad range of actors including consumers, consumer associations, bio-based related workers, processors, producers, retailers, international organizations, ministries and the local government, certification bodies, CSOs, researchers, academics and EU bio-based related projects representatives. Lastly, all these actors were associated with the categories of stakeholder under analysis, based on the following criteria: consumers and consumer associations were assigned to the consumer category, employees to the worker category while processors, producers and retailers were assigned to the value chain actors category. Moreover, drawing on Siebert et al.15 international organizations, certification bodies, civil society organizations (CSOs), researchers, academics and EU bio-based related projects representatives were associated with the society category, whereas ministries and the local government were associated with the local community category. Figure 6.2 summarizes the main steps undertaken to select the participants, as described previously.

6.4.2

Stakeholders Mapping According to Their Power and Interest

Once the identification and classification stage was completed, we proceeded to map our stakeholders by assessing their involvement towards biobased product development based on their level of power and interest. Mapping stakeholders’ involvement essentially means moving from the actor identification and classification under different stakeholder categories (see Figure 6.1) to the actor characterization, with the aim of deepening our knowledge of specific characteristics and the degree of heterogeneity in the selected stakeholders. Accordingly, we took into consideration interest and power, two key dimensions often assessed when performing a stakeholder analysis.81,83,84 Specifically, each stakeholder has a certain level of power and interest that determine her/his level of involvement in the development of bio-based products.

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Figure 6.2

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Main steps of workshops participants identification.71

With the aim of mapping the effective stakeholders’ involvement, we proposed 10 tailored variables able to capture stakeholders’ power and interest in the development of bio-based products. Each proposed variable can be found adherent or not to the investigated stakeholder taking the value 1 or 0, respectively. The following list represents the set of variables affecting stakeholders’ interest for bio-based product development:  Profitability (capacity for generating profits and benefits)  Bio-based jobs (capacity for generating jobs)  Health and safety (associated with the consumption and production processes of bio-based products)  Preservation of natural resources  Reduction of GHG emissions Likewise, in order to appraise stakeholders’ power with regards to biobased products development, the following variables are proposed:     

Control of strategic resources (financial and production resources) Possession of specialized knowledge and skills Reputation as perceived by other stakeholders Potential to influence public policies Medium to long term involvement (the timeframe the stakeholder is in the market/consuming bio-based products)

Following Olander and Landin,81 a stakeholder matrix is proposed (Figure 6.3), showing exemplarily how stakeholders might be differentiated

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Figure 6.3

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Stakeholder matrix based on power and interest.81

by the combination of their power and interest in the topic under investigation. Along this line, stakeholders can be placed in one of four groups of involvement according to their characterizations of power and interest:  Active: stakeholders who have high levels of both power and interest in the development of bio-based products;  Inactive: stakeholders who have a low interest and power with regards to bio-based product development;  Intentionally passive: stakeholders who have a high level of power but low level of interest in the bio-based product development;  Unintentionally passive: stakeholders who have a high level of interest in bio-based products but relatively low power. In addition, each participant was mapped based on his/her potential impact on the local or global community, i.e. whether his/her decisions or activities can affect the local or more global contexts. Following the assessment conducted using the identified variables, all stakeholders were placed, as illustrated by Figure 6.4, into the power– interest matrix. The stakeholders mapping is based on a two-step approach. First, a desk analysis allowed for the calculation of all criteria based on the information gathered through a wide variety of sources, especially websites, reports and key informants’ knowledge. Subsequently, in order to increase confidence in

Social Assessment

Figure 6.4

179

Mapping of the workshops’ participants. Shape represents the stakeholder category (i.e. circles ¼ workers; stars ¼ consumers; triangles ¼ society; squares ¼ local community; diamonds ¼ value chain actors); Shading represents the level of impact (dark grey ¼ stakeholders impacting on global community; light grey ¼ stakeholders impacting on local community).

our stakeholder analysis, a validation step was undertaken, at a later stage, during the interactive workshops. As a matter of fact, we asked participants to confirm the category within which they were associated and to corroborate our mapping based on their power and interest. As Figure 6.4 shows, more than 50% (i.e. 18) of involved stakeholders are positioned in the top right sector of the matrix, furthermore, it can be seen that about 90% (i.e. 29) of stakeholders are located within the two quadrants on the right, meaning that despite them not all being substantially powerful they at least show a keen interest in the development of bio-based products. For the purpose of our analysis, i.e. validating and integrating the identified list of social value items, this was a foreseen result. Indeed, it is desirable to have stakeholders with meaningful influence on decisions as well as those who are interested in a decision concerned with bio-based products but have little or no influence over decision-making processes. It is worth noting that as expected, the society was the most represented stakeholder category since this category encompasses a broader variety of actors, ranging from researchers, academics, certification bodies to civil society associations. This also applies to the other most represented categories, i.e. value chain actors (e.g. processors, producers and retailers) and

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the local community (e.g. national public authorities and ministries). Given this, we can state that overall all groups of different actors have had the same chances to take part in the interactive workshops. Moreover, we can also see that a fairly balanced involvement of stakeholders impacting on the global and local community has been achieved, despite the higher number of those affecting the local community. Finally, another interesting feature relates to the fact that all actors impacting on the global community are either active or unintentionally passive, whereas the ‘inactive’ is made up of all actors which have an impact on the local community.

6.4.3

Stakeholders Validation of Social Impact Categories, Subcategories and Indicators

The second methodological step took the form of four regional workshops held from July to September 2018 in Rome, Santiago de Compostela, Berlin and Turin, conducted within the framework of the Horizon 2020 funded project STAR-ProBio8 (Sustainability Transition Assessment and Research of Bio-based Products) with representatives of the stakeholder categories identified in the previous section. The choice of workshops locations – a within-countries is not random and is coherent with our aim. Essentially, three out of four workshops conducted took the form of regional workshops and for the sake of expediency (e.g. presence of task partners of the project, availability of facilities, etc.) were held at the headquarters of the involved project’s partners, namely Rome, Santiago de Compostela and Berlin. Moreover, one international workshop was carried out with supranational representatives of the stakeholder categories, as a side event of the ‘‘International Forum on Industrial Biotechnology and Bioeconomy’’ held in September 2018 in Turin. Table 6.4 shows the number of participants associated with the stakeholder categories for each workshop and the type of involvement in bio-based products. The 32 participants who joined the four workshops come from different organizations and belong to all the considered stakeholder categories. All stakeholder categories were properly represented showing a good degree of representativeness throughout different workshops with the only exceptions being in the consumer category in one workshop (TUB) and the worker category in two workshops (i.e. Berlin and Santiago de Compostela). Each workshop lasted from two hours to two and a half hours. A synthetic overview of the structuring of the workshop was sent in advance to each actor in order to facilitate the effectiveness of their knowledge sharing. Each workshop was held following the same protocol of action. Specifically, the workshops were introduced by two facilitators with a short presentation of the research project, its main objectives and related activities. This helped participants to better focus on the topic under investigation. The role of 8

http://www.star-probio.eu/

Social Assessment Table 6.4

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Workshops composition. Stakeholder categories – Consumers (C); General Society (GS); Local Community (LC); Value chain actors (VC); Workers (W). Involvement towards bio-based products – Active (A); Inactive (I); Intentionally Passive (IP); Unintentionally Passive (UP). Source: own elaboration.

Location

Participants

Rome (Unitelma Sapienza) Santiago de Compostela (USC) Berlin (TUB) Turin (IFIB)

6 8 9 9

Stakeholder categories C GS LC VC W

Involvement A I IP UP

1 1

4 5 7 2

1

2 2 4 4

1 2 3 1

1 3 2 1

1 1

2 1

2 1 2 6

facilitators is crucial for ensuring a well-structured meeting, focussing on a common goal and a common process for staying neutral, recording the group’s discussion and providing efficient ways to reach consensus and productive outcomes. Following Steinert et al.85 participants, after having shared their opinions, were asked to reach a consensus on the most important social topics for the social assessment of bio-based products. In doing so, each workshop was divided into two phases, namely: (i) validation of the social impact categories – participants were asked to discuss with their peers about the social impact categories and subcategories (provided by the facilitators) in terms of relevance for the evaluation of the bio-based product sustainability performance; (ii) brainstorming on the relevant social indicators – participants were asked to select the relevant social indicators (associated with the identified impact categories), for the social assessment of bio-based products. Participants had the chance to signal if any impact categories and/or social indicators were missing from the preliminary list proposed by facilitators. Figure 6.5 shows the different level of importance assigned to the identified impact categories. The participants were asked to appraise according to a three-option Likert scale (from 1 ¼ can be removed to 3 ¼ must be considered) the relevance of each impact category towards the social sustainability assessment of bio-based products. As recognized by the totality of respondents, the most relevant social impact categories for S-LCA of bio-based products are: health and safety, social acceptability and human rights. The discussion leads participants to acknowledge the strong relationship between these impact categories and their transversal importance for possible affected stakeholder categories. For example, the health and safety impact category is generally seen as very relevant since it permits the assessment of different stakeholders’ wellbeing. Considering the workers’ category, their health and safety are consequences of an adequate presence of labour rights and respect for human rights in the workplace. The occurrence of such positive conditions has a relevant impact on the social acceptability of bio-based products whose lack

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Figure 6.5

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Impact categories tailored to bio-based products. Dark grey circle ¼ should be considered; light grey circle ¼ can be considered; white circle ¼ can be removed.

might represent a dramatic barrier for a transition towards a bio-based economy.86 In contrast, the impact category migration is deemed slightly relevant and could thus be removed from the assessment. Subsequently, participants were asked to provide their opinions about the relevance of each impact subcategory and related indicators with the aim of looking at the social impacts towards the considered stakeholders’ categories. Table 6.5 shows the list of relevant subcategories and related social indicators, as judged by workshop participants, to measure the social impacts of bio-based products. Overall, workshop participants found most of the identified impact subcategories and indicators adequate for the assessment of the social sustainability of bio-based products. However, in order to restrict the number of indicators we asked them to provide a ranking priority. Specifically, the relevance of each impact subcategory was judged according to a four-option Likert scale (from 1 ¼ not relevant to 4 ¼ very relevant) to avoid any possible neutral answers on an odd-numbered scale. Scoring represents the percentage of workshop participants who find the social indicators associated to a particular subcategory very relevant and thus, indispensable for the social assessment.

Social Assessment Table 6.5

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Ranking of social impact subcategories and indicators tailored to biobased products.

Stakeholder category

Subcategory

Indicators

Score

Workers

Child labour

Presence of children working under the legal age of each country Workers are free to terminate their employment within the prevailing limits Annual salary per category Number of workers with high incidence or high risk of diseases related to their occupation

81%

Forced labour Fair salary Health and safety of workers

Consumers

Health and safety of Tests performed to check safety end users Land use Land use change Feedback mechanisms Number of actions to ensure stakeholder engagement Transparency Publication of a sustainability report Benefits of the product Products from natural source Public commitments Available certification or to sustainability documentation about issues sustainability issues

Local community Contribution to econo- Contribution of the product/ mic development service/organization to economic progress (revenue, gain, paid wages, R þ D costs in relation to revenue, etc.) Contribution to empLocal employment produced loyment Health and safety of Management efforts to minimize local community use of hazardous substances

72% 66% 72%

84% 78% 66% 72% 69% 66%

72%

91% 91%

General society

Food security

Edible feedstock diverted from 75% food chain to bio-based materials

Value chain actors

88% Fair competition in the Promoting flow of information market between alternatives available in the market

Looking at Table 6.4 it is possible to observe that all stakeholder categories were properly considered showing a good degree of representativeness of our proposed framework. With reference to workers, the most relevant impact subcategory is ‘‘child labour’’ where the ‘‘presence of children working under the legal age of each country’’ represents a possible threat that needs to be opportunely considered along the whole value chain. Consequently, information about the origin of feedstocks and related conversion processes are of

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paramount importance. Looking at the consumers category, the ‘‘health and safety of endusers’’ subcategory was ranked as very relevant by 84% of workshop participants. It can be drawn from the workshop discussion that the presence of tests performed to check product safety is highly appreciated by consumers. This seems to be the factor that most influences their willingness to pay for ecofriendly alternatives. When it comes to the local community, ‘‘management efforts to minimize the use of hazardous substances’’ and ‘‘local employment produced’’ are generally deemed very relevant for the appraisal of the social impacts of bio-based products. As a representative of a local community stated, when deciding to substitute conventional petroleum-based raw materials with bio-based ones, it is important to understand the origin of these materials and their possible adverse impacts in all parts of their life cycles, in order to minimize the use of hazardous substances. Moreover, with reference to general society, the relevance of food security emerged as an important issue when feedstock are diverted from food chain to bio-based materials. This is particularly true for lowincome economies where the emphasis is placed on the socio-economic situation and the performance of small-scale farmers completely neglects sustainability challenges.87 Finally, fair competition in the market was rated as the most important subcategory for value chain actors. According to the stakeholders, bioproducts should not have more market restrictions than fossil-based products.

6.5 Conclusions Sustainability represents one of the most important goals, if not the primary goal, for modern society, requiring major changes in production and consumption patterns, necessitating at the same time decisive and coordinated policy actions at global, regional and local levels. Notably, sustainability must be jointly conceived of three dimensions from which it is composed, i.e. environmental, social and economic. However, its socio-economic dimension has been under-investigated until recently. This is particularly true when restricting the spectrum of the analysis to the bioeconomy.88 Though, measuring and communicating social impacts is of utmost importance for promoting the market uptake of bio-based products, given that the economic cost of bio-based products is generally higher than fossil-based counterparts.89 Therefore, it is critical to demonstrate that bio-based products are likewise sustainable from social and socio-economic perspectives in order to enhance public acceptance and boost demand.90 Evaluating the sustainability performance of bio-based products, by means of effective assessment methods which encompass different stakeholder’s perceptions and impacts35 is important also to understand the strengths and weaknesses of alternative sustainability options.75 Against this background, and by means of a two-step methodology, the present chapter focuses on: (i) a stakeholder analysis for identifying and categorizing stakeholders according to their power and interest with regards to the development of bio-based products; and (ii) the validation, through a participatory approach engaging the identified stakeholders, of a list of social impact categories, subcategories and indicators.

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This allows for the definition of a social impact framework that, according to the insights of relevant stakeholders dealing in different ways with the bioeconomy sector, are worthy to be considered for an effective S-LCA of bio-based products. The validation exercise also serves the purpose of narrowing down the number of social indicators creating the basis for reducing the amount of data needed for carrying out the assessment and decreasing the associated costs. In particular, as recognized by the totality of participants, the most relevant social impact categories for S-LCA tailored to bio-based products are health and safety, social acceptability and human rights which encompass all groups of stakeholders (i.e. workers, consumers, local community, general society and value chain actors). Particularly, child labour, health and safety of endusers, contribution to employment, food security and fair competition in the market represent the most relevant social impact subcategories worth to be considered for an effective S-LCA of bio-based products. The choice of implementing a participatory method of investigation allowed the gathering of different sustainability viewpoints in order to make the proposed framework more shared and robust. However, given the broad variety of bio-based products already on the market, this general framework needs to be empirically tested. In spite of this, a first step has been taken. More effort is required to make this approach a valuable tool for policy makers and organizations to understand the social impacts at the basis of specific products. Building on the framework developed in this chapter, future steps should be taken, which focus on different case studies, for determining whether there are limitations and potential methodological drawbacks associated with the set of socio-economic topics and indicators proposed. The work presented is, thus, meant to be a first step towards the development of an efficient choice of social indicators tailored to bio-based products and their possible application as a framework of analysis.

Acknowledgements The authors are very grateful to the STAR-ProBio project (Sustainability Transition Assessment and Research of Bio-based Products) for their financial support. The project is funded by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 727740, Work Programme BB-01-2016: Sustainability schemes for the bio-based economy.

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68. F. T. Gillund, A. I. Myhr, A. Utskarpen and A. Hilbeck, Stakeholder views on issues to consider when assessing the sustainability of genetically modified potato, Int. J. Agric. Sustain., 2016, 14(3), 357–376. 69. R. Popper, M. Popper and G. Velasco, Towards a more responsible sustainable innovation assessment and management culture in Europe, Eng. Manag. Prod. Serv., 2017, 9(4), 7–20. 70. A. Colantonio, Measuring Social Sustainability: Best Practice from Urban Renewal in the EU, Vol. 1, EIBURS Working Paper Series, 2007. 71. M. A. Lelea, G. M. Roba, A. Christinck and B. Kaufmann, Methodologies for Stakeholder Analysis: For Application in Transdisciplinary Research Projects Focusing on Actors in Food Supply Chains: Reload Reducing Losses Adding Value, German Institute for Tropical and Subtropical Agriculture (DITSL), Witzenhausen, Germany, 2014. 72. K. L. Blackstock, G. J. Kelly and B. L. Horsey, Developing and applying a framework to evaluate participatory research for sustainability, Ecol. Econ., 2007, 60(4), 726–742. 73. S. Martire, V. Castellani and S. Sala, Carrying capacity assessment of forest resources: Enhancing environmental sustainability in energy production at local scale, Resour., Conserv. Recycl., 2015, 94, 11–20. 74. S. Mathe, Integrating participatory approaches into social life cycle assessment: the SLCA participatory approach, Int. J. Life Cycle Assess., 2014, 19(8), 1506–1514. 75. M. Martin, F. Røyne, T. Ekvall and Å. Moberg, Life Cycle Sustainability Evaluations of Bio-based Value Chains: Reviewing the Indicators from a Swedish Perspective, Multidisciplinary Digital Publishing Institute, Sustainability (Switzerland), Vol. 10, 2018, p. 547. ¨glund and G. Finnveden, Screening potential 76. E. Ekener-Petersen, J. Ho social impacts of fossil fuels and biofuels for vehicles, Energy Policy, 2014, 73, 416–426. ¨n, Social life cycle as77. A. Siebert, A. Bezama, S. O’Keeffe and D. Thra sessment: in pursuit of a framework for assessing wood-based products from bioeconomy regions in Germany, Int. J. Life Cycle Assess., 2018, 23(3), 651–662. 78. P. M. Falcone, Analysing stakeholders’ perspectives towards a sociotechnical change: The energy transition journey in Gela Municipality, AIMS Energy, 2018, 6(4), 645–657. 79. R. Sisto, A. Lopolito and M. van Vliet, Stakeholder participation in planning rural development strategies: Using backcasting to support Local Action Groups in complying with CLLD requirements, Land Use Policy, 2018, 70, 442–450. 80. K. Pavelin, S. Pundir and J. A. Cham, Ten Simple Rules for Running Interactive Workshops, PLoS Comput. Biol., 2014, 10(2), e1003485. 81. S. Olander and A. Landin, Evaluation of stakeholder influence in the implementation of construction projects, Int. J. Proj. Manag., 2005, 23(4), 321–328.

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82. C. Schiller, M. Winters, H. M. Hanson and M. C. Ashe, A framework for stakeholder identification in concept mapping and health research: A novel process and its application to older adult mobility and the built environment, BMC Public Health, 2013, 13, 428. 83. U. Berardi, Stakeholders’ influence on the adoption of energy-saving technologies in Italian homes, Energy Policy, 2013, 60, 520–530. 84. E. A. Chinyio and A. Akintoye, Practical approaches for engaging stakeholders: Findings from the UK, Constr. Manag. Econ., 2008, 26(6), 591–599. 85. Y. Steinert, M. Boillat, S. Meterissian, S. Liben and P. J. McLeod, Developing successful workshops: a workshop for educators, Med. Teach., 2008, 30(3), 328–330. 86. K. McCormick and N. Kautto, The Bioeconomy in Europe: An Overview, Sustainability, 2013, 5, 2589–2608. 87. S. L. Saravia-Matus, S. Gomez y Paloma and S. Mary, Economics of food security: selected issues, Bio-based Appl. Econ. J., 2012, 1, 65–80. ¨¨ 88. M. Sillanpa a and C. Ncibi, A Sustainable Bioeconomy: The Green Industrial Revolution, Springer International Publishing, 2017. 89. T. Haer, Environmental, Social and Economic Sustainability of Biobased Plastics. Biopolyethylene from Brazil polylactic acid from US 2012. 90. L. Elghali, R. Clift, P. Sinclair, C. Panoutsou and A. Bauen, Developing a sustainability framework for the assessment of bioenergy systems, Energy Policy, 2007, 35(12), 6075–6083.

CHAPTER 7

Indirect Land Use Change and Bio-based Products D. MARAZZA,* E. MERLONI AND E. BALUGANI University of Bologna, Interdepartmental Centre for Research in Environmental Sciences (CIRSA), via Sant’Alberto 163, Ravenna 48123, Italy *Email: [email protected]

7.1 Traditional and Novel Uses of Land The earth’s surface can be thought as a board game made of different patches, one for each type: oceans would make the most of the surface followed by terrestrial land divided into grasslands, deserts and barren lands, permanent snow and glaciers, forests, pastures, cropland and artificial surfaces. Agricultural land, and cropland in particular, has to be spotlighted on this imaginary board game as the most important piece. Humankind uses and shares this unique and finite patch of the earth’s surface. The most basic and elementary activity is to produce food and feed as well as non-food commodities such as textiles, wood and other products; these have been known for centuries as the traditional output of agricultural land use. Agricultural crops for human consumption belong to the category of crops that meet basic, physiological needs. Their demand is driven by dietary requirements with the average income level determining the ratio of food intake per capita. For this reason, the demand of food and feed crops is difficult to change and the related average food intake per capita is generally steady with notable important exceptions and qualifications such as meat and dairy products. As an example, cereals used to produce food such as Green Chemistry Series No. 64 Transition Towards a Sustainable Biobased Economy Edited by Piergiuseppe Morone and James H. Clark r The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

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bread and pasta were consumed at the world average rate of 158 kg per capita per year in 2010 and are projected to reach 160 kg in 2050 and 161 kg per capita per year in 2080. Meat was consumed at 38.7 kg per capita per year in 2010 and is projected to reach 49.4 and 55.4 kg per capita per year in 2050 and 2080 respectively.1 If the 2010 measured ratio is multiplied by the population of the corresponding year, the global demand of the respective commodity will around 1 billion tonnes of cereals and one quarter billion tonnes of meat in 2010. Differences and inequalities across regions are relevant, yet trends of food demand are similar. To understand the subject of this chapter, the reader is invited to think of an invisible strand connecting and balancing a hungry world together with land availability; such a strand would be the global demand for food and non-food commodities. Indeed, besides the traditional uses, a new industry has been developing, to extract from the biomass and synthetise bio-based chemicals and plastics, surfactants, lubricants, pharmaceuticals and to use forest-based products such as paper, fibres and materials for innovative composite and insulating materials. Also, among new uses, biofuels and bioenergy have to be included in the list of novel products. In the European Union only this industry accounts for an annual turnover of EUR 600 billion and employs 3.2 million people,2 and is still growing word wide with a compound annual growth of 2–3% per year,3 a pace double or triple that of food and feed which was below 1%. Most of the literature on this topic is addressing biofuels. There are many differences between biofuels and bio-based products with respect to the feedstock, end products, benchmarks and end-of-life pathways. They are summarised in the Table 7.1. The bio-based material industry is still in its infancy, with production volumes much smaller than those of biofuels.4 However, despite the differences, both biofuels and bio-based materials have biomass as a feedstock and ultimately land as a resource in common. Both biofuels and bio-based materials compete for land with the traditional uses. In the followings, it will be showed how such a competition leads to indirect land use change (iLUC) irrespective of the specific substance to be produced.

7.2 Direct and Indirect Land Use Changes The goal of this chapter is to introduce the reader to the effects of iLUC, i.e. land use change (LUC) driven by demand outside the boundaries of a system producing specific products, such as biofuels, bio-plastics or other bio-based materials. The accentuation is on LUC and a distinction will be introduced between direct and indirect effects. To better understand such a distinction, two possible change routes are illustrated. Route 1 (Figure 7.1). The demand for a specific good and/or service requires that a patch of land (Land use 1, in the figure) is changed from land originally not in use. By ‘‘not in use’’ it is intended that the land was not economically exploited at the time of the change; this might include a virgin or natural area or abandoned, marginal, idle land. It is easy to think to

194 Table 7.1

Chapter 7 Qualitative differences between biofuels and bio-based products.

Feedstock

End products

Biofuels

Bio-based materials

Few selected crops, mainly starch-rich crops and oil seeds as for conventional biofuels, many secondary raw materials as for advanced biofuels/ cellulosic fuels Few fuel types complying with fuels standards

Many different raw materials, including starch-rich crops, oil seeds, fibre-based materials, fungi, bacteria derived materials, and secondary raw materials

Lifetime Reference price and benchmarks

Less than 1 year Oil, renewable energies

End-of-life

Combustion

Incentive measures

In many countries biofuels are subsidised provided they contribute to renewable energy policies and environmental goals

Figure 7.1

Broad spectrum of materials and articles of solids, liquids, hard and softplastics, films 1–20 years Petrochemical counterparts of bio-based products which are manifold and non-homogenous Composting, material recycling and reuse Some materials are favoured because their fossil-based counterparts are subject to limitation such as the single plastic ban in the EU

Land use 1 provides the market with a specific good (filled circles) to meet a specific demand. Such a good is grown on a land that was changed from a land not in use. The eye icon indicates position of the system boundary and time reference.

Land use 1 as an area providing food or fibres or wood and/or having a recreative function. In such a route all impacts due to the change can be observed and measured within the system boundary, i.e. the area under study;5 also note that this area is directly affected by changes in demand; such area is referred as foreground in life cycle assessment (LCA) studies. Route 2 (Figure 7.2). The demand for a specific good and/or service is no longer met by the output from Land use 1 which was in turn changed into Land use 2. It is convenient to think to Land use 2 as a land providing the

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feedstock for a bio-based product. The market will then seek for an equivalent provision of the good and/or service formerly provided by Land use 1 and will make another area productive, thus entailing a change from Land cover/use 3 to Land use 1. In such a route we can clearly distinguish two changes; having fixed the system boundaries in Land use 2, the first change, from Land use 1 to Land use 2 is direct, the second, from 3 to 1 is indirect. In other terms the second change was indirectly provoked when changing land from use 1 to use 2. The total changed land is the sum of the areas related to Land use 1 and Land cover/use 3. Note that Land use 2 is referred as background in LCA studies. It should be noted that although the terms ‘land cover’ and ‘land use’ are sometimes used interchangeably, it is widely acknowledged that they refer to different concepts. ‘Land cover’ refers to the physical surface characteristics of the land, such as the type of vegetation or the presence of artificial structures. ‘Land use’ describes the economic and social functions of land to meet demands for food, fibre, shelter, and natural resources.6 To illustrate and apply this mechanism to the concerned topic, it is convenient to think of a fixed global demand in food, feed, textile commodities – the traditional commodities – as an element interacting with the rise of new needs expressed by new commodities such as bio-based materials and bioenergy, which are referred to as non-traditional. When portions of fertile, productive agricultural lands are converted to generate a non-traditional output, or in other terms the traditional output is

Figure 7.2

Land use 1, originally meeting a specific demand and its related market, is changed into Land use 2 providing a good (filled triangles) not meeting the market. Unmet demand causes the change from Land cover/use 3 to Land Use 1. The eye icon indicates position of the system boundary and time reference.

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displaced by novel uses, the food and traditional goods flow is reduced overall. When commodities turn relatively scarcer, due to a concurrent demand of novel goods on the same portion of land, a greater value is assigned by markets and governments to the scarcer goods, e.g. wheat and wheat lands.7 This is usually explained by the classic law of demand and supply in economics and it can entail a price change, a governmental policy, large private investments, change in trade. These factors affect crop production at a global scale are the means by which the effects are conveyed in other regions. Since markets are global so are the effects. These effects are also called leakage, spill-over or teleconnection and will be the subject of this chapter. Possible outcomes of the increased demand for agricultural land can be grouped into three categories8,9  Reduction: the global market adjusts to the diminished availability; this outcome can be further divided into two alternatives: (a) consumers underpinning the demand definitely renounce the good without any form of substitution; in this specific case, consumers completely diminish the food intake (e.g. meat); (b) consumers use substitute goods that absorb the higher demand; in this specific case, consumers substitute meat with dairy products or with protein-based vegetables. Both alternatives essentially depend on the elasticity of demand for goods; i.e. the extent to which the goods can substitute one another. It is noted that the second option entails potential consequences, including land expansion related to a higher demand of protein-based vegetables.  Intensification: the production system, at both the harvest and post-harvest phase, becomes more efficient and produces more output with the same quantity of inputs; this depends on yields at the farm level and the capacity to generate co-products at the industry level.  Expansion: if reduction or intensification do not take place, then a LUC occurs in order to meet the higher demand. This generally occurs outside the system boundaries of the studied system, as illustrated in Figure 7.2. Indeed, under these changed conditions, either because of higher prices or because of higher product value, farmers may find it convenient to convert or, to be more specific, change the use of their land and increase the land surface occupied by crops, forestry or pasture. In doing so, the increase in production will meet the higher food demand. This is, in essence, an iLUC: ‘‘a change in the use or management of land, which is a consequence of direct LUC, but which occurs outside the product system being assessed’’ as defined by the International Standard Organisation (ISO) in 2012.10

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Distinguishing between the direct and indirect causes of LUC, and, consequently, between direct and indirect LUC, is not straightforward because only the effects are recorded and measured. Directness and indirectness depend on the boundaries of the system under study and would imply the knowledge of the causes at the root of the change. With reference to route 2, whether a LUC is indirect can be decided only having established that has been caused by a change in demand upstream.

7.3 Evidence of iLUC Effects A few cases are described in the literature and they mainly refer to biofuels,11 with a few exceptions.12 The most extensively studied case, in terms of size and effects, concerns ethanol, a biofuel mainly obtained from maize. More specifically, the term ‘conventional renewable fuels’ in the US regulations applies to fuel ethanol derived from corn starch.13 Ethanol has been used in internal combustion engines for decades, since Ford’s Model T as a stand-alone fuel and most recently as a blending agent for motor gasoline. Blended into conventional petrol, it constitutes about 10% of the fuel burned by America’s vehicles today. Ethanol has been subsidised in the United States since 1978, when it was first granted a waiver to allow blending up to 3.6% oxygen by mass (i.e., E10) with gasoline. The 1990 Clean Air Act (CAA) amendments required the use of reformulated gasoline in certain areas starting in 1995 and consequently the use of ethanol increased. A significative boost was provided by ‘‘the Energy Independence and Security Act of 2007’’ which mandates that fuel sold or introduced on the market in the United States contains at least the applicable volume of renewable fuel, advanced biofuel, cellulosic biofuel, and biomass-based diesel, determined according to specific calendar year from 2006 through 2022.13 Besides federal incentives, state-specific initiatives exist also. The sum of the federal and state-based running incentives and laws, including grants, tax incentives, loans, leases, rebates and exemptions amounts to 309 policy measures. Observing the production of maize by sector of destination in Figure 7.3(a), the strong increase in ‘‘Other uses’’ since circa 2007 becomes evident, with a corresponding decrease of maize produced, used domestically for feed and exported. It is noted that in the case of the USA, the label ‘‘Other uses’’ used in the FAOSTAT set mostly corresponds to maize grain production and maize used for fuel ethanol.14 As an example, the maize grain production and maize used for fuel ethanol was 130 Mt in 2013 and 137 Mt according to the label ‘‘Other uses’’ in FAOSTAT which was used in the present analysis to ensure data consistency. In Figure 7.3(b) the USA maize yields and cultivated area increase linearly and cannot sustain the increase in ‘‘Other uses’’ demand completely, hence the decrease in exports; it is worth noting the outstanding USA yields (circa 12 t ha1 in 2013). Figure 7.3(c) depicts the Rest Of the World (ROW) and shows how the local

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Figure 7.3

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(a) USA produced maize by sector destination; (b) USA maize yields and area; (c) World produced maize by sector destination; (d) world maize yields and area. Elaborated upon FAOSTAT.52

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US biofuel production emerges as a leakage or spill-over effect: maize production increased for the sector of destination feed and ‘‘Other uses’’; ‘‘Other uses’’ was 189 Mt (72% corresponding to the USA) in the world in 2013. Finally, since yields increased linearly (global yields are about half of the USA yields) as shown in (c), the increase in the global demand for maize production due to the domestic demand in the USA is satisfied by an expansion in maize cultivated land in other countries. The dotted line in exhibit (d) represents the relative increase in maize area due to increase in ‘‘Other uses’’ consumption. The net change in the period 2007–2013 for ‘‘Other uses’’ in the world is around 12.6 Mha. In the same period, the net change in the US was 9.9 Mha. On this basis, one m2 used for biofuels corresponds to about 128 m2 in the ROW for the same use. Moreover, because 0.41 l of bioethanol can be produced at the pump from one m2 of productive USA maize land, this means that one litre corresponded roughly to land expansion of 3 m2 in the ROW due to yield differences between USA and ROW. The effects can be easily observed and decoupled from other drivers when they are of such a magnitude and when they can be attributed to a few players. Despite the lack of a certain causal relationship, few doubts remain that the biofuel policy in the USA is related to land expansion abroad.

7.4 Consequences and Magnitude of the LUC The causes of global deforestation are, mainly, cultivated land expansion (32.6%), pasture expansion along with ruminant livestock production (23.5%), and unexplained or mixed causes (18.6%) such as illegal logging and fuelwood collection. Generally, LUC occurs at the expense of primary or secondary forests, grasslands and other types of prairies.15 These systems are dominated by slow, conservative dynamics of the soil, contributing to the maintenance of the level of biodiversity and high rates of cycling of nitrogen, phosphorous and soil organic carbon (SOC). Croplands, on the contrary, are dominated by fast cycles and by external inputs such as fertilisers and pesticides; the carbon stock is consumed at a higher rate on cultivation and managed areas. As an example, the mean residence time of soil carbon under conventional tillage conditions is almost half than in the original grassland soils under no tillage.16 When LUC takes place and forests or grasslands are converted to croplands, above- and below-ground biomass and the total storage capacity of carbon are affected. The current total carbon storage capacity is estimated at 450 billion tonnes of carbon, whereas the potential could be more than 900 billion tonnes.17 This difference highlights the massive effect of land use and of cumulative LUC in the last 200 years. Deforestation and other land use and land cover changes are responsible for 53–58% of the difference between the current and potential biomass stocks17 while the remaining 42–47% difference is due to land management effects. This suggests that current land uses halve the amount of carbon that is potentially stored in

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terrestrial biomass. This is also due to the oxidation of the below-ground biomass. This is represented by the SOC such as plant litter – humified organic matter actively consumed by living organisms – and different forms of stored organic matter bound to mineral particles or within soil aggregates; the latter are more stable and have higher residence times than humus. In the croplands, because of tillage mainly, the SOC is exposed to the atmosphere and oxidises to CO2.18 This aspect is significant when permanent grasslands or woodland are converted to arable use. Land is both a source and a sink of greenhouse gases (GHGs) and plays a key role in the exchange of energy, water and aerosols between the land surface and atmosphere. Anthropogenic net CO2 emissions from LUC were 0.9  0.8 billion tonnes per year throughout the past decade. This represents about 10% of the total anthropogenic CO2 emissions due to fossil fuel combustion and cement production.19 Since there is a high causation relationship between LUC and GHGs changes, the latter has been adopted as the main indicator of the consequences of LUC. This will be expanded in the following sections. However, the issue is not only limited to GHG emissions; GHGs are rather an indication of a more severe and comprehensive issue known as loss of ecosystem services. Ecosystems provide food, fibre, fuel and materials for shelter; additionally, they provide a range of benefits to human societies.20,21 As an example, forests and woodlands can mitigate flooding by slowing down water discharge and snowmelt in temperate forests. Forests and grasslands create or regenerate fertile soils. Functional soils in these ecosystems also allow for mechanical filtration, groundwater recharge and protection against soil erosion, thus preventing desertification. Forest and grasslands regulate water purification. This regenerative process is essential in certain areas of the world and plays a role in the developing countries; as an example it has proven a relevant factor subsistence slash-and-burn farming systems and connected to the social structure of these countries.20 Far from being exhaustive on this matter, it suffices to remind that LUC entails changes in the quantity and quality of the ecosystem services. The LUC effects are cumulative sensu Meyer and Turner.22,23 Although the effects are not physically connected through a globally operating system, they can reach a scale and status when their occurrence in many places adds up and become evident when a certain threshold is reached. LUC for food and feed cumulates with the one for fibres, wood, bioenergy, biofuels and biomaterials. As an example, Meyer and Turner (1994) observed and reported that, slow, cumulative desertification has little apparent effect whereupon the landscape degrades rapidly. Also, in the case of LUC, despite being local, manifest at a global scale: carbon removal capacity has global effects and so are the increased GHG emissions. For purposes of climate modelling, an IPCC group24 has reconstructed the changes occurring since the 16th century and has modelled the global area changes from 2005 to 2100 (Figure 7.4). Here on is reported the results of their work in a scenario targeting transformations to stay below 2 1C from the years ahead.

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Figure 7.4

Time series of fraction of global land surface area from urban below up to the primary forest. For 2005–2100, land use and wood harvest information were based the particular model and scenario RCP2.6-IMAGE. Adapted from ref. 24 with permission from, Springer Nature, Copyright 2011.

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Most of the LUC effects, when affecting uncultivated and unmanaged areas, are reversible only in the long run. Koellner and co-workers,25 for example, estimated that old-growth forests, also called primary forests, take up to 1000 years for complete regeneration measured in terms of species diversity in the temperate zone, and to 100–300 years in tropical climates. The regeneration of biomass density at the original level can take even longer. Secondary forests – where secondary refers to land previously disturbed by human activities and is recovering – in the tropics can return to biomass carbon stocks comparable to old-growth forest within five to six decades but, again, the same is not the case for soil carbon.19 Recent studies have shown that, in many cases, LUC is synergetic to other drivers of change such as climatic change. According to the preliminary conclusions of an IPCC special report ‘‘at the regional scale, changing land conditions can reduce or accentuate warming and affect the intensity, frequency and duration of extreme events. The magnitude and direction of these changes vary with location and season (high confidence)’’.26 These studies suggest that climate change and LUC have the same direction of impacts and that the consequences of both are amplified by their interaction, with biodiversity and water recharge being the most affected.27,28

7.5 Assessment of LUC Impacts The direct and indirect impacts of LUC are assessed when performing a LCA either at the product level, to measure the sustainability performance of a product, or at the system level, especially for policy-making purposes. LCA assigns a good or service an impact on the basis of the findings like those presented in the previous paragraph. For example, a bio-based shopping bag can be assigned an impact in terms of GHGs emissions due to the inputs and emissions bound to the production cycle, the so-called flows. Power in the manufacturing phase is a flow accounted in the inventory that entails specific emissions. Flows are multiplied by a Characterisation Factor (CF), a standard factor converting all flows into impacts. In this way inputs related to land occupation and land management, such as tillage, pesticides and other inputs can be reported, and their effects are accounted in terms of GHGs emissions, affected biodiversity, freshwater eutrophication etc. In order to account these flows, the product undergoes an inventory phase where all inputs are enlisted. In Table 7.2, flows are divided into three sections: i) output, ii) from field to gate and ii) from gate to cradle; all flows are usually averaged on an annual base. In this generic example the entry corresponding to LUC reports that 0.1 m2 were changed in order to make one shopping bag.

7.5.1

LUC Impacts and the Time Dimension

The first question that arises is how to charge the shopping bag with LUC effects in the life cycle impact (LCIA) phase. The physical changes indeed vary over different timescales, e.g. biomass burning occurs at a less than one

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An example reporting a generic inventory to make one bio-based shopping bag and related flows.

Output Shopping bag Inputs from field to gate Energy for manufacturing ......... Transportation Land occupation Land Use Change (LUC) Pesticides Field emissions to air (e.g. NO2) Inputs from gate to cradle Transportation ........................................

Flow

Unit

1

unit

500 10 0.2 0.1 0.3 0.005

J J m2 m2 g g

year scale, decomposition of wood at a decade scale, and loss of soil carbon at a several decades scale. Biodiversity loss occurs in shorter time, more often between one and three years. In terms of GHG emissions, clearings and reduction of biomass density causes instantaneous changes. One option consists of allocating all the impacts due to the change in the first year t1 after the change, thus implying that the environmental report would be significantly different at t1 and all impacts in the following years would be neglected. On the contrary, if impacts are spread over a long period, their importance will be diluted, and reporting records or information can be lost from one reporting period to another. To resolve this issue, three approaches have been proposed: (a) amortisation or discounted values in a fixed amortisation period for all kinds of land conversions; (b) allocating different values at different times depending on a specific dynamic function; (c) dynamic accounting. The first solution is the most widely applied and consists of an annual amortisation of the initial carbon emissions using a 20 year period in accordance with IPCC suggestions for SOC emissions.29 The amortisation period is the number of years that the CO2 emissions in year t1 should be divided by to determine the yearly emissions. The information has to be kept for at least 20 years. The timing of emissions is, therefore, constant over time, e.g. one kg CO2 emitted in year t1 has the same effects, i.e. radiative forcing, as if it was emitted in t2. This solution has been included in many standards such as the PAS 2050 (2011).30 The third approach has been mainly applied to GHGs emissions and was proposed by Schmidt and co-workers.31 It is based on the dynamic net concentration of CO2 after an initial pulse into the atmosphere, modelled

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according to an atmospheric climate change model such as the Bern Carbon Cycle. Carbon is emitted at the right times, following a true carbon emission function and the effects of the emitted CO2 are accounted for separately. In this way, the timing of the effects of emissions is different at each time, e.g. one kg CO2 emitted in year t1 has to be multiplied by a specific characterisation factor, i.e. radiative forcing, at the time of the computation t2. Consequently, the first years are more important and the effects vary over time according to the carbon dioxide decay function in the atmosphere for a given time horizon.29 This approach does not specify the time horizon to be adopted. These three approaches have been applied or proposed only for the Climate Change impact category, while as for other impact categories such as Biodiversity, Terrestrial and Freshwater Eutrophication, there are no specifications.

7.5.2

Food vs. Fuel Debate

Some products and activities are focused and typically pointed out as iLUC drivers, while for others the same does not occur. For example, the expanding dairy production increases the demand for concentrate feed and for maize competing with croplands cultivated for food and, as a consequence, generates iLUC and related impacts.12 The same happens when urbanisation and infrastructure or building construction take place at the expenses of croplands, pastures or other productive lands. However, beside biofuels, it is hard to find cases in the literature where iLUC effects are accounted for. The reason why one litre of biofuel is assigned a cost in terms of iLUC while one litre of milk or 1 kg of concrete used in infrastructures is not, deserves an explanation. As for artificial infrastructures and urban land a first explanation is that their expansion is negligible with respect to the magnitude of cropland and pastures expansion.32,33 However, with respect to dairy products, there is not a substantial difference. A first argument is ethical, mostly reflected in the ‘‘food vs. fuel’’ debate. In accordance to ethical rules, staple food, feed and dairy products are assigned a higher priority in the hierarchy of human needs: while the food belongs to physiological needs, fuel belongs to a lower degree of priority. Within the goods classification, fuels are part of the energy security level. More importantly, while fossil fuels are accepted as a non-renounceable, a popular commodity, biofuels are considered a new technology, the fruit of few a more or less vested interests against the interest of the many, especially in the light of the subsidies they received.34 Recapitulating, the underlying ethical judgement against biofuels is that they would be immoral ‘‘because they sacrifice the vital interests of the poor to favour the convenience of a much better-off middle class’’.35 A major study on the ethical aspects of the ethanol production technologies was conducted by the Nuffield Council in the United Kingdom.36 The study is exemplary because it also reflects the principles contained in many certification schemes, analysed in the course of the project STAR-ProBio.

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It contains a list of guiding principles for the development and implementation of biofuels. These principles are: 1. Biofuel development should not be at the expense of people’s essential rights. 2. Biofuels should be environmentally sustainable. 3. Biofuels should contribute to the net reduction of total GHG emissions and not exacerbate climate change. 4. Biofuels should recognise the rights of people to just reward. 5. Costs and benefits of biofuels should be distributed in an equitable way. Going further the review on the ethical aspects, it can be convenient to focus on point 3. The most notable and relevant biofuels regulations, such as the Energy Security Act in 2007 and RED in 2009, have been enacted with the purpose to improve and reduce the GHG emissions of conventional fuels. To do so, both regulations provide subsidies and public money. When the emissions effects were received and perceived as counter-productive with respect to the initial goal and pertinent studies supported this effect, biofuels were flagged and stigmatised as flawed because of iLUC.

7.6 iLUC Assessment and Related Uncertainties Different approaches and models have been proposed in recent years to quantify iLUC and its impacts.2,37,38 In accordance with a classification suggested by De Rosa,38 the followings classes of models can be distinguished:    

ad hoc iLUC economic equilibrium models causal descriptive models biophysical models normative or rule-based frameworks

In between these classes there are also integrated or hybrid models which derive or embody selected methodologies belonging to the classes mentioned above. Ad hoc iLUC economic equilibrium models are formulated and built on the basis of classic economic concepts and theories. International agencies such as OECD, FAO, JRC have adopted and promoted them for policy-making purposes.39 Cause-effect relationships are caught mainly through statistical values and derived coefficients. Indeed, all available models have been applied to biofuels and provide many functions that are illustrated next. Causal descriptive models (CDMs) are deductive models. iLUC is explained as the output resulting from a chain of causes connecting land expansion to the product or process under study. They can be or should be falsifiable sensu Popper,40 i.e. they are formulated in such a way that the underling hypothesis can be tested by direct observation. CDMs are based

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upon the classic research model: observation, research design, data collection, data analysis interpretation and possibly validation; they do not follow a specific school of thought, in contrast to economic models. This distinction is underlined because economic modelling embodies core assumptions in the theoretical framework while CDMs describe and make explicit causes, effects and underlying assumptions. Biophysical models are also a class of CDMs; their adoption is meant to represent the biological and physical effects of land/crop responses like crop suitability and growth, erosion and water effects as well as use/management emission and consequent GHG emissions. Normative or rule-based frameworks are assertive and inductive sets of rules: they command actions or evaluations, based on previous crystalised experience.40 Certification schemes and normative standards containing rules on LUC accounting are a clear example.

7.6.1

Economic Equilibrium Models

As explained by Hertel and co-workers,11 most mainstream economic models are based on the concept of general equilibrium that establishes a link between demand for crops (and, hence, for land) and LUC. Leon Walras (1834–1910) recognised that there are many markets for any commodity and service and that these markets interact in complex ways with each other so that everything depends on everything else. These are the foundations of the so-called computable general equilibrium (CGE) models describing the motivations and behaviour of all economic players in an economy and the linkages among them (Figure 7.5). A CGE model is a system of equations, based on macro and micro economic theory, which describe an economy as a whole together with the interactions among its parts.

PRODUCERS Public spending for goods and services

Loans,finance market INVESTMENT FUNDS Private spending for goods and services

Funds GOVERNMENT

Savings

Taxes

Salaries

HOUSEHOLDS

Figure 7.5

Players and their connections modelled through a computable general equilibrium (CGE) model.

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A CGE model is made up by an aggregated database and a set of equation relating the quantities in the database. The database provides the values of all exogenous variables and parameters, and the initial conditions (values) of all endogenous variables. It has two components: (a) A Social Accounting Matrix (SAM), which describes the circular flow of income and spending in a national economy during a specific time period, with values of goods and services that are produced and the income generated from their sale, households income and spending, government tax revenues, saving and investment spending, international trade, etc. It is usually composed of: (1) producers that respond to demand by purchasing input, hiring workers, and using capital equipment, with the aim to maximise their efficiency; (2) households that purchase goods and earn wages, with the aim to maximise their utility (satisfaction); (3) the state, which collects tax revenues and uses them for (4) public sector investments. This describes the circular flow of the economy, e.g. the transition of value from producers to households and back to producers and the state, and from households back to producers again. (b) The elasticity parameter set, which describes the relationship between the various economic quantities, e.g. price and quantities, price and trade, etc. Since these two matrixes are usually very large (up to thousands of records), they must be aggregated to provide a summary of the economic activity, e.g. various industries are aggregated in representative groups, like ‘‘agriculture’’, ‘‘manufacturing’’ and ‘‘services’’. As illustrated in Figure 7.6, CGE models have found application in iLUC impact assessment for biofuels. In order to apply a CGE to quantify iLUC effects, they typically elaborate the information through three departments:  the economic layer includes the above described SAM; it serves the purpose of computing the effects of the introduction of biofuels in the fuel market and other connected markets, such as the food and feed market; effects of trades are also modelled at this level;  the agronomic layer, including yield effects, crop switching and area response and land suitability; at this level the geographical allocation of the effects is also realised;  the environmental layer where GHG emissions are calculated depending on the specific Agro-Ecological Zone where the effects take place. Each layer makes reference to a group of disciplines and theories such as economics, agronomy and geology and earth science. All layers make use of specific assumption discussed in paragraph 6.6.3.

ECONOMIC LAYER (SocialAccounting Matrix)

Figure 7.6

AGRONOMIC LAYER

ENVIRONMENTAL LAYER

Structure of an iLUC ad hoc equilibrium economic model partitioned in layers.

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Causal Descriptive Models

CDMs, like economic models, aim at linking the production of a product under study to the environmental impacts this production causes. The process, workflow and related chain of reasoning of a CDM as well as its application to a bio-based product is presented here. Following the reasoning of Brandao,37 an example based on consequential life-cycle thinking is given focusing on indirect impacts only. In this example, in the foreground system, a biomaterial not destined for food, is obtained from soybean oil that is usually placed in the domestic, reference food market for soybean, M1; on the other hand, M2 represents the domestic feed market where the co-product, a soybean meal, was initially placed. More generally, Mi is the reference market potentially affected by the production of the substituting good (i ¼ 1,2. . .n). Impacts are computed with reference to the production of an additional functional unit (FU) of a bio-based product in the studied system (foreground), for example one tonne of biomaterial and investigates effects in the affected markets outside the system boundary (background). The workflow includes the following activities. 1. Assess the importance of the demand response and decide if there is a significant change in the reference markets M1 and M2, i.e. decide if changes in the supply of the marginal products such as feed and food will activate a change of output in the background system.41 In this example, the supply of soybean to the food industry (M1) is diverted to the bio-based industry; the new processing still generates, as before the change, a co-product: soybean meal still supplies the feed market (M2). Depending on the share of these markets and economic preferences, a response may be triggered. In order to decide if a response is activated, thresholds or buffers have to be defined. 2. Determine the marginal products, such as feed, affecting the reference Mi markets. Soybeans, in this example, generate soybean hulls, a coproduct serving the feed market as soybean meal. 3. In each market, each product is assigned one or more marginal feedstock. Products can be made comparable if feedstocks are classified in accordance to their functionality in terms of nutritional values, calorific intake or other binding properties such as their reference price. A vector of feedstock, products and co-products and related properties is prepared. Some examples: a. from one tonne of soybean (feedstock): 0.8 tonne of dry soybean meal (product) are obtained containing 15 GJ of metabolisable energy and 0.30 tonne of protein and 0.2 tonne of soybean oil (co-product); b. from one tonne of palm oil: 0.86 tonne of refined vegetable oil are obtained (including oil from kernel), together with 0.14 kg of co-product consisting of palm kernel meal containing 2 GJ of metabolisable energy and 0.14 tonne of proteins;

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c. therefore, in terms of energy in meals, the palm kernel is equivalent to four units of soybean and, in terms of protein, to 0.15. In this way, the feedstock markets are transposed to a market of properties, such as the nutritional values, to make the products and coproducts and their feedstock inter-changeable and correlated. 4. Determine marginal quantities by solving the system of linear equations given specific assumptions. The goal is to optimise, using linear programming, the energy and protein intake as the sum of the energetic value, protein and cost, each multiplied by the specific factors, subject to binding conditions such as lowest cost, minimum protein intake, etc. In this example, an additional quantity of soybean production will a) decrease the use of palm oil in the market of feed M2 because the nutritional values and price of the soybean meal will make it preferable to the palm kernel meal; the assumption here is that palm oil production will decrease as well, being correlated with the production of palm kernel meal; b) it will increase the use of seeds oil (e.g. sunflower, rapeseed) in food market M1. 5. For the increased feedstocks, it is necessary to determine if changes in marginal production are met by changes in yields (intensification) or area (expansion). This is resolved using values obtained from the pertinent literature. 6. Determine the land use/land cover change. This is performed by assigning to each feedstock a prevalent country of origin or country main exporter or a cluster of prevalent exporters. These countries are associated to prevalent biomes and are identified from the literature and past market data. As a result of the process, the model output is a so-called characterisation factor (CF) expressing the land demand, for that specific path (country, feedstock, exporter country) per functional unit, FU, multiplied the amortisation period a (see paragraph 6.5.1). CFland ¼ haexporter_country  a  FU1

(7.1)

In order to translate that into a GHGs emission, it is necessary to model the ensuing LUC emissions. This step is similar to the environmental layer and can be called, ‘‘environmental box’’ (Figure 7.7). Different methods can be used for this translation. The most widespread is by tabulating emission factors for the corresponding affected biomes or agro-ecological zones as defined in the IPCC Guidelines for National Greenhouse Gas Inventories.29 Other models4 compute GHGs emissions making reference to the sole deforestation effects applying the so-called iLUC factors proposed in the European Union (EU) Directive 2015/1513,42 annex V and VIII and the IPCC values. These iLUC factors were originally reported per type of crop required (differing between starch-rich, sugar-rich, and oil-rich) as g CO2-eq. MJ1 and intended to be applied to the assessment. In order to apply these figures to

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Figure 7.7

Workflow of a consequential life-cycle thinking model to quantify the total expanded surface for specific land use/land cover (LULC) type to produce an additional functional unit (FU) of biomaterial.

non-energy products, it is necessary to multiply these factors by a carbon factor that can be obtained from: CFILUCcarbon ¼ CFlandexporter[haexportercountry  a  FU1]  CFcarbon[g CO2-eq.  ha1  a1] (7.2) An inter-comparison study for biofuels showed that this factor ranges from 10 up to 130 g CO2-eq. MJ1 in different studies.2 Besides the choice of the model and the scope of the analysis, the variations depend on factors such as: inclusion of the co-product, emissions from peatland, yield changes, choice of the proxy to measure LUC. It is noted that the so-called iLUC factor contribute only to climate change and, considering the carbon monoxide during clearings and burning, the photochemical ozone formation.

7.6.3

Uncertainties Related to Existing Models

Difficulties in modelling iLUC stems from the following problems:5,43 (a) local causes of LUC, such as the increased demand of crops for biomaterials production, can potentially spill over to any other part of the world; (b) spill-over is mediated by the global economy, with a huge number of interacting actors such as small farmers, big crop producers, crop traders, governments, etc. and variables such as climate, soil quality, macroeconomics, geo-politics, etc.; (c) iLUC is a dynamic process, implying delays in the spill-over effects, feedback effects and adaptive behaviour of the system, including societal response and policy making. This means that, when studying iLUC, all the world should be taken into account, resulting in a very large system with many interacting actors and many feedback effects. The different approaches to modelling iLUC need to tackle the complexity of the system under study: (a) ad hoc iLUC economic models focus on

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modelling a very wide system, in order to include all relevant actors, market sectors and products, at the cost of a decrease in details; (b) CDMs trade the complex and comprehensive modelling of the macro-economy with statistical analysis of the markets, i.e. using tabulated values for market trends, with more focus on the measurable physical chain of cause-effects (amount of material needed, actual historical change in land use), reducing the uncertainty of the parameters but increasing the number of assumptions made by the model.37 Most of these modelling approaches are static: they represent a snapshot of the global agricultural market for a certain year and assume constant conditions in time for all exogenous variables. The uncertainties within a model are usually related to the uncertainty in its many input variables and parameters, while the large difference in estimates between models are related to the different assumptions made in various models (model framework uncertainty, Figure 7.8). For example, the model GTAP applied to the route wheat-ethanol in Europe, showed an iLUC factor of 130 g CO2-eq. MJ1 per year; this value was the central value having a minimum of 30 and a maximum of 320. The model impact ranged between 20 and 90 with a central value of 40.43 In order to decrease the uncertainty of iLUC estimates, certain strategies are possible: (a) decrease the amount of uncertainty related to all relevant parameters of a model; (b) decrease the number of parameters and variables used in a model; (c) evaluate the assumptions used in a model and define different scenarios for different choices. It should be noted that model assumptions cannot be avoided, since, as already discussed, they are the only way to decrease the complexity of the system. There is a trade-off between these two types of uncertainties, as shown in Figure 7.8. Since the complexity of a model can be reduced by restricting its boundaries and considering a global scale, the uncertainty related to its framework,

Figure 7.8

Relationship between the uncertainties due to the model framework variables and parameters; with a depiction of the trade-off between model complexity (comprehensiveness) and uncertainty.

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such as the nature of the assumptions, remains the main problem (see assumptions in Figure 7.7). More specifically, most of the uncertainty related to iLUC is related to the definition of the actual impacts of LUC, which depends on which land use is being replaced. As an example, these models assume that any land expansion first displaces abandoned or fallow cropland and grassland, before forests are converted to cropland, etc. The definition of the trade elasticity parameters, the assumptions required about the source country for a certain increase in crop production, the substitutions chain of land use that take place the actual geographical location in a particular country that is affected by LUC, all require a set of assumptions with a certain related uncertainty. The large uncertainty related to the iLUC estimated land expansion within a specific iLUC model and between various iLUC models is the main reason for the adoption of simple rule-based methods to limit iLUC effects on the side of policy makers:44,45 instead of using black box models with many uncertain parameters and assumptions, the policy makers choice is to use conservative quantities such as the crop production, area of expansion, market shares, used as threshold values in order to define low and high risk biomasses. This approach is adopted in the REDII and illustrated here below.

7.6.4

The Renewable Energy Directive RED II: An Example of Normative Framework

In December 2018, the recast Renewable Energy Directive 2018/2001/EU46 (REDII) defined the European policy framework for climate and energy from 2020 to 2030 targeting the use of renewables by 2030 to 32% of overall energy use as a means to reduce GHG emissions. EU member states must require fuel suppliers to supply a minimum of 14% of the energy consumed in road and rail transport by 2030 as renewable energy provided sustainability requirements are fulfilled. The RED II also sets binding targets for the use of advanced, non-food-based biofuels to 3.5% by 2030, and a blending cap of 1.7% for advanced biofuels produced from waste fats and oils. Advanced biofuels will be double-counted towards both the 3.5% target and towards the 14% target. These targets are expected to be subsidised or supported by MS through incentives, exemptions or quota mechanisms. For the implementation of this approach, as required by the Directive, the Commission has adopted the Delegated Regulation (EU) 2019/807,47 through a delegated act mechanism, named ‘‘High indirect land-use change-risk feedstock and the certification of low iLUC-risk biofuels, bioliquids and biomass fuels’’ introducing novel and notable concepts for iLUC evaluation and acceptance. The most relevant one is the concept of additionality, developed through the Clean Development Mechanism in the framework of the Kyoto Protocol and analysed in a paper by Tim

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48

Searchinger. Additionality measures occur when the feedstock results from crops grown by means of improved agricultural practices or from areas which were previously not used for cultivation of crops. Improved agricultural practices means increases in yields above normal/ historical increase in yields over the 3-year period immediately preceding the year when the additionality measure was applied. Indeed, such measures must meet at least one of the following conditions: (i) their feasibility is proved irrespective of subsidies; (ii) they allow for cultivation of food and feed crops on abandoned land or severely degraded land; (iii) they are applied by small holders defined as users owning less than 2 ha of land; To be counted as renewables, biofuels must avoid iLUC effects that can occur when the cultivation of crops for biofuels or liquids substitutes previous agricultural land uses, displacing traditional production of crops for food and feed purposes in countries other than the one where the direct LUC has taken place and, eventually, substituting areas of high-carbon stock and peatlands. Even though a biomass can be classified as high iLUC risk it can still be certified as low iLUC risk. To that purpose the Delegated Regulation lays down specific criteria (Figure 7.9) both for:  determining the high iLUC risk feedstock  certifying low iLUC risk biofuels, bioliquids and biomass fuels. The Delegated Regulation defines as high iLUC risk feedstock raw biomass obtained from feed and food crops that expanded their area, with respect to 2008, by more than 100 000 ha and by more than 1% of their global area, and r10% of this expansion occurred on high-carbon stock land. Biofuels from feed and food crops with high iLUC risk cannot be counted as renewables and they will be phased out by 2030. Despite the qualification as high iLUC risk, a biofuel can still be accounted towards the 3.5% target and certified through a certification mechanism by either national verification systems or by one of the 17 voluntary schemes approved by the European Commission (EC) and valid in the EU so far. Member states will still be able to use and import fuels covered by these limits, but they will not be able to include these volumes for the purpose of their renewable targets. These limits consist of a freeze at 2019 levels for the period 2021–2023, which will gradually decrease from the end of 2023 reaching zero by 2030. Low iLUC risk feedstock can be qualified as such if the following criteria are met jointly: (a) biofuels meet GHG emission saving criteria; and (b) biofuels derive from biomass produced from additional feedstock obtained through additionality measures.

214 Mechanism and specific criteria, provided by the Delegated Regulation47 for determining high and low iLUC risk feedstock.

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Figure 7.9

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One way to ensure that biofuels meet the sustainability and GHG savings requirements of the REDII is to have the biofuel certified by a voluntary scheme. Therefore, the Directive, even if applied only to biofuels, bioliquids and biomass fuels, and does not cover other biomaterials, is an example of how iLUC modelling can be used to determine and measure the risk of the feedstock used to manufacture biomaterials.

7.7 The STAR-ProBio Approach: The SydiLUC Model Another possible way to study iLUC is to try to map the cause-effect chain in a dynamic framework, directly including the time dimension in the system under study. This can be done by considering not only the cause-effect links in the system but also by relating them to a certain rate, i.e. at what rate the cause occurs, and at what rate the effects take place; for example, the rate at which a certain material is produced and the rate at which its price changes as a consequence of the increase in its supply to the market. In this way, it is possible to include directly both delayed and feedback effects in the system. A delayed effect occurs whenever there is a certain time delay between a cause and its effects, e.g. the increase in bioplastic production uses up all the crop reserves for a certain agricultural year, causing the farmers to increase the production of crops in the next year. A feedback effect occurs whenever the effects of a certain event change the condition of the system, sending back a signal to the original cause and reinforcing or balancing it. For example, the increased consumption of a certain crop in one year drives up its price and results in a switch to another crop (or source material) by the industries that utilise it, hence decreasing the general demand for that crop. This is called a balancing feedback. Another example concerns the increase in the price of a certain crop that results in the increase in yields with a feedback signal to the price. This can be presented as a two-step sequence: firstly, the crop price increases, incentivising the farmers to invest in agricultural improvements to increase crop yields, secondly, and as a consequence of that, the production of the crop increases, and the increased availability of the crop on the market decreases its price, balancing the initial increase. In a dynamic model, the delayed effect is simply modelled by assuming the passage of a certain time between a certain cause and the materialisation of its effects, while the feedback effect is structured in time steps: during the first time step the cause generates the effects, in the second time step the effects send back a signal to the cause, re-adjusting the rate at which it occurs. An example of such a cause-effect dynamic system is shown in Figure 7.10: a change in bio-based material production has a direct effect on the amount of raw biomass stored, eventually depleting it. This has two effects: on the one hand, it increases the price of the raw biomass and, on the other, it gives the signal to farmers to increase the production of raw biomass. As shown in the Figure 7.10, the increase in the production of raw biomass can be achieved by increasing the area of agricultural land dedicated to the production of that particular biomass (agricultural expansion), or

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Figure 7.10

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Example of the core cause-effect to model the dynamics of bio-based products and land expansion, with arrows indicating the relationship flowing from causes to effects. The circle arrows represent feedback loops.

by increasing the agricultural yields of the crop used to obtain the raw biomass. The increase in agricultural yields is usually assumed to be the result of a biomass price increase. Indeed, within a short time frame, an increase in agricultural yield is usually achieved by increasing investment in fertilisers and irrigation (agricultural intensification). The result of both agricultural expansion and intensification is an increase in raw biomass production rates. This is an example of a reinforcing feedback loop. On the other hand, the price increase of that particular raw biomass makes it less competitive with respect to other raw biomasses or other source materials for the industries that utilise it (feed and food, for example). Therefore, these industries will substitute it with other source materials, with the result of decreasing the overall demand for biomass (balancing feedback loop). Some examples of the equations used in the SydiLUC model for the yields of transformation and for the price changes effects on production are: Bio based production ¼ K BioProd RBcons Raw Biomass Ð

Raw Biomass dt ¼ K RBcons RBprice Raw biomass price

(7.3) (7.4)

Where: Bio based production is the production of bio-based material, in mass per time [Mg per year]; Raw Biomass is the market supply of raw biomass, in mass per time [Mg per year]; Raw biomass price is the price of the raw biomass at a certain point in time [US dollars]; t is time [year]; KBioProd RBcons is the yield of bio-based material obtained from a unit mass of raw biomass [Mg Mg1]; KRBcons RBprice is the price elasticity of the raw biomass supply for a certain year. The use of a dynamic cause-effect framework, therefore, solves the problem of the introduction of time in modelling iLUC. However, two other

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problems remain: the complexity of the system and the large uncertainties related to the iLUC estimates. Indeed, including all possible cause-effect links in the iLUC modelling, for example all possible trade exchange between all world countries, taking into account all relationships determining the elasticity parameters of the market and its economic operator, such as crop producers, crop traders, bio-based industry, government, inflates the model until the number of equations and variables it contains is so large that every possible output can be obtained with a minimal adjustment of the model parameters. Essentially, the model is not predictive and, therefore, not useful anymore. Moreover, a large number of parameters, each with its own uncertainty, has the result of increasing the final uncertainty in the model estimates, until it is larger than the estimates themselves. SydiLUC is a model developed within the STAR-ProBio project to account for iLUC effects of the production of bio-based products, observing the REDII purpose to distinguish low from high iLUC risk feedstock. The SydiLUC model is a dynamic, global model that estimates, through a chain of cause-effects relationships, the predicted global change of land needed to meet the demand for raw biomass coming from a certain increase in the production of a specific bioplastic. With reference to model classification and structure presented previously, the cause-effect chain is divided into two parts: (i) a biophysical layer, which considers the mass of raw biomass needed to produce a certain amount of bioplastic and the area of land needed to grow that raw biomass; and (ii) an economic layer, which considers the effects of the change in demand and supply on prices, and the effect of prices on other parameters (e.g. on the yields, as shown in Figure 7.10). Within the model, all relevant parameters that are not directly calculated through cause-effect relationships are modelled as trends in time, e.g. the increase in crop yields not related to crop prices (usually due to technological advances and closure of the yield gap) is modelled using the linear trend of increase reported in the scientific literature.49–51 The model requires the definition of a goal: either a production target of a specific product or the production of a planned volume of material in time. The output is twofold: an accurate estimate of the land expansion in area units required to attain the goal and an estimate of iLUC risk. The land expansion estimate is expressed as the overall land required in hectares or multiples, e.g. [Mha], to attain the production goal reflecting the functional unit in mass, number of units or other. The output can be easily processed as shown in 7.5.2 and enter the same ‘‘environmental box’’ other models share. That would allow to compare model result with those obtained from other models. The second output is an estimate of the risk associated to these values. The variety of possible assumptions and scenarios are modelled with the SydiLUC model to obtain a range of estimates of land needed to sustain the increase in biomaterial production. These estimates are statistically divided

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Figure 7.11

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Example of the SydiLUC model output: the input (bioplastic production increase in time) causes, through a chain of effects, the increase of agricultural land required for the production of that amount of bioplastic. This projected increase in land is then assigned a grade of iLUC risk.

into grades which make up the iLUC risk classes. Therefore, to calculate the risk of iLUC related to a certain increase in the production of a certain bioplastic, the SydiLUC model is run with the set of input information for that specific case (e.g. polylactic acid (PLA) obtained from maize cultivated with traditional, intensive practices) and the estimated expansion of agricultural land is assigned to a certain iLUC risk class previously defined (Figure 7.11). In this way, the uncertainty in the model framework is kept explicit in the model output as ‘‘levels of risk’’ (instead of specific values of estimated impacts), represented by the size of the iLUC risk classes. The use of the model allows mainly for micro-level decision support for questions related to specific products, processes and sites or companies. It can be used also for strategic and policy decision support and policy impact assessment for sectoral industries.

7.8 Conclusion This chapter has discussed the question of LUC that is associated with any industry using biomass as a raw material, including the bio-based material industry which is still in its infancy and must address the indiscriminate use of biomass. Land is a finite resource, bound to the production of essential goods and providing the society with manifold services. The effects of LUC are translated as loss in primary and secondary forests; the growth of croplands and grazing lands entails also subtle and scarcely detectable effects due to changes in land management. Such changes manifest at a global scale are cumulative and climate relevant, reversible or irreversible in the long run and, in some cases, synergistic with climate change. A point of concern for the bio-based industry is that indirect effects arise because of changes in land already in use, mainly croplands, as a

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consequence of market feedbacks. In this regard wastes and agricultural residues have been considered not subject to this issue. While the use of wastes in the bio-based industry is safely iLUC-free, the use of agricultural residues currently used in the industry such as feed cannot be exempted from an in-depth scrutiny as the diversion of their use might entail market effects. Having showed how relevant these effects are, it has to be said that iLUC effects are not an exclusive issue of biofuels or bio-based materials. They also belong to other products and activities, such as artificial infrastructures and dairy products. However, due to proven counter-productive effects of first-generation biofuels, biofuels and bio-based materials are subject to specific attention and, in the case of the biofuels, to specific regulation. In this regard the Renewable Energy Directive was presented as an example of a normative approach. This regulation puts emphasis on the certification of low iLUC risk feedstock and thus to the implementation of methods aimed at establishing the extent of the risk to provoke iLUC effects. Certification schemes entail methods of measuring iLUC effects. The evaluation of iLUC s not a trivial problem; iLUC effects are not physically different from direct LUC – they cannot be observed and computed, for example, by satellite imaging. They have to be measured through modelling. Ad hoc iLUC economic equilibrium models paved the way showing how economic, biophysical or agronomic and environmental aspects should be integrated together to measure iLUC. For purposes of transparency and accessibility, a new class of models is being adopted; namely, the CDMs based on transparent assumptions and clear information processing. Both economic and CDMs, focus on the measure of the carbon emissions due to LUC and return an iLUC factor expressing GHGs emissions in g CO2-eq. MJ1. This chapter introduced a dynamic system model, named SydiLUC, developed in the context of the STAR-ProBio project, which aims at assessing iLUC risk, observing the REDII purpose to distinguish low from high iLUC risk feedstock.

Acknowledgements This work was funded by STAR-ProBio project, European Union’s Horizon 2020 research and innovation programme: Grant Agreement Number 727740. The authors thanks Daniele Terranova for the fruitful discussion on the LUC effects and their reversibility and for the elaboration of Figure 7.4.

References 1. FAO and ITPS, Status of the World’s Soil Resources: Main Report, FAO, Rome, Italy, 2015. 2. European Commission, Environmental Impact Assessments of Innovative Bio-based Product – Task 1 ‘Study on Support to R&I Policy in the Area of Bio-based Products and Services’, Luxembourg, 2019.

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35. P. B. Thompson, Agriculture, 2012, 2, 339–358. 36. Nuffield Council on Bioethics, Biofuels: Ethical Issues, Abingdon, Oxfordshire, 2011. ˜o, in Sustainability Assessment of Renewables-based Products, 37. M. Branda John Wiley & Sons, Ltd, Chichester, UK, 2015, pp. 81–96. 38. M. De Rosa, M. T. Knudsen and J. E. Hermansen, J. Clean. Prod., 2016, 113, 183–193. ¨rner and W. Britz, Environ. Res. Lett., 2018, 39. N. Escobar, S. Haddad, J. Bo 13(12), 125005. 40. Stanford University and Center for the Study of Language and Information (U.S.), Stanford Encyclopedia of Philosophy, Stanford University, 1997. 41. B. P. Weidema, N. Frees and A.-M. Nielsen, Int. J. Life Cycle Assess., 1999, 4, 48–56. 42. European Parliament, DIRECTIVE (EU) 2015/1513 of 9 September 2015 amending Directive 98/70/EC relating to the quality of petrol and diesel fuels and amending Directive 2009/28/EC on the promotion of the use of energy from from renewable sources, https://eur-lex.europa.eu/legal-content/EN/ TXT/HTML/?uri=CELEX:32015L1513&from=EN, (accessed 7 August 2019). 43. L. Marelli, D. Mulligan, R. Edwards and Institute for Energy (European Commission), Critical Issues in Estimating ILUC Emissions: Outcomes of an Expert Consultation 9–10 November 2010, Publications Office, Ispra, Italy, 2011. 44. R. Edwards, D. Mulligan and L. Marelli, Indirect Land Use Change from Increased Biofuels Demand, 2010. 45. L. Marelli, D. Mulligan and R. Edwards, Critical Issues in Estimating ILUC Emissions, 2011. 46. European Parliament, Directive (EU) 2018/2001 of the European Parliament and of the Council of 11 December, 2018 on the promotion of the use of energy from renewable sources OJ L 328, 21.12.2018, 2018. 47. European Commission, Commission Delegated Regulation (EU) 2019/807 of 13 March 2019 supplementing Directive (EU) 2018/2001 of the European Parliament and of the Council as regards the determination of high indirect land-use change-risk feedstock for which a significant expans, https://eur-lex.europa.eu/legal-content/EN/TXT/?qid=1565144427774& uri=CELEX:32019R0807, (accessed 7 August 2019). 48. T. D. Searchinger, Environ. Res. Lett., 2010, 5, 024007. 49. T. Iizumi, M. Yokozawa, G. Sakurai, M. I. Travasso, V. Romanenkov, P. Oettli and T. Newby, Glob. Ecol. Biogeog., 2014, 346–357. 50. M. K. Van Ittersum, K. G. Cassman, P. Grassini, J. Wolf, P. Tittonell and Z. Hochman, F. Crop. Res., 2013, 143, 4–17. 51. D. K. Ray, N. D. Mueller, P. C. West and J. A. Foley, PLoS One, 2013, 8(6), e66428. 52. FAOSTAT, http://www.fao.org/faostat/en/#data, (accessed 9 August 2019).

CHAPTER 8

Conclusions J. H. CLARK University of York, Green Chemistry Centre of Excellence, Heslington, York YO10 5DD, UK Email: [email protected]

In order to meet decarbonisation goals and implement a genuinely sustainable circular economy model, the chemical industry needs to transition from fossil to renewable sources of carbon. Current chemical production is dominated by petroleum where this largely uniform feedstock is separated using a quite simple process to give a small range of molecules that are the platform to very many products that are the basis of the modern consumer society. In a bio-refinery however, many feedstocks of widely varying composition are processed using many different technologies to give a wide range of bio-derived platform molecules. In this book we have considered how sustainability can be properly integrated into this transition by looking at environmental assessments, techno-economic assessments, social assessments and cross-cutting issues such as indirect land use. The choice of feedstocks for future, genuinely sustainable biorefineries is also key. The decrease in traditional primary resources, coupled with ever-increasing volumes of waste are two of the most significant factors that pose a major threat to achieving this sustainability. The uncontrollable growth of the last 50 years or so has been based on the linear economic model of ‘take-make-consumethrow away’, fuelled by a growing and very profitable industry that led to a huge growth in consumer demand.1,2 This rapid growth relied on cheap, readily available and abundant but largely non-renewable mineral resources. Being ‘renewable’ does not necessarily equate to being green and environmentally sustainable. An example of this is the use of palm oil in the Green Chemistry Series No. 64 Transition Towards a Sustainable Biobased Economy Edited by Piergiuseppe Morone and James H. Clark r The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

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production of biodiesel: the introduction of vast areas of commercial palm plantations in Southeast Asia has led to the irreversible destruction of natural ecosystems through deforestation, peatland destruction and consequential animal extinction.3 There is also the ever-growing concern about ‘food vs non-food’ which this and many other bio-fuel programmes, such as the use of corn to make bioethanol, have made worse. Second or third generation feedstocks should be converted using integrated, low environmental impact processes in order to generate multiple products fully utilising the carbon source of choice in a sustainable manner. Bio-wastes are especially attractive and can include a host of different waste streams although the organic composition may not be all bio-based due to the growing presence of non-renewable plastic polymers in waste streams. We need to be able to cope with this contamination ideally seeing the waste plastics as another (carbon rich) feedstock. The most abundant bio-derived feedstock on the planet is lignocellulosic biomass, with a significant proportion of the total ca. 180 billion MT already available as wastes from established industries like paper and pulp. Its volume makes it very attractive for substituting ultimately all of the ca. 1 billion MT of petroleum used in the chemicals industries. One of the largest types of bio-wastes around the world is food supply chain waste with over 1 billion MT per year according to reports from the United Nations Food and Agriculture Organisation.4 This waste is from primary production (agricultural residues) through to secondary production and waste from human consumption. The target for sustainable and socially acceptable biorefineries is unavoidable food waste including inedibles such as peels, stones and skins.5 The use of microalgae for the manufacture of chemicals and energy has some significant advantages when compared to terrestrial lignocellulosic plants including higher photosynthetic efficiency leading to higher growth rates and all year-round production. Most microalgae exploitation to date has utilised the lipophilic fraction for biodiesel production but this fraction is only about 10% of the total weight of the biomass leaving a lot of biowastes.6 The presence of biologically-fixed nitrogen opens the door to highvalue nitrogen-containing compounds that can be important molecules in the pharmaceutical and textile industries. Municipal solid waste (MSW) includes plastics, glass, metals, food, and textiles. In Asia and North Africa, for example, it is dominated by organic waste (ca. 61–62%).7 It has been estimated that more than a million MT is generated, each year and this is expected to at least double in the next 5 years. MSW often ends up in landfills (ca. 90% in developing countries) and is a serious environmental problem, as its decomposition contributes significantly to greenhouse gases, metal poisoning and other environmental impacts. Currently, the major waste management valorisation strategies for this waste are incineration for energy recovery and the generation of syngas as a chemical feedstock8 but these strategies represent a loss of valuable functionality that adds to the value of chemical products.

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The bio-economy, the bio-based products that it leads to and now the circular economy that aims to keep resources in circulation for as long as possible have become major initiatives in many regions encouraged by legislation, incentives and research. Our experience with bio-fuels has taught us to be very careful over the choice of feedstocks and the potential their use has on other critical issue such as food production. True sustainability needs to go far beyond using renewable resources and an increasing emphasis on waste feeds will also help to solve the increasing problem of pollution. Bio-waste based biorefineries within a well-managed and monitored bio-economy offer us a unique opportunity to make a major step change in societies development and decouple growth from resource consumption.

Acknowledgements The author is very grateful to the STAR-ProBio project (Sustainability Transition Assessment and Research of Bio-based Products) for its financial support. The project is funded by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 727740, Work Programme BB-01-2016: Sustainability schemes for the bio-based economy.

References 1. J. H. Clark, From waste to wealth using green chemistry: The way to long term stability, Curr. Opin. Green Sustain. Chem., 2017, 8, 10–30. 2. A. G. Olabi, Circular economy and renewable energy, Energy, 2019, 181, 450–454. 3. K. T. Tan, K. T. Lee, A. R. Mohamed and S. Bhatia, Palm oil: Addressing issues and towards sustainable development, Renewable Sustainable Energy Rev., 2009, 13, 420–427. 4. K. Paritosh, S. K. Kushwaha, M. Yadav, N. Pareek, A. Chawade and V. Vivekanand, Food Waste to Energy: An Overview of Sustainable Approaches for Food Waste Management and Nutrient Recycling, BioMed. Res. Int., 2017, 2017, 19. 5. P. Morone, A. Koutinas, N. Gathergood, M. Arshadi and A. Matharu, Food waste: Challenges and opportunities for enhancing the emerging bioeconomy, J. Cleaner Prod., 2019, 221, 10–16. 6. Y. Yang, H. Zhong, R. He, X. Wang, J. Cheng and G. Yao, Synergetic conversion of microalgae and CO2 into value-added chemicals under hydrothermal conditions, Green Chem., 2019, 21, 1247–1252. 7. A. S. Nizami, M. Rehan, M. Waqas, M. Naqvi, O. Ouda, K. Shahzad, R. Miandad, M. Z. Khan, M. Syamsiro, I. M. I. Ismail and D. Pant, Waste biorefineries: Enabling circular economies in developing countries, Bioresour. Technol., 2017, 241, 1101–1117. 8. K. Latha, R. Velraj, P. Shanmugam and S. Sivanesan, Mixing strategies of high solids anaerobic co-digestion using food waste with sewage sludge for enhanced biogas production, J. Cleaner Prod., 2019, 210, 388–400.

Subject Index anaerobic digestion (AD), 63, 114 atom economy (AE), 48 BASF eco-efficiency indicators, 47–48 biobased plastic waste for materials recovery, 116 for organic recycling, 116–117 biobased polybutylene adipate terephthalate (PBAT), 63 biobased polybutylene succinate (bio-PBS) resin, 60 biobased product-oriented process, 94 biobased products pathways from raw material feedstock, 96 supply chain of, 89 biodegradability, 141 bioeconomy, 110, 135 central goals of, 133 circular bioeconomy, 110 principles of, 55 resource use, 84 sustainable growth, 1 targets, 59 biomass, resources of, 93 bioproducts maize, 30 sugar beet, 31 BoPLA (biaxially oriented PLA), 58 packaging film, 68–71 business-to-business (B2B) markets, 141 causal descriptive models (CDMs), 205 certification scheme, 137

certification system, 137 chemical recycling processability, 115 circular economy (CE), 110 Circular Economy Package (CEP), 110 climate change, 166 compostability, 115 conformity assessment system, 137 cost-effective biomass feedstock, 85 downstream environmental assessment BASF eco-efficiency indicators, 47–48 conventional LCA indicators, 51–52 Dow’s chemical index, 48 existing efficiency and circular metrics, 52–53 feedstock intensity, 54 hazardous chemical use, 53–54 waste factor, 54–58 gate-to-gate impact and resource efficiency agricultural mulch film, 72 BoPLA packaging film, 68–71 polymer resin, 72 goal, scope and functional unit, 60–61 green chemistry metrics, 48–49 LCA complementary efficiency indicators comprehensive LCA, 50 cross-functionality, 51

Subject Index

easier implementation and interpretation, 50–51 sustainable development targets, 51 LCA of STAR-ProBio case studies, 58–60 literature review, 45–47 material circularity indicators – Ellen MacArthur Foundation, 50 packaging films, 61–63 allocation methods, 67 mulch films, 63–65 out of scope, 67–68 polybutylene succinate (PBS), 65–67 recovery and reuse of resources, 67 transformation efficiencies, 67 transportation, 68 Portfolio Sustainability Assessment (PSA) methodology, 49–50 process description, 61 resource efficiency and waste minimisation strategies, 73–74 proposed sustainability analysis methods, 74–75 scenario description, 61 Dow’s chemical index, 48 E-factor, 48 EN16751:2015: Biobased products: Sustainability criteria, 46 end-of-life (EoL), 46, 81 engineering design process, 94, 97 environmental life cycle assessment (E-LCA), 167 environmental sustainability of maize, 24–28 of sugar beet, 17–22 environmental uncertainty, 5

227

EU-based value chains, 90 extended producer responsibility (EPR), 110 feedstock selection, 105 fermentable sugars flow diagram of, 13 life cycle assessment (LCA), 28–29 allocation, 32–33 maize and stover processing, 29–30 selected environmental impact categories, 32 sugar beet processing, 30–32 maize, 22–28 sugar beet, 16–22 financial feasibility, 118 financing problems, 81 functionality uncertainty, 4 greenhouse gas (GHG) emissions, 166 gross profit, 101 health uncertainty, 5 hotspots analysis, 37–38 iLUC. See indirect land use change (iLUC) indirect land use change (iLUC), 192–193 assessment and related uncertainties, 205–206 causal descriptive models (CDMs), 208–210 economic equilibrium models, 206–207 Renewable Energy Directive 2018/2001/EU (REDII), 212–215 uncertainties, 210–212 economic equilibrium models, 205, 210, 219 direct and indirect land use changes, 193–197

228

indirect land use change (iLUC) (continued) effects, 197–199 STAR-ProBio Approach: The SydiLUC Model, 215–218 internal rate of return (IRR), 101 International Reference Life Cycle Data System (ILCD) Handbook, 45 International Sustainability and Carbon Certification (ISCC 202: Sustainability requirement), 46 investment cost, 101 land use change (LUC) assessment of, 202 food vs. fuel debate, 204–205 and time dimension, 202–204 consequences and magnitude of, 199–202 life cycle assessment (LCA), 8, 13–15, 90 of fermentable sugars, 28–29 allocation, 32–33 maize and stover processing, 29–30 selected environmental impact categories, 32 sugar beet processing, 30–32 life cycle costing (LCC), 167 life cycle impact assessment (LCIA), 32 life cycle sustainability assessment (LCSA), 167 linear low-density polyethylene (LLDPE)-based mulch film, 59 low-density polyethylene (LDPE), 65 maize into bioproducts, 30 environmental profiles, 35, 36 environmental sustainability of, 24–28 mass and economic values for, 33 sugar production from, 34

Subject Index

market assessment biobased economy quality infrastructure, 137–138 sustainability assessment schemes, 137–138 sustainability transition, 134–137 user acceptance, 138–139 buying decisions, 155–156 end consumers, 147 professionals’ sustainability preferences, 147 buying decisions, 147–150 preferences regarding environmental aspects, 150–151 preferences regarding social and economic aspects, 151–154 research methodology, 145–147 for specific products, 156–159 sustainability certification, relevance of, 154–155 sustainable biobased products environmental topics, 141–142 fundamental characteristics of, 140–141 research gaps, 144 social and economic criteria of, 142–143 materials recovery, 112 mechanical recycling processability, 114 net present value (NPV), 101 net profit, 101 operating cost, 101 organic mass and biogas recovery efficiency, 119 organic recycling, 112 organic recycling products quality, 117

Subject Index

229

reaction mass efficiency (RME), 48 recovered biobased materials, 118 Renewable Energy Directive (RED), 45 resources utilisation efficiency, 120 resource uncertainty, 4

sugar beet into bioproducts, 31 environmental profiles, 35 environmental sustainability of, 17–22 mass and economic values for, 33 sugar production from, 34 sustainability, 82 sustainability assessment schemes, 137 sustainability certification scheme, 137 sustainability of organic recycling, 120 Sustainable Chemical Index (SCI), 48 Sustainable Development Goals (SDGs), 135, 166 Sustainable Materials Management (SMM), 110

secondary market, traceability schemes of, 123 SMGP-PEF (Single Market for Green Products-Product Environmental Footprint), 45 social assessment bio-based products, 171–173 social sustainability studies, 174–175 methodology main features, 168–170 measurement challenges, 170–171 stakeholder identification and classification, 175–176 stakeholders mapping, 176–180 stakeholders validation, 180–184 social life cycle analysis (S-LCA), 82, 88 social sustainability, 81 social uncertainty, 5 sorting efficiency, 114 STAR-ProBio, 8, 45

TEA. See Techno-Economic Assessment (TEA) technical uncertainty, 4 Techno-Economic Assessment (TEA), 81–82 recapitulation, 97–98 in sustainability aspects, 94–97 techno-economic efficiency and process profitability biorefinery development, 107–108 process improvements, 106–107 utilisation of alternative crude renewable feedstock, 107–108 Techno-Economic Sustainability Assessment (TESA), 83 definition, 80–81 natural renewable resources, 83–85 in relation to biomassbased resources, 86–88 and resource use efficiency, 85–86

payback period (PBP), 101 photosynthetic efficiency, 224 polybutylene succinate (PBS), 59, 65 polylactic acid (PLA), 58 polymer resins, 65, 72 polypropylene (PP), 65 polystyrene (PS), 65 Portfolio Sustainability Assessment (PSA), 49 process mass intensity (PMI), 48 production cost, 101 quality infrastructure, 137

230

Techno-Economic Sustainability Assessment (TESA) (continued) objectives, 88 post-consumer biobased products methodology, 109–113 post-consumer/postindustrial biobased products, 113–123 renewable feedstock resources to biobased products methodology development, 98–104 principle, criteria & indicators, 105–109 scope of, 105 system boundaries, 104–105 resource use in abiotic resources, 93–94 biomass resources, 92–93 supply chain and life cycle material flow scheme, 88–92 techno-economic viability, 102 technological improvements, 105 TESA. See Techno-Economic Sustainability Assessment (TESA)

Subject Index

uncertainty, 3–4 bridging, 6–7 environmental, 5 map, 7 mapping, 6–7 social, 5 techno-economic, 4 upstream environmental assessment sugar sources maize, 21–28 sugar beet, 16–22 value chains, 90, 95 waste materials recovery, 120–121 organic recycling, 121 waste factor energy intensity, 56–58 process material circularity, 56 product renewability, 55 WBCSD. See World Business Council for Sustainable Development (WBCSD) World Business Council for Sustainable Development (WBCSD), 49