Current Developments in Biotechnology and Bioengineering: Photobioreactors: Design and Applications 0323999115, 9780323999113

Table of contents :
Cover



Contents
Contributors
Preface
SECTION
I - General & design considerations
1 - Photobioreactors: An introduction
1.1 Introduction
1.2 Types of photobioreactors
1.2.1 Tubular type photobioreactors
1.2.2 Flat panel photobioreactors
1.2.3 Column types photobioreactors
1.2.4 Soft frame photobioreactors
1.3 Factors affecting microalgae productivity in photobioreactors
1.4 Modeling and simulation of photobioreactors
1.5 Applications of photobioreactors
1.5.1 Photobioreactors for microalgae-based wastewater treatment
1.5.2 Cultivation of diatoms in photobioreactors
1.5.3 Cultivation of astaxanthin in photobioreactors
1.5.4 Production of biopolymers in photobioreactors
1.5.5 Production of biohydrogen in photobioreactors
1.6 Conclusions and perspectives
References
2 - Design and scale-up of photobioreactors
2.1 Introduction
2.2 Microalgae cultivation scaling-up process
2.3 Photobioreactor (PBR) design and its scalability principles
2.3.1 Vertical tubular photobioreactors
2.3.1.1 Bubble column photobioreactors (BCPBRs)
2.3.1.2 Airlift photobioreactors (ALPBRs)
2.3.2 Flat panel photobioreactors (FTB/FPPBRs)
2.3.3 Horizontal tubular photobioreactors (HTPBRs)
2.3.4 Helical type photobioreactors (HPBRs)
2.3.5 Stirred tank photobioreactors (STPBRs)
2.3.6 Hybrid type photobioreactors
2.3.7 Flat-panel airlift photobioreactors (FPAPBRs)
2.3.8 Internally illuminated photobioreactors (IIPBRs)
2.3.9 Low-cost plastic bag photobioreactors
2.4 Challenges
2.5 Conclusions and perspectives
References
3 - Types of photobioreactors
3.1 Introduction
3.2 Vertical column photobioreactors
3.2.1 Stirred tank photobioreactors (ST-PBRs)
3.2.2 Bubble column photobioreactors (BC-PBRs)
3.2.3 Airlift photobioreactors (A-PBRs)
3.3 Horizontal tubular photobioreactors (HT-PBRs)
3.3.1 General description
3.3.2 The mixing in HT-PBRs
3.3.3 Innovative HT-PBRs
3.3.4 Helical tubular photobioreactors
3.4 Flat plate photobioreactors (FP-PBRs)
3.4.1 General description
3.4.2 The mixing in FP-PBR
3.4.3 Innovative FP-PBRs
3.5 Flat panel-airlift photobioreactors (FPA-PBRs)
3.6 Plastic bag photobioreactors (PB-PBRs)
3.7 Taylor vortex photobioreactors (TV-PBRs)
3.8 Torus photobioreactors (T-PBRs)
3.9 Internally illuminated photobioreactor (II-PBRs)
3.10 Other innovative photobioreactors
3.11 Conclusions and perspectives
References
4 - Factors affecting the microalgal biomass productivity in photobioreactors
4.1 Introduction
4.2 Factors influencing the general productivity in photobioreactors (PBR)
4.2.1 PBR design considerations
4.2.2 Light illumination and intensity
4.2.2.1 Light intensity
4.2.2.2 Light path
4.2.2.3 Light utilization
4.2.3 Effect of pH
4.2.4 Temperature
4.2.4.1 Temperature versus productivity
4.2.5 Microalgal strains
4.2.6 Trophic modes of cultivation
4.2.7 Operation modes of cultivation
4.2.8 Mixing, heat, and mass transfer
4.2.8.1 Mass transfer characteristics
4.3 Factors influencing the process scale-up
4.3.1 Engineering parameters
4.3.1.1 Light regime
4.3.1.2 Mixing rate
4.3.1.3 Hydrodynamic stress
4.3.1.4 Mass transfer
4.3.2 Operational parameters
4.3.2.1 Carbon and mineral nutrient requirements
4.3.2.2 pH control
4.3.2.3 Thermal regulation
4.4 Conclusions and perspectives
Acknowledgment
References
5 - Photobioreactors modeling and simulation
5.1 Introduction
5.2 Stoichiometry and kinetics of microalgal growth
5.2.1 Composition of microalgal biomass
5.2.2 Kinetics of microalgal growth
5.2.3 Kinetics of nutrient consumption
5.3 Photobioreactor modeling
5.3.1 Light supply
5.3.2 Temperature
5.3.3 Multiple factors
5.3.4 Medium pH
5.3.5 Dissolved inorganic carbon
5.4 Photobioreactor simulation
5.5 Conclusions and perspective
Acknowledgements
References
6 - Photobioreactors for microalgae-based wastewater treatment
6.1 Introduction
6.2 Phycoremediation potential of microalgae—assimilatory nutrients removal
6.3 Open systems for microalgae-based wastewater treatment
6.3.1 High rate algal ponds (HRAP)
6.3.2 Algal turf scrubbers
6.3.3 Advantages, disadvantages, and opportunities of open reactors for efficient and economic wastewater treatment
6.4 Closed photobioreactors for microalgae-based wastewater treatment
6.4.1 Vertical column, tubular and flat plate PBRs
6.4.2 Soft frame photobioreactors
6.4.3 Membrane photobioreactor (MPBR)
6.4.4 Algal biofilm-based photobioreactors
6.4.5 Bottlenecks in the application of closed PBRS for cost-effective wastewater treatment
6.5 Conclusions and perspectives
References
SECTION
II - Applications of photobioreactors
7 - High-density microalgal biomass production in internally illuminated photobioreactors
7.1 Introduction
7.2 General rules for the design and operation of internally illuminated photobioreactor
7.2.1 Why internal illumination?
7.2.2 Technical trade-offs associated with internal illumination
7.2.3 Heuristic rules for internally illuminated photobioreactor
7.3 Design and demonstration of internally illuminated photobioreactors
7.3.1 Internally illuminated photobioreactor with a double-layered glass tube for thermal insulation
7.3.2 Adjusting light placement depth in internally illuminated cylindrical photobioreactor
7.3.3 Large-scale demonstration of internally illuminated photobioreactor
7.4 Opportunities for photobioreactor with internal illumination
7.5 Conclusions and perspectives
Acknowledgements
References
8 - The application of cyanobacteria in photobioreactors
8.1 Introduction
8.2 Cyanobacteria
8.3 Applications of cyanobacteria
8.3.1 Nutritional value
8.3.2 Medical value
8.3.3 Other values
8.4 Controlling cultivation of cyanobacteria
8.4.1 Light and temperature on cyanobacteria
8.4.2 Salinity and pH
8.4.3 Nutrient elements and carbon sources
8.5 Use of cyanobacteria in a photobioreactor
8.5.1 Open photobioreactor
8.5.2 Tube photobioreactor
8.5.2.1 Design of tube photobioreactors
8.5.3 Flat-plate photobioreactor
8.5.4.1 Design of flat-plate photoreactors
8.5.4 Columnar photobioreactor
8.5.4.1 Design of a columnar photobioreactor
8.6 Conclusions and perspectives
Authors’ contributions
References
9 - Cultivation of diatoms in photobioreactors
9.1 Introduction
9.2 Physiological and biotechnological advantages of diatoms
9.3 Growing diatom in large-scale culture systems
9.4 Selection of bioreactors and their design
9.5 Factors influencing diatom productivity in PBR systems
9.5.1 Light
9.5.2 Temperature and pH
9.5.3 Nutrient requirements
9.5.4 Trophic mode
9.6 Conclusions and perspectives
References
10 - Photobioreactor systems for production of astaxanthin from microalgae
10.1 Introduction
10.2 Photobioreactor (PBR) systems
10.2.1 Vertical tubular PBR
10.2.1.1 Bubble column PBR
10.2.1.2 Airlift PBR
10.2.2 Horizontal tubular PBR
10.2.3 Stirred tank PBR
10.2.4 Energy-free rotating floating PBR (RF-PBR)
10.2.5 Flat panel airlift PBRs (FP-ALPBR)
10.2.6 Hybrid usage of PBR
10.3 Conclusions and perspectives
Acknowledgements
References
11 - Production of biopolymers in photobioreactors
11.1 Introduction
11.2 Biopolymers from microalgae
11.2.1 Poly (hydroxyalkanoates)
11.2.2 Proteins
11.2.3 Polysaccharides
11.3 Upstream and downstream factors that maximize microalgal biopolymer production
11.3.1 Nitrogen source
11.3.2 Light intensity and temperature
11.3.3 Modes of obtaining energy
11.3.4 Extraction methods
11.4 Photobioreactors used to produce biopolymers
11.4.1 Biopolymer production from microalgae
11.5 Conclusions and perspectives
Acknowledgements
References
12 - Production of biohydrogen in photobioreactors
12.1 Introduction
12.2 Biohydrogen production in photobioreactor
12.2.1 Role of photobioreactor in biohydrogen production
12.2.2 Key factors of photobioreactor affecting biohydrogen production
12.2.3 Light-heat-mass transfer mechanisms in photobioreactor
12.3 Operation parameters of photobioreactor in the biohydrogen production process
12.3.1 Raw material type
12.3.2 Initial pH
12.3.3 Substrate concentration
12.3.4 Mixing methods
12.3.5 Temperature
12.3.6 Lighting patterns
12.3.7 Operation modes
12.4 Light-heat-mass transfer properties of photobioreactor during biohydrogen production process
12.4.1 Light transfer properties
12.4.2 Heat distribution
12.4.3 Metabolism of substrate and electron transfer
12.5 Cases of typical photobioreactors adopted in biohydrogen production process
12.5.1 Tubular photobioreactor
12.5.2 Circulating tank photobioreactor
12.5.3 Solar energy-based 5 m³ baffle photobioreactor
12.5.4 Combined photo and dark fermentation mode 11 m³ baffle photobioreactor
12.6 Conclusions and perspectives
Acknowledgements
References
Index

Citation preview

Current Developments in Biotechnology and Bioengineering Photobioreactors: Design and Applications Editors Ranjna Sirohi School of Health Sciences and Technology, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India

Ashok Pandey Centre for Innovation and Translational Research, CSIR-Indian Institute of Toxicology Research, Lucknow, India & Sustainability Cluster, School of Engineering, University of Petroleum and Energy Studies, Dehradun, India

Sang Jun Sim Department of Chemical and Biological Engineering, Korea University, Seoul, Republic of Korea

Jo-Shu Chang Department of Chemical and Materials Engineering, Tunghai University, Taichung, Taiwan; Research Center for Smart Sustainable Circular Economy, Tunghai University, Taichung, Taiwan; Department of Chemical Engineering, National Cheng Kung University, Tainan, Taiwan

Duu-Jong Lee Department of Chemical Engineering, National Taiwan University, Taipei, Taiwan; Department of Mechanical Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong

Current Developments in Biotechnology and Bioengineering

Series Editor: Professor Ashok Pandey Centre for Innovation and Translational Research CSIR-Indian Institute of Toxicology Research Lucknow, India & Sustainability Cluster School of Engineering University of Petroleum and Energy Studies Dehradun, India

Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States Copyright © 2023 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/ permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. ISBN: 978-0-323-99911-3 For Information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals Publisher: Susan Dennis Editorial Project Manager: Helena Beauchamp Production Project Manager: Kiruthika Govindaraju Cover Designer: Mark Rogers Typeset by Aptara, New Delhi, India

Contents Contributors  xi Preface  xv Section I General & design considerations

1

1.

3

Photobioreactors: An introduction Ranjna Sirohi, Sang Jun Sim, Ashok Pandey 1.1 Introduction

3

1.2 Types of photobioreactors

4

1.3 Factors affecting microalgae productivity in photobioreactors 5 1.4 Modeling and simulation of photobioreactors

6

1.5 Applications of photobioreactors

6

1.6 Conclusions and perspectives

8

References 8

2.

Design and scale-up of photobioreactors

11

Jeyaprakash Dharmaraja, Sutha Shobana, Menghour Huy, Ann Kristin Vatland, Veeramuthu Ashokkumar, Gopalakrishnan Kumar 2.1 Introduction

11

2.2 Microalgae cultivation scaling-up process

12

2.3 Photobioreactor (PBR) design and its scalability principles

13

2.4 Challenges

26

2.5 Conclusions and perspectives

27

References 28

v

vi  Contents

3.

Types of photobioreactors

33

Yoong Kit Leong, Jo-Shu Chang, Duu-Jong Lee 3.1 Introduction

33

3.2 Vertical column photobioreactors

34

3.3 Horizontal tubular photobioreactors (HT-PBRs)

39

3.4 Flat plate photobioreactors (FP-PBRs)

43

3.5 Flat panel-airlift photobioreactors (FPA-PBRs)

47

3.6 Plastic bag photobioreactors (PB-PBRs)

48

3.7 Taylor vortex photobioreactors (TV-PBRs)

49

3.8 Torus photobioreactors (T-PBRs)

50

3.9 Internally illuminated photobioreactor (II-PBRs)

50

3.10 Other innovative photobioreactors

51

3.11 Conclusions and perspectives

52

References 53

4.

Factors affecting the microalgal biomass productivity in photobioreactors 59 S. Deepak Mohan Reddy, N. Deepika, Meghana Reddy Dropathi, S. Vishwanutha, J. Dhanish Daaman, C. Nagendranatha Reddy, Rajasri Yadavalli 4.1 Introduction

59

4.2 Factors influencing the general productivity in photobioreactors (PBR)

60

4.3 Factors influencing the process scale-up

73

4.4 Conclusions and perspectives

78

Acknowledgment 79 References 79

5.

Photobioreactors modeling and simulation

89

Eva M. Salgado, José C.M. Pires 5.1 Introduction

89

5.2 Stoichiometry and kinetics of microalgal growth

90

Contents vii

5.3 Photobioreactor modeling

100

5.4 Photobioreactor simulation

110

5.5 Conclusions and perspective

112

Acknowledgements 113 References 113

6.

Photobioreactors for microalgae-based wastewater treatment 121 Dillirani Nagarajan, Chun-Yen Chen, Duu-Jong Lee, Jo-Shu Chang 6.1 Introduction

121

6.2 Phycoremediation potential of microalgae—assimilatory nutrients removal

122

6.3 Open systems for microalgae-based wastewater treatment

124

6.4 Closed photobioreactors for microalgae-based wastewater treatment 130 6.5 Conclusions and perspectives

143

References 144

Section II Applications of photobioreactors 7.

High-density microalgal biomass production in internally illuminated photobioreactors

153 155

Hee-Sik Kim, Dae-Hyun Cho, Jin-Ho Yun 7.1 Introduction

155

7.2 General rules for the design and operation of internally illuminated photobioreactor

158

7.3 Design and demonstration of internally illuminated photobioreactors 162 7.4 Opportunities for photobioreactor with internal illumination

170

7.5 Conclusions and perspectives

172

Acknowledgements 174 References 174

viii  Contents

8.

The application of cyanobacteria in photobioreactors

177

Congying Zhang, Yi Wu, Ruibing Peng 8.1 Introduction

177

8.2 Cyanobacteria

178

8.3 Applications of cyanobacteria

184

8.4 Controlling cultivation of cyanobacteria

186

8.5 Use of cyanobacteria in a photobioreactor

190

8.6 Conclusions and perspectives

197

Authors’ contributions

199

References 199

9.

Cultivation of diatoms in photobioreactors

207

Thomas Kiran Marella, Archana Tiwari 9.1 Introduction

207

9.2 Physiological and biotechnological advantages of diatoms

207

9.3 Growing diatom in large-scale culture systems

208

9.4 Selection of bioreactors and their design

210

9.5 Factors influencing diatom productivity in PBR systems

214

9.6 Conclusions and perspectives

220

References 221

10. Photobioreactor systems for production of astaxanthin from microalgae 229 Young Joon Sung, Jaemin Joun, Byung Sun Yu, Sang Jun Sim 10.1 Introduction

229

10.2 Photobioreactor (PBR) systems

231

10.3 Conclusions and perspectives

240

Acknowledgements 243 References 243

Contents ix

11. Production of biopolymers in photobioreactors

247

Jorge Alberto Vieira Costa, Gabriel Martins da Rosa, Suelen Goettems Kuntzler, Ana Gabrielle Pires Alvarenga, Michele Greque de Morais 11.1 Introduction

247

11.2 Biopolymers from microalgae

248

11.3 Upstream and downstream factors that maximize microalgal biopolymer production

252

11.4 Photobioreactors used to produce biopolymers

255

11.5 Conclusions and perspectives

259

Acknowledgements 260 References 260

12. Production of biohydrogen in photobioreactors

269

Quanguo Zhang, Zhiping Zhang, Huan Zhang, Yameng Li 12.1 Introduction

269

12.2 Biohydrogen production in photobioreactor

271

12.3 Operation parameters of photobioreactor in the biohydrogen production process

274

12.4 Light-heat-mass transfer properties of photobioreactor during biohydrogen production process

280

12.5 Cases of typical photobioreactors adopted in biohydrogen production process

283

12.6 Conclusions and perspectives

295

Acknowledgements 296 References 296

Index  301

Contributors Ana Gabrielle Pires Alvarenga  Laboratory of Microbiology and Biochemistry, College of Chemistry and Food Engineering, Federal University of Rio Grande, Rio Grande, RS, Brazil Veeramuthu Ashokkumar  Center of Excellence in Catalysis for Bioenergy and Renewable Chemicals, Faculty of Science, Chulalongkorn University, Bangkok, Thailand Jo-Shu Chang  Department of Chemical and Materials Engineering, Tunghai University, Taichung, Taiwan; Research Center for Smart Sustainable Circular Economy, Tunghai University, Taichung, Taiwan; Department of Chemical Engineering, National Cheng Kung University, Tainan, Taiwan Chun-Yen Chen  University Center for Bioscience and Bioengineering, National Cheng Kung University, Tainan, Taiwan Dae-Hyun Cho  Cell Factory Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea Jorge Alberto Vieira Costa  Laboratory of Biochemical Engineering, College of Chemistry and Food Engineering, Federal University of Rio Grande, Rio Grande, RS, Brazil J. Dhanish Daaman  Department of Biotechnology, Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana, India Gabriel Martins da Rosa  Laboratory of Biochemical Engineering, College of Chemistry and Food Engineering, Federal University of Rio Grande, Rio Grande, RS, Brazil N. Deepika  Department of Biotechnology, Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana, India Michele Greque de Morais  Laboratory of Microbiology and Biochemistry, College of Chemistry and Food Engineering, Federal University of Rio Grande, Rio Grande, RS, Brazil Jeyaprakash Dharmaraja  Division of Chemistry, Faculty of Science and Humanities, AAA College of Engineering &Technology, Amathur, Sivakasi, Tamil Nadu, India Meghana Reddy Dropathi  Department of Biotechnology, Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana, India Menghour Huy  Department of Chemistry, Bioscience, and Environmental Engineering, Faculty of Science and Technology, University of Stavanger, Stavanger, Norway Jaemin Joun  Department of Chemical and Biological Engineering, Korea University, Seoul, Republic of Korea xi

xii  Contributors

Hee-Sik Kim  Cell Factory Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea; Department of Environmental Biotechnology, KRIBB School of Biotechnology, University of Science & Technology (UST), Daejeon, Republic of Korea Gopalakrishnan Kumar  Department of Chemistry, Bioscience, and Environmental Engineering, Faculty of Science and Technology, University of Stavanger, Stavanger, Norway Suelen Goettems Kuntzler  Laboratory of Microbiology and Biochemistry, College of Chemistry and Food Engineering, Federal University of Rio Grande, Rio Grande, RS, Brazil Duu-Jong Lee  Department of Chemical Engineering, National Taiwan University, Taipei, Taiwan; Department of Mechanical Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong Yoong Kit Leong  Department of Chemical and Materials Engineering, Tunghai University, Taichung, Taiwan Yameng Li  Key Laboratory of New Materials and Equipment for Renewable Energy of Ministry of Agriculture and Rural Affairs of China, Henan Agricultural University, Zhengzhou, China Thomas Kiran Marella  Algae Biomass and Energy System R&D Center, University of Tsukuba, Tsukuba, Ibaraki, Japan Dillirani Nagarajan  Department of Chemical Engineering, National Taiwan University, Taipei, Taiwan; Department of Chemical Engineering, National Cheng Kung University, Tainan, Taiwan Ashok Pandey  Centre for Innovation and Translational Research, CSIR-Indian Institute of Toxicology Research, Lucknow, India; Sustainability Cluster, School of Engineering, University of Petroleum and Energy Studies, Dehradun, India Ruibing Peng  Key Laboratory of Applied Marine Biotechnology, Ningbo University, Ministry of Education, Ningbo, Zhejiang, People’s Republic of China José C.M. Pires  LEPABE—Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, Porto, Portugal; ALiCE — Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, Porto, Portugal S. Deepak Mohan Reddy  Department of Biotechnology, Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana, India C. Nagendranatha Reddy  Department of Biotechnology, Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana, India Eva M. Salgado  LEPABE—Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, Porto, Portugal; ALiCE — Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, Porto, Portugal

Contributors xiii

Sutha Shobana  Green Technology and Sustainable Development in Construction Research Group, Van Lang School of Engineering and Technology, Van Lang University, Ho Chi Minh City, Vietnam Sang Jun Sim  Department of Chemical and Biological Engineering, Korea University, Seoul, Republic of Korea Ranjna Sirohi  School of Health Sciences and Technology, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India Young Joon Sung  Department of Chemical and Biological Engineering, Korea University, Seoul, Republic of Korea Archana Tiwari  Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India Ann Kristin Vatland  Department of Chemistry, Bioscience, and Environmental Engineering, Faculty of Science and Technology, University of Stavanger, Stavanger, Norway S. Vishwanutha  Department of Biotechnology, Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana, India Yi Wu  Key Laboratory of Applied Marine Biotechnology, Ningbo University, Ministry of Education, Ningbo, Zhejiang, People’s Republic of China Rajasri Yadavalli  Department of Biotechnology, Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana, India Byung Sun Yu  Department of Chemical and Biological Engineering, Korea University, Seoul, Republic of Korea Jin-Ho Yun  Cell Factory Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea Congying Zhang  Key Laboratory of Applied Marine Biotechnology, Ningbo University, Ministry of Education, Ningbo, Zhejiang, People’s Republic of China; School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Science, Hangzhou, Zhejiang, People’s Republic of China Quanguo Zhang  Key Laboratory of New Materials and Equipment for Renewable Energy of Ministry of Agriculture and Rural Affairs of China, Henan Agricultural University, Zhengzhou, China Zhiping Zhang  Key Laboratory of New Materials and Equipment for Renewable Energy of Ministry of Agriculture and Rural Affairs of China, Henan Agricultural University, Zhengzhou, China Huan Zhang  Key Laboratory of New Materials and Equipment for Renewable Energy of Ministry of Agriculture and Rural Affairs of China, Henan Agricultural University, Zhengzhou, China

Preface The book titled Photobioreactors: Design and Applications is a part of the Elsevier book series  on  Current Developments in Biotechnology and Bioengineering (Editor-in-Chief: Ashok Pandey). This book covers recent trends and technological advances in photobioreactors (PBRs) engineering and discusses their possible industrial applications and advancement in the design of PBRs. It presents state-of-the-art technological perspectives of PBRs. A photobioreactor is the core of microalgae bioprocess engineering. PBR is a type of bioreactor  which  utilizes a light source for the cultivation of phototrophic microorganisms that produce biomass using light and CO2. The design and operation of photobioreactors have a  broad interest in biotechnological industrial tracking. Technically, these configurations, in current operation, are extrapolations from conventional chemical reactors. These systems, as well as their variations, have been developed and adapted to meet the peculiarities of microalgae and biohydrogen bioprocesses. This book examines the advancements, design, construction, types, applications, and current research on photobioreactors. It aims to comprehensively explore the engineering advances in the design of PBRs, types and applications of PBRs. It also introduces key principles that enable chemical and environmental engineers to engage in analysis, optimization, and design with consistent control over biological and chemical transformations. There are fast technological developments taking place in the chemical and bioprocessing sectors which adopt them with state-of-the-art techniques to keep up with the rising demand of the industry and R&D. The use of computational modeling of the processes and control systems is the need of the hour. This book covers these aspects in detail which will take the readers through a stepby-step journey of chemical and bioprocessing while guiding them towards a new era and future of bioprocess, chemical and environmental engineering, focusing on PBRs. The contents of this book are organized into two sections with a total of 12 chapters. All the chapters have been contributed by global experts in the field of bioprocessing, biochemical, chemical,  and environmental engineering. The first section deals with a comprehensive introduction, design and scale-up of PBRs. There are five chapters in this section. Topics covered  in this section include design consideration and scale-up of PBRs, types of PBRs, important factors affecting the productivity of desired products in PBRs, and modeling and simulation of PBRs. Chapter 1 deals with the basic information about PBRs. Chapter 2 covers scale-up and engineering aspects of PBRs systems, including design and operation and relevant aspects for the selection of PBRs for various applications. Chapter 3 focuses on the types of PBRs, including their limitations, advantages, and disadvantages. Chapter 4 discusses the effects of design, thermodynamic, operational and ecological factors on the cultivation of microalgae in PBRs. Chapter 5 details the most important models, computer simulation (CFD) xv

xvi  Preface

that relate microalgal growth and chemical and physical environmental factors. The second section of the book presents the applications of PBRs and comprises seven chapters. Chapter 6 discusses various PBRs designs applied for wastewater treatment with microalgae. The advantages, disadvantages, and opportunities of each system are also discussed in this chapter along with a critical analysis of the challenges in using closed photobioreactors for effective and economic wastewater treatment. Chapter 7 supports the promise of internal illumination in  terms  of improving PBRs light utilization efficiency, which in turn could promote the production of the photosynthetic organism and its bioactive compound. Chapter 8 summarizes the basic biological characteristics, application value, and culture conditions of cyanobacteria, generalizes and analyzes the current algae PBRs to provide a promising application scheme for  low-cost production of high-quality cyanobacteria products. Chapter 9 comprehensively discusses the diatom species cultured in PBRs under different cultivation modes and its impacts on overall productivity. It also provides an overview on critical physicochemical conditions influencing their productivity in bioreactors and also includes the advantages and limitations of different bioreactors used to culture diatoms. Chapter 10 illustrates the structure of various PBRs systems and compares the productivity of astaxanthin in each system. Moreover, it analyzes how  the change of the culture environment conditions caused by the PBR system affects the physiological activity of cells and astaxanthin production. Chapter 11 covers the most recent researches that address the main types of biopolymers produced in photobioreactors, as well as the cultivation conditions that influence the production of biopolymers from microalgae. Chapter 12 provides state-of-the-art information  and details of various photobioreactors used  for biohydrogen production. The effects of significant factors affecting the biohydrogen production performance such as raw material type, initial pH, substrate concentration, mixing methods, temperature, lighting patterns, and operation modes, are also discussed. We are grateful to the authors for compiling the pertinent information required for chapter writing, which we believe will be a valuable source for both the scientific community and the audience in general. We are thankful to the expert reviewers for providing their useful comments and scientific insights, which helped to shape the chapter organization and improved the scientific discussions, and overall quality of the chapters. We sincerely thank the Elsevier team comprising Dr. Kostas Marinakis, Former Senior Book Acquisition Editor, Dr. Katie Hammon, Senior Book Acquisition Editor, Moises Carlo Catain, Editorial Project Manager, Mohan Raj Rajendran and the entire Elsevier production team for their support in publishing this book. Editors Ranjna Sirohi Ashok Pandey Sang Jun Sim Jo-Shu Chang Duu-Jong Lee

SECTION

I

General & design considerations

1. 2. 3. 4. 5. 6.

Photobioreactors: An introduction............................................................................... 3 Design and scale-up of photobioreactors.................................................................. 11 Types of photobioreactors .......................................................................................... 33 Factors affecting the microalgal biomass productivity in photobioreactors........... 59 Photobioreactors modeling and simulation .............................................................. 89 Photobioreactors for microalgae-based wastewater treatment............................ 121

1 Photobioreactors: An introduction Ranjna Sirohia, Sang Jun Simb, Ashok Pandeyc,d a SCHOO L O F HEALTH S CI ENCES AN D T E C H N O L O G Y, U N I V E R S I T Y O F P E T R O L E U M A N D E NERGY S TUDI ES , DEHRADUN, UTTARA K H A N D , I N D I A b D E PA RT ME N T O F C H E MI C A L A N D BIOLOGICAL ENGI NEERI NG, KO REA UNI V E R S I T Y, S E O U L , R E P U B L I C O F K O R E A c C E N T R E F O R INNOVATI O N AND TRANS L ATI O NAL RE S E A R C H , C S I R - I N D I A N I N S T I T U T E O F T O X I C O L O G Y RE SE ARCH, L UCKNO W, I NDI A d S USTA I N A B I L I T Y C L U S T E R , S C H O O L O F E N G I N E E R I N G , UNI VERS I TY O F PETR O L E U M A N D E N E R G Y S T U D I E S , D E H R A D U N , I N D I A

1.1 Introduction A photobioreactor (PBR) is a sealed, illuminated culture vessel that utilizes a light source to cultivate phototrophic microorganisms and these organisms use photosynthesis to generate biomass from light and carbon dioxide. A PBR is a closed structure that is locked off from the outside environment and has no possible exchange of gases or pollutants within it. PBRs have the advantage of minimizing the toxicity and providing improved conditions such as pH, temperature, light, and CO2 concentration and also allows for high biomass concentrations and complex biopharmaceutical processing (Singh & Sharma, 2012). Generally, PBRs have been considered as most suitable systems for the cultivation of microalgae. Initially, the mass cultivation of photoautotrophs has been studied in open raceways. The first open raceways (shallow mixed pond) were introduced in the early 1960s by Oswald (Dodd, 1986). Generally, two types of open raceway ponds are used. In the first one, concrete is used for making the lining, while in the second one, a shallow earthen tunnel in lined with 1–2 mm thick sheets of polyvinyl chloride or other durable food-grade plastic material. Durability of the lining and cost of the component are the major capital investment to design such reactors and have great impact on the economic feasibility of mass production of microalgae and cyanobacteria (Vonshak & Richmond, 1988). Open raceways systems, however, show several bottlenecks in their large-scale applications. These include the control of the temperature and water column, among others as the most important drawbacks in open raceways. The optimal temperature for cyanobacteria production is in the range of 35°C which is not commonly reached in open raceway systems in many places. The water column in the pond should not be reduced below 0.15 m, to prevent reduction of flow and turbulence, which also is a serious scalability issue. Keeping these limitations in mind, closed tubular systems came in existence in 1983. John Pirt and coworkers proposed the theory and design for tubular PBRs and the first tubular system with 1000 m2 was developed by Gudin and Chaumont (1983) for the cultivation of Porphyridium sp. This PBR developed in Florence was made with transparent plexiglass tubes with 0.13 m diameter and its capacity Current Developments in Biotechnology and Bioengineering. DOI: https://doi.org/10.1016/B978-0-323-99911-3.00008-7 Copyright © 2023 Elsevier Inc. All rights reserved.

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4  Current Developments in Biotechnology and Bioengineering

was about 100 liters of culture suspension per m2 of illuminated surface. Each PBR was made up of several tubes laid side by side on a white polyethylene sheet joined by a connection to form a loop and each connection incorporating a narrow tube for oxygen release. At the exit, a receiving tank was placed for receiving the culture suspension. The drawback of these systems was temperature control since closed systems heat up quickly and must be cooled to attain high productivity. For this, cooling systems are required which add additional costs. Closed systems are more difficult to clean; tube material might partially decrease sunlight penetration. However, closed systems have many advantages, including reduced risk of contamination and microalgae can be grow at optimum conditions without environmental influences (Masojidek & Torzillo, 2014). To-date, one of the largest pond 1.25 ha for microalgae cultivation for biofuel production is operating in New Zealand (Pina-Pérez et al., 2019). In today’s time, PBRs are considered as the representative for the new type of algae culture device, which can not only ensure the high and stable output of cell biomass, but also solve the problems of large culture area and susceptibility to weather. It has become an important key to solve the efficient production of cyanobacteria and microalgae and ensure the quality of the value added products derived from them.

1.2  Types of photobioreactors For the production of value-added commodities from microalgae and cyanobacteria, various types of photobioreactors have been designed and studied. The most basic configurations of photobioreactors include vertical columns, horizontal tubes, and flat plates. To overcome the limitations in these classical configurations, several innovative photobioreactors have been developed such as helical tubular, flat panel-airlift, plastic bag type, Taylor vortex, and internally illuminated, among others. Each of the different types of photobioreactors offer some advantages and disadvantages, and have variation in operational principles and innovations. Some innovative photobioreactors with unique shapes such as conical, fractal tree-like, L-shaped, pyramid, ring, torus, V-shaped, X-shaped, and others have also been developed. Among all photobioreactor designs, horizontal tubular and flat-panel airlift demonstrate the highest potential for commercial applications for mass cultivation of photosynthetic microorganisms owing to the advantage of large illumination surface area to volume ratio and efficient mass transfer. A brief overview of the different types of PBRs is discussed below.

1.2.1  Tubular type photobioreactors Tubular photobioreactors are one of the most suitable forms for outdoor mass cultures among all the photobioreactors. The majority of outdoor tubular photobioreactors are made of glass or plastic tubes, and their cultures are re-circulated using a pump or, preferably, an airlift device.

1.2.2  Flat panel photobioreactors Flat panel PBRs are distinguished by their high surface-to-volume ratio, vertical or slanted slope of the channels from horizontal, and lack of mechanical mechanisms for cell suspension. The

Chapter 1 • Photobioreactors: An introduction  5

cuboidal design of the flat panel reactor allows for a short light path. Transparent materials such as glass, plexiglass, and polycarbonate can be used to create it. Furthermore, the culture movement, gas exchanged, and degassing is done by bubbling air from the bottom of each channel. Air is bubbled from one side through a perforated tube, or it is manually rotated by a motor to produce agitation.

1.2.3  Column types photobioreactors Column or vertical tubular photobioreactors are alternative of stirred reactor in which agitation is done by air sparging. They are also classified as airlift reactors, and bubble column, based on the mode of liquid flow. The culture is aerated with air or CO2 for mixing to initiate the suspending process. The advantages of these types of systems include excellent gas-liquid mass transfer and biomass production, low shear stress, good mixing, low energy consumption, and light/ dark cycle control characteristics. Bubble column reactors are widely used in the industry for the manufacture of baker’s yeast, beer, vinegar, and wastewater treatment.

1.2.4  Soft frame photobioreactors Soft-frame PBRs, unlike typical PBRs that use hard materials and are immobile, may be split into small modules and are, therefore, more transportable. However, because it must withstand a significant pressure, the material employed in its construction should not be prone to damage. Soft frames are composed of ethylene vinyl acetate/low-density polyethylene, polyethylene, and polytetrafluoroethylene, all of which are flexible and require less space for installation. Many other advanced PBRs along with possible integrations of classic PBRs in buildings and novel synergic applications have also been developed. Some of these include the membrane cultivation systems (porous substrate bioreactors [PSBRs] and twin layer [TL]), offshore membrane enclosures for growing algae (OMEGA), and pyramid PBRs, among others. Large-scale PBRs have been developed in order to offset the production costs, increase energy efficiency, and economic profitability toward its commercialization within next decade.

1.3  Factors affecting microalgae productivity in photobioreactors The potential of microalgae for biofuel and value-added products generation has been recognized for years because they contain oils and produce biomass rapidly, as well as the fact that they can grow in nonarable soils and wastewater. Microalgae contributing to food, pharmaceutical, aquaculture, and cosmetic sectors are also important for producing bioactive compounds, antioxidants, carbohydrates, vitamins, and polyunsaturated fats (PUFAs). The enhanced productivity of microalgal biomass is dependent on effective utilization of substrate (organic or inorganic CO2), sunlight (illumination), nutrients, and many other parameters, viz., bioreactor design parameters, mixing regimes, overcoming the mass transfer limitations, and, hydrodynamic stresses, etc. Microalgae contain important biomolecules, which have functional values for human health and nutrition. The productivity of these biomolecules is affected by the

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culture conditions such as presence or absence of different nutrients in the culture medium, light intensity quality and quantity, temperature, aeration, photoperiod, harvesting and processing (Khan et al., 2018; Sirohi et al., 2021a).

1.4  Modeling and simulation of photobioreactors Microalgal-based processes have received increasing attention for different applications, including environment protection, bioenergy, and food production. The cultivation step is crucial as it determines the final product cost and, therefore, the success of microalgae business in different markets. Consequently, knowing how the microalgae grow in different environments is essential for the optimization of biomass production. Several models have been developed for microalgal growth and chemical and physical environmental factors affecting the growth. The models have been divided into groups according to the analyzed environmental factor and their concepts. Multiple factor modeling has also been studied. These models can be coupled with the simulation of hydrodynamics given by the Computational Fluid Dynamics (CFD). CFD is an interesting tool to assess the variability of culture variables in different PBR geometries, avoiding costly and time-consuming experimental work. CFD modeling can be used to understand the complex fluid dynamic behaviors of PBRs which can help in its design and scale-up. The complete understanding of the underlying processes of photobioreactor through modeling is more challenging due to multitime and multiscale coupling between physical, chemical and biological phenomena. These processes in PBRs are interconnected by various subprocesses such as fluid dynamics, light distribution, and algae growth rate. Thus, for comprehensive modeling of a photobioreactor, various submodeling systems need to be considered such as multiphase CFD modeling for fluid dynamics, radiation model for light distribution, and kinetic modeling for algal growth rate. Among the various subprocesses, knowledge about the multiphase CFD modeling of fluid dynamics involves mixing and mass transfer behaviors in PBRs which is still not completely understood. This is mainly due to the inherent complex flow behavior of the multiphase system. Coupling the simulation of hydrodynamics and the different models that relate microalgal growth with several environmental factors enabled a complete and robust performance simulation of several PBR designs.

1.5  Applications of photobioreactors 1.5.1  Photobioreactors for microalgae-based wastewater treatment Microalgae are being increasingly recognized as a bioremediation agent for effective nutrient recovery from various wastewaters. Microalgae have demonstrated excellent tolerance toward the harsh conditions of wastewaters including increased organic carbon and ammonia, pollutants such as heavy metals, organic compounds, hormones, antibiotics, and personal care products. Microalgae-based wastewater treatment has been carried out in open ponds, called waste stabilization ponds, which were upgraded as high rate algal ponds for better algal biomass production

Chapter 1 • Photobioreactors: An introduction  7

and nutrient recovery. Closed photobioreactors have potential advantages over open systems, such as protection from contamination and high biomass productivity, while cost-effective installation and operation is a major roadblock. Recently, various photobioreactors have been applied for the treatment of wastewaters using microalgae, such as vertical column, tubular, flat plate, membrane and biofilm-based photobioreactors. Various photobioreactor designs have been applied for wastewater treatment with microalgae and removal of heavy materials.

1.5.2  Cultivation of diatoms in photobioreactors Diatoms are unicellular protists belonging to Bacillariophyceae of stramenopile class. Due to their unique evolutionary history of secondary endosymbiotic event, they possess diverse differences in cellular and metabolic makeup compared to other algae classes. This metabolic repertoire empowers them to biosynthesize potent functional biomolecules such as fucoxanthin, chrysolaminarin, ecosapentaenoic acid (EPA), phytosterols, and for liquid biofuels. Their species diversity, trophic, and environmental flexibility make them ideal candidates for industrial scale production. Despite these unique advantages, they are grossly underrepresented in terms of research regarding their high cell density culturing in photobioreactors or fermenters. To attain the sustainability, there is an urgency to find ways to increase biomass productivity for which a paradigm shift from present autotrophic open pond cultivation to mixotrophic or heterotrophic photobioreactor or fermenters is needed

1.5.3  Cultivation of astaxanthin in photobioreactors Astaxanthin, which has strong antioxidant ability, is steadily increasing in demand in the nutraceutical and pharmaceutical industries because of its ability to effectively treat various diseases. In particular, microalgae-derived astaxanthin has excellent efficacy and can be produced through direct conversion of CO2, making it sustainable (Yu et al., 2021). However, low productivity, contamination vulnerability, and the processing complexity of microalgae prevent large-scale commercialization. Accordingly, various technologies including strain development, culture mode selection, contamination control, and extraction have been developed to improve production efficiency in all process steps, from upstream to downstream processes.

1.5.4  Production of biopolymers in photobioreactors Synthetic polymers of fossil origin have generated an accumulation of waste when improperly discarded in the aquatic environment and terrestrial ecosystem, driving the development of measures that can slow down the use of these polymers. The economic transition from fossil to renewable biological platforms offers the most promising solution to meeting global warming mitigation. Biopolymers of natural origin are an alternative to synthetic plastics, as they can be degraded by microorganisms, resulting in carbon dioxide (CO2) and water (Sirohi et al 2021b). Polyhydroxyalkanoates (PHAs) are nontoxic, biocompatible biopolymers with mechanical properties similar to synthetic materials. Proteins and polysaccharides are biopolymers with high structural variability, enabling their industrial use in several areas. Microalgae are photosynthetic microorganisms that can produce a high concentration of biopolymers as a carbon

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reserve mechanism from industrial waste as a source of nutrients and minimize environmental impacts (Sirohi et al., 2021c). The concentrations and/or productivities of biopolymers can be maximized through the use of different strains, culture medium, conducting mode, extraction methods, among other changes in downstream and upstream. PBRs can increase not only the production of biomass but also the production of biopolymers.

1.5.5  Production of biohydrogen in photobioreactors Photo-fermentative biohydrogen production is a complex temperature-sensitive photobiochemical reaction process, and the light-heat-mass transfer performance in the PBR greatly affects the potential of biohydrogen production. Therefore, reasonable PBR is the key to efficient hydrogen production. Tubular and circulating tank PBRs are commonly used for biohydrogen production. Raw material type, initial pH, substrate concentration, mixing methods, temperature, lighting patterns and operation modes, are the factors which significantly affect the biohydrogen production performance. Diverse photobioreactors had their own advantages and disadvantages in biohydrogen production process. Four cases of photobioreactors utilized for biohydrogen production process include circulating tank reactor, tubular photobioreactor, 5 m³ baffle photobioreactor and 11 m³ baffle bioreactor. The insights of the biohydrogen production performance from micro and macro perspectives of diverse photobioreactors showed great help to improve the structure of photobioreactors and strengthen the biohydrogen producing capacity.

1.6  Conclusions and perspectives For commercial applications, an “ideal” photobioreactor should have high illumination surface area to volume ratio, high mixing efficiency and mass transfer rate, low energy requirement, easy control of operating parameters (pH, temperature, dissolved CO2, and O2 concentration), and be able to achieve high biomass productivities with low space requirements. Closed photobioreactors can effectively control the culture conditions of microalgae, reduce pollution, and are suitable for most algal species. Although flat-plate and pipeline-type bioreactors provide easy to control conditions, large light areas and a large algae biomass which are some of the currently considered factors to have the most commercial potential, their higher maintenance costs are major bottlenecks. Internally illuminated photobioreactors attracted research attention due to the separate light-harvesting and cultivation process, while disposable photobioreactors (plastic bag type) are low cost and possibly sustainable, though much research is needed in this sector. For outdoor cultivation, the solar irradiation filtration technologies can be integrated into the photobioreactors for garnering multiple advantages.

References Dodd, J. C. (1986). Elements of pond design and construction. In: Richmond, A. (Ed.), Handbook of microalgal mass culture (pp. 265–283). Boca Raton, Florida: CRC Press. Gudin, C., Chaumont, D. (1983). Solar biotechnology study and development of tubular solar receptors for controlled production of photosynthetic cellular biomass. In: Palz, W., Pirrwitz, D. (Eds.), Proceedings of the workshop and E.C. Contractor’s meeting in Capri (pp. 184–193). Dordrecht: D. Reidel Publishing Co.

Chapter 1 • Photobioreactors: An introduction  9

Khan, M. I., Shin, J. H. & Kim, J. D. (2018). The promising future of microalgae: current status, challenges, and optimization of a sustainable and renewable industry for biofuels, feed, and other products. Microbial Cell Factories, 17 (1), 1–21. Masojídek, J. & Torzillo, G. (2008). Mass cultivation of freshwater microalgae. In S. E. Jorgensen, B. Fath (Eds.). Encyclopedia of Ecology (pp. 2226–2235). Pina-Pérez, M. C., Brück, W. M., Brück, T. & Beyrer, M. (2019). Microalgae as healthy ingredients for functional foods. The role of alternative and innovative food ingredients and products in consumer wellness (pp. 103–137). Academic Press. Singh, R. N. & Sharma, S. (2012). Development of suitable photobioreactor for algae production – A review. Renewable and Sustainable Energy Reviews, 16 (4), 2347–2353. Sirohi, R., Lee, J. S., Yu, B. S., Roh, H. & Sim, S. J. (2021c). Sustainable production of polyhydroxybutyrate from autotrophs using CO2 as feedstock: Challenges and opportunities. Bioresource Technology, 341, 125751. Sirohi, R., Pandey, J. P., Tarafdar, A., Agarwal, A., Chaudhuri, S. K. & Sindhu, R. (2021b). An environmentally sustainable green process for the utilization of damaged wheat grains for poly-3-hydroxybutyrate production. Environmental Technology & Innovation, 21, 101271. Sirohi, R., Ummalyma, S. B., Sagar, N. A., Sharma, P., Awasthi, M. K., Badgujar, P. C., Madhavan, A., Reshmy, R., Sindhu, R., Sim, S. J. & Pandey, A. (2021a). Strategies and advances in the pretreatment of microalgal biomass. Journal of Biotechnology, 341, 63–75. Vonshak, A. & Richmond, A. (1988). Mass production of the blue-green alga Spirulina: an overview. Biomass, 15 (4), 233–247. Yu, B. S., Sung, Y. J., Choi, H. I., Sirohi, R. & Sim, S. J. (2021). Concurrent enhancement of CO2 fixation and productivities of omega-3 fatty acids and astaxanthin in Haematococcus pluvialis culture via calcium-mediated homeoviscous adaptation and biomineralization. Bioresource Technology, 340, 125720.

2 Design and scale-up of photobioreactors Jeyaprakash Dharmarajaa, Sutha Shobanab, Menghour Huyc, Ann Kristin Vatlandc, Veeramuthu Ashokkumard, Gopalakrishnan Kumarc a DI VI S I O N O F CHEM I S TRY, FACU LT Y O F S C I E N C E A N D H U MA N I T I E S , A A A C O L L E G E OF E NGI NEERI NG &TECHNO L O GY, A MAT H U R , S I VA K A S I , TA MI L N A D U , I N D I A b G R E E N TE CHNOL O GY AND S US TAI NABL E DE V E L O P ME N T I N C O N S T R U C T I O N R E S E A R C H G R O U P, VAN LANG S CHO O L O F ENGI NEERI NG A N D T E C H N O L O G Y, VA N L A N G U N I V E R S I T Y, H O C H I MINH CITY, VI ETNAM c DEPARTM ENT O F C H E MI S T RY, B I O S C I E N C E , A N D E N V I R O N ME N TA L ENGIN EERI NG, FACULTY O F S CI ENC E A N D T E C H N O L O G Y, U N I V E R S I T Y O F S TAVA N G E R , STAVANGER, NO RWAY d CENTER OF E X C E L L E N C E I N C ATA LY S I S F O R B I O E N E R G Y A N D RENEWABL E CHEM I CAL S , FAC U LT Y O F S C I E N C E , C H U L A L O N G K O R N U N I V E R S I T Y, BANGKOK, THAILAND

2.1 Introduction Microalgal biorefinery has been driven into many modern technology sectors, including wastewater treatment, bioenergy, feed, nutraceutical, and pharmaceutical products, etc. (Bhattacharya & Goswami, 2020). In addition, microalgae can mitigate CO2 emission through photosynthesis and produce high value-added products such as carbohydrates, protein, lipid, polyunsaturated fatty acids, carotenoids, etc. (Chen et al., 2018; Li et al., 2020). In this context, researchers are focused on the scalability of laboratory culture to large-scale biomass production with low-cost technologies. At a commercial scale, open raceway ponds and closed photoreactors play a vital role; however, each system has its own advantages and disadvantages. Open raceway cultivation (artificial ponds, shallow raceway ponds) has the advantages of low capital investment, simple configuration, and operating conditions normally seen in wastewater treatment facilities or producing large amounts of bulk biomass (Singh & Sharma, 2012). However, it strongly depends on the weather and parameters control. Up to date, it is still cheaper to produce a large amount of biomass compared to closed photobioreactors (Koyande et al., 2019). This chapter focuses on the scalability of microalgal culture to a larger volume using different photobioreactor systems. Depending on the requirements, photobioreactors are normally designed to facilitate major tasks such as treating wastewater, capturing CO2, producing bulk biomass, and value-added compounds (pigments), biofuel and feed (Posten, 2009; Song et al., 2020). In a closed system, the critical parameters such as CO2 level and aeration rate, nutrient level, pH, temperature were fully controlled for high biomass density. Further, the other sensitive parameters (nutrient detention, strong light intensity, high temperature) also play a crucial Current Developments in Biotechnology and Bioengineering. DOI: https://doi.org/10.1016/B978-0-323-99911-3.00010-5 Copyright © 2023 Elsevier Inc. All rights reserved.

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role in the enhanced production of lipid and carotenoids (Wang et al., 2012). In a closed cultivation system, the vertical/horizontal tubular photobioreactor is a conventional type that is still popular and operates at an industrial scale. In algae cultivation, the PBRs are designed to maintain the unialgal culture and for a high production of biomass. In this context, a helical type photobioreactor is designed with the same configuration of a conventional tubular photobioreactor, but it provides efficient space utilization (Singh & Sharma, 2012). On the other hand, bubble columns and airlift photobioreactors are mainly developed for efficient heat/mass transfer and gas exchange (Li et al., 2021); a flat plane photobioreactor is specifically designed for efficient light-harvesting where the larger surface of the reactor is operated in such a way to capture the maximum light (Posten, 2009). The stirred tank photobioreactors provide proper homogenized condition to cell culture (Ogbonna et  al., 1996; Singh & Sharma, 2012), which is popular at the industrial level. The cultivation process is normally designed and tested in the series processes from laboratory-scale using Erlenmeyer flask, laboratory-scale photobioreactor, pilot-scale photobioreactor before going into the industrial-scale photobioreactor. The process, requirements, and considerations of upscaling from laboratory-scale to industrial-scale photobioreactor have been reviewed and detail given under the sections.

2.2  Microalgae cultivation scaling-up process Scaling-up of microalgal culture from laboratory to large scale through the open or closed system is a complex and challenging process requiring various skills toward its operation and maintenance. In the scaling-up process, the essential factor is a selection of desired algal species followed by raising the initial culture. The basic optimization procedure must be implemented to increase the inoculum with high culture density. Further, the acclimatization step should be followed to transfer the algae culture from the laboratory to a large scale using a photobioreactor with a high growth rate and less operation cost, is also a tedious process, and this must be addressed carefully. Additionally, to minimize the requirement of stock cultures inoculum for maintaining a unialgal culture that is free from other contamination should be taken care during mass cultivation. Other concerns are maintaining unialgal culture for the long term, with stable biomass productivity is a vital and aggregation process due to prevailing conditions such as variable irradiance, temperature, rainfall, etc. Therefore, developing standard methods and protocols for successful algal cultivation both on the laboratory and industrial scale should be established. Another common feature in algal cultivation is maintaining the culture reliability for a long period and having high biomass productivity is based on the operators’ experience (Borowitzka & Vonshak, 2017). The scale-up of algal culture is done by 1:10 volume ratio, that is, 100 mL seed culture in 1 L culture medium. Some algal species are highly sensitive to highlight; thus, for this reason, the scale-up factor may need to be reduced to avoid the photoinhibition problems after culture inoculation. During this process, extended scale-up time may also increase the cost and high risk of contaminations. Therefore, to address these issues on a large scale, a semicontinuous culture system should be encouraged rather than a batch culture system. Most tests of biochemical products are done on a lab-scale. Although many articles report upscaling, there is a lack of analysis of the limitations and solutions since the experience

Chapter 2 • Design and scale-up of photobioreactors  13

depends on the facility. Further, the success of the industry has a competitive advantage related to the successful upscale process. Apart from the type of photobioreactors used, the principal goal of scaling-up on microalgal photobioreactors mainly involves the maintenance in transitioning the volume of desired level productivity from small, lab-, pilot-, and up to industrial-scale levels, and control in biofouling, oxygen build-up, as well as temperature management. It eventually requires certain hydrodynamic circumstances like appropriate degree of agitation to attain a turbulent flow of the culture and some specific environmental status like lighting for the optimization of the light regime with a good mass transfer. When compared to the open raceways scaling up, the photobioreactors can be considered as the most favorable one for microalgal productivity since they reduced detrimental cultural contamination as well as material degradation, reliability, and sustainability (Cuello et al., 2016). For instance, the volumetric productivity of Spirulina platensis could go over by the open raceways as much as 24 times. Frequently, the scaling-up of microalgal productivity at the small scale has been evaluated in terms of the performance of photobioreactor. While pilot-scale scaling-up expectations are based on authentically published experimental outputs. The scaling-up efforts should be minimized for the application of fresh long lasting materials for photobioreactors to widen the range of valuable products from microalgae, beyond that a huge R&D investment for innovative and sustainable antifouling coatings at the inner surfaces of the bioreactors is essential in the near future (Silva & Reis, 2015). In addition to these, the optimal design, operation, of photobioreactors has given substantial importance to minimize the shearrelated cell death for the microalgal strain. The first step of the most excellent technique in scaling-up is scaling-down to the pilot scale under the experimental conditions for the culture, which can be utilized at the final scale of productivity (Silva & Reis, 2015). The traditional scalingup is habitually based on certain empirical criteria, viz. steady power input per unit volume, mass transfer coefficient, mixing time, and impeller tip velocity (Shuler & Kargi, 2002).

2.3  Photobioreactor (PBR) design and its scalability principles Generally, the PBRs refer to closed design configuration systems used to grow the microalgae under a controlled environment, high biomass productivity, and minimum contamination risk. During the PBRs cultivation process, different light sources such as natural (sunlight) or artificial (such as fluorescent lights, RLEDs—red light emitting diodes and LEDs—light emitting white light) are given (Mohammed et al., 2014; Molina Grima et al., 1994; Musa et al., 2019). Different designs of PBRs are available for the scaling up process and they were (i) vertical tubular photobioreactor; it is further divided into two types, namely the bubble column and airlift, (ii) flat panel, (iii) horizontal tubular, (iv) helical type, (v) stirred tank, (vi) hybrid type, (vii) flat-panel airlift, (viii) internally illuminated, and (ix) low-cost plastic bag photobioreactors (Acién Fernández et al., 2013; Deniz, 2020; Loubiere et al., 2011; Mohammed et al., 2014; Quinn et al., 2012; Singh & Sharma, 2012; Slegers et al., 2011; Wongluang et al., 2013; Xu et al., 2009). The closed PBR systems have been shown more advantages than the open systems and are summarized in Table 2.1.

Table 2.1  Description of the cultivation of microalgae in open and closed bioreactor systems [Adopted and modified Refs. Carvalho et al., 2006; Jerney & Spilling, 2020; Pulz & Scheibenbogen, 2007]. Parameters

Open (pond or raceway) systems

Closed (photobioreactor) systems

Loss of H2O Loss of CO2 Quality of biomass Cell concentration Surface area to volume ratio Microalgal cell density Efficiency of harvesting Sterility Variability as to cultivatable microalgal species Contamination risk Contamination control Most expensive parameters Mixing Gas transfer control Super dissolved oxygen (DO) concentrations Temperature control Biomass concentration during production Reproducibility of biomass production Overheating problems Treatment process efficiency Efficient use of light Space occupied Flexibility of production

Extremely high High Not susceptible Low Low Low Low None Not given and the cultivation possibilities are restricted to a few algal species Extremely high Difficult Mixing Poor Low Low

Very low or almost none Very low or almost none Susceptible High High High High Achievable High and nearly all microalgal varieties. Very low or almost none Easy Temperature and O2 control Uniform High High

Difficult Low

More uniform High

Less possible

Possible

Low Low Poor Large Change of production between the possible varieties nearly impossible Not given and the reproducibility depend on exterior conditions Low or medium

High High High Small Change of production without any problems Possible within certain tolerances

Simple Not possible Absolute, production impossible during rain

Complicated Possible Insignificant because closed configurations allow production also during very bad weather conditions Relatively short period, approximately 2–4 weeks

Reproducibility of production parameters Production of complex biopharmaceuticals Process control Standardization Weather dependence

Period until net production is reached after start or interruptions Biomass concentration during production Efficient treatment process Construction cost Operation costs Capital investment Maintenance process

Long periods, approximately 6–8 weeks

High

Low, approximately 0.1–0.2 g/L

High, approximately 2.0–8.0 g/L

Low, time-consuming, large volume flows due to low concentrations Low Low Small Easy

High, shot-time, relatively small volume flows High High Big Difficult

Chapter 2 • Design and scale-up of photobioreactors  15

PBRs are made up of either clear glass or plastic materials for the allocation as well as penetration of light sources. Most of the bioreactors mainly have been fallen under two major categories, namely, (i) suspension culture systems (stirred-tank, airlift, and bubble-column bioreactors) and (ii) immobilization culture systems (membrane, packed-bed, and fluidizedbed bioreactors). But some of the bioreactors have been applied for both the systems, that is, the immobilized cells or enzymes on suitable carriers have been suspended in the stirred tank reactors (STRs) and airlift/bubble-column bioreactors. The selection as well as design of the bioreactors are distinctive; moreover, the reactor design and selection should majorly involve an adequate transfer of gaseous substances (O2 and CO2), sufficient supply of nutrients, proper mixing, continuous removal of waste products, and low shear stress (Varley & Birch, 1999; Wang & Zhong, 2007). A good large-scale bioreactor system should be (i) inexpensive as well as simple, (ii) simple ease of handling and operation, (iii) provide a balanced care for both the mixing as well as mass transfer process, (iv) modest shear sensibility between the cells, and (v) easy to control and monitor the working temperature, pH, concentration of DO (dissolved oxygen), and the substrates, etc. (Varley & Birch, 1999; Wang & Zhong, 2007). Also, the bioreactor design and selection should be considered as cGMP (current good manufacture practice) compliance in the biopharmaceutical industry. The design and selection considerations for PBRs should be (i) permit the cultivation of various microalgae species commonly, (ii) provide uniform illumination of the microalgae culture surface and a fast mass transfer of CO2 and O2, (iii) minimize the reactor fouling, especially with its light-transmitting surfaces, (iv) attain high rates of mass transfer with neither the damage of cultured cells nor suppress their growth, (v) work under the conditions of intense foaming with high rates of mass transfer, (vi) supply the nutrients effectively to the cells, (vii) control the contamination, and (viii) have low or minimum nonilluminated regions. Besides, both the designing and selection of PBRs are determined by the separation of desired end products in the cultivated biomass, as well as the quality of the target products (Acién Fernández et  al., 2013; Carvalho et al., 2006; Wang & Zhong, 2007). The design of various types PBRs has been discussed below in detail. Fig. 2.1 depicts the various type of photobioreactors utilized for mass cultivation of microalgae biomass.

2.3.1  Vertical tubular photobioreactors In general, the closed tubular photobioreactors (TPBRs) have widely been utilized for industrial scale biomass production (Zittelli et  al., 2013). These types of PBRs are made of transparent glass or plastic tubes and pumps or air streams circulate the culture. Also, these TPBRs have a high S/V ratio up to 80 m–1, which allows working with a maximum biomass concentration culture. They are generally constructed with transparent tubes of 0.1 m in diameter, that is, the length and diameter of the tubes should be well designed to protect O2(g) accumulation and to reduce the photobioreactor heat loss. TPBRs can further be subdivided into three main types, namely, (a) serpentine, (b) manifold, and (c) helical photobioreactors. The serpentine and manifold photobioreactors can be horizontal, vertical, inclined, or conical (Zittelli et al., 2013). The most widely stirred tank, bubble column, and air-lift PBRs are extensively utilized in closed systems at an industrial scale, which all come under the category of tubular PBRs

16  Current Developments in Biotechnology and Bioengineering

FIG. 2.1  Various types of photobioreactors are utilized for the mass cultivation of microalgae biomass.

(Acién Fernández et al., 2013; Carlozzi, 2008) and also they allow to control the culture conditions as well as reduce the risk of contamination (Acién Fernández et  al., 2013). The vertical column photobioreactors (VCPBRs) are made by vertical transparent glass or acrylic materials tubing, thereby are transparent for the light penetration to the autotrophic microalgae cultivation and at the bottom of the photobioreactor, there found a gas sparger system for the effective conversion of the inlet gas to tiny bubbles. It drives the mixing as well as the mass transfer of CO2 that eliminates the produced O2, during the photosynthetic process. Generally, there is no implementation of manual agitation systems in the design of VCPBR. They are further classified on the basis of their liquid flow patterns inside the reactor into (i) BCPBR (bubble column photobioreactor) and (ii) ALPBR (airlift photobioreactor) (Kumar et al., 2011). The airlift PBR possesses very excellent mixing possessions, while the bubble column PBR configuration lets effective ventilation (Dasgupta et al., 2010). The agitated photobioreactors (PAPBRs) are a kind of gas–liquid dispersion reactors, that is, transfer of gaseous substances such as O2 and CO2 with the liquid phase, which consists of a cylindrical vessel with nozzles, perforated plates/a ring sparger, used for aeration, proper mixing, and fluid circulation that allows the compressed air/ gas mixtures through the bottom via, without moving mechanical parts.

2.3.1.1  Bubble column photobioreactors (BCPBRs) The PBRs contain vertical cylindrical columns of twice the diameter as that of the light source, which is often externally supplied (Singh & Sharma, 2012). It can be characterized by costeffective investment, elevated S/V ratio, short of moving parts, suitable heat and mass transfer, comparatively homogenous environment to culture, the comparable release of O2, gaseous mixture residues, etc. The outside of the column only supplies light energy for autotrophic cultivation. The rate of gas flow with shapely created light–dark cycles determines the photosynthetic efficacy greatly. The increase in gas flow rate leads to shorter light–dark cycles that could significantly increase the photosynthetic efficiency of microalgae (Singh & Sharma, 2012).

Chapter 2 • Design and scale-up of photobioreactors  17

Both the mass transfer of CO2 and mixing have been done through gas bubbling from a sparger (Kumar et al., 2011; Wang et al., 2012); therefore, the design of sparger is critical to the performance of bubble column, which is also different from that of tubular PBRs. In bubble columns, the mixing can be arbitrary as well as erratic through turbulence created by the gas mixture that is sparging from the bottom of the PBRs (Halim et al., 2011; Wang et al., 2012). Consequently, the uneven light intensity may be exposed to microalgae cells in favor of the occurrence of cell sedimentation. In scale-up of the photobioreactor, installation of the perforated plates (act as the sparger) and redistribution of the coalesced bubbles inside the column help to raise the turbulence (Halim et al., 2011; Wang et al., 2012).

2.3.1.2  Airlift photobioreactors (ALPBRs) Airlift photobioreactors (ALPBRs) manly possess an old-style bioreactor design, made by a vessel of two internally connected zones. The ALPBRs with various configurations have been constructed for use in a variety of fermentation processes, cell cultures, and biological wastewater treatment. The ALPBRs designs can further be classified on the basis of circulation mode, into two forms, viz (i) internal and (ii) external loops (Acién Fernández et al., 2013). Moreover, the ALPBRs showed some characteristic advantages over the stirred tank photobioreactors (STPBRs) and they are (i) distributing shear stress more gently as not having a mixer or impeller (ii) easy to construct, (iii) scale-up with a low cost, etc. But the lack of an impeller also brings some disadvantages such as poor fluid mixing for highly viscous culture, compared to STPBR and serious foaming under high aeration. It is also suggested to have better mixing characteristics that are a rectangular ALPBR possesses an effective photosynthesis efficacy, though the complexity in design and difficulties in scale-up are the demerits.

2.3.2  Flat panel photobioreactors (FTB/FPPBRs) Samson and Leduy designed FPB or FPPBR bioreactors for the very first time, which are illuminated and agitated on both sides by fluorescence lamps and by aeration, respectively (Samson & Leduy, 1985). The most popular selection among the closed PBRs, are having a cuboidal shape and consists of a narrow light path (Singh & Sharma, 2012). Such reactors are made by glass, plexiglass, thin-film plastics and polycarbonate materials, pasted with silicone rubber. The light path can easily be altered and characterized by a high S/V (surface area to volume) ratio and open gas separation systems. Agitation is provided by either bubbling air from one side through a perforated tube or rotating it mechanically through a motor (Singh & Sharma, 2012). For the cultivation of microalgae, both horizontal and vertical FPBs or FPPBRs have commonly been utilized, although the vertical system necessitates a good solar orientation for maximizing the irradiance capacity (Richmond & Cheng-Wu, 2001; Sierra et al., 2008; Xu et al., 2009). These photobioreactors have widely been utilized for high microalgae biomass production within indoor and outdoor culture systems. Hence, its characteristic advantages include low accumulation of DO and high illuminating surface area when compared to the horizontal tubular photobioreactors and their modular design is enough to scale-up process. The comparisons of different type of tubular bioreactors with flat plate photobioreactors are summarized in Table 2.2. These thinner tubular FPPBRs showed some advantages, as they possess narrow

Large

Large

Horizontal tubular model

Helical tubular model

Medium

Flat panel pivoted at Medium center model Floating type Medium bioreactor model

Flat panel bubbled at bottom model

Flat plate photobioreactors

α-shaped bioreactor Large

Small

Vertical tubular model

Tubular photobioreactors

Type of photobioreactors

––

Degasser

No cooling required

Sea saw motion

Bubbling

Degasser

Heat exchanger

Bubbling at Heat exchange coils bottom or from sides, recirculation Pulsating motion Heat exchange coils

Airlift

Centrifugal pumps Heat exchanger

Open gas exchange at headspace Injection into feed and dedicated degassing units Injection into feed and dedicated degassing units Injection in the vertical units and degassed at top

Gas exchange

Recirculation Shading, overlapping, with diaphragm/ water spraying mechanical pumps

Airlift, bubble column

Surface area to volume Temperature (S/V) ratio Agitation system control Disadvantages

Shear due to entrainment of cells till bubbles burst Good mixing, Scale-up process is difficult Low shear Operate at low –– energy condition, Good agitation, Easy installed on lakes and sea floor

Open gas transfer avoids O2(g) build-up

Scale-up is limited, Major light is reflected due to angle High shear due to pumps, risk of O2(g) build-up and biofouling, Separate gas exchange unit is required High S/V ratio, O2(g) build-up, Easy scale-up by Separate gas exchange, increasing the Pumps exert more shear, number of units Cell debris accumulate inside High unidirectional Formation of foam due to flow rate with low air high cell density flow rate, High S/V ratio

Good mixing, Efficient CO2(g) supply and Removal of O2(g) Adequate angle toward sunlight

Advantages

Table 2.2  Comparison of various types of tubular and flat plate photobioreactors with their characteristic features [Adopted and modified Refs. Das, 2015; Dasgupta et al., 2010].

18  Current Developments in Biotechnology and Bioengineering

Annular triple jacketed with lighting from innermost chamber model Induced diffused photobioreactor model Not required

Large

––

Outer water jacket

Cooling fans

Marine impeller

Magnetic stirrer

Heat exchange coils

Impellers

Medium

Fermentor type with Small internal and external lighting Torus shaped reactor Medium model

––

Greater thickness achievable

High degree of control of various parameters CO2(g) inlet after Good mixing impeller, output conditions owing to at top shape avoiding dead zones Open gas Excellent S/V ratio exchange and temperature control, Open gas exchange

By sparger

Cost of materials

Scaling up is difficult, biofouling

––

Light conversion efficiency is less

Chapter 2 • Design and scale-up of photobioreactors  19

20  Current Developments in Biotechnology and Bioengineering

U-turns (Pulz & Scheibenbogen, 2007). The culture medium is well mixed with air, can be introduced from a perforated bottom tube. Moreover, the panels have mainly been illuminated by one side via direct sunlight as they are inclined/positioned vertically at an optimum angle to face the sun rays (Carvalho et al., 2006; Janssen et al., 2003; Xu et al., 2009). Tredici and Zlttelli (1998) developed and designed near the horizontal flat panel and were further longitudinally divided into five channels along with two plexiglass manifolds at the top as well as bottom with a specific S/V ratio is 40 m–1 in a gas hold up the capacity of 10.3%. The CO2 gas mixture was injected axially via the bottom tubular plexiglass manifolds and the efficiency of photosynthetic process is achieved at 4.8%, which is less compared to the inclined tubular reactor (5.6%) using Arthrospira (Spirulina) platensis M2. Doucha et al. described an optimized large-scale flat plate photobioreactor module of 1000 m2, and one commercially available flat plate photobioreactor has a reported capacity of 6000 L. A continuous culture of Chlorella sorokiniana using FPB or FPPBR showed a short path length under high irradiance conditions. The volumetric productivity obtained was 12.2 g/L/d and it was found to be higher among the green algae, so far discovered under oversaturating light conditions (Cuaresma et al., 2009).

2.3.3  Horizontal tubular photobioreactors (HTPBRs) Horizontally displayed tubular photobioreactors (HTPBRs) have mainly been considered for bulk cultivation of microalgae since they possess a large illuminated area as well as better utilization of sunlight. Some HTPBR systems are successfully scaled up to a volume of about 4000 L or more. The horizontal tubular photobioreactors (HTPBRs) are mainly consisting of a parallel set of connected loops of tubes or transparent polypropylene acrylic or polyvinylchloride (PVC) or low/high-density polyethylene (LDPE/HDPE) pipes with small internal diameters, which are placed horizontally or inclined at a particular angle (Singh & Sharma, 2012; Xu et al., 2020). Its designed to shape offers some advantages when they are utilized for outdoor culture in their orientation toward sunlight. Consequently, this system showed higher light conversion efficiency. Generally, the mixing and agitation of the culture are maintained through an air pump to provide circulation in HTPBR systems and also, the accumulation of O2 could be removed with the help of a degassing system. The industrial large-scale-up processes using these HTPBR systems are relatively easier, when compared to other PBR designs. This PBR system shows some characteristics advantageous due to its high S/V ratio, allowing for adequate microalgae light-harvesting (Ugwu et  al., 2002; Xu et  al., 2020). However, oxygen accumulation is difficult to eliminate in HTPBR systems, which inhibits photosynthesis as well as limits the total culture volume to ensure an adequate oxygen stripping efficiency maintained in the degassing zones of the PBR (Babcock et al., 2016). During scaling up using these HTPBR systems, increasing in the diameter of the tubes will decrease the S/V ratio; rising the length of the tubes could generate CO2 and nutrient gradients as well as the concentration of O2 level that could rise up to even the toxic levels. The design of HTPBR systems are combined in inclined tubular PBRs, which have lower hydrodynamic stress and better illumination because the incidence light angle can be adjusted with the inclination of the PBR; also, mixing is better than in horizontal tubular PBRs. These are with suitable air-residence time, which can provide more dissolved CO2. Such HTPBR systems are basically designed to the effective utilization of

Chapter 2 • Design and scale-up of photobioreactors  21

natural sunlight, but also utilizing artificial light from outside of the tube. An average energy requirement in the HTPBR system is about 4000% that of the bubble column and the flat plate PBRs. Though, similar to the vertical-type tubular PBR, the horizontal-type PBR systems possess some factors like the need for high energy requirement and DO accumulation, restraining the HTPBR systems performance (Sawdon & Peng, 2015; Singh & Sharma, 2012). The operational difficulties in HTPBR systems are similar to other PBR systems in the view that (i) the light penetration can be prevented by the microalgae growth on the wall of the tubes, and (ii) inhibition of the photosynthesis process due to high concentration of oxygen.

2.3.4  Helical type photobioreactors (HPBRs) Helical type photobioreactor (HPBR) is a promising coil-type design that proved an experimentally higher microalgae culture yield (Briassoulis et al., 2010; Soletto et al., 2008). The most spacious HPBR system was designed on the basis of a coil-type bioreactor. This PBR allows a larger S/V ratio for the massive microalgae cultivation and the incident light energy input per unit of volume is high (Acién Fernández et al., 2013; Hall et al., 2003). This HPBR system has a cylindrical shape, constructed from transparent tubing and the photostage that consists of a tube; it is wound helically on a vertical supporting structure. The main advantages of using helical-tubular coiltype photobioreactor (Briassoulis et al., 2010) systems are (i) common to most coil-type systems, (ii) larger S/V ratio to receive illumination effectively, (iii) easy temperature control, (iv) easy to control contaminants, (v) spatial interface, (vi) effective O2 removal, (vii) operation at days, (viii) admiration of artificial light system during the night-time and the overcast periods without any time interval of dark phase throughout the production period, (ix) easy control of pH level via automatically adjusting the supply of CO2 in the helical–tubular coil through the continuous air phase-media inter-phase, (x) usage of a specific type of media circulating pump to avoid cell damage due to hydrodynamic stress, (xi) easy to large scale-up process, (xii) advanced harvesting system that provides a frequent cell concentration monitoring, etc. Carvajal-Oses et al. (2018) reported the production of Spirulina platensis, Isochrysis galbana, Skeletonema costatum, and Chlorella vulgarisvia helical PBR and type of PBRs, showed characteristic benefits for the cultivation of microalgae biomass for more days, require a smaller area and operating costs and are lower in the medium term. But, still, now this helical PBR system shows some problems as it possesses (i) not effective cleaning process due to the hydrodynamic stress on microalgae, (ii) transfer of gas from low to high, (iii) lesser algae growth in tube walls since blockage of the light, (iv) limit on the length of the tube in a single run, (v) high oxygen concentration that can inhibit photosynthesis, etc.

2.3.5  Stirred tank photobioreactors (STPBRs) Stirred tank reactor (STR) is the chief conventional reactor for microalgae productivity; but, the agitation process is carried out mechanically with the help of different sizes as well as shape impellers (Singh & Sharma, 2012). The STR has been turned into a stirred tank photobioreactor (STPBR) through illuminating fluorescent lamps, optical fibers, or light-emitting diodes (LEDs). This STPBR are the most conventional as well as ecofriendly photobioreactor

22  Current Developments in Biotechnology and Bioengineering

and they have extensively been utilized for carrying out culturing the suspension of microbial cells and enzymatic processes, industrial bioprocesses, batch operations, etc., that is, this type of photobioreactor is considered as the backbone of the industrial fermentation process with “undeniable emperor” in this field (Merchuk, 1991). Usually, the air bubbles containing enriched industrial-grade CO2 sources and are bubbled at the bottom of the STR for microalgae growth with the baffles that are widely utilized to reduce the vortex. The STPBRs are commonly utilized to grow the microalgae photoautotrophically through sunlight or artificial light sources since the STPBR is mainly used as a laboratory as well as the industry standard (Del Campo et al., 2007; Li et al., 2003; Xu et al., 2009). The STPBR are generally utilized for small to medium productivity of microalgae process via batch or fed-batch operations, but in the industry, the continuous microbial cultural process is somewhat difficult. In the industrial-scale-up the process, the STPBRs commonly consist of a stainless-steel vessel, motor-driven impeller, whereas, in the laboratory scale-up process, borosilicate glass or polycarbonate is commonly used. While in aerobic processes, the devices for the injection of air (gas sparger) into PBR at a position below the impeller are required. Currently, the continuous flow stirred tank photobioreactor (CFSTPBRs or CFSTRs) have widely been utilized as a model to predict maximum productivity of microalgae as well as to establish the practical possibility for large scale-up process (Xu et al., 2009). Moreover, this STPBR shows several merits such as easy to large scale-up, easier process control on lab scale experiments, excellent heat and mass transfer, enhanced mixing quality of fluids as well as the ability of O2 transfer, alternate impellers, etc. However, this type of STPBR shows some disadvantages such as high energy consumption and shear stress, low surface area to volume ratio, which in turn decreases light-harvesting efficiency, concern about sealing and stability of shafts in tall BRs (Deniz, 2020; Saeid & Chojnacka, 2015; Singh & Sharma, 2012). Now-a-days, several modifications on conventional STPBR have been implemented by developing multiple impeller systems that effectively leads to enhancing biomass productivity.

2.3.6  Hybrid type photobioreactors Hybrid type PBRs or semiclosed PBR systems are extensively utilized, which effectively utilize the advantages of two different types of reactors and one overcomes the disadvantage of the other (Deprá et al., 2019; Narala et al., 2016; Xu et al., 2020), that is, these photobioreactors combine two or more system configurations of open and closed systems and also arise attempting to compensate the disadvantages of one PBR system and to enhance the virtues of the other. Deprá et al. (2019) developed and tested at a lab-scale novel PBR configuration, which consists of two major PBR configuration units of a closed bubble column reactor coupled to an open illuminated tubular plat-form structure. These novel PBR systems have been shown to reduce the required surface area and capital costs for the designing process, easy to scale-up of the system with environmental applications as well as commodities development. Xu et al. (2020) developed a pond-tubular hybrid photobioreactor (PTH-PBR), which is composed of one set of horizontal tubular photobioreactors and three raceway ponds for the cultivation of Chlorella PY-ZU1 biomass. The improvement of microalgae biomass yield by PTH-PBR is 31.2% higher than that of the traditional raceway pond, which clearly shows an appropriate absorption of light by horizontal tubes before reaching the raceway pond to generate alternating light and

Chapter 2 • Design and scale-up of photobioreactors  23

dark regions for microalgae growth. The areal microalgae biomass yield is also improved by 54.7% in PTH-PBR compared to the traditional raceway pond, owing to the enhanced flash effect. An integrated airlift system was reported by (Acién Fernández et  al., 2013) and in a thermostatic pond of water there is an external tubular loop that was placed horizontally with a total volume is 200 L. On the one hand, the external loop acts as a light-harvesting unit as it gives a high surface area to volume ratio and controls the temperature of the culture. On the other hand, the airlift system acts as a degassing system where probes can also be integrated to regulate the other culture variables. The main advantages include better control over culture variables that enable higher productivities and reducing power consumption (Acién Fernández et al., 2013; Singh & Sharma, 2012). Similarly, Molina Grima et al. (1994) and Richmond et al. (1993) were introduced an integrated hybrid type photobioreactor system, whereas it is different from the external light-harvesting unit with a loop-like structure from the former one that had horizontal parallel sets of tubes. The temperature of the systems are controlled by previously utilized water via spray over the externally kept light-harvesting unit. However, the horizontally placed tubes will enhance the efficiency of photosynthesis as well as reduce the cost. The major disadvantage is to occupy large land areas and very narrow lightharvesting units, so these PBR systems are cost-intensive, and associated with the requirement of large land area. Lee et al. (1995) designed anα-shaped reactor, that is another type of hybrid system and its shape construction is based mainly on algae physiology as well as sunlight. The culture has flown down to an inclined PVC tube of 2.5 cm ID × 25 m, and lifted 5 m by air to a receiver tank thereby-making 25o with the horizontal to reach another set of air riser tubes. Such processes were repeated to the next set of tubes. A high liquid flow rate could be achieved relatively at low airflow rates as well as with a large S/V ratio, leading to the very high efficiency of the photosynthetic process.

2.3.7  Flat-panel airlift photobioreactors (FPAPBRs) The novel flat-panel airlift photobioreactors (FPAPBRs) are specially designed for the large scale-up industrial production of microalgae as well as cyanobacteria (Bergmann & Trösch, 2018; Bergmann et  al., 2013). This low-cost and environmentally friendly disposal photobioreactor system are developed on the airlift loop principle for the mass production of microalgae using sunlight. These FPAPBR systems are experimentally operated with integrated flow directing static mixers (horizontal culture flow) and downcomer domains (vertical culture flow and loop principle). The reactor was initially designed, developed, patented (Patent number WO 00926833.5; EP 1326959 B1; and EP 1169428 B1), and described (Bergmann & Trösch, 2018; Bergmann et al., 2013) by the Fraunhofer Institute for Interfacial Engineering and Biotechnology IGB (IGB), Stuttgart, Germany in 2000. Subitec GmbH, Stuttgart, Germany, now commercializes such a reactor. In a large-scale-up process, the volume of the FPAPBR system is increased from 5 L lab-scale into 30 L industrial-scale and then finally increased to 180 L by Subitec GmbH and this scale-up step to a pilot plant consists of linking several reactor modules. The FPAPBR is well suited for smaller and larger-scale production of microalgae. The most characteristic noticeable feature of the FP PBR is the mostly incorporated static mixers, allowing for a controlled movement of microalgae cells from the illuminated surface area to the dimly

24  Current Developments in Biotechnology and Bioengineering

lit interior of the PBR. The reactor itself is inexpensively made from two deep-drawn plastic sheets, including static mixers, manufactured by twin-sheet technology. The performance of FPAPBRs is mainly depend on four phases (Bergmann et al., 2013), being, as such, for ordinary PBRs, gas (O2/CO2 in and exhaust gas out), liquid (medium), and solid (biocatalyst), coupled with the fourth phase being lighted. Hereby, the efficiency may be defined by the mixing time/ energy input required per reactor volume for a growth-limiting substrate and the resulting volumetric productivity in gram dry weight per liter reactor volume per time (Pvol). The sufficient mass transfer of CO2  and O2  for unlimited growth is ensured by combining the airlift-driven principle and static mixers. This PBR is characterized through a special shape including an airlift-driven intermixing, combined with static mixers, which offers an efficient distribution of light with a low energy input for intermixing, that leads to high productivities as well as biomass concentrations and also low shear forces taking effect on the microalgae cells. It also generates a circulating flow within the PBR compartments when air bubbles rise to the top. Due to the static mixers, the upcoming gas bubbles are directly inducing definite vortices in the interconnected reactor compartments. The vertical tube in the middle of the PBR leads the microalgae suspension back to the bottom, resulting in a vertical circulation of the reactor content (Vogel & Bergmann, 2018). Moreover, highly transparent plastic materials in the PBR system are used to cultivate photosynthetic microorganisms, mostly microalgae but can also be used for other applications to which an optimized liquid flow and a direct insight into the cultivation chamber might be of significance. Issarapayup et al. (2009) proposed a novel feasible alternative design of flat panel airlift photobioreactor (FPALPBR) to cultivate Haematococcus pluvialis NIES-144 and the large scale-up could be achieved via just increasing the length of the reactor system. The17 L FPALPBR system has proven that maximum cultivation with a specific growth rate of 0.63 day–1, which is higher than the conventional 17 L cylindrical ALPBR with a specific growth rate of 0.32 day–1. Also, the best growth performance was obtained by operating the system at a superficial velocity of 0.4 cm/s and a downcomer-to-riser cross-sectional area ratio of 0.4. The 17L FPALPBR system showed a capable of reasonable growth characteristics with a maximum cell density of 4.1 × 105 cell per mL and a specific growth rate of 0.52 day–1 being achieved. A similar level of performance was obtained from the 90 L FPALPBR system, that is, cell density of 40 × 104 cell per mL, but a slight decrease in specific growth rate to 0.39 day–1. From the simple economic analysis, the 90 L FPALPBR system is found to be the most cost-effective process with the 18 g cultivation of algae for approximately US$ 21 than other systems.

2.3.8  Internally illuminated photobioreactors (IIPBRs) Generally, the novel design of PBR systems has been characterized by its small layer thickness to assure a sufficient illumination of the photosynthetic cells, which leads to maximum growth of microalgae biomass, that is, to require high S/V ratio, high efficiency in the use of CO2 and good utilization of light energy for the intensive large scale-up process. The most popular tubular type PBR systems, the tubes are usually consisting of transparent glasses or plastic materials with their diameter 10

48 ± 5.4 mg/L/day

Agateswar et al. (2017)

4.2.4 Temperature Temperature is one of the major abiotic factors that influences the variation in photosynthetic metabolism and the specific growth rate as the duration of cell division and the cell cycle is susceptible (Ivanov et al., 2021) to changes in temperature. Extreme temperatures or frequent temperature fluctuations do not support the growth of the organism making it stagnant or can even destroy it. Ideal temperatures help an organism to perform biochemical reactions by utilizing the chemicals and the environmental factors around it to its needs. Considering the effects of temperature on the growth of the organism can lead to deriving efficient temperature control systems and can also lead to higher production of the desired organism/product. Bioreactors with temperature control allow us to maintain ideal conditions for the organism to grow and sustain. (Serra-Maia et  al., 2016). Most algal species have optimum productivity rates in the temperature range of 10–40oC (Gonçalves et  al., 2016). At subzero temperatures, though few species might survive, there is a possibility of the formation of ice crystals which would eventually cause cell death. At temperatures above 40°C, there would be cell death and destruction of enzymes and products with an exception in thermophilic algal species like Desmodesmus (Endres et al., 2018). D. salina could be viable up to temperatures of 43°C and soon the viability decreased after this temperature. This was measured by experimentally controlled conditions at five climatic locations such as tropical, subtropical, temperate, etc. (Rohit et al., 2016). The temperature which was optimum and yielded higher biomass concentrations varied for different species under the same conditions. For species Chlorella vulgaris, the optimum temperature was 25.4°C. Similarly, the optimum temperatures for species, Synechocystis salina, Microcystis aeruginosa was found to be 26.4°C and 25.6°C respectively (Gonçalves et al., 2016). It was also observed that the process of cell death due to high temperatures was not a sudden or a one-step process but a two-step process which is quick depletion of the integrity of the cells during heat exposure and then a slower process which occurs after the cells have been exposed to higher temperatures. It was also observed that the cells became mildly porous when exposed to this kind of environment especially during the faster stage (Béchet et al., 2017). Algal species like Chaetoceros pseudocurvisteus and Chaetoceros sp. have an optimum temperature

Chapter 4 • Factors affecting the microalgal biomass productivity in photobioreactors  67

Table 4.3  Data representing microalgal species with optimum temperatures. Species

Temperature (°C)

Biomass productivity

References

Chlorella sp.

25–30

–

Singh and Singh (2015), Gatamaneni et al. (2018)

Chlorella vulgaris

20–25

13.5–49.7 (mgdwL−1d−1)

Gatamaneni et al. (2018)

Chaetoceros calcitrans

30

0.270 g/L

Gatamaneni et al. (2018)

Phaeodactylum tricormutum

16–26

–

Gatamaneni et al. (2018) −1 −1

Synechocystis salina

15–35

5–38.2 (mgdwL d )

Gonçalves et al. (2016)

Nannochloris oculata

20–30

–

Gonçalves et al. (2016)

Tetraselmis gracilis

11–16

–

Gatamaneni et al. (2018)

Microcystis aeruginosa

25

–

Gonçalves et al. (2016), Singh and Singh (2015)

Scenedesmus almeriensis

35

0.730 g/L

Gatamaneni et al. (2018)

Nannchloropsis salina

26–35

–

Gatamaneni et al. (2018)

Scenedesmus sp.

20–30

–

Singh and Singh (2015)

Tetraselmis subcordiformis

20–25

–

Gatamaneni et al. (2018)

Chlorella minutissima

28

–

Gonçalves et al. (2016)

B. braunii

30

–

Singh and Singh (2015)

Chlorella Sorokiniana

35–40

7.7–13.9 g DW/m2

Béchet et al. (2013)

*DW/dw represents dry weight.

as 25°C (Gatamaneni et al., 2018). During the production of lipids using the microalgal species, it was observed that the increase in the temperature caused more lipid production especially saturated fatty acids. This might also vary for algal species and can also decrease in a few. In algal species such as Nannochloropsis oculata has an increase in the production of saturated fatty acid content (Ma et al., 2016). Optimal growth concerning temperature for a few species are cited in Table 4.3. Geographical locations of the bioreactors can contribute to the temperature variations that occur during the production process. Regardless of the type of PBR, either closed or open, are directly or indirectly affected by the temperatures that surround them. Temperature fluctuations based on the place of production are very prominent mainly when the bioreactor is outdoors (or which uses direct sunlight as the light source). Production process parameters can be changed likewise if accurate predictions of these temperature fluctuations can be made (Béchet et al., 2013). For open PBRs, the temperatures vary with changes in seasons. In summers, due to extreme heat especially in tropical regions, the temperature might reach up to 30°C or even more. This might cause an increase in lipid production but not always because it’s generally not considered as the optimal temperature for enzyme activity (Robinson, 2015). Also, there is denaturation of proteins at this temperature leading to the loss of essential components. The temperature effects need to be controlled in such a way that they help produce ideal components without causing any degradation to the existing components or the algal species itself. It was also observed that in most algal species, the optimal temperature range caused a lengthy plateau phase (Suh et al., 2003).

68  Current Developments in Biotechnology and Bioengineering

4.2.4.1  Temperature versus productivity Enzyme activities increase with temperature when the temperature is within the range of the optimum temperature or when less than the optimum temperature. This increase in temperature (within an optimal temperature range of the species) can have an impact on the enzymeenzyme interactions, enzyme kinetics, etc. A case can be taken wherein C. vulgaris the enzyme activity of Rubisco or Ribulose-1.5-bisphosphate was high in the range of 20–38°C and for the species, Phaeodactylum tricornutum the increase was observed in the range of 10–20°C (Gonçalves et  al., 2016). Biomass productivity was also measured in species like T. suecica, which showed good biomass productivity at a temperature of 30°C. The lipid content produced by the microalgal species of T. suecica, Chaetoceros sp, Nannochloropsis sp experienced a fourfold decrease when the temperature was raised to 40°C (Lim et al., 2012). For cultures such as Auxenochlorella pyrenoidosa the biomass productivity was high in the temperature range of 25–40°C and ranged from a concentration of 0.126–0.134 g/L/day and biomass productivity decreased drastically as the temperature was increased to 60°C (Mello & Chemburkar, 2018). When the temperature is increased, dissolved oxygen concentration also increases in the nutrient broth. This might lead to higher photosynthesis in cells but kills a fraction of cells. The nutrients which are utilized by the killer cells and the cells can cause the accumulation of waste products. This fraction of cells cannot be recovered and hence can cause a decrease in the biomass content when considered on a broader scale (Mello & Chemburkar, 2018).

4.2.5  Microalgal strains Numerous microalgal strains have been extensively researched to enhance productivity and valueadded products (Rajasri et  al., 2020a). Among the different strains, the most commonly grown and found strain of the microalgae is Chlorella sorokiniana (Chen et al., 2013). Table 4.4 depicts Table 4.4  Various microalgal strains used for studying the productivity in different PBRs. S. no Microalgal strain

Type of PBR

Biomass produ­ Lipid productivity ctivity (g/L/day) (g/L/day) References

1

Chlorella sorokiniana

Bubble column PBR

0.58

0.044

Chiu et al. (2008)

2

Chlorella vulgaris

Bubble column PBR

0.73

0.079

Chiu et al. (2008), Rajasri et al. (2014)

3

Neochloris species

Bubble column PBR

0.08–0.10

0.20

Peng et al. (2016)

4

Spirogyra species

Flat-panel airlift bioreactor

0.25–0.45

0.06–0.07

Vogel and Peter (2018)

5

Chlorella species

Bubble column PBR

0.19–1.484

0.034

Chiu et al. (2008)

6

Chlamydomonas sps.

Torus PBR

0.24

0.159

Takache et al. (2012)

7

Arthrospira maxima

Tubular PBR

0.205

0.052

Ferreira et al. (2012)

8

Brotrycoccus braunii

Bubble column PBR

0.25

0.05

Kojima and Kai (1999)

9

Nanochloropsis sps.

Flat-panel PBR

0.17–0.143

0.060

Safafar et al. (2016)

Stirred tank PBR

0.8

0.0077

Santek et al. (2017)

10 Euglena gracilis

Chapter 4 • Factors affecting the microalgal biomass productivity in photobioreactors  69

the type of microalgal strain and the type of PBR used for enhancing the overall productivity. Besides the species of Chlorella, other green algae such as Euglena, Spirogyra, Chlamydomonas, Nanochloropsis species have greater importance and play a vital role in the ecosystem. Some well-known examples of microalgae species that have been found suitable for the production of biodiesel using heterotrophic modes are Amphipleura, Cytotella, Cymbella, etc. Some heterotrophically grown chlorophytic algae include Botryococcus, Chlorella, Chlorococcum, Neochloris, and many more (Jareonsin Surump & Pumas Chayakorn, 2021; Silva et al., 2021). The growth of the microalgae is considerably very fast under optimum conditions. Biomolecules such as carbohydrates, proteins and lipids are considered to be major components of a microalgae cell, different strains have different components of these mentioned biomolecules. Minor components such are carotenoids and chlorophyll are also present that are generally used in industries such are pharmaceuticals, cosmetics, and food. Other sources or components such as light, CO2, pH, and temperature also affect the growing conditions of the microorganism.

4.2.6  Trophic modes of cultivation The mode of growth mechanism also has a great influence on biomass yield in microalgal cultivation. Among the three growth mechanisms; autotrophic, mixotrophic, and heterotrophic, mixotrophic is particularly attractive due to the ability of the algae to be grown via both autotrophic and heterotrophic metabolism by using sunlight and inorganic/organic carbon (Roostaei et al., 2018). Using the light source as an energy requirement and CO2 as a carbon source makes the autotrophic mode of operation effective as the microalgae can take advantage of both the assimilatory factors naturally present (Saxena et  al., 2020). The biggest disadvantage of this mode of operation is that there is a lot of lipid and pigmentation loss which results in the lesser accumulation of sunlight and during the absence of light this mode of operation is least effective (Perez-Garcia & Bashan, 2015) On the contrary the heterotrophic mode of operation shows how these microorganisms are cultivated using an external organic source. Though external organic sources are used for cultivation yet these heterotrophic modes have shown significant advantages which include high cell density, increased specific growth rate, increase in the lipid content, and many more (Barros et al., 2019; Perez-Garcia et al., 2011). For any lipid-rich microalgae, to grow under heterotrophic conditions few factors have to be taken care of viz., it must be able to gown in the absence of sunlight, it should quickly adapt to the changes in the environment, there should be easy uptake of external organic substances, and should be able to take up the stress rising during the reaction in the bioreactor. Some microalgae which use organic carbon as energy sources are found to be advantageous as they do not require light as an energy source which is considered to be very advantageous. The mixotrophic mode of operation is more complex as it involves the combination of both auto and heterotrophic modes of operation. Both the autotrophic and heterotrophic operations occur concurrently by assimilating the CO2 and organic material. The mixotrophic strategy can reduce the cost of production and energy requirement as well. Mixotrophic microalgae can help in the treatment of flue gases and wastewater as they have a dual advantage of absorbing CO2 and also utilizing the organic carbon present in the medium of growth. Mixotrophic cultivation offers an edge over the facts of the high rate of heterotrophic cultivation and lower biomass

70  Current Developments in Biotechnology and Bioengineering

Table 4.5  Cultivation modes using different microalgae and PBRs. Microalgae type

Cultivation type

PBR type

References

Chlorella vulgaris

Photo autotrophic

• Tubular PBR • Flat-plate PBR

Saha et al. (2018)

Porphyridium cruentum

Photoautotrophic

• Tubular PBR

Saha et al. (2018)

Schizochytrium sp.

Heterotrophic

• Grown in large stainless- Sushanta kumar et al. steel fermenters (2018)

Dunaliella salina

Two-way cultivation using photo autotrophic method

• Tubular PBR • Unstirred open ponds

Wolf et al., 2020, Rebolledo et al. (2019)

Nannochloropsis sp.

Mixotrophic and photo autotrophic

• Helical tubular PBR • Raceway pond

Saha et al. (2018)

Haematococcus pluvialis

Photo autotrophic and mixotrophic

• bubble column • airlift bioreactor

Koyande et al. (2019)

Arthrospira sp.

Photo autotrophic

• Tanks • Open raceway ponds • stirrers

Rogers et al. (2014), Saha et al. (2018)

Phaeodactylum tricornutum

Photoautotrophic

• Tubular PBR

Rodolfi et al., 2017

Odontella aurita

Photoautotrophic, Mixotrophic and Heterotrophic

• flat-plate PBR • cylindrical glass columns

Saha et al. (2018)

Botrycoccus braunii

Open raceway pond cultivation

• Bubble column PBR

Ashok kumar and Rengasamy, 2012

productivity of autotrophic cultivation in large-scale production (Hari Prasad et al., 2018; Zhan et al., 2017). Studies have shown microalgae initially grow in heterotrophic/mixotrophic mode until a minimum substrate concentration is available, later continue to grow under autotrophic metabolism (Mirzaie et al., 2016). Table 4.5 shows the different modes of cultivation in which different microalgae are grown and the type of PBR used.

4.2.7  Operation modes of cultivation The above said operational modes can be open, three other strategies implemented to cultivate the microalgae on large scale are Batch, Fed-batch, and continuous modes. Unfavorable conditions exposure of microalgae will initiate the accumulation of TAGs (Hu et al., 2008). In batch mode of operation, the TAGs are produced in conditions that ensure nitrogen rich conditions followed by nitrogen starvation for its accumulation (Benvenuti et al., 2016; Breuer et al., 2015; Mulders et  al., 2012; Rodolfi et  al., 2009; Santos et  al., 2014). Batch mode, a simple process, have the ability to accumulate TAGs up to 60% of total algal biomass dry weight (Breuer et al., 2012). But, the fed-batch mode of operation will aid in achieving high biomass densities as they are frequently fed with high quantities of nutrients and the end products are removed so as to maintain optimum conditions in the reactor. The literature survey exhibits the highest biomass productivity in the fed-batch mode operation (Bumbak et  al., 2011). And, the final operational mode, continuous mode, is typically productive in comparison to batch and fed-batch

Chapter 4 • Factors affecting the microalgal biomass productivity in photobioreactors  71

processes, as it functions in steady-state conditions, control of the process can be simpler and more specific (Coelho et al., 2014).

4.2.8  Mixing, heat, and mass transfer For effective microalgal cultivation, mixing is the most important parameter. Different types of mixing mechanisms are available in microalgae cultivation which are based on the microalgae strain being grown, cultivation system (open ponds or closed systems), and scale of the cultivation (small or commercial scale cultures) (Ugwu & Aoyagi, 2012). Mixing in microalgal cultivation is mainly done to enhance the mass transfer efficiency in the culture, keep the cells in suspension, and also maintain efficient distribution of gases CO2/air apart from nutrients. Moreover, efficient mixing would improve the photosynthetic activity s and thus, enhance the biomass productivities. It is, therefore, important to implement efficient mixing to maximize the potentials of microalgae during cultivation (Matteo Prussi et  al., 2014; Qingshan et  al., 2017; Ugwu & Aoyagi, 2011). Mixing ensures uniform distribution of light in the PBR and thus improves the light utilization by the algal cells. In a well-mixed photo bioreactor cells from the highly illuminated surfaces are circulated to the low illuminated surfaces, resulting in a flashing light effect (Xue et al., 2013). On the other hand, if algal cultures are not well mixed, the cells closer to the highly illuminated regions are photo inhibited by the high illumination whereas those at the lower part of the PBR are light-starved. Generally, in open pond systems, paddle wheels are used for effective mixing (Hase et al., 2000). One of the oldest methods of cultivating microalgae in the open pond is the Raceway system. Paddlewheels are designed by mounting blades axially on a rotor that circulates the cultures in a raceway manner in the pond. Mixing speed in ponds is relatively slow and not turbulent, unlike closed systems. Poor mixing of microalgae in ponds would result in flocculation of the cells. A combination of paddling and baffling can provide better mixing of cultures (Okoro et al., 2019). Mixing in closed systems is done by aerating directly with an air pump or indirectly by airlift system (Yustinadiar et al., 2020). Bubbling of air at high aeration rates can be used in an airlift system whereby a tremendous amount of force is required to circulate cultures from the riser to the downcomer sections however it has to be as moderate as possible to avoid some damages to the algal cells. Airlift bioreactors are highly energy-efficient relative to stirred fermenters as there is no stirring mechanism involved in the former (Guieysse et al., 2011). Heat and mass transfer characteristics are good and it is efficient in suspending the solids than bubble columns. All performance characteristics of airlift systems are related to gas injection rate and the resulting rate of liquid circulation. Liquid velocity is also affected by the geometry of the vessel and the viscosity of the fluid. In tubular PBR introduction of vertical mixing (Grima et al., 1999) or installation of static mixers (Ugwu et al., 2003; Ugwu & Aoyagi, 2011) are used. Static mixers can ensure that cells are circulated between the upper and lower sections of the tubes, thereby resulting in high mass transfer and efficient distribution of light and nutrients in the PBR. Ambient air was filtered and bubbled along with pure CO2 through a porous plate sparger located just above the bottom of the inside cylinder (Al Taweel et al., 2012; Podola et al., 2017). Although draft tube types are very promising in column PBRs, they can cause light stratification problems, especially the opaque types (Bitog et al., 2011). Including the internal lighting

72  Current Developments in Biotechnology and Bioengineering

structures with transparent material will offset the problem to a certain extent. The temperature generated due to sparging and metabolic reactions inside the reactor can be controlled using the coolant that is pumped outside the chamber through a recirculation process.

4.2.8.1  Mass transfer characteristics In algae, photosynthesis production is always associated with oxygen production and carbon dioxide consumption. Some microalgal species are inhibited by oxygen levels above air saturation (Pruvost et al., 2016b), whereas carbon dioxide concentrations should not fall below a critical level, as this limits the supply of carbon sources. The volumetric mass transfer coefficient (kLa) must therefore be high enough to ensure adequate oxygen levels and CO2 availability in the culture medium. It is important to note that high oxygen concentration does not seem to hinder the growth rate of some strains. In volumetric mass transfer coefficients (kLa), two terms are involved: (1) the mass transfer coefficient (kl), and (2) the interfacial area per unit volume of the aerated reactor (Barbosa et al., 2003). kLa is primarily determined by superficial gas velocity, sparger design, and medium properties. Due to the greater number of bubbles formed during the homogeneous regime, the volumetric mass-transfer coefficient increases linearly as the superficial gas velocity increases. Bubbles do not interact under these conditions. The overall volumetric mass transfer coefficient (kLa) and gas hold up are very useful parameters for studying the performance of a PBR. Aeration rate and gas holdup influence the availability of light in bubble columns. The oxygen generated during photosynthesis has to be removed since excessive dissolved oxygen leads to photosynthetic suppression. The magnitude of the overall gas-liquid mass-transfer coefficient, kLa governs the overall removal capacity of oxygen. Apart from mixing the culture, aeration removes the photosynthetically produced oxygen from the broth. It is well known that the accumulation of oxygen inhibits photosynthesis (Pedruzi et al., 2020). Oxygen removal capacity is governed by a good mass transfer coefficient. Similarly, for efficient transfer of CO2 in photosynthetic cultures, good mass transfer of gas-liquid is also required. The influence of process operation parameters on characteristics of mass transfer was discussed by Bang-Fuh Chen and co-workers (2018). The concentration of dissolved oxygen was measured using a dynamic method which was developed by Winkler (1888). The kLa was then calculated using the Eq. (4.1).

(C − C ) = k a t − t ln ( ) (4.1) (C − C) *



o

*

L

0

Where, C*- Saturation concentration of dissolved oxygen, Co- Initial concentration of dissolved oxygen at a time to and C- Dissolved oxygen at any time ‘t’. For understanding the factors influencing kLa value a case study of internally illuminated bubble column PBR was considered. Gas-liquid mass transfer in bubble columns systems is reported extensively (Chisti, 1989, 1998, 1999a; Mubarak et al., 2019; Zedníková et al., 2018). In addition, compared to airlift reactors, few factors influence kLa values in bubble columns. For a given fluid, the kLa data obtained in different columns generally compare well irrespective of the column aspect ratio (Chisti, 1989), so long as the column diameter exceeds about 0.1 m, which was the case here in IIBCPBR. The measured kLa value [0.0056 min−1] by some of the well-known correlations obtained in a bubble column reactor. Based on this data, it can be deduced that the longer mixing time could result

Chapter 4 • Factors affecting the microalgal biomass productivity in photobioreactors  73

FIG. 4.1  Various factors affecting the algal productivity.

in longer residence time which will invariably improve the gas-liquid transfer efficiency in the PBR (Musa et al., 2019). Hence, various engineering (light and hydrodynamics) and operational (pH, microalgal strains, PBR design, temperature, cultivation mode, etc.) parameters influence the algal productivity and the same has been depicted in Fig. 4.1.

4.3  Factors influencing the process scale-up 4.3.1  Engineering parameters 4.3.1.1  Light regime A cell’s light regime depends upon how it receives light and by the amount of light it receives. All PBRs operating with high biomass concentrations have an abrupt light gradient because of cellular absorption and mutual shading. Zones of dark and light coexist in dense systems, and cells circulate between them, receiving intermittent light. Based on the duration of each cycle and the ratio between light and dark cycles, photosynthetic efficiency can be calculated (biochemical energy stored in biomass relative to light energy absorbed by cells). A dark-light cycle of several seconds to tens of seconds does not improve photosynthetic efficiency. Such long cycles decrease photosynthetic efficiency in comparison with continuous light (Barbosa et

74  Current Developments in Biotechnology and Bioengineering

al., 2003; Janssen et al., 2003). Moreover, photodamage during long periods of intense illumination decreases photosynthetic efficacy. They are less effective at growing microalgae because of the long cycle times (Barbosa et al., 2003). Conversely, short light/dark cycles (milliseconds or microseconds) can enhance photosynthetic efficiency and reduce photoinhibition (damage to the photosynthetic apparatus) under high levels of light illumination. To reach the best photosynthetic efficiencies, the light/dark cycle period is required to approach the photosynthetic unit transition time (Liao et al., 2014), optical paths (in flat panels) and diameters (in bubble columns), as well as gas flow rate determine average circulation time for each reactor design. In the flat panel, reaction times were calculated by measuring the liquid flow as the rate at which dye disperses inside the reactor and by presuming that the liquid flows at the same speed along the light-path axis. It is not yet known whether this assumption holds for all-optical paths. Therefore, the efficiency of photosynthesis obtained in different systems varies greatly, with the flat-panel yielding higher yields as close to the theoretical maximum as possible (33%). It takes 8 molecular photons (at 680 nm) with corresponding energy of 0.175 MJ to fix one molecule of CO2 (Masojídek et al., 2021). When optically thin cultures are used, only the light intensity can limit photosynthetic activity and cell growth if all other conditions are optimal (Barbosa et al., 2003). As cell concentration increases and the cells receive intermittent light, cell density becomes the most important factor in productivity, as it determines how much light is available to each cell. To reduce the duration of liquid circulation inside the reactor a reduction in the optical path was explored (Rohit et al., 2016; Nagendranatha Reddy et al., 2016). The reduction of the light path 27-fold, from 20 cm to 0.75 cm, led to productivity increase of 50%. In the flat panel PBR attached to a short light path, good biomass concentrations and photosynthetic efficiency were obtained (Janssen et  al., 2003) due to its short optical path. Light regimes can also be affected by gas bubbles. Light can be dispersed and transmitted through gas bubbles, allowing light to penetrate further along the reactor optical path. The impact depends on the size of the bubble, the path of the light, and the density of the cells. The design of the reactor, sparger, the gas input, and the liquid possessions influence the optimal light regime in PBR (Barbosa et al., 2003).

4.3.1.2  Mixing rate On the cell concentration scale, provided that nutrient limitation exists, the mixing rate becomes increasingly effective as a quality control indicator if nutrient sufficiency is not maintained. If the rate of mixing cannot be increased further, due to shear or due to the reactor’s design, determining the light regime for each cell depends on the length of the optical axis. By reducing the optical path, ultra-high cell concentrations can be maintained, thus increasing the ratio of illuminated surface-to-volume and the frequency of light-to-dark cycles. Growth inhibition reduces culture growth as cell concentration increases. Initially, the greater the illumination of the light source, the greater (potentially) the ideal cell density: higher cell density will yield a higher production per culture volume under given conditions, and mixing magnitude has a larger influence on output (Metris et al., 2003). An increase in the mixing rate will result in an enhancement of the light regime as well as a rise in cell density and productivity. If the gas flow rate is increased further, two different things could happen: (1) decreased productivity caused by damage to cells, (2) limitation of light will not allow further increase in productivity; an increase in superficial-gas velocity will not lead to an increase in mean liquid velocity,

Chapter 4 • Factors affecting the microalgal biomass productivity in photobioreactors  75

but will increase fluctuation velocities and increase turbulent dissipation (Serejo et al., 2015). Consequently, improving fluid dynamics by introducing more gas no longer leads to higher efficiency (Modestra et al., 2020). The mechanical simplicity of flat panels and bubble columns is in stark distinction to the intricate flow patterns that develop in these systems. With bubble columns and flat panels, the gas phase exists as a scattered bubble phase in a perpetual liquid stage. Depending on the type of dispersion, the gas phase moves in one of three distinct regimes: (1) A homogeneous bubble regime with superficial gas velocities ( S. The Monod model assumes that the specific growth rate depends on the concentration of a limiting nutrient, which can be carbon, nitrogen or phosphorus. In particular conditions, when the culture is limited simultaneously by two nutrients, the Monod equation can be written as follows:

µ = µ max

S1 S2 (5.7) K S1 + S1 K S 2 + S2

This model has been applied in numerous studies describing nitrogen (Aslan & Kapdan, 2006; Fré et al., 2016; Xin et al., 2010), phosphorus (Aslan & Kapdan, 2006; Wang et al., 2014; Xin et  al., 2010), and carbon (Chen et  al., 2010) uptake by different microalgal species, such as Chlorella vulgaris, Scenedesmus sp., Micratinium sp. and Dunaliella tertiolecta. The kinetic parameters for the Monod model determined in these studies are presented in Table 5.2, as well as for other group A-I models, as a function of a single substrate. Despite the higher applicability of the Monod model, it fails when high nutrient concentrations have an inhibitory effect on microalgal growth (i.e., ammonium or carbon dioxide). Eq. (5.8) shows the relationship between the specific growth rate and nutrient concentration, considering the inhibition effect for higher values.

µ=

µ max (5.8) S   KS   1+ 1+ S   K inh  

where Kinh (in mg L−1) is the inhibition constant. The critical concentration of the nutrient is the value that corresponds to the maximum of the specific growth rate. It can be determined by Scrit = (KSKinh)1/2. Another model describing nutrient inhibition on microalgal growth is the Andrews model (an empirical model). It is a modification of the Monod model, adding a term with an inhibitory effect (see Eq. 5.9).

µ = µ max

S KS + S +

S2 (5.9) KI

This inhibitory effect was observed by Chen and Johns (1994) when growing the microalga Chlamydomonas reinhardtii in environments with different acetate concentrations. For concentrations below 0.4 g L−1, the Monod model effectively described the microalgal growth. However, for higher concentrations, a decrease in the specific growth rate and biomass yield were observed, indicating growth inhibition. In this case, the Andrews model was used to represent the experimental data. Furthermore, inhibition by nitrogen was reported by Zhang et al. (1999) for the same microalgal strain, grown with nitrate, ammonium or urea as nitrogen sources. The Monod model also presents other limitations when describing microalgal growth under nutrient absence in the culture medium. In this case, microalgae can still grow using the nutrients stored in the cell. Several research studies reported this behavior (Flynn, 2003;

Model reference

(Monod, 1949)

Considering nutrient

Limitation µ = µmax

S KS + S

Equation

Scenedesmus sp. LXI

Batch cultures in 250-mL flasks in modified BG-11 medium, at 25°C, a 14 h light/10 h dark regime with an irradiance of 55–60 μmol photons m−2 s−1

Batch cultures in 2.2-L flat-panel air lift reactors in modified f/2 medium, at 28°C, pH 7.5–8.5, continuously illuminated with an irradiance of 17.5 klx

Dunaliella tertiolecta

Chlorella vulgaris Batch cultures in 1-L glass reactors, at 28°C, pH 6, a 14 h light/10 h dark regime with an irradiance of 9.0 W m−2 Batch cultures in 2-L Pyrex bottles Micratinium sp. in a mixture of primary effluent and anaerobic digestion centrate, at 20°C, pH 6.3–7.4, a 16 h light/8 h dark regime with an irradiance of 60 μmol photons m−2 s−1 Chlorella sp.

Chlorella vulgaris

Microalgal species

Batch cultures in 1-L flasks in synthetic wastewater, at 20°C, pH 6.5–7, continuously illuminated with an irradiance of 4100 lux

Experimental conditions

P0: 3.5 mg P L−1 μmax = 0.23 d−1 KS = 3.01 mg P L−1 N0: 12 mg N-NO3 L−1 μmax = 0.0279 h−1 KS = 0.015 mg N L−1 N0: 148 mg N-NO3 L−1 μmax = 0.0262 h−1 KS = 0.65 mg N L−1

P0: 3.5 mg P L−1 μmax = 0.35 d−1 KS = 4.20 mg P L−1

N0: 13.2–410 mg N-NH4 L−1 μmax = 0.225 d−1 KS = 31.5 mg N L−1 P0: 7.7–199 mg P-PO4 L−1 μmax = 0.07 d−1 KS = 10.5 mg P L−1 N0: 2.5–25 mg N-NO3 L−1 μmax = 1.78 × 106 cells mL−1 d−1 KS = 11.8 mg N L−1 P0: 0.1–2 mg P-PO4 L−1 μmax = 1.02 × 106 cells mL−1 d−1 KS = 0.28 mg P L−1 (CO2)0: 0.07–1.5 g HCO3− L−1 μmax = 0.605 d−1 KS = 0.09 g HCO3− L−1

Kinetic parameters

Table 5.2  Group A-I microalgal growth kinetic models as a function of a single substrate.

(Continued)

(Fré et al., 2016)

(Wang et al., 2014)

(Chen et al., 2010)

(Xin et al., 2010)

(Aslan & Kapdan, 2006)

Parameter references

Chapter 5 • Photobioreactors modeling and simulation  95

Model reference S

Limitation, Martinez et al. inhibition and (1999) absence µ=

µm1KinhS + µm2S2 + µm3KSKinh KSKinh + KinhS + S2

µ S + µm2KS Limitation and Martinez Sancho µ = m1 absence et al. (1997) S + KS

S2 KS + S + KI

Equation

Limitation and (Andrews, 1968) µ = µmax inhibition

Considering nutrient

Table 5.2  Cont’d

Batch cultures in 500-mL oblong glass flasks in a culture medium containing half-strength aged seawater, at 25°C, continuously illuminated with irradiances higher than 300 μmol photons m−2 s−1 Batch cultures in 1-L reactors Scenedesmus obliquus P0: 0–9.29 mg P-PO4 in a mineral medium, at 30°C, L−1 μm1 = 0.0466 h−1 continuously illuminated with an μm2 = 0.0256 h−1 KS = 0.20 irradiance of 11.334 klx μM Batch cultures in 1-L reactors Scenedesmus obliquus P0: 0–11.5 mg P-PO4 in a mineral medium, at 30°C, L−1 μm1 = 0.0471 h−1 continuously illuminated with an μm2 = 0.0350 h−1 irradiance of 11.334 klx μm3 = 0.0272 h−1 KS = 0.25 μM Kinh = 0.955.72 μM

Batch cultures in 1-L glass fermenters in modified CR-M1 medium, at 35°C, pH 6.3–7.5, grown in darkness

Martinez et al. (1999)

Martinez et al. (1999)

(Kurano & Miyachi, 2005)

(Zhang et al., 1999)

(Moya et al., 1997)

(CO2)0: 2–10 g C2H3O2− L−1 μmax = 14.8 d−1 KS = 58.5 g C2H3O2− L−1 KI = 0.078 g C2H3O2− L−1 Chlamydomonas N0: 0.2 g N-NO3 L−1 reinhardtii CS-51 KS = 2.6085 g N L−1 KI = 0.1065 g N L−1 N0: 0.2 g N-NH4 L−1 KS = 2.2956 g N L−1 KI = 0.1557 g N L−1 N0: 0.2 g N L−1 (as urea) KS = 2.3978 g N L−1 KI = 0.0708 g N L−1 Chlorococcum littorale (CO2)0: 0–0.2 pCO2 CS-51 μmax = 0.12 h−1 KS = 0.00048 pCO2 KI = 0.31 pCO2

Batch cultures in 300-mL Erlenmeyer flasks in a mineral medium, at 23°C, grown in darkness

Haematococcus lacustris

(CO2)0:0.29–3.30 g (Chen & Johns, C2H3O2− L−1 μmax = 0.084 1994) −1 − h KS = 0.028 g C2H3O2 L−1 KI = 1.76 g C2H3O2− L−1

Chlamydomonas reinhardtii CS-51

Batch cultures in 800-mL glass fermenters in modified CR-M1 medium, at 35°C, pH 6.9, grown in darkness

Parameter references

Kinetic parameters

Microalgal species

Experimental conditions

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Chapter 5 • Photobioreactors modeling and simulation  97

Regaudie-de-Gioux et al., 2015). Consequently, Martinez Sancho et al. (1997) proposed modifying the Monod Model by adding a term corresponding to the specific growth rate in the absence of an external nutrient (µm2). In Eq. (5.10), if no nutrient is present in the microalgae medium (S = 0), the specific growth rate is not zero but µm2. µ=



µ m1 S + µ m 2 K S (5.10) S + KS

In this modified version of the Monod model, µm1 represents the maximum specific growth rate (S>>KS), and KS corresponds to the nutrient concentration at which the specific growth rate is the average of µm1 and µm2. Martinez et al. (1999) evaluated the growth of the microalga Scenedesmus obliquus in a medium with different initial phosphorus concentrations. The authors found that at 30°C and initial phosphorus concentrations between 0 mg L−1 and 9.29 mg L−1, the model represented in Eq. (5.10) was the one that best reproduced the experimental data. However, at a concentration of 11.5 mg L−1, phosphorus had an inhibitory effect on microalgal growth. To have a model that describes nutrient absence, limitation and inhibition state, the authors proposed the Eq. (5.11) that considers an inhibition constant (Kinh) and two maximum specific growth rates (µm2 and µm3): (1) for nutrient absence state, the specific growth rate is µm1; and (2) for nutrient inhibition state (S>>Kinh), the specific growth rate decreases with the nutrient concentration. The main drawback of this model is the number of parameters to be determined (5 in total), which requires a significantly higher number of experimental data.

µ=

µ m1K inh S + µ m 2 S2 + µ m 3 K S K inh (5.11) K S K inh + K inh S + S2

Group A-II models relate the specific growth rate and the nutrient concentration inside the cell. Therefore, these models are more realistic to describe microalgal growth. They were applied to describe resource competition between microalgae and the modifications of cells due to the limitation of resources in the environment (Klausmeier et  al., 2004b). The main drawback of these models is the difficulty of measuring the nutrient quota. The most commonly applied is the Droop model, which relationship is described in Eq. (5.12). In this model, Q0 represents the minimum value of cell quota, corresponding to the null specific growth rate (for values of Q lower than Q0, the specific growth rate is also considered zero). For high values of Q, the specific growth rate tends to μmax.

 Q  µ = µ max  1 − 0  (5.12) Q 

The Droop model has been used in a wide variety of studies describing the growth of several microalgae with different nitrogen and phosphorus cell quotas: Monochrysis lutheri (Burmaster, 1979); Scenedesmus and Chlorella (Grover, 1991); Achnanthes sp., Amphora sp., Navicula sp. and Nitzschia sp. (Kwon et al., 2013); Dunaliella tertiolecta (Benavides et al., 2015; Fré et al., 2016); and Microcystis aeruginosa (Kong et al., 2020). Table 5.3 presents kinetic parameters obtained in literature for group A-II models as a function of a single substrate.

(Droop, 1968)

 Q  µ = µmax 1 − 0  Q 

Model reference Equation

Microalgal species

Nitzschia sp.

Navicula sp.

Amphora sp.

Semi-continuous cultures in artificial seawater L1 Achnanthes sp. medium, at 20°C, a 12 h light/12 h dark regime with an irradiance of 100 μmol photons m−2 s−1

Continuous cultures in 1-L culture vessels in Monochrysis AQUIL culture medium, at 20°C, continuously lutheri illuminated with an irradiance of 21 μE m−2 s−1 Continuous cultures in cylindrical borosilicate Scenedesmus vessels, at 12°C, pH 7.2, continuously illuminated with an irradiance of 1016 quanta m−2 s −1 Chlorella

Experimental conditions −1

Parameter references

P: 0.702–13 fmol P cell (Burmaster, 1979) μmax = 1.03 d−1 Q0 = 0.702 fmol cell−1 P: 5.16–276 fmol P cell−1 (Grover, 1991) μmax = 0.755 d−1 Q0 = 5.16 fmol P cell−1 P: 0.352–65.8 fmol P cell−1 μmax = 0 .842 d−1 Q0 = 0.352 fmol P cell−1 N: 0.39–5 pmol N cell−1 (Kwon et al., 2013) μmax = 0.63d−1 Q0 = 0.39 pmol cell−1 P: 0.03–0.8 pmol P cell−1 μmax = 0.66 d−1 Q0 = 0.03 pmol cell−1 N: 0.28- 6 pmol N cell−1 μmax = 0.54 d−1 Q0 = 0.28 pmol cell−1 P: 0.02–0.3 pmol P cell−1 μmax = 0.58 d−1 Q0 = 0.02 pmol cell−1 N: 0.51–20 pmol N cell−1 μmax = 0.71 d−1 Q0 = 0.51 pmol cell−1 P: 0.03–1.6 pmol P cell−1 μmax = 0.69 d−1 Q0 = 0.03 pmol cell−1 N: 0.74–20 pmol N cell−1 μmax = 0.73 d−1 Q0 = 0.74 pmol cell−1 P: 0.04–2 pmol P cell−1 μmax = 0.70 d−1 Q0 = 0.04 pmol cell−1

Kinetic parameters

Table 5.3  Group A-II microalgal growth kinetic models as a function of a single substrate, considering internal nutrient storage.

98  Current Developments in Biotechnology and Bioengineering

Caperon and Meyer (1972)

µ = µmax

(Q − Q0 ) (Q − Q0 ) + KC Heterosigma carterae Alexandrium minutum Aureoumbra lagunensis

P: (0.25–2.4) × 10−8 µmol P cell−1 μmax = 0.0002 (Yao et al., min−1 Q0 = 0.25 × 10−8 µmol P cell−1 Kc= 2011) 0.25 × 10−8 µmol P cell−1

(Liu et al., 2001)

(Davidson & Gurney, 1999)

(Kong et al., 2020)

N: μmax = 0.39–0.40 d−1 Q0 = (5–7) × 10−3 mg N mg (104 cells)−1 P: μmax = 0.32–0.40 d−1 Q0 = (6–8) × 10−4 mg P mg (104 cells)−1

Microcystis aeruginosa

N: (7.0–40) × 10−7 µg N cell−1 μmax = 0.23 h−1 Q0 = 7.0 × 10−7 µg N cell−1 Kc = 2.9 × 10−6 µg N cell−1 μmax = 0.16 h−1 Q0 = 1.75 × 10−5 µg N cell−1 Kc = 9.1 × 10−5 µg N cell−1 μmax = 0.034 h−1 Q0 = 8.8 × 10−5 µg N cell−1 Kc = 2.0 × 10−4 µg N cell−1 N: 0.043–0.067 mol N mol C−1 μmax = 0.697 d−1 Q0 = 0.043 mol N mol C−1 Kc= 0.0083 mol N mol C−1

(Fré et al., 2016)

N0: 12 mg N-NO3 L−1 μmax = 0.0467 h−1 Q0 = 0.0263 mg N g−1 N0: 148 mg N-NO3 L−1 μmax = 0.0463 h−1 Q0 = 0.118 mg N g−1

Dunaliella tertiolecta

Thalassiosira pseudonana

(Benavides et al., 2015)

N: 0.0344–0.065 g N g C−1 μmax = 1.209 d−1 Q0 = 0.0344 g N g C−1

Dunaliella tertiolecta

Continuous cultures in polycarbonate cell culture bottles in modified f/2 culture medium, at 22°C, continuously illuminated with an irradiance of 130 μmol photons m−2 s−1 Batch cultures in Erlenmeyer Scenedesmus flasks in M11 culture quadricauda medium, at 25°C, a 12 h light/12 h dark regime with an irradiance of 37.5 μmol photons m−2 s−1

Batch cultures in 13-L flatpanel reactors, at 23–28°C, pH 7.5, continuously illuminated with an irradiance of 150 μmol photons m−2 s−1 Batch cultures 2.2-L flatpanel air lif reactor in modified f/2 medium, at 28°C, pH 7.5–8.5, continuously illuminated with an irradiance of 17.5 klx Batch cultures in M-II culture medium supplied with three different types of fish feed (HT, HP or ZT) as the only N and P sources, at 20–28°C, a 12 h light/12 h dark regime with an irradiance of 3000 lx Batch cultures in 5-L flasks in aged filtered seawater, at 18°C, a 12 h light/12 h dark regime with an irradiance of 366 μmol photons m−2 s−1

Chapter 5 • Photobioreactors modeling and simulation  99

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Caperon and Meyer (1972) used nitrogen to carbon atom ratio to evaluate the nutritional state (Q) in a modified Michaelis-Menten model, considering that the specific growth rate depends on nutrient quota. This model differs from Droop’s by considering the subsistence quota into saturation-type kinetics (Bekirogullari et al., 2020). In Eq. (5.13), KC represents the half-saturation constant.

µ = µ max

( Q − Q0 ) ( Q − Q0 ) + K C

(5.13)

This formulation of the quota model was found capable of simulating the growth of Thalassiosira pseudonana, Heterosigma carterae, Alexandrium minutum batch cultures (Davidson & Gurney, 1999), and continuous cultures of Aureoumbra lagunensis (Liu et  al., 2001), considering the internal nitrogen concentration. This model was also applied by (Yao et al., 2011) when describing the batch culture growth of Scenedesmus quadricauda in environments with different phosphorus cell quotas.

5.2.3  Kinetics of nutrient consumption The nutrients are necessary for growth (cell division) and the formation of metabolic products. Microalgae have different nutrient requirements, depending on the specie and the environmental cultivation conditions. Usually, biomass yield by substrate/nutrient (YS/X in mg g−1) is calculated to evaluate the relationship between biomass production and nutrient consumption in microalgal cultivation experiments, according to the following equation:

YX = S

∆X (5.14) ∆S

where ΔX (in mg L−1) is the variation of biomass concentration and ΔS (in mg L−1) is the variation of nutrient concentration. In a continuous PBR, the temporal variation of nutrient concentration in the medium is described by the following equation (del Rio-Chanona et al., 2017):

ds µX =− + Fin Sin − Fout Sout (5.15) dt YX S

where Fin and Fout are the volumetric flowrates (in L d−1) of the input and output streams, Sin and Sout are the nutrient concentrations (in mg L−1) in the input and output streams. The same equation can be applied in the batch reactor, with volumetric flow rates equal to zero.

5.3  Photobioreactor modeling 5.3.1  Light supply The performance of a PBR is highly dependent on the efficient light penetration and distribution in the culture. As a free resource, natural light (from the sun) is often used in microalgae

Chapter 5 • Photobioreactors modeling and simulation  101

cultivation to reduce the total costs. However, sunlight varies with the weather, time of day and the season. Solar radiation presents higher intensity (approximately 2000 µmol m−2•s−1 in summer) than the one required by microalgae (light saturation at 200 µmol m−2•s−1). Moreover, the light requirements depend on the culture density; microalgal growth may be limited by low (photolimitation) or high light intensity (photoinhibition) (Gifuni et al., 2019). Also, the effect of light spectrum range reaching microalgal cultures should be analysed, as microalgae do not absorb light in all visible light spectrum (400–700 nm – photosynthetically active radiation, about 50% of sunlight) (Esteves et  al., 2020). Light absorption by photosynthetic organisms depends on their constitutive pigments. All chlorophylls have two main absorption bands: (a) blue or blue-green (450–475 nm); and (b) red (630–675 nm). Radiation outside this wavelength range is the main reason for the temperature rise of the culture. Moreover, ultraviolet radiation is lethal for cells. The light intensity distribution inside the PBRs is not uniform due to the phenomena like absorption and scattering (Huang et al., 2017; Quan et al., 2004). The light attenuation depends on its wavelength, cell concentration, PBR geometry and penetration distance of the light. Light intensity decreases exponentially with the distance away from the illuminated surface of PBR. Consequently, the PBR can be divided into three different regions: (1) strong illuminated zone in which the cells are exposed to high light intensity (which can cause photoinhibition) – this region is limited by the PBR surface and the point with light intensity corresponding to the maximum specific growth rate, (2) weak illumination zone that ends on the point with light intensity corresponding to the maintenance of the culture, and (3) dark zone, corresponding to negative cell growth rate due to limited light availability (photolimitation). To evaluate the growth of microalgae inside the PBR, the light spatial distribution should be assessed. The Beer-Lambert law is the most commonly applied model, which considers an exponential decrease of light intensity from the external PBR surface, being represented by the following equation:

I ( l ) = I0 exp ( −σXl ) (5.16)

where I(l) is the light intensity at the distance l from the external surface of PBR, I0 is the light intensity in the system boundary, and σ is the parameter that corresponds to light absorption in the culture medium. The application of this model has the following conditions (Huesemann et al., 2013; Pottier et al., 2005): (1) the culture medium must be isotropic, which means that the optical properties must not depend on the light direction (that could be guaranteed for the wellmixed culture); and (2) microalgae must not scatter light (condition not verified). However, this model is often applied to describe the light attenuation in microalgal cultures in several PBR designs, as light scattering is assumed to be negligible relative to absorption can be considered for biomass concentrations up to 3 g L−1 (Huesemann et al., 2013; Quinn et al., 2011). However, Wágner et  al. (2018) developed a microalgal biokinetic model based on the activated sludge modeling (ASM-A) framework. The light attenuation was predicted through the Lambert-Beer and Schuster models (the last one considering light scattering) in column PBRs for different biomass concentrations (maximum value of 158 mg L−1). Besides working at concentrations lower than 3 g L−1, the authors concluded that light scattering influences the light distribution in

102  Current Developments in Biotechnology and Bioengineering

the PBRs with a narrow diameter or in cultures with low biomass concentrations and decreased pigmentation. Empirical models were also developed to consider the light scattering, such as:

 k Xl  I ( l ) = I0 exp  − 1  (5.17)  k2 + X 

where k1 and k2 are empirical constants. This and other empirical models achieved good performance indexes compared to experimental data (Fernandez et al., 1997; Katsuda et al., 2000; Suh & Lee, 2003), but the parameters depend on the studied species. Therefore, these models should be determined for a specific range of cell concentrations and each species, which is time-consuming. As an alternative, the radiative transfer equation (RTE) can be applied in three dimensions. A small element of fluid is considered to perform the radiation balance taking into account incident, absorbed, transmitted, and scattered radiation sources. RTE is the simplification of the Boltzman transport equation considering two characteristics of photons (Dauchet et al., 2016; Pruvost & Cornet, 2012): (1) all photons propagate at a locally identical speed; and (2) the photons do not interact with each other, but only with the medium (microalgal culture). This model calculates with accuracy and confidence the spectral field of irradiance in the culture. Dauchet et al. (2016) applied RTE to model the growth of the cyanobacterium Arthrospira platensis. A complete stoichiometric, kinetic and thermodynamic model was created. In the model development, the authors assumed that radiation transfer was the only limitation of the photosynthesis reaction. After determining the model parameters, this modeling approach presented high fitting performance to the experimental results, being suitable to simulate several PBR designs under different operating conditions. Considering the non-uniform distribution of light intensity inside the PBR, the kinetic models relating the specific growth rate of microalgae with this variable are divided into three groups (B-I, B-II and B-III) (Bechet et al., 2013). Group B-I model predicts the specific growth rate as a function of the incident or average light intensity reaching the culture. Group B-II model determines the productivities as a sum of local productivities within the culture (based on the light intensity that was absorbed by cells) without considering short light cycles (these models do not consider the movement of cells between regions with different light conditions). Group B-III model considers the impacts of light gradients and short light cycles. There are several models to describe the effect of light intensity. Béchet et al. (2013) presented an extensive list of models that consider the impact of temperature on microalgal production. The most common are the Monod model, described by the following equation (at constant temperature):

µ = µ max

I (5.18) KI + I

where I is the incident light intensity (in µmol m−2 s−1), and KI is the half-saturation constant (in µmol m−2 s−1). Some authors considered that the hyperbolic tangent model is suitable for the prediction of microalgal growth (Eq. 5.19 - K′I is a constant).

 I µ = µ max tanh  ¢  KI

  (5.19) 

Chapter 5 • Photobioreactors modeling and simulation  103

The Aiba model can be applied to predict the effect of light intensity under the three light regimes (Cordara et al., 2018; Zhang et al., 2015): (1) photo-limitation, (2) photo-saturation, and (3) photo-inhibition. In this equation:

µ = µ max

I I + K I² +

I2 (5.20) K inh

where K″I is a constant (in µmol m−2 s−1) and Kinh is the inhibitory constant (in µmol m−2 s−1). Han et al. (2015) compared the performance of Monod and Aiba models in the prediction of light intensity effect on microalgal growth. For values below the light saturation, the relationship between specific growth rate and light intensity was closer to Monod model. On the other hand, for higher values, the Aiba model showed higher fitting performance. The Steele model (Eq. 5.21) and Eilers and Peeters model (Eq. 5.22) can also model photoinhibition (Goncalves et al., 2016; Wagner et al., 2016):

µ = µ max

I Iopt

 I   1−   Iopt  

e

2 × (1 + β ) ×

µ = µ max

 I   Iopt

2

(5.21)

I Iopt

 I +1  + 2 × I opt 

(5.22)

where Iopt corresponds to the optimal value of light intensity (in µmol m−2 s−1) for microalgal growth and β is a model parameter. Goncalves et al. (2016) studied the effect of light and temperature on the growth of two microalgae and two cyanobacteria. The authors combine two models (one for each variable), being the Steele model used to describe the effect of light intensity. The developed model correctly described the observed growth for all microorganisms, being possible to determine the optimal light intensity and temperature values. This information enables the reduction of experimental time and costs associated with the optimization of these culture variables. Kurano and Miyachi (2005) analyzed the effect of light intensity and CO2 concentration on the growth of Chlorococcum littorale in batch cultures. Four mathematical models were compared: (1) a rectangular hyperbolic function, (2) Steele’s exponential function, (3) a Poisson function, and (4) a hyperbolic tangent function. The last model achieved the best fitting performance to the experimental data. Group B-II model is determined based on three steps: (1) assessment of light gradient in the culture, (2) selection of the biological model that predicts microalgal growth based on the local light intensity, and (3) sum of the local contributions to determine the growth in the culture. For example, the local biomass productivity can be determined by the combination of the Monod

104  Current Developments in Biotechnology and Bioengineering

model (to relate biomass productivity with light intensity) and Beer-Lambert law (for light spatial distribution), according to the following equation: P ( l ) = Pm

I0 exp ( −σXl )

K I + I0 exp ( −σXl ) (5.23)

where P(l) is the local biomass productivity (in g L−1 d−1) located at a distance l from the illuminated surface, Pm is the maximum biomass productivity (in g L−1 d−1). The biomass production is then determined by the integration of local productivities over the entire PBR volume:

P = ∫ P ( l ) dV (5.24) V

where V is the culture volume (in L). Béchet et al. (2013) presented several studies that applied Group B-II models. This type of model showed higher accuracy than the Group B-I models and, when tested for different PBR geometries, they achieved an accuracy level of 15% (Cornet & Dussap, 2009). However, the applied models can be improved, considering the light cycles experienced by microalgae due to their movement in the culture. The cycle between highirradiance zones to low-irradiance zones enable microalgae to recover from an inhibition state due to light intensity. This phenomenon is not considered in models of type B-II; therefore, the light inhibition is overestimated. Group B-III model evaluates the microalgal growth as a function of the temporal variability of light exposure (light story). This model comprises: (1) determination of the light story of cells, (2) application of kinetic growth model to individual cells, and (3) integration of all contributions of growth rates of an individual cell to determine the growth of the culture in the cultivation system. To evaluate the individual movement of cells in the culture, particle image velocimetry (PIV) can be applied to determine cell trajectories within the PBR. The experimental determination of cell trajectories may be difficult, and, as an alternative, they can be estimated using computational fluid dynamics (CFD).

5.3.2 Temperature In autotrophic cultures, the ratio of culture volume to the land area should be low to guarantee light penetration. Consequently, the temperature of the culture may increase significantly on sunny days of summer. The temperature has a strong influence in different aspects in the culture: (1) the kinetics of photochemical reactions (and metabolic and enzymatic activities), (2) the chemical equilibrium of species, (3) the solubility of gases (CO2 and O2), and (4) medium pH. Based on temperature tolerance, microalgae can be classified into three groups (ascending order of optimum temperature (Chen & Berns, 1980)): (1) psychrophilic (optimum temperature above 17 °C), (2) mesophilic, and (3) thermophilic (optimum temperature up to 40 °C). Mesophilic microalgae (the most common) has the optimum range of temperatures between 20 to 24 °C, with tolerance between 16 and 35 °C (Bitog et al., 2011; Ras et al., 2013). The specific growth rates of microalgae decrease significantly for values outside this range. For values lower than 16 °C, the kinetics of metabolic reactions decreased significantly, while for values higher than 35 °C, the culture may collapse, reducing the biomass productivity significantly

Chapter 5 • Photobioreactors modeling and simulation  105

(Bechet et al., 2017). In outdoor cultures, the temperature varies during the day and seasons. It can achieve a level of 10–30 °C higher than the ambient temperature on sunny days without a temperature control system (Wang et  al., 2012). Thus, a cost-effective temperature control system is essential for commercial production systems to keep this culture variable within a favorable range. For open systems, the temperature is controlled by water evaporation (Chisti, 2007). On the other hand, for closed systems, there are several methods to control this variable: (1) use of dark sheets for shading (Ugwu & Aoyagi, 2008), (2) spaying water to the illuminated surface removing heat by water vaporization (Pugazhendhi et al., 2020), (3) submerge part or the entire PBR in a water pool (water has a high specific heat capacity—reduced temperature variability) (Carlozzi et al., 2006; Wang et al., 2012), (4) overlapping tubes (for the case of tubular PBRs) (Singh & Sharma, 2012), (5) decrease the temperature of feed stream (Singh & Sharma, 2012), or (6) install a heat exchanger for the PBR. However, the applied system will increase the microalgal production costs, and some of them reduce the light intensity to the culture and, consequently, productivity. Several models were developed to assess the effect of temperature on microalgal growth. A simple one was defined by James and Boriah (2010): µ = µ max e



(

− K T−Topt

) (5.25) 2

where T (in °C) is the culture temperature, Topt (in °C) is the value corresponding to the maximum microalgal growth rate, and K is an empirical constant. Based on this model, a positive or negative deviation from the optimum temperature value induces a decrease in the specific growth rate of microalgae. This model was applied in several modeling studies of PBR simulation (Drewry et al., 2015; Gharagozloo et al., 2014; Quiroz-Arita et al., 2020). Arrhenius equation describes the effect of temperature in chemical reactions. However, this model does not consider the negative effect of temperature on the enzymatic activity of biological systems. To solve this issue, a combination of the Monod model and Arrhenius model was proposed:  E  exp  − a   kT  µ = µ max (5.26)  E¢  1 + K × exp  a   kT 



where K is a dimensionless constant, k is the Boltzmann constant (in J K−1), T is the absolute temperature (in K), Ea and E′a (in J) are the activation energies for photosynthesis and enzyme denaturation, respectively. Other models were proposed to infer the effect of temperature on microalgal growth based on cardinal temperatures, which have a biological significance (Bernard & Remond, 2012; Yan & Hunt, 1999):

µ = µ max

(T

opt

( T − Tmax ) ( T − Tmin )

2

− Tmin ) ( Topt − Tmin ) ( T − Topt ) − ( Topt − Tmax ) ( Topt + Tmin − 2 T ) 

(5.27)

106  Current Developments in Biotechnology and Bioengineering



µ = µ max

Tmax − T  T − Tmin  Tmax − Topt  Topt − Tmin

Topt −Tmin

 Tmax −Topt  (5.28) 

where Tmin and Tmax are the minimum and maximum values of temperature (in °C) for microalgal growth. Bernard and Remond (2012) developed a new model that comprised the light and temperature effect. The model fitted the experimental data achieved with 15 microalgal species for different experimental conditions. The cardinal temperatures (Tmin, Topt and Tmax) were determined. To predict the temperature variability in the culture during the day, an accurate heat balance should comprise the main heat transfer mechanisms. For outdoor cultures, solar radiation has a high impact on the temperature rise, in which PBR design and geographical orientation play an essential role. Several equations are described in scientific publications (Androga et al., 2017; Bechet et al., 2010; Marsullo et al., 2015).

5.3.3  Multiple factors The limitation by multiple factors (nutrients, light, and temperature, among others) may also occur in microalgal cultivation, and it is called co-limitation (Arrigo, 2005; Kovárová-Kovar & Egli, 1998; Lee et al., 2015; Saito et al., 2008). To better describe microalgal growth, this concept should be applied in the development of kinetic models. These models assume that each limitation contributes to the decrease of the growth and are divided into (1) threshold models; and (2) multiplicative models. The threshold model (Liebig’s law of minimum) considers that growth rate is affected by the most limited resource. Besides the mathematical expression is similar to the single factor models, the threshold model has the concept of co-limitation because all resources were considered to construct the model. The specific growth rate is calculated by (Shriwastav et al., 2018):

µ = µ max × min ( φ1 , φ2 , φ3 , …) (5.29)

S in Eq. KS + S (5.6) to consider the limitation of nutrients). The multiplicative model considers all the contributions of limiting resources. The overall specific growth rate is then calculated by (Buhr & Miller, 1983; Jayaraman & Rhinehart, 2015): where ϕi are mathematical factors considering all the resources (for example, φ1 =

b



µ = µ max ∏ φi (5.30) i=a

where a and b correspond to limiting resources (nutrients, light and temperature, among others). Eq. (5.7) is an example of a multiplicative model of co-limitation, considering the simultaneous limitation of two nutrients. The combination of light and temperature limitations in microalgal growth models is common. Gonçalves et al. (2016) evaluated the combined effect of light intensity and temperature on the growth of two microalgae and two cyanobacteria. The authors combined Eqs. (5.21) and (5.25) to create a kinetic model to describe the growth of

Chapter 5 • Photobioreactors modeling and simulation  107

these species in different environmental conditions. The best combinations of light intensity and temperature were then determined. Also, Béchet et  al. (2013) presented several models with the combination of these variables.

5.3.4  Medium pH Several microalgal species should be cultivated under a favorable medium pH between 8.2 and 8.7; however, they can still grow in the pH range 7–9. Some species can tolerate adverse conditions in more acid or basic media (Wang et al., 2012). The addition of CO2 (by bubbling CO2 enriched gaseous stream) to the culture helps to maintain the pH of the culture and provides carbon to the cells. In autotrophic cultures, microalgae perform photosynthesis, reducing the concentration of CO2 in the medium. Therefore, the medium pH tends to increase if an external source of CO2 is not provided. The addition of CO2 from the atmosphere (about 410 ppm) is not enough to maintain high biomass productivities, being a limiting resource for microalgal growth. This issue is solved, providing flue gases (which have a concentration of 5–14% of CO2) or an enriched CO2 gaseous stream to the culture (with an optimum concentration of 5–10%). Medium pH also indirectly affects the microalgae by modifying the medium composition due to the availability of nutrients (mainly the macronutrients carbon, nitrogen and phosphorus) to cells. Fig. 5.2 shows the distribution of inorganic carbon sources by the medium pH (see chemical reactions presented in the next section). For high pH, the inorganic carbon is mainly in the form of carbonates that is not metabolized by microalgae (Kim et al., 2019). Therefore,

FIG. 5.2  Distribution of inorganic carbon forms with pH.

108  Current Developments in Biotechnology and Bioengineering

FIG. 5.3  Effects of pH and temperature on the distribution of ammonia and ammonium ion in water.

cell growth would be limited by carbon resources. On the other hand, for low pH values, the inorganic carbon is mainly in the form of dissolved CO2, which can be easily lost to the atmosphere, reducing CO2 utilization. Regarding nitrogen, ammonium availability is highly dependent on culture pH. For higher values (see Fig. 5.3), ammonium is converted into free ammonia that can volatilize due to the constant air stripping provided to the culture (Huang & Shang, 2006). The chemical reaction is the following:

NH 4+ ( aq ) + OH − ( aq ) ⇔ NH3 ( aq ) + H2 O ( l ) (5.31)

The increase of culture pH also contributes to the chemical precipitation of phosphate, which can significantly remove this nutrient from the medium (Doran & Boyle, 1979; Larsdotter et al., 2007; Mesplé et al., 1996; Moutin et al., 1992). Phosphorus can precipitate with a wide range of cations present in the medium; however, calcium is one of the most common ion, due to its concentration in different microalgal culture media.

5.3.5  Dissolved inorganic carbon The solubility of CO2 in water is low: 1650 ppm at 25°C in pure water (Vasumathi et al., 2012). The addition of CO2 to the culture decreases the culture pH, as it dissolves with water to form carbonic acid. Then, the dissolved inorganic carbon is presented as four different compounds (CO2, H2CO3, HCO3− and CO32−), which equilibrium reactions are pH-dependent. These reactions are the following (Ji et al., 2017; Rubio et al., 1999):

CO2 ( aq ) + H2 O ( l ) ⇔ H2 CO3 ( aq ) (5.32)



H2 CO3 ( aq ) + H2 O ( l ) ⇔ HCO3− ( aq ) + H3 O+ ( aq ) (5.33)

K1

Chapter 5 • Photobioreactors modeling and simulation  109

K2



HCO3− ( aq ) + H2 O ( l ) ⇔ CO23− ( aq ) + H3 O+ ( aq ) (5.34)



2 H2 O ( l ) ⇔ OH − ( aq ) + H3 O+ ( aq ) (5.35)

Kw

where K1, K2 and KW are chemical reaction equilibrium constants, defined as:

HCO3−  H3 O+  K1 =  = 10 −6.381 (5.36) [H2 CO3 ]



CO23−  H3 O+  K2 = = 10 −10.377 (5.37) − HCO3 



K W = OH −  H3 O+  = 10 −14 (5.38)

In microalgal cultures, the dissolved inorganic carbon concentration ([CT]) can be considered as a sum of the concentrations of CO2, HCO3− and CO32−. From Eqs. (5.36) and (5.37), the following equations could be derived:



K [H CO ] K [CO2 ] HCO3−  = 1 2 + 3 = 1 H3 O  H3 O+  CO23−  =

K 2 HCO3−  H3 O  +

=

K 2 K1 [CO2 ] H3 O+ 

2

(5.39)

(5.40)

The variations of the concentrations of the different inorganic carbon forms can be inferred by:





d HCO3−  =

d CO23−  =

K1 H3 O+  d [CO2 ] − K1 [CO2 ]d H3 O+  H3 O+ 

2

(5.41)

K 2 K1 H3 O+  d [CO2 ] − 2K 2 K1 [CO2 ]d H3 O+  H3 O+ 

3

(5.42)

 K1 K 2 K1 d [CT ] = d [CO2 ] + d HCO3−  + d CO23−  =  1 + + +  H 3 O  H O +  2   3      K1 2K 2 K1  d [CO2 ] − [CO2 ] d H O +  +  H O +  2 H O +  3   3   3   3  

   

(5.43)

With these last equations, it is possible to assess the concentrations of different species of inorganic carbon based on the variation of pH ([H3O+] = 10−pH).

110  Current Developments in Biotechnology and Bioengineering

When autotrophic cultures are fed by a CO2 enriched gaseous stream (being the primary source of inorganic carbon), the following mass balance can be performed:

Qg Cg 0 − Qg Cg = Vg

dCg dt

+ VL

dCT VL dX + dt YX/CO2 dt

(5.44)

where Qg is the volumetric flowrate of the gaseous stream (in dm3 min−1), Cg0 and Cg are the mass concentrations of CO2 in the inlet and outlet gaseous streams (in mg dm−3), respectively, Vg and VL is the volume of gas and liquid inside the PBR (in dm3), respectively. The mass transfer of CO2 between gaseous and liquid phases are dependent on the concentration gradient, gas-liquid interfacial area (S0, in m2) and the overall mass transfer coefficient (KL, in m s−1):

VL

dCT VL dX + = K L S0 ( C* − [CO2 ]) dt YX/CO2 dt (5.45)

where C* corresponds to the mass concentration of CO2 in the liquid phase that is in equilibrium with the concentration of the same compound in the gaseous phase. This value is calculated by Henry’s Law.

5.4  Photobioreactor simulation CFD is one of the most used software for PBR simulation to assess its performance, reducing the design costs (in addition to reduced workload and shorter design period) and improving reactor efficiencies (other software also used for this purpose was presented by Perez-Castro et al. (2017)). It is supported by the theory of fluid dynamics, which are described by partial differential equations corresponding to conservation laws for mass, momentum and energy. CFD converts these equations to the same number of algebraic equations being solved numerically. They describe the relationship between fluid velocity, pressure, pressure and liquid density. This software can perform a qualitative prediction of fluid flow using (Bitog et al., 2011; Papacek et al., 2018): (1) mathematical modeling through Navier-Stokes transport equations, (2) numerical methods, and (3) solvers, pre- and post-processing utilities. The design of PBRs must consider lighting, mixing, CO2 and O2 mass transfer, nutrient supply to microalgae and temperature of the culture medium. Thus, the interactions between several phenomena should be described to model correctly the microalgal growth inside a PBR (Perner et al., 2003). Fig. 5.4 presents a scheme with the interactions between hydrodynamics, light supply, mass and heat transfer and biological kinetics in microalgal cultures (Pires et al., 2017). Table 5.4 presents several simulation studies of different PBR geometries. In the phase of PBR development, it should be taken into account that a complex design is more versatile; however, it is also more expensive to construct and operate. The selection of PBR type depends on several aspects: (1) microalgal species and growth conditions requirements, (2) chemical composition of medium, and (3) market value of the final product. The PBR design should have the main objective to maximize the biomass areal productivity, reducing the costs and land-use change.

Chapter 5 • Photobioreactors modeling and simulation  111

FIG. 5.4  Interactions between hydrodynamics, light supply, mass and heat transfer and biological kinetics in microalgal cultures.

Table 5.4  Recent CFD studies focusing different PBR geometries. PBR

CFD code

Raceway pond

ANSYS Fluent

Modelled phenomena

References

FD: RNG k−ε turbulence model; (Amini et al., 2018) BK: multiple factors (light intensity, temperature and pH); LS: radiative transfer equation; EV: 0.5 m2 raceway pond (Chlorella vulgaris). COMSOL Multiphysics; FD: k–ε model; EV: 500 m2 raceway pond. (Inostroza et al., 2021) ANSYS Fluent Airlift PBR ANSYS CFX FD: SST k-Ω model. (Guler et al., 2020) Hybrid tubular PBR ANSYS Fluent FD: RNG k–ε model; EV: 11.7 m3 PBR. (Belohlav et al., 2021) Stirred tank PBR ANSYS Fluent FD: k–ε model; LS: radiative transfer (Saini et al., 2018) equation. Flate-plate PBR Comsol Multiphysics FD: k–ε model; EV: 10 L PBR (Hinterholz et al., 2019) (Poterioochromonas malhamensis). Thin-layer cascade PBRs OpenFOAM FD: k−ω SST (Severin et al., 2018) BK, biological kinetics; EV, experimental validation; FD, fluid dynamics; LS, light supply; PBR, photobioreactor; RNG, renormalization group; SST, shear stress transport.

The study of hydrodynamics is relevant to determine the influence of PBR geometry in the energy consumption for moving the fluid (energy loss due to friction) (Ali et  al., 2015; Chiaramonti et al., 2013; Zeng et al., 2016). When compared with conventional systems, significant energy savings (more than 80%) were achieved with the developed geometry. On the other hand, CFD can be applied to study the effect of PBR geometry and flow rates in the presence of dead zones in different reactors (Morschett et al., 2017). The reduction of these stagnation regions improves biomass productivity. Moreover, these regions have good hydrodynamic conditions for biofilm growth. For fluid velocities higher than 0.20 m s−1, biofilm formation is significantly reduced (Gómez-Pérez et al., 2015).

112  Current Developments in Biotechnology and Bioengineering

The simulation of the mixture in the culture is important not only to reduce the nutrient gradients but also to move the cells between the light and dark regions inside the PBR. CFD can then be applied to predict individual cell trajectories that, combined with the spatial distribution of light inside the PBR, enable the evaluation of the light/dark cycle frequencies experienced by microalgae (Tong et al., 2020). This information allowed estimating the specific growth rate of microalgae in different PBR geometries. For instance, Zhang et al. (2013) studied the introduction of helical static mixers to analyse their effect on cell trajectories and energy savings in tubular PBRs. With this configuration, microalgae experienced light/dark cycles, improving biomass production by 37% compared with the conventional system. Fernández del Olmo et al. (2021) concluded that the raceway ponds are poorly mixed. Varying the circulation velocities between 0.2 and 0.8 m/s (with a medium depth of 0.2 m), no significant variation was observed in the light regime to the cells in the culture. Amini et al. (2018) developed an integrated model considering growth kinetic, light transfer and fluid dynamics in open raceway ponds. Growth parameters were determined with experimental data from Chlorella vulgaris cultures, varying light intensity, temperature and pH value. Different pond depths were tested: 0.20, 0.25 and 0.30 m. The developed model achieved good fitting performance for all medium depths (concerning the biomass areal productivities), presenting an overall coefficient of determination (R2) of 0.972. Besides the PBRs, simulations were also performed to optimize its components. Kusmayadi et  al. (2020) analyzed the effect of CO2 spargers in the light transfer and culture mixing in a 20 L raceway pond. Microalgal growth (C. vulgaris) was promoted by the increase of paddlewheel rotation from 13 rpm to 30 rpm. CFD simulations allowed the identification of regions with low fluid velocities (less than 0.1 m/min, called dead zones), which can cause cell settling and low microalgal growth. The installation of CO2 spargers (at 30 mL/min) in dead zones increased biomass productivity 2.6 times more. Ali et  al. (2019) also analyzed the effect of sparger design parameters (number and diameter of sparger holes and gas flow rates) on the distribution of gas bubbles in the reactor, power requirements, light intensity and microalgal production (Chlamydomonas reinhardtii). The optimum sparger design increased the biomass concentration by 18%. Other analyzed PBR components were the impellers. The hydrodynamic shear stress was evaluated with impellers Rushton-Rushton and Rushton-marine in a stirred bioreactor at different rotation speeds (Verma et al., 2019). Values ranging 75–150 rpm corresponded to the shear stress of 1.97–3.96 Pa suitable for different microalgal species.

5.5  Conclusions and perspective Microalgal growth is affected by several factors; most of them are correlated. This chapter presents several models for individual factors and also for multiple factors. The last ones can achieve a higher performance in the prediction of microalgal growth. Still, they are more complex, having a higher number of parameters and requiring a higher experimental effort for their determination. On the other hand, CFD is a powerful tool that will predict PBR performance without several expensive and time-consuming experiments. The simulations focused mainly the hydrodynamics, but the temporal and spatial distribution of light inside the PBR can be

Chapter 5 • Photobioreactors modeling and simulation  113

assessed. In addition, biological kinetics can be incorporated into the CFD software to achieve a better and complete description of the process. Besides the main factors affecting microalgal growth are identified, the specific mechanisms behind them are unclear. Guidelines should be defined to construct the microalgal growth model (threshold or multiplicative) based on a better understanding of the individual contributions of different factors on the cells. The complete simulation of the effect of light will be the most challenging step. Besides the various phenomena that influence the light transmission inside the culture and its natural (daily and seasonal) variability in outdoor cultures, the light spectrum should also be considered.

Acknowledgements This work was financially supported by: (i) LA/P/0045/2020 (ALiCE) and UIDB/00511/2020-UIDP/00511/2020 (LEPABE) funded by national funds through FCT/MCTES (PIDDAC); and (ii) Project PhotoBioValue (ref. PTDC/ BTA-BTA/2902/2021), funded by FEDER funds through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI) and by national funds (PIDDAC) through FCT/MCTES. E.M. Salgado thanks FCT for the financial support of her work through the FCT PhD Research Scholarship 2021.07412.BD.

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Tong, Z.X., Li, M.J., Yan, J.J., Gu, Z.L., 2020. A theoretical analysis of the hydrodynamic influence on the growth of microalgae in the photobioreactors with simple growth kinetics. International Journal of Heat and Mass Transfer 158, 119986. Ugwu, C.U., Aoyagi, H., 2008. Influence of shading inclined tubular photobioreactor surfaces on biomass productivity of C-sorokiniana. Photosynthetica 46, 283–285. Valdovinos-Garcia, E.M., Barajas-Fernandez, J., Olan-Acosta, M.D., Petriz-Prieto, M.A., Guzman-Lopez, A., Bravo-Sanchez, M.G., 2020. Techno-economic study of CO2 capture of a thermoelectric plant using microalgae (chlorella vulgaris) for production of feedstock for bioenergy. Energies 13 (2), 413. https://doi. org/10.3390/en13020413. Vasumathi, K.K., Premalatha, M., Subramanian, P., 2012. Parameters influencing the design of photobioreactor for the growth of microalgae. Renewable and Sustainable Energy Reviews 16, 5443–5450. Verma, R., Mehan, L., Kumar, R., Kumar, A., Srivastava, A., 2019. Computational fluid dynamic analysis of hydrodynamic shear stress generated by different impeller combinations in stirred bioreactor. Biochemical Engineering Journal 151, 107312. Wagner, D.S., Valverde-Perez, B., Plosz, B.G., 2018. Light attenuation in photobioreactors and algal pigmentation under different growth conditions: Model identification and complexity assessment. Algal Research 35, 488–499. Wagner, D.S., Valverde-Perez, B., Saebo, M., de la Sotilla, M.B., Van Wagenen, J., Smets, B.F., Plosz, B.G., 2016. Towards a consensus-based biokinetic model for green microalgae: The ASM-A. Water Research 103, 485–499. Wang, B., Lan, C.Q., Horsman, M., 2012. Closed photobioreactors for production of microalgal biomasses. Biotechnology Advances 30, 904–912. Wang, M., Kuo-Dahab, W.C., Dolan, S., Park, C., 2014. Kinetics of nutrient removal and expression of extracellular polymeric substances of the microalgae, Chlorella sp. and Micractinium sp., in wastewater treatment. Bioresource Technology 154, 131–137. Xin, L., Hong-ying, H., Ke, G., Ying-xue, S., 2010. Effects of different nitrogen and phosphorus concentrations on the growth, nutrient uptake, and lipid accumulation of a freshwater microalga Scenedesmus sp. Bioresource Technology 101, 5494–5500. Yaak, ob, M.A., Mohamed, R.M.S.R., Al-Gheethi, A., Gokare, R.A., Ambati, R.R., 2021. Influence of nitrogen and phosphorus on microalgal growth, biomass, lipid, and fatty acid production: An overview. Cells (Basel) 10, 393. Yan, W.K., Hunt, L.A., 1999. An equation for modelling the temperature response of plants using only the cardinal temperatures. Annals of Botany 84, 607–614. Yao, B., Xi, B., Hu, C., HuoJing, S., Liu, S., 2011. A model and experimental study of phosphate uptake kinetics in algae: Considering surface adsorption and P-stress. Journal of Environmental Sciences 23, 189–198. Zeng, F., Huang, J., Meng, C., Zhu, F., Chen, J., Li, Y., 2016. Investigation on novel raceway pond with inclined paddle wheels through simulation and microalgae culture experiments. Bioprocess and Biosystems Engineering 39, 169–180. Zhang, D., Dechatiwongse, P., Hellgardt, K., 2015. Modelling light transmission, cyanobacterial growth kinetics and fluid dynamics in a laboratory scale multiphase photo-bioreactor for biological hydrogen production. Algal Research 8, 99–107. Zhang, Q., Wu, X., Xue, S., Liang, K., Cong, W., 2013. Study of hydrodynamic characteristics in tubular photobioreactors. Bioprocess and Biosystems Engineering 36, 143–150. Zhang, X.-W., Chen, F., Johns, M.R., 1999. Kinetic models for heterotrophic growth of Chlamydomonas reinhardtii in batch and fed-batch cultures. Process Biochemistry 35, 385–389.

6 Photobioreactors for microalgaebased wastewater treatment Dillirani Nagarajana,b, Chun-Yen Chenc, Duu-Jong Leea,d, Jo-Shu Changb,e,f a DE PARTM ENT O F CHEM I CAL ENGI N E E R I N G , N AT I O N A L TA I WA N U N I V E R S I T Y, TA I P E I , TAIWAN b DEPARTM ENT O F CHEM I CAL EN G I N E E R I N G , N AT I O N A L C H E N G K U N G U N I V E R S I T Y, TAI NAN, TAI WAN c UNI VERS I T Y C E N T E R F O R B I O S C I E N C E A N D B I O E N G I N E E R I N G , NAT IONAL CHENG KUNG UNI VERS I TY, TA I N A N , TA I WA N d D E PA RT ME N T O F ME C H A N I C A L EN GI NEERI NG, CI TY UNI VERS I TY O F H O N G K O N G , K O W L O O N T O N G , H O N G K O N G e DEPARTM ENT O F CHEM I CAL AND MAT E R I A L S E N G I N E E R I N G , T U N G H A I U N I V E R S I T Y, TAICHUN G, TAI WAN f RES EARCH CENTE R F O R S MA RT S U S TA I N A B L E C I R C U L A R E C O N O MY, T U N G H A I U N I V E R S I T Y, TA I C H U N G , TA I WA N

6.1 Introduction Wastewaters are increasingly becoming an environmental concern, with the expanding global population and simultaneous growth in agricultural and industrial sectors. Wastewaters from domestic use and industrial sources need to be treated effectively, which involves (1) the removal of nutrients, such as carbon, nitrogen, and phosphorus so that the treated wastewater does not lead to eutrophication in the receiving water bodies, (2) removal of organic and inorganic pollutants, such as heavy metals, textile dyes, pesticides, and pharmaceutical compounds, and (3) removal of pathogenic bacteria and viruses (Nagarajan et al., 2020). The resultant treated wastewater can be safely released into the environment without any threat of secondary pollution. Currently, the annual global wastewater production is 359.5 billion m3, of which 48% is being released into the environment without being treated (Jones et al., 2020). The wastewater treatment most widely used at present is the activated sludge process, which involves the disintegration or dissimilation of the complex compounds present in wastewater by aerobic/anaerobic bacteria. However, the process is energy-intensive and creates large amounts of sludge as secondary waste, which was approximately 13 million tons in 2020 (Mohsenpour et al., 2021). Microalgae-based wastewater treatment (MWT) recovers nutrients into valuable organic biomass, which is in agreement with the principles of the circular economy. The amount of N and P discharged in wastewater annually will reach 13.5–17.9 Tg and 1.6–2.4 Tg, respectively by the year 2050 (van Puijenbroek et al., 2019). With microalgal assimilation of waste N and P, wastewater is considered a new sustainable resource for finite nutrients essential for agriculture and microalgal cultivation, especially nitrogen and phosphorus (Liu et al., 2018; Zhang & Liu, 2021). Current Developments in Biotechnology and Bioengineering. DOI: https://doi.org/10.1016/B978-0-323-99911-3.00002-6 Copyright © 2023 Elsevier Inc. All rights reserved.

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MWT has been traditionally carried out in open photobioreactors (PBR), such as waste stabilization ponds, raceway reactors, and the recent sophisticated high-rate algal ponds (Leong et al., 2021). Open systems are economical with simple operational requirements, but require large amounts of land and longer hydraulic retention times for effective treatment of wastewaters (Young et al., 2017). Closed PBRs have also been applied for MWT, in which properly controlled environmental conditions resulted in superior wastewater treatment efficiency (Ashok et  al., 2019). As discussed previously in the preceding chapters, closed systems require high installation and operating costs, which is not economically feasible for wastewater treatment. The cost and energy associated with the microalgal process are expected to be offset by the valuable microalgal biomass obtained at the end of the process (Bhatia et al., 2021). Given the regulations regarding the quality of microalgal biomass for food and animal feed applications (Becker, 2013), biofuel production seems to be the most viable option for the end application of wastewater-derived algae. This chapter discusses the utilization of open and closed PBRs for MWT. The advantages and disadvantages of open and closed systems pertaining to wastewater treatment are presented and the common design criteria for PBRs with respect to wastewater treatment are presented.

6.2  Phycoremediation potential of microalgae—assimilatory nutrients removal Microalgae are primary photosynthetic organisms present in the ecosystem, and they are highly resilient and adaptable with the ability to survive in a variety of habitats. Microalgae fix atmospheric CO2 into organic biomass by photosynthesis and forage for other nutrients, such as nitrogen, phosphorus, and micronutrients in the environment. Algal blooms are common in eutrophic waters where the nutrient concentrations are high compared to adjacent areas, which promotes rapid algal growth called blooms (Zhang et al., 2021a). On the other hand, the nutrient utilization capacity of microalgae from wastewaters can be applied to the bioremediation of wastewater. The mechanism of nutrient and pollutant removal by microalgae is briefly presented in Table 6.1. While nutrients are assimilated in the biomass, pollutants are removed/ inactivated as a part of the microalgal metabolism. In the absence of significant inhibition, the optimal C:N:P ratio for the effective nutrient removal of wastewater is 100/18/2 (Serejo et al., 2020). Most wastewaters do not meet the carbon requirements of microalgae, and most wastewater treatment systems operate with carbon limitation. Thus, gaseous CO2 supply boosts both wastewater remediation efficiency and biomass accumulation in wastewater treatment systems. The environmental impacts of microalgal cultivation and the carbon footprint can be reduced with the use of flue gas in outdoor ponds co-located with thermal power plants (Yadav et al., 2020). In addition, the N:P ratio limits P removal. However, microalgae can uptake and store large amounts of P as intracellular poly-phosphate due to the inherent survival mechanism of microalgae in low-P environments (Solovchenko et al., 2019). In wastewater treatment, microalgae co-exist with bacteria in a symbiotic association. Microalgal photosynthesis provides bacteria with the required oxygen for the biological degradation of organic matter, and bacteria respiration provides CO2 for microalgal photosynthesis.

Chapter 6 • Photobioreactors for microalgae-based wastewater treatment  123

Table 6.1  Nutrient and pollutant removal mechanism of microalgae in wastewater treatment. Pollutant

Mechanism of removal by microalgae

Nutrient—carbon

• Assimilation into biomass via mixotrophic or heterotrophic growth • Degradation by symbiotic bacteria provides CO2 for photosynthesis • Abiotic CO2 stripping

Nutrient—gaseous CO2 in flue gas and biogas

• Effective carbon capture into microalgal biomass • Assimilation into biomass via photosynthesis • Simultaneous biogas upgrading when using biogas

Nutrient—nitrogen

• Assimilation into biomass after being reduced to ammonium • Direct assimilation of ammonium into amino acids • Photosynthetic activity and oxygenation promote ammonia stripping

Nutrient—phosphorus

• Uptake and assimilation into biomass for growth • Uptake and storage as poly-phosphate during starvation • Photosynthetic activity and oxygenation promote phosphate precipitation

Nutrient—sulfur

• Assimilated into biomass • Photosynthetic oxidation at high pH

Pollutant—heavy metals

• Physical adsorption on the cellular surface via interaction with charged functional groups • Bioaccumulation—accumulation inside cells • Chelation with metal chelators—intracellular metallothioneins and extracellular polymeric substances • Precipitation under microalgae cultivation conditions

Organic pollutants—antibiotics, pharmaceutical compounds, personal care products, textile dyes

• Physical adsorption on the cellular surface via interaction with various functional groups • Bioaccumulation—uptake and accumulation inside algal cells • Biodegradation—intracellular and extracellular breakdown • Photo degradation—direct or indirect photolysis by UV light or oxidation • Volatilization under microalgae cultivation conditions

Biological pollutants—pathogenic • Microalgal photosynthetic activity, high dissolved oxygen, and high bacteria, viruses, and nematode/ pH unsuitable for the survival of common pathogens helminth eggs • Prolonged exposure to UV light in open treatment systems disinfect

bacteria and viruses • Sedimentation in open ponds remove helminthic/nematode eggs Information source: (Dar, Sharma, Kaur & Phutela, 2019; Hena et al., 2021; Leng et al., 2020; Mohsenpour et al., 2021; Serejo et al., 2020).

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Nevertheless, the interaction between microalgae and bacteria is complex. Microalgae host bacteria on their cell surface in a specialized zone called the rhizosphere (Samo et al., 2018). Bacterial associates provide microalgae with growth-promoting substances, such as hormones, vitamins, anti-microbial substances, chelators, and lipophilic compounds (Wienhausen et al., 2017). Microalgae-bacterial consortia are effective in the total bioremediation of wastewater; bacterial degradation is responsible for the removal of the high COD and BOD content of wastewaters, while microalgal assimilation is required for the removal of phosphorus, nitrite, nitrate, ammonium, and urea levels of wastewater.

6.3  Open systems for microalgae-based wastewater treatment Open pond systems for MWT have been used historically. William J. Oswald observed that photosynthetic oxygenation provided by microalgae is highly suitable for bacteria degradation of the organic matter in wastewater (Oswald, 1963). Open systems include unstirred ponds, raceway reactors with mixing, and high rate algal ponds (Ting et al., 2017). Algal biofilm-based treatment systems, such as algal turf scrubbers (ATS) have also been applied as open wastewater treatment systems (Leong et al., 2021).

6.3.1  High rate algal ponds (HRAP) The term “high rate algal pond” was first coined by William J. Oswald of the University of California (Oswald, 1963). HRAPs indicate wastewater treatment ponds with a high algal growth rate which in turn results in a high wastewater treatment efficiency (Fig. 6.1). HRAPs are open, shallow raceway reactors of about 0.3–0.4 m depth, with effective paddlewheel-based mixing to ensure high algal growth and prevent biomass settling (Park et al., 2011). Mixing with paddlewheels or baffles provides a horizontal flow with a velocity of 0.15–0.3 m/s. The liquid flow in the reactor could be a single loop or multi looped based on the requirements of the treated wastewater (Park et al., 2011). HRAPs are provided with facilities for CO2 injection, an influent inlet, and an effluent outlet connected to a biomass harvesting unit. Gaseous CO2 addition in HRAPs can be performed via a regular pump located within the raceway tracks and the bubbling of CO2 provides a certain degree of turbulence (Yen et al., 2019). If waste CO2 sources, such as flue gases or biogas are used, a separate adsorption column is employed where CO2 is captured as dissolved inorganic carbon in the medium, and the inorganic carbon water is recirculated in the HRAP. This setup is described as an HRAP-adsorption column system (HRAP-AC) and has been employed for carbon capture from biogas for microalgal growth in HRAPs (Bahr et al., 2014). Adsorption columns are especially useful in carbon capture when the CO2 point source contains other potential pollutants, such as methane, NOx, SOx, heavy metals, halogenated hydrocarbons, and particulate matter which might inhibit microalgal growth and ultimately wastewater treatment efficiency (Leong et al., 2021). The inoculum for HRAP is typically the indigenous bacterial and algal population (Arashiro et al., 2019; Buchanan et al., 2018b). Filamentous microalgae forming algal biofilms on support materials can be applied

Chapter 6 • Photobioreactors for microalgae-based wastewater treatment  125

(A)

Sloenoid valve Paddle wheel

Wastewater influent

Central dividing Central baffle wall Water flow

Gas flowmeter

CO2 addition controller pH Sensor

CO2 source

Effluent to algal harvester

30-50 cm water depth

CO2 addition sump (~1.5 m)

High rate algal pond

(B)

FIG. 6.1  (A) Schematic illustration of the operation of a high rate algal pond (reproduced with permissions from Park et al. (2011)). (B) A four-channel pilot-scale raceway reactor at the National Cheng Kung University, Tainan, Taiwan.

in HRAPs to promote nutrient removal efficiency and the harvested filamentous algae can be applied as biofertilizer due to the rich organic content (Kim et al., 2002; Kim et al., 2018). HRAPs are the most commonly used wastewater treatment system in many countries, such as the United States, China, Switzerland, Morocco, Spain, France, New Zealand, and the United Kingdom (Young et  al., 2017). Various types of wastewaters have been successfully treated using HRAPs as summarized in Table 6.2. Nutrient removal in HRAPs is carried out by the growth and nutrient assimilation by the microalgae-bacteria consortia. Microalgae remove nutrients (carbon, nitrogen, and phosphorus) present in wastewater by uptake and metabolic assimilation in organic biomass. Aerobic and anaerobic heterotrophic bacteria metabolize and disintegrate the organic matter present in the wastewaters (Nagarajan et al., 2019). Microalgal growth and photosynthetic activity increase the pH towards the alkaline side in HRAPs. Thus, abiotic nutrient removal at high pHs, such as ammonia stripping, phosphate precipitation,

Wastewater treated

Secondary treated municipal wastewater

Secondary treated municipal wastewater

Anaerobically treated domestic wastewater Anaerobically treated domestic wastewater Domestic sewage

Indigenous microflora of the wastewater

Indigenous microflora of the wastewater

(Buchanan et al., 2018b)

Biomass production of 31.7 g/m2/d, >90% BOD5 removal, Ammonia removal: 33–49% in winter, 88–94% in summer. E. coli log removal values 1.75–2.75 Single-channel 223 m2 outdoor HRAPs, paddlewheel 48.89% BOD5 removal, 53.52% TN removal, mixing with a velocity of 0.41 m/s, 0.3 m depth, 68.76% NH4-N removal, 16.67% PO4-P removal, 4 days HRT, influent enriched with CO2 from real 1.15 E. coli log removal value biogas: free CO2 110.00 mg/L, and inorganic carbon, 175.00 mg /L Single-channel 223 m2 outdoor HRAPs, paddlewheel 36.63% BOD5 removal, 59.13% TN removal, mixing with a velocity of 0.41 m/s, 0.3 m depth, 4 76.46% NH4-N removal, 17.17% PO4-P removal, days HRT, influent free CO2 9.3 mg/ L, and inorganic 1.22 E. coli log removal value carbon, 89.6 mg/L Single-channel 3.3 m2 outdoor HRAP, paddlewheel 40–43% COD removal, 54–65% TOC removal, mixing with a velocity of 0.1–0.15 m/s, 0.2–0.4 m 39–76% NH4-N removal, E. coli log removal depth, supplied with CO2 via a carbonation column value—2 Single-channel 3.3 m2 outdoor HRAP, paddlewheel 40–42% COD removal, 62–64% TOC removal, mixing with a velocity of 0.1–0.15 m/s, 0.2–0.4 m 47–62% NH4-N removal, E. coli log removal depth value—2 Single-channel 3.3 m2 outdoor HRAP, 0.3 m depth, 59% COD removal, 78% NH4-N removal, 16% HRT 10 days, operated for 6 months, influent flow PO4-P removal, E. coli log removal value—1 rate of 0.1 m3/d. Biomass composition: 32% proteins, 11% carbohydrates, and 18% lipids.

(Rodrigues de Assis et al., 2020)

(Couto et al., 2021)

(Couto et al., 2021)

(Young et al., 2019)

(Young et al., 2019)

(Taylor et al., 2021)

(Cantera et al., 2021)

(Kim et al., 2018)

References

80% of incoming carbon and 50% of incoming nitrogen incorporated in biomass, biomass production 317.18 g/m3 effluent

Upgraded biogas: 95.2% CH4, 1.4% CO2, and no H2S. Effective nutrient removal in summer

79.8% TN removal, 81.2% TP removal, Oxygen production: 11.0 g O2/g FAM/d

Nutrient removal efficiency

HRAP, high rate algal pond; HRT, hydraulic retention time; COD, chemical oxygen demand; BOD5, 5-day biological oxygen demand; TN, total nitrogen; NH4-N, ammonia nitrogen; TP, total phosphorus; PO4-P, phosphate phosphorus.

Indigenous microflora of the wastewater

Indigenous microflora of the wastewater

Outdoor HRAP, continuous operation for 150 days, 0.3 m depth, 4 days HRT, influent flow rate 910–1110 L/d. Pilot-scale 180 L outdoor HRAP, continuous operation for 10 months, 50 days HRT, 0.2 m/s fluid velocity for mixing, biogas captured via an adsorption column, carbon enriched anaerobic digestate influent rate 3.4 L/d.

HRAP operational conditions

Anaerobic digestate and simulated biogas (CH4 (70%), CO2 (29.5%) and H2S (0.5%)) Anaerobically Outdoor HRAP dual pond system—3700 L and 1700 digested, stabilized L, continuous operation for 200 days, 0.25 m and brewery effluent 0.11 m depth in ponds 1 and 2, 3 days HRT, influent flow rate 1800 L/d, mixing velocity of 4.1–6.1 m/s. Septic tank effluent Outdoor, single-loop raceway, paddlewheel mixing with a velocity of 0.2 m/s, 0.32–0.55 m, 4.5–9.1 days HRT, continuous operation for 1 year.

Indigenous microflora of the wastewater

Indigenous microflora of the wastewater

Indigenous microflora of the wastewater

Microalgal consortia + activated sludge

Filamentous algal matrix Polluted rural of Spirogyra sp. stream water

Microalgal source

Table 6.2  High rate algal ponds for the effective treatment of various wastewaters.

Chapter 6 • Photobioreactors for microalgae-based wastewater treatment  127

and sulfate oxidation due to photosynthetic oxygenation is known to occur (Nagarajan et al., 2020). In outdoor HRAPs, exposure to sunlight, alkaline pH, increase in temperature, and the presence of algal metabolites aid in the removal of pathogenic bacteria (Dar, Sharma, Kaur & Phutela, 2019). Bio-adsorption, bioaccumulation, biodegradation, and photo-degradation are some of the mechanisms involved in the removal of other pollutants, such as heavy metals, and organic compounds including pesticides, textile dyes, and pharmaceutical compounds (Mohsenpour et  al., 2021). Compared to the traditional activated sludge system, HRAPs consume two-thirds lower energy (0.11 kW/m3 of effluent treated Vs 0.29 kW/m3 in activated sludge system). In addition, a higher degree of nutrients can be recovered in algal biomass, while only a small percentage is recovered in the sludge (Taylor et al., 2021). Life cycle analyses performed by Garfi et al. indicated that the environmental impacts (climate change, fossil fuel depletion, ozone depletion, and eutrophication potential) of HRAP-based wastewater treatment are two to five times lower compared to the activated sludge process (Garfí et al., 2017). Furthermore, HRAP based wastewater treatment has 50% lower land requirements compared to traditional lagoons, require minimal maintenance thereby reducing labor costs, and has a lower carbon footprint (Buchanan et al., 2018a). The major factors influencing effective wastewater treatment in HRAPs include pond depth, hydraulic retention time, influent nutrient loading, and CO2 loading to promote algal growth (Leong et al., 2021). The optimal operational conditions for effective wastewater treatment in HRAPs are as follows: a pond depth of 0.4 m, continuous mixing with a speed of 0.2 m/s, moderate nutrient loading in the order of 15–30 g/m3, optimal CO2 addition which maintains the pH in the range of 6.5–7, and a hydraulic retention time of 4 days in summer in tropical countries (Sutherland & Ralph, 2020). To ensure pathogenic viral removal, the ratio of the length to the width of the entire raceway system should not be less than 6:1 for single-channel systems, wall shading should be minimized with optimal orientation, and the raceway reactor should be lined with EPA approved liners in proper anchoring (SA, 2020).

6.3.2  Algal turf scrubbers ATS are engineered raceway reactors where an inclined platform with attached microbial population participates in nutrient removal from wastewater which flows over the platform at a predefined rate. Typically, a mesh made of a sturdy material is laid upon the raceway to support the attachment of the microbial population, and biofilm formation is encouraged before being exposed to the wastewater (Siville & Boeing, 2020). The original design of the algal scrubbers supposedly mimics the coral reef system, which inspired this low cost, simple, low maintenance, and effective wastewater treatment system (Adey et  al., 2011). The wastewater flows over the attached biomass, where algal photosynthetic activity assimilates nutrients and releases oxygen. Then, the treated wastewater with lower nutrients and higher oxygen levels is returned to the source (Liu et al., 2016). Even though the name implies an algal population, the attached biomass that grows on the platform includes algae, bacteria, and fungi in varying proportions. Hence, the name periphyton was coined for the benthic microbial population in ATS (Sandefur et al., 2014). Initially, ATS units were successfully employed for the purification of

128  Current Developments in Biotechnology and Bioengineering

eutrophic waters, and the comparatively low nutrient and light limiting conditions, along with the constant wave motion exposing the unit to nutrients, resulted in high biomass productivity (Adey et al., 2011; Kangas et al., 2017; Mulbry et al., 2010). ATS employed for the effective treatment of various wastewaters are summarized in Table 6.3. The microalgal biomass in the ATS unit is harvested frequently before the films mature, because mature algal films interfere with light availability for continuous algal growth and wastewater treatment efficiency. The biomass is simply scraped off the turf and the residual biomass retained after harvest serves as the seed for the subsequent wastewater treatment cycle (Craggs, 2001). Operational parameters that influence wastewater treatment efficiency include the length of the flow channel, water depth, illumination employed, wastewater flow rate, nutrient loading, and biomass harvest time (Pizarro et al., 2006). An optimal depth of 0.2–0.4 m, a high flow rate and weekly or monthly harvest (for high productivity and low productivity time, respectively) are recommended for maximal biomass production and wastewater treatment efficiency (Leong et al., 2021).

6.3.3  Advantages, disadvantages, and opportunities of open reactors for efficient and economic wastewater treatment The advantages of an open system with respect to wastewater treatment are multifold: (1) the technology is mature, with waste stabilization ponds and high rate algal ponds have been applied for wastewater treatment from the early 1960s, (2) scale-up is manageable, (3) the installation and operational costs are low, (4) the systems require minimal maintenance, implying reduced labor costs, and (5) the energy requirements and consequential environmental impacts are low compared to the conventional activated sludge system (Sutherland & Ralph., 2020). The cost of wastewater treatment per m3 of wastewater is around 0.13–0.64 € in Europe (Moral Pajares et al., 2019), 0.27–0.43 USD in the middle east (Arif et al., 2020), and 1.34 USD in Japan (Ishizaki et al., 2020). Installation costs accounted for 58% of the total cost in conventional wastewater treatment processes for preliminary treatment, while operation and maintenance accounted for 58% of the treatment cost in tertiary treatment plans (Ozgun et  al., 2021). In Japan, MWT resulted in a cost of 1.29–1.36 USD/m3 (Ishizaki et  al., 2020). The application of ATS for the treatment of dairy wastewater resulted in a treatment cost of 1.42 USD/m3 (Higgins & Kendall, 2012). Thus, MWT in open systems can be economic and close to the conventional treatment system without severe environmental impacts. The major challenge in MWT is the per capita land requirement, which is 10 m2. A per capita land requirement of 2 m2 is acceptable, and hence higher wastewater loading of the systems is required (Acién Fernández et  al., 2018). In addition, microalgae-based systems cannot handle higher organic carbon loading, resulting in longer retention times and lower wastewater treatment capacity (Acién Fernández et al., 2018). Thus, microalgae-based open systems are better suited for the treatment of low carbon wastewaters, such as secondary and tertiary wastewaters, and nitrogen rich wastewaters like animal manure and anaerobic digestates (Mohsenpour et al., 2021).

Chapter 6 • Photobioreactors for microalgae-based wastewater treatment  129

Table 6.3  Algal turf scrubbers for the treatment of various wastewaters. Wastewater treated Aquaculture wastewater

Algal turf scrubber (ATS) operation

Algae productivity and nutrient removal 2

Fiberglass ATS trough with 1 m growing area, angled at a slope of 1–2%, 48 L/min flow rate.

2

Biomass productivity: 88.8 g/m /d, Nitrogen removal rate: 12.2 g-N/ m2/d, Phosphorus removal rate: 0.25 g-P/m2/d Aquaculture ATS tank of 2 m2 growing area, Biomass production: 1.08 kg wet wastewater 5% inlet to outlet slope angle, 0.3 biomass/week, ammonia-nitrogen mm stainless steel mesh placed one removal: 0.656 g/m2/d cm above the surface to promote sludge settling Agriculture drainage Six 50 m2 pilot scale ATS with 2% Annual biomass productivity: 5 g/ water slope, 95 L/min flow rate m2/d, Biomass composition: 1.8% N, 0.21% P, Nitrogen removal rate: 220 Kg-N/ha/y, Phosphorus removal rate: 22 Kg-P/ha/y Dairy manure effluent Four 30 m3 pilot scale ATS Biomass productivity: 2.5–24 g/m2/d, raceways, 1–2% slope, wastewater Biomass composition: 7% N, 1% P, loading: 0.3–2.5 g TN/m2/d, 0.08– N and P recovery values—50–80% 0.42 g TP/m2/d Citrus farm discharge Single-channel 234 × 1.20.09 m Biomass productivity: 5.5–11 g/ dimensions, angled at 0.5%, nylon m2/d, Biomass composition: 3.8% mesh as biomass support, 227 L/ N, 0.8% P, Nitrogen removal rate: min flow rate, 0.49 g-N/m2/d, Phosphorus removal rate: 0.05 g-P/m2/d Diluted food waste Nine channels of 1 × 0.2 m Nitrogen removal rate: 0.27–1.65 centrate channels at 0.5% incline, 5–150 g-N/m2/d, phosphorus removal rate: mm depth, polypropylene mesh 0.02–0.18 g-P/m2/d used as attachment for biomass, seeded with the microalgal consortia Oedogonium sp. (70%), Zygnema sp. (20%) and Oscillatoria sp. (< 10%), 25 L/min/m flow rate, Horticulture A 120 L, 1 m2 ATS with 1% Biomass productivity: 1.2–2 g/m2/d wastewater incline, Seeded with a mixture Biomass composition: 6% N, 2% P of Klebsormidium sp. and Nitrogen removal rate 3.5–6.4 mg Stigeoclonium spp., 2–8 L/min flow N/L/d, Phosphorus removal rate: rate 3.3–3.9 mg P/L/d Swine manure effluent A 1 m2 lab-scale ATS, 55 L/min flow Biomass productivity: 7.1–9.4 rate, nutrient loading range—0.27– g/m2/d Biomass composition: 3.7– 1.39 g TN and 0.08–0.42 g TP 5.7% N, 0.85–1.8%, P 98% TN recovery, 76% TP recovery N, nitrogen; P, phosphorus; TN, total nitrogen; TP, total phosphorus.

References (Ray et al., 2015)

(Valeta & Verdegem, 2015)

(Kangas & Mulbry, 2014)

(Mulbry et al., 2008)

(D’Aiuto et al., 2015)

(Sutherland et al., 2020)

(Liu et al., 2016)

(KebedeWesthead et al., 2006)

130  Current Developments in Biotechnology and Bioengineering

6.4  Closed photobioreactors for microalgae-based wastewater treatment As the name indicates, closed PBRs are sealed from the environment, protecting the algal culture from contamination. Cultivation parameters, such as temperature, pH, dissolved oxygen, and carbon dioxide supply are properly controlled, resulting in better biomass productivity (Sukačová et  al., 2021). The major challenges in closed PBR design are optimal light supply, improved hydrodynamics without imparting shear stress on microalgal cells, improved mass transfer between the liquid, solid and gaseous phases, and energy-efficient systems (Posten, 2009). This section discusses in detail the PBR configurations applied in wastewater treatment.

6.4.1  Vertical column, tubular and flat plate PBRs Among the various closed PBR designs, the vertical column PBR, the horizontal tubular PBR, and flat plate PBRs are the most commonly used designs for the cultivation of microalgae. Thus, these PBR designs are also the most used configurations for MWT. MWT with these closed PBR configurations is summarized in Table 6.4. A brief description of the basic configuration of the PBR design is as follows. Vertical column photobioreactors are cylindrical PBRs with an optimal surface–volume ratio provided by the tall design for maximal light utilization efficiency and mixing can be achieved by gas spargers or baffles. The PBRs are made of glass or transparent polymeric materials such as plexiglass to allow proper light penetration (Acién et al., 2017). Vertical column PBRs display various advantages such as compact structure, low cost, easy to moderate operational skills, and high average biomass productivity (Pawar, 2016). An optimal height of 4 m is required to prevent nutrient gradients in the column, and a diameter of 0.2 m is optimal for maximal light penetration without light shading in the middle of the column (Ramasamy et al., 2020). Mixing is of utmost importance in vertical column PBRs, to ensure light exposure to cells and avoid dead zones, proper gas exchange to avoid oxygen buildup or CO2 starvation in particular zones, and proper distribution of nutrients along with the height of the column (Ashok et al., 2019). Mixing can be attained by various means according to the PBR configuration. Impeller blades and baffles are applied in stirred column PBR, gas sparging from the bottom of the column provides mixing in bubble column PBRs (Fig. 6.2A) and a specially designed air-flow provides mixing in an air-lift PBRs (Singh & Sharma, 2012). Column PBRs are also considered suitable for carbon capture from point sources, such as flue gas, with minimal CO2 losses to the atmosphere (Fig. 6.2B) (Kao et al., 2014). Tubular PBRs are essentially tubes aligned in various configurations, such as the horizontal, inclined, helical, pyramid, and spiral to attain a high surface-to-volume ratio in the order of 100 and effective light harvesting (Posten, 2009). The diameter of the tubes can be minimal (10–60 mm) in contrast to vertical column PBRS, which overcomes light limitations. In addition, the arrangement of the tubes in various configurations increases the length of the PBR to several meters in a given unit area, which in turn increases the areal productivity of the system (Gupta et al., 2015). Mixing in tubular PBRs is attained by air pumping using a pump or airlift configuration. Optimization of the geometric configuration of the tubes for maximal light harvesting, and

Mixed microalgae bacteria consortia Mixed microalgae bacteria consortia

Mixed microalgal consortia Chlorella sp.

Spirulina platensis

Chlorella sp

Mixed microalgal consortia Microalgal consortia

Cooking cocoon wastewater

Chlorella sorokiniana

Photobioreactor design Treatment condition

Synthetic municipal wastewater

Flue gas as waste CO2 source Secondary municipal wastewater Secondary municipal wastewater Rose oil processing effluent Municipal wastewater

Stirred tank PBR, pilot scale

64 days, internally illuminated PBR, light intensity of 582.7 μmol/m2/s, 25% CO2 at 25 mL/min

8-day batch, stirred tank PBR, 12 h:12 h light/ dark cycle, illumination at 360 μmol/m2/s, 19°C

Indoor greenhouse conditions

Tubular PBR-indoor

Stirred tank PBRindoor

20-month outdoor cultivation, ambient light, and temperature, CO2: 2.5–20%

Pilot-scale bubble column PBR

Bubble column PBR- 7-day batch, light intensity of 300 μmol/m2/s, indoor and outdoor aeration with different flue gas percentage (3–25%) at 0.2 vvm, 0.3 g/L inoculum size Pilot-scale bubble 20-month outdoor cultivation, ambient light column PBR and temperature, CO2: 2.5–20%

Bubble-column PBR- 7-day batch experiments, sterilized wastewater indoor as a nutrient medium, 0.8 g/L inoculum size, aeration 3.34 vvm, continuous illumination, and ambient temperature. Diluted human Bubble-column PBR- 6-day batch, 5.5% diluted human urine, urine indoor aerated with 4% CO2 at 0.14 vvm, continuous illumination, and ambient temperature. Domestic Pilot-scale BubbleContinuous, HRT of 1–2 days wastewater column PBR-outdoor

Wastewater

Microalga

NH4-N: 84.1% PO4-P: 90.7% CO2 fixation rate: 0.29 g/L/d

COD: 86.43% TN: 85.66% NH4-N: 97.96% TP: 97.96%

Nutrient removal efficiency

COD:>70%

COD: 98.2% TN: 88.3% PO4P: 64.8%

10.9 g/m2

–

COD: 53% BOD: 60% NH4-N: 34.95%

COD: 72–99% TN: 75–92% TP: 100% –

0.796–0.950 g/L/d

37.2 mg COD/L/d 39.3 mg N/L/d 4.7 mg P/L/d 5 log removal of E. coli and coliforms 1.873–2.53 g/L CO2: 15–25% CO2 fixation rate: 20–35 g/L/d NOx: 65–95% SO2: 93% 0.796–0.950 COD: 71–90% TN: 70–93% g/L/d TP: 90%

–

1.06 g/L 0.14 g/L/d

2.83 g/L 476.25 g/L/d

Biomass production

Table 6.4  Microalgae-based wastewater treatment in the column, tubular and flat plate PBRs.

(Continued)

(Mohammed et al., 2014)

(Su et al., 2011)

(Uysal & Ekinci, 2021)

(Almomani et al., 2019)

(Almomani et al., 2019)

(Kao et al., 2014)

(Dalvi et al., 2021)

(Patil et al., 2021)

(Xue et al., 2021)

References

Chapter 6 • Photobioreactors for microalgae-based wastewater treatment  131

Pilot-scale flat plate PBR

Centrate

2

12.73 mg/L/d 32.48% PHB 470 mg/L/d

Biomass production

Semi-continuous operation, outdoor condition, 47.7 g/m2/d 20% centrate, intermittent flue gas sparging with 10.9% CO2 at 0.1 vvm, ambient light, and temperature

14-day batch, 27–30 °C, 40 μmol/m /s, ambient air supplied at 1 L/min Continuous, HRT-2 days, continuous illumination at 400 μmol/m2/s, 30°C

Treatment condition

(Krasaesueb et al., 2019) (Luo et al., 2019)

References

COD: 82% TN: 85% TP: 100% (RomeroVillegas et al., 2018)

NH4-N: 98.07% NO3-N: 80.1% NO2-N: 67.9% PO4-P: 96.99% TN: 46–59%% NH4-N: 95% TP: 63–81%

Nutrient removal efficiency

PBR, photobioreactor; HRT, hydraulic retention time; vvm, volume of air per volume of medium per minute; COD, chemical oxygen demand; BOD, biological oxygen demand; TN, total nitrogen; NH4-N, ammonia nitrogen; NO3-N, nitrate-nitrogen; NO2-N, nitrite nitrogen; TP, total phosphorus; PO4-P, phosphate phosphorus.

Flat plate PBRindoor Novel open flat plate PBR

Shrimp culture wastewater Piggery biogas slurry

Synechocystis sp. Desmodesmus sp.—bacteria consortia Geintlerinema sp. dominant

Photobioreactor design

Wastewater

Microalga

Table 6.4  Cont’d

132  Current Developments in Biotechnology and Bioengineering

Chapter 6 • Photobioreactors for microalgae-based wastewater treatment  133

(B)

(A)

FIG. 6.2  (A) A laboratory-scale bubble column photobioreactor. (B) Outdoor vertical column photobioreactors for microalgal cultivation.

determination of the flow rate and circulation velocity of the medium based on the tube length for effective nutrient supply. A flow rate of 0.2–0.5 m/s is typically applied for large scale cultivation (Huang et al., 2017). The major challenges in tubular PBRS are the high heating due to the increased surface area to volume ratio, photoinhibition in high light intensities, oxygen hold up due to the increased length of the PBRs, and higher power consumption for proper mixing along the length of the PBR (Gupta et al., 2015). Flat plate PBRs are considered as the most effective PBR design which overcomes the light limitation commonly seen in deep PBR designs. Flat plate PBRs are composed of two flat plates fastened together with varying thickness (a few-70 mm) resulting in a very short light path and high photosynthetic efficiency (Posten, 2009). Dark zones are non-existent in this arrangement. Typical flat plate PBR configurations apply 16 mm thick plexiglass panels (Gupta et al., 2015). Aeration and agitation are provided by pumping of air/gaseous CO2 via a sparger or an airlift design, which produces minimal shear stress to the algal cells (Posten, 2009). The flap plate PBRs can be arranged in a vertical, horizontal, or inclined position to form a unit. Effective capture of incident light in such conformations is achieved by maintaining an optimal tilt angle, in which the PBR is exposed to the light source. For outdoor systems, the orientation of the unit, the geographical location, and seasonal variation can influence the optimal tilt angle (Ramasamy et al., 2020). The major issue with flat plate PBRs is the high risk of photoinhibition

134  Current Developments in Biotechnology and Bioengineering

with high light intensity due to the thin nature of the PBR, excessive heating of the PBRs resulting in huge temperature fluctuations, poor mass transfer efficiency, expensive materials for construction, and difficulty in cleaning (Wang et al., 2012). Among these three basic designs and the varying configurations, flat plate photobioreactors can attain very high biomass production in the order of 7.5–96.4 g/L, followed by vertical column PBRs with biomass production in the range of 19–20 g/L (Vo et  al., 2019). However, limited knowledge exists on the best-suited PBR design for nutrient and pollutant removal by microalgae. Vo et al. opined that biomass production can be considered as a measure of nutrient consumption from the treated wastewater (Vo et al., 2019).

6.4.2  Soft frame photobioreactors Soft frame PBRs do not possess a rigid structural frame as the other regular PBRs, instead, have soft and flexible materials, such as plastic bags and plastic sheets. Plastic bag type PBRs are applied for the cultivation of microalgae on land, while offshore floating type PBRs float on the ocean, with sunlight as the light source and mixing provided by the gentle wave motion. Plastic bag-type PBRs are of various shapes and sizes. They are hung on a sturdy frame either in the vertical position (Chinnasamy et al., 2010; Menke et al., 2012) or inclined position based on the cultivation requirements. Aeration and mixing are provided by sparging air or CO2 via proper provisions (Chinnasamy et al., 2010). The most common material used for plastic bags is polyethylene, and PE has a 92% light transfer efficiency for a 3.2 mm bag, with a refractive index of 1.51 (Johnson et al., 2018). Transparency increases with decreasing thickness of the bag. Plastic bags have been applied as the framework for a flat plate PBE for effective light transfer and utilization (Sierra et al., 2008). Large-scale cultivation of Chlorella in polyethylene bags has been applied for commercial algal biomass production (Borowitzka, 1999). The advantages of using plastic bag-type PBRs for wastewater treatment are multifold: they are inexpensive, have simple pre-sterilization, and have a higher potential for large-scale wastewater treatment with a reduced land footprint. They have been utilized for wastewater treatment with substantial nutrient removal potential (Chinnasamy et  al., 2010; Menke et  al., 2012). The major design consideration in plastic bag type PBRs is the material used, size, aeration and mixing strategy, the frame applied, and the orientation and arrangement of the system (Ting et al., 2017). The major challenge is the environmental impact of the used bags as waste. The bags can be reused multiple times, but effective sterilization post-use is difficult, so disposable bags are applied. Eventually, the disposal of used non-biodegradable bags is a serious concern (Wang et al., 2012). Bio-degradable bags may be an option, which has not been explored yet. Other disadvantages include the distortion of the bag due to gravity, which leads to leakage and light limitation, fragile nature, sub-optimal aeration and mixing, and difficulty in scale-up (Huang et al., 2017). Floating offshore PBRs are specifically recommended by the United States space agency— National Aeronautics and Space Administration (NASA) for simultaneous municipal wastewater treatment and microalgal biomass production. The system aptly called the Offshore Membrane Enclosures for Growing Algae (OMEGA) system (Wiley et al., 2013) displayed several advantages: no land occupation, municipal wastewater treatment using freshwater algae, no biological hazard concern as the leaked freshwater algae cannot survive in saline oceans,

Chapter 6 • Photobioreactors for microalgae-based wastewater treatment  135

temperature control by the surrounded water, mixing and hydrodynamics provided by wave motion, and probable concentration of microalgae culture due to osmosis effect in seawater (Trent et al., 2012; Zhu et al., 2019a). The OMEGA system was tested for a period of two years in the San Francisco Bay with appreciable results (Trent et al., 2012). Algae Systems LLC tested a similar offshore non-diffusive membrane-based PBR for the treatment of municipal wastewater in Daphne AL with successful outcomes and discharge quality treated water (Novoveská et al., 2016). Nevertheless, some bottlenecks exist, such as bio-fouling of floating PBR surfaces and condensation in the closed bags, leading to limiting light intensity and possible eutrophication of the treatment zone due to accidental PBR damage and nutrient spillage (Zhu et al., 2019b).

6.4.3  Membrane photobioreactor (MPBR) As the name indicates, MPBR involves a membrane component in a typical PBR system. The membrane can either be submerged in the cultivation medium/wastewater (submerged MPBR) or held in a separate module in which the cultivation medium/wastewater is recirculated (side stream MPBR). The membrane module acts as a filtration unit that retains the biomass in the PBR, while the treated effluent is removed. The higher residence time of the microalgae in the wastewater improves pollutant removal efficiency due to longer adaptation time, and removal of toxic pollutants with slow kinetics (Galinha et al., 2018). Since the design is applied for biomass retention in the PBR, it is called membrane biomass retention PBR (BR-MPBR) (Bilad et  al., 2014a). In addition, the membrane could serve as a substratum for attached microalgal growth increasing the biomass productivity, reducing the land footprint required for high microalgal productivity, facilitating maximal nutrient removal, and easy harvest of the final biomass (Bilad et al., 2014b; Drexler & Yeh, 2014). The major application of MPBRs is to decouple the close interrelation between the hydraulic retention time (HRT) of the wastewater and biomass retention time (MRT)/solids retention time (SRT) for harvesting biomass. Lower HRT is generally applied in PBRs that results in low biomass growth and biomass washout due to a short contact time with nutrients in wastewater. Longer HRTs are not economically feasible in closed PBR-based wastewater treatment. The application of a membrane module can effectively decouple the relation between HRT and MRT, as the biomass is retained in the membrane (Wang et al., 2017a). A very low HRT of 1-d has been applied for efficacious wastewater treatment in MPBRs (Gao et  al., 2016). Xu et al. successfully utilized a 5 h HRT and 6-day SRT for the treatment of secondary wastewater with biomass productivity of 22.4 g/ m2/d in a stirred tank system (Xu et al., 2015). The membrane module can be attached to any closed PBR design, such as stirred tank (Lee et al., 2018; Xu et al., 2015), column (Bilad et al., 2014b; Marbelia et al., 2014) or flat panel PBR (Azizi et al., 2021; González-Camejo et al., 2018a; González-Camejo et al., 2020b; Viruela et al., 2018). However, it can also be applied in an open system, such as HRAP resulting in higher biomass production, enhanced nutrient removal, and lower energy requirements (Robles et al., 2020). With sufficient aeration and mixing, attached microalgal growth is boosted. A hollow membrane with a provision for gas supply can be used for pumping CO2 into the medium, which provides mixing by sparging (Kalontarov et al., 2014; Vu & Loh, 2016). Such PBRs with membranes for carbonation of the cultivation medium are

136  Current Developments in Biotechnology and Bioengineering

(A)

(B)

(C)

FIG. 6.3  Membrane PBR configurations. (A) A submerged MPBR. (B) A side stream MPBR with the membrane module isolated is an adjacent tank with the wastewater being recirculated. (C) A carbonation MPBR with a hollow fiber membrane promoting aeration (adapted from Bilad et al., (2014a) and Drexler & Yeh (2014)).

called membrane carbonation PBRs (C-MPBR) (Bilad et al., 2014a). The biomass retention and carbonation MPBR are illustrated in Fig. 6.3. Based on the function and pore size, membranes used in algal technology can be classified as follows: macro-filtration (10–100 µm), micro-filtration (900 Å–10 µm), ultrafiltration (40–100 Å), nano-filtration (8–80 Å) and reverse osmosis (5–50 Å) (Drexler & Yeh, 2014). Many synthetic membranes have been applied in algal technology for use in MPBRs, such as cellulose-based membranes—cellulose acetate, reactivated cellulose, and cellulose ester, polymeric membranes, such as polyamide, polysulfone, and polyethersulfone. Other membranes made of polyvinylidene fluoride (PVDF), polypropylene (PP), polytetrafluoroethylene (PTFE), and polyacrylonitrile have also been used. Membranes are chosen based on the end application in biomass retention or carbonation MPBRs (Bilad et al., 2014a; Drexler & Yeh, 2014). Membrane fouling in MPBRs is an obvious challenge in MPBR-based wastewater treatment. Fouling causes changes in membrane permeability and results in membrane flux degeneration. Fouling in algal photobioreactors is mainly due to the deposition of algal organic matter, such as extracellular polymeric substances, including polysaccharides, proteins, and other algal metabolites (Fortunato et  al., 2020). Design of membranes resistant to fouling, alterations in operational conditions, such as HRT, SRT, and membrane flux, pretreatment of the influent wastewater, periodic membrane cleaning, and a combination of any of the above-mentioned techniques are some of the strategies suitable for fouling mitigation in MPBRs (Novoa et al., 2021). Wastewater treatment with membrane PBRs is summarized in Table 6.5.

6.4.4  Algal biofilm-based photobioreactors Microalgae are capable of forming biofilms on surfaces, and attached microalgal cultivation has been applied for higher biomass productivity and easy biomass harvesting (Zhang et al., 2015). Microalgal extracellular polymeric substances provide attachment sites on surfaces, on which

Anaerobically treated malting wastewater

Aquaculture wastewater

Chlorella vulgaris plus activated sludge

Chlorella vulgaris

Scenedesmus sp-bacterial consortia Chlorella vulgaris

Botryococcus braunii

Column plexiglass PBR with a PVDF hollow fiber microfiltration membrane module, inflow rate of 1 L/d, 4 HRT, 20 d SRT, 30°C, ambient air sparged at 40 mL/min, 82.4–90.6 µmol/m2/s, 80 rpm agitation. Column PBR with a side stream flat sheet PVDF membrane module, ambient air sparged at 3.39 L/min, 8400 lux light intensity, 3 d HRT, 10–30 d SRT. Column PBR with a submerged PVDF membrane module, fiber balls as carriers, 4% CO2 at 0.5 L/ min, 101.5 to 112.3 µmol/m2/s, 26–30°C, 1–2 d HRT, 70 days operation

Cultivation conditions

Column PBR with a submerged hollow fiber PVDF membrane module, 2 d HRT, red/blue light at 101.5 to 112.3 µmol/m2/s, ambient air sparged at 0.5 L/min, pH maintained at 6.8–7.6 with 99% CO2 sparging, 25–28°C Secondary Stirred tank PBR with a submerged PVDF treated livestock membrane module, 25°C, 220 µmol/m2/s, ambient wastewater air sparged at 6 L/min, semi-continuous operation with 90% replacement and 3–5 days HRT, 14–16 days SRT Synthetic grey Stirred tank PBR with commercial microfiltration wastewater membrane module, 6000 lux, 12 h/12 h light/dark cycle, HRT 1–7 d, SRT 14 d, Simulated Flat-panel PBR with submerged hollow fiber PVDF secondary membrane, red/blue light at the ratio of 4:1, 4% effluent CO2 at 2 L/min, 26–28°C, 2 d HRT

Chlorella vulgaris, Secondary Scenedesmus municipal obliquus wastewater

Anaerobically treated municipal wastewater

Wastewater

Chlorella pyrenoidosa plus activated sludge

Microalgal source

Nutrient removal efficiency References

0.948 g/L, 0.05 g/L/d

48 mg/L/d

3.5 g/L

1.72–1.84 g/L, 29.8% lipid in C. vulgaris biomass, 36.9% lipid in S. obliquus biomass

14.02–22.03 mg/L/d

1.34–3.4 g/L

(Zhang et al., 2021b)

(Continued)

BOD: 95% TN: (Shafiquzzaman 59.5% TP: 34.5% et al., 2021) Surfactants: 96% TN: 64.9% NH4- (Gao et al., 2015) N: 95.2% TP: 85.2%

TN: 96% TP: 85% (Lee et al., 2018)

DIN: 91.0–99.6% (Peng et al., DIP: 92.1–98.4% 2020) SDZ: 61.0–79.2% SMZ: 50.0–76.7% SMX: 60.8– 82.1% (Gao et al., 2019)

COD: 94% TN: 19.26% TP: 54.95%

Algae lipid production rate: TN: 96.7% TP: (Gao et al., 2021) 19.66 mg/L/d 98% TOC: 95.9%

Biomass production

Table 6.5  Microalgae-based wastewater treatment in membrane PBRs.

Chapter 6 • Photobioreactors for microalgae-based wastewater treatment  137

Wastewater

Secondary pulp and paper wastewater

Outdoor pilot-scale flat plate PBR with 10 cm light path and an industrial scale hollow fiber ultrafiltration membrane, sunlight plus white light at 300 µmol/m2/s, 25°C, pH 7, 1.5 d HRT, 3 d HRT. Outdoor flat panel PBR with industrial-scale hollow fiber ultrafiltration membrane, ambient air sparged at 0.09 vvm, pH maintained at 7.5 with periodic 4% CO2 sparging, sunlight plus white light at 300 µmol/m2/s, 2.5 d HRT, 4.5 d BRT. Flat-panel PBR with a membrane module, 25°C, 300 µmol/m2/s, 1 d HRT, continuous illumination

Cultivation conditions

0.17 g/L/d

78 mg VSS/L/d

258 mg VSS/L/d 5.68% photosynthetic efficiency

Biomass production

TN: 57% TP: 43% (Azizi et al., 2021)

12.5 mg.N/L/d 1.5 (González-Camejo mg.P/L/d et al., 2018b)

29.7 mg.N/L/d 3.8 (González-Camejo mg.P/L/d et al., 2020a)

Nutrient removal efficiency References

Footnote: DIN: dissolved inorganic nitrogen, DIP: dissolved inorganic phosphorus, TOC: total organic carbon, COD: chemical oxygen demand, BOD: biological oxygen demand, TN: total nitrogen, TP: total phosphorus, SDZ: sulfadiazine, SMZ: sulfamethazine, SMX: sulfamethoxazole, PVDF: polyvinylidene fluoride, HRT: hydraulic retention time, SRT: solids retention time, vvm: volume of air per volume of medium per min, VSS: volatile suspended solids.

Chlorella vulgaris

Mixed microalgae Tertiary sewage and bacterial consortium

Mixed microalgae Secondary and bacterial effluent consortium

Microalgal source

Table 6.5  Cont’d

138  Current Developments in Biotechnology and Bioengineering

Chapter 6 • Photobioreactors for microalgae-based wastewater treatment  139

microalgal cells and heterotrophic bacteria could grow. Eventually, microalgal photosynthesis close to the surface boosts bacterial growth which in turn promotes algal photosynthesis forming a mature biofilm (Zhao et al., 2021). Light utilization and photosynthetic efficiency on algal biofilms are high, due to the thin nature of the biofilms and the co-existence of growth-promoting heterotrophic bacteria (Wang et al., 2017b). Biofilm-based photobioreactors are highly advantageous because the harvested biomass has the consistency of a slurry with 10–20% water content, thereby reducing harvesting and drying costs (Gross et al., 2015). Phototrophic biofilm communities comprised of photosynthetic benthic microalgae and heterotrophic bacteria are a beneficial system for nutrient removal in low-strength wastewaters, such as secondary municipal wastewater. In laboratory-scale experiments, various carriers, such as activated carbon, polyurethane sponge, clay discs (Chen et al., 2021), fiber bundles (Gao et al., 2015), polyether sponges (Akao et al., 2021), and walnut shell (Zou et al., 2021), have been added as a substrate for attached microalgal growth. The overall biomass productivity in such systems is a total of the biomass growth in suspension and the attached biomass in carriers, which results in improved biomass productivity compared to suspended cell systems (Chen et al., 2021; Gao et al., 2015). Other biofilm configurations include the stationary biofilm for nutrient removal applied in the algal turf scrubber (Section 3.2), which is a horizontal orientation. Stationary biofilms in a vertical position are known as flat-plate biofilm reactors, in which the attachment substrate is submerged in the cultivation medium. Such configurations are applied in closed systems and are protected from contamination, compared to turf scrubbers (Boelee et al., 2014; Lin et al., 2003). The second type of configuration, called the rotating type, in which the support material rotates or switches between the liquid phase with nutrients and air for gas exchange have been developed. Various rotating type PBRs such as rotating drum PBR, rotating disk PBR, revolving drum PBR and conveyor belt type PBR have been applied for microalgal cultivation and wastewater treatment (Li et al., 2017; Sivasangari, VelRajan & Nandhini, 2019). The third type of biofilm reactor, which applies a porous substrate for improved microalgal attachment and biofilm formation is called a porous substrate PBR (Ekelhof & Melkonian, 2017; Garbowski et al., 2020). Porous substrate PBRs can utilize natural agro-industrial wastes, such as shells, barks, and peels with a porous surface as attachment carriers, participating in waste reduction. As mentioned earlier, easy harvesting is a major advantage in biofilm-based reactors. In addition, the improved light utilization efficiency and carbon assimilation boost biomass productivity. Similar to membrane PBRs, biofilm reactors assist in higher biomass retention time, with the uncoupling of HRT and SRT (Gross et al., 2015). However, the optimization of suitable substrate materials, design, and engineering concepts, and scale-up for large-scale cultivation are challenges in the development of biofilm-based PBRs for microalgal cultivation, even though they have been successfully applied in wastewater treatment (Wang et al., 2017b). The characteristics and performance of wastewater treatment with algal biofilm PBRs are summarized in Table 6.6.

6.4.5  Bottlenecks in the application of closed PBRS for cost-effective wastewater treatment Applications of PBRs for large-scale microalgal cultivation include high installation and operating costs, challenges in optimal light supply, and difficulty in process scale-up. Wastewater

Wastewater

Aquaculture wastewater

Column PBR with a submerged PVDF membrane module, fiber balls as biofilm attachment carriers, 4% CO2 at 0.5 L/ min, 101.5 to 112.3 µmol/m2/s, 26–30°C, 1–2 d HRT, 70 days operation Swine wastewater Fixed bed biofilm reactor, 150 μmol/m2/s, 16/8-hour light/ dark cycle, 5% CO2 at 0.2 L/min

Piggery wastewater

Chlorella vulgaris

Chlorella sorokiniana

–

0.5–1.4 g/m2/d

Bubble column PBR with polyurethane sponge and activated carbon as carriers, semi batch operation with 90% medium replacement, 150 μmol/m2/s, 27°C, 300 rpm agitation, 2% CO2 at 0.1 vvm,

TN: 77.8–80% NO3-N: 99.3% TP: 52–97%% PO4-P: 59–93% TN: 64–81% TP: 97–99% Reduction in sewage suspended solids COD: 95.67% TN: 69.55% NH4N: 91.24% TP: 64.4%% DIN: 91.0–99.6% DIP: 92.1–98.4%

COD: 90.3– 95.2% TN: 58.9–63.8% TP: 92–94%

Nutrient removal

TN: 85.79% TP: 96.56% Cu(II): 93.7% 6 g/L 0.49 g/L/d COD: 95.7% BOD: 99% TN: 94.1% TP: 96.9%

49.7 g/m2/d

14.02–22.03 mg/L/d

Column dissolved gas flotation PBR with cotton cloth curtains 7.37 g/m2 as biofilm attachment substrate, 25°C, 200 μmol/m2/s,

Hog manure wastewater

Chlorella vulgaris

Cylindrical PBRs with pine bark as attachment substrate, pH 7–8, 612 lux at night, sunlight during the day,

Raceway ponds with vertical geotextiles, polyethylene, and cotton textile materials and biofilm attachment substrate, 20°C, 120 μmol/m2/s, ambient air sparged at 3.2 L/min

Treated sewage

Chlamydomonas sp.

Biomass production

Algal biofilm enhanced raceway pond, 0.11 ms/flow velocity, 84.35–117.41 polyester-based vertical biofilms with support, 28°C, pH 6.8, g/m2 425 μmol/m2/s, 14/10 hour light/dark cycle, 0.05% CO2 at 6 L/min

Culture conditions

Indigenous sewage microalgae

Synthetic domestic grey wastewater and Synthetic piggery wastewater Chlorococcum sp. Secondary municipal wastewater

Chlorella vulgaris, Scenedesmus obliquus, Oscillatoria tenuis

Microalgae

Table 6.6  Wastewater treatment with microalgae in biofilm PBRs.

(Chen et al., 2021)

(Shen et al., 2019)

(Peng et al., 2020)

(Wu et al., 2019)

(Garbowski et al., 2020)

(Orfanos & Manariotis, 2019)

(Zhang et al., 2018)

References

140  Current Developments in Biotechnology and Bioengineering

-

15.93 mg/L/d 0.82 g/m2/d 1.373 g/L, 0.072 g/L/d

12.21 g/m2/d

5.67 g/m2/d

6 mg.P/m2/min

COD: 96.96% TN: 50.35% TP: 94.19%; NH4-N: 59.06% TP: 97% 0.16 g.P/ m2/d TN: 52.6% TP: 66.6% TN: 82% NH4-N: 96% TP: 85.9%

(Miyauchi et al., 2021)

(Gao et al., 2015)

(Sukačová et al., 2015) (Tao et al., 2017)

(Yu et al., 2020)

COD, chemical oxygen demand; BOD, biological oxygen demand; TN, total nitrogen; NH4-N, ammonia nitrogen; NO3-N, nitrate nitrogen; PO4-P, phosphate P; TP, total phosphorus; HRT, hydraulic retention time.

Chlorella kessleri

Chlorella vulgaris

Tertiary wastewater Treated sewage

Mixed microalgal consortium Chlorella vulgaris

Inclined algal film PBR with a polyester cloth as biofilm substrate, 60 μmol/m2/s, 25°C,

Horizontal Flat Panel PBR, cement slab as biofilm attachment surface, flow rate 8.8 L/min, 24°C. Airlift algal biofilm PBR with terylene as biomass support material, 120 μmol/m2/s, red: blue light at 4:1, 1 d HRT Simulated Flat-panel PBR with submerged hollow fiber PVDF membrane, secondary effluent flexible fiber bundles as biofilm carrier, red/blue light at the ratio of 4:1, 4% CO2 at 2 L/min, 26–28°C, 2 d HRT Ethanol factory Portable PBR—Acrylic tube-based PBR with cotton cloth wastewater as biofilm attachment substrate, P-depleted Chlorella cells coated on cotton cloth, 100 μmol/m2/s, 30°C, 2% CO2 as gaseous carbon

Anaerobically digested kitchen waste effluent

Scenedesmus sp. Chlorella sp.

Chapter 6 • Photobioreactors for microalgae-based wastewater treatment  141

142  Current Developments in Biotechnology and Bioengineering

treatment requires commercial scale PBRs. The average cost for the installation of PBRs for 1-ha is way over 1 million USD, based on the PBR design. However, scalability over 100 m2 is a huge challenge (Benemann, 2008). The payback period estimated for a vertical tubular PBR in a sustainable building design for algae-derived power generation (from biomethane) was estimated to be 30 years. For a flat panel PBR, the payback period was estimated as 46 years (Bender, 2017). On average, the payback period of PBR installation costs is around 9–13 years, and it can be attained early with the generation of valuable by-products (Vo et al., 2019). Even in the long run, with the high operation and maintenance costs, MWT in PBRs is not economically viable. In addition, the inherent characteristics of wastewaters might corrode or damage the PBR structure, necessitating the use of disposable PBRs (plastic bag types), which are not eco-friendly (Benemann, 2008). Even if certain PBRs are implemented for wastewater treatment, they will be restricted to the treatment of secondary municipal wastewater with low carbon content, optimal N and P and as the final stage of treatment (Marbelia et al., 2014). As discussed previously in Section 3.3, the cost of MWT in open systems can be close to the currently used wastewater treatment methods with slightly reduced environmental impacts. However, the cost of wastewater treatment in PBRs is high. The estimated cost of urban wastewater treatment in an on-site bubble column PBR in a wastewater treatment plant is 95 €/m3 of treated wastewater (Gouveia et  al., 2016). The cost of conventional wastewater treatment in Europe is anywhere between 0.2–0.6 €/m3. The open algal systems come close to this cost, around 1.1 € (1.4 USD) (Ishizaki et  al., 2020). This huge cost gap between the conventional and PBR microalgal system needs to be overcome by an effective large-scale PBR design and reduced energy consumption for aeration and mixing. The treatment cost could come down to 1.6 €/m3 of wastewater if the reactor is scaled up to 1500 L or more, with a 0.35 v/v/d aeration rate and specific energy consumption of 360 W/m3 (Gouveia et  al., 2016). The cost of MWT system is expected to be offset by the revenue stream of the microalgal biomass. However, wastewater treatment is drastically different from a microalgal biorefinery concept. In a microalgal biorefinery, the application of wastewater as a nutrient medium is expected to reduce production costs (Bhatia et al., 2021). In a wastewater treatment system, the primary objective is a treated effluent that meets the regulatory standards for discharge. The biomass generated is not of high-value products, but is most suited for biofuel production purposes (Collotta et al., 2018). Even though several kinetic models exist for the modeling of algal growth in PBRs, more focus is needed for studying the dynamics of the algal interaction with wastewater components and the co-existing microbes, with the resultant wastewater bioremediation, and the microalgal biomass generation (Ramasamy et al., 2020). Due to the vast diversity both in wastewaters and microalgae, the possibility of such studies could be restricted to the interaction between one type of wastewater and one specific microalga. Optimal light supply is crucial in MWT. Nutrient removal and pollutant removal mechanisms require optimal light intensity. Mixotrophic growth is the common mode of microalgal growth in wastewater (Su, 2021). In mixotrophic growth, organic carbon and nitrogen sources are acquired via specific transporters, which are light-stimulated. The wastewater in itself can vary in color and suspended solids content, with numerous particulate matters scattering and absorbing light, eventually interfering with the effective utilization of incident light (Huang

Chapter 6 • Photobioreactors for microalgae-based wastewater treatment  143

et al., 2017). Outdoor cultivation utilizing sunlight is a cost-effective light source option, while outdoor PBR designs with high light harvesting efficiency, such as flat panel and tubular PBR are not suitable configurations for prolonged wastewater treatment in continuous operations. Bio-fouling on PBR surfaces is a serious concern, and in PBRs for wastewater treatment, the threat is high with the high bacterial and organic carbon load. Microalgae-bacterial consortia typically seen in wastewater treatment systems are prone to form biofilms on surfaces with the exopolymeric substances of the bacterial counterpart and the algal exudates. Biofilm formation in the microalgal-bacterial consortium is influenced by the microalgal species (Giraldo et al., 2019), the composition of the algal exudates (Soriano-Jerez et al., 2021), the nutritional status of the medium, and the PBR material (Zeriouh et al., 2019b). Bio-fouling on PBR surfaces interferes with light penetration and effective light utilization, reducing photosynthetic efficiency necessitating periodic cleaning. Attempts have been made to reduce biofouling in PBRs by developing anti-fouling surfaces, surfaces coated with anti-fouling compounds, and various cleaning strategies including physical, chemical, and mechanical methods (Harris et al., 2013; Zeriouh et al., 2019a). Thus, fouling resistant PBR materials is a primary concern. Although often overlooked, draining of the wastewater treatment PBR after application, cleaning, sterilization/sanitation, reassembly, and resuming operation of a PBR is tedious. The persistent odor of wastewaters and the umami of algal growth are hard to overcome, and in general, closed PBRs are difficult to clean (Masojídek & Torzillo, 2014). The cost of cleaning PBRs between runs is significant with labor, chemicals, specific equipment, and reduced biomass production due to the lack of PBR use during cleaning (Olaizola & Grewe, 2019). Some PBR designs, such as tubular and flat plate systems with several internal designs or bends coated with biofilms or fouling, are usually very challenging to clean. For improved cleanability, a large internal area to facilitate cleaning, a smooth internal surface, and reduction in internal structures and bends are preferable (Wang et al., 2012). Various technologies, such as cleaning with mild acid/alkali, scrubbing with soft brushes, cleaning with high-pressure water hoses, and sometimes ultrasonication to clean the surfaces are crucial in maintaining the transparency and light penetration in PBRs (Olaizola & Grewe, 2019). The effect of carryover microbial load on subsequent wastewater treatment operation has never been studied before. Thus, it is recommended to use sanitation with surface application of sanitizing agents, such as sodium hypochlorite and hydrogen peroxide (Krug et al., 2019). In summary, the PBRs used for MWT need to be sturdy, easy to clean, low-cost, feasible for large-scale operation with optimal light supply and be able to attain efficient pollutant removal with satisfactory algal biomass productivity, which could be reutilized to offset the higher capital or operating costs when compared with conventional wastewater treatment systems.

6.5  Conclusions and perspectives Microalgal wastewater bioremediation is an effective circular bioeconomy strategy to recover the nutrients from wastewaters for reuse, with simultaneous waste reduction. Open systems have been historically used for MWT. The technology is mature and several pilot-scale treatment systems exist currently. High-rate algal ponds are most commonly used for the secondary

144  Current Developments in Biotechnology and Bioengineering

or tertiary treatment of municipal wastewater. ATS are highly useful for recirculating water systems, such as aquaponics and aquaculture systems. The challenges in open systems for wastewater treatment are higher land requirements, limited geographical locations, and lower biomass productivity. Closed PBRs possess high installation and operating costs, which is not economically viable for cost-effective wastewater treatment. Flat plate PBRs display the highest biomass productivity and concomitant nutrient removal efficiency, but scaling up of flat plate PBRs is challenging. Tubular PBRs have high energy requirements, and the configurations render the system difficult to clean. Column PBRs are compact, easy to clean, and are easily integrated with membrane systems for effective wastewater treatment. However, membrane cost, energy requirement, and membrane fouling are typical bottlenecks. Biofilm-based reactors are cost-effective and have proven successful for wastewater treatment. However, their application is very limited in real wastewater treatment. Furthermore, PBR designs are not universal, and the microalgal strain, the geographic location, and the process output are taken into account for design considerations. Thus, it is safe to state that the application of closed PBRs for microalgal wastewater treatment is limited by technology. A cost-effective, large-scale, easy to clean, energy-efficient, and economically viable PBR design is required for the realization of using PBR in commercial microalgal cultivation and wastewater treatment.

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SECTION

II

Applications of photobioreactors

7. High-density microalgal biomass production in internally illuminated photobioreactors....................................................................................................... 155 8. The application of cyanobacteria in photobioreactors.......................................... 177 9. Cultivation of diatoms in photobioreactors............................................................ 207 10. Photobioreactor systems for production of astaxanthin from microalgae .......... 229 11. Production of biopolymers in photobioreactors..................................................... 247 12. Production of biohydrogen in photobioreactors.................................................... 269

7 High-density microalgal biomass production in internally illuminated photobioreactors Hee-Sik Kima,b, Dae-Hyun Choa, Jin-Ho Yuna a C EL L FACTO RY RES EARCH CEN T E R , K O R E A R E S E A R C H I N S T I T U T E O F B I O S C I E N C E AND BI O TECHNO L O GY ( KRI BB) , D A E JE O N , R E P U B L I C O F K O R E A b D E PA RT ME N T O F ENVIRONM ENTAL BI O TECHNO L O GY, KR I B B S C H O O L O F B I O T E C H N O L O G Y, U N I V E R S I T Y O F S CI ENCE & TE C H N O L O G Y ( U S T ) , D A E JE O N , R E P U B L I C O F K O R E A

7.1 Introduction Compared with traditional open pond systems, photobioreactors (PBRs) have been recognized as a suitable platform for producing biomass and/or bioactive compounds with minimal impurity since operational parameters and the issue of biocontamination are more manageable in an enclosed PBR (Johnson et al., 2018; Yun et al., 2019). Therefore, photosynthetic organisms produced in closed or semi-closed PBRs were acknowledged to have a multitude of industrial applications (Cañedo & Lizárraga, 2016; Hu & Sato, 2017). Regardless, high costs associated with the assembly and operation of PBRs limited their commercial operations exclusively to producing products with a high market price (Yun et al., 2019); for products that require a large quantity of biomass from cultivation systems (e.g., biofuels), PBRs were usually not a desirable production platform (Singh & Sharma, 2012). Notably, as the focus of photosynthetic organism-based biorefinery has shifted towards the recovery of high-value products, which include nutraceuticals, pharmaceuticals, and recombinant proteins (Heining & Buchholz, 2015), an increasing number of studies are exploring novel designs of PBR as well as new production processes with some reporting successful industrialscale demonstrations (Cho et  al., 2021; Cohen et  al., 2020). For instance, Cho et al. reported the production of astaxanthin, a strong natural antioxidant, from Haematococcus pluvialis in a large-scale polymeric photobioreactor using flue gas from a local power plant; the results indicated germination-based semi-continuous process led to a 2.6 times increment in the productivity of astaxanthin than the conventional batch culture system (Cho et al., 2021). Furthermore, Cohen et al. recently demonstrated a new PBR that was assembled with multiple high-porous polypropylene beds and reported its excellent scalability as well as effectiveness in the simultaneous remediation of aqueous and gaseous pollutants (Cohen et al., 2020). Current Developments in Biotechnology and Bioengineering. DOI: https://doi.org/10.1016/B978-0-323-99911-3.00006-3 Copyright © 2023 Elsevier Inc. All rights reserved.

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Although the authors agree with Koller that there is no ideal PBR constituting the best solution for each cultivation scenario (Koller, 2015), it should be noted that light is considered as a primary resource directly influencing the production of different photosynthetic organisms (Heining & Buchholz, 2015). Therefore, a good number of efforts in modifying PBR configurations and operational conditions have been focused on improving light utilization efficiency (Simionato et al., 2013). For instance, the use of new PBR construction materials with high transparency as well as mechanical strength has been reported (da Ponte et al., 2016; Huang et al., 2017; Johnson et al., 2018; Sergejevová et al., 2015; Wang et al., 2012). Furthermore, energy-efficient light sources were tested in artificial illumination system under different operational settings (Heining & Buchholz, 2015; Murray et al., 2017). In addition, physical configuration of PBR itself has been modified to maximize surface-to-volume ratio (SVR), thereby increasing the surface of PBR that is exposed to incident light (Cañedo & Lizárraga, 2016; Hincapie & Stuart, 2015). Moreover, different turbulence and aeration conditions were tested to increase cellular exposure to the lighting surface and minimize the dark zone (Koller, 2015; Sergejevová et al., 2015). Of the approaches that bear a great industrial potential with respect to improving PBR’s light use efficiency, this chapter focuses on the use of illumination modules directly inside PBR units (Amaral et al., 2020). Indeed, placing light sources inside PBR or designing PBR with light guides has long been explored throughout the literature (Lee & Palsson, 1994; Sergejevová et al., 2015)—Sergejevová et al. report that one of the earliest demonstrations of internally illuminated PBR (referred to hereupon as IIPBR) is dated 1965 with helical looped-PBR with high-pressure mercury lamps placed inside (Sergejevová et al., 2015; Šetlík et al., 1966). Thereafter, different types of IIPBR equipped with a variety of illumination modules have been discussed (Lee & Palsson, 1994; Sun et  al., 2016). In this respect, Heining and Buchholz attempted to classify IIPBRs based on whether a given IIPBR used an artificial light source or light guides (i.e., optical structures, plates, and fibers) (Heining & Buchholz, 2015) –Table 7.1 and Fig. 7.1 provide a wide range of IIPBR configurations available in recent studies, although a combination of both illumination elements is certainly possible (Heining & Buchholz, 2015). Notably, the results of these studies suggest the effectiveness of different types of internal illumination in improving PBR’s light use efficiency; however, it should be also pointed that internal illumination module itself could lead to a compromise in other key parameters associated with PBR’s performance (Cañedo & Lizárraga, 2016; Chen et  al., 2011). Thus, understanding technical trade-offs and identifying possible solutions would be imperative to achieve advanced IIPBR designs that are readily deployable at the industrial scale (Yun et al., 2016). In the first part of this chapter, some of the recent innovations with respect to IIPBR is briefly summarized. The authors then identify general rules that could be considered in the future modifications of IIPBR. Considering these heuristic rules, the second part of the chapter presents newly designed IIPBRs from the authors’ group. IIPBR was first modified to minimize thermal interference from an internal light source; the influence of different light placement depths was then tested to find out the possibility of minimizing energy cost associated with internal illumination. Provided that a number of studies recognized the lack of industrial scale demonstration of IIPBR (Amaral et  al., 2020), newly configured IIPBRs in the authors’ group were further demonstrated up to 500 L operational volume.

Chapter 7 • High-density microalgal biomass production in internally illuminated  157

Table 7.1  Non-exclusive list of studies demonstrating internally illuminated photobioreactors. Note that a variety of lighting systems and light sources were explored for different PBR types. Strain

PBR type

Lighting system

Light source

References

Chlorella vulgaris

Flat-plate PBR

Light guides

Sun et al. (2016)

Dunaliella tertiolecta

Cylindrical PBR

Light-emitting diode (LED)

Hu and Sato (2017)

Chlorella vulgaris

Tubular PBR

Light guides using hollow PMMA tubes Coiled LED strip fixed on stainless steel mesh vertically inside PBR LED unit inserted inside PBR Vertically installed inside PBR

Light-emitting diode (LED) Flexible blue LED tapes inside a flexible transparent PVC tube Flexible blue LED tapes inside a flexible transparent PVC tube Flexible blue LED tapes inside a flexible transparent PVC tube Plastic Optics Fiber (POF) and LED Wireless internal light sources powered by near-field resonant inductive coupling Wireless internal light sources powered by near-field resonant inductive coupling 30 W fluorescent light

Lee and Palsson (1994) Amaral et al. (2020a)

EKE light bulb of 21 V and 150 W

Hincapie and Stuart. (2015)

Chlorella minutissima Cylindrical PBR

Chlorella minutissima Modified column PBR Chlorella minutissima Modified column PBR

Coiled around PBR unit and also installed inside vertically Coiled around PBR unit and also installed inside vertically Light units vertically placed inside PBR Free-floating internal light modules inside PBR

Scenedesmus sp.

Cylindrical PBR

Chlorella vulgaris

Cylindrical PBR

Haematococcus pluvialis

Cylindrical PBR

Free-floating internal light modules inside PBR

Scenedesmus sp., Nannochloropsis salina Chlorella sp.

Annular column PBR

Lights placed inside the inner column of annular PBR Plastic optic fiber cables coupled with an artificial light source

Cylindrical PBR

Amaral et al. (2020a) Amaral et al. (2020b) da Ponte et al. (2016) Murray et al. (2017)

Murray et al. (2017)

Pegallapati et al. (2013)

Overall, this chapter supports the promise of internal illumination in terms of improving PBR’s light utilization efficiency, which in turn could promote the production of photosynthetic organism and its bioactive compound (s). Although discussions present here primarily concern the photoautotrophic cultivation of microalgae (including cyanobacteria), the authors emphasize that most of the key ideas are also relevant to the design and operation of PBR with other photosynthetic organisms as well as under different trophic modes.

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FIG. 7.1  Classification of internally illuminated photobioreactors (adopted and modified from Heining & Buchholz, 2015).

7.2  General rules for the design and operation of internally illuminated photobioreactor 7.2.1  Why internal illumination? As the word itself includes, light (photo-) is the key factor that has driven modifications in PBR configuration (Cañedo & Lizárraga, 2016; Molina et al., 2001). Generally, light enters from the outer surface of the PBR and it would be advantageous when the illuminated surface area is increased (Hincapie & Stuart, 2015). Therefore, Johnson et al. identified the surface-to-volume ratio (SVR) of PBR as one of the key design parameters determining light penetration and distribution for photosynthetic organisms being cultivated (Johnson et al., 2018). Indeed, successful demonstration of the positive influence of an increased SVR on microalgal production has been reported (Hincapie & Stuart, 2015; Morweiser et al., 2010); however, it should be cautioned that constructing PBR with a high SVR could lead to a substantial increase in construction costs compared with the case of assembling the identical volume of PBR with a smaller SVR because of more materials needed (Huang et al., 2017; Molina et al., 2000). Moreover, an increased SVR could also result in an increased physical or chemical gradient within a PBR, necessitating additional adjustments to operational conditions (e.g., gas flow rate, turbulence) to maintain cellular growth (Gudin & Chaumont, 1991). Providing artificial light sources (either externally or internally) could thus be considered, especially when these limitations associated with a high SVR are substantial—by increasing the absolute amount of incident light, compromises in other key PBR design parameters could be avoided (Cañedo & Lizárraga, 2016; Fernández et al., 1999). A number of studies reported the effectiveness of artificial light source in promoting the production of photosynthetic organisms (de Mooij et al., 2016; Lee & Palsson, 1994); for indoor production of high-value products (e.g.,

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carotenoid pigments), artificial light sources have been successfully utilized as a primary light source (Sergejevová et al., 2015). Nonetheless, energy costs associated with artificial light source (often more than one) likely hinder their broad industrial implementation, although energyeffective light sources (e.g., LED) have been actively explored since 1990s (Lee & Palsson, 1994). In this respect, IIPBR of various configurations could be promising alternatives to conventional PBRs with external illumination since the direct placement of light source or the use of light guide could significantly reduce (or completely remove) costs associated with illumination (Heining et al., 2015; Pegallapati & Nirmalakhandan, 2013). Indeed, successful demonstrations of both types of IIPBR (with or without an artificial light source) have been reported. Sun et al., for example, embedded hollow polymethyl methacrylate (PMMA) tubes into a flat-plate PBR to allow the transmission of a fraction of incident light to the interior of the PBR (Sun et  al., 2016); the results indicated an increased light distribution inside PBRs and a 23.42% increase in biomass production (Sun et al., 2016). In addition, several studies reported direct installation of internal illumination unit (i.e., artificial lighting) inside PBRs, which in turn led to a substantial increase in biomass productivity (Lee & Palsson, 1994; Sergejevová et al., 2015). Notably, the positive influence of internal light sources on the production output could remain substantial even after accounting for energy inputs associated with the internal illumination (Sergejevová et al., 2015).

7.2.2  Technical trade-offs associated with internal illumination While the effectiveness of IIPBR in different configurations was reported (Table 7.1), it should be noted that most of these successful demonstrations were limited to laboratory-scale models (Heining & Buchholz, 2015; Xue et al., 2013). Indeed, only a handful of pilot-scale demonstrations are available and these tests were mostly performed in indoor setups with the largest culture volume of 250 L (Heining & Buchholz, 2015; Sergejevová et al., 2015; Xue et al., 2013). One of the few exceptions is the study performed by Zitelli et al., in which the outdoor cultivation of microalga Tetraselmis sp. was carried out in 120 L annular PBRs with an aim of utilizing the inner space of annular PBR as a light guide (Koller, 2015; Zittelli et al., 2006). However, to our knowledge, no outdoor demonstration was performed using pilot-scale IIPBR equipped with an artificial light source. In addition to uncertainties associated with scalability, there are technical trade-offs associated with IIPBR configurations that call for extensive investigations. More specifically, internal light source or light guide could compromise key operational parameters of PBR. Internal illumination modules, for instance, may compromise turbulence within PBR culture volume, thereby limiting mass transfer of nutrients and CO2 (Heining & Buchholz, 2015). In addition, ineffective removal of oxygen generated could inhibit the growth of photosynthetic organisms as well as the production of bioactive compounds (Cañedo & Lizárraga, 2016). Furthermore, the incorporation of an internal illumination module could also substantially reduce the reactor space available for cultivation. Therefore, the design and operation of internal illumination systems should be directed towards avoiding these possible compromises in the rest of functionality parameters (Endres et al., 2016; Koller, 2015; Quinn et al., 2012).

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Critically, it should be cautioned that the degree to which each design of IIPBR impacts the other key operational parameters has not been the subject of most literature. The authors speculate that this lack of multi-aspect evaluation of IIPBR is partially because of the fact that there is no one-size-fits-all criterion when it comes to the design and operational performance of PBR (Koller, 2015)—in the case of microalgal industry, a diverse group of commercial crops with distinctive physiological traits has been identified and it is well known that culture conditions need to be substantially modified based upon the target product (e.g., biomass vs. bioactive compound) even when cultivating the identical industrial crop (Ye et  al., 2018; Yun et  al., 2019). Thus, a compromise in an operational parameter due to the introduction of internal illumination module could not always have a negative influence on the overall performance of IIPBR. For instance, temperature rise because of the use of internal light source has been identified as a possible issue with an IIPBR equipped with an artificial light source; however, as Heining and Buchholz discussed, this may not always be a disadvantage, especially when culturing thermophilic photoautotrophic organisms (Heining & Buchholz, 2015). Therefore, as in the design of any PBR, the authors insist that evaluating technical trade-offs associated with the design of IIPBR should be centered around the strain being cultured as well as target compounds. It also should be pointed out that high context dependency does not discourage large-scale demonstration of a proposed IIPBR. Rather, the authors believe there is a great incentive (more precisely, great necessity) to pursue systematic demonstrations of IIPBR beyond laboratoryscale because context-dependency, in other words, suggests that an IIPBR configuration deemed energy- and cost-effective exclusively at the large-scale can only be reliably translated into full industrial implementation (Smith & Crews, 2014; White & Ryan, 2015). Given that some of the potential interferences of internal illumination module could just become distinct at the large-scale (e.g., mass transfer, turbulence), the authors reiterate that the future design of IIPBR should consider scalability as one of the key design factors (Fig. 7.2).

FIG. 7.2  Some of the key factors to be considered when designing internally illuminated photobioreactors. Note that these factors are not mutually exclusive.

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7.2.3  Heuristic rules for internally illuminated photobioreactor A brief survey of the existing literature led the authors to identify that the design of IIPBR should be focused on avoiding substantial compromise in PBR volume dedicated to cultivation and/or other key culture conditions, including temperature and mass transfer (turbulence), to achieve the industrial implementation of IIPBR. Based on this, general rules for the design and operation of IIPBR could be summarized as below. However, the authors note that these non-exhaustive rules are not mutually exclusive to each other. (1) Ensuring cost- and energy-efficiency of the entire configuration: Though the supplementation of artificial light to photosynthetic organisms promotes their growth, the extent to which a given IIPBR exhibits an increase in biomass or bioactive compound production should not be offset by costs spent on the internal illumination. Apparently, this will be dependent on the market price of the target product as well as operational conditions of IIPBR. (2) Managing thermal interference from internal light source: Regardless of the type of light sources used, any light not absorbed or not used in photosynthesis will be converted into thermal energy (Lee & Palsson, 1994). Heining and Buchholz noted that thermal interference by the internal light source is not always a disadvantage; however, cooling would be required to avoid cell damage by heat (An & Kim, 2000; Heining & Buchholz, 2015), especially when targeting to grow strains with high thermal sensitivity and low heat tolerance (Fig. 7.3). (3) Minimizing interference with cultivation volume and mass transfer: Spatial integration of internal illumination module (either light guide or light source) will inevitably reduce PBR’s working volume, which in turn could negatively influence overall productivity. Moreover, internal illumination modules could also affect the turbulence as well as gas and mass transfers inside PBRs.

FIG. 7.3  One of the major issues of internally illuminated photobioreactor (IIPBR) is undesirable increase in culture temperature due to the heat generated from light source. Note that cultivating strains with high thermal tolerance (e.g., thermal-tolerant Chlorella sp.) would avoid this issue. Moreover, if the accumulation of a target compound is induced under high temperature conditions, the use of internal illumination module will be advantageous.

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It should be emphasized that the purpose of these heuristic rules is to guide the future innovations, not to limit the focus of research and development efforts. In addition, although not listed above, it is true that the design of IIPBR should be fine-tuned based on target products (Johnson et al., 2018). For instance, when the target product from the operation of IIPBR is a secondary carotenoid, it would be advantageous to deploy light sources that could effectively induce the accumulation of this target carotenoid (e.g., using a light source with specific wavelength profile) (Aratboni et al., 2019; Kim et al., 2020; Ma et al., 2018). Moreover, the incorporation of such internal illumination system could be delayed until the later stage at which the accumulation of secondary metabolites is induced, which could also positively contribute to costs associated with IIPBR operation (Aratboni et al., 2019; Kim et al., 2020). In the section below, the authors summarize a series of attempts in which novel IIPBR designs were demonstrated. In particular, these demonstrations were first focused on minimizing the thermal interference from an internal light source (36 W fluorescent light); the possibility of minimizing the size of light source was then explored, which could not only reduce energy cost, but also minimize the volumetric interference with the deployment of internal illumination module. Based on positive results observed in carboy-shaped 20 L cylindrical PBRs, the authors present large-scale demonstrations (up to 500 L of working volume) in both outdoor and indoor setups. Finally, the systematic investigations of IIPBR configurations from laboratory to field allowed us to propose new strategies for operating industrial-scale (e.g., >1000 L working volume) PBRs equipped with internal illumination.

7.3  Design and demonstration of internally illuminated photobioreactors 7.3.1  Internally illuminated photobioreactor with a double-layered glass tube for thermal insulation To overcome some of the issues associated with the industrial implementation of IIPBR, the authors demonstrated a newly designed IIPBR with internal light source. In this IIPBR, a double-layered glass tube was placed inside the culture volume, where 36 W fluorescent parallel lamp (FPL) was housed inside the module (Figs. 7.4–7.6). A factor that was of key concern in this design was thermal insulation as a single fluorescent light was enough to raise the temperature of 20 L cylindrical PBR up to nearly 39°C (Fig. 7.4). For most microalgal crops, including the ones with high thermal tolerance, such a thermal interference would substantially inhibit growth, thereby necessitating an effective cooling system (Hanagata et  al., 1992; Yun et  al., 2019). The design of IIPBR with a tube encasing for artificial light source is provided in Fig. 7.6. Importantly, this double-layered tube was equipped with a water circulator that enabled thermal maintenance of the PBR culture. While a 36 W fluorescent light used in this assembly was observed to reach the highest ambient temperature of 121.8°C when PBR’s culture space was empty, both single- and double-layered tubes seemed to thermally insulate the inner culture space of PBR (Fig. 7.4). However, double-layered one seemed to insulate the PBR from temperature rise more

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27 25 23 21 19 17 15

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FIG. 7.4  Temperature of a fluorescent light (36 W FPL-type) inside a cylindrical PBR (A). Single- and double-layered tubes for light source were tested; and temperature rise inside PBR culture vessel was monitored for 24 hours with growth medium filled in (B). While double-layered glass tube acted as a better thermal insulator than single-layered tube even without operating cooling system, (C) indicates a decrease in the temperature of PBR’s inner culture space as water circulator was operated by circulating 15°C chilled water inside the isolated (bottom) layer of double-layered glass tube.

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FIG. 7.5  Proposed internally illuminated photobioreactor (IIPBR) system. Cylindrical PBR with external lighting exhibited “mutual shading” when the cellular density of a Parachlorella strain reached 2.0 × 107 cells/mL. The dark zone inside externally illuminated PBR could be lit by placing an internal illumination unit inside the culture volume, which would then substantially increase the amount of photic energy available for cellular growth.

(A)

(B)

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FIG. 7.6  Design and actual configuration of an internally illuminated photobioreactor (cylindrical) equipped with a temperature control unit (water circulator). The culture volume of the entire carboy is 20 L and the volume of the glass tube inside this cylindrical PBR is roughly 1.9 L.

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effectively than single-layered tube (30°C vs. 38°C after 24 hours) possibly because of heat absorption in extra glass layer. Thus, even without water circulation, double-layered glass tube acted as an efficient thermal insulator. Finally, when temperature adjustment using water circulator was performed with doubled-layered light encasing, the temperature of the inner culture space of PBR cooled down to 17°C in 24 hours, supporting that this water circulation unit is suitable to maintain desirable temperature conditions for high production of microalgal strains being cultured (Fig. 7.4). Following the confirmation of thermal insulation using double-layered glass tube, the effectiveness of internal light source in promoting the production of a target microalgal strain (i.e., Parachlorella sp.) was tested (Heo et al., 2018). First, the growth of Parachlorella sp. was performed until Day 5 using either single internal light source or five external light sources (5 of 36 W FPL light sources) in 20 L cylindrical PBR with the same configuration (Fig. 7.7). The results indicated the cellular density on Day 5 was 0.91 g/L when using five external light sources, whereas it was 0.43 g/L in the case of operating IIPBR with a single light source. Even though the IIPBR exhibited a lower biomass density, it was notable that the external provision of five times higher light energy only led to ca. 100% increase in cellular density. Furthermore, when turning on light source(s) that remained off from Day 5, the results supported that the provision of a single internal light led to nearly 60% additional increase in biomass production. Given that the later provision of five external light sources also led to ca. 60% of additional increase in biomass production, these tests collectively indicated the effectiveness of the internal illumination module in facilitating microalgal growth (Fig. 7.7). Finally, it should be also noted that IIPBR with temperature controller has been demonstrated in previous studies (Sergejevová et al., 2015). For instance, Sergejevová et al. demonstrated a 10 L volume column equipped with high intensity LEDs and thermal control units that is directly incorporated inside the culture volume (i.e., not in the illumination unit) (Sergejevová et  al., 2015). The same authors also demonstrated a 100 L annular PBR with a LED unit by submerging the light source inside microalgae culture with a metal holder (Sergejevová et al., 2015); the metal holder for the light source was equipped with the water circuit of a temperature controller. Conceptually, this IIPBR configuration is similar to the IIPBR demonstrated above, although our lighting unit allowed the provision of artificial light without submerging a light source directly inside culture vessel. However, not much of information has been provided with respect to the thermal maintenance capability of the IIPBR demonstrated in Sergejevová et al. as well as the effectiveness of internal illumination on cellular growth (Sergejevová et al., 2015). While the authors encourage novel demonstrations of different IIPBR configurations, it should be emphasized that extensive investigations into the corresponding growth performance along with other key culture parameters will be necessary since such data would facilitate evidencebased improvement of each IIPBR configuration for industrial implementation.

7.3.2  Adjusting light placement depth in internally illuminated cylindrical photobioreactor While the results above supported the effectiveness of internal illumination in promoting cultural growth with minimal interference on the temperature condition, another consideration that went into further modification of our IIPBR design was reducing the size of the light source

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(A)

(B)

FIG. 7.7  Effectiveness of a single internal light source in enhancing biomass production. Two cases were compared here: (1) 5 external fluorescent lights were provided throughout the entire 8-day cultivation period, and a single internal fluorescent light (identical to those used externally) was provided from Day 5 (2) a single internal fluorescent light was provided throughout the entire cultivation period, and 5 external lights were supplemented from Day 5. Growth promoting influence of additional light supplementation was greater (in terms of g/L of biomass increased) when a single light source was provided internally. The strain cultured here was Parachlorella sp. and other growth conditions remained identical.

used in the internal illumination module (Sergejevová et  al., 2015; Vasumathi et  al., 2012). Indeed, utilizing a smaller light source could not only reduce the energy cost, but could also reduce the amount of PBR’s volume taken by the internal illumination module, thereby freeing up culture space as well as possibly mitigating the negative influence of the illumination module on turbulence and mass transfer (Cañedo & Lizárraga, 2016). Based on this postulate, four 20 L cylindrical PBRs identical to the one demonstrated in the section above were operated with different lengths of an internal light source (i.e.,

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FIG. 7.8  Comparison of different light placement depths (i.e., different sizes of an internal light source) on the production of algal biomass. As the figure on the right suggests, providing an internal illumination unit down to a third of the entire depth of 20 L cylindrical PBR was enough to result in a comparable increment in biomass production.

different light placement depth) (Fig. 7.8). Importantly, the results indicated that an IIPBR exhibited a comparable level of final culture density even with one third of the full light placement depth (Fig. 7.8). In other words, the results suggested that full-depth placement of light source inside PBR may not be necessary to facilitate additional cellular growth. Moreover, even though the length of a light guide (i.e., glass encasing for light source) remained identical, the results hinted that the entire internal module could be minimized to allow more space for cellular cultivation. To our knowledge, adjusting the placement depth of an internal light source has been rarely explored in the literature; the authors believe the effectiveness of such a modification will be closely influenced by culture operation conditions including the strain being cultured (Smith & Crews, 2014; Yun et al., 2019). Regardless, reducing light placement depth could be necessary when scaling up an IIPBR configuration since it would be costly to place an internal light source through the entire culture depth in a large-scale PBR vessel (Ogbonna et al., 1995).

7.3.3  Large-scale demonstration of internally illuminated photobioreactor Although an increasing number of literatures has investigated different configurations of IIPBRs, most of these demonstrations are limited to a small laboratory-scale (less than 100 L working volume) (Amaral et al., 2020; M. S. Amaral et al., 2020). However, it is critical to further demonstrate proposed IIPBRs at a scale relevant to the industrial microalgal production to validate their effectiveness and identify areas where additional modifications or innovations are necessary (Koller, 2015).

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FIG. 7.9  Demonstration of an internal illumination module with 200 L flat panel PBR.

Based on the positive results observed from laboratory-scale demonstrations, the authors further assembled both cylindrical and flat-panel IIPBRs with a working volume of 500 L and 200 L, respectively (Figs. 7.9 and 7.10). In the case of the cylindrical PBR, the effectiveness of internal illumination was investigated by comparing cylindrical IIPBR’s growth performance with the case where the identical light sources were provided externally (Fig. 7.10). As Fig. 7.10 indicates, the results clearly supported more than twice increase in the biomass production when using internal light sources, confirming the applicability of our internal illumination module in large-scale production systems. Although such a test was not performed with the flat-panel PBR, it should be noted that a relatively long length of the reactor would enable the installation of more internal light sources than a cylindrical PBR with the identical working volume (Fig. 7.9). While the authors confirmed that full-depth deployment of internal light source may not be necessary, another large-scale (300 L) demonstration of IIPBR was performed with a cylindrical reactor with a greater height than the aforementioned 500 L IIPBR, in which light sources were placed through the full depth of PBR’s culture vessel (Fig. 7.11). The height of this cylindrical PBR was 2 m and the working volume was 300 L; the authors placed the light down to a third of the full depth of PBR culture space (i.e., 0.5 m). Overall, 4 internal light sources were installed along with a light guide (plastic tube with a length of the full depth of PBR’s culture space). The cultivation was performed in an outdoor setup and the growth of Parachlorella sp. was tested under 3 conditions: PBR under natural light regime (control), PBR with a light guide only, PBR with a light guide and 4 internally placed light sources (Fig. 7.11). The results clearly indicated that the contribution of light guide to the growth of Parachlorella was not significant: the final cell density in control was 0.57 g DW/L, whereas it was 0.39 g DW/L in the PBR equipped with a light guide only. Combined together with the volume loss due to the placement of the light guide (ca. 19.8 L), which accounted for 6.7% of the culture volume

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FIG. 7.10  Demonstration of the effectiveness of internal illumination with 500 L cylindrical PBR equipped with 4 50-W FPLs (each light source in tube encasing with a water circulation-based temperature controller). Compared to the case in which the identical FPLs were provided externally (bottom left), the internal illumination increased the final biomass density more than twice after 8-day long cultivation period.

(300 L), the results did not justify the use of light guide as a means to promote microalgal growth. Although these results do not completely rule out the effectiveness of a light guide in improving light distribution within PBR, the placement of an internal light guide likely had a negative influence on turbulence as well as mass transfer inside PBR culture, which could limit the growth of microalgae. If this were the case, the authors expect that the use of smaller (and effective) light guides (e.g., light fibers) could turn out as an effective alternative with a substantial positive influence on overall biomass productivity (Zijffers et al., 2008). The results also indicated that the IIPBR equipped with both light sources and light guide exhibited a significant increase in microalgal biomass density compared to the other PBR configurations (Fig. 7.11). In particular, the final culture density on Day 8 was 1.84 g DW/L, which was more than three times greater than that observed in control and nearly five times greater than the final biomass density observed in light guide equipped PBR. While the highest lutein productivity was also observed in the IIPBR equipped with both internal light sources and light guide (Fig. 7.11), these results reiterate the effectiveness of internal light sources on promoting the production of microalgal biomass as well as target compounds (Sergejevová et al., 2015).

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FIG. 7.11  Outdoor demonstration of IIPBR using 300 L cylindrical reactors. The length of these cylindrical PBR is 2 m and three configurations were tested: (1) control with no light amendment (natural light only) (2) PBR with an internal light guide (3) PBR with an internal light guide and internal light sources. In the case of (3), 4 50-W FPLs were used. The comparison of biomass productivity after 8-day long cultivation period indicated that the light guide had a negative influence on biomass production, whereas the provision of internal light sources led to more than thrice increase in biomass productivity. Lutein (target high-value compound from the cultured Parachlorella sp.) production was proportional to biomass accumulation with (3) exhibiting the highest lutein productivity.

Combined together, the series of large-scale demonstrations of IIPBR in this section convince that the proposed IIPBR module is effective in terms of promoting the production of microalgal crop. Especially, the positive influence of internal light sources on microalgal production remained substantial in large-scale IIPBRs, although further modifications to IIPBR could be necessary with respect to the configuration (e.g., light guide) and overall operational conditions (e.g., use of light sources with different wavelength profiles). Importantly, these modification efforts should accompany a comparative economic analysis to determine their effectiveness.

7.4  Opportunities for photobioreactor with internal illumination Although our demonstrations of IIPBR was focused on the scenario in which internal lighting is continuously provided to facilitate the growth of microalgae under photoautotrophy, it is true that operational conditions of IIPBR could be modified based on different cultivation scenarios,

Chapter 7 • High-density microalgal biomass production in internally illuminated  171

FIG. 7.12  Design of 1000 L cylindrical PBR equipped with an internal illumination module with light guide. Note that the operation of this IIPBR could be adjusted based on the light availability. For example, internal light sources could be turned on during nighttime only to facilitate microalgal growth, while saving energy costs.

through which cost-effectiveness of IIPBR is further improved. For instance, when deploying an IIPBR in outdoor cultivation setups, the operation of an internal illumination module could be adjusted based on the availability of natural light. One example is providing internal illumination only during nighttime when no natural light is available (Fig. 7.12)—this approach is likely to reduce biomass loss to cellular respiration and thus have a substantially positive influence on the overall biomass and target compound production (Nwoba et al., 2019; Wang et al., 2012). Similarly, light sensor could be equipped with a PBR unit and the internal illumination can be provided only when natural light availability reached a certain threshold that is not suitable to sustain microalgal growth (Chiu et al., 2016; Nwoba et al., 2019). In authors’ experience, seasonal and diurnal fluctuations in light availability have been one of the key factors determining the productivity of biomass or target compound in large-scale outdoor cultivation regardless of the type of cultivation system. Thus, under outdoor cultivation setups, internal illumination modules could act as a “makeshift treatment” to sustain minimal growth and quality of microalgal culture. Currently, 1000 L PBR that is a scaled-up version of the 300 L IIPBR has been designed with such a sensor-based feedback system and its assembly and outdoor operation is underway in the authors’ group. Another area where the authors’ internal illumination module could be applied is the use of internal illumination as a post-cultivation treatment for microalgal culture grown in industrial heterotrophic fermenters. Even though heterotrophic cultivation itself explicitly rules out the use of light source in the cultivation process, an increasing number of studies have identified the possibility of inducing a certain high-value secondary metabolites (e.g., carotenoid pigments) by exposing heterotrophically-grown cells to a certain period of light condition

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FIG. 7.13  Deployment of rod-shaped internal light sources in a microalgal fermenter. Such a lighting system could facilitate the accumulation of secondary metabolites in heterotrophic cultures that reached the stationary phase.

(Kim et al., 2020). Indeed, the authors’ preliminary test suggested the possibility of enhancing the production of a carotenoid pigment from an industrial microalgal crop when rod-shaped internal light sources were supplemented to 1000 L microalgal fermenter (Fig. 7.13). Even though internal light sources used in IIPBRs demonstrated in this chapter were all rod-shaped fluorescent lamp types, it should be also pointed out that a number of reports on the use of different light sources in IIPBR are available in the literature. For example, Murray et al. deployed wirelessly powered submerged-light illuminated PBR (Murray et al., 2017); the use of free-floating, wireless internal light sources would minimize possible negative influences on turbulence and mixing as well as reduce safety concerns with minimal modifications to the PBR modules. In addition, a new type of light guide that could not just minimize, but improve the mixing of culture suspension has been demonstrated (Sun et al., 2016), suggesting that future research efforts should not be limited to simply minimizing technical trade-offs. With a myriad of opportunities available, the authors strongly urge researchers and practitioners in the field to test out new IIPBRs with different light sources and materials under varying operational conditions to address some of the issues associated with the wide adaptation of IIPBRs in algal industry.

7.5  Conclusions and perspectives In this chapter, the authors identified heuristic rules that should be considered when designing and operating IIPBRs. In particular, developing energy efficient IIPBR with minimal interference on other operational parameters is certainly a challenging task, but not an unachievable

Chapter 7 • High-density microalgal biomass production in internally illuminated  173

one. Importantly, the authors identify that one of the hurdles is the lack of large-scale efforts to demonstrate different IIPBR configurations—the authors insist that IIPBR with at least a few hundred liters of working volume should accompany any IIPBR design proposal upon initial conceptual validation in laboratory. Demonstrations of new IIPBRs from the authors’ group were focused on addressing a few challenges associated with the industrial implementation of IIPBRs. First, thermal interference due to the internal placement of light source was addressed by using a double-layered tube, which enabled the circulation of chilled water within a layer separate from the light source. Even though air and glass layers themselves seemed to act as a thermal insulator, the operation of water circulator clearly suggested its effectiveness in keeping thermal conditions in PBR’s culture volume favorable for the growth of a microalgal crop. In addition, different placement depths of an internal light source were investigated to determine whether it is possible to minimize energy costs associated with light supplementation as well as to reduce likely interference from the illumination module on turbulence and mass transfer within PBR’s culture volume. Clearly, the results with 20 L cylindrical PBR indicated that even placing a light source down to a third of the entire PBR depth was sufficient to facilitate a high level of biomass growth in IIPBR. Based on these demonstrations with small laboratory-scale PBRs, the authors designed and operated larger-scale PBRs equipped with the internal illumination module. Both flat-panel and cylindrical PBRs with a few hundred liters of working volume were successfully equipped with internal light sources; the results of these demonstrations supported that the internal illumination could increase microalgal biomass productivity more than twice than the case in which the identical light sources were provided externally. Furthermore, the authors demonstrated 300 L PBR that was deployed with 50 cm long rod-shaped internal light sources and a light guide; comparison of three PBR configurations indicated that the light guide itself did not lead to a significant increase in biomass production, whereas PBR module deployed with internal light sources exhibited a substantial increase in biomass and lutein productivity. Taken together, the authors’ systematic investigations of IIPBR from laboratory to field support high industrial potential of the proposed IIPBRs under different production scenarios. Although demonstrations in this chapter were focused on addressing the challenges associated with the scale-up of an IIPBR using continuously illuminated internal light sources under photoautotrophy, the authors insist that the use of internal illumination module could be adjusted based on ambient light conditions. Furthermore, internal illumination could be considered in the operation of heterotrophic fermenters as light could induce high accumulation of a certain group of bioactive compounds. Lastly, the authors insist that innovations in optics should be actively adapted in the context of improving the cost- and energy-efficiency of IIPBR in different configurations. Importantly, new innovations should not be limited to developing advanced lighting sources that are energy efficient, but should entail novel materials for improved IIPBR configurations as well as a suite of smart devices that enable the effective control of operational parameters of IIPBRs (e.g., light intensity, L/D cycle). As the list of high-value compounds from photosynthetic organisms continues to expand, the authors believe that the need for a novel production platform will continue to increase; translating excitements around IIPBR in laboratory into actual industrial deployment will thus be a key area of research in the coming years.

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Acknowledgements The authors acknowledge supports from Carbon to X Project (Project No. 2020M3H7A1098291) through the National Research Foundation (NRF) funded by the Ministry of Science and ICT (MSIT), Republic of Korea; KRIBB’s research initiative program (KGM5252221); and a grant from the Commercializations Promotion Agency for R&D Outcomes (COMPA) funded by the MSIT of Korea (No. 2021B100). The authors are also grateful to Prof. Sang Jun Sim and the series Editor, Prof. Ashok Pandey, for the opportunity to contribute to this important series.

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Šetlík, I., Komárek, J., Prokeš, B., 1966. Short account of the activities from 1960 to 1965 and some future prospects. Ann. Rep. Algol. Labor 1966, 5–36. Simionato, D., Basso, S., Giacometti, G.M., Morosinotto, T., 2013. Optimization of light use efficiency for biofuel production in algae. Biophysical Chemistry 182, 71–78. Singh, R., Sharma, S., 2012. Development of suitable photobioreactor for algae production: A review. Renewable and Sustainable Energy Reviews 16 (4), 2347–2353. Smith, V.H., Crews, T., 2014. Applying ecological principles of crop cultivation in large-scale algal biomass production. Algal Research 4, 23–34. Sun, Y., Huang, Y., Liao, Q., Fu, Q., Zhu, X., 2016. Enhancement of microalgae production by embedding hollow light guides to a flat-plate photobioreactor. Bioresource Technology 207, 31–38. Vasumathi, K., Premalatha, M., Subramanian, P., 2012. Parameters influencing the design of photobioreactor for the growth of microalgae. Renewable and Sustainable Energy Reviews 16 (7), 5443–5450. Wang, B., Lan, C.Q., Horsman, M., 2012. Closed photobioreactors for production of microalgal biomasses. Biotechnology Advances 30 (4), 904–912. White, R.L., Ryan, R.A., 2015. Long-term cultivation of algae in open-raceway ponds: lessons from the field. Industrial Biotechnology 11 (4), 213–220. Xue, S., Zhang, Q., Wu, X., Yan, C., Cong, W., 2013. A novel photobioreactor structure using optical fibers as inner light source to fulfill flashing light effects of microalgae. Bioresource Technology 138, 141–147. Ye, Y., Huang, Y., Xia, A., Fu, Q., Liao, Q., Zeng, W., Zheng, Y., Zhu, X., 2018. Optimizing culture conditions for heterotrophic-assisted photoautotrophic biofilm growth of Chlorella vulgaris to simultaneously improve microalgae biomass and lipid productivity. Bioresource Technology 270, 80–87. Yun, J.-H., Cho, D.-H., Heo, J., Lee, Y.J., Lee, B., Chang, Y.K., Kim, H.-S., 2019. Evaluation of the potential of Chlorella sp. HS2, an algal isolate from a tidal rock pool, as an industrial algal crop under a wide range of abiotic conditions. Journal of Applied Phycology 31 (4), 2245–2258. Yun, J.-H., Smith, V.H., La, H.-J., Keun Chang, Y., 2016. Towards managing food-web structure and algal crop diversity in industrial-scale algal biomass production. Current Biotechnology 5 (2), 118–129. Zijffers, J.-W.F., Janssen, M., Tramper, J., Wijffels, R.H., 2008. Design process of an area-efficient photobioreactor. Marine Biotechnology 10 (4), 404–415. Zittelli, G.C., Rodolfi, L., Biondi, N., Tredici, M.R., 2006. Productivity and photosynthetic efficiency of outdoor cultures of Tetraselmis suecica in annular columns. Aquaculture 261 (3), 932–943.

8 The application of cyanobacteria in photobioreactors Congying Zhanga,b, Yi Wua, Ruibing Penga a

KE Y LABOR ATO RY O F APPL I ED M ARI NE B I O T E C H N O L O G Y, N I N G B O U N I V E R S I T Y, MI N I S T RY OF E DUCATI O N, NI NGBO , ZHEJ I ANG , P E O P L E ’ S R E P U B L I C O F C H I N A b S C H O O L O F L I F E SC I ENCE, HANGZHO U I NS TI TUT E F O R A D VA N C E D S T U D Y, U N I V E R S I T Y O F C H I N E S E ACADEM Y O F S CI ENCE, HAN G Z H O U , Z H E JI A N G , P E O P L E ’ S R E P U B L I C O F C H I N A

8.1 Introduction Blue-green algae are one of the most primitive prokaryotic photoautotrophs, and they have many similarities with bacteria, which is why they are also called cyanobacteria (Percival & Williams, 2014). In terms of the chemical composition of the cell wall, it is a viscous aminopeptide and organelle structure without membranes (Vachard, 2021; Vincent, 2009). Therefore, cyanobacteria are similar to bacteria in growth, reproduction, and ecological distribution, showing rapid proliferation and strong environmental adaptability (Gaysina et al., 2018). In the course of several billion years of life-evolution history, hypopuses such as akinetes and heterocysts have appeared to resist adverse environments (high temperature, lack of water, etc.). Cyanobacteria not only have the characteristics of bacteria and other prokaryotes, but also belong to the genus Cyanophyta. Their autotrophic lifestyle based on photosynthesis provides a large amount of energy for life activities, such as synthesizing cyanobacteria starch, pigments, and proteins and other specific high nutritional value-added substances (Percival & Williams, 2014). Engineered cyanobacteria, represented by Spirulina Maxima, have the characteristics of a high protein content, a variety of disease-resistant compounds and easy digestion, so they have become a high-quality food and an important source of natural medicine (Belay et al., 1993). Since the nutritional value of Spirulina from Lake Sosa Texcoco in Mexico has been validated by scholars worldwide, the research on the domestication and cultural conditions of Spirulina have become a focus of cyanobacteria research (Baldia et  al., 1995). Controlling the culture conditions of cyanobacteria, such as light, temperature, salinity, and nutrients, is the basis for the industrial production of cyanobacteria (Avinash et al., 2020). As people move towards the era of automation and information, the inefficient old production mode can no longer meet the society’s needs. Therefore, a new type of algae culture device represented by photobioreactor can not only ensure high and stable output, but also solve some problems of occupied areas and vulnerability to weather. The engineering production mode of “cyanobacteria + photobioreactors” Current Developments in Biotechnology and Bioengineering. DOI: https://doi.org/10.1016/B978-0-323-99911-3.00011-7 Copyright © 2023 Elsevier Inc. All rights reserved.

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provides a new method for the efficient production of food and natural medicine (Hu et  al., 2018; Schulze et al., 2014). In this chapter, a brief introduction for cyanobacteria, and the applications of different types of photobioreactors and engineering cyanobacteria in photobioreactors are introduced.

8.2 Cyanobacteria Blue-green algae are one of the oldest producers on earth, and they are small and flagella-free and have the most complete photosynthesis machinery (mainly chlorophyll a + b and phycocyanin-based photosynthetic pigments). They also have subcellular structures such as peptidoglycan cell walls, formed thylakoids, particles, and pseudo-vacuoles (Fig. 8.1A and B) (Holt & Edwards, 1972; Walsby, 1994). Cyanobacteria usually live in single-celled individuals, and most of them form filaments or live in colony groups. The shapes of the single cells are mostly spherical, sickle-shaped, ovate, and columnar. The populations are spherical, oval, irregular, oval, and reticulate, and the agglomerated populations are often wrapped in the form of some polysaccharides (Fig. 8.2) (Otsuka et  al., 2001). These long-term evolutionary adaptations of biological characteristics have allowed cyanobacteria over billions of years of biological evolution to become the dominant producer position. The classification of cyanobacteria is mainly based on its morphological structure, reproduction methods and other characteristics (Singh & Montgomery, 2011), and they can be mainly divided into Chroococcales, Osillatoriales, and Nostocales (Table 8.1). Chroococcales usually form colonies, with few single-cell species, others that form spherical colonies, and many populations form gelatinous quilts (Markov & Zakharov, 2009). The common species are Chroococcus, Merismopedia, Microcystis, and Dactylococcopsis. Filamentous cyanobacteria are externally coated with colloid sheath with various colors and texture, which are heterocyst and thick-walled spores in most species (Sumina & Sumin, 2013). The location of the heterocysts is closely related to the characteristics of their genera. The common species include Anabaena, Anabaenopsis, Nostoc, and Aphanizomenon. Although there are many kinds of cyanobacteria, the only species that can be cultured on a large scale are Spirulina platensis, Spirulina maxima, Nostoc flagelliforme, which are selected based on their culture conditions and utilization value (Bao et al., 2012; Saeid, 2016). Cyanobacteria are different from other eukaryotic microalgae and have no way of sexual propagation mainly including vegetative reproduction and asexual reproduction. Spirulina usually grows and propagates in the form of algal colonies (Fig. 8.3, life history of spirulina) (Ciferri, 1983; Hense & Beckmann, 2010; Sivakami, 2004). Some filamentous cyanobacteria also can produce akinetes to resist adverse environments, which are formed by nutrient accumulation (cyanophycins) and thickening of the cell wall, and are called hypopus. Similar to Osillatoriales, filamentous cyanobacteria can also form heterocysts that have thick cell-wall, lack phycobilin, and no gas vesicle or stored substances. There are also a few species that can form exospores and endospores. Blue-green algae are highly adaptable and widely distributed in a variety of natural environments, including various bodies of water, soil and on or in certain organisms. It can even be

Chapter 8 • The application of cyanobacteria in photobioreactors  179

(A)

(B)

(C)

FIG. 8.1  A structural representation of cyanobacteria cells. (A). Transmission electron microscope (TEM) of cyanobacteria cell (Synechococcus lividus Copeland). Central nuclear region (n) containing a polyhedral body (b), polyphosphate granules (g), thylakoidal membranes (t) running nearly parallel with the plasma membrane (pm), and the cell wall (cw) are represented. Arrows indicate rows of particles (phycobilisomes) along outer surfaces (stroma side) of thylakoids; (B). The structure of cyanobacteria cells mode; (C). A TEM image of Microcystis sp. The cylindrical gas vesicles (P) occupied in the most regions of cyanobacteria cell (adapted from Holt and Edwards (1972) and Walsby (1994)).

180  Current Developments in Biotechnology and Bioengineering

(A)

(B)

(C)

(D)

(E)

(F)

(G)

(H)

(I)

(J)

(K)

(L)

FIG. 8.2  Morphological diagrams of common cyanobacteria species in water. (A): Dactylococcopsis acicularis; (B): Chroococcus sp.; (C): Synechococcus sp.; (D): Merismopedia sp.; (E): Gomphosphaeria sp.; (F): Microcystis aeruginosa; (G): Oscillatoria sp.; (H): Spirulina major; (I): Phormidum sp.; (J): Anabaenopis sp.; (K): Anabaena sp.; (L): Aphanizomenon sp. The picture source is based on following websites.

found on rock surfaces and in other harsh environments (high and low temperatures, salt lakes, deserts, ice sheets, etc.) (Gaysina et al., 2018). They are known as “pioneer creatures”. They play an important role in rock weathering, soil formation, and water ecological balance. The reason why cyanobacteria have strong adaptability is that they have evolved some special functions in the process of their long-term adaptive evolution (Chen et al., 2021). Most cyanobacteria have the ability to fix nitrogen, and the heteromorphic intracellular nitrogenase of Aphanizomenon can fix and oxidize free-nitrogen to nitrogen-containing compounds (Staal et al., 2003). These abilities allow them to occupy a dominant position in phytoplankton in extremely nitrogen-deficient waters, and provide large amounts of nitrogen to the freshwater

Chapter 8 • The application of cyanobacteria in photobioreactors  181

Table 8.1  Taxonomic characteristics of different species and genera of cyanobacteria. Cyanophyceae

Features

Marking

Common genera

Chroococcales

Single cell or population, without branching processes, individual cells without apical and basal differentiation. Uniseriate filamentous bodies with no heterocyst and obvious algal colonization segments.

Single cells: spherical, wedgeshaped and oval. Populations: spherical or irregular groups. Being camping and floating. Freshwater products. With or without sheaths. Without heterocyst and thick-walled spores, generally unbranched or form crossed opposite branches. Arranged in a row of unbranched or pseudobranched filaments. The colloidal sheath is “hydrated” or very strong, transparent and colorless or in a variety of colors.

Dactylococcopsis acicularis; Chroococcus minutus; Synechococcus; Merismopedia elegans; Microcystis aeruginosa; Aphanocapsa; Aphanothece Oscillatoria Formosa; Spirulina maxima; Spirulina jenneri; Phormidium tenue; Trichodesmium; Lyngbya

Osillatoriales

Nostocales

Uniseriate filaments with heterocyst and obvious algal segments. The cells on the filaments are round, and some of the apical cells are gradually narrow.

Anabaenopsis; Anabaena spiroides; Nostoc flagelliforme; Raphidiopsis; Aphanizomenon; Gloeotrichia echinulata

HORMOGON

VEGATIVE CELLS

NECRIDIA MATURE CELLS FIG. 8.3  Life cycle of spirulina. Mature hormogon of spirulina can form specific death hollow cells (necridia), which divide the hormogon into several fragments. These fragments turn into hormogonias under sliding functions. Every hormogonia can develop a new hormogon of spirulina (adapted from Ciferri (1983)).

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FIG. 8.4  Utilization pathways of nitrogen assimilation in cyanobacteria. NRT, nitrate transporter; URT, urea transporter; CYT, cyanate transporter; AMT, ammonium nitrogen transporter; NR, nitrate reductase; NIR, nitrite reductase; Glu, glutamate; Gln, glutamine; GS, glutamine synthetase; GOGAT, glutamate synthase; 2-OG, 2-ketoglutaric acid.

food chain, accelerating the nitrogen cycle (Fig. 8.4) (Boussiba, 1991; De Philippis & Vincenzini, 1998). Therefore, the inoculation of nitrogen-fixing cyanobacteria can increase the bioavailable nitrogen in agricultural soil and increase the yield of rice (Pankratova et al., 2008). Some cyanobacteria can also form pseudovacuoles, which contain nitrogen and other mixed gases to a maintain dynamic balance with dissolved gases in water (Holt & Edwards, 1972). Blue-green algae can make use of the synthesis and cleavage of pseudovacuoles to allow them to move, vertically in the water layer, and select suitable light conditions for photosynthesis and nutrient absorption and utilization (Fig. 8.1C) (Walsby, 1994). In addition, cyanobacteria can secrete extracellular polysaccharides to resist external adverse environments, including nutritional storage, protection against oxygen attack, protection against metal toxicity, prevention of predation by herbivores, etc. (Fig. 8.5) (De Philippis & Vincenzini, 1998). In addition, cyanobacteria also have cyanophycean toxins and CO2 concentrating mechanisms (Fig. 8.6) (Badger et al., 2002).

Chapter 8 • The application of cyanobacteria in photobioreactors  183

(A)

(C)

(E)

(B)

(D)

(F)

FIG. 8.5  The different exocellular polysaccharides of cyanobacterial strains. (A) Chroococcus sp. (1000×); (B) Phormidium sp. (1000×); (C) Cyanothece CE 4 (775×; bright field); (D) Nostoc sp. (480×); (E) Cyanothece PCC9224 (775×); (F) Nostoc PCC7906 (194×). (A) and (B) are attributed to sheaths. (C) and (D) are belonged to capsules. (E) and (F) are classified to slimes (adapted from De Philippis and Vincenzini, (1998)).

FIG. 8.6  The CO2 concentration mechanism (CCM) of cyanobacteria. BCT1, BicA1 and BicA2 was assigned to bicarbonate transporters. NDH-14 and NDH-13 were the parts of if CO2 uptake systems. Carboxysomes included RuBisCO and CcmM. Non-carboxysomal carbonic anhydrases contained CahB1 proteins. NDH-14 and NDH-13 were expressed by ChpX and ChpY gene. EPS, exopolysaccharide layer; OM, outer membrane; CM, cytoplasmic membrane; TM, thylakoid membrane.

184  Current Developments in Biotechnology and Bioengineering

8.3  Applications of cyanobacteria 8.3.1  Nutritional value Cyanobacteria can utilize light energy to efficiently produce and accumulate proteins, fats, vitamins, and other organic compounds with photosynthetic pigments, therefore implies abundant nutrition and commercial values (Rajneesh et  al., 2017). Some metabolites of cyanobacteria, such as b-carotene and g-linoleic acid, are used as feed supplements and food additives (Ötleş & Pire, 2001; Spolaore et al., 2006). Cyanobacteria have gradually been developed and industrialized as food and health products, especially Spirulina and Nostoc (Table 8.2) (Grosshagauer et al., 2020). Spirulina is protein-rich, greatly far beyond eggs (Aouir et al., 2017; Muys et al., 2019). It contains Vitamin B12, bioactive polysaccharide and iron, thereby exhibits antibacterial, antifungal, antioxidative properties. Spirulina is often sought after by food nutritionists because of its comprehensive nutrition, even referring to it as the “nutrition champion on the earth”. Among them, large-scale production varieties such as Arthrospira platensis and Spirulina maxima (Table 8.2), have high protein levels (up to 70% of their dry weight) and are rich in comprehensive essential amino acids, which meet the human body’s demand for essential amino acids (Ciferri, 1983). Nostoc is abundant in various environments, including Nostoc flagelliforme, Auricularia auricula, Nostoc Sphaeroides, which are rich in a variety of amino acids, trace elements, and vitamins to meet the nutritional needs of humans (Table 8.2) (Gao, 1998; Kadnikova et  al., 2015). N. Sphaeroides is rich in calcium, and the content of harmful metals such as chromium is very low, so it is an ideal source of calcium.

8.3.2  Medical value Chemically active metabolites such as polysaccharides, cryptoalgin, and phycobiliproteins extracted from cyanobacteria exhibit anticancer, antibacterial, antivirus, antiparasite, or enhance immunity and prevent diseases (Singh et al., 2011). In terms of anticancer and antitumor, cryptophycin 1 extracted from cyanobacteria is a powerful anti-cancer substance, that is 100–1000 times stronger than the existing anticancer drugs such as vincristine and taxon in inhibiting human colon cancer and nasopharyngeal carcinoma (Tschappat, 2010). In addition, other substances extracted from cyanobacteria can also effectively inhibit the activity of breast cancer, lung cancer, prostate cancer, and other cancer cells (Coleman et al., 2003; Tschappat, 2010). Moreover, due to the long-term use of the same anticancer drug, many cancer cells have developed drug resistance, so new anticancer drugs extracted from cyanobacteria are expected to become a powerful new force in the “fight against cancer” (Singh et al., 2011). Studies have shown that the phagocytic activity and antigen of immune cells in mice and chickens increased significantly after ingestion of Spirulina (K. Hayashi et al., 1996; T. Hayashi et  al., 1996). In the human blood cells cultured with an extract of Spirulina, the substances related to immune regulation were significantly higher than the original level (Khan et al., 2005).

Chapter 8 • The application of cyanobacteria in photobioreactors  185

Table 8.2  The nutrition composition of various common blue-green algae, including lipids, proteins, and metal elements. SFA, statured fatty acid; PUFA, polyunsaturated fatty acid; MUFA, monosaturated fatty acid. Nutrition parameters

Arthrospira platensisa, b, c

Spirulina maximad, e, f

Nostoc commune

Nostoc flagelliforme

Microcystis Chroococcus aeruginosag, h minutus

Crude lipids (%) C16: 0 (%) C18: 2n-6 ∑SFA ∑MUFA ∑PUFA ∑ω-6 PUFA Crude protein (%) EAA (g/100 g)

3.94 ± 2.34

3.60 ± 0.10

0.21 ± 0.04

0.31 ± 0.01

15.42 ± 2.07

0.99 ± 0.09

52.14 16.76 67.92 10.78 21.30 21.26 52.60

9.83 4.89 6.29 1.10 5.38 5.35 3.46

35.82 16.34 46.31 11.24 51.90 35.09 44.90 ± 1.80

– – – – – – 2.22 ± 0.57

– – – – – – 23.05 ± 0.94

– – – – – – 55.60

44.88 ± 0.12 6.01 ± 0.20 59.86 ± 0.38 15.34 ± 0.05 24.80 ± 0.36 24.41 ± 0.33 61.82 ± 0.24

27.75 ± 1.21

39.19 ± 3.20

7.07 ± 0.01

37.60

21.60

Isoleucine (Ile)

3.64 ± 0.20

6.03 ± 0.51

5.57

2.64

Leucine (Leu)

6.17 ± 0.23

8.02 ± 0.70

8.75

5.42

Lysine (Lys)

3.40 ± 0.02

4.59 ± 0.43

5.23

2.58

Methionine (Met) Phenylalanine (Phe) Threonine (Thr)

1.71 ± 0.11

1.37 ± 0.35

1.73

1.51

3.33 ± 0.12

4.97 ± 0.63

4.23

2.83

3.31 ± 0.07

4.56 ± 0.01

5.68

3.11

Tryptophan (Try) 0.85 ± 0.02 Valine (Val) 4.21 ± 0.10

1.40 ± 0.00 6.49 ± 0.39

– 6.20

– 3.19

Histidine (His)

1.13 ± 0.04

1.76 ± 0.18

1.40

0.84

NEAA (g/100 g) Alanine (Ala)

33.94 ± 0.09

51.77 ± 4.17

52.18

56.41

5.02 ± 0.07

6.79 ± 0.64

7.88

6.11

Arginine (Arg)

4.47 ± 0.05

6.50 ± 0.47

0.71

3.94

Aspartic acid (Asp) Glutamic acid (Glu) Glycine (Gly)

6.31 ± 0.16

8.63 ± 0.38

12.95

6.18

8.47 ± 0.19

12.67 ± 1.40

12.81

7.98

3.43 ± 0.10

4.72 ± 0.34

4.79

2.89

Proline (Pro)

2.53 ± 0.04

3.92 ± 0.19

3.55

1.97

± ± ± ± ± ± ±

(8.78 ± 0.93) × 10−2 1.10 ± 0.02 (0.18 ± 0.00) × 10−2 1.50 ± 0.00 (2.21 ± 0.24) × 10−2 0.60 ± 0.00 (0.22 ± 0.00) × 10−2 0.20 ± 0.00 (0.38 ± 0.01) × 10−2 1.02 ± 0.02 (3.01 ± 0. 56) × 10−2 1.25 ± 0.03 (0.31 ± 0.00) × 10−2 0.07 ± 0.01 – 1.57 ± 0.01 (1.66 ± 0.11) × 10−2 0.22 ± 0.01 (0.81 ± 0.00) × 10−2 10.87 ± 0.02 (12.42 ± 0.31) × 10−2 1.45 ± 0.00 (0.27 ± 0.00) × 10−2 1.05 ± 0.00 (0.53 ± 0.00) × 10−2 2.78 ± 0.01 (0.38 ± 0.00) × 10−2 – (1.17 ± 0.06) × 10−2 – (4.20 ± 0.17) × 10−2 0.71 ± 0.01 (3.81 ± 0.01) × 10−2

(Continued)

186  Current Developments in Biotechnology and Bioengineering

Table 8.2  Cont’d Nutrition parameters

Arthrospira platensisa, b, c

Spirulina maximad, e, f

Nostoc commune

Nostoc flagelliforme

Microcystis Chroococcus aeruginosag, h minutus

Cysteine (Cys)

0.64 ± 0.03

0.40 ± 0.16

0.03 ± 0.00

0.28

0.08

Tyrosine (Tyr)

3.07 ± 0.05

3.95 ± 0.43

0.26 ± 0.03

4.00

2.48

Serine (Ser)

–

4.19 ± 0.16

0.91 ± 0.01

(0.01 ± 0.00) × 10−2 (0.11 ± 0.00) × 10−2 (1.94 ± 0.07) × 10−2

5.20

2.68

Mental element (mg/kg) Ca –

9100

–

3.5 93.6 24.6 3500 1.1 – –

15 079.43 ± 4.01 13.88 ± 0.91 367.62 ± 3.31 NA 816.54 ± 2.70 3.30 ± 0.05 127.59 ± 2.13 0.68 ± 0.01

–

Zn Fe Mn Mg Cu Sr Se

128.82 ± 9.08 5.70 ± 0.06 52.76 ± 0.62 2.01 ± 0.01 27.01 ± 0.20 0.37 ± 0.01 – –

– – – – – – –

– – – – – – –

9.00 6.40 3.10 2.40 4.00 – –

± ± ± ± ±

1.00 2.00 0.40 0.10 1.00

(a, Aouir et al., 2017; b, Bashir et al., 2016; d, Batista et al., 2013; f, Clément et al., 1967; c, Cogne et al., 2003; h, de la Fuente et al., 1977; e, Ötleş & Pire, 2001; g, Piorreck et al., 1984.

8.3.3  Other values The high oil content of cyanobacteria has great potential for use as fuel and is expected to replace fossil fuels as a more economical, sustainable, and environmentally friendly fuel source (Anahas & Muralitharan, 2018). Cyanobacteria can improve soil conditions through nitrogen fixation and ammonium transfer, which is of great significance to maintain soil fertility and restore degraded soil; Cyanobacteria can also degrade plastics and solve the problems that have plagued environmental protection for many years (Paul et al., 2013; Sahu et al., 2012).

8.4  Controlling cultivation of cyanobacteria 8.4.1  Light and temperature on cyanobacteria Considering the dynamic nature of the overall environmental factors of the aquatic ecosystem, the variation range of ecological factors such as salinity, temperature and nutrients is relatively stable, while the variation range of light factor remains highly unstable (Duanmu et al., 2017). Light is critical for cyanobacteria growth and reproduction, dominant population formation and their ecological distribution (Montgomery, 2016). Light factors can affect the shape and size of cyanobacteria populations, which may be related to the synthesis of external polysaccharides, and populations show different perforation phenomena under different light intensities

Chapter 8 • The application of cyanobacteria in photobioreactors  187

(Montgomery, 2015). In addition, the physiological growth of cyanobacteria greatly depends on the light quality and photoperiod, and some specific light characteristics can enhance or weaken some special metabolites of cyanobacteria (Table 8.3). A suitable photoperiod can maximize the efficiency of energy savings and improve the production efficiency of spirulina. Certain studies have found that the rhythm of cyanobacteria is regulated by the kaiC, kaiA, and kaiB genes (Dvornyk et al., 2003). Temperature has a significant effect on the biomass accumulation, temporal and spatial distribution, and population morphology of cyanobacteria (Stal, 2009; Walls et al., 2018). Similar to the other physiological characteristics of microalgae, cyanobacteria also have the most suitable growth temperature range (Table 8.4). For example, Oscillatoria shows stronger low-temperature tolerance, while Microcystis shows the opposite (Levis & Pfennig, 2020; Nadeau & Castenholz, 2000). This may be related to the water environment, the adaptability and genetic characteristics of different cyanobacterial genera. Temperature affects the metabiotic activity and growth-related enzymes in cyanobacteria, and then affects their growth, reproduction, and cell division (Visser et al., 2016). Some studies have pointed out that the water temperature is directly related to the outbreaks of filamentous cyanobacteria blooms, and an increase in temperature may increase the frequency and intensity of filamentous cyanobacteria blooms (Visser et al., 2016). In a large-scale photobioreactor of cyanobacteria, a temperature and light control device is very important to ensure the continuous output of the whole cultivation system. Temperature will not only affect the normal growth and reproduction of cyanobacteria, but also affect the growth of bacteria and other disease organisms in the water, resulting in the deterioration of water quality. Combining the advantages of terrain and automatic control circuit, not only ensures the large-scale and efficient cultivation of cyanobacteria but also minimize the cost of electricity, and improve the commercial application value of cyanobacteria.

8.4.2  Salinity and pH The change in the relative proportion between cyanobacteria and other eukaryotic algae is significantly correlated with the change of salinity. An Observation that the change of algae community in the solar saltern evaporation ponds of Eilat, Israel, Halothece sp. Possess in medium salinity ponds and was weak in low salinity ponds (Řeháková et al., 2009). The salinity composition of marine water is mainly Na+ and Cl−, but the main ions components of freshwater in different areas vary greatly, including HCO3−, SO42−, Mg2+, and Ca2+. Studies on ion channel proteins and the salinity tolerance of sodium and chloride ions have been performed, but there are few studies about the effects of other ions on cyanobacteria (Bachin et al., 2015; Gicheru & Chakrapani, 2018). Cyanobacteria have different adaptations to different salinities. Their tolerance to pH is not as widely adaptable as to salinity and other ecological factors. There are few cyanobacteria tolerant of a low pH and they are found only in acidified lake water (pH < 2) (Steinberg et al., 1998). In contrast, most cyanobacteria can survive in high pH environments and occupy a dominant position in aquatic ecosystems. Spirulina maxima was first discovered in Sosa Texcoco Sosa-Lake in the suburbs of Mexico (Ciferri, 1983). It was determined that the pH value of lake water was very high, which was suitable for the growth of Spirulina maxima (Sivakami, 2004).

2

Light Cycle

Light Quality

Aphanizomenon flos-aquae Synechocystis sp. PCC 6803 Arthrospira platensis

60 μmol/(m2•s)

Nostoc sphaeroides Kutzing Synechococcus sp. Arthrospira platensis

White light; blue light green and blue light Mix of light quality (red: green: blue = 8: 0.5: 1.5) light: dark (8 h: 16 h)

Anabaen aphanizomenoides

light: dark (15 h: 9 h)

light: dark (8 h: 16 h)

Spirulina platensis Nostoc calcicole Desmonostoc salium CCMUFV059 Schizothrix calcicole

light: dark (18 h: 6 h) light: dark (12 h: 12 h) light: dark (16 h: 8 h)

Crocosphaera watsonii

Nostoc flagelliforme Nostoc sp. ATCC 53789 Louisiana Chlorella vulgaris/ Leptolyngbya sp.

Red light Orange light (filter) Red light; Green light

Pink light

Aphanothece microscopica Nägeli Oscillatoria sp. BTCC/A0004

198 μmol/(m2•s)

300-1000 μmol/(m2•s) 115 μmol/(m2•s)

Microcystis aeruginosa

Pseudanabaena galeata

Species

10-100 μmol/(m2•s)

Light Intensity 30-50 μmol/(m •s)

Light conditions

Highest growth rate (0.28 d−1) + Max Photosynthesis (6.54 ± 0•69 mg O2 (mg Chl a)−1 h−1) Maximal cell growth (μ (d−1) = 1.46)

Biomass production with higher carbon and nitrogen cell contents Highest carbohydrate yields (27.84 mg•L−1 day−1) Optimum biomass production Max biomass production (1.60 g•L−1)

Minimum growth rate and Max production in cylindrospermopsin Maximal cell growth Optimum cell growth (μ (d−1) = 0.41) and max EPS (extracellular polymeric substance) production (266.8 mg•L−1) Maximum specific growth rates (0.04 h−1) and carbon fixation rates (109.2 mg• L−1 h−1) Cell growth and pink pigments extracellularly (OsPP) production Improvement of polysaccharide productivity Optimum cell growth rate and production in Cryptophycin-1 Red light: the highest growth rate (0.41 d−1) and biomass productivity (95 mg•L−1 d−1) Green light: the highest Chla content (1649 μg/L) Optimum growth and phycobiliprotein accumulation Increase the accumulation of photosynthetic pigments Highest efficiency of biomass production (161.53 mg• L−1 kW−1 h−1)

Growth rate and Chla-content

Growth rate and Chla-content

Optimum performance

Table 8.3  Optimum light condition of different cyanobacteria.

Zaparoli et al. (2020) Barnett et al. (2017) Alvarenga et al. (2020) Tang and Vincent (2000) Sabour et al. (2009)

Dron et al. (2013)

Ma et al. (2015) Kim et al. (2014) Mao and Guo (2018)

Han et al. (2015) Polyzois et al. (2020) Barnett et al. (2017)

Jacob-Lopes et al. (2008) Karseno et al. (2018)

Ogawa et al. (2018) Trabelsi et al. (2009)

Muhetaer et al. (2020) Muhetaer et al. (2020) Preußel et al. (2009)

References

188  Current Developments in Biotechnology and Bioengineering

Chapter 8 • The application of cyanobacteria in photobioreactors  189

Table 8.4  Adaptation of different cyanobacteria to different temperatures. Temperature gradient

Cyanobacteria

Sampling position

References

High temperature (>30°C)

Chlorogleopsis sp. (SC2) Thermosynechococcus sp. (CL-1) Achnanthidium sp., Aphanocapsa sp., Synechocystis sp., and Leptolyngbya sp. Phormidium sp. Oscillatoria subbrevis, Oscillatori. tenuis, O. limentica, O. angusta, O. articulate, Synechocystis aquatilis, S. Cerdorum Gloeobacter violaceus B-470 Synechococcus sp. B-266 Spirulina platensis (Nordst.) Geitl. B-256 Tolypothrix sp. Kütz B-464 Lyngbya murrayi AntBrack-1 Phormidium autumnale Ant-Brack-2 Phormidium subproboscidea Ant-Brack-3 Oscillatoria priestleyi AntG17 Oscillatoria deflexa Ant-SOS

NA Chin-Lun hot spring (pH 9.3, 62°C), eastern Taiwan Two geothermal hot spring sites: (1) Hazen; (2) Monitor, central Nevada

Ono and Cuello (2007) Hsueh et al. (2007)

Hot springs in Ayas, Turkey Geno hot spring, Bandar Abbas, Iran

Ertuğrul et al. (2008) Heidari et al. (2012)

NA

Maslova et al. (2004)

Medium temperature (at around 20°C)

Low temperature (10 g L−1 DCW) higher macronutrient concentration is recommended. Therefore, optimization of production medium specific for

218  Current Developments in Biotechnology and Bioengineering

species to be cultured is recommended. Many planktonic species like Chetoceros sp. and Skeletonema sp. are known to be dominant in low nutrient waters compared to benthic diatoms like Phaeodactylum tricornutum and Cyclotella sp. which are known to inhabit inter tidal zones with high nutrients (Barnett et al., 2014; Edwards et al., 2013). This difference in natural environment equips diatoms to strengthen key metabolic processes which enable their growth in high nutrient mediums essential for commercial scale culturing. In commercial scale cultivation systems, use of cheap inorganic salts is recommended to minimize product cost. Use of commercial agriculture fertilizers for nitrogen and phosphorus are increasingly used for this purpose but not algae can utilize the commercial formulations efficiently (Popovich et al., 2020). Diatom’s urea cycle is quite distinct in terms of its role compared to mammals. Diatom urea cycle not only recycles and distributes nitrogen but also carbon and it is known to play a key role in their response to nutrient stress and in utilization of varied N sources (Allen et  al., 2011). Presence of complete urea cycle enables diatom to be grown using urea containing commercial formulations. In diatoms nutrient composition and nutrient source of the medium not only influences growth but also value-added products like EPA and fucoxanthin. Growing two Cylindrotheca strains on nitrate, urea and ammonia resulted in distinct changes in lipid and PUFA content and preferred N source for optimum growth (Suman et al., 2012). Similar studies using industrial strain of Phaeodactylum (UTEX 640) has shown that nitrate and urea are preferred N sources for its growth. In flat panel airlift PBR Phaeodactylum doubled its biomass productivity with urea compared to nitrate (Meiser et al., 2004). Silicate is one of the major nutrients which directly influences biomass productivity due to silica frustule formation in diatoms. Silica starvation can lead to downregulation of carbon storage and metabolism related genes resulting in reduced carbon storage as chrysolaminarin. It is needed in same molar ratio as nitrogen for sustained diatom growth. Despite its significance, it is the least studied medium component in diatoms due to extensive research impetuous on using model diatom Phaeodactylum tricornutum which is less silicified diatom and does not build fully silicified frustules (Sapriel et al., 2009). From mass balance studies, to produce 1 g of dry cell weight diatoms need approx. 75 mg of SiO2, in Cylotella sp. a specific yield of 1.34 g DCW was obtained with 1 g of Na2SiO35H2O (Pahl et al., 2011). But many of the media formulations recommend only 35 mg L−1 of Na2SiO35H2O so most diatom mediums are silica limited and act as sustenance mediums rather than production mediums. Other major constraint of using silica in high concentration is its solubility, at between pH 7–9 maximum silica solubility in water is 1–2 mM. Adding silica above 250 mg L−1 to medium will result in formation of precipitates which cannot be effectively utilized by diatoms leading to decreased growth. So, to attain highdensity growth fed batch mode with silica addition is recommended. Other key component for diatom growth is iron as it plays a key role as building block in photosynthetic pigments like chlorophyll c and fucoxanthin which perform similar role of heme in human blood. Iron starvation can lead to autolysis of cells in T. pseudonana (Yang et al., 2020). So, providing iron it in desired amounts is crucial due to varied light dynamics prevalent in tubular bioreactors. Diatom media recipes has been studied and updated extensively but formulation of production media and fed batch mode for complex substates like Si needs more impetuous for their commercial-scale cultivation.

Chapter 9 • Cultivation of diatoms in photobioreactors  219

9.5.4  Trophic mode To achieve higher biomass productivity selection of right cultivation mode is an important factor. Diatom algae due to their evolutionary advantages had acquired some unique genetic and metabolic mechanisms which enable them to grow in all three trophic modes which are photoautotrophic, mixotrophic and heterotrophic (Villanova & Spetea, 2021). During heterotopic mode organic carbon assimilation is performed through oxidative phosphorylation in presence of oxygen. In mixotrophic mode microalgae can utilize both inorganic and organic carbon source’s simultaneously through aerobic respiration and photosynthesis. Majority of benthic diatoms from Nitzschia sp. can grow in both phototrophy and mixotrophy using varied organic carbon sources like glycerol, acetate, and glucose (Marella et al., 2021). But compared to photosynthetic mode mixotrophic and heterotrophic modes has advantages like higher biomass productivity, higher lipid content, lower dependence on light optima, simpler bioreactor design and operation, potential use of excess carbon from wastewater. Heterotrophic diatoms like Nitzschia alba are successfully cultured in traditional stirred tank bioreactors in high cell densities (>10 g L−1 d−1) (Barclay et al., 1994). Use of fermenters instead of PBRs is easier to scale-up and maintain due to smaller surface to volume ratio and requirements to control light availability. Due to higher cell density downstream processing steps like harvesting becomes cost effective compared to low density phototrophic cultures. But major draw backs of using heterotrophic mode is availability of diatom strains which can grow in absence of light, requirement of organic carbon source and oxygen which increases the production costs, so use of fermenters are more preferred for high value products like EPA and DHA which can offset the higher input costs with higher product cost. Use of closed PBRs is ideally suited for mixotrophic cultivation. During mixotrophy cells utilize both inorganic carbon by photosynthesis and organic carbon by aerobic respiration leading to higher productivity compared to photo-autotrophy. In a recent study on Cylindrotheca sp., comparative analysis on mixotrophy using glycerol with autotrophy resulted in four times higher cell density under mixotrophic mode (Marella et  al., 2021). In Pheaodactylum use of glycerol and urea resulted in 42.13 mg L−1 d−1 and 1.52 mg L−1 d−1 EPA and biomass productivity respectively which is considerably higher than phototropic control (Wang et  al., 2019a). The major advantages of using mixotrophic mode for diatoms are availability of a greater number of strains which can utilize organic carbon in presence of light, higher growth rate and biomass productivity, extended exponential growth phase, reduced dark respiration biomass loss, and reduced photooxidative stress. Existing tubular and flat panel PBRs can be employed for mixotrophic growth instead of major design modifications as in the case of fermenters for heterotrophic species. In diatoms, organic carbon supplementation can modify cell response to light by increasing light saturation constant, photosynthetic rate, dark respiration rate and in minimizing dark biomass loss along with increase in lipid and fucoxanthin content (Villanova et al., 2017). In N. laevis, use of glucose and a mixture of organic nitrogen sources like tryptone and yeast extract resulted in eight-fold increase in EPA productivity compared to autotrophic mode (Alipanah et al., 2018). Organic carbon supplementation to Phaeodactylum cultures has resulted in upregulation of key enzymes related to PUFA biosynthesis resulting in higher EPA productivity (Wang

220  Current Developments in Biotechnology and Bioengineering

et  al., 2019b). Although glucose is preferred carbon substrate for heterotrophic cultivation of diatoms its use for mixotrophic cultivation resulted in mixed results which indicates many diatoms need light to perform enzymatic reactions related to glucose metabolism. Despite numerous advantages with mixotrophic and heterotrophic cultivation further research focus is needed on looking for novel diatom strains which can utilize multiple cheap carbon sources like lignocellulose materials and food waste hydrolysates coupled with design optimization of existing PBRs to switch between trophic modes.

9.6  Conclusions and perspectives Current commercial scale cultivation practices for diatoms are impeded by factors like PBR design, scale up process, operation control, strain selection and culture conditions. In spite the availability of vast data regarding different cultivation systems one agrees that no one system is considered superior to another. So, there is an urgent need to explore possibilities to increase diatom biomass and biomolecule productivity to make them more attractive in high-value biomolecule value chain which is least explored compared by live feed and bioenergy sectors. Therefore, future development in diatom biorefinery needs viable alternatives to reduce production cost, to develop cost effective PBRs and to make use of wastewater nutrients to make the cultivation practices environmentally sustainable. Major technical challenges encountered while using PBRs include inability to provide uniform illumination, existence of dark high ratio of dark regions inside the tubes, biofouling of reactor surfaces, high S/V ratio, high land footprint and optimization of mixing and gaseous. Some of these challenges can be addressed by optimizing PBR designs like reducing the tube diameter there by reducing light path which can reduce dark regions, illumination of reactor surfaces from both sides to improve uniform illumination, using shorter and intermittent mixing regimes to reduce gas buildup. Operational challenges include high capital cost and limitations in scale up. Labor and depreciation cost are known to significantly contribute to overall cost escalation in tubular PBRs. In spite of these challenges, use of large-scale cultivation systems using PBRs are successfully employed but unfortunately majority of these systems employ green algae such as Chlorella and Heamatococcus sp. The main reason for this can be attributed to high CAPEX involved in these systems which warrants for their use to produce high-value products. Phaeodactylum tricornutum is the only species which is commercially cultivated in outdoor PBRs for fucoxanthin production whereas Nitzschia alba and Nitzschia laevis are commercially produced in heterotrophic mode using fermenters for EPA production. Use of closed PBRs is ideal to maintain axenic monocultures with minimum bacterial contamination which is preferred for production of biomolecules for human consumption. To address technical barriers regarding growth, photosynthetic efficiency, and metabolite productivity in large–scale PBR systems optimization of photobioreactor design in sync with physiology of species to be cultures is needed. Present available gene pool is limited especially with diatoms which are capable to perform mixotrophic growth using varied carbon sources. So, there is an urgent need to identify, isolate and characterize novel diatom strains which can achieve higher productivity in PBR systems. For successful outdoor culturing of diatoms during

Chapter 9 • Cultivation of diatoms in photobioreactors  221

whole year controlling medium temperature in PBRs as close to optimum for growth is necessary especially in temperate climatic zones. But temperature control is scale up systems needs high energy input which escalates the product cost. So instead of temperature control isolation of strains which can be grown under wide temperature gradient is needed. With the availability of whole genome sequence data for model diatoms such as Phaeodactylum tricornutum, Thalassiosira sp., etc. possibility and technical feasibility to perform genetic modification to improve strain traits suitable for photobioreactor growth is feasible and more research impetus in this area is warranted. Use of microalgae feedstock for biofuel production has been the primary objective which fueled research impetuous into large-scale algae culturing but even after two decades of extensive research, techno-economic constraints like energy efficient harvesting systems and efficient use of wastewater nutrients for algae growth remain unsolved. High density culturing of algae using PBR systems can provide a partial solution by decreasing the harvesting cost but research on design and optimization of systems to grow microalgae using wastewater is needed. Life cycle analysis is critical step in gauging the potential of microalgal biomass for sustainable microalgal biorefinery and in evaluating its economic feasibility at present many of the existing mass scale production systems lack this critical data.

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Xia, S., Gao, B., Fu, J., Xiong, J., Zhang, C., 2018. Production of fucoxanthin, chrysolaminarin, and eicosapentaenoic acid by Odontella aurita under different nitrogen supply regimes. Journal of Bioscience and Bioengineering 126, 723–729. http://doi.org/10.1016/j.jbiosc.2018.06.002. Xia, S., Wang, K., Wan, L., Li, A., Hu, Q., Zhang, C., 2013. Production, characterization, and antioxidant activity of fucoxanthin from the marine diatom Odontella aurita. Marine Drugs 11, 2667–2681. Xiang, X., Ozkan, A., Chiriboga, O., Chotyakul, N., Kelly, C., 2017. Techno-economic analysis of glucosamine and lipid production from marine diatom Cyclotella sp. Bioresource Technology 244, 1480–1488. http://doi. org/10.1016/J.BIORTECH.2017.05.079. Yang, R., Wei, D., Xie, J., 2020. Diatoms as cell factories for high-value products: Chrysolaminarin, eicosapentaenoic acid, and fucoxanthin. Critical Reviews in Biotechnology 40, 993–1009. http://doi.org/10.1080/073885 51.2020.1805402. Zeriouh, O., Marco-Rocamora, A., Reinoso-Moreno, J.V., López-Rosales, L., García-Camacho, F., Molina-Grima, E., 2019. New insights into developing antibiofouling surfaces for industrial photobioreactors. Biotechnology and Bioengineering 116, 2212–2222. http://doi.org/10.1002/BIT.27013. Zheng, N., Shimizu, Y., 1997. The isolation and structure of bacillariolide III, an extracellularmetabolite of the diatom, Pseudo-nitzschia multiseries. Chemical Communications, 399–400. http://doi.org/10.1039/ A608369B. Zheng, Y., Quinn, A.H., Sriram, G., 2013. Experimental evidence and isotopomer analysis of mixotrophic glucose metabolism in the marine diatom Phaeodactylum tricornutum. Microbial Cell Factories 12, 1–17. http:// doi.org/10.1186/1475-2859-12-109.

10 Photobioreactor systems for production of astaxanthin from microalgae Young Joon Sung, Jaemin Joun, Byung Sun Yu, Sang Jun Sim DEPARTME NT O F CHEM I CAL AND BI O L O G I C A L E N G I N E E R I N G , K O R E A U N I V E R S I T Y, S E O U L , REPUBLIC OF KOREA

10.1 Introduction Astaxanthin has a long chain structure, and two ionone rings that include a hydroxyl group and a carbonyl group, which are oxygenated groups, are bonded at both ends (Lenzer et  al., 2009). These structures and functional groups can contribute to astaxanthin having a high antioxidant capacity compared to other carotenoids, including β-carotene, lutein, and zeaxanthin (Kobayashi & Sakamoto, 1999). In addition, astaxanthin can inhibit lipid peroxidation due to its scavenging of single oxygen and free radicals (Yuan et al., 2011). Owing to these properties, astaxanthin is able to confer various biological protective functions, such as an anti-inflammatory effect, a protective role against ultraviolet (UV) irradiation, and immunomodulating actions, to a variety of living organisms, including humans (Jyonouchi et al., 1991; Kim & Kim, 2018; Li et  al., 2020). Accordingly, astaxanthin has been reported to have clinical effects on various human diseases, including cancer, diabetes, cardiovascular disorders, and Alzheimer's disease (Hussein et al., 2006; Palozza et al., 2009; Pashkow et al., 2008; Xu et al., 2015). It has thus been widely applied to human foods as well as pharmaceutical, nutraceutical, and cosmetic fields and has been produced as various value-added products, leading to the rapid growth of the related markets (Cuellar‐Bermudez et al., 2015; Lim et al., 2018; Tominaga et al., 2012; Valenti et al., 2020). As the demand for astaxanthin has rapidly increased, synthetic astaxanthin has been produced via the Wittig reaction of C15-triaryl phosphonium salt and C10-dialdehyde (Widmer et  al., 1981). More than 95% of the astaxanthin produced in recent years was artificially synthesized (Koller et  al., 2014). However, compared with naturally synthesized astaxanthin, synthetic astaxanthin has 50 times and 20 times lower quenching of singlet oxygen and neutralization of free radicals, respectively, so its antioxidant effect is significantly lowered (Shah et al., 2016). Natural astaxanthin thus satisfies market needs and has a high market value compared to synthetic equivalent (Lorenz & Cysewski, 2000). Current Developments in Biotechnology and Bioengineering. DOI: https://doi.org/10.1016/B978-0-323-99911-3.00005-1 Copyright © 2023 Elsevier Inc. All rights reserved.

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Natural astaxanthin can be produced by a variety of organisms, from microalgae, yeast, and bacteria at the low levels of the food chain to relatively high-level predators including krill, shrimp, salmon, and trout (Ambati et al., 2014; Higuera-Ciapara et al., 2006; Parisenti et al., 2011; Yang et al., 2013). Unlike aquatic animals, which produce astaxanthin by accumulating pigments, astaxanthin-rich microalgae are the efficient bio-platform for the economical production of astaxanthin because they are the basis of the food chain and are capable of direct astaxanthin biosynthesis (Davies, 1985). In particular, Haematococcus pluvialis and Chlorella zofingiensis are the representative microalgae species capable of astaxanthin production (Kang et al., 2005). H. pluvialis is the most widely known astaxanthin producer and can obtain high concentrations of astaxanthin. However, these microalgae still have high production costs due to physiological and technical limitations such as relatively low cell growth rates, susceptibility to contamination, and multi-stage process derived from differences in culture conditions that are significantly different between the green and red stages (Guerin et  al., 2003; Oslan et al., 2021; Shah et al., 2016; Zhang & Lee, 1999). On the other hand, fast-growing C. zofingiensis with low astaxanthin content and ease of cultivation has been studied for commercial application based on its potential as a substitute for H. pluvialis (Chen et al., 2017; Orosa et al., 2001; Pelah et al., 2004). Moreover, microalgae including the aforementioned species can be cultivated under heterotrophic, autotrophic, and mixotrophic culture conditions (Kobayashi et al., 1992; Liu et al., 2011). Nutrient sources, energy sources, and the environmental conditions required for culturing microalgae differ depending on the cultivation mode. In addition, since microalgae are grown in aquaculture, a culture space capable of confining the culture broth is essential. Microalgal cultivation systems are roughly classified into open and closed modes. The open system, represented by the raceway pond, was initially attempted for large-scale production of astaxanthin from microalgae based on its easy construction, low operating cost, simplified process, and cooling through direct contact with air or seawater (Onorato & Rösch, 2020; Shin et al., 2018; Zhang et al., 2009). However, because the open system is easily exposed to contaminants, it was utilized in a process requiring a relatively short incubation period or in culturing microalgae that require peculiar environmental conditions like high salinity, where contaminants are difficult to grow (Aratboni et al., 2019; Jorquera et al., 2010; Olaizola & Huntley, 2003). Nevertheless, from the viewpoint of high-value bio-compound production for humans, the control of contamination and strict culture conditions are essential to produce high-quality astaxanthin (Acién et al., 2017; Lu et al., 2021). Astaxanthin, which is expensive and requires a long accumulation time, has a great loss if culture control fails. Therefore, for economic production, a closed system was introduced into commercial microalgae culture (Olaizola, 2000). The closed system represented by the photobioreactor (PBR) has the following advantages compared to the open system: (1) ease of monoculture with minimal exposure to contaminants; (2) reduced CO2 loss; (3) controllable culture conditions such as light, pH, temperature, and CO2 supply; and (4) prevention of water evaporation (Dogaris et al., 2015). Based on these advantages, closed systems can be more suitable for astaxanthin, which is difficult to produce among various microalgae-derived products. Hence, various PBR systems for the efficient production of astaxanthin have been reported

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(Choi et  al., 2018; Hong et  al., 2019). Nevertheless, insufficient productivity, PBR installation cost, and operating cost are pointed out as the main factors hindering economical astaxanthin production (Pérez-López et al., 2014; Zittelli et al., 2013). Herein, this chapter presents various approaches in terms of PBR systems for the economical production of astaxanthin from microalgae. It details PBR characteristics according to the structure and compares astaxanthin content and productivity from microalgae using various PBR systems. It then reveals the characteristics of the PBR system that could contribute to the efficient production of astaxanthin. Finally, this chapter compares the pros and cons of various PBR systems developed so far and presents the perspective of the future PBR system design.

10.2  Photobioreactor (PBR) systems In the design of the PBR systems for the autotrophic culture of microalgae, an efficient supply of light and CO2 are essential for photosynthesis and should thus be considered, unlike the fermenter that is used for organic carbon sources. In addition, microalgal cells grown in an aquatic environment require a continuous external fluid flow to prevent sinking. Therefore, a PBR design that facilitates an efficient supply of nutrients while minimizing cell damage and stress is required. Additionally, the PBR requires a baffle, motor, gas line, and reactor holder to supply a continuous fluid flow. PBR design elements that directly improve cell productivity include light penetration, mixing, CO2 transfer efficiency, and areal productivity (PBR diameter and PBR arrangement considering sunlight). With a focus on the microalgae process, other productivity-enhancing approaches include reduced installation and operating costs, which are determined by PBR materials, accessories, and ease of operation. PBRs that can be classified into five types according to the type of reactor and the gas exchange method: vertical tubular PBR (Bubble column PBR and airlift PBR), horizontal tubular PBR, stirred tank PBR, rotating floating PBR, and flat panel airlift PBR (Singh & Sharma, 2012; Yen et al., 2019). There are also hybrid culture methods that use various PBRs in actual large-scale cultures. In this chapter, the characteristics of each PBR and the PBR systems that have been developed for the economically feasible production of CO2-derived astaxanthin from microalgae will be described.

10.2.1  Vertical tubular PBR Vertical tubular PBR consists of a container perpendicular to the light needed for photosynthesis and a sparger at the bottom of the reactor that converts air from the outside into bubble form. Through the momentum obtained by air bubbles, the culture medium is stirred and CO2 is transferred, so no further physical stirring is required. The advantages of vertical tubular PBR are as follows: circulation occurs without moving parts, which reduces the possibility of contamination; it can avoid cell damage by mechanical pumping; and due to gas exchange by pumps, it can remove oxygen produced by photosynthesis (Molina et al., 2001). Vertical tubular PBR could be classified as bubble column and airlift PBR depending on the flow of fluid (Singh & Sharma, 2012).

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10.2.1.1  Bubble column PBR The bubble column reactor is a culture widely used in chemical and petrochemical industries as well as microalgae culture and has the advantages of excellent heat transfer and material transfer capability and low maintenance costs (Kantarci et al., 2005). Because light comes from the outside, when microalgae grow, a dark zone is created in the center of the column that cannot be photosynthesized. Therefore, the rate of gas flow that could stir the culture media is important for efficient photosynthesis and growth of the culture. The bubble column PBR is made of a transparent film for the column and a stone sparger, which can achieve the purpose of effective microalgae culture (Choi et al., 2018; Hong et al., 2019; Yoo et  al., 2013). Considering the stable supply and economic feasibility of CO2, flue gas, which is made up of 3.5% CO2-enriched air, that was emitted from an LNG-fired power plant was used as an inorganic carbon source of microalgae. In this study, the bubble column was selected as the reactor for large-scale cultivation because it is easy to scale-up and allows a large volume of microalgae to grow in a small space. In the bubble column system, a V-shaped bottom of the PBR was developed to overcome the phenomenon of cells piling up in the dead zone at the bottom of the reactor. As a material for the reactor, the use of transparent film instead of reinforced glass or acrylic, which are used for most bubble columns, was made for the ease of scaling up. Thin-film column PBR could not only dramatically reduce maintenance costs and an initial investment cost but could handle CO2 generated from large-scale industrial plants (coal-fired power plants, LNG-fired power plants) through the establishment of a large-scale microalgae culture system (Kaewpintong et  al., 2007). Choi et al. (2018) reported that the volume of the reactor was increased by 354% compared to the previous reactor without biomass loss after optimizing the H/D ratio to 6:1. The biomass and astaxanthin productivity of H. pluvialis NIES-144 were achieved as 0.052 g L−1 d−1 and 1.48 mg L−1 d−1, respectively, like with conventional reactors (Choi et al., 2018). Thin-film column PBR was scaled up to 100 L and achieved biomass growth and astaxanthin growth at 0.127 g L−1 d−1 and 5.47 mg L−1 d−1, respectively using H. pluvialis M160, derived from H. pluvialis NIES-144 (Hong et al., 2019) (Fig. 10.1). Kim et al. (2016) developed split-column PBR (SC-PBR) to control the intensity of light to increase the productivity of astaxanthin (Fig. 10.2). The SC-PBR is composed of two linked bubble columns of different sizes. A large-sized column maximizes the cell concentration without light supply, and a smaller column provides strong light intensity to efficiently provide light to all cells in the column without mutual shading due to increased cell density. Unlike conventional type bubble column PBRs, microalgae enter the smaller column of SC-PBR, causing relatively high light stress. In this respect, a more efficient induction process in SC-PBR can improve astaxanthin productivity. After the cultivation of the H. lacustris, the astaxanthin productivity of SC-PBR under high-light intensity (815 µE m−2 s−1) and 5% of CO2 with air was 5.35 mg L−1 d−1, 28% higher than control. However, the height/diameter ratio of the column should be optimized for the enhancement of astaxanthin productivity using SC-PBR. In addition, it was also difficult to adapt this PBR to large-scale production.

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FIG. 10.1  Structure and mimetic diagrams of polymeric thin-film PBR, various column diameter (D: 10, 15, and 20 cm) for optimizing height/diameter (H/D) ratio, and production of astaxanthin with optimized PBRs in large-scale (reprinted from Choi, Y. Y. et al. (2018). Improvement in modular scalability of polymeric thin-film photobioreactor for autotrophic culturing of Haematococcus pluvialis using industrial flue gas. Bioresource Technology, 249, 519–526, with permission from Elsevier).

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(B)

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FIG. 10.2  Schematic diagram of (A) bubble column PBR (B) and split-column PBR. Photographs of (C) bubble column PBR and (D) split-column PBR cultivating Haematoccus lacustris (reprinted from Kim et al. (2016). Enhancing photon utilization efficiency for astaxanthin production from Haematococcus lacustris using a splitcolumn photobioreactor. Journal of Microbiology and Biotechnology, 26(7), 1285–1289, with permission from The Korean Society for Microbiology).

10.2.1.2  Airlift PBR The airlift PBR, which is common in traditional bioreactors, consists of two interconnected zones. The interconnected areas are divided into a riser that receives direct gas supply and a downcomer that does not receive gas supply. The riser plays a similar role as the bubble column, where the gas and culture media rise upwards. In the downcomer, the gas is not supplied, so the culture media moves downward. The actions of the riser and downcomer result in the circulation of the media, which allows the microalgae to utilize the flashing-light effect through the circulation of light and dark zones. Therefore, the advantage of airlift PBR is that it facilitates the circulation of growth media using compressed gases while enabling the exchange of substances between gases and media. The airlift PBR is also divided into internal loop and external loop depending on the reactor’s structure (Singh & Sharma, 2012; Yen et al., 2019). H. pluvialis has been cultivated in diverse types of reactors like bubble column reactors and stirred tank and floating PBR. Because H. pluvialis takes a long time to reach the maximum astaxanthin accumulation and is sensitive to shear, simple items such as spargers or pneumatically stirred bioreactors with low shear force are preferred over mechanically agitated reactors. In aerial systems such as bubble column reactors and airlift PBR, low shear stress and low energy consumption are possible through mass transfer and stirring generated by aeration of gas. Kaewpintong et al. (2007) developed an internal loop airlift bioreactor with an inner column that consists of a draft tube and bubble column to achieve high astaxanthin productivity (Fig. 10.3). Unlike the bubble column, the airlift PBR prevents cell clumping and helps cell growth by making culture media flow in a certain direction. The draft tube in the airlift PBR

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(A)

(B)

FIG. 10.3  Schematic diagram of (A) internal loop airlift PBR and (B) bubble column (reprinted from Kaewpintong, K. et al. (2007). Photoautotrophic high-density cultivation of vegetative cells of Haematococcus pluvialis in airlift bioreactor. Bioresource Technology, 98, 288–295, with permission from Elsevier).

provided optimal conditions for cell growth because it was exposed to light in a uniform flow along the length of the reactor and most cells circulated along the axial direction of the reactor. However, this airlift bioreactor also had limitations in increasing the height and diameter, so it was difficult to scale up. Outdoor cultivation was conducted in vertical external-loop airlift PBRs (García-Malea et al., 2006). In this experiment, airlift PBR showed higher biomass productivity because it can receive greater irradiance effect when using smaller diameter tubes than bubble columns. In the irradiance effect model, irradiance of light and dilution rate was considered and applied by simulating in outdoor PBR. In this system, astaxanthin productivity was 4.4 mg L−1 day−1. Aslanbay Guler et al. conducted the scale-up of the reactor from 2 L to 8 L. Computational fluid dynamics (CFD) simulation was applied to identify the circulation of substances and patterns of flow, which were important in the airlift reactor (Aslanbay Guler et al., 2020). The productivity of astaxanthin was 7.82 mg L−1 day−1, and CFD simulation confirmed that stirring in the downcomer was not conducted efficiently by turbulence kinetic energy and that the arrangement of the column and diameter of sparger needed to be adjusted to expeditious agitation. H. pluvialis culture was composed of two stages: a growth stage for cell growth and an induction stage for astaxanthin production. Because the culture conditions required in each

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stage (light intensity, nitrogen concentration, etc.) are quite different, culturing H. pluvialis requires a long cultivation period and high production costs to maintain optimized environment conditions. To construct the conventional two-stage culture system within one reactor, Suh et al. (2006) developed double-layered PBR (DL-PBR), a type of internal-loop airlift PBR, to produce astaxanthin from H. pluvialis. In the cylindrical double-section PBR, the green stage of growth was performed in the inner core section and astaxanthin amassed in the outer cover section, which was illuminated by excessive irradiation to enhance the accumulation of astaxanthin in the cells (Fig. 10.4). The supplied high-light energy was significantly reduced as it passed through the outer cover section, and the reduced light was supplied to the inner core section and utilized as the minimum light for cell growth. In the outer cover section, astaxanthin accumulation was conducted under nitrate starvation and high-light condition, resulting in an increase of astaxanthin productivity (16.2 mg L−1 day−1). In contrast, the growth of green cells was achieved through a relatively low intensity of light and a sufficient supply of nitrogen sources. However, DL-PBR has limitations in that it is expensive to install the equipment and difficult to maintain and repair it to perform mass production through outdoor culture, so it can be used only on a lab scale.

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FIG. 10.4  (A) Photograph of double-layered (DL) PBR. (B) Side view and (C) top view of DL-PBR: (1) inner-core section, (2) outer-cover section, and (3) fluorescent lamp, (i) inoculation port, (ii) sampling port, (iii) medium feeding port, (iv) gas outlet port, and (v) gas inlet port (reprinted from Suh, I. S. et al. (2006). A novel double-layered photobioreactor for simultaneous Haematococcus pluvialis cell growth and astaxanthin accumulation. Bioresource Technology, 125, 540–546, with permission from Elsevier).

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10.2.2  Horizontal tubular PBR The horizontal tubular PBR, like other tubular PBR, consists of pipes using transparent polyvinylchloride or polypropylene acrylic. It is also characterized by its small diameter of pipes, which increase light permeability. Horizontal tubular PBR has the advantage that CO2 dissolves in the culture because the air has a longer residual time than that of vertical tubular PBR. However, the disadvantage is that it requires 40 times more power consumption than bubble column and flat-plate reactors because the flow rate of the culture media should be maintained at 20–50 ms−1 (Singh & Sharma, 2012). López et al. (2006) showed that tubular PBR is useful for H. pluvialis culture because it can utilize light more efficiently compared to bubble column PBR. The biomass productivity of H. pluvialis with tubular PBR was 0.41 g L−1 d−1, which is 6.83 times higher than that of bubble column PBR. A relatively thin tube in tubular PBR enabled efficient astaxanthin accumulation. In this condition, the size of H. pluvialis could grow from 20 μm to 35 μm. However, since the diameter of the reactor cannot be increased beyond a certain level for efficient photosynthesis, attempting to increase the length of the horizontal tubular PBR raises the installation cost, which reduces the economic feasibility of the PBR (Fig. 10.5). In addition, since the cost of maintaining and repairing the tubular PBR is also significant, its scale-up has limitations.

FIG. 10.5  Schematic diagrams of airlift tubular photobioreactor and bubble column for outdoor cultivation of Haematococcus pluvialis (reprinted from López, M. C. G.-M. et al. (2006). Comparative analysis of the outdoor culture of Haematococcus pluvialis in tubular and bubble column photobioreactors. Journal of Biotechnology, 123, 329–342, with permission from Elsevier).

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10.2.3  Stirred tank PBR Tubular PBR or flat-plate PBRs can decrease the possibility of contamination and enhance the control capacity for growth parameters and astaxanthin production. Because of their low surface-to-volume ratio, the scale-up of these PBRs led to decreased light supply, the dissolution of CO2, and lower biomass productivity compared to that in lab-scale experiments. Meanwhile, when stirred tank PBRs were used, heat and mass transfer were enhanced and the degree of dispersion of light and mixing quality were improved, hence stirred tank PBR showed much higher biomass and astaxanthin production in lab-scale experiments. Total carotenoid productivity was measured to be 0.2343 mg L−1 day−1 in 10 L stirred tank PBRs (Deniz, 2020). However, there were important limitations, like high-energy requirements, foaming, and shear stress that should be settled before applying this PBR to the large-scale production of microalgae. Among the disadvantages mentioned above, to reduce cell damage and shear stress from Rushton turbine impeller used in stirring, Guler et al. (2020) used computational fluid dynamics (CFD) to analyze hydrodynamic parameters and the behavior of fluids. Based on the analyzed data, the biomass productivity in stirred tank PBR was increased by reducing the gap between two impellers, changing the type of impeller, and optimizing the baffle structure (Fig. 10.6).

10.2.4  Energy-free rotating floating PBR (RF-PBR) As the highest astaxanthin sources among the microalgae species, H. pluvialis and C. zofingiensis are currently utilized for astaxanthin production. Although H. pluvialis could produce a high content of astaxanthin, it had limitations in that the cell density was low, the cultivation

FIG. 10.6  Schematic diagram of stirred tank PBR (reprinted from Aslanbay Guler, B. et al. (2020). Computational fluid dynamics modelling of stirred tank photobioreactor for Haematococcus pluvialis production: Hydrodynamics and mixing conditions. Algal Research, 47, 101854, with permission from Elsevier).

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(A)

(B)

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(D)

FIG. 10.7  (A) 3D Schematic diagram of rotating floating PBR. (B) Sectional drawing of rotating floating PBR. (C) A picture from the side of rotating floating-PBR filled with C. zofingiensis culture. (D) C. zofingiensis-culture-filled rotating floatingPBR in a raceway pond (reprinted from Zhang, Z. et al. (2017). Two-step cultivation for production of astaxanthin in Chlorella zofingiensis using a patented energy-free rotating floating photobioreactor (RFP). Bioresource Technology, 224, 515–522, with permission from Elsevier).

period was long, and the possibility of contamination was high. C. zofingiensis has also been used recently to replace these problems. The RF-PBR reactor was developed to efficiently culture C. zofingiensis (Zhang et al., 2017). As shown in Fig 10.7, RF-PBR is water-based floating PBR. Stirring in the reactor is done through the flow of culture solution and requires no external power, so the RF-PBR could be applied to mass cultivation. Furthermore, the RF-PBR could also maintain its temperature without consuming energy due to its naturally hydraulic powers, unlike conventional reactors that require electrical energy to sustain their temperatures. Electrical energy for maintaining the culture temperature in PBR was substituted with heat transfer between RF-PBR and water. Because the contact between RF-PBR barrels and water was frequent, the rotary movement of RF-PBR may advance the heat exchange between the cells in the RF-PBR and water, thereby maintaining a more appropriate environment for C. zofingiensis growth. Using the RF-PBR and two-step cultivation, an astaxanthin concentration of 5.26 mg L−1 day−1 was acquired, which is higher than other C. zofingiensis result values that have been reported thus far. However, when the midsummer temperature rises above the optimum culture temperature condition, it is difficult to control the temperature, and the

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RF-PBR is vulnerable to natural occurrences such as rain and wind. In addition, as the culture is scaled up, the required area also considerably increases.

10.2.5  Flat panel airlift PBRs (FP-ALPBR) Although there have been many studies on H. pluvialis culture on a lab scale, studies on the large-scale cultivation of H. pluvialis are extremely rare so far. In general, astaxanthin productivity is quite often inversely proportional to the size of the reactor, and it is difficult to control all conditions in the outdoor environment that are required for large-scale cultivation. Therefore, FP-ALPBR was developed by Issarapayup et al. (2009) to scale up the ALPBR while maintaining its hydrodynamic properties. The reactor combines the airlift and the flat plate to make up a rectangular column (Fig. 10.8). Because the length of FP-ALPBR can be easily adjusted, various volumetric reactors could be manufactured. In this paper, considering both the gas flow rate and ratio of the downcomer and riser, the scale-up of FP-ALPBR was achieved to 90 L. In economic terms, the reactor could be used for up to three years, assuming that it was driven for 300 days a year, which could compensate for its high upkeep. However, the scale-up range is still too small to keep up with the global astaxanthin scale market, and the installation cost is high. Additionally, the efficiency is lowered in terms of reactor volume per unit area.

10.2.6  Hybrid usage of PBR Hybrid-type reactors are widely used to maximize the advantages of each PBR and to compensate for their disadvantages. In the case of H. pluvialis cultivation, it is more advantageous to use a hybrid-type reactor because the environmental conditions optimized in the green stage, where cell growth is robust, and the red stage, where the accumulation of astaxanthin is performed, are different. Specifically, in the green stage, microalgae will ideally grow in a general environment that avoids strong light intensity conditions. In contrast, the red stage requires stress such as strong light intensity, high temperature, nitrogen source deficiency, and the addition of metal ions to accumulate astaxanthin. In a study by Olaizola (2000), the green stage of H. pluvialis was cultured using a type of horizontal tubular PBR called the Aquasearch Growth Module (AGM). In the red stage, research was conducted using open pond to accumulate astaxanthin. Aflaloet al. (2007) suggest using a 500 L flat vertical panel–type PBR for the green stage and a 2000 L horizonal tubular type PBR for the red stage for the outdoor cultivation of H. pluvialis Flotow 1844 em. Wille K-0084. Through this incubation method, astaxanthin productivity was increased to 10.1 mg L−1 day−1. The examples of reactors mentioned so far that could be used for large-scale microalgae culture using CO2 and their respective productivities of astaxanthin are summarized in Table 10.1.

10.3  Conclusions and perspectives PBR systems show high astaxanthin productivity through long-term culturing of microalgae with suppressed contamination based on the advantages of the closed system. Considering mass transfer and flow dynamics, the PBR design enable enhanced mixing and efficient supply

Chapter 10 • Photobioreactor systems for production of astaxanthin from microalgae  241

FIG. 10.8  Schematic diagram of FP-ALPBR: (1) column of PBR, (2) vertical plate, (3) spargers, column height (HR), column length (LR), column width (WR), plate height (Hr), and bottom clearance (HB) (reprinted from Issarapayup, K. et al. (2009). Flat panel airlift photobioreactors for cultivation of vegetative cells of microalga Haematococcus pluvialis. Journal of Biotechnology, 142, 227–232, with permission from Elsevier).

of gaseous CO2 and nutrient sources. In particular, an elongated PBR structure for a long residence time of gaseous CO2 with gas bubbling can efficiently transfer gaseous CO2 to the cells suspended in liquid culture. In addition, complex PBR forms have been reported for compact structure considering the culture area. A more energy-intensive power source is required to reduce the fluid resistance due to the complex structure. In addition to the structural design of the reactor, it is possible to maximize the productivity by introducing a stirrer operated by an external power source. However, forced fluid circulation using energy has a limitation in that the operating cost of the entire process increases rapidly with scale-up. In terms of carbon footprint, the enormous energy input can offset CO2 reduction using microalgae, lessening its merit as a green technology. In most PBR systems, the diameter of the PBR is optimized to minimize the attenuation of light, leading to enhanced cell growth and astaxanthin accumulation under autotrophic conditions. A small diameter is advantageous for light penetration but has disadvantages of low durability and cell fouling. The PBR system has strengths in the economic

242  Current Developments in Biotechnology and Bioengineering

Table 10.1  Cultivation of microalgae for astaxanthin production in various types of PBRs and scales.

PBR type

Culture volume (L)

Strain

Productivity of astaxanthin (mg L−1 day−1)

CO2 composition

References Choi et al. (2018)

Thin-film column PBR (bubble column)

42.52

Haematococcus pluvialisNIES-144 (wildtype)

1.48

3.5% CO2, 1.36 ppm CO, 10.17 % O2, 21.63 ppm NOx

Thin-film column PBR (bubble column)

100

Haematococcus pluvialis (mutant M160)

5.47

3.5% CO2, 10% Hong et al. O2, 20 ppm NOx, 3 (2019) ppm CO (LNG-fired heat and power plant)

SC-PBR

3

Haematococcus lacustris

5.35

5% CO2 enriched air

External-loop airlift PBR

220

Haematococcus pluvialis CCAP 34/8

4.4

– (bubbled with air, García-Malea 1.0 v/v/min) et al. (2006)

Internal-loop airlift PBR

6.5

Haematococcus pluvialisEGE MACC-32

7.82

– (air pump, 1 L/min)

Double-layered PBR 11 (a kind of internalloop airlift PBR)

H. pluvialis UTEX 16 (CCAP 34/1b, H. lacustris)

16.2 (calculated) 5% CO2 enriched air

Suh et al. (2006)

Horizontal tubular PBR

50

Haematococcus pluvialis

8

5% CO2

López et al. (2006)

Stirred tank PBRs

10

Haematococcus pluvialis EGE MACC-32

0.2343 (Total carotenoid, calculated)

– (1 vvm aeration)

Deniz (2020)

Energy-free RFP

5

Chlorella zofingiensis ATCC30412

5.26

– (Mixotrophy)

Zhang et al. (2017)

Flat panel airlift PBR (FP-ALPBR)

90

H. pluvialis (NIES144)

–

1% CO2

Issarapayup et al. (2009)

Hybrid (horizontal tubular PBR and raceway pond)

25,000

Haematococcus – pluvialis AQSE002

–

Olaizola (2000)

Hybrid (flat vertical panel type and horizontal tubular type)

500 (flat vertical panel), 2000 (horizontal tubular type)

Haematococcus pluvialis Flotow 1844 em. Wille K-00 84

1.5% CO2

Aflalo et al. (2007)

10.1

Kim et al. (2016)

Aslanbay Guler et al. (2020)

Chapter 10 • Photobioreactor systems for production of astaxanthin from microalgae  243

production of high-quality value-added substances owing to high-concentration cell culture, prevention of contamination, and ease of control of culture conditions. Nonetheless, the relatively complex system configuration is a significant problem for the broad utilization and scalability of the PBR system. Specifically, it is necessary to overcome the scalability limitations based on technical and economical approaches because the scale-up process is essential for astaxanthin commercialization. From this point of view, the PBR composed of the multi-polymer film can be suitable for the economical production of astaxanthin because it is cheap and easy to fabricate by heat compared with glass or polycarbonate PBR. Overall, since the productivity of astaxanthin in the PBR system and the energy consumption/ operation cost are inversely correlated, it is vital to secure a system design optimized for the culture conditions for economically feasible astaxanthin production.

Acknowledgements This work was supported by the “Carbon to X Project” (no. 2020M3H7A1098295), which was funded by the National Research Foundation (NRF) funded by the Ministry of Science and ICT and Republic of Korea, grant (no. NRF-2019R1A2C3009821/2020R1A5A1018052) from the National Research Foundation of Korea (NRF).

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Lim, K.C., Yusoff, F.M., Shariff, M., Kamarudin, M.S., 2018. Astaxanthin as feed supplement in aquatic animals. Reviews in Aquaculture 10 (3), 738–773. Liu, J., Huang, J., Sun, Z., Zhong, Y., Jiang, Y., Chen, F., 2011. Differential lipid and fatty acid profiles of photoautotrophic and heterotrophic Chlorella zofingiensis: Assessment of algal oils for biodiesel production. Bioresource Technology 102 (1), 106–110. López, M.C.G.-M., Sánchez, E.D.R., López, J.L.C., Fernández, F.G.A., Sevilla, J.M.F., Rivas, J., Guerrero, M.G., Grima, E.M., 2006. Comparative analysis of the outdoor culture of Haematococcus pluvialis in tubular and bubble column photobioreactors. Journal of Biotechnology 123 (3), 329–342. Lorenz, R.T., Cysewski, G.R., 2000. Commercial potential for Haematococcus microalgae as a natural source of astaxanthin. Trends in Biotechnology 18 (4), 160–167. Lu, Q., Li, H., Zou, Y., Liu, H., Yang, L., 2021. Astaxanthin as a microalgal metabolite for aquaculture: A review on the synthetic mechanisms, production techniques, and practical application. Algal Research 54, 102178. Molina, E., Fernández, J., Acién, F.G., Chisti, Y., 2001. Tubular photobioreactor design for algal cultures. Journal of Biotechnology 92 (2), 113–131. Olaizola, M., 2000. Commercial production of astaxanthin from Haematococcus pluvialis using 25,000-liter outdoor photobioreactors. Journal of Applied Phycology 12 (3), 499–506. Olaizola, M., Huntley, M.E., 2003. Recent advances in commercial production of astaxanthin from microalgae. Biomaterials and Bioprocessing 9, 143–164. Onorato, C., Rösch, C., 2020. Comparative life cycle assessment of astaxanthin production with Haematococcus pluvialis in different photobioreactor technologies. Algal Research 50, 102005. Orosa, M., Valero, J., Herrero, C., Abalde, J., 2001. Comparison of the accumulation of astaxanthin in Haematococcus pluvialis and other green microalgae under N-starvation and high light conditions. Biotechnology Letters 23 (13), 1079–1085. Oslan, S.N.H., Shoparwe, N.F., Yusoff, A.H., Rahim, A.A., Chang, C.S., Tan, J.S., Oslan, S.N., Arumugam, K., Ariff, A.B., Sulaiman, A.Z., 2021. A Review on Haematococcus pluvialis bioprocess optimization of green and red stage culture conditions for the production of natural astaxanthin. Biomolecules 11 (2), 256. Palozza, P., Torelli, C., Boninsegna, A., Simone, R., Catalano, A., Mele, M.C., Picci, N., 2009. Growth-inhibitory effects of the astaxanthin-rich alga Haematococcus pluvialis in human colon cancer cells. Cancer Letters 283 (1), 108–117. Parisenti, J., Beirão, L., Maraschin, M., Mourino, J., Do Nascimento Vieira, F., Bedin, L., Rodrigues, E., 2011. Pigmentation and carotenoid content of shrimp fed with Haematococcus pluvialis and soy lecithin. Aquaculture Nutrition 17 (2), e530–e535. Pashkow, F.J., Watumull, D.G., Campbell, C.L., 2008. Astaxanthin: A novel potential treatment for oxidative stress and inflammation in cardiovascular disease. The American Journal of Cardiology 101 (10), S58–S68. Pelah, D., Sintov, A., Cohen, E., 2004. The effect of salt stress on the production of canthaxanthin and astaxanthin by Chlorella zofingiensis grown under limited light intensity. World Journal of Microbiology and Biotechnology 20 (5), 483–486. Pérez-López, P., González-García, S., Jeffryes, C., Agathos, S.N., McHugh, E., Walsh, D., Murray, P., Moane, S., Feijoo, G., Moreira, M.T., 2014. Life cycle assessment of the production of the red antioxidant carotenoid astaxanthin by microalgae: From lab to pilot scale. Journal of Cleaner Production 64, 332–344. Shah, M., Mahfuzur, R., Liang, Y., Cheng, J.J., Daroch, M., 2016. Astaxanthin-producing green microalga Haematococcus pluvialis: From single cell to high value commercial products. Frontiers in Plant Science 7, 531. Shin, Y.S., Choi, H.I., Choi, J.W., Lee, J.S., Sung, Y.J., Sim, S.J., 2018. Multilateral approach on enhancing economic viability of lipid production from microalgae: A review. Bioresource Technology 258, 335–344. Singh, R.N., Sharma, S., 2012. Development of suitable photobioreactor for algae production: A review. Renewable and Sustainable Energy Reviews 16 (4), 2347–2353. Suh, I.S., Joo, H.-N., Lee, C.-G., 2006. A novel double-layered photobioreactor for simultaneous Haematococcus pluvialis cell growth and astaxanthin accumulation. Journal of Biotechnology 125 (4), 540–546.

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11 Production of biopolymers in photobioreactors Jorge Alberto Vieira Costaa, Gabriel Martins da Rosaa, Suelen Goettems Kuntzlerb, Ana Gabrielle Pires Alvarengab, Michele Greque de Moraisb a

LABO RATO RY O F BI O CHEM I CAL E N G I N E E R I N G , C O L L E G E O F C H E MI S T RY A N D F O O D ENGI NEERI NG, F EDERAL UNI V E R S I T Y O F R I O G R A N D E , R I O G R A N D E , R S , B R A Z I L b LABOR ATO RY O F M I CRO BI O L O GY A N D B I O C H E MI S T RY, C O L L E G E O F C H E MI S T RY A N D FOOD ENGI NEERI NG, F EDERAL UNI V E R S I T Y O F R I O G R A N D E , R I O G R A N D E , R S , B R A Z I L

11.1 Introduction The main contemporary challenge is to reduce the use of fossil fuels and protect the environment to maintain and improve the welfare of living beings. In this context, combined with the population increase in recent years, the demand for synthetic petroleum-based polymers has increased (Devadas et al., 2021). Thus, the economic transition to biological alternatives offers the most promising solution for resolving these issues (Catone et al., 2021). Biopolymers are natural macromolecules synthesized by living beings and have advantages in relation to petroleum-based plastics (Anjum et al., 2016). Biopolymers are promising because of their potential use and rapid degradation by bacteria and microalgae (Costa et al., 2019). These microorganisms can synthesize biopolymers such as PHAs, PSs, and proteins, directly dependent on the species and cultivation conditions employed (Chen et  al., 2013). Proteins are strongly linked to cell structure and multiplication; thus, their concentration is commonly reduced by nutritional stress and growing conditions (Rosa et al., 2019). In contrast, in this adverse scenario, the concentration of PSs (Chentir et al., 2017; Sivaramakrishnan et al., 2020) and PHAs (Martins et al., 2014; Mendhulkar & Shetye, 2017) lean-to increase. Starch, cellulose, and hemicellulose are the predominant PSs in microalgae and have variable concentrations (Chen et al., 2013). Similarly, the concentration of proteins presents in each microalgal cell ranges from 10% w w−1 to 70% w w−1, which can be processed by molding or electrospinning to form biofilms (Hayes et al., 2017). PHAs are polyesters synthesized by several species of microorganisms, including microalgae. In this category, polyhydroxybutyrate (PHB) and polyhydroxybutyrate co-hydroxyvalerate (PHB-HV) are highlighted for presenting interesting characteristics their potential applications in several areas (Costa et al., 2019). The main requirements for microalgae-based bioprocesses are the supply of light and nutrients and the maintenance of adequate culture conditions, including the culture system and photobioreactors (PBRs) (Lutzu et al., 2021; Zittelli et al., 2013). The purpose of producing Current Developments in Biotechnology and Bioengineering. DOI: https://doi.org/10.1016/B978-0-323-99911-3.00012-9 Copyright © 2023 Elsevier Inc. All rights reserved.

247

248  Current Developments in Biotechnology and Bioengineering

biomass and biopolymers is the main reason for defining an appropriate microalgal cultivation system (open or closed). Closed systems, such as closed flasks (Cassuriaga et al., 2018) or tubular (Troschl et al., 2018), are most commonly used for the production of biopolymers, although open systems, such as tanks, ponds, and lakes, are the most common (Godos et al., 2014). Closed PBRs are systems isolated from the external environment to avoid contamination and adverse external influences, which usually provide higher biomass and bioproduct productivity than open systems (Acién et al., 2017). The accentuated concentration of biopolymers can be verified in closed bench systems (0.25 and 2.0 L) for Nostoc muscorum (69.0% w w−1) (Bhati & Mallick, 2015), Spirulina sp. (45.0% w w−1) (Martins et al., 2014); and in pilot-scale (200 L) with Synechocystis sp. (Troschl et  al., 2018). In closed PRBs, high protein productivity of Chlorella pyrenoidosa (5.62 g L−1 d−1) (Wang et al., 2020) and PS in Neochloris oleoabundans (70% w w−1 in relation to carbohydrates) (Ruiz et al., 2020). Therefore, this chapter aims to report the most recent research that addresses the main types of biopolymers produced in photobioreactors and the cultivation conditions that influence their production from microalgae.

11.2  Biopolymers from microalgae Biopolymers produced in PBRs are mainly proteins, lipids, or carbohydrates (Lutzu et al., 2021), which are of commercial interest because of their thermoplasticity, gelling power, and foaming capacity (Chaogang et al., 2010; Delattre et al., 2016). Therefore, the main biopolymers obtained from PBRs, which have the replacement characteristics of synthetic polymers in technological and industrial applications, will be discussed. In addition, Table 11.1 presents the main cultivation conditions and the yield of biopolymer production by different microalgal strains.

11.2.1  Poly (hydroxyalkanoates) PHAs are biopolymers produced and accumulated by various photosynthetic microorganisms as an energy storage mechanism, commonly in the stationary growth phase (Lutzu et al., 2021; Mendhulkar & Laukik, 2017). Photoautotrophic microalgae can synthesize PHAs by accumulating neutral lipids, nutrient limitation, and CO2 as a carbon source (Costa et al., 2019). PHAs can be found as cytoplasmic inclusions composed of proteins and lipids that are insoluble in the presence of excess carbon and nutrient limitation in the medium (Laycock et  al., 2013). In cultivation with industrial waste, the production of PHAs from Arthrospira (Spirulina) platensis reduced (from 1.1% to 0.5% w w−1) when the carbon source changed from pure to crude glycerol (Corrêa & Teixeira, 2021). The structure of the PHAs shows the ester bond of the hydroxy acid monomers. The biopolymers were classified according to the number of carbon atoms. The short chains of PHAs are composed of three to five carbon atoms, medium chains feature six to fourteen carbon atoms, and long chains are more than 15 carbon atoms (Anjum et al., 2016; Kunasundari & Sudesh, 2011). The properties of PHAs depend on the size of the polymer chains and the degree of polymerization, resulting in different structural rearrangements (Costa et al., 2019). The thermal degradation characteristics, crystallinity, and mechanical properties are similar to those of

Nostoc sphaeroides Tetraselmis sp.

Synechocystis sp. PCC6803

Cassuriaga et al. (2018) García et al. (2021) Moradi et al., 2021 Silva et al. (2018)

Roh et al. (2021) Taghavijelouda et al. (2021) Nguyen et al. (2020) Devi, Tiwari, & Goud, 2021 Naveed et al., and Ge (2020) Zhong et al. (2021) Yang et al. (2021)

17.4 ± 1.5b 29.92b 12.7 ± 1.7b 10.6b

21.1b 51a 35.9b 29.36 ± 1c 34.6-46.4b

28  100 100 55.08

400 39.2 40.5

BG-11 medium with As(V) (0, 10, 50, 100, 200, 50 500 μM) BG11 medium 80 Artificial seawater with 2.5 mg dm−3 of 28 17α-ethinylestradiol Addition of 12.2 mm sodium acetate on 168 the BG11 medium BG-11 medium with 4.05 mg L−1 Pb (II) 28 BG-11 medium with 0.5 mg L−1 28 Cd (II)

Alvarez et al. (2021) Cui et al. (2021) Shen et al. (2018)

1463 ± 16a 19b 60.4b

30b 70.9b

Cassuriaga et al. (2020)

206 ± 0.1a

41.6

Data not provided; aYield (mg L−1); bYield (% w w−1); cYield (mg g−1).

Synechocystis sp. PCC6803 Synechocystis sp. PCC6803

Exopolysaccharides Nostoc sp. PCC 7936

Polysaccharides

Proteins

Chlamydomonas reinhardtii CC1021

PHB

Culture medium

Tris-acetate-phosphate culture media with NH4Cl concentrations of 6 g L−1 and 20 mg L−1 of d-xylose Chlorella fusca LEB 111 BG-11 medium with a 50% reduction in the nitrogen source and d-xylose Scenedesmus sp. (UTEX 1589) BG-11 medium with 1 g L−1 of glucose, limited phosphorus and salinity 0.5 g L−1 Spirulina platensis Zarrouk medium with 60 mg L−1 of Azo dye Direct Green 6 Spirulina sp. LEB 18 Zarrouk medium supplemented with the 25% (v v−1) PHB extraction waste previously neutralized with sodium thiosulfate Synechococcus 2973-phaCAB BG-11 medium with 5% CO2 gas Chlorella sorokiniana BG11 medium with treatment 1000 mg L−1 triton X-100 Chlorella vulgaris Original medium with 50 mg L−1 of seafood wastewater medium Limnothrix sp. DDVG II BG11 medium

Strain

Biopolymer

Light intensity (μmol photons Biopolymer m2 s−1) yield References

Table 11.1  Summary of microalgal strains used for biopolymers production.

Chapter 11 • Production of biopolymers in photobioreactors  249

250  Current Developments in Biotechnology and Bioengineering

polypropylene and can be used as an alternative to thermoplastic materials of petrochemical origin (Bugnicourt et al., 2014). PHAs are non-toxic to cells and tissues, and the rate of degradation of these biopolymers depends on extrinsic factors such as temperature, humidity, pH, and nutrient supply. Intrinsic factors, such as additive composition, crystallinity, and surface area, influence the biodegradability of these biopolymers (Sharma & Mudhoo, 2011). PHAs, when degraded in active microbial environments, form CO2 and water, which can be reintegrated back into nature and complete the carbon cycle (Balaji et al., 2013; Meixner et al., 2018). Different polymers and copolymers can be obtained depending on the substrate used and the metabolism of photosynthetic microorganisms. The most studied PHAs are polyhydroxybutyrate (PHB) and polyhydroxybutyrate co-hydroxyvalerate (PHB-HV), which are characterized as aliphatic polyesters and biodegradable (Hempel et  al., 2011). PHB exhibits optical purity, thermoplastic processability, hydrophobicity, and non-toxicity (Chaogang et al., 2010). During PHB synthesis, two molecules of acetyl-CoA reductase are joined by a condensation reaction catalyzed by the enzyme 3-β-ketothiolase to form acetoacetyl-CoA. This enzyme competes with acetyl-CoA in other metabolic pathways, such as acetate and citrate formation, and fatty acid synthesis. The product is reduced to 3-hydroxybutyryl-CoA in a reaction catalyzed by NADPH-dependent acetoacetyl reductase. High concentrations of NADPH and NADH inhibit the enzyme citrate synthase, which is responsible for acetyl-CoA entering the tricarboxylic acid cycle, making acetyl-CoA available for 3-β-ketothiolase. Thus, PHB is synthesized from the polymerization of 3-hydroxybutyryl-CoA units by PHA synthase (Abdo & Ali, 2019; Roja et al., 2019). The synthesis of PHB-HV copolymer can occur using carbon sources such as glucose, acetate, propionic acid, and valeric acid. Intermediates, such as acetyl-CoA or acyl-CoA, are involved in this process, which is finalized by polymerization of the monomer by PHA synthase (Aikawa et al., 2015; Bhati & Mallick, 2015). PHB presents properties such as water resistance (insoluble and impermeable), stability to ultraviolet radiation, and ideal storage conditions or during use. However, PHB presents low tensile strength owing to its high crystallinity and low nucleation rate during crystallization kinetics (Corrêa et al., 2008). However, it is still the most economically studied and industrially exploited microalgal biopolymer (Price et al., 2020).

11.2.2 Proteins Microalgae are considered sustainable sources of protein because of the high possible content (∼70% w w−1) of this compound in their biomass, the ability to grow rapidly, and the use of industrial by-products as a nutrient source to minimize environmental impacts (Becker, 2007; Grossmann et  al., 2020). Different amino acids are found in microalgal proteins such as alanine, glutamate, glycine, aspartate, arginine, leucine, lysine, serine, phenylalanine, proline, and threonine (Siahbalaei et al., 2021). In addition, an important characteristic of proteins is their solubility, which directly affects their emulsifying, gelling, and foaming capacity and influences the techno-functional properties of proteins (Garcia et al., 2018). The intrinsic factors that alter the water solubility of proteins are molecular mass, amino acid composition, and propensity

Chapter 11 • Production of biopolymers in photobioreactors  251

to form the α-helix, such as pH, ionic strength, and temperature (Diaz et al., 2010; Pelegrine & Gasparetto, 2005). Grossmann et  al. (2019b) and Weiss (2019b) evaluated the influence of pH on the solubility of proteins extracted from Chlorella sorokiniana, Phaeodactylum tricornutum, and Nannochloropsis oceanica. Soluble proteins from N. oceanica showed high solubility (≥79 g/100 mL) in the pH range of 6–12, whereas lower solubility was observed for proteins from C. sorokiniana (≥68 g/100 ml) and P. tricornutum (≥50 g/100 mL). The minimum solubility was observed at pH 4 for C. sorokiniana, pH 2 for P. tricornutum, and N. oceanica. The insoluble proteins extracted from all microalgae showed low solubility at all pH values tested. The authors found that the presence of strongly bound protein aggregates in the extract prevented the action of H+ ions. Dai et al. (2019) and Weiss (2019) investigated the rheological properties of insoluble proteins and hydrolysates of Chlorella protothecoides as a function of pH 3, 5, 7, and 9. The results showed that the interfacial viscoelasticity of the insoluble proteins was lower than that of the hydrolysates at all pH values, owing to the formation of aggregates in the dispersion of the insoluble proteins. Proteins can be used as thermoplastic biopolymers in various areas. They are biodegradable, biocompatible, and have high mechanical properties (Wang et al., 2019; Zhu et al., 2017). Moreira et al. (2018) extracted proteins from the biomass of Spirulina sp. LEB 18 and used as a biopolymer for the development of nanofibers. The concentrations of 5 and 10% (w w−1) proteins in the polymer solution resulted in nanofiber production for application in biodegradable food packaging. Grossmann et al. (2019a) and Weiss (2019a) produced gels with soluble protein extracts from Chlorella sorokiniana under heat treatment (61°C). The results showed that the gels were stable, with high elasticity and firmness. Teuling et al. (2019) and Wierenga (2019) found that protein isolates from Nannochloropsis gaditana, Tetraselmis impellucida, and Arthrospira (Spirulina) maxima exhibited high emulsion forming ability at pH 8 of size 0.2–0.3 μm.

11.2.3 Polysaccharides PSs are produced by microalgae and are found in cells as a form of energy storage, cell wall components, and extracellular polymer (EPS) (Bernaerts et al., 2019). In addition, PSs are polymers with high structural variability due to the long chains of monosaccharide units and the different glycosidic bonds between the anomeric hydroxyl group of pentoses, hexoses, and other monosaccharides (Prybylski et al., 2020). Storage PSs are present in the organelles of microalgae, such as chloroplasts, vacuoles, and cytosol (Suzuki & Suzuki, 2013). The outer cell wall is composed of structural PSs that can remain associated with the cell surface or be released into the medium depending on the growth phase of the microalgae (Delattre et al., 2016). Starch is the main PSs found inside microalgal cells. Noguchi et al. (2021) used the microalga Chlorella vulgaris in wastewater cultivation for starch production. The results showed that during 39 d of cultivation, the starch/carbohydrate accumulation was between 43.4 ± 5.8 and 62.6 ± 23.3 mg L−1. Ruiz et al. (2020) cultured the microalgae Neochloris oleoabundans in nitrogendeficient artificial saline water. In this study, the total carbohydrate content was approximately

252  Current Developments in Biotechnology and Bioengineering

27% w w−1, containing approximately 70% w w−1 starch concentration. According to a study by Lee et al. (2018) and Choi (2018), the cell wall of the microalgae Nannochloropsis oceanica and Nannochloropsis salina are composed of cellulose as a structural PS. They found cellulose contents of 47% w w−1 and 34% w w−1 in N. oceanica and N. salina, respectively. EPS are macromolecules of complex structures with polymeric chains of homopolysaccharides or heteropolysaccharides without repeating units (Paniagua-Michel et  al., 2014). These biopolymers can be synthesized in the Golgi complex of microalgae and are excreted by the cells, forming a viscous coating that reduces the penetration of unneeded ions to the cell surface (Delattre et al., 2016). EPS are classified into two types according to the intensity of their binding to cells. Soluble EPS are secreted into the medium and weakly bound to cells and cell-bound EPS (Naveed et al., 2019). Bound EPS have a compact structure and are divided into tightly bound EPS in the inner layer and loosely bound EPS in the outer layer (Babiak & Krzeminska, 2021). EPS are composed of various monosaccharides and can have low or high molecular weights depending on the microalgal genus (Villarcorte et al., 2015). Zhang et al. (2019) and Chen (2019) determined the molecular weight of EPS synthesized from Chlorella pyrenoidosa, Scenedesmus sp., and Chlorococcum sp. to be 1.94 × 105, 7.39 × 103, and 3.24 × 104 g mol−1, respectively. The monosaccharides present at different concentrations in the EPS in all microalgae were d-mannose, ribose, l-rhamnose, glucosamine, galacturonic acid, d-glucose, galactosamine, d-galactose, d-arabinose, and l-fucose. Gaignard et al. (2019) identified EPS extracted from Dunaliella sp., such as galactose, rhamnose, xylose, mannose, and glucuronic acid at concentrations of 28, 21, 17, 13, and 11%, respectively.

11.3  Upstream and downstream factors that maximize microalgal biopolymer production Primary nutrients, such as phosphorus, carbon, and nitrogen, are the macronutrients required for microalgal growth (Wang et al., 2019). Nitrogen and phosphorus are absorbed as nitrates and phosphates, respectively. Urea may be a suitable and viable source of organic nitrogen. CO2 can be added as a carbon source and a bicarbonate form. However, the CO2 present in flue gas can be used as a carbon source for large-scale cultivation (Costa et al., 2015). The micronutrients potassium (K), iron (Fe), magnesium (Mg), manganese (Mn), boron (B), and zinc (Zn) are required in low amounts; however, they are essential for microalgal growth because they influence the enzymatic activities of the cells (Gardner-Dale et al., 2017).

11.3.1  Nitrogen source Zhang et  al. (2018) cultivated Chlamydomonas reinhardtii under heterotrophic conditions and with different nitrogen sources (nitrate, ammonium, and urea). With the same species, Cassuriaga et al. (2018) found that reducing the nitrogen source (8 to 6 g L−1) was not sufficient to promote PHB production by C. reinhardtii. However, when supplementation with organic carbonic (D-xylose) was combined with a reduction in the concentration of the nitrogen compound (6 g L−1), increased PHB production (206.0 mg L−1) occurred (Cassuriaga et al., 2020).

Chapter 11 • Production of biopolymers in photobioreactors  253

Nutrient limitation is a commonly used strategy to increase the accumulation of bioactive compounds (Khan et al., 2018). Kamravamanesh et al. (2017) observed that using N/Plimited conditions, PHB productivity from the cyanobacterium Synechocystis sp. PCC 6714 promoted the accumulation of 59 mg L−1 d−1. PHB production was more efficient (30.7%) when Spirulina sp. LEB 18 was grown in a nitrogen-deprived medium (0.05 g L−1) (Coelho et al., 2015). In another study, PHB production by Spirulina sp. LEB 18 cultivated in culture medium containing 0.25 g L−1 NaNO3 resulted in 44.2% w w−1 accumulation (Martins et al., 2014). The influence of the nitrogen source (70% reduction) on the production of PHAs by microalgae was verified at the end of the exponential phase and the beginning of the stationary phase of cell growth (Costa, Miranda et al., 2018). Under this nutrient restriction condition, the authors observed 300 and 400% accumulation of biopolymers synthesized by the microalgae Synechococcus subsalsus and Spirulina sp. LEB 18 compared to the control condition (Costa, Miranda et al., 2018).

11.3.2  Light intensity and temperature Luminosity can enhance biomass growth and consequently enable higher biopolymer yields. PHB production by Synechocystis sp. under high light intensity (300 µmol m−2 s−1) resulted in PHB accumulation with a yield of 241 mg L−1 (Gracioso et al., 2021). Fradinho et al. (2019) and Reis (2019) observed that increasing the light intensity from 15 to 30% resulted in an increase in PHB production. Chlorogloea fritschii grown under continuous light (100 µmol m−2 s−1) resulted in PHB accumulation of 531 mg L−1 (Monshupanee et al., 2016). A mixed culture of cyanobacteria under constant lighting and P limitation resulted in higher PHB yields (104 mg L−1). The authors also found higher carbohydrate concentrations (838 mg L−1) under N-limited conditions with a 12 h light: 12 h dark photoperiod (Arias et  al., 2018). PHB accumulation (7.63% w w−1) was higher under light: dark photoperiod conditions than under continuous lighting (1.51% w w−1) in N. muscorum NCCU 442 (Ansari & Fatma, 2016). Optimization of temperature (30°C) in the cultivation of N. muscorum NCCU 442 favored the PHB concentration (7.61% w w−1) when compared to other temperatures (15, 20, 25, 40, and 45°C) (Ansari & Fatma, 2016). Cultivation of the cyanobacterium Synechocystis sp. PCC6803 reached the maximum PHB concentration at 28°C (Panda et  al., 2006). In cultivation with Nostoc flagelliforme, the highest EPS production (228.6 mg L−1) occurred with increasing light intensity and temperature compared to cultivation at 25°C (Yu et al., 2010). Han et al. (2014) and Tan (2014) studied the influence of light on the cultivation of Nostoc flagelliforme and the production of extracellular and capsular PSs. The results showed that red and blue lights significantly increased the production of PSs compared to white light (control condition). Trabelsi et  al. (2009) and Ghoul (2009) concluded that optimization of EPS production by A. platensis was realized under light intensities of 180 µmolphotons m−2 s−1 at 35°C. The accumulation of PHB in N. muscorum cultivation was 18.0% w w−1, 20.5% w w−1, and 24.1% w w−1 at a photoperiod (light: dark) of 14:10, 12:12, and 10:14 h, respectively (Ansari & Fatma, 2016).

254  Current Developments in Biotechnology and Bioengineering

11.3.3  Modes of obtaining energy Nutrient and energy sources vary according to cultivation conditions, influencing biomass and lipid productivity (Hu et al., 2018). Microalgal cultivation can be performed using different trophic conditions, such as photoautotrophic, heterotrophic, and mixotrophic. Although PHB production is less than 10% w w−1 under standard growth conditions (Bathi et al., 2010), this concentration can be increased under nitrogen-limited conditions (Mata et  al., 2010). Kamravamanesh et  al. (2017) studied PHB production in Synechocystis sp. PCC 6714 under photoautotrophic cultivation under nitrogen-limited conditions. The authors reported a 10% increase in PHB production. Chlorogloea fritschii TISTR 8527 grown under photoautotrophic conditions increased the conversion of acetate substrate to PHB (51.0% w w−1) by two-stage cultivation (photoautotrophic and heterotrophic) (Monshupanee et al., 2016). EPS production by Arthrospira platensis was studied in photoautotrophic (100 µmol m−2 s−1), heterotrophic (1.5 g L−1 glucose), and mixotrophic (100 µmol m−2 s−1 and 1.5 g L−1 glucose) conditions. Maximum EPS production was observed in mixotrophic culture (290.5 mg L−1) compared to photoautotrophic (219.6 mg L−1) and heterotrophic (30.3 mg L−1) conditions (Trabelsi et al., 2013). Mixotrophic cultivation of Chlorella sp. using glycine as an organic carbon source and salinity of 3.5% w v−1 promoted EPS production (0.031 g L−1) (Vo et al., 2020). Panda et al. (2006) studied the impact of PHB accumulation on mixotrophic cultivation. In this study, PHB accumulation increased to 29% w w−1 compared to photoautotrophic conditions. In addition, nutrient limitations, such as nitrogen and phosphorus, stimulated PHB accumulation by 9.5% and 11% w w−1, respectively (Panda et al., 2006).

11.3.4  Extraction methods Following cultivation conditions, proper extraction methods are essential to promote the high yield and purity of the isolated biopolymers. In addition, it is of interest these methods are effective, economical, and environmentally-friendly (Delattre et  al., 2016). Extraction associated with biomass pretreatment is used to obtain high PHB content based on cell weight (Costa, Moreira et al., 2018). Martins et al. (2014) centrifuged the culture medium to precipitate the microalgal biomass. Thereafter, extraction was performed with sodium hypochlorite from 10% v−1 to 12% v−1 and centrifuged again. The precipitate was washed with distilled water, and acetone was added to obtain the biopolymer. PHB extraction performed by Balaji et al. (2013) found the maximum PHB concentrations after chloroform evaporation of 7.4% v v−1, 4.5% v v−1, 3.7% v v−1, and 2.3% v v−1 for the strains Phormidium sp., Synechococcus sp., Synechocystis sp., and Anabaena sp., respectively. In this study, the microalgal cells were centrifuged, washed with distilled water, and suspended in methanol. The biopolymer was obtained by centrifugation and drying (1 h) using the Soxhlet method with chloroform (Balaji et al., 2013). The processes used to separate microalgal cells from the PS/EPS released into the culture medium include filtration and centrifugation. The PSs are concentrated, commonly by centrifugation, and precipitated with methanol, ethanol, isopropanol, or acetone (Delattre et  al., 2016). Alternative strategies, such as sonication, microwave-assisted extraction, and

Chapter 11 • Production of biopolymers in photobioreactors  255

ultrasound-assisted extraction treatments, have been proposed. In addition, PS/EPS may remain bound to the cells during extraction, requiring other methods to release the compounds into the liquid medium (Arad & Levy-Ontman, 2010). Chemical and ionic methods such as formaldehyde, glutaraldehyde, ethylenediaminetetraacetic acid, sodium hydroxide, hot water, and ion resin are also used to extract the cell-bound PS fraction (Delattre et al., 2016; Gaignard et al., 2019).

11.4  Photobioreactors used to produce biopolymers The PBRs chosen must be based on the specific characteristics of obtaining biomass and/ or bioproducts from a given microalgal strain. The most diverse configurations of open and closed PBRs have already been proposed. However, there is no existing ideal project for PBR (Acién et al., 2017). Therefore, knowledge of the requirements of the biotechnological system to be used consolidates the ideal starting point for the necessary design for the most suitable photobioreactor. For the cultivation of photosynthetic microorganisms, light energy is among the main design parameters in PBRs because it defines the geometry and the surface-volume ratio (S/V). Natural or artificial lighting sources must be selected in conjunction with other parameters such as volume, agitation (Gupta et al., 2015), pH, temperature, gas exchange, and the possibility of cleaning/sterility in situ (Wang et al., 2012). The second important design factor for PBRs is stirring because it can promote inadequate shear or inhibit microalgal growth (Gupta et  al., 2015). Furthermore, stirring minimizes the effects of mutual shading between cells and improves heat transfer (Kirnev et  al., 2020). The most commonly used stirring in PBRs occurs through convective movements by injection of gases (Gupta et al., 2015), or mechanical systems with rotating blades or impellers (Kirnev et al., 2020). Raceway-type open PBRs (such as shown in Fig. 11.1A) were one of the first projects reported (Godos et al., 2014), which have been improved to this day. The main aspect of these PBRs is the total area (between 100 and 5000 m2). Thus, from the defined total surface area, RacewayPBRs are divided into channels along the way to recirculate the cultivation. The channels have a length proportional to the width (from 10 to 20 to 1), with lower ratios preferable to reduce pressure drops. Similarly, the smallest depths (∼0.2 m) can increase biomass productivity since light permeation into cultivation is more effective. In these situations, the S/V ratio is low (5–10 m−1) (Acién et al., 2017). This type of PBR configuration may have a vessel (or sump) along with one of the channels for spraying gases such as CO2 (Pawlowski et al., 2017). The main disadvantages of using open PBRs are reduced biomass concentrations reached (∼1.0 g L−1), evaporative losses, low CO2 diffusion, contamination proneness, and limited lighting at cultivation heights greater than 0.03 m (Brennan & Owende, 2010). Among the advantages are the ease and reduced cost of construction and operation (Singh & Sharma, 2012). Compared to tubular PBRs, construction costs can be up to four times cheaper (Chisti, 2013; Norsker et al., 2011).

256  Current Developments in Biotechnology and Bioengineering

(A)

(B)

(C)

(D)

FIG. 11.1  Scales of photobioreactors used for the cultivation of and biopolymer production using microalgae. (A) raceway open (18,000 L each) used in the pilot plant of the Presidente Médici Thermoelectric Power Plant in southern Brazil, (B) flasks (1.0 L), (C) vertical tubular (2.0 L), and (D) horizontal tubular with airlift (150 L).

Closed-PBRs have been designed to improve open cultivation systems (Gupta et al., 2015). Tubular-PRBs are the most common among closed-PBRs. However, a limited number of microalgal production facilities employ these systems (Posten, 2009). Tubular-PBRs (Fig. 11.1B and C) consist of a single or a series of concurrent transparent pipes, generally made of synthetic polymeric material through which the microalgal suspension is circulated with the aid of a gas stream (Brennan & Owende, 2010) (Fig. 11.1B). Tubular-PBRs have S/V ratios of up to 80 m−1, length variable, the diameter of sections up to 0.1 m (Brennan & Owende, 2010; Chisti, 2007). These PBR settings make it possible high biomass productivity (∼60 g m−2 d−1) (Zhang et al., 2015).

Chapter 11 • Production of biopolymers in photobioreactors  257

Tubular PRBs can be arranged vertically, horizontally, obliquely, or cover a predefined shape. The north-south alignment maximizes the use of solar energy by the tubular section (Molina et al., 2001; Torzillo & Zittelli, 2015). However, significant amounts of heat can require temperature control (Wang et  al., 2012) to cool the PBR systems, such as heat exchangers, shading, water spray, or immersion of tubular sections in a temperature-controlled fluid (Acién et al., 2017).

11.4.1  Biopolymer production from microalgae Obtaining biopolymers by photosynthetic microorganisms, whether raw or purified, can be obtained in different configurations and cultivation volumes, as shown in Table 11.2. However, most studies showed that for the biopolymer concentration range (between 7.0 and 69%), a closed-PBR design was used. In addition, closed-PBRs can also have high biomass productivity (Zhang et al., 2015). In a biorefinery system, the production of carbohydrates and PHB by native cyanobacteria has been studied (Rueda et al., 2020). In this study, a demonstrative scale of three horizontal semi-enclosed PBRs (11.7 m3 each) was used to treat wastewater and, with the addition of CO2, trigger off accumulate PHB and carbohydrates. Although the PHB concentration was relatively low (4.5% w w−1), in addition to the high carbohydrate content (69% w w−1) obtained, the system provides important information on a strategy to produce PHB from cyanobacteria on a large scale (Rueda et al., 2020). In a controlled cultivation system (DASbox Mini Bioreactor System), in closed glass PBR, Synechocystis sp. PCC 6714 can be obtained up to 37% w w−1 PHB from CO2 as an inorganic carbon source. The authors attributed the high production of the biopolymer to random mutations obtained in the strain with the aid of ultraviolet light (Kamravamanesh et  al., 2018). In Erlenmeyer-type glass PBR, also 0.25 L, N. muscorum produced a high concentration of PHB (69.0% w w−1), aided by nutritional phosphorus reduction (Bhati & Mallick, 2015). From vertical tubular-PBR, semi-continuous mode, medium renewal rate of 40% v v−1, was verified a maximum PHB concentration (7.1% w w−1) of Spirulina sp. LEB 18 (Moreira et  al., 2016). With this same PBR configuration and microalgal strain but slightly reduced dimensions (1.8 L, θinternal = 0.075 m, h = 0.60 m), the residue from PHB extraction (25% v v−1) was used to obtain a higher concentration of biopolymer (10.6% w w−1) (Silva et al., 2018). From Spirulina sp. LEB 18 with the Erlenmeyer-type glass closed-PBR configuration (Fig. 11.1D), a higher raw biopolymer production (∼45% w w−1) was obtained with the aid of the modification of the Zarrouk culture medium (reduction of 10% of the nitrogen source and 50% of carbon source) (Martins et al., 2014). PHB production has been studied in eukaryotic green microalgae, such as C. reinhardtii (Cassuriaga et  al., 2020) and Chlorella fusca LEB 111 (Cassuriaga et  al., 2018), both in Erlenmeyer-type closed-PBRs. The assays with C. reinhardtii have shown that the reduction of 75% w w−1 of the nitrogen source from the standard medium and the addition of D-xylose (20 mg L−1) promoted the production of PHB (206 mg mL−1), which was not detected in the control assay (Cassuriaga et  al., 2020). In this same PBR configuration, assays with C. fusca LEB 111 showed that the addition of D-xylose (20 mg L−1) and reduction of light exposure for

258  Current Developments in Biotechnology and Bioengineering

Table 11.2  Biopolymer production by microalgal strains in different photobioreactors. Photobioreactor type (volume) Strain

Biopolymer Biopolymer type content −1

Additional condition

References Bhati and Mallick (2015) Shrivastav et al. (2010) Kamravamanesh et al. (2018) Singh et al. (2019)

Flask (0.25 L)

Nostoc muscorum PHB

69.0% w w

Phosphorus deficiency

Flask (0.25 L)

Spirulina subsalsa

7.5% w w−1

Increased salinity

Flask (0.25 L)

Synechocystis sp. PHB PCC 6714 Scytonema geitleri PHB Bharadwaja Synechocystis sp. PHB

Flask (0.5 L) Flask (0.5 L) Flask (0.5 L) Flask (0.5 L)

Synechococcus elongates Scenedesmus sp.

Conical flask (1 L) Anabaena sp. CCC-746 Flask (2.0 L) Spirulina sp. LEB 18 Flask (2.0 L) Spirulina sp. LEB 18 Vertical tubular Spirulina sp. LEB (2.0 L) 18 Vertical tubular Spirulina sp. LEB (2.0 L) 18 Fernbach flask Synechocystis (2.8 L) and glass PCC 6803 flask (0.5 L) Cylindrical (20 L) Spirulina sp. LEB 18 Cylindrical (20 L) Synechococcus subsalsus Horizontal tubular Synechocystis sp. (200 L) CCALA192 Semi-closed cyanobacteria horizontal selected (11,700 L)

PHA

37.0% w w−1 Random mutagenesis with ultraviolet light 7.1% w w−1 Acetate addition

PHA

11.0% w w−1 Nitrogen and phosphorus deficiency 17.2% w w−1 Nitrogen deficiency

EPS

*0.12 g L−1

EPS

*0.34 g L−1

PHB

45.0% w w−1

PHB

30.7% w w−1

PHB

7.1% w w−1

PHB

10.6% w w−1

PHB

∼15% w w−1

PHA

12.0% w w−1

PHA

16.0% w w−1

PHB

12.5% w w−1

PHB

4.5% w w−1

Panda et al. (2006)

Mendhulkar and Shetye (2017) Two-stages; microwaves Sivaramakrishnan radiation et al. (2020) Supplementation of Tiwari et al. (2020) CaCl2 Carbon and nitrogen Martins et al. reduction (2014) Nitrogen deficiency Coelho et al. (2015) Medium renewal rate Moreira et al. of 40% w w−1 (2016) Addition of PHB Silva et al. (2018) extraction waste Two-stages; nitrogen Dutt and Srivastava reduction lacking (2018) nitrogen or phosphorus. Nitrogen deficiency Costa, Miranda et al. (2018) Nitrogen deficiency Costa, Miranda et al. (2018) Two-stages; nutrient Troschl et al. limitation (2018) Wastewater and Rueda et al. (2020) intermittent CO2 addition

EPS, Extracellular Polymeric Substances; PHB, polyhydroxybutyrate; PHA, polyhydroxyalkanoate.

6 h promoted the production of PHB (17.4% w w−1), compared to the control condition (12 h of light; PHB concentration = 0.5% w w−1) (Cassuriaga et al., 2018). From a pilot-scale horizontal acrylic tubular PBR (200 L and 80 m long), 12.5% w w−1 PHB was obtained from Synechocystis sp. CCALA192 using a two-stage cultivation strategy. In this study, the first stage (also called the growing or green stage) was prioritized to obtain a greater

Chapter 11 • Production of biopolymers in photobioreactors  259

concentration of biomass through an adequate nutritional supply; whereas in the second stage (also called the yellow stage), the biopolymer production increased with the depletion of nutrients (Troschl et al., 2018). The double-stage strategy was also used for the cultivation of Synechocystis sp. PCC 6803 for photoautotrophically in Fernbach-type closed PBRs (2.8 L), and photomyxotrophically (with the addition of 0.4% w w−1 acetate) in Erlenmeyer-type closed PBRs (0.5 L), biomass productivity was maximized. However, in the later stage, with nitrogen and phosphorus source deprivation, the PHB concentration remained at ∼15% w w−1 (Dutt & Srivastava, 2018). The use of C. pyrenoidosa to treat wastewater with high salinity and high NH4+ concentration (Wang et  al., 2020) showed that both the cultivation conditions and the volume of PBR used influence protein concentration and productivity. In this study, when PBR of 5 L was used, 19% and 37% more protein were obtained (50% w w−1) and protein productivity (5.6 g L−1 d−1), compared to batch in PBR of 50 L (42.1% w w−1 and 4.1 g L−1 d−1) (Wang et al., 2020). The use of tubular-PBR (2 L), C. fusca LEB 111 with the application of magnetic fields (intensity of 30 mT, 24 h d−1), presented a high protein concentration of 56.2% w w−1 (Deamici et al., 2019) and 61.3% w w−1 (Deamici et  al., 2016), keeping biomass productivity practically unchanged (0.12–0.13 g L−1 d−1). Determination of EPS concentrations in Anabaena sp. CCC-746 (0.34 g L−1) was maximized using a 1 L conical closed-PBR. This biopolymer produced by the cyanobacterium Spirulina sp. showed a high specific concentration (1.0 g g−1) when it was cultivated in two stages. The first step of this study was conducted in a closed-PBR (5.0 L), whereas the second step (or stress stage) was performed in a closed-PBR (0.25 L (Chentir et al., 2017). However, when the PBRclosed was kept, without volume change at two-stage strategy, Scenedesmus sp. has shown a lower specific concentration of EPS (0.04 g g-1) (Sivaramakrishnan et al., 2020).

11.5  Conclusions and perspectives In recent years, although the use of microalgae and biopolymers has significantly increased, their productivity is still not sufficient to meet the increased commercial needs for superfoods and biopolymers. There are breakthroughs in microalgal biotechnology, such as bioreactor design, strain development, and genetic and metabolic engineering, leading to higher biomass productivity and biopolymer accumulation. In addition, low-cost harvesting processes could contribute to driving the microalgal bioeconomy. The main biopolymers produced in PBRs by microalgae are discussed in this chapter, highlighting PHB, which is a promising material to replace fossil plastics sustainably in the nottoo-distant future. Several genera of microalgae, such as Spirulina sp., Scenedesmus sp., Nostoc sp., and Chlorella sp., can synthesize and store intracellular or extracellular biopolymers. However, optimization of the growing conditions for the production of biopolymers is essential for economic viability. In this chapter, biopolymers are mostly obtained in closed or semi-closed PBRs on a bench or pilot scale. Thus, the information reported here can be used to find more adequate strategies for scaling up to produce biopolymers in PBRs. Among these, the nutritional deprivation

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of N and P and the change in the C/N ratio combined with the use of two or more cultivation stages, also reported as “feast and famine” phases, may offer the desired path for scaling up this bioprocess. In addition, the use of wastewater and industrial by-products has been increasingly established to reduce the operational cost of producing biomass and biopolymers in PBRs. In this chapter, it was also demonstrated that biopolymer production, such as PHB and EPS, in PBRs can be maximized with the conversion of organic carbon sources, such as acetate and glucose, by up to 50% w w−1 combined with photoautotrophic and heterotrophic modes. Thus, although it has a high potential to eliminate the operating cost with the carbon source, the biopolymer photoautotrophic production in PBRs has lower biopolymer yields. Therefore, researchers have highlighted a possibility of an efficient, sustainable biological system to match the potentialities related to biopolymer production in a hybrid way: photoautotrophic and heterotrophic. With mixotrophy, which, if added to the optimization of process parameters and metabolic engineering, the sustainable cycle necessary for biopolymer production by microalgae in PBRs can be achieved. Thus, this hybrid biosystem would contemplate the economical production of biopolymers, providing an alternative to fossil plastics and reducing global warming with CO2 biofixation.

Acknowledgements The authors would like to thank the Coordination for the Improvement of Higher Education Personnel (CAPES)— Finance Code 001, National Council for Scientific and Technological Development (CNPq), and the Ministry of Science, Technology, and Innovation (MCTI) for their financial support. This research was developed within the scope of the Capes-PrInt Program (Process # 88887.310848/2018-00). In addition, G.M. Rosa would like to thank the National Council for Scientific and Technological Development (CNPq) for granting a postdoctoral fellowship (process number 161006/2019-1).

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Naveed, S., Li, C., Zhang, J., Zhang, C., Ge, Y., 2020. Sorption and transformation of arsenic by extracellular polymeric substances extracted from Synechocystis sp. PCC6803. Ecotoxicology and Environmental Safety 2020, 111200. doi:10.1016/j.ecoenv.2020.111200. Nguyen, T.D.P., Vo, C.T., Nguyen-Sy, T., Tran, T.N.T., Le, T.V.A., Chiu, C.Y., Sankaran, R., Show, P.L., 2020. Utilization of microalgae for self-regulation of extracellular polymeric substance production. Biochemical Engineering Journal 159, 107616. doi:10.1016/j.bej.2020.107616. Noguchi, M., Aizawa, R., Nakazawa, D., Hakumura, Y., Furuhashi, Y., Yan, S., Ninomiya, K., Takahashi, K., Honda, R., 2021. Application of real treated wastewater to starch production by microalgae: Potential effect of nutrients and microbial contamination. Biochemical Engineering Journal 169, 107973. doi:10.1016/j. bej.2021.107973. Norsker, N.H., Barbosa, M.J., Vermuë, M.H., Wijffels, R.H., 2011. Microalgal production: A close look at the economics. Biotechnology Advances 29, 24–27. doi:10.1016/j.biotechadv.2010.08.005. Panda, B., Jain, P., Sharma, L., Mallick, N., 2006. Optimization of cultural and nutritional conditions for accumulation of poly-β-hydroxybutyrate in Synechocystis sp. PCC 6803. Bioresource Technology 97, 1296–1301. doi:10.1016/j.biortech.2005.05.013. Paniagua-Michel, J., Olmos-Soto, J., Morales-Guerrero, E.R., 2014. Algal and microbial exopolysaccharides: New insights as biosurfactants and bioemulsifiers. Advances in Food and Nutrition Research 73, 221–257. doi:10.1016/B978-0-12-800268-1.00011-1. Pawlowski, A., Guzmán, J.L., Berenguel, M., Acién, F.G., Dormido, S., 2017. Event-based control systems for microalgae culture in industrial reactors. In: Tripathi, B.N., Kumar, D. (Eds.), Prospects and challenges in algal biotechnology. Springer Singapore, pp. 1–48. doi:10.1007/978-981-10-1950-0_1. Pelegrine, D.H.G., Gasparetto, C.A., 2005. Whey proteins solubility as function of temperature and pH. Journal of Food Science and Technology 38, 77–80. doi:10.1016/j.lwt.2004.03.013. Posten, C., 2009. Design principles of photo-bioreactors for cultivation of microalgae. Engineering in Life Sciences 9, 165–177. doi:10.1002/elsc.200900003. Price, S., Kuzhiumparambil, U., Pernice, M., Ralph, P.J., 2020. Cyanobacterial polyhydroxybutyrate for sustainable bioplastic production: Critical review and perspectives. Journal of Environmental Chemical Engineering 8, 104007. doi:10.1016/j.jece.2020.104007. Prybylski, N., Toucheteau, C., El Alaoui, H., Bridiau, N., Maugard, T., Abdelkafi, S., Fendri, I., Delattre, C., Dubessay, P., Pierre, G., Michaud, P., 2020. Bioactive polysaccharides from microalgae. In: Jacob-Lopes, E., Maroneze, M.M., Queiroz, M.I., Zepka, L.Q. (Eds.), Handbook of microalgae-based processes and products. Cambridge: Academic Press, pp. 533–571. Roh, H., Lee, J.S., Choi, H.I., Sung, Y.J., Choi, S.Y., Woo, H.M., Sim, S.J., 2021. Improved CO2-derived polyhydroxybutyrate (PHB) production by engineering fast-growing cyanobacterium Synechococcus elongatus UTEX 2973 for potential utilization of flue gas. Bioresource Technology 327, 124789. doi:10.1016/j. biortech.2021.124789. Roja, K., Sudhakar, D.R., Anto, S., Mathimani, T., 2019. Extraction and characterization of polyhydroxyalkanoates from marine green alga and cyanobacteria. Biocatalysis and Agricultural Biotechnology 22, 101358. doi:10.1016/j.bcab.2019.101358. Rosa, G.M., Morais, M.G., Costa, J.A.V., 2019. Fed-batch cultivation with CO2 and monoethanolamine: Influence on Chlorella fusca LEB 111 cultivation, carbon biofixation and biomolecules production. Bioresource Technology 273, 627–633. doi:10.1016/j.biortech.2018.11.010. Rueda, E., García-Galán, M.J., Ortiz, A., Uggetti, E., Carretero, J., García, J., Díez-Montero, R., 2020. Bioremediation of agricultural runoff and biopolymers production from cyanobacteria cultured in demonstrative full-scale photobioreactors. Process Safety and Environment Protection 139, 241–250. doi:10.1016/j. psep.2020.03.035. Ruiz, C.A.S., Baca, S.Z., Van den Broek, L.A.M., Van den Berg., C., Wijffels, R.H., Eppink, M.H.M., 2020. Selective fractionation of free glucose and starch from microalgae using aqueous two-phase systems. Algal Research 46, 101801. doi:10.1016/j.algal.2020.101801.

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Sharma, S.K., Mudhoo, A., 2011. A handbook of applied biopolymer technology: Synthesis, degradation and applications. Royal Society of Chemistry. Shen, L., Li, Z., Wang, J., Liu, A., Li, Z., Yu, R., Wu, X., Liu, Y., Li, J., Zeng, W., 2018. Characterization of extracellular polysaccharide/protein contents during the adsorption of Cd (II) by Synechocystis sp. PCC6803. Environmental Science and Pollution Research International 25, 20713–20722. doi:10.1007/s11356-018-2163-3. Shrivastav, A., Mishra, S.K., Mishra, S., 2010. Polyhydroxyalkanoate (PHA) synthesis by Spirulina subsalsa from Gujarat coast of India. International Journal of Biological Macromolecules 46, 255–260. doi:10.1016/j. ijbiomac.2010.01.001. Siahbalaei, R., Kavoosi, G., Noroozi, M., 2021. Protein nutritional quality, amino acid profile, anti-amylase and anti-glucosidase properties of microalgae: Inhibition and mechanisms of action through in vitro and in silico studies. Lebensmittel-Wissenschaft & Technologie 150, 112023. doi:10.1016/j.lwt.2021.112023. Silva, C.K., Costa, J.A.V., Morais, M.G., 2018. Polyhydroxybutyrate (PHB) synthesis by Spirulina sp. LEB 18 using biopolymer extraction waste. Applied Biochemistry and Biotechnology 185, 822–833. doi:10.1007/s12010017-2687-x. Singh, M.K., Rai, P.K., Rai, A., Singh, S., Singh, J.S., 2019. Poly-β-Hydroxybutyrate production by the cyanobacterium Scytonema geitleri Bharadwaja under varying environmental conditions. Biomolecules 9, 198. doi:10.3390/biom9050198. Singh, R.N., Sharma, S., 2012. Development of suitable photobioreactor for algae production: A review. Renewable and Sustainable Energy Reviews 16, 2347–2353. doi:10.1016/j.rser.2012.01.026. Sivaramakrishnan, R., Suresh, S., Pugazhendhi, A., Pauline, J.M.N., Incharoensakdi, A., 2020. Response of Scenedesmus sp. to microwave treatment: Enhancement of lipid, exopolysaccharide and biomass production. Bioresource Technology 312, 123562. doi:10.1016/j.biortech.2020.123562. Suzuki, E., Suzuki, R., 2013. Variation of storage polysaccharides in phototrophic microorganisms. Journal of Applied Glycoscience 60, 21–27. Taghavijeloudar, M., Kebria, D.Y., Yaqoubnejad, P., 2021. Simultaneous harvesting and extracellular polymeric substances extrusion of microalgae using surfactant: Promoting surfactant-assisted flocculation through pH adjustment. Bioresource Technology 319, 124224. doi:10.1016/j.biortech.2020.124224. Teuling, E., Schrama, J.W., Gruppen, H., Wierenga, P.A., 2019. Characterizing emulsion properties of microalgal and cyanobacterial protein isolates. Algal Research 39, 101471. doi:10.1016/j.algal.2019.101471. Tiwari, O.N., Muthuraj, M., Bhunia, B., Bandyopadhyay, T.K., Annapurna, K., Sahu, M., Indrama, Th., 2020. Biosynthesis, purification and structure-property relationships of new cyanobacterial exopolysaccharides. Polymer Testing 89, 106592. doi:10.1016/j.polymertesting.2020.106592. Torzillo, G., Zittelli, G.C., 2015. Tubular Photobioreactors. In: Prokop, A., Bajpai, R.K., Zappi, M.E. (Eds.), Algal biorefineries: Products and refinery design. Springer, pp. 187–212. doi:10.1007/978-3-319-20200-6_5. Trabelsi, L., Ben Ouada, H., Zili, F., Mazhoud, N., Ammar, J., 2013. Evaluation of Arthrospira platensis extracellular polymeric substances production in photoautotrophic, heterotrophic and mixotrophic conditions. Folia Microbiologica 58, 39–45. doi:10.1007/s12223-012-0170-1. Trabelsi, L., Ouada, H.B., Bacha, H., Ghoul, M., 2009. Combined effect of temperature and light intensity on growth and extracellular polymeric substance production by the cyanobacterium Arthrospira platensis. Journal of Applied Phycology 21, 405–412. doi:10.1007/s10811-008-9383-8. Troschl, C., Meixner, K., Fritz, I., Leitner, K., Romero, A.P., Kovalcik, A., Sedlacek, P., Drosg, B., 2018. Pilot-scale production of poly-β-hydroxybutyrate with the cyanobacterium Synechocytis sp. CCALA192 in a non-sterile tubular photobioreactor. Algal Research 34, 116–125. doi:10.1016/j.algal.2018.07.011. Villarcorte, L.O., Ekowai, Y., Neu, T.R., Kleijn, J.M., Winters, H., Amy, G., Schippers, J.C., Kennedy, M.D., 2015. Characterisation of algal organic matter produced by bloom-forming marine and freshwater algae. Water Research 73, 216–230. doi:10.1016/j.watres.2015.01.028. Vo, H.N.P., Ngo, H.H., Guo, W., Liu, Y., Chang., S.W., Nguyen, D.D., Zhang, X., Liang, H., Xue, S., 2020. Selective carbon sources and salinities enhance enzymes and extracellular polymeric substances extrusion

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of Chlorella sp. for potential co-metabolism. Bioresource Technology 303, 122877. doi:10.1016/j. biortech.2020.122877. Wang, B., Lan, C.Q., Horsman, M., 2012. Closed photobioreactors for production of microalgal biomasses. Biotechnology Advances 30, 904–912. doi:10.1016/j.biotechadv.2012.01.019. Wang, L., Addy, M., Lu, Q., Cobb, K., Chen, P., Chen, X., Liu, Y., Wang, H., Ruan, R., 2019. Cultivation of Chlorella vulgaris in sludge extracts: Nutrient removal and algal utilization. Bioresource Technology 280, 505–510. doi:10.1016/j.biortech.2019.02.017. Wang, Q., Yu, Z., Wei, D., 2020. High-yield production of biomass, protein and pigments by mixotrophic Chlorella pyrenoidosa through the bioconversion of high ammonium in wastewater. Bioresource Technology 313, 123499. doi:10.1016/j.biortech.2020.123499. Wang, Z., Chen, S., Chen, S., Chu, F., Zhang, R., Wang, Y., Fan, D., 2019. Preparation and characterization of a soy protein based bio-adhesive crosslinked by waterborne epoxy resin and polyacrylamide. RSC Advances 9, 35273–35279. doi:10.1039/C9RA05931H. Yang, Q., Xu, W., Luan, T., Pan, T., Yang, L., Lin, L., 2021. Comparative responses of cell growth and related extracellular polymeric substances in Tetraselmis sp. to nonylphenol, bisphenol A and 17α-ethinylestradiol. Environmental Pollution 274, 116605. doi:10.1016/j.envpol.2021.116605. Yu, H., Jia, S., Dai, Y., 2010. Accumulation of exopolysaccharides in liquid suspension culture of Nostoc flagelliforme cells. Biotechnology and Applied Biochemistry 160, 552–560. doi:10.1007/s12010-008-8428-4. Zhang, J., Liu, L., Ren, Y., Chen, F., 2019. Characterization of exopolysaccharides produced by microalgae with antitumor activity on human colon cancer cells. International Journal of Biological Macromolecules 128, 761–767. doi:10.1016/j.ijbiomac.2019.02.009. Zhang, L., Chen, L., Wang, J., Chen, Y., Gao, X., Zhang, Z., Liu, T., 2015. Attached cultivation for improving the biomass productivity of Spirulina platensis. Bioresource Technology 181, 136–142. doi:10.1016/j. biortech.2015.01.025. Zhang, Z., Tan, Y., Wang, W., Bai, W., Fan, J., Huang, J., Wan, M., Li, Y., 2018. Efficient heterotrophic cultivation of Chlamydomonas reinhardtii. Journal of Applied Phycology 31, 1545–1554. doi:10.1007/s10811-018-1666-0. Zhong, G., Pan, W., Huang, Z., Guo, K., Hu, J., Liu, P., Chen, S., Wang, Y., Ai, L., Huang, Z., 2021. Physicochemical and geroprotective comparison of Nostoc sphaeroides polysaccharides across colony growth stages and with derived oligosaccharides. Journal of Applied Phycology 3 (3), 939–952. doi:10.1007/s10811-021-02383-6. Zhu, N., Ye, M., Shi, D., Chen, M., 2017. Reactive compatibilization of biodegradable poly(butylene succinate)/Spirulina microalgae composites. Macromolecular Research 25, 165. doi:10.1007/s13233-0175025-9 –117. Zittelli, G.C., Biondi, N., Rodolfi, L., Tredici, M.R., 2013. Photobioreactors for mass production of microalgae. In: Richmond, A., Hu, Q. (Eds.), Handbook of microalgal culture: Applied phycology and biotechnology. John Wiley & Sons, Ltd, pp. 225–266. doi:10.1002/9781118567166.ch13.

12 Production of biohydrogen in photobioreactors Quanguo Zhang, Zhiping Zhang, Huan Zhang, Yameng Li KE Y LABO RATO RY O F NEW M ATERI A L S A N D E Q U I P ME N T F O R R E N E WA B L E E N E R G Y O F MINI S TRY O F AGRI CULTURE AND R U R A L A F FA I R S O F C H I N A , H E N A N A G R I C U LT U R A L U N I V E R S I T Y, Z H E N G Z H O U , C H I N A

12.1 Introduction Hydrogen energy has attracted much more attention due to the advantages of high calorific value, clean, and environmentally friendly. Compared with the traditional thermochemical hydrogen production technology, biological fermentative hydrogen production is shown to have great potential for the development of a practical biohydrogen system which can be conducted at normal temperature and pressure, and a wide source of substrates such as agricultural waste straw, food waste, animal manure, and industrial wastewater. Biological fermentative hydrogen production technology can be divided into dark fermentation hydrogen production and photo fermentation hydrogen production. Dark fermentation hydrogen production from organic matter by dark fermentation bacteria was carried out in the absence of light conditions. For photo fermentation hydrogen production, light is an indispensable role, which provides photoelectron for the hydrogen production metabolic activities of photosynthetic bacteria. Dark fermentation hydrogen production shows the advantages of a higher hydrogen production rate and shorter fermentation period, however, the lower substrate conversion efficiency is detected in dark fermentation because by-products volatile fatty acids (VFAs) are also produced in the process, which could not be adopted to produce hydrogen by dark fermentation bacteria resulting in low substrate conversion efficiency (hydrogen yield is limited to 30% of the theoretical) (Trchounian et  al., 2017), however, VFAs can be transferred into hydrogen by photosynthetic bacteria in the presence of light (Li et al., 2020b; Sağır et al., 2018). Therefore, photo fermentation hydrogen technology shows higher substrate conversion efficiency as compared to dark fermentation hydrogen production technology. During photo fermentation hydrogen production, much more substrates are consumed by photosynthetic bacteria to produce hydrogen, meanwhile, the VFAs produced during fermentation can also be used by photosynthetic bacteria to produce hydrogen, resulting in the decease of the cost of fermentation effluents treatment. At present, photo fermentation hydrogen production has attracted much more attention, in order to overcome the bottleneck of hydrogen production Current Developments in Biotechnology and Bioengineering. DOI: https://doi.org/10.1016/B978-0-323-99911-3.00004-X Copyright © 2023 Elsevier Inc. All rights reserved.

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by microbial fermentation, some scholars have adopted a series of research programs, such as screening of high-performance bacteria, optimization of hydrogen production process, and design of high efficiency reactor (Krishnan et al., 2019; Sattar et al., 2016). In addition, some scholars enhanced the metabolic performance of hydrogen-producing microorganisms by adding trace reagents to improve the energy of substrate transferring to hydrogen and decrease the energy of substrate transferring to bacteria growth and by-products including organic acids, alcohol, and acetone. A photochemical reactor is a kind of device which can be used in the culture of photosynthetic microorganism biochemical catalytic reaction, which provides a microenvironment for the survival and metabolism of microorganisms to protect the normal metabolism of microorganisms from the interference of the external environment. The photochemical reactor with excellent performance needs strict structure, good liquid mixing performance, high light and heat transfer rate, and suitable detection and control device. The design principle of photochemical reactor, light source distribution, biomass concentration, stirring, shear force, temperature control, and gas-liquid mass transfer rate should be taken into account which affected the performance of photochemical reactor. In general, the photobioreactor can be diverted into a batch operation reactor, semi-continuous reactor, and continuous reactor. During the batch operation reactor, the fermentation effluents are removed at the end of a fermentation cycle, and new fermentation broth is injected batch reactor, it is easy to control fermentation process. Many studies have been reported on photo fermentation hydrogen production with batch reactor. Li et al. (2017) used 150 mL flash as reactor to produce hydrogen from Platanus orientalis leaves by photosynthetic bacteria HAU-M1, the maximum hydrogen yield reached 64.10 mL/g TS. If part of fermentation medium is removed from reactor and replaced by fresh medium, which is defined as semi-continuous reactor. Wu et al. (2016) found semi-continuous mode showed better hydrogen production performance with acetate as carbon. Continuous reactor is time independent because inflow and outflow occur simultaneously, in which the hydrogen can be produced stably. Lu et al. (2018) studied the effect of substrate concentration on photo-fermentative hydrogen production in a self-designed 4 m3 pilot-scale baffled photo-fermentative hydrogen production reactor, the result showed that a maximum hydrogen production rate of 148.65 ± 4.19 mol/m3/d was obtained when organic loading rate was maintained at 20 g/L/d during continuous biohydrogen production with glucose as substrate. Different types of fermentation reactors are designed to adapt to different fermentation environments. The optimal design of photobioreactor is of great significance for the industrial application of photo fermentation technology. Photobioreactor with excellent performance requires tight structure, good liquid mixing performance, high thermal-mass transfer rate, and appropriate detection and control unit. Besides, light intensity and bacterial biomass are important parameters to be considered in photobioreactor design. Based on the above, some researchers have designed a variety of reactors for hydrogen production by photosynthetic bacteria in recent years. Different reactors have different light source distribution, solid-liquid mixing mode, biomass retention, and their rationality, practicability and hydrogen production performance need to be verified (Jinling Cai, 2014; Lin et al., 2011).

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12.2  Biohydrogen production in photobioreactor 12.2.1  Role of photobioreactor in biohydrogen production The bioreactor provides the necessary environment for biochemical reaction for hydrogen production by photosynthesis. During photo fermentation hydrogen production system, hydrogen is produced under the action of nitrogenase, the presence of oxygen could affect the activity of nitrogenase resulting in lower hydrogen production yield, anaerobic environment can be formed in photobioreactor to protect the activity of nitrogenase. During hydrogen production by some pure photosynthetic hydrogen producing bacteria, if non-hydrogen producing bacteria enter the reactor, partly which will consume the substrate to cell growth resulting in low amount of substrate consumed by photosynthetic hydrogen-producing bacteria, partly nonhydrogen producing bacteria may inhibit the activity of photosynthetic hydrogen-producing bacteria resulting in low hydrogen yield from substrate. Photobioreactor creates a microenvironment for hydrogen-producing bacteria, which enhances the synergy between strains, and increases the buffering capacity of hydrogen-producing bacteria to the external environment. During photo fermentation hydrogen production, the photobioreactor with excellent performance can increase the hydrogen production yield and energy efficiency.

12.2.2  Key factors of photobioreactor affecting biohydrogen production A photobioreactor is the key equipment of photosynthetic biological hydrogen production system. Its purpose is to provide a suitable environment for the growth and metabolism of photosynthetic bacteria and maximize the production of hydrogen. In the process of photochemical reactor hydrogen production, the structure and operation method of the reactor are different, which will affect the transmission characteristics of light-heat-mass in the photochemical reactor, and then affect the hydrogen production process of photosynthetic organisms. Therefore, the design of biochemical reactor should fully grasp the biochemical reaction mechanism of hydrogen-producing microorganisms and have a clear understanding of the factors affecting the transmission process. Some scholars believe that in order to optimize the process of photofermentative hydrogen production to the greatest extent, the design and selection of photobioreactor should meet the following characteristics: (1) good seal, (2) good transparency, maximize the ability of light penetration, (3) high surface area volume ratio to better and more uniform light distribution, (4) the operation requirements of biochemical reaction, which should be suitable for microbial growth and metabolism, such as anaerobic and aseptic environment, (5) providing good mixing performance and promoting light, heat and mass transfer, (6) the material should be durable, easy to clean and sterilize, and do not participate in the reaction, and (7) the system should have practical pipeline and instrument control components, such as pH value, temperature, viscosity, etc. (Argun & Kargi, 2010a; Tian et al., 2010). Vertical, flat, tubular, and spiral tubular reactors are often used in the process of photosynthetic hydrogen production (Dasgupta et  al., 2010). At the same time, because the stirring process can make the distribution of light and temperature more uniform, and accelerate the contact between

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photosynthetic bacteria and hydrogen-producing substrate, it can increase hydrogen production and remove the hydrogen and carbon dioxide generated in the reactor at the same time. Therefore, in the process of large-scale hydrogen production, it is generally necessary to design the stirring link. All types of reactors, can be divided into two modes of hydrogen production: batch hydrogen production and continuous hydrogen production. In the process of batch hydrogen production reactor, hydrogen production generally decreases when photosynthetic bacteria grew to a stable stage, the continuous hydrogen production mode can prolong the logarithmic growth period of photosynthetic bacteria and ensure maximum hydrogen production. Some studies show that the adoption of continuous photochemical reactor greatly improves the hydrogen production rate, reaching 180 mL of H2−1•h−1 (Zürrer & Bachofen, 1982). It is very important to maintain the proper concentration of photosynthetic bacteria in the whole hydrogen production cycle. Through the study of the light-heat-mass transport characteristics and its influencing factors in the process of hydrogen production, many problems and limiting factors affecting hydrogen production were found, and many innovative designs were put forward which are conducive to improving hydrogen production performance and light energy utilization. Table 12.1 compares the operation methods of different types of reactors and the performance of photo fermentative hydrogen production. Through the analysis of the hydrogen production of photochemical reactors with different forms and different light supply modes, the results show no matter at the laboratory level or pilot test level, the design and operation of the photochemical reactor should fully consider how to realize the correct selection of light source, how to improve the utilization of light energy, and how to ensure the stable growth and metabolism environment of photosynthetic bacteria. In addition to mastering the design and operation, genetic engineering technology should be used to improve photosynthetic hydrogen-producing bacteria to increase their light energy capture ability, weaken their hydrogen absorbing enzyme activity and enhance their tolerance to inhibitory by-products, it is also an important means to control the distribution of light and temperature field in the multiphase flow of biomass photosynthetic hydrogen production by using various analysis software.

12.2.3  Light-heat-mass transfer mechanisms in photobioreactor The transfer characteristics of photochemical reactor mainly include the transfer characteristics of light, heat and mass. In the process of hydrogen production from biomass powder, when the solid-liquid ratio is small, it is conducive to the mass transfer and heat transfer process of microorganisms. However, due to the existence of factors such as the viscosity, turbidity, and uniformity of the reaction liquid itself, it is very sensitive to the change of temperature and also has a great impact on the light intensity and distribution and transmission characteristics. The flow characteristics of biomass multiphase flow, the transfer and mass transfer of light and heat energy directly affect the hydrogen production process of photosynthetic microorganisms. The transmission and distribution of light energy in the photobioreactor are very complex, and can be divided into three parts: one part of the light energy enters the reactor through the wall of the reactor and is captured by photosynthetic bacteria. After a series of complex transmission and transformation, light is used for the metabolism of photosynthetic bacteria to produce

moderate/high

low moderate/high

high

low

High

Outdoor (using sunlight) LED light source

High

Plate reactor

High

Solar fiber

low

moderate/high

high

Traditional type

Hydrogen production capacity

Immobilized cells moderate (incandescent lamp)

Operational stability

Types of reactors

The light wave length of LED is beneficial to the growth of photosynthetic bacteria and increases the light energy conversion rate; Different forms can be nested into various reactors; Low energy consumption, long life and low heat production.

No electricity to supply light.

During the continuous operation, the immobilized cells can enhance the retention period of cells and reduce the loss under short HRT; increase the contact between bacteria and fermentation substrate, and improve the hydrogen production rate, hydrogen production, and substrate conversion rate. Large area light distribution and short light path; Low operation cost and clean up easily; high cell density and hydrogen production.

The side light fiber is used to collect sunlight to the maximum extent; the built-in light source ensures the uniform distribution of light; It can reduce the shadowing effect caused by the increase of cell concentration.

It is easy to operate by using natural light or artificial light source to supply light.

Advantages

It is not conducive to large-scale application, and the cost is slightly higher; It is difficult to control temperature; Easy to conjunctive, high head pressure. Poor stability, unable to ensure stable light intensity, high operating costs.

Low light-heat-mass transport capacity; light energy decreases exponentially with the increase of light path; weak growth ability of photosynthetic bacteria; Low hydrogen production capacity. Due to the periodicity and uncertainty of the sunlight, the light intensity fluctuates greatly; The use of optical fiber for light supply, light energy collection and transmission makes the cost increase, and the service life is short, and regular replacement increases the cost. Cell immobilization increases the space occupied, affect the light penetration, and reduces the utilization of light energy.

Disadvantages

Table 12.1  Hydrogen production capacity comparisons of different types of photo-bioreactors.

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hydrogen and synthesize intracellular substances; the other part of the light energy is absorbed by the reaction solution, converted into heat energy, and accumulated in the reaction solution; the rest is lost. Light energy participates in biochemical reactions in the form of radiant energy. Light energy transfer has significant effects on the growth, metabolism, light energy conversion efficiency and hydrogen production capacity of photosynthetic bacteria. Improving the light transfer efficiency in the photobioreactor has become one of the bottlenecks in its large-scale application. Photobioreactor for photosynthetic hydrogen production is a typical multiphase flow reaction system with obvious coexistence of gas-liquid and solid phases. The studies of mass transfer characteristics of photochemical reactor mainly refers to the study of the flow characteristics of the multiphase flow fluid in the photobiological hydrogen production system caused by different structures and operation modes of the photo biochemical reactor, and the influence of the rheological characteristics of the multiphase flow reaction fluid on the mass transfer performance of organic components in the process of hydrogen production and the hydrogen production characteristics of the photosynthetic bacteria degrading organic compounds through biochemical reactions. The main factors affecting mass transfer are: operating conditions (including temperature, pressure, stirring rate, etc.), physical and chemical properties of reaction liquid (viscosity and composition of reaction liquid, flow state of reaction liquid, biochemical reaction type, product inhibition, etc.), and structure of reactor (different types of reactors, design specifications of each part of reactor, design process of reactor stirring, etc.). The heat transfer characteristics of photochemical reactor directly affect the temperature of reaction solution. Most biochemical reactions are sensitive to temperature changes, and temperature is the main limiting factor for the growth and metabolism of photosynthetic bacteria. At the same time, it also has an impact on the diffusion of components in the reaction solution, matrix transformation, and biochemical reactions. The distribution of temperature field in photochemical reactor is usually affected by physical and chemical processes such as flow state, radiation heat transfer, evaporation heat transfer, biochemical reaction heat, thermophysical characteristics of reaction liquid, etc. only by fully considering each link, can the distribution of temperature field in photochemical reactor be more accurately described. In the process of photo fermentative hydrogen production, the activity of photosynthetic bacteria and the enzymes involved in the reaction are particularly sensitive to temperature changes. High or low temperature in some or all areas of the reactor may lead to low cell activity or even death. Therefore, it is necessary to study the thermal behavior of the photosynthetic hydrogen production system, and to grasp and control the internal heat transfer characteristics of the photochemical reactor is the most important to achieve efficient hydrogen production.

12.3  Operation parameters of photobioreactor in the biohydrogen production process 12.3.1  Raw material type The raw materials used for photosynthetic hydrogen production fermentation are widely distributed, which can be divided into lignocellulose biomass, starch waste, livestock manure,

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and organic wastewater. Different raw materials with different compositions show different hydrogen production potential. Agricultural waste and forestry waste are representative lignocellulosic biomass. Lignocellulose is an organic mixture composed of cellulose, hemicellulose, and lignin, which can be hydrolyzed into monosaccharide organic compounds by cellulase and then used for hydrogen production. Zhang et al. (2014) used cellulase to hydrolyze different types of agricultural residues, and then the reducing sugars obtained from different types of agricultural residues were used to photo fermentation hydrogen production by HAU-M1, the hydrogen yield of corncob, corn stover, sorghum stover, rice straw, soybean stalk and cotton stalk reached 230.09, 145.75, 150.39, 240.26, 130.65, and 119.29 mL, respectively. Jiang et al. (2021) studied the photo fermentation hydrogen production potential by reusing feedstock of Arundo donax L, the result showed the total hydrogen yield could reach 331.8 mL/U. Forestry waste is also a potential substrate for hydrogen production, which is in carbohydrates. Wang et al. (Yi et al., 2020) exploited the role of ultrafine pretreatment to Paulownia biomass as sole a carbon source to evaluate photo fermentation biohydrogen production potential, and found the hydrogen yield could reach 82.0 mL/g substrate. Li et al. (2017) used the Platanus orientalis leaves to produce hydrogen through simultaneous saccharification fermentative method with mixed photosynthetic bacteria, and optimized the fermentation process with central composite design, the results showed the maximum hydrogen yield of 65.03 ml H2/g TS was obtained at the conditions of initial pH of 6.18, temperature of 35.59°C, and inoculation amount of 26.29% (v/v). Shrub landscaping waste is also a representative forestry waste, Yue et al. (2021) selected eight of shrub landscaping wastes (Photinia fraseri, Buxus megistophylla, Buxus sinica, Pittosporum tobira, Sabina Chinensis, Berberis thunbergii, Ligustrum vicaryi, and Ligustrum quihoui) as substrate to photo fermentation hydrogen production, and buxus megistophylla was found to be the most suitable substrate for photo fermentation hydrogen production, the maximum hydrogen yield could reach 73.82 H2/g TS. The waste starch mainly comes from food waste and food processing, which can be hydrolyzed into glucose, and used to produce hydrogen. Adessi et al. (2018) investigated the hydrogen production potential from bread wastes by photo fermentation by Rhodopseudomonas palustris 42O L, found the hydrogen yield reached 3.1 mol H2/mol glucose. Hu et al. (2020) evaluated the biohydrogen yield potential from potato residue collected from a student canteen, firstly using α-amylase to hydrolyze potato residue, and then enzymatic hydrolysate was used to photo fermentation hydrogen production, it was found that the maximum hydrogen yield (642 ± 22 mL) and highest hydrogen production rate (77.78 mL/(L•h)) were obtained at initial pH of 7. Assawamongkholsiri et al. (2018) investigated the hydrogen production from sugar manufacturing plant wastewater by Rhodobacter sp. KKU-PS1, the batch experiments were carried out 1.7 L photo-bioreactor with a working volume of 1.2 L, the hydrogen production rate could reach 9.05 mL H2/L•h. At present, many scholars also used microalgae for hydrogen production fermentation, microalgae have high biomass easy growth, low cost and rich cellulose substances which just meet the requirements of raw materials for biohydrogen production. Liu et al. (2020) used cellulase and protease to hydrolyze the chlorella vulgaris and optimized the photo fermentation hydrogen production process from chlorella vulgaris, found the hydrogen yield reach the maximum value of 260.8 mL under inoculation amount of 10%, substrate concentration was 25 g/L and cellulase: protease of 3:2.

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12.3.2  Initial pH In the biological process, initial pH displays a significant effect on hydrogen producing performance of PSB by affecting FeFe-hydrogenase activity and metabolic pathway. The lower or higher pH can lead to poisonous photosynthetic bacteria and reducing biohydrogen yield caused by the metabolic shift from acidogenesis to solventogenesis. Hu et al. (2020) evaluated the effect of initial pH varying from 5 to 9 on photo-fermentation biohydrogen production from starch agricultural leftover in a working volume of 150 mL conical flasks, it was found that the maximum hydrogen yield (642 ± 22 mL) and highest hydrogen production rate (77.78 mL/ (L•h)) were obtained at initial pH of 7. Zhang et al. (2021) studied the effects of initial pH on co-digestion photo fermentative hydrogen production from duckweed and corn straw, when the mix ratio of duckweed and corn straw was 5:1, the optimal initial pH was 8, under which the hydrogen production yield reached the maximum value of 85.6 mL/g TS. Yue et al. (2021) optimized the effect of initial pH on simultaneous saccharification photo fermentation hydrogen from Buxus megistophylla, results showed that the optimization initial pH was 6.78. Potential accumulation of organic acids and decrease of pH are the major problems in batch operation. Zagrodnik and Laniecki (2015) compared the hydrogen yield from 0 under pH control and uncontrolled, results have shown that pH control at pH 7.5 increased photo fermentative hydrogen production from 0.966 to 2.502 L H2/L medium when compared to the uncontrolled process.

12.3.3  Substrate concentration Substrates, also known as carbon sources, provide energy for the growth and hydrogen production of photosynthetic bacteria. Low substrate concentration will lead to an insufficient supply of organic matter resulting in low hydrogen yield, high substrate concentration will result in inhibition effect, because under a high substrate concentration environment, the organic matter is not utilized rapidly, the fermentation environment will be acidified, in which the activity of photosynthetic bacteria decrease or even die. Fermentation substrates provide carbon, nitrogen, and trace elements for microbial metabolism, different types of substrates contain different carbon and nitrogen elements leading to different substrate concentrations for the same photosynthetic bacteria. Shrub landscaping waste Buxus megistophylla composing of 42.49% C, 5.73% H, 1.19% N, and 41.08% O was used substrate to produce hydrogen by photo fermentation by mixed photosynthetic bacteria HAU-M1, the optimal substrate was 21.49 g/L, in which the hydrogen yield reached the maximum value of 73.82 mL/g TS (Yue et al., 2021). Lu et al. (Zhang et al., 2021) used alfalfa consisting of cellulose of 38.25%, hemicellulose of 26.95% and lignin of 13.03% as the substrate of photo fermentation hydrogen production by HUA-M1, found the optimal substrate concentration of 31.23 g/mL, under which the highest hydrogen yield of 55.81 mL/g substrate was obtained. Different types of substrate and fermentation bacteria will cause the difference in the most substrate concentration. Policastro et al. (2020) investigated single-stage photo fermentation of winery wastewater, experiments were conducted using a purple nonsulfur bacteria mixed consortium, subject to variable nutrient conditions, to analyze the effect

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of initial chemical oxygen demand and the available nitrogen source on the metabolic response, the hydrogen could reach the maximum value of 468 mL/L at chemical oxygen demand of 1500 mg/L. Lu et al. (2018) studied the effect of substrate concentration on photo-fermentative hydrogen production was studied with a self-designed 4 m3 pilot-scale baffled photo-fermentative hydrogen production reactor, hydrogen production rate increased when organic loading rate was increased from 3.3 to 20 g/L/d, then decreased when organic loading rate was further increased to 25 g/L/d. A maximum HPR of 148.65 ± 4.19 mol/m3/d was obtained when organic loading rate was maintained at 20 g/L/d during continuous bio-hydrogen production.

12.3.4  Mixing methods During photo fermentation, some substrates have the characteristics of specific physical properties of heterogeneity, low density, and high water-holding capacity, which make it not uniformly distributed inside of the reactor, resulting in low hydrogen production potential and substrate conversion efficiency. Giving that, mixing methods are proposed due to it can prevent stratification, keep the solids suspension and homogenize the contents of reactors. Mixing intensity, as one of the key operational variables, has direct effect on performance of anaerobic fermentation. Too high mixing intensity showed a negative effect on substratemicrobe aggregates, resulting in instable performances and low gas production. Too low mixing intensity led to sedimentation and floatation of the substrate, gas evolution could not be effectively improved (Castillo-Hernández et al., 2015). Optimal mixing intensity is closely related to the substrate concentration, substrate type, and mixing mode. Mechanical mixing, hydraulic mixing, and pneumatic mixing are the main mixing technology (Arooj et al., 2008; Han et al., 2016). Zhu et al. used oscillator to provide the shaking condition to enhance the mass transfer situation during photo fermentation hydrogen production in 180 mL conical flasks. Diverse shaking velocity (0, 80, 120, and 160 rpm) and substrate concentration (0, 2, 4, 6, 8, and 10 g) were studied, to evaluate the influence on the hydrogen yield capacity. The results showed that shaking could help to accelerate gas release, shorten the fermentation time, and improve hydrogen production rate. Hydrogen yield was significantly enhanced at high substrate concentration under shaking condition. The highest hydrogen yield of 57.08 ± 0.83, 57.62 ± 1.37, and 62.28 ± 0.84 mL/g-volatile solids (VS) were observed at shaking velocities of 80, 120, and 160 rpm with 6, 8, and 10 g corn stover powder, respectively. For some photobioreactors with baffles, the fermentation broth will flow up and down when passing through the baffle during continuous hydrogen production, which increases the mixing of liquids, resulting in high substrate conversion. Therefore, the baffled reactor is a hot research topic at present. Zhang et al. (2017) developed a 4 m3 pilot-scale baffled continuous-flow photoreactor and evaluated its photo-fermentative hydrogen production from wastewater that contains 10 g/L glucose using a functional consortium, resulted showed the fermentation broth was well mixed and the hydrogen yield from substrate was promoted. Meky et al. (2019) developed a novel lab-scale stand-alone circular dark/photo reactor for treatment of synthetic gelatinaceous wastewater and the enhancement of biohydrogen production using mixed microbial culture, the results showed that the reactor was efficient for the removal of chemical oxygen demand,

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the total chemical oxygen demand removal efficiency was recorded to be 78% and the hydrogen production rate was enhanced.

12.3.5 Temperature Temperature is among the most crucial factors governing the performance of enzymes, particularly nitrogenase which is optimum at 30°C, Therefore, most of the isolated strains of photosynthetic bacteria reported earlier for hydrogen production are mesophilic, performing best in the temperature range from 25 to 35°C (Assawamongkholsiri & Reungsang, 2015; Chen et al., 2017) Assawamongkholsiri and Reungsang reported an optimal hydrogen production at 25.6°C using R. sphaeroides KKU-PS1 (Assawamongkholsiri & Reungsang, 2015). R. sphaeroides DSM 1710 is optimal at an almost similar temperature, 26.8°C (Androga et al., 2014). At even 54.5°C, hydrogen production is more than at 28.2°C (Hu et al., 2017), which is in the normal range of optimal temperatures reported by several past studies (25–35°C) (Assawamongkholsiri & Reungsang, 2015). du Toit and Pott (2021) assessed the growth and hydrogen productivity of two closelyrelated strains of R. palustris acclimated to higher temperatures, revealing markedly increased strain-dependent optima than the 30°C previously accepted. Strain CGA009 grew 53% faster at 35°C, with a 2.4-fold higher hydrogen production rate, while at 40°C strain ATH 2.1.37 displayed 86% faster growth and 4-fold higher production rate, along with improved specific production and substrate conversion efficiency.

12.3.6  Lighting patterns Lighting is one of the key factors in photo-fermentation, since the process itself is highly dependent on light energy to generate the ATP required for H2 generation by irreversible nitrogenase action. One of the most straightforward optimization efforts is regarding light intensity. Light intensity defines the rate of energy transfer to photosynthetic bacteria in order to overcome the activation energy for the process to occur. Li et al. (2017) used response surface methodology with central composite design to optimize the light intensity during photo fermentation hydrogen by mixed bacteria HAU-M1, the light intensity of 3500 lx was suitable for mixed bacteria HAU-M1 to produce hydrogen in standing fermentation process. Agitation also influences light penetration and hence optimal light intensity. Optimal light intensity increases from 3000 to 4000 lux in non-agitated culture to 6000-7000 lx in shaking condition for the mixed HAU-M1 (Zhu et  al., 2018). Meanwhile, for photo fermentation hydrogen production, the supplement of light intensity was affected by mixing strength, in the work of Zhang et al. (2020) found dynamic light intensity (4000-7000-4000 lx) accompanied by dynamic mixing speed (50-15050 RPM) was the optimal condition. Real effluent from manufacturing or other fermentation processes may require higher intensity for better performance, as colloids, colored compounds, and leftover biomass may interrupt light penetration and reception by photosynthetic bacteria (Zagrodnik et  al., 2015). A combined dark-photo-fermentation process (single-stage) also needs a higher light intensity due to a similar reason. Light intensity of 10 klux is optimum for a combined process rather than 5 klux for R. sphaeroides RV (Argun & Kargi, 2010a, 2010b). In photosynthetic immobilized cultures, it was shown that transparent gel granule enhanced

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light utilization and thereby hydrogen production (Tian et al., 2009). In the work of Tian et al. (2010), in which glass beads were used for immobilization of Rhodopseudomonas palustris, they observed photoinhibition at high light intensities between 5000 and 8000 lux. However, a remarkably high LCE (56%) was achieved at 5000 lux.

12.3.7  Operation modes The mode of the operation and the type of the processes (e.g., batch, semi- continuous (fed-batch), continuous) play significant roles in microbial systems in terms of feasibility, efficiency, and cost of the systems. Batch mode is operated by consuming the initial given substrates, the reactions are time-dependent due to no materials flow in or out of bioreactor. Continuous mode is time independent because of inflow and outflow occur simultaneously. If part of fermentation medium is removed together with H2 producing bacteria and replaced by equal amount of fresh medium, the operation process is defined as semi-continuous (Li et  al., 2020a). Padovani et al. (2015) compared batch, semi-continuous (fed-batch), and continuous hydrogen production with Rhodopseudomonas palustris sp from acetate, the best performances were attained when operating the photobioreactor in fed-batch mode. A maximum hydrogen production rate of 15.21 mL(H2)/L h was achieved. 1.42 mol H2/mol acetic acid when the culture was operated in fed-batch mode, and 0.85 mol H2/mol acetic acid under a batch growth regimen. In the work of (Kim & Kim, 2012), a semi-continuous operation of photo-fermentative H2-producing reactor was attempted at various decanting volume ratios (DVR, decanting volume per day/total working volume, %), ranging 30–70%, using Rhodobacter sphaeroides KD131. H2 production was not efficient with showing low H2 yields of 0.2 and 0.5 mol H2/mol succinate added at 30% and 40% DVR, respectively. The low performance ascribed to the fact that over 70% of substrate electrons were diverted towards cell growth under these conditions. Meanwhile, cell growth was limited at DVR ≥ 50%; therefore, higher H2 yields (>2.0 mol H2/mol succinate added) were observed. Both the highest H2 yield of 3.7 mol H2/mol succinate added and production rate of 1494 mL H2/L-reactor/d were achieved at 60% DVR. Li et al. (2020a) used dark fermentation effluents as substrate to photo fermentation hydrogen production, the influence of different operation modes (batch, semicontinuous and continuous) on H2 production potential and electron distribution was investigated. Results from experiments indicated a better H2 production performance was obtained in semi-continuous system. Both the maximum average H2 production rate of 8.44 mL/h and substrate electrons partitioning to hydrogen of 37.71% were detected at 50% DVR) and 24 h feeding interval time, under which the H2 yield reached to 1386.22 ± 44.23 mL H2/g TOC. The low performance in batch mode ascribed to 56.39% substrate electrons were transferred to cell growth and soluble microbial products. For continuous mode, more substrate electrons were diverted toward soluble microbial products with the increase of hydraulic retention period due to the fact that longer cell retention, more chances are provided for cell lysis. However, Not all substrates are suitable for semi-continuous fermentation, the substrate with larger particle size is more suitable for batch fermentation due to poor fluidity.

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12.4  Light-heat-mass transfer properties of photobioreactor during biohydrogen production process 12.4.1  Light transfer properties The transmission and distribution of light energy in the photobioreactor are very complex, which can be divided into three parts: one part of the light energy enters the reactor through the wall of the reactor, and is captured by photosynthetic bacteria. After a series of complex transmission and transformation, it is used for the metabolism of photosynthetic bacteria to produce hydrogen and synthesize intracellular substances; the other part of the light energy is absorbed by the reaction solution, converted into heat energy, and accumulated in the reaction solution; the rest is lost. Light energy participates in biochemical reactions in the form of radiant energy. Light energy transfer has significant effects on the growth, metabolism, light energy conversion efficiency and hydrogen production capacity of photosynthetic bacteria. Improving the light transfer efficiency in the photobioreactor has become one of the bottlenecks in its large-scale application. The structure of photochemical reactor is various, and due to the mutual shielding and light absorption effect of photosynthetic bacteria and other suspended solids in the reaction solution, the light energy is continuously attenuated. At present, the Lamber Beer law in the classical optical theory is often used to describe the attenuation law of cell concentration and light path in the photochemical reactor on the light transmission process. The main factors affecting light energy transmission are light intensity, photoperiod, cell density, and reactor structure. Light intensity must meet the needs of photosynthetic bacteria for photosynthesis, otherwise, it will affect the efficiency of photosynthesis, and the amount and activity of bacteria will be weakened. The higher the light intensity is, the stronger the penetration of light energy in the reaction solution is. However, if the light intensity is too strong, it may exceed the light intensity limit that photosynthetic bacteria can tolerate and reduce the utilization rate of light energy. Under the unsuitable photoperiod, the growth and metabolism of photosynthetic bacteria will also be affected, and even accelerate their decline. The higher the cell density, the greater the shielding effect on light energy. The light intensity will decay rapidly in the reaction medium. The ordinary sunlight can only penetrate through the culture medium a few centimeters deep in the microalgae culture reactor, and not go deep into the interior. This also causes the common problems of uneven distribution of light sources and lack of light in the photochemical reactor. Different photochemical reactor structures (such as tubular, open, flat, etc.) and reactor materials (such as plastic, glass, plexiglass, or other transparent materials) will also affect their light transmission performance, and play a crucial role in the distribution of light sources. Light is the main energy source of photosynthesis in cells or tissues in the photochemical reactor. In the process of hydrogen production by photosynthetic organisms, ATP and free electrons with reduction capacity are consumed. An important factor for effective and efficient hydrogen production is to have sufficient ATP supply. ATP synthesis needs to be carried out under light, and the suitable wavelength is 522, 805, and 850 nm (Akkerman et al., 2002; Chen et al., 2006). Therefore, the light source type and light intensity should be fully considered in the process of selecting light source in the photochemical reactor. Miyake et al. used sunlight for biological hydrogen production, and the efficiency of light energy conversion

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reached 8% (Nakada et al., 1995). Akkerman et al. (2002) found that the maximum theoretical conversion rate of light energy is 10%. Many literatures have studied the light transmission characteristics of photochemical reactor, and the results showed that the light utilization rate was improved under low illumination, but the hydrogen production, cumulative hydrogen production and hydrogen production rate were decreased (Akkerman et al., 2002). However, if the light intensity is too high, it is also not conducive to the improvement of reaction efficiency. Light saturation during photosynthesis is also an important factor affecting hydrogen production and the growth and metabolism of photosynthetic bacteria. Excessive absorption of light and ineffective dissipation in the process of light radiation absorption should be avoided as far as possible (Melis, 2009). In order to enhance the efficiency of light energy conversion, maintain the appropriate cell concentration and create an efficient environment for biochemical reaction, it is very important to have the appropriate light intensity and wavelength, the uniform distribution of light source and the stirring in the reaction process. Stirring can make photosynthetic bacteria stay in the light area, and expose for a short time in the process of growth and metabolism, creating an alternating light and dark environment (Koku et al., 2003). Janssen et al. (2002) investigated the light intensity gradient in three different types of photochemical reactors, the light dark cycle in the reactor caused by stirring, and the photosynthetic efficiency. Vertical column reactor (airlift type and bubble type), plate reactor and tubular reactor are different in morphology and operation means. Cells circulate in the exposure area and dark area inside the reactor. The shorter the alternation time is, the better the photosynthetic efficiency is. The size of light transmission zone is related to the size of the reactor, cell concentration, wavelength of incident light, absorption rate, and other factors. The plate reactor has a good photochemical effect and high cell yield. The tubular reactor has higher efficiency of light energy conversion because of its short period of light-dark alternation. However, the traditional reactor uses an external light supply. Due to the distance between the light source and the reactor wall, the light intensity decays exponentially before reaching the reactor wall, which limits the light energy conversion rate (Zhang et al., 2014). Kumar et al. (2013) used the image analysis method based on the theory of three primary colors to analyze the light source distribution inside the reactor, studied the light distribution of the external light supply full mixing tank photochemical reactor, studied the distribution of different light sources, and obtained the distribution of light sources near the wall and inside the reactor, The improved beer Lamber law was established to predict the illumination in different cell concentrations and light intensity in the reactor (Kumar et al., 2013).

12.4.2  Heat distribution The heat transfer characteristics of photochemical reactor directly affect the temperature of reaction solution. Most biochemical reactions are very sensitive to temperature changes, and temperature is the main limiting factor for the growth and metabolism of photosynthetic bacteria. At the same time, it also affects the diffusion of components in the reaction solution, matrix transformation, and the progress of biochemical reactions. Therefore, it is necessary to study the thermal behavior of biomass multiphase flow photosynthetic hydrogen production system, and it is most important to grasp and control the internal heat transfer characteristics of the

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photochemical reactor. The temperature field distribution in a biochemical reactor is usually affected by the physical and chemical processes such as flow state, light radiation heat transfer, evaporation and heat dissipation in the reactor, heat of biochemical reaction, thermophysical characteristics of reaction liquid, etc. only by fully considering each link can the temperature field distribution in the reactor be described more accurately. In the process of photo fermentative hydrogen production, the activity of photosynthetic bacteria and the enzymes involved in the reaction are particularly sensitive to temperature changes. High or low temperature in some or all areas of the reactor may lead to low activity of bacteria, or even death. For the closed photo fermentative biohydrogen production reactor, the temperature is easy to gradually increase with the progress of the reaction, or even exceeds the optimal temperature range of photosynthetic bacteria. Therefore, heat transfer is an important limiting factor in the process of photo fermentative hydrogen production. The main factors affecting the heat transfer in the photochemical reactor are the physical and chemical properties of the reaction liquid (such as thermal conductivity, specific heat capacity, etc.), the rheological characteristics of the multiphase flow reaction liquid (such as viscosity, flow pattern, concentration distribution, etc.), the changes of the external space environment (such as light intensity, room temperature, etc.), the structure and heat transfer mechanism of the biochemical reactor, etc. However, up to now, there are few studies on the internal heat transfer characteristics of the biochemical reactor system from the perspectives of fluid flow and heat transfer mechanism, and there is no exact description of the heat transfer in the multi-phase flow reaction system of photo fermentative photosynthetic biological hydrogen production.

12.4.3  Metabolism of substrate and electron transfer Photobioreactor for photosynthetic hydrogen production is a typical multiphase flow reaction system with obvious coexistence of gas-liquid and solid phases. The main factors affecting mass transfer are: operating conditions (including temperature, pressure, stirring rate, etc.), physical and chemical properties of reaction liquid (viscosity and composition of reaction liquid, flow state of reaction liquid, biochemical reaction type, product inhibition, etc.) and structure of reactor (different types of reactors, design specifications of each part of reactor, design process of reactor stirring, etc.). H2 and CO2 produced by metabolism of photosynthetic bacteria in biochemical reactor are in the reaction liquid and top space in the form of bubbles. The concentration of dissolved hydrogen in the reaction solution directly affects the metabolism of photosynthetic bacteria and the process of biochemical and enzymatic reaction, that is, hydrogen partial pressure affects mass transfer efficiency. The hydrogen production activity is restrained and the mass transfer efficiency is reduced with the increase of hydrogen partial pressure. Therefore, reducing the concentration of dissolved hydrogen in the reaction liquid will promote the transmission between the gas and liquid, and increase the hydrogen production of hydrogen production by photo fermentation. Because the rheological characteristics of multiphase flow in the photochemical reactor are closely related to the structure and size of the reactor, the concentration distribution of the solid phase and the physical and chemical properties of the liquid phase are different with different structures and sizes of the photochemical reactor. Temperature and pressure will affect

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the physical and chemical properties of the reaction solution and the biological activity of photosynthetic bacteria, and then affect the mass transfer capacity of the reactor. The viscosity, density, apparent tension of reaction solution, the diffusion coefficient of solute, and properties of biochemical reaction products all affect the mass transfer coefficient. Generally speaking, stirring can improve the mass transfer efficiency, because it can break the bubbles generated in the reaction process, make the reaction liquid fully mixed, maintain the suspension state of photosynthetic bacteria, and increase the contact with the reaction liquid. However, the heat production of biochemical reaction and agitation is accompanied by the fermentation process, and the heat accumulation is not conducive to the biochemical reaction, so it needs to be released to maintain a better reaction temperature. The reasonable mixing rate should also be paid attention to in the mixing process, because too fast may destroy the structure of photosynthetic bacteria and produce a large amount of foam to limit the mass transfer capacity.

12.5  Cases of typical photobioreactors adopted in biohydrogen production process 12.5.1  Tubular photobioreactor Tubular photobioreactor is the most commonly used photobioreactor in photobiological hydrogen production, Tubular photobioreactors have high surface to volume ratio and light transmittance when compared with flat panel photobioreactor, which can provide more effective illumination for photosynthetic bacteria, making it a promising configuration for photo fermentation. Fig. 12.1 schematically describes the self-designed continuous photo-fermentative hydrogen production system. It consisted of a long tubular photobioreactor, sample injection system, gas collection system, and control system. The working volume, interior dimeter and length of the PBR were 1.26 L, 4 cm, and 100 cm, respectively. There were 5 liquid sampling valves in the axial direction of the long tubular photobioreactor, and the distance between two adjacent sampling valves was 25 cm. Thus, the distributions of 5 sample valves were 0 cm, 25 cm, 50 cm, 75 cm, and 100 cm (site 1, 2, 3, 4, and 5) from the inlet, respectively. The PBR was operated at a temperature of 30 ± 1°C with hot water circulation. LED light (3 w) was applied as the main source of light. The angle of the long straight tubular reactor and horizontal plane was 30. The photobioreactor was equipped with a medium inlet on the bottom of the end placed on the horizontal plane and a waste effluent outlet on the top of the other end. Substrate solution and photosynthetic bacteria were maintained in two separate containers incubated at 30°C. They were continuously fed to the photobioreactor through a three-way valve using a peristaltic pump. The produced gas was collected by water displacement after a gas-liquid separator. The substrate container was loaded with corn stalk pith enzymatic hydrolysate (reducing sugar concentration of 10.5 g/L, initial pH of 7.3 ± 0.5). The photosynthetic bacteria container was loaded with nutrient medium and photosynthetic consortium (biomass density of 0.8 g/L in exponential phase) to achieve an inoculation of 30% (v/v) at the inlet. The time-course profiles of cell optical densities (presented by OD660), pH value, and reducing sugar concentration

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FIG. 12.1  Scheme of experimental system. 1. incubator; 2. photosynthetic bacteria container; 3. substrate container; 4. peristaltic pump; 5. LED light; 6. PBR; 7. liquid sampling valves1; 8. hot water inlet; 9. hot water outlet; 10. gas collector; 11. water container; 12. gas sampling valve; 13. gas-liquid separator; 14. liquid effluent container.

at different locations (site 1, 2, 3, 4, and 5) of the tubular photobioreactor under different HRTs (12, 18, 24, 30, and 36 h) are shown in Fig. 12.2. At site 1 (liquid sample valve 0 cm from the inlet), the cell densities under different HRTs were similar to each other, which increased to 2.0 in 72 h and then maintained at about 2.0 thereafter. The comparable cell optical densities under different HRTs could be attributed to the angle (30°C) of the long tubular photobioreactor with the horizontal plane, resulting in an accumulation of sediments on the bottom of the photobioreactor. In contrast, the pH values decreased sharply during the initial 12 h under different HTRs, and then decreased slowly in the range of about 5.0–6.0. Similarly, a sharp decrease of sugar concentrations was observed under different HRTs in the first 24 h, and then sugar concentrations maintained low level with minor decrease thereafter. Same phenomenon was found in previous studies, in which the time-change profiles of pH value and reducing sugar concentration were similar with the results in this study. At site 2 (25 cm from the inlet), a slight decrease of cell optical density was observed under different HRTs, while the cell optical density could still reach 2.0 after 60 h except for the HRT of 24 h and 36 h, both of whose highest cell optical density were 1.86 during the 240 h photo fermentation. While no significant differences (P > 0.05) of variability of pH value and sugar concentration between site 1 and 2 were found. When monitor location was further increased to site 3 (50 cm from the inlet), cell optical density could reach 2.0 only after 180 h, and the maximum cell optical density during the 240 h photo fermentation at HTR of 12, 18, 24, 30, and 36 h were 1.90, 2.1, 1.67, 2.1, and 1.8, respectively. The sugar concentration declined to a stable lever within 24 h with the pH value maintained in the range of 5.0–6.0. However, no cell optical density that higher than 2.0 was found at sites 4 (75 cm from the inlet) and 5 (100 cm from the inlet). The pH value and the sugar concentration at sites 4 and 5 showed the same pattern as those at sites 1 to 3.

Chapter 12 • Production of biohydrogen in photobioreactors  285

FIG. 12.2  Time-course profiles of cell optical density, pH, and sugar at different sites of the self-designed long tubular PBR under different HRTs.

The long tubular photobioreactor was operated in continuous mode with one HRT at a time during the 240 h photo fermentation and then gradually increase the HRT from 12 to 36 h (succession). The time-course profiles of cumulative gas productions and hydrogen content are shown in Fig. 12.3. The entire process was continuous regime whose purpose was to incubate bacteria, aiming for integrating microbial growth and hydrogen production in the tubular PBR simultaneously. The cumulative gas production under 5 HRTs were 7951 mL, 9260 mL, 9135 mL, 8612 mL, and 7126 mL, respectively. The hydrogen content peaked at 48–96 h, and then decreased gradually, which indicated that the microbial community structure might have shifted during the 240 h photo fermentation resulting an unstable hydrogen production. Under the designed mode, the HRT of 24 h had the highest cumulative hydrogen production (2670 mL), which was 40.7%, 26.4%, 25.5%, and 20.3% higher than that obtained from the HRT of 12 h, 18 h, 30 h, and 36 h, respectively. Likewise, the highest hydrogen yield (211.9 mL/Lmedium) was also achieved at HRT of 24 h. The highest hydrogen yield is comparable with that (220 mL/L-waste) achieved by a previous study in which Rhodobacter sphaeroides O.U. 001 was used for hydrogen production from brewery wastewater.

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(A)

(B)

FIG. 12.3  Time-course profiles of cumulative gas production (A) and hydrogen content (B) under different HRTs.

In an appropriate range of HRT (12-24 h), the light conversion efficiency increased from 0.25% at HRT of 12 h to 0.42% at HRT of 24 h. In contrast, when HRT was further increased from 24 h to 36 h, the light conversion efficiency decreased from 0.42% to 0.20% instead. In a previous study, in which continuous hydrogen production was carried out with Rhodobacter capsulatus Hup mutant as inoculum and acetate as substrate, light conversion efficiency of 0.2% was obtained. The maximal hydrogen production rate of 38.4 mL/L/h was also observed at HRT of 24 h. As a result, the long tubular PBR performed at HRT of 24 h was considered to be the optimum condition for photo-fermentative hydrogen production from corn stalk pith hydrolysate under continuous mode, since HRT of 24 h could satisfied the requirement of relative proportional fresh medium supplementation of the inoculum. Moreover, accumulation of hydrogen gas in the liquid phase when HRT extended, making hydrogen yield decrease due to the consumption of hydrogen through synthesis of ethanol or propionic acid, however, although shortened HRT can eliminate hydrogen consumption problems, can decease hydrogen yield by reducing the contact time between microbe and medium.

12.5.2  Circulating tank photobioreactor The photosynthetic biohydrogen production reactor is mainly composed of reactor tank, reaction liquid mixing and temperature control, sunlight collection and transmission, auxiliary light source part and parameter real-time monitoring equipment, as shown in Fig. 12.4. The photo fermentative hydrogen production experiments carried out in a reactor with an effective volume of 31.07 L. The raw material for hydrogen production was added into the reactor with 5 L immobilized particles by feeding pump. The total volume of reaction liquid was 30 L, and the temperature of reaction liquid was controlled at (31 ± 2)°C. The illumination was provided by sunlight with a wavelength of 380 nm–780 nm, which was collected and filtered in the reactor during the day, and then imported into the sleeve inside the reactor. At night or on cloudy days, incandescent lamps were used to assist illumination. Batch and continuous mode

Chapter 12 • Production of biohydrogen in photobioreactors  287

FIG. 12.4  Schematic diagram structure of bioreactor for photosynthetic biohydrogen production. 1. Gas production outlet; 2. Strain inoculation inlet; 3. Biochemical parameter adjustment outlet; 4. Bacterial liquid outlet; 5. Sampling port; 6. Reaction liquid circulation inlet; 7. Bacterial liquid circulation outlet/raw material inlet; 8. Biochemical parameter measuring equipment outlet; 9. Heat exchanger; 10. Biochemical parameter control equipment; 11. Sunlight collection and transmission equipment; 12. Auxiliary light source; 13. Reactor tank; 14. Circulating feeding pump; 15. Discharge port.

were used for hydrogen production. The mixed gas produced by the reaction passes through the gas flowmeter and enters the gas storage tank. The photosynthetic hydrogen producing mixed bacteria were cultured to the late logarithmic growth stage, and the solid bacteria were isolated at 8000 rpm. According to the ratio of sodium alginate to cell dry weight of 10:3, the photosynthetic bacteria were immobilized in 3% sodium alginate aqueous solution, and the immobilized particles were made into 1 mm. After crosslinking with 0.7% glutaraldehyde, the immobilized particles were loaded into the photosynthetic bioreactor. The substrate of photosynthetic hydrogen production was wet pig manure from Xinda breeding pig farm in the eastern suburb of Zhengzhou. After dark aerobic pretreatment for 4 days, the collected wet pig manure is diluted and soaked with a certain amount of tap water. Then, the pig manure sewage was filtered with 40 mesh sieve to remove impurities such as straw and sediment, and the chemical oxygen demand (COD) was diluted to about 5000 mg•L−1. The results of batch hydrogen production experiment from the beginning of the experiment to 120 h are shown in Table 12.2. The data in Table 12.2 showed that the total hydrogen production was 60.9 L in the process of batch hydrogen production within 120 h. The higher hydrogen production rate lasted for nearly 96 h, and the hydrogen production reached 60.1 L at this time. Only a small amount of hydrogen was produced after the 96 h of the experiment, so the total fermentation time of batch hydrogen production was 96 h. The average hydrogen production rate was 484.7 mL/L•d, and the maximum hydrogen production rate was 877.4 mL/L•d.

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Table 12.2  Total H2 produced and H2 generation rate in batch cultures process. Time (h)

12

24

36

48

60

72

84

96

108

120

Hydrogen production (L) Hydrogen production rate (mL/L•d)

4.3

13.2

26.8

37.4

45.5

52.1

57.5

60.1

60.7

60.9

277.4

574.1

877.4

683.9

522.6

425.8

348.4

167.7

38.7

12.9

After 48 h from the beginning of the experiment, the hydrogen producing substrate was discharged and added at a dilution rate of 0.06 h−1 every 12 h, and the COD of the substrate raw material was adjusted between 5000 mg•L−1 and 5500 mg•L−1. The experiment lasted for 69 days, and the stable hydrogen production time was 63 days. The hydrogen production and hydrogen production rate during the continuous hydrogen production experiment are shown in Fig. 12.5. From the 3rd day to the 65th day of the experiment, the daily hydrogen production was generally about 20 L, and the hydrogen production rate was relatively stable, mostly between 600 mL/L•d and 650 mL/L•d. The average hydrogen production rate was 633.1 mL/L•d, and the maximum hydrogen production rate during the stable hydrogen production period was 722.6 mL/L•d. The continuous hydrogen production process can be divided into three stages. The first stage was the initial stage of hydrogen production. The hydrogen production rate and the daily hydrogen production increased significantly from the beginning of the reaction to the third day; The second stage was the stable hydrogen production period. The hydrogen production rate changed slightly and basically stabilized between 600 mL/L•d and 650 mL/L•d from the 4th day to the 65th day; The third stage was the end of the hydrogen production process. The hydrogen production rate and the daily hydrogen production dropped sharply on the 66th day. In the circulating tank photosynthetic bioreactor, hydrogen production by photosynthetic bacteria fixed with sodium alginate was studied using pretreated pig manure wastewater as substrate. (1) In the batch hydrogen production experiment, the higher hydrogen production rate lasted for nearly 96 h. The average hydrogen production rate was 484.7 mL/L•d, and the maximum hydrogen production rate was 877.4 mL/L•d. The COD hydrogen production rate was 171.4 mL2/g COD•d, and the conversion utilization rate of raw materials was 68.4%; (2) In the continuous hydrogen production process, the continuous hydrogen production experiment lasted for 69 days, and the continuous hydrogen production was stable for 63 days. The maximum hydrogen production rate was 722.6 mL/L•d. During the stable hydrogen production period, the average hydrogen production rate was 633.1 mL/L•d. The COD hydrogen production rate was 172.9 mL/g COD•d, and the average conversion utilization rate of raw materials was 61.7%.

12.5.3  Solar energy-based 5 m³ baffle photobioreactor On the basis of summarizing the current development of photobioreactor, combined with the growth and hydrogen production characteristics of photosynthetic bacteria, a 5 m3 baffled

Chapter 12 • Production of biohydrogen in photobioreactors  289

FIG. 12.5  H2 production ability of photobioreactor in continuous-flow cultures process.

continuous photobioreactor was developed, and the operation process of the photobioreactor was studied. The whole system for photo-fermentative biohydrogen production mainly consists of six parts: photobioreactor, solar collector and heat exchange unit, solar concentrator and transmission unit, solar photovoltaic conversion unit, gas collection and storage unit, and operation parameter control unit. Photobioreactor adopts baffled structure with an effective working volume of 5.18 m3; solar collector unit adopts a vacuum tube collector with heat collecting area of 6 m2 and effective volume of hot water tank of 1.3 m3; heat exchanger is made of φ 20 stainless steel triangle finned tube with heat dissipation area of 8.6 m2. The system adopts the multi-point distributed light supply mode of built-in light source with solar energy as the main light source and LED as the auxiliary light source, with 228 light distribution channels, and the lighting area of solar concentrator is 4.18 m2. The capacity of solar panel is 120 Wp and the capacity of battery is 180 Ah. The design and research of the photo-fermentative biohydrogen production system provide a scientific reference and theoretical basis for the large-scale application of photo-fermentative biohydrogen production technology. The degradation rate of the substrate and the hydrogen yield of the system changed with the different amount of inoculum addition. The hydrogen yield in each compartment of photobioreactor with different amount of inoculum addition (10∼40%) is shown in Fig. 12.7. It can be seen from Fig. 4.6 that with the increase of the amount of inoculum addition, the hydrogen yield in each compartment of the photobioreactor also increased. The hydrogen yield of each compartment was also significantly different under different amount of inoculum addition. When the amount of inoculum addition was 10%, the hydrogen production peak mainly occurred in the first and second compartment, while the hydrogen yield of the third and fourth compartment gradually decreased with the reaction. On the 13th day of the reaction, the hydrogen production of the third and fourth compartment basically stopped, while the hydrogen production of the first and second compartment was still stable. When the amount of inoculum addition

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FIG. 12.6  5 m3 baffled continuous photobioreactor (Zhang et al., 2017). 1. Incubator; 2. Feed box; 3. Flowmeter; 4. Automatic control unit; 5. Light sensor; 6. Solar panels; 7. Battery; 8. Discharge port; 9. Outfall; 10. Pump; 11. Electric heater; 12. Temperature sensor; 13. Hydrogen storage; 14. Purification equipment; 15. Fuel cells.

FIG. 12.7  Hydrogen yield in each compartment of photobioreactor with different amount of inoculum addition.

Chapter 12 • Production of biohydrogen in photobioreactors  291

FIG. 12.8  Hydrogen yield and hydrogen production rate of the system with different amount of inoculum addition.

was 30%, the hydrogen yield of the third compartment was almost close to that of the second compartment, and the hydrogen production was in a stable state. Seen from Fig. 12.8, the hydrogen yield and hydrogen production rate of the system also increased with the increase of the amount of inoculum addition, but the increasing trend became slow when the amount of inoculum addition exceeded 30%. According to the operation of photobioreactor with different amount of inoculum addition, the minimum amount of inoculum addition should not be less than 20% to keep the reactor in normal and continuous operation, and more than 30% of inoculum addition can make the reactor in stable operation. In consideration of all aspects, 30% was selected as the optimal amount of inoculum addition for the continuous and stable operation of the photobioreactor. Different hydraulic retention time will lead to different residence time of glucose in each compartment of the reactor, which will further affect the degradation degree of glucose and hydrogen yield in the process of hydrogen production. Hydrogen yield in each compartment of the photobioreactor under different HRT is shown in Fig. 12.9. This study was conducted under the condition of 30% inoculation and glucose concentration of 3%, and HRT was set as 24, 36, 48, 60, and 72 h. It can be seen from Fig. 12.9 that the hydrogen yield of each compartment of the reactor changed significantly under different HRT conditions. Further observation showed that the hydrogen yield of compartments 1#∼4# basically increased with the extension of HRT, and the hydrogen yield were higher when HRT were 60 and 72 h. While the hydrogen yield of compartments 5#∼8# increased first and then decreased with the extension of HRT, and the hydrogen yield was higher when HRT was 36 h. Fig. 12.10 shows the changes of hydrogen production rate and total hydrogen yield of hydrogen production system under different HRT. It can be seen from Fig. 12.10 that both the hydrogen production rate and the total hydrogen yield of the system reached the maximum at HRT = 36 h. In conclusion, 36 h was the optimal HRT, which can not only achieve the full degradation of glucose, but also avoid the decrease of hydrogen yield caused by excessive accumulation of by-products.

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FIG. 12.9  Hydrogen yield in each compartment of photobioreactor under different HRT.

Chapter 12 • Production of biohydrogen in photobioreactors  293

FIG. 12.10  Hydrogen production rate and total hydrogen yield of hydrogen production system under different HRT.

12.5.4  Combined photo and dark fermentation mode 11 m³ baffle photobioreactor Pilot tests of sequential dark and photo fermentation H2 production were for the first time conducted in an 11 m3 reactor (3 m3 for dark and 8 m3 for photo compartments). A combined solar and light-emitting diode illumination system and a thermal controlling system was installed and tested. The hydrolyzed corn stover was used as substrate. The activated sludge was used as inoculum in the dark fermentation, and the mixed photosynthetic bacterial used in photofermentation is the consortia HAU-M1. The test was composed of the adaption stage (60 d) and production stage (30 d). At the beginning of the adaption stage, 300 kg of activated sludge was pumped into the dark-fermentation unit (Fig. 12.11A) with addition of 2 m3 cultivation medium to mix for 48 h. Then the hydrolysate from corn stover with substrate concentration of 10 g COD/L, was fed at HRT of 16 h. The dark fermentation unit maintained at pH 4.5 and 35°C. The effuent from the dark-fermentation unit was adjusted to pH 7.0 and to C/N ratio of 10:1 at the latter portion of the unit. Then the effuent was pumped to the photo fermentation unit (Fig. 12.11B), which was kept at 30°C with internal light intensity 3000 lux. The photo fermentation unit was operated under HRT of 48 h. The inoculum with cell concentration of 2.1 g/L from the cultivation reactor (Fig. 12.11C) was fed at a rate 25% (v/v) of feed. Stable operation was achieved after 60-day adaption period. Then the performance of the reactor was recorded in the subsequent production period. Over the 30-day production period, stable H2 production rates were noted: #1(6.4 m3/ 3 m -d), #2 (12.5 m3/m3-d), #3 (3.3 m3/m3-d). Fig. 12.12 shows the H2 production rates in the eight compartments of photo fermentation unit. Over the 30-day production period, stable H2 production rates were observed for the two rows. Row 1 had the following production rates: #1–1 (1.1 m3/m3-d), #1–2 (2.9 m3/m3-d), #1–3 (5.9 m3/m3-d), #1–4 (7.7 m3/m3-d); row 2 had the sequence #2–1 (2.1 m3/m3-d); #2–2 (3.9 m3/m3-d); #2–3 (5.3 m3/m3-d); #2–4 (9.8 m3/m3-d). The

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(A)

(B)

(C)

FIG. 12.11  Schematic of the experimental setup. (A) Dark-fermentation unit; (B) photo fermentation unit; (C) inoculum cultivation reactor.

compartments on row 2 produced more H2 than row 1, likely owing to the uneven distribution of feed and inoculum at both rows. The overall production rate for the current reactor was 87.8 ± 3.8 m3/d, with H2 content of 68.0 ± 0.8%. The average H2 production rate was 59.7 m3/d, or 2440 mol-H2/d. The current units produced 59.7 m3-H2 per day, 22.4 m3/d from dark and 37.3 m3/d from photo unit, yielding an average volumetric H2 production rate of 7.5 m3/m3-d for the former and 4.7 m3/m3-d for the latter. Since the H2 production rate was monotonically increased when moving from compartment #1 to #4, there should be room for improvement of the performance. The very large variation of H2 production rates noted from different compartments suggests that the mixing of the suspension inside can be further enhanced, however, the so-increased mixing cost should be considered in overall optimization.

Chapter 12 • Production of biohydrogen in photobioreactors  295

FIG. 12.12  Hydrogen production rates in the three compartments of the dark-fermentation unit.

(A)

(B)

FIG. 12.13  Hydrogen production rates of the photo-fermentation unit (Zhang et al., 2018). (A) Row 1; (B) Row 2.

12.6  Conclusions and perspectives Hydrogen is definitely a clean sustainable fuel to substitute the near-exhausted fossil fuels in the future. Photo fermentation is one of the widely studied methods to produce biohydrogen by photosynthetic bacteria. However, its slow productivity and low light conversion efficiency have become a tremendous challenge to further largescale application. Optimization and modification on biohydrogen production medium, abiotic factors, lighting regime to improve the light distribution and production yield of photo-fermentative biohydrogen are still the focus of future research. Additionally, a combined approach integrating individual strategies could also possibly lead to a synergistic improvement in term of biohydrogen productivity. Some recommendations are also suggested for further research study to improve photo-hydrogen productivity in the future.

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Acknowledgements The work was financed by the National Natural Science Foundation of China (52076068).

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Chapter 12 • Production of biohydrogen in photobioreactors  299

Zhang, Z., Yue, J., Zhou, X., Jing, Y., Jiang, D., Zhang, Q., 2014. Photo-fermentative bio-hydrogen production from agricultural residue enzymatic hydrolyzate and the enzyme reuse. BioResources 9, 2299–2310. doi:10.15376/biores.9.2.2299-2310. Zhang, Z., Zhang, H., Li, Y., Lu, C., Zhu, S., He, C., Ai, F., Zhang, Q., 2020. Investigation of the interaction between lighting and mixing applied during the photo-fermentation biohydrogen production process from agricultural waste. Bioresource Technology 312, 123570. doi:10.1016/j.biortech.2020.123570. Zhu, S., Zhang, Z., Li, Y., Tahir, N., Liu, H., Zhang, Q., 2018. Analysis of shaking effect on photo-fermentative hydrogen production under different concentrations of corn stover powder. International Journal of Hydrogen Energy 43, 20465–20473. doi:10.1016/j.ijhydene.2018.09.150. Zürrer, H., Bachofen, R., 1982. Aspects of growth and hydrogen production of the photosynthetic bacterium Rhodospirillum rubrum in continuous culture. Biomass 2, 165–174. doi:10.1016/0144-4565(82)90027-0.

Index Page numbers followed by “f ” and “t ” indicate, figures and tables respectively. A Adenosine triphosphate (ATP), 62–63 Agitation, 278–279 Aiba model, 103 Airlift photobioreactor (A-PBR), 17, 34, 37, 234 Algal biofilm-based photobioreactors, 136 Algal turf scrubbers (ATS), 127 Aquasearch growth module, 240 Arlift tubular photobioreactor, 237f Arrhenius equation, 105 Astaxanthin cultivation, 229, 230–231 in photobioreactor, 7 B Baffle photobioreactor, 8 Beer-Lambert law, 101–102 Biohydrogen cultivation, in photobioreactor, 8 Biohydrogen production process, 271, 274–275 Biological fermentative hydrogen production technology, 269–270 Biopolymer production, 257 Biopolymers, 229, 247, 258t cultivation, 7 microalgae, 178–180, 247 Biorefinery system, 257 Bubble column PBR, 232 Bubble column photobioreactor, 5, 16, 34, 36 C Cellulose, 247 Closed-PBRs, 256 Closed photobioreactors, 130 algal biofilm-based photobioreactors, 136 bottlenecks, 139 membrane photobioreactor, 135 soft frame, 134 vertical column, 130

Columnar photobioreactor, 196 design, 194 Column types photobioreactor, 5 Computational fluid dynamics (CFD), 6 simulation, 235 Cyanobacteria, 178 application, 184 classification, 178 columnar photobioreactor, 196 controlling cultivation, 186 flat-plate photobioreactor, 195 light and temperature, 186 medical value, 184 nutrient elements and carbon sources, 189 nutritional value, 184 open photobioreactor, 191 in photobioreactor, 255 perspectives, 197 salinity and pH, 187 tube photobioreactor, 192 D Dark fermentation hydrogen production, 269–270 Diatom productivity, in photobioreactor, 214 light, 214 nutrient requirements, 217 temperature and pH, 216 trophic mode, 219 Diatoms cultivation, in photobioreactor, 7 in large-scale culture systems, 208 physiological and biotechnological advantages, 207 Dissolved inorganic carbon, 108 Double-layered (DL) PBR, 236f Double-stage strategy, 259 Droop model, 97

301

302  Index

E Ecosapentaenoic acid (EPA), 7 Electrical energy, 238f Energy-free rotating floating PBR, 238–240 Extraction methods, 254 F Flat panel airlift PBRs, 240 Flat panel airlift photobioreactor (FPA-PBR), 23, 47 Flat plate photobioreactors, 4, 17, 43, 195 design, 196 innovative, 46 mixing, 44 Fluorescent parallel lamp (FPL), 162 G Gas-liquid mass transfer rate, 270 Gompertz model, 93 H Heat distribution, 281–282 Helical type photobioreactors (HPBR), 21, 42 Hemicellulose, 247 Heuristic rules, for II-PBR, 161 High rate algal ponds (HRAP), 124 Horizontal tubular PBR, 237 Horizontal tubular photobioreactor (HT-PBR), 20, 39 helical tubular, 42 innovative, 41 mixing, 40 Hybrid type photobioreactor, 22 Hybrid-type reactors, 240 Hydraulic retention time, 291 Hydrogen energy, 269 Hydrogen-producing bacteria, 271 Hydrogen production process, 288 I Internally illuminated photobioreactor (II-PBR), 24, 50, 158 adjusting light placement depth, 165 design and demonstration, 162 double-layered glass tube, 162

heuristic rules, 161 large-scale demonstration, 167 opportunities, 170 technical trade-offs associated, 159 L Lamber Beer law, 278–279 Light harvesting complex (LHC), 214 Light-heat-mass transfer mechanisms in photobioreactor, 271–272 Low-cost plastic bag photobioreactor (PBPBR), 25 Luminosity, 253 M Mean volumetric rate of energy absorption (MVREA), 64 Membrane photobioreactor (MPBR), 135 Michaelis-Menten model, 100 Microalgae-based wastewater treatment (MWT), 247 advantages, 128 algal biofilm-based photobioreactors, 136 algal turf scrubbers, 127 bottlenecks, 139 closed photobioreactors, 130 disadvantages, 128 high rate algal ponds, 124 membrane photobioreactor, 135 open systems, 124 opportunities, 128 photobioreactor, 6 soft frame, 134 vertical column, 130 Microalgae cultivation scaling-up process, 12 Microalgal biopolymer production, 252 Microalgal cultivation systems, 230, 248 Microalgal strains, 249t Mixing methods, 287 Monod model, 93–94 N Natural astaxanthin, 230 Nicotinamide adenine dinucleotide phosphate oxidase (NADPH), 62–63

Index 303

Nitrogen source, 252 Non-photochemical quenching (NPQ), 214 Nutrient and energy sources, 254 Nutrient limitation, 253 O Offshore membrane enclosures for growing algae (OMEGA), 5 Open systems, for MWT, 124 advantages, disadvantages and opportunities, 128 algal turf scrubbers, 127 high rate algal ponds, 124 Outdoor cultivation, 235 P Photoautotrophic microalgae, 248 Photobioreactor (PBR), 3, 271–272, 282, 289–291 advantage, 62t airlift, 17 applications, 6 astaxanthin cultivation, 7 biohydrogen cultivation, 8 biopolymers cultivation, 7 bioreactors and their design, 210 bubble column, 16 carbon and mineral nutrient requirements, 77 challenges, 26 closed, 60–61 column types, 5 cyanobacteria in, 190 design considerations, 60 diatom cultivation, 7 diatom productivity in, 214 disadvantage, 62t dissolved inorganic carbon, 108 factors influencing general productivity, 60 flat panel, 4, 17 flat-panel airlift, 23 helical type, 21 horizontal tubular, 20 hybrid type, 22 hydrodynamic stress, 75 internally illuminated, 24 light, 214

light illumination and intensity, 62 light intensity, 63 light path, 64 light regime, 73 light supply, 100 light utilization, 65 low-cost plastic bag, 25 mass transfer characteristics, 72 medium pH, 107 microalgae-based wastewater treatment, 6 microalgae cultivation scaling-up process, 12 microalgae productivity, 5 microalgal biomass composition, 90 microalgal growth, 90, 92 microalgal strains, 68 mixing, heat, and mass transfer, 71 mixing rate, 74 modeling, 100 multiple factors, 106 nutrient consumption, 100 nutrient requirements, 217 open, 60–61 open raceway ponds, 3, 4 operational parameters, 76 operation modes of cultivation, 70 optimal design, 270 pH control, 77 pH effect, 65 photosynthetic hydrogen production, 274 phycoremediation potential, 122 processes, 6 scalability principles, 13 simulation, 6, 110 soft frame, 5 stirred tank, 21 systems, 231 temperature, 66, 104, 216 temperature vs. productivity, 68 thermal regulation, 77 trophic mode, 69, 219 tubular type, 4 types, 4 vertical tubular, 15 v-shaped bottom, 232 Photobioreactor systems, 229, 255

304  Index

Photochemical reactor structures, 270, 280–281 Photosynthetic biohydrogen production reactor, 286 Photosynthetic microorganisms, 255 Plastic bag photobioreactors (PB-PBR), 48 Polyhydroxyalkanoates, 7–8 Polyhydroxybutyrate co-hydroxyvalerate (PHB-HV), 247 Polymeric thin-film PBR, 233f Polymethyl methacrylate (PMMA), 159 Polysaccharides, 186 Polyunsaturated fats, 5–6 Pond-tubular hybrid photobioreactor (PTH-PBR), 22–23 Porous substrate bioreactors (PSBR), 5 Primary nutrients, 252 Proteins, 187 R Raceway-type open PBRs, 255 Radiative transfer equation (RTE), 102, 238f Rushton turbine impeller, 238 S Soft frame photobioreactor, 5, 134 Starch, 177, 251 Stirred tank PBR, 238f, 238

Stirred tank photobioreactor (ST-PBR), 17, 21, 35 Stirred tank reactors (STR), 15 Substrates, 276 Surface-to-volume ratio (SVR), 158 T Taylor vortex photobioreactors (TV-PBR), 49 Torus photobioreactors (T-PBR), 50 Tube photobioreactors, 4, 15–16, 192, 238, 283, 285 design, 194 U Urea, 252 V Vertical alveolar panel (VAP), 46 Vertical column photobioreactors (VCPBR), 15–16, 34, 231 airlift photobioreactors, 37 bubble column photobioreactors, 36 stirred tank photobioreactors, 35 Vertical tubular photobioreactor, 5, 15 W Waste stabilization ponds, 6–7