Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2 Reduction Measures : CO2 Calculation Approach, Analysis and CO2 Reduction Measures [1 ed.] 9783954897032, 9783954892037

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Konstantin Veidenheimer

Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports

Copyright © 2014. Diplomica Verlag. All rights reserved.

CO2 Calculation Approach, Analysis and CO2 Reduction Measures

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

Veidenheimer, Konstantin: Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2 reduction measures. Hamburg, Anchor Academic Publishing 2014 The research in this book was undertaken in 2011. Buch-ISBN: 978-3-95489-203-7 PDF-eBook-ISBN: 978-3-95489-703-2 Druck/Herstellung: Anchor Academic Publishing, Hamburg, 2014 Bibliografische Information der Deutschen Nationalbibliothek: Die Deutsche Nationalbibliothek verzeichnet diese Publikation in der Deutschen Nationalbibliografie; detaillierte bibliografische Daten sind im Internet über http://dnb.d-nb.de abrufbar. Bibliographical Information of the German National Library: The German National Library lists this publication in the German National Bibliography. Detailed bibliographic data can be found at: http://dnb.d-nb.de

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Das Werk einschließlich aller seiner Teile ist urheberrechtlich geschützt. Jede Verwertung außerhalb der Grenzen des Urheberrechtsgesetzes ist ohne Zustimmung des Verlages unzulässig und strafbar. Dies gilt insbesondere für Vervielfältigungen, Übersetzungen, Mikroverfilmungen und die Einspeicherung und Bearbeitung in elektronischen Systemen. Die Wiedergabe von Gebrauchsnamen, Handelsnamen, Warenbezeichnungen usw. in diesem Werk berechtigt auch ohne besondere Kennzeichnung nicht zu der Annahme, dass solche Namen im Sinne der Warenzeichen- und Markenschutz-Gesetzgebung als frei zu betrachten wären und daher von jedermann benutzt werden dürften. Die Informationen in diesem Werk wurden mit Sorgfalt erarbeitet. Dennoch können Fehler nicht vollständig ausgeschlossen werden und die Diplomica Verlag GmbH, die Autoren oder Übersetzer übernehmen keine juristische Verantwortung oder irgendeine Haftung für evtl. verbliebene fehlerhafte Angaben und deren Folgen. Alle Rechte vorbehalten © Anchor Academic Publishing, Imprint der Diplomica Verlag GmbH Hermannstal 119k, 22119 Hamburg http://www.diplomica-verlag.de, Hamburg 2014 Printed in Germany

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

PREFACE Maritime container transport accounts for approximately 90 percent of global trade volumes. Largest container vessels represent challenges for container ports, such as the required draft of approximately 15.5 meters. In Europe there is a small group of deepwater ports that can accommodate world’s largest container vessels. These ports are integrated in maritime supply chains and often compete for the same hinterland. Furthermore, environmental issues play a growing role in the maritime business. Hence, this book concentrates on CO2 emissions from maritime supply chains considering European deepwater ports. This research investigates carbon dioxide emissions of maritime container transport from Asia into the European hinterland through new built German Jade-Weser-Port (JWP) in Wilhelmshaven compared to the deepwater ports of Rotterdam, Antwerp, Zeebrugge and Trieste. Furthermore, these ports are compared on the basis of competitive factors such as port characteristics and hinterland connectivity. This book also addresses measures for CO2 reduction in maritime door-to-door container transport.

ACKNOWLEDGEMENT I would like to thank Robert Woolford and Andre Kreie for their great advice during the writing of this book. Furthermore, I am very grateful to Prof. Dr. Alan McKinnon for sharing his comprehensive knowledge in green logistics. Many thanks also to Hermann Müller from Jade-Weser-Port Logistics Zone who took time for a personal conversation and gave valuable information concerning Jade-

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Weser-Port in Wilhelmshaven, Germany. At this point, I would also like to say a special "thank you" to my family and my wife Rita for their great patience and understanding, during the creation of this book.

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TABLE OF CONTENTS PREFACE ...................................................................................................................... 5 ACKNOWLEDGEMENT ............................................................................................. 5 LIST OF FIGURES ....................................................................................................... 9 LIST OF TABLES ....................................................................................................... 10 LIST OF DIAGRAMS................................................................................................. 10 ABBREVIATIONS ..................................................................................................... 11 1.

2.

CHAPTER – INTRODUCTION .......................................................................... 13 1.1

Problem statement .................................................................................................. 14

1.2

Introduction of the considered deepwater ports.................................................... 17

1.3

Objectives and Research questions ......................................................................... 18

1.4

Book Structure ......................................................................................................... 19

CHAPTER – LITERATURE REVIEW ............................................................... 20 2.1

Introduction ............................................................................................................. 20

2.2

Research Background .............................................................................................. 20

2.3

Green logistics related terms .................................................................................. 22

2.3.1

Environmental impacts of logistics .................................................................. 22

2.3.2

Global warming potential and conversion factors .......................................... 24

2.4

2.4.1

Maritime Supply Chain .................................................................................... 25

2.4.2

Hinterland ........................................................................................................ 26

2.4.3

Port competitiveness ....................................................................................... 28

2.4.4

Intermodal transport ....................................................................................... 29

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2.5

3.

Maritime related Terms........................................................................................... 25

Carbon auditing / Carbon footprinting .................................................................... 29

2.5.1

Carbon auditing of ocean going vessels .......................................................... 30

2.5.2

Carbon auditing of port related emissions ...................................................... 34

2.5.3

Carbon auditing of road freight transport ....................................................... 35

2.5.4

Carbon auditing of rail freight transport ......................................................... 37

2.5.5

Carbon auditing of inland waterway transport ............................................... 39

2.6

Measures for CO2 reduction of maritime supply chain ........................................... 40

2.7

Conclusion ............................................................................................................... 42

CHAPTER – RESEARCH METHODOLOGY ................................................... 43 3.1

Introduction ............................................................................................................. 43

3.2

Research philosophy................................................................................................ 43

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

3.3

Research approach .................................................................................................. 44

3.4

Data collection ......................................................................................................... 44

3.4.1

Secondary data ................................................................................................ 45

3.4.2

Primary data .................................................................................................... 47

3.5

4.

3.5.1

Ocean transport............................................................................................... 48

3.5.2

Road transport ................................................................................................. 52

3.5.3

Rail intermodal transport ................................................................................ 53

3.5.4

Inland waterway intermodal transport ........................................................... 53

3.5.5

Average hinterland emissions ......................................................................... 55

3.5.6

Port related emissions ..................................................................................... 56

3.6

Investigation of port characteristics and hinterland connectivity .......................... 57

3.7

CO2 reduction measures for JWP’s Maritime Supply Chain .................................... 57

3.8

Research reliability .................................................................................................. 57

3.9

Research validity ...................................................................................................... 57

3.10

Conclusion ............................................................................................................... 58

CHAPTER – FINDINGS AND RESULTS ......................................................... 59 4.1

Introduction ............................................................................................................. 59

4.2

Research Question 1 ................................................................................................ 59

4.2.1

CO2 emissions from ocean transport ............................................................... 59

4.2.2

CO2 emissions from road transport ................................................................. 61

4.2.3

CO2 emissions from rail transport ................................................................... 62

4.2.4

CO2 emissions from barge transport ............................................................... 64

4.2.5

Average hinterland emissions ......................................................................... 65

4.2.6

Total maritime supply chain emissions ........................................................... 66

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4.3

5.

Applied methods and tools for calculation of CO2 emissions ................................. 48

Research Question 2 ................................................................................................ 69

4.3.1

Jade-Weser-Port in Wilhelmshaven ................................................................ 73

4.3.2

Port of Antwerp ............................................................................................... 76

4.3.3

Port of Zeebrugge ............................................................................................ 78

4.3.4

Port of Trieste .................................................................................................. 81

4.4

Research Question 3 ................................................................................................ 82

4.5

Summary .................................................................................................................. 84

CHAPTER – ANALYSIS .................................................................................... 85 5.1

Introduction ............................................................................................................. 85

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5.2

5.2.1

CO2 emissions from ocean transport ............................................................... 85

5.2.2

CO2 emissions from road transport ................................................................. 87

5.2.3

CO2 emissions from rail transport ................................................................... 88

5.2.4

Average hinterland emissions ......................................................................... 89

5.2.5

Total maritime supply chain emissions ........................................................... 90

5.3

Research question 2 ................................................................................................ 91

5.4

Research question 3 ................................................................................................ 93

5.4.1

Analysis of measures for reduction of ocean emissions ................................. 94

5.4.2

Analysis of measures for reduction of port emissions .................................... 95

5.4.3

Analysis of measures for reduction of hinterland emissions .......................... 96

5.5

6.

Research question 1 ................................................................................................ 85

Summary .................................................................................................................. 97

CHAPTER – CONCLUSION .............................................................................. 98 6.1

Summary of important research findings................................................................ 98

6.2

Limitations of the research and further research possibilities ................................ 99

REFERENCES .......................................................................................................... 101

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APPENDICES ........................................................................................................... 114

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

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LIST OF FIGURES Figure 1.1 Generations of Container Vessels .......................................................................... 14 Figure 1.2 European container ports that compete for the same hinterland as Jade-WeserPort .......................................................................................................................................... 16 Figure 1.3 Current status of construction from Jade-Weser-Port .......................................... 17 Figure 2.1 Extraordinary growth in CO2 emissions through the 20th century ....................... 21 Figure 2.2 Emissions share per logistics activity ..................................................................... 23 Figure 2.3 Contributors to SOx emissions in ports by source category .................................. 23 Figure 2.4 Demarcation of the North and Baltic Sea SOx Emission Control Areas ................. 24 Figure 2.5 Simplified Maritime Supply Chain with research boundary................................... 26 Figure 2.6 Port foreland and hinterland.................................................................................. 27 Figure 2.7 Overlapping of port hinterlands ............................................................................. 27 Figure 2.8 Typical land-side sources of air pollution in port ................................................... 35 Figure 2.9 Road and rail network connection by EcoTransIT’s routing algorithm .................. 39 Figure 2.10 Inland waterway ship-classes ............................................................................... 40 Figure 3.1 Types of secondary data......................................................................................... 44 Figure 3.2 Defined Asia-Europe sea route in the “Distance Table” tool ................................. 49 Figure 3.3 Numerical example for calculation of CO2 emissions from sea transport ............ 51 Figure 3.4 Map containing considered deepwater ports and hinterland locations................ 52 Figure 3.5 EcoTransIT tool settings for inland waterway intermodal transport ..................... 54 Figure 3.6 Connection of sea and inland ports to different inland waterway classes ............ 54 Figure 3.7 Numerical example for calculation of average hinterland emissions .................... 56 Figure 4.1 Corridor that represents the overlapping of hinterlands from considered deepwater ports ...................................................................................................................... 68 Figure 4.2 Simulated picture from completed Jade-Weser-Port ............................................ 73 Figure 4.3 Layout from Jade-Weser-Port ................................................................................ 74 Figure 4.4 Deepwater Terminals from Port of Rotterdam at Maasvlakte 1 ........................... 75 Figure 4.5 Simulated picture showing Maasvlakte 1 and 2 .................................................... 76 Figure 4.6 Deepwater Terminals from Port of Antwerp ......................................................... 77 Figure 4.7 Tunnels that connect Antwerp’s deepwater terminals with motorway A12......... 77 Figure 4.8 Deepwater Terminals from Port of Zeebrugge ...................................................... 79 Figure 4.9 PSA’s container terminal data from first and final construction phase ................. 80 Figure 4.10 Rotterdam’s, Antwerp’s and Zeebrugge’s connection to the European inland waterway network .................................................................................................................. 81 Figure 4.11 Trieste Marine Terminal ....................................................................................... 82 Figure 4.12 Measures for reduction of ship emissions ........................................................... 83 Figure 4.13 Measures for reduction of port emissions ........................................................... 83 Figure 4.14 Measures for reduction of hinterland emissions ................................................. 84 Figure 5.1 Deviation from main shipping route in order to achieve Port of Trieste ............... 92 Figure 5.2 Extension of motorway A29 up to Jade-Weser-Port.............................................. 93

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LIST OF TABLES Table 2.1 Global warming potential (GWP) of the six Kyoto greenhouse gases..................... 25 Table 2.2 Characteristics of 8,000 and 13,000 TEU ships........................................................ 32 Table 2.3 Load Factors for Ship’s Main Propulsion and Auxiliary Machinery ......................... 32 Table 2.4 Power emission factors used by Port of Seattle ...................................................... 33 Table 2.5 CO2 emissions from container terminals of Rotterdam Port .................................. 34 Table 2.6 Conversion factors for diesel, LPG and petrol ......................................................... 36 Table 2.7 Emission factors for averagely loaded diesel powered trucks ................................ 36 Table 2.8 Published Emission Factors for Rail Freight Movement (gCO2 / tkm) .................... 38 Table 3.1 Features from positivist and phenomenological paradigm .................................... 43 Table 3.2 Key words for secondary data search ..................................................................... 45 Table 3.3 Organizations whose websites served for secondary data collection .................... 46 Table 3.4 Applied tools for calculation of distances and CO2 emissions ................................ 48 Table 3.5 Assumptions for carbon auditing of ocean transport ............................................. 50 Table 3.6 Defra’s average conversion factor for an articulated truck (>33t) .......................... 52 Table 3.7 Modal split data from the investigated deepwater ports ....................................... 55 Table 4.1 Distances between Shanghai and the investigated deepwater ports ..................... 60 Table 4.2 Modal slit from each deepwater port ..................................................................... 65 Table 4.3 General port characteristics from the investigated ports ....................................... 71 Table 4.4 Hinterland transport mode connections from the investigated ports .................... 72 Table 5.1 Emission factors for EURO I–V vehicles (>34-40 tonnes) ........................................ 88

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LIST OF DIAGRAMS Diagram 4.1 CO2 emissions from 8,000 and 13,000 TEU ships operating at a speed of 19 knots (kg CO2e/TEU) ............................................................................................................... 60 Diagram 4.2 Comparison of CO2 emissions from a 13,000 TEU ship operating at speeds of 19 and 24 knots (kg CO2e/TEU) ................................................................................................... 61 Diagram 4.3 CO2 emissions from road transport (in kg CO2e/TEU) ....................................... 62 Diagram 4.4 CO2 emissions from rail transport (in kg CO2e/TEU) ......................................... 63 Diagram 4.5 CO2 emissions from barge transport (in kg CO2e/TEU) ..................................... 64 Diagram 4.6 Comparison of rail and barge emissions (kg CO2e/TEU) on the example of Dortmund ................................................................................................................................ 65 Diagram 4.7 Average CO2 emissions from hinterland transport (in kg CO2e/TEU) ............... 66 Diagram 4.8 Total average maritime supply chain emissions (in kg CO2e/TEU) .................... 67 Diagram 4.9 Hinterland locations that can be reached most environmentally through JadeWeser-Port .............................................................................................................................. 69 Diagram 5.1 Increase of engine load factor with rising vessel speed (knots) ......................... 86

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

LIST OF FORMULAS Formula 2.1 Calculation of CO2 emissions from container vessels ........................................ 31 Formula 2.2 Calculation of the engine load factor ................................................................. 32 Formula 2.3 Calculation of CO2 emissions using fuel-based approach .................................. 36 Formula 2.4 Calculation of CO2 emissions using activity-based approach............................. 36

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ABBREVIATIONS AT

Activity time

BSFC

Break specific fuel consumption

CO2

Carbon dioxide

CO2e

CO2 equivalent

DC

Distribution Centre

EC

Energy consumption

EF

Emission Factor

etc.

et cetera

FCL

Full Container Load

GHG

Greenhouse gas

GRT

Gross register tonnage

GVW

Gross vehicle weight

GWP

Global warming potential

ha

hectare/-s

HDV

Heavy duty vehicle

HGV

Heavy goods vehicle

HWU

Heriot-Watt University

i.e.

id est

IMO

International Maritime Organisation

JWP

Jade-Weser-Port

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kj

Kilojoule

LF

Load Factor

MEPC

Marine Environment Protection Committee

MCR

Maximum Continuous Rating

n.a.

Not applicable

nm

nautacal miles

NMHC

Non-methane hydrocarbons

NOx

Nitrous oxides

PM

Particulate matter

ppm

Parts per million

RQ

Research question

SECAs

SOx Emission Control Areas

SO2

Sulfur dioxide

TEU

Twenty-foot equivalent unit

tkm

Tonne kilometre

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

1.

CHAPTER – INTRODUCTION

Global container transport is by far the most important factor in international trade. Approximately 90 percent of global trade volume moves in sea containers (Lam, 2011 and Kaluza et al., 2010). In order to accommodate the expected growth in container shipping and to reduce unit costs by exploiting economies of scale, shipping lines utilize ever growing container-vessels (Cullinane and Khanna, 1999). The “sixth” generation or “E-class” container vessel (figure 1.1), with “Emma Maersk” as the world’s largest container ship, has also particular geographical requirements on container ports such as the draft or draught of 15.5 meters (Maersk Line, 2011). Maersk’s Triple-E class vessels with 18,000 TEU will probably set new challenges for container ports. The predicted growth in global container movements leads one to expect that the number of mega container vessels will probably increase significantly in the medium- and long-term. The emerging Jade-Weser-Port (JWP) in Wilhelmshaven, with a tide-independent draft of 16.5 meters, will be able to accommodate the currently largest container vessels. In this book a “deepwater port” is defined as a port which provides a minimum draught of 15.5 meters. Besides the pressure on container ports to deal with the current and future generation of container ships, there is also a growing public interest in environmental issues. Thus, some ports have begun to implement carbon auditing to figure out their contribution to air pollution. In conjunction with global container transport, carbon auditing can be used to estimate CO2 emissions of maritime supply chains. McKinnon et al. (2010a) define maritime supply chain as the transportation of goods from one particular point to another including at least one sea link. This research is aiming to examine CO2 emissions from maritime container transport

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chains passing through the Jade-Weser-Port and other European deepwater ports.

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Figure 1.1 Generations of Container Vessels

Source: Container Transportation, 2011

1.1 Problem statement The strongly developing trade relations between Asia and Europe lead to an increasing flow of goods between these continents. Thereby China is by far the most important European trade partner. Statistically, the EU imports (€215 billion) more than twice as much from, than it exports (€81.7 billion) to China (European Commission, 2010). Hence, this book will concentrate only on container flows from China to Europe using Shanghai as the port of origin, since this is the largest Chinese port and an important regional hub. The term “hub” is related to the hub and spoke Copyright © 2014. Diplomica Verlag. All rights reserved.

system. Most shipping lines operate their largest container vessels between hub ports which serve as transhipment points for onward sea shipping and/or transit gateways for hinterland distribution (Rodrigue and Notteboom, 2010 and Rodrigue et al., 2009). Since Jade-Weser-Port (JWP) is the only deepwater port in Germany and the most easterly one in the European North Range (Eurogate, 2011), it is aiming to be both a gateway port for the German and Eastern European hinterland, and a transhipment

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

hub for feeder traffic into the Baltic Sea. European North Range includes all container ports between Le Havre and Hamburg (Vernimmen et al, 2007). The ability to accommodate fully loaded ultra-large container vessels with a draught of 15.5 meters indicates a potential niche market in the European region (Kleinsteuber, 2002). Figure 1.2 illustrates all those European ports competing for the same hinterland as JWP, whereby Le Havre has been excluded from consideration due to its far distance. However, only the ports of Rotterdam, Antwerp, Zeebrugge and Trieste provide sufficient draft to be categorised as deepwater ports in this research. Since JWP’s aims are to become a part of global supply chains and to establish a “green port” image, there is particular interest in figuring out JWP’s competitiveness towards above mentioned deepwater ports particularly in terms of CO2 emissions of

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maritime supply chains (Mueller, 2011).

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

Source: Google Earth, 2011

Figure 1.2 European container ports that compete for the same hinterland as Jade-Weser-Port

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1.2 Introduction of the considered deepwater ports Jade-Weser-Port is located in Wilhelmshaven close to the German ports of Hamburg and Bremerhaven. The terminal is expected to start its operations in August 2012 (Jade-Weser-Port, 2011). Figure 1.3 illustrates the current construction status of the container terminal in July 2011. Figure 1.3 Current status of construction from Jade-Weser-Port

Source: Jade-Weser-Port, 2011 Rotterdam, Antwerp and Zeebrugge are located close to each other in the approximate middle of the North-Range. Thereby, Antwerp is situated little further in the inland along the river Scheldt between Rotterdam and Zeebrugge. Rotterdam is the largest European port and is directly connected to the Rhine river system. However, also Zeebrugge and Antwerp are situated at the entrance to the European inland waterway network, so that all three ports can serve the industrialised German Ruhr Area by

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barge. Trieste is situated in the North Adriatic Sea on the Italian coast. The port provides advantageous location towards other deepwater ports since Trieste is located at the shortest distance to Shanghai.

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1.3 Objectives and Research questions The “overall objective” of this research is to investigate carbon dioxide emissions of container transport from Shanghai into the hinterland of Central and Eastern Europe through the emerging German deepwater port in Wilhelmshaven compared to other European ports with a draft of at least 15.5 meters. Thereby, following supplementary research questions will be considered: 1. How much CO2 emissions are produced by container transport passing through the investigated deepwater ports and what regions can be reached more environmentally friendly through Jade-Weser-Port rather than through Rotterdam, Zeebrugge, Antwerp and Trieste? 2. What are the general port characteristics and the quality of hinterland connections? In this context, “general port characteristics” are competitive criteria such as maritime accessibility, availability of a logistics zone, expanding capacity and others. “Quality” can be understood as connectivity to different inland transport modes and the features of these transport modes, such as distance to the nearest motorway including the number of motorway lanes, connection of railway track to electricity and inland waterway classes. 3. What are the possible measures for reduction of CO2 emissions of maritime supply chain or door-to-door container transport passing through Jade-Weser-Port? It is not the aim of this stdy to implement new carbon estimation methods, but rather to find and to use straightforward carbon auditing approaches or tools that are most

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appropriate to achieve the overall objective. Furthermore, the emphasis is not on CO2 emissions from the different ports but rather on the maritime supply chains passing through the investigated ports.

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

1.4 Book Structure This book is structured as follows. Firstly there will be a review of literature elucidating the research background and particular terms which are relevant for the three research questions. The greater part of literature review will focus on approaches for estimation of CO2 emissions. Secondly, the research methodology will describe secondary and primary data collection, and explain applied methods, tools and assumptions for calculation of carbon emissions. Thirdly, findings will be presented for each research question, followed by analysis of the results in chapter 5. The text will end with a conclusion including limitations of the research and recommendations

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for further research.

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2. CHAPTER – LITERATURE REVIEW 2.1 Introduction The literature review will start with the research background addressing historical developments and research gaps. Subsequently, some important green logistics and maritime related terms will be addressed which are of particular relevance for the three research questions. In order to address the overall objective of this study, the greater part of this chapter will focus on literature concerning methods for estimation of CO2 emissions from container ports and all transport modes evolved in maritime transport chain.

2.2 Research Background According to the United Nations Economic and Social Commission for Asia and the Pacific (UN ESCAP) (2011), global container traffic has grown between 1980 and 2010 from 13.5 to 138.9 million TEU. This corresponds to an increase by 930 percent over a span of 30 years, having its peak in 2008 with 152.0 million TEU (Port Economics, 2011). Containerized trade is predicted to increase to 177.6 million TEU by 2015 (UN ESCAP, 2011) and to 211 to 265 million TEU by 2020, already involving the economic downturn in 2008 (European Parliament, 2009). The European Parliament’s Committee on Transport and Tourism has indicated that there will be a strong growth in the fleet of “+10,000 TEU” container vessels and that especially the Asia-Europe trade lane will be served mainly by these ultra-large container vessels. As a matter of fact, just recently Maersk Line ordered 10 new gigantic “Triple-E” container ships with a capacity of 18,000 TEU and has set an option for further 20 vessels. This trend of ever growing container ships might create a niche market and competitive advantage (Kleinsteuber, 2002; Zondag, et al., 2010;

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Tongzon and Oum, 2007) for ports that provide maritime access for the largest container ships today and in the future (Hesse, 2006; Zondag, et al., 2010). In the literature review there have been some publications comparing the competitiveness of North Italian towards North-Range ports, especially because the former have advantageous geographical location along the container flows from Asia to Europe (Zondag, et al., 2010; Pohnert, 2010; Cazzaniga Francesetti, 2005). Other

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

papers occupy with the competition between North Range Ports in terms of short sea shipping (Ng, 2009), container rail freight services (Gouvernal and Daydou, 2005), port services (Parola and Musso, 2007), hinterland connections, maritime access, and port performance factors such as capacity and efficiency (Zondag, et al., 2010). However, during the literature review it became apparent that there is a lack of research with regard to the comparison of European “deep-water ports” that can accommodate New Panamax or Sixth Generation container ships with its particular dimensions and a draft of 15.5 meters (figure 1.1). For ports there is also a growing interest in environmental issues as a consequence of public and governmental concerns associated with increasing greenhouse gas (GHG) emissions and the resulting global warming. Especially in the last two centuries the concentration of carbon dioxide in the atmosphere has increased significantly. Figure 2.1 illustrates the dramatic increase of CO2 emissions over the last 200 year compared to a time span of 10,000 years. Figure 2.1 Extraordinary growth in CO2 emissions through the 20th century

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Source: Freight Best Practice, 2010 The climate changes have become visible through major environmental disasters such as drought and floods. Especially the hunger catastrophe in summer 2011 in East Africa appears to be a result of increasing drought (BBC News, 2011). McKinnon (2010a) indicated that environmental sustainability has become ‘a new priority for

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logistics managers’ (p.3). Thereby the greatest attention is currently paid to the greenhouse gas emissions (Kanji and Chopra, 2010). In recent times there has been growing awareness of ports as elements in global supply chains (Panayides and Song, 2008; Bichou and Grey, 2004; Rodrigue and Notteboom, 2009; Notteboom, 2008). It can be assumed that the linkage of maritime logistics with the supply chain concept resulted in the development of the term “maritime supply chain” (Song and Lee, 2009; Banomyong, 2005). However, although there is a wide range of publications dealing with CO2 emissions from supply chains, there are hardly papers addressing emissions from maritime container transport chains. Port of Seattle (2009) conducted a study examining the carbon footprint of a container moving from several Asian ports through different U.S. container terminals into the North American hinterland. However, there is no one comparable work at European level. This underpins a gap in research.

2.3 Green logistics related terms Section 2.3 will explain environment related terms which are of particular importance for the first research question. It will start with environmental impacts of freight transport and will then explain the terms conversion factors and global warming potential which are relevant for calculation of CO2 emissions.

2.3.1 Environmental impacts of logistics Logistics has numerous effects on the environment, whereby the most widely reported impact is air pollution. According to the World Economic Forum (2009), logistics activities account for approximately 5.5 percent of overall global CO2 emissions, whereby road and ocean freight are the main contributors to air pollution as illustrated Copyright © 2014. Diplomica Verlag. All rights reserved.

in figure 2.2.

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

Figure 2.2 Emissions share per logistics activity

Source: World Economic Forum, 2009 Especially in terms of ocean transport, numerous publications have addressed the fact that ocean going vessels emit by far more air pollutants, such as sulphur oxide (SOx), nitrogen oxide (NOx) and particulate matter (PM), than other transport modes (McKinnon et al., 2010b; ISL, 2010; Miller et al., 2009; Eyring et al., 2005). According to Moon (2011) ocean going vessels are the main contributors to SOx emissions in ports as highlighted in figure 2.3.

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Figure 2.3 Contributors to SOx emissions in ports by source category

Source: Moon, 2011

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

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This is because ships burn dirty heavy fuel oil (HFO) or residual oil, which contains around 27,000 parts per million (ppm) of sulphur, where for example truck diesel fuel comprises 10-15 ppm (McKinnon et al., 2010b). Cannon (2009) mentions an even higher sulphur content figure of 45,000 ppm. For this reason IMO Marine Environment Protection Committee (MEPC) defined so-called “SOx Emission Control Areas” (SECAs) in the North and Baltic Sea (figure 2.4) within which the sulphur content in ship fuels must be reduced to 0.1% by 2015 (ISL, 2010). Figure 2.4 Demarcation of the North and Baltic Sea SOx Emission Control Areas

Source: IFEU, 2010

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2.3.2 Global warming potential and conversion factors Atmospheric emissions consist of a large number of greenhouse gases (GHGs) that are combined into six main GHGs in the Kyoto Protocol (UNFCCC, 2008). Each of these GHGs has a particular global warming potential (GWP) (table 2.1) measured in carbon dioxide equivalents (CO2e). For example, to estimate the pollution impact of nitrous oxide (N2O), the emitted amount of N2O must be multiplied by the GWP 310.

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

This is done to express air emissions by means of a common denominator, namely CO2e because carbon dioxide accounts for more than 85 percent of total atmospheric pollutions (Cullinane and Edwards, 2010). Therefore, a large proportion of publications often only relate to CO2 when addressing air emissions. Table 2.1 Global warming potential (GWP) of the six Kyoto greenhouse gases Greenhouse gas

GWPs from DEFRA

GWPs from IPCC

Carbon dioxide (CO2)

1

1

Methane (CH4)

21

25

Nitrous oxide (N2O)

310

298

Hydrofluorocarbons (HFCs)

140-11,700

124-14,800

Perfluorocarbons (PFCs)

6,500-9,200

7,390-12,200

Sulphur hexafluoride (SF6)

23,900

22,800

Source: Cullinane and Edwards, 2010 Conversion or emission factors are used to calculate GHG emissions from activities and processes associated with energy consumption (EPA, 2010; DEFA, 2009). Typical energy sources are fuels, gases, coal, and grid electricity.

2.4 Maritime related Terms This section will elucidate some important maritime related terms which are of particular relevance for the second research question. The terminology comprises maritime supply chain, hinterland, port competitiveness and intermodal transport.

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Thereby the former is also important for the first research question.

2.4.1 Maritime Supply Chain McKinnon et al. (2010a) define maritime supply chain as ‘door-to-door freight delivery containing at least one sea movement’ (p.1). Berle et al. (2011) used the expression “maritime transportation system” consisting of five components, namely, sea operations, navigable waterways, ports, terminals and intermodal connection. The

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authhors also diistinguish between tram mp and lineer shipping, whereby thhe first is based b on the t principlle of random m shipping services, annd the laterr is a network of sched duled servvices includding land-siide containner movemeent (World Shipping Council, C 20 011). How wever, abovve definitionns do not deescribe the single stepss or elementts of a mariitime suppply chain which w are important to t be undeerstood in the t contextt of the ov verall objeective. Undder the exprressions “linner shippinng operationns” or “worrk flow of liner shippping logisttics” Ting (22011) and Song S (2011)) addressed typical conntainer mariitime movvement pattterns. Also P Port of Los Angeles (22010) outlinned an extennded descrip ption of maritime m suupply chainn, that can be describees as a seqquence of following f steps. Firsstly, the em mpty containner is deliveered to the point of orrigin for stuuffing. Thee full conttainer is thhen hauled to the portt of discharrge (e.g. Shhanghai) whhere the bo ox is loadded on a coontainer vesssel for the onward occean freightt to the porrt of destinaation (e.gg. Rotterdam m). Subsequuently, portt handling aat the impoort side, on-carriage to o the finaal destinatioon and the rreplacementt of empty ccontainer taake place. However, H in n this reseearch only ocean o transpport, terminnal handlingg and hinterrland deliveery to particcular locaations are considered c as emphassised by thee border inn figure 2.55. Thus, em mpty conttainer moveements in prep and post-carriage are excludeed from esttimation of CO2 emiissions. Figu ure 2.5 Sim mplified Marritime Suppply Chain w with researchh boundary

Souurce: adapted from Frauunhofer IML L, 2011.

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2.4.2 Hinterrland In the t maritim me industryy there is a distinctioon betweenn foreland and hinterlland. Theereby hinterrland lies beehind the port p on the lland-side, aand ‘forelannd is the occeanwarrd mirror off the hinterlaand’ (Rodriigue and Nootteboom, 2010 2 p.5) ass exemplifieed in figuure 2.6. In order o to adddress the seccond researcch questionn, more detaailed descripption of thhe term hintterland is reequired.

26

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

Figure 2.6 Port foreland and hinterland

Source: Rodrigue and Notteboom, 2006 The hinterland of a port generates goods for outbound and demand for inbound movements (Rodrigue and Notteboom 2006; Venus Lun et al., 2009). Thereby each container port serves particular hinterland consisting of main hinterland and so-called competition margin or area (Rodrigue and Notteboom, 2006). Figure 2.7 illustrates these two areas from port A and B. Thereby, “main hinterland” represents that region where a port plays a predominant role. The “competition margin” area of port A can overlap with that of port B. In this overlapping area container terminals compete for the same customers. For example, Ferrari et al. (2007), Cazzaniga Francesetti (2005) and Pohnert (2010) argue that container ports from the North-Range and from North Italian/North Adriatic Sea (figure 1.1) compete for the same hinterland region, namely, Central and Eastern Europe.

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Figure 2.7 Overlapping of port hinterlands

Source: Rodrigue and Notteboom, 2006.

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Theoretically, the concept of main hinterland and competition margin could be transferred to port competition in terms of carbon emissions. Thus, one could argue that the main hinterland of Jade-Weser-Port is that area which can be reached most environmentally friendly through Wilhelmshaven. In regions where maritime supply chain emissions from particular ports are similar, there is an overlapping of competition margin areas from these ports.

2.4.3 Port competitiveness In order to address the second research question it is important to figure out characteristics that make a port competitive. Common competitive factors are geographical location, maritime access, port terminal performance, port charges, terminal capacity, dedicated berths, free trade zone, value added services, ability to handle different cargo types (e.g. general cargo/containers, roll-on/roll-off and bulk cargo) and inland connectivity (Ferrari et al., 2011; Pohnert, 2010; Leggate et al., 2005; Ng, 2009; Notteboom, 2009; Bichou and Gray, 2004). Song and Panayides (2008) argue that nowadays port supply chain integration is major competitive factor. If one transfers the supply chain competition concept from Christopher (2005) to the maritime industry one can state that competition no longer occurs between single ports but rather between maritime supply chains, within which ports are integral parts (Ferrari et al., 2011). Bichou and Gray (2009) differentiated between “organisational” and “intermodalism” port supply chain integration. The former means the linkage of nodes and different transport modes, whereas the latter is described as the prior cooperation between organizations in order to achieve intermodalism. Panayides and Song (2009), on the other hand, describe organizational integration as the ability of ports to provide value added services to companies. Notteboom (2008a; 2008b), argues that connection to advanced hinterland networks is a major prerequisite for

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successful supply chain integration, and that further development of hinterland links is indispensable in order to remain competitive.

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

2.4.4 Intermodal transport “Intermodal transport” or “multimodal transport” is the movement of goods in a loading unit, such as ISO container or trailer, by at least two different transport modes (Branch, 2007; Rowbotham, 2008; Bauer et al., 2010; Winebrake et al. 2008). According to Venus Lun et al. (2009) in containerized movement intermodalism is an inherent part and enables worldwide door-to-door transport. Thus, in order to address the overall objective, following section will review the literature concerning estimation of carbon emissions from maritime door-to-door container transport.

2.5 Carbon auditing / Carbon footprinting A carbon footprint is the amount of emitted green house gases from individuals, organisations, products, supply chains and activities. Carbon footprinting or carbon auditing is the CO2 estimation process (Carbon Trust, 2007; Piecyk, 2010; McKinnon, 2009). For carbon auditing of freight transport operations there are two basic approaches, namely, energy-based and activity-based method (Piecyk, 2010). According to Piecyk (2010) the former is quite simple to apply due to standardised energy or fuel conversion factors. However one need access to accurate fuel consumption figures (McKinnon, 2007). Activity-based method is based on transport activity data expressed typically in tonne kilometres (tkm). For calculation of activity data the weight of carried goods (in tonnes) and distance travelled (in kilometres) is needed. Distance data can be obtained by using online distance calculation tools. However, McKinnon and Piecyk (2010) argue that it might be difficult to get distance data from rail and barge or inland waterway transport. Furthermore, the authors argue that activity based approach might be more difficult to apply since there is a wide range of Copyright © 2014. Diplomica Verlag. All rights reserved.

various emission factors that are based on numerous assumptions from different organizations. This study will use both activity and energy based methods. Following subsections will review the literature concerning various carbon auditing methods and tools for ocean freight, port handling, and hinterland transport by road, rail and inland waterway.

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2.5.1 Carbon auditing of ocean going vessels The UK Department for Environment, Food and Rural Affairs (DEFRA) (2010) proposes an activity-based approach by multiplying the tonne kilometre (tkm) value by the appropriate conversion factor, expressed in “kg CO2e/tkm”. However, according to Leonardi and Browne (2010) fuel consumption of container vessels is less determined by the distance but rather by the time in particular operating mode. Therefore the authors suggest a fuel-based approach by estimating the average duration at sea and in ports, and multiplying the number of days from each operating mode by the appropriate daily fuel consumption. It should also be mentioned that Leonardi and Browne considered only container vessels with a maximum nominal capacity of 6000 TEU. However, ultra large container vessels with a nominal capacity of more than 11,000 TEU are assumed to produce less CO2 emissions per TEU (Tozer, 2003). The Port of Seattle (2009) considered different sizes of container ships including vessels with a capacity of 12,500 TEU which are more relevant for deepwater ports. Port of Los Angeles (2010), Port of Seattle (2009) and the World Ports Climate Initiative (WPCI) (2010) propose also an activity based approach but additionally include the “maneuvering” mode besides cruising at sea and idling in port. Maneuvering occurs in a particular distance between the open sea and a port, and can vary significantly from port to port. Emissions from maneuvering mode are of particular importance for ports that examine both shore-side and water-side GHG emissions such as done by the Port of Los Angeles (2010). However, if one considers the whole distance between Asian and northern European ports, than the proportion of maneuvering is vanishingly small. Thus, IFEU (2010) and Leonardi and Browne (2010) suggest to consider ship emissions only at sea and in port. Most papers differentiate between propulsion and auxiliary power systems. The

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propulsion engine is responsible for driving the propeller and auxiliary engine provides electricity for various ship operations and serves as emergency power system in case of main engine breakdown (WPCI, 2010). These two engine types work at different engine loads depending on the operating mode. In order to estimate CO2 emissions from ocean going vessels, Port of Seattle (2009), WPCI (2010) and Port of Los Angeles (2010) use the following equation.

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

Formula 2.1 Calculation of CO2 emissions from container vessels ‹••‹‘• ൌ ࡹ࡯ࡾ ൈ ࡸࡲ ൈ ࡭ࢀ ൈ ࡱࡲ Where, MCR

= Maximum Continuous Rating of the combustion engine in use (kW) Æ I

LF

= Load Factors

Æ II

AT

= Activity time (hours)

Æ III

EF

= Power based emission factor (kg/kW-hr) for the greenhouse gas

Æ IV

Source: Port of Seattle, 2009 The four above mentioned calculation factors (I – IV) are explained in more detail bellow:

I.

Maximum Continuous Rating (MCR)

Maximum continuous rating (MCR) is the installed engine power and is usually measured in kilowatt (kW). Typically, maximum 80 percent of that power is used (De Meyer et al., 2008; IFEU, 2010 and Port of Seattle, 2009) due to fuel consumption and engine maintenance reasons (WPCI, 2010). The rated power from propulsion and auxiliary engines from different organizations are illustrated in table 2.2. According to Port of Seattle (2009) the MCR of a 12,500 TEU vessel is 80,080 kW. However, E.R. Shiffahrt (2011) illustrates smaller value of 74,760 kW for its 13,100 TEU vessels. Also WPCI (2010) provides lower average figure of 72,027 kW for 13,000 TEU ships. WPCI’s MCR data seem to be more appropriate, since they represent average

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values.

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Table 2.2 Characteristics of 8,000 and 13,000 TEU ships Port of Seattle

WPCI

Ship capacity Propulsion MCR (kW)

8,214 TEU

12,500 TEU

68,640

80,080

Auxiliary MCR (kW)

12,200

14,000

-

Max. rated speed (kn.)

-

-

25.2

8,000 TEU

E.R. Schiffahrt 8,204 TEU

13,100 TEU

68,640

74,760

-

-

-

24.7

25.3

24.7

13,000 TEU

67,824 72,027 (av. of 177 ships) (av. of 17 ships)

Source: Port of Seattle, 2009; E.R. Shiffahrt, 2011; WPCI, 2010 II.

Load Factor (LF)

The engine load factor is determined by dividing the actual cruising speed by the maximum vessel speed and taking the cube from the outcome as shown in formula 2.2 (WPCI, 2010, Port of Los Angeles, 2010). Table 2.3 summarizes the average load factors from propulsion and auxiliary engines applied by Port of Seattle (2009). Formula 2.2 Calculation of the engine load factor ࡭ࡿ ૜ ࡸࡲ ൌ ൬ ൰  ࡹࡿ Where, LF

= Load Factor

AS

= Actual speed (knots)

MS

= Maximum speed (knots)

Source: WPCI, 2010 Table 2.3 Load Factors for Ship’s Main Propulsion and Auxiliary Machinery Copyright © 2014. Diplomica Verlag. All rights reserved.

Load Factors

At sea

In port

Propulsion engine

0,80

0,00

Auxiliary engine

0,13

0,17

Source: adapted from Port of Seattle, 2009

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

III.

Activity time (AT)

The activity time is calculated by dividing travelled distance by average speed. According to WPCI (2010) and IFEU (2010) the average cruising speed from container ships has been around 24 knots. Deniz and Durmusoglu (2008) and De Meyer et al. (2008) suggest an average value of around 19 knots. Especially after the financial crisis in 2008, shipping lines started to operate their vessels at so-called “slow steaming” mode with 19-20 knots to reduce fuel consumption (Rodrigue et al., 2009; Brick, 2011). As a matter of fact, Woodburn and Whiteing (2010) state that a vessel consumes one third less fuel when it reduces speed from 24 to 20 knots. The average idling time in port can vary significantly depending on factors such as port handling efficiency, number of unloaded and loaded containers, tide dependence, terminal IT system, and others (Sohn and Jung, 2009). IV.

Emission factors (EF)

Cooper (2002), Miller et al. (2009), Agrawal et al. (2010), Georgakaki et al. (2005) and Dalsoren et al. (2009) provide a wide range of various GHG emission factors and fuel conversions from different ship types. The power emission factors (table 2.4) used by Port of Seattle are based on Intergovernmental Panel on Climate Change (IPCC) (2007). Table 2.4 Power emission factors used by Port of Seattle Power Emission Factors (kg pollutant / kWh) Propulsion

Auxiliary

GWP

CO2

0.548

0.595

1

CH4

0.00005

0.00005

25

N2O

0.00001

0.00002

298

CO2e

0,55223

0,60221

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Source: adapted from Port of Seattle, 2009 In order to allocate ship emissions to TEU one should consider the average ship capacity utilization. The Port of Seattle uses a value of 90 percent. However, Defra (2010) and IFEU (2010) suggest a figure of 70 percent. Thereby IFEU’s utilization value is based on +7,000 TEU vessels operating on the Asia-Europe trade lane. Therefore 70% seems to be more appropriate for this research.

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2.5.2 Carbon auditing of port related emissions The literature for estimation of port emissions is quite limited. WPCI (2010) and Port of Los Angeles (2010) introduce three approaches for examining emissions inventory in ports, namely, activity-based, surrogate-based and hybrid approach. The former is based on energy and fuel consumption values which are multiplied by corresponding emission factors. In case of lack of primary energy consumption data, surrogates are used in form of estimates and published data. The hybrid approach is a combination of previous two methods. Geerlings and Van Duin (2011) estimated CO2 emissions from various container terminals in Rotterdam. The authors used a bottom-up approach by examining the overall annual consumption of diesel (in litre) and electricity (in kWh) from terminal equipment such as quay cranes, rail cranes, reach stackers and others. The terminal layout was used to examine the average distance travelled by the equipment. The CO2 emissions were derived from annual electricity and fuel consumption. Total CO2 emissions were divided by the annual throughput in order to get average values per TEU. Depending on the terminal, the emissions vary between 9.35 and 24.0 kg CO2/TEU, whereby the average value is 17.29 as can be seen in table 2.5. Table 2.5 CO2 emissions from container terminals of Rotterdam Port

Delta

Total CO2 Emissions (kton CO2/year) 71.30

CO2 Emissions per TEU (kg CO2/TEU) 16.73

Home

15.01

15.01

Hanno

1.20

24.00

APM

35.95

16.34

RST

10.76

09.35

Uniport

6.53

17.18

140.75

17.29

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Container Terminal

Total / Average

Source: Geerlings and van Duin, 2011 34

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

However, it is mentionable that Geerlings and van Duin calculated only emissions within the container terminal (figure 2.8). The above mentioned CO2 value per TEU could be much higher if one would also include landside and waterside emissions beyond terminal boundaries as it has been done by Port of Los Angeles (2010). This resulted in 134.93 kilogram CO2e per TEU, based on total CO2e emissions of 910,647 tonnes and total throughput of 6,748,995 TEUs in 2009. Figure 2.8 Typical land-side sources of air pollution in port

Source: Moon, 2011 However, other ports provided a similar CO2 value to that from Geerlings and Van Duin (2011). For example, the Port of Felixstowe (2010) estimated 17.26 and APM Terminals (2009) presented an average worldwide value of 17.5 kg CO2/TEU. This figure could also serve as assumption for port emissions, in case of a lack of data from the investigated deepwater ports.

2.5.3 Carbon auditing of road freight transport Piecyk (2010) described two basic approaches for measuring CO2 emissions from

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road freight operations, i.e. fuel-based and activity-based approach which have been described previously in section 2.5. The “fuel-based” method multiplies the amount of fuel consumed on a particular trip or during particular time by the corresponding emission factor as illustrated bellow in formula 2.3. Table 2.6 summarises conversion factors from DEFRA (2010) for three most common fuel types.

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

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Formula 2.3 Calculation of CO2 emissions using fuel-based approach ‫ݏ݊݋݅ݏݏ݅݉݁ʹܱܥ‬ሺ݇݃ሻ ൌ ܽ݉‫݈݁ݑ݂݂݋ݐ݊ݑ݋‬ሺ݈݅‫ݏ݁ݎݐ‬ሻ ൈ ݁݉݅‫ݎ݋ݐ݂ܿܽ݊݋݅ݏݏ‬ሺ݇݃‫݁ʹܱܥ‬Ȁ݈݅‫݁ݎݐ‬ሻ

Table 2.6 Conversion factors for diesel, LPG and petrol Fuel Type Diesel LPG Petrol

Units litres litres litres

kg CO2e per unit 2,672 1,492 2,322

Source: adapted from DEFRA, 2010. The “activity-based” emissions are calculated by multiplying the activity factor, expressed in tonne kilometres by CO2e emission factor (formula 2.4). Table 2.7 summarizes activity-based emission factors for heavy goods vehicles (HGVs) based on UK’s average weight utilisation values. Formula 2.4 Calculation of CO2 emissions using activity-based approach ‫ܱܥ‬ଶ ݁݉݅‫ݏ݊݋݅ݏݏ‬ሺ݇݃ሻ ൌ ݀݅‫݈݈݀݁݁ݒܽݎݐ݁ܿ݊ܽݐݏ‬ሺ݇݉ሻ ൈ ‫݀ܽ݋݈ݕܽ݌‬ሺ‫ݐ‬ሻ ൈ ݁݉݅‫ݎ݋ݐ݂ܿܽ݊݋݅ݏݏ‬ሺ݇݃‫ܱܥ‬ଶ ݁Ȁ‫݉݇ݐ‬ሻ

Table 2.7 Emission factors for averagely loaded diesel powered trucks

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Truck Type

Rigid Rigid

Gross Vehicle Weight (tonnes) >7.5-17t >17t

Articulated Articulated

>3.5-33t >33t

% weight laden (UK Ø) 41% 53%

UK Ø payload (tonnes goods carried per truck) 1,82 4,91

0.41693 0.20246

45% 61%

5,56 11,31

0.15438 0.08778

kg CO2e per tonne km

Source: adapted from DEFRA, 2010.

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

However, according to McKinnon and Piecyk (2010) the emission factors for a 40 tonne articulated truck vary in a range from 59 to 109 g CO2 per tkm depending on the various assumptions from several organizations. For example, DEFRA’s (2010) CO2 conversions are based on average fuel consumption values (miles per gallon) from different truck types and vehicle load factors. However, there is a wider range of additional parameters that can affect truck emissions. These are EURO emission standards, road type (e.g. motorways or city roads), road gradient (e.g. flat or mountainous roads), driver behaviour, road congestion and travel speed (Cullinane and Edwards, 2010; IFEU, 2010; McKinnon, 2007; McKinnon, 2010b). Furthermore, Keller and De Haan (1998), Peng et al. (2008), and Kim and Van Wee (2009) argue that a cold engine, so-called cold-start, emits higher level of pollutants than a hot engine. Indeed, during the first three minutes a cold diesel engine emits more than twice as much hydrocarbon (HC), particular matter (PM) and carbon monoxide (CO) as that of hot start (Peng et al, 2008). However, the engine achieves its regular working temperature already after 10 km so that the additional emissions produced by cold-start, are negligible compared to the whole average distance and time that a truck operates with a hot engine (Kim and Van Wee, 2009).

2.5.4 Carbon auditing of rail freight transport CO2 emissions from rail freight highly depend on the energy source used by the locomotives. One distinguishes between diesel and electric trains. Thereby electrically powered vehicles usually emit less CO2 per tkm than diesel powered locomotives as can be seen in table 2.8. Furthermore, it can be noted that emission factors of electrichauled trains also vary significantly between 1.8 and 19 g CO2 per tkm (McKinnon and Piecyk, 2010). This is because the energy mix for electricity production is different for each country. For example, ADEME’s emission factor of 1.8 gram CO2

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per tkm is based on French energy mix that consists of more than 80% of nuclear power. IFEU, on the other hand, estimated an average value of 18 gram CO2 per tkm for Germany, where coal accounts for more than 40% (IFEU, 2010).

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

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Table 2.8 Published Emission Factors for Rail Freight Movement (gCO2 / tkm) Organization

all rail freight

diesel-powered

electric-powered

ADEME

7.3

55

1.8

NTM

15

21

14

22.7

38

19

35

18

INFRAS IFEU

Source: adapted from McKinnon and Piecyk, 2010 There are several calculation methods for estimation of CO2 emissions from rail freight. DEFRA (2010) uses an activity based approach for rail emissions by multiplying the tkm-figure by CO2 conversion factor. However, DEFRA’s emission factor is an overall average of UK’s diesel and electric trains. Thus, there is no differentiation between these two types of locomotives. According to Ceuster et al. (2007) and IFEU (2010) the basic calculation method for CO2 emissions from diesel and electric trains is to determine the energy or fuel consumption of the total train considering the total gross train weight. According to McKinnon and Piecyk (2010) it might be difficult to get distance data between rail terminals, wherefore the authors recommend using the online tool “EcoTransIT” for calculation of carbon emissions from intermodal transport. This tool has been developed by the German institute for energy and environmental research (IFEU) (2010) and major European rail companies. Ecotransit includes a routing algorithm that can link the networks from various transport modes. If, for example, the estimator selects “rail” as transport mode between two locations and the calculated route has no consistent rail-connection between the chosen geographical points, than

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the algorithm uses the road network for the part where is no railway line. This concept is depicted in figure 2.9.

38

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

Figure 2.9 Road and rail network connection by EcoTransIT’s routing algorithm

Source: IFEU, 2010

2.5.5 Carbon auditing of inland waterway transport Reviewing the literature on carbon auditing, only a few publications have been found dealing with carbon footprint of barge transport. WPCI (2010) provides two methods, namely, energy-based approach using annual fuel consumption, and activity-based method by calculating CO2 emissions on the basis of rated power, engine load factor and annual operating time. However, the weaknesses from WPCI’s approaches, is that there might occur difficulties with the acquisition of required data from inland waterway ships, and that both methods are based on annual CO2 emissions and not on TEU or tonne kilometre (tkm) basis. Defra (2010) suggests tkm-based emission factors for container ships. However, Defra’s conversion factors do not differentiate between various inland waterway categories which can accommodate different ship

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sizes (Briene et al., 2006). In order to calculate CO2 emissions, distances between inland waterway terminals are required. Since there is a lack of distance calculation tools for inland waterways, McKinnon and Piecyk (2010) suggest using previously mentioned online Ecotransit tool. The advantage of Ecotransit is that this tool also differentiates between different inland ship classes, namely “class IV” Euroships and Jowi-class container ships that

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

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are used on “>class V” waterways. Figure 2.10 summarizes capacity differences in TEU between these two inland ship categories. Figure 2.10 Inland waterway ship-classes Euroship: used on “class IV” waterways

Jowi-class container vessel: used on “>class V” waterways

Source: European Commission, 2011. Thereby a Jowi-class vessel can accommodate approximately 8 times more TEUs than a class IV ship and around 6 times as much as a train (IFEU, 2010).

2.6 Measures for CO2 reduction of maritime supply chain In order to address the third research question, this section will briefly review the literature concerning decarbonisation of maritime supply chain. AEA Group (2007) investigated CO2 reduction measures for ships focusing on enhancement of fuel efficiency from main engines, improved fleet management and the use of alternative energy sources, such as nuclear power and bio fuels. Also Business and the Environment (2008) suggests to use cleaner fuels, to reduce sea

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speed, to modify ship and propeller design, and to use wind power by implementing kind of sail or kite. Maersk Line (2011) states that larger container vessels produce less CO2 emissions per TEU and that Maersk’s largest triple-E container vessels will probably provide lowest CO2 emissions per TEU.

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

However, McKinnon et al. (2010a) criticise that most literature focus on decarbonisation measures from supply side, wherefore the authors illustrate measures that can be taken by shippers in order to reduce carbon emissions from maritime supply chains. These measures go beyond sea movement and consider door-to-door container transport. Indeed, shippers and especially multinational corporations can affect shipping industry, because approximately 50 percent of worldwide container movements take place between subsidies of global companies (Bichou, 2009). Thus, shippers can directly influence CO2 emissions for example by better utilization of container space and by the choice of transport mode, port and carrier, among others (McKinnon et al., 2010a). In order to reduce port emissions cold ironing can be implemented. This means shoreside electricity supply to vessels (Hall, 2010). Cannon (2009) also propose to use alternative fuels and grid electricity for terminal equipment or to blend diesel with bio diesel. Geerlings and Van Duin (2011) figured out that by adding 30 percent bio diesel, 20 percent less CO2 emissions per TEU can be achieved. Moon (2011) suggests an appointment system for ships and trucks in order to reduce port congestion and the associated GHG emissions. Woolford and McKinnon (2010) argue that the establishment of port-centric logistics and dry port can help to reduce hinterland emissions. The former is based on the idea that distribution centres (DCs) within the port can help eliminating a container movement leg from the supply chain by stripping import containers in the container terminal and distributing the goods directly from the port (Mangan et al., 2008). The dry port concept is based on the idea to provide typical container terminal services such as container freight station (CFS) operations in the hinterland. Thus, cargo can be bundled in inland for onward intermodal transport directly to the sea port and vice

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versa. Hence, CO2 emissions can be reduced since freight is shifted from road to rail or inland waterway (Roso et al., 2009).

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2.7 Conclusion This chapter addressed the historical background and gaps in research. Thereby it was figured out that there is a lack in research dealing with competition between European “deepwater ports”, and carbon emissions associated with maritime container transport between Asia and the European hinterland. In this chapter also green logistics related terms were described which are of particular importance for the first research question. Furthermore, maritime related terms such as hinterland and port competitiveness were explained in order to address the second research question. Section 2.5 reviewed the literature concerning carbon auditing of ports and all relevant transport modes that are involved in maritime container transport chain. Finally, a brief overview of literature concerning CO2 reduction measures has been given. The next chapter will describe the methodology that has been used in order to address the research questions in this book. Thereby, applied carbon auditing methods will be

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based on those introduced in the literature review.

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3. CHAPTER – RESEARCH METHODOLOGY 3.1 Introduction The previous chapter reviewed the literature regarding important maritime and environmental terms and elucidated the various techniques for estimation of CO2 emissions. This chapter will describe which assumptions and carbon auditing techniques have been applied in order to address the three research questions. Firstly, the research philosophy and research approach will be introduced, followed by the description of secondary and primary data sources. Secondly, methodologies will be described, that have been used in order to cover the three research questions. The chapter ends with research reliability, research validity and a brief conclusion.

3.2 Research philosophy One distinguishes between two main research philosophies or paradigms namely “positivist” and “phenomenological” (Hussey and Hussey, 1997; Saunders et al., 2000). Table 3.1 summarizes some key features of these two paradigms. This study is based on positivistic research philosophy, because it uses mainly quantitative data. Table 3.1 Features from positivist and phenomenological paradigm

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Positivistic paradigm

Phenomenological paradigm

Tends to produce quantitative data

Tends to produce qualitative data

Uses large samples

Uses small samples

Concerned with hypothesis testing

Concerned with generating theories

Data is highly specific and precise

Data is rich and subjective

The location is artificial

The location is natural

Reliability is high

Reliability is low

Validity is low

Validity is high

Generalises from sample to population

Generalises from one setting to another

Source: Hussey and Hussey, 1997

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3.3 Research approach Saunders et al. (2000) differentiate between deductive and inductive approach. The later uses methods such as action research or case studies. On the other hand, typical deductive methodologies are surveys and experimental studies that are relevant for this study (Hussey and Hussey, 1997). Deduction is mainly based on quantitative data collection, whereby it does not mean that qualitative data is certainly excluded (Saunders et al., 2000). Data collection is described bellow in more detail.

3.4 Data collection In order to address the three research questions primary and secondary data have been collected. Secondary data are available publically. Figure 3.1 illustrates three types of secondary data. Where no secondary data could be found, primary data have been used.

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Figure 3.1 Types of secondary data

Source: Adapted from Saunders et al., 2000

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3.4.1 Secondary data Secondary data have been accessed by using both printed and electronic sources. The library at Heriot-Watt University (HWU) has been used to get printed books, journals and dissertations. HWU library also provides the online search tool “discovery”, which is connected to over 130 bibliographic databases such as Emerald, Science Direct and others. Additional electronic data have been searched by using Google and various websites from relevant governmental and public organisations. Following keywords (table 3.2) have been used to find appropriate journal articles through the HWU discovery tool. Table 3.2 Key words for secondary data search

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Environment related key words “Air Pollution” “Carbon auditing” “Carbon calculation” “Carbon dioxide” “Carbon dioxide emissions” “Carbon estimation” “Carbon footprint” “CO2 emissions” “CO2 estimation” “CO2 measuring” “CO2 Reduction“ “Container Terminal” + “emissions” “Conversion factor“ “Emission factor“ “Environmental impact” “Feeder ships” + “emissions” “Green Logistics” “Greenhouse gas” “Greenhouse gas emission” “Global Warming Potential” “Inland water way” + “emissions” “Intermodal” + “emissions” “Ocean vessels” + “emissions” “Port” + “emissions” “Road” + “emissions” “Rail” + “emissions” “Truck” + “emissions”

Maritime related key words “Asia Europe trade lane” “Container” “Container movement pattern” “Container maritime transport” “Container port” + “draft” “Container terminal” + “draft” “Container Transport Chain” “Container vessels” + “draft” “Container vessel class” “Container vessel generation” “Deepwater port” “Deepwater port competition” “European North Range” “Hinterland connection” “Hinterland accessibility” “Intermodal” “Liner shipping” “Maritime logistics” “Maritime transport chain” “Maritime supply chain” “Maritime container transport” “North Adriatic Sea ports” “North Italian ports” “North Range Ports” “Port competition” “Port competitiveness”

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Initially, it was important to find container ports that have suitable geographical location and sufficient draft to compete with JWP for the same hinterland. For this reason, the websites from all relevant ports in figure 1.1 and corresponding container terminal operators have been browsed to figure out container terminals with a draft of at least 15.5 meters to be categorised as deepwater ports in this book. For the first research question it was important to find literature that provides carbon auditing methods for the appropriate transport modes and container terminals. Since there has been unsatisfactory range of journal articles, the author also used websites of particular governmental and private organizations in order to obtain secondary data. These organizations are outlined in following list (table 3.3). Table 3.3 Organizations whose websites served for secondary data collection

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Name of Organization

Country

Carbon Trust

UK

IVL - Swedish Environmental Research Institute

SE

DECC – Department of Energy & Climate Change

UK

DEFRA – Department for Environment, Food and Rural Affairs

UK

EPA – Environmental Protection Agency

US

European Commission

EU

Fraunhofer IML – Fraunhofer Institute for Material Flow and Logistics

DE

Freight Best Practice

UK

German Federal Environment Agency

DE

IFEU – Institute for Energy and Environmental Research

DE

IPCC – Intergovernmental Panel on Climate Change

CH

46

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

ISL –Institute of Shipping Economics and Logistics

DE

Standards from British Standards Institution (PAS:2050)

UK

Port of Los Angeles

US

Port of Seattle

US

UNFCCC – United Nations Framework Convention on Climate Change

Int.

WPCI – World Ports Climate Initiative

NL

3.4.2 Primary data In order to obtain primary data, personal interviews (I), a semi-structured questionnaire (II) and online tools for calculation of distances and carbon emissions (III) have been used. These primary data sources are elucidated bellow in more detail: I.

Personal Interviews

Saunders et al. (2000) distinguish between structured, semi-structured and unstructured interviews. In this study two unstructured face to face interviews have been conducted. The interview with Hermann Mueller from the company “JadeWeser-Port Logistics Zone” served to get a general idea in what research area the company is interested and what are the aims of the port. The second interview has been done with the author’s acquaintance Daniel Brick, a professional sea captain from the shipping line “E.R. Shiffahrt”. The conversations with Daniel Brick helped to get particular information regarding maritime related questions. Among others, Daniel recommended a tool for the calculation of distances between sea ports, and

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provided information concerning average speed and berthing time of container vessels. II.

Semi-structured questionnaire

Since there have been no emission figures from the investigated ports, except from the Port of Rotterdam, a semi-structured online questionnaire has been used to get emissions data and other general environmental information from container ports. The

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questionnaire was sent by e-mail to port authorities and container terminal operators. The survey (appendix 7) included both choice-based and opened questions. III.

Online tools for distance and carbon calculation

In order to calculate CO2 emissions, distance data from various transport modes were necessary. For this reason, approved online distance and carbon auditing instruments (table 3.4) have been used. Table 3.4 Applied tools for calculation of distances and CO2 emissions

Transport mode Ocean transport

Tool “Distance Table” from AXS Marine

Features Distance

http://www1.axsmarine.com/distance/ Road transport

“Map24” from Navteq

Distance

http://www.uk.map24.com/ Rail transport

“EcoTransIT” from IFEU

Distance +

http://www.ecotransit.org/ecotransit.en.phtml

CO2 emissions

Inland water way

“EcoTransIT” from IFEU

Distance +

tramsport

http://www.ecotransit.org/ecotransit.en.phtml

CO2 emissions

3.5 Applied methods and tools for calculation of CO2 emissions This section explains the applied methodology in order to address the first research question. It describes how above mentioned tools have been deployed and which assumptions have been used to estimate CO2 emissions.

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3.5.1 Ocean transport For carbon auditing of ocean going vessels formula 2.1 has been used. Since this book focuses on deepwater ports, vessel data from a large 13,000 TEU ship have been applied. Ship emissions have been calculated on the basis of activity times at sea (I) and in port (II) as follows:

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I.

Activity time at sea

For the calculation of activity time at sea, an average speed of 19 knots has been assumed as a result from personal interview with a professional ship captain (Brick, 2011). The distances between ports have been calculated by means of “Distance Table” from AXS Marine. This tool enables to choose between various routing options. It has been determined that the route from Shanghai to Europe should lead through Suez Canal and avoid the piracy zone close to Somalia (figure 3.2), since piracy is still a current problem in this region. Figure 3.2 Defined Asia-Europe sea route in the “Distance Table” tool

Source: AXS Marine, 2011.

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II.

Activity time in port

As a general rule, a container ship calls several ports during the voyage from Asia to Europe. To figure out the average number of stops on the routes from Shanghai to the considered European ports, line service schedules from ten different carriers have been examined (appendix 1). Since Jade-Weser-Port did not start its operations yet, Bremerhaven has been used as reference container port due to its very close proximity to JWP in Wilhelmshaven. According to Daniel Brick, a professional sea captain, a

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13,000 TEU container vessel operating on Asia-Europe trade lane stays seldom for longer than 24 to 36 hours in port. For this reason an average of 30 hours is assumed for 13,000 TEU ships and 24 hours for 8,000 TEU ships. According to European Parliament (2009), the average ship size on Far East-Europe trade lane is 8,000 TEU. However, also world’s largest +13,000 TEU container vessels operate on this route. Hence, carbon auditing has been done for both vessel sizes. Table 3.5 summarizes the applied assumptions for carbon auditing of ocean going vessels. Table 3.5 Assumptions for carbon auditing of ocean transport

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Criterion

Propulsion engine

Auxiliary engine

MCR (13,000 TEU ship)

72,027 kW

14,000 kW

MCR (8,000 TEU ship)

67,824 kW

12,200 kW

Engine load factor (LF) at sea

based on sea speed

0.13

Engine load factor (LF) in port

0.00

0.17

Power emission factor (EF)

0.55223kg CO2e/kWh

0.60221kg CO2e/kWh

Maximum speed (13,000 TEU ship)

24.7 knots

Maximum speed (8,000 TEU ship)

25,2 knots

Average speed at sea

19 knots

Average time (AT) in port

30 hours (13,000 TEU ship)

Average time (AT) in port

24 hours (8,000 TEU ship)

Capacity utilisation

70 % (IFEU, 2010)

Notes: MCR = Maximum Continuous Rating of the combustion engine in use (kW)

Source: based on Port of Seattle, 2009; WPCI, 2010; IFEU, 2010; Brick, 2011

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For clarification, following numerical example explains the calculation of sea transport emissions from a 13,000 TEU ship between Shanghai and Wilhelmshaven (figure 3.3). Figure 3.3 Numerical example for calculation of CO2 emissions from sea transport Distance Shanghai-Wilhelmshaven:

11,122 nm (appendix 1)

Average number of port calls:

7 (appendix 1)

ࡱ࢓࢏࢙࢙࢏࢕࢔࢙ ൌ ࡹ࡯ࡾ ൈ ࡸࡲ ൈ ࡭ࢀ ൈ ࡱࡲ Activity time (AT) at sea: ‫ ܶܣ‬ൌ

ͳͳǡͳʹʹ ݀݅‫݁ܿ݊ܽݐݏ‬ ൌ ൌ ૞ૡ૞ࢎ࢕࢛࢙࢘ ͳͻ ܽ‫݀݁݁݌ݏ݁݃ܽݎ݁ݒ‬

Activity time (AT) in port ‫ ܶܣ‬ൌ ݊‫݋‬Ǥ ‫ ݏ݈݈ܽܿݐݎ݋݌݂݋‬ൈ ܽ‫ ݐݎ݋݌݊݅݁݉݅ݐ݁݃ܽݎ݁ݒ‬ൌ ͹ ൈ ͵Ͳ ൌ ૛૚૙ࢎ࢕࢛࢙࢘ Load Factor (LF) from propulsion engine at sea ‫ ܨܮ‬ൌ ൬

ܽ‫ ݀݁݁݌ݏ݁݃ܽݎ݁ݒ‬ଷ ͳͻ ଷ ൰ ൌ൬ ൰ ൌ ૙ǡ ૝૞૞૚ૠ ݉ܽ‫݀݁݁݌ݏ݉ݑ݉݅ݔ‬ ʹͶǤ͹ MCR

LF

AT

EF

Propulsion engine emissions Æ at sea:

‫ ݏ݊݋݅ݏݏ݅݉ܧ‬ൌ ͹ʹǡͲʹ͹ ൈ ͲǡͶͷͷͳ͹ ൈ ͷͺͷ ൈ Ͳǡͷͷʹʹ͵ ൌ ͳͲǡͷͻͳǡͳͻͳ݇݃‫ܱܥ‬ଶ ݁

Æ in port:

‫ ݏ݊݋݅ݏݏ݅݉ܧ‬ൌ Ͳ

Auxiliary engine emissions Æ at sea:

‫ ݏ݊݋݅ݏݏ݅݉ܧ‬ൌ ͳͶǡͲͲͲ ൈ Ͳǡͳ͵ ൈ ͷͺͷ ൈ Ͳǡ͸Ͳʹʹͳ ൌ ͸Ͷͳǡͳ͹͵݇݃‫ܱܥ‬ଶ ݁

Æ in port:

‫ ݏ݊݋݅ݏݏ݅݉ܧ‬ൌ ͳͶǡͲͲͲ ൈ Ͳǡͳ͹ ൈ ʹͳͲ ൈ Ͳǡ͸Ͳʹʹͳ ൌ ͵ͲͲǡͻͺͷ݇݃‫ܱܥ‬ଶ ݁

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Total ship emissions between SHA and JWP: ‫ݏ݊݋݅ݏݏ݅݉ܧ‬ሺ‫݈݁ݏݏ݁ݒ‬ሻ ൌ ͳͲǡ͹Ͳ͵ǡͷ͹ͻ ൅ ͸Ͷͳǡͳ͹͵ ൅ ͵ͲͲǡͻͺͷ ൌ ͳͳǡ͸Ͷͷǡ͹͵͹݇݃‫ܱܥ‬ଶ ݁ Allocation of CO2 emissions: ‫ݏ݊݋݅ݏݏ݅݉ܧ‬ሺܶ‫ܷܧ‬ሻ ൌ

‫ܱܥ‬ଶ ݁݉݅‫݈݁ݏݏ݁ݒݎ݁݌ݏ݊݋݅ݏݏ‬ ‫ ݕݐ݅ܿܽ݌݈ܽܿ݁ݏݏ݁ݒ‬ൈ ܿܽ‫݊݋ݑ݅ݐܽݖ݈݅݅ݐݑݕݐ݅ܿܽ݌‬

‫ݏ݊݋݅ݏݏ݅݉ܧ‬ሺܶ‫ܷܧ‬ሻ ൌ

ͳͳǡ͸Ͷͷǡ͹͵͹݇݃‫݁ʹܱܥ‬ ൌ ૚ǡ ૛ૡ૙࢑ࢍ࡯ࡻ૛ ࢋȀࢀࡱࢁ ͳ͵ǡͲͲͲ ൈ Ͳǡ͹

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3.5.2 Road transport For the calculation of road emissions activity-based approach has been used by multiplying tonne kilometre (tkm) figures by DEFRA’s CO2 emission factor 0,08778 for an averagely loaded “>33 tones” articulated truck (table 3.6). Transport activity figures (tkm) have been determined by using the average container load weight of 10.5 tonnes (IFEU, 2010) and the distances from each port to particular cities, calculated by means of “Map24”. Table 3.6 Defra’s average conversion factor for an articulated truck (>33t)

Vehicle type Articulated >33t (average load)

Total tonne km travelled e.g. 500 km

X kg CO2e per tonne.km 0,08778 x

Source: DEFRA, 2010. In order to get a basis of comparison, 15 hinterland locations (figure 3.4) have been selected according to their size, economic importance and geographical location.

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Figure 3.4 Map containing considered deepwater ports and hinterland locations

Notes: Red locations: connected to rail, road and inland waterway; Yellow locations: connected to rail and road.

Source: Google Maps, 2011 52

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

Figure 3.4 summarizes these 15 locations, whereby cities that are represented by yellow place marks are accessible by road and rail, and red place marks can additionally be arrived by inland waterway ships.

3.5.3 Rail intermodal transport For estimation of rail carbon emissions also above mentioned hinterland locations have been used as reference points. The online “EcoTransIT” tool served for carbon auditing. This is the only publically available tool that calculates distances between railway stations at European level. The estimator has to enter freight weight (in tonnes) or number of TEUs. Thereby one TEU with “average goods” is equal to 10.5 tonnes (IFEU, 2010). After selection of relevant transport mode, origin and destination railway station, the tool calculates air emissions, expressed in tonnes CO2 equivalents (t CO2e) per TEU.

3.5.4 Inland waterway intermodal transport Ecotransit has also been used for carbon auditing of inland waterway transport. However, the distinctiveness is that not all considered hinterland locations are connected to barge services, and that only the ports of Rotterdam, Antwerp and Zeebrugge are located at the entrance to the European inland waterway network. Figure 3.5 illustrates applied Ecotransit settings for inland navigation. In order to calculate barge emissions the estimator has to type in the number of TEUs, select the location type (e.g. Harbour), enter the names of origin and destination location and choose between “Euro ship” (class IV) or “>class V” ship type as emphasised by the red circle in figure 3.6. Zeebrugge and Dortmund are connected to class-IV waterways as emphasised by the red circles in bellow map. Therefore, for all Copyright © 2014. Diplomica Verlag. All rights reserved.

routes that contain at least one of these locations, “Euro ship” has been selected as ship type. Remaining routes have been calculated on the basis of “>class V” ships.

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Figure 3.5 EcoTransIT tool settings for inland waterway intermodal transport

Source: Ecotransit, 2011.

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Figure 3.6 Connection of sea and inland ports to different inland waterway classes

Notes: Black circles: locations with connection to “>class V” waterways; red circles: connection to “class IV” waterways

Source: adapted from IFEU, 2010

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3.5.5 Average hinterland emissions To estimate average CO2 emissions that include all hinterland transport modes, modal split data from each port have been used, which are summarized in table 3.7. Since no modal split data from Port of Trieste could be found, the author applied modal split figures from Italian domestic transport provided by Eurostat (2011). Table 3.7 Modal split data from the investigated deepwater ports Port

road (%)

rail (%)

barge (%)

Rotterdam

56

11

33

Antwerp

56

10

34

Zeebrugge

59

40

1

Trieste

88

12

n.a.

Wilhelmshaven (JWP)

50

50

n.a.

Source: based on Port of Rotterdam, 2010; Eurostat, 2011; Jade-Weser-Port, 2009; Port of Antwerp, 2011; Port of Zeebrugge, 2011 Following numerical example demonstrates how average hinterland emissions have been determined. Bellow example is subdivided into two parts, namely emissions from Rotterdam-Hannover and Rotterdam-Dortmund transport. This is done because Dortmund can be served by road, rail and barge, whereas Hannover is only accessible

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by road ad rail.

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Figure 3.7 Numerical example for calculation of average hinterland emissions Average hinterland emissions between “Rotterdam and Hannover”: Road emissions:

418 kg CO2e/TEU

Æ 56% (modal split)

Rail emissions:

92 kg CO2e/TEU

Æ 11% (modal split)

Barge emissions:

0

Æ 33% (modal split)

‫ ݏ݊݋݅ݏݏ݅݉ܧ׎‬ൌ ൬Ͷͳͺ ൈ

ͷ͸ ͳͳ ൰ ൅ ൬ͻʹ ൈ ൰ ൌ ૜૟૝݇݃‫݁ʹܱܥ‬Ȁܶ‫ܷܧ‬ ͷ͸ ൅ ͳͳ ͷ͸ ൅ ͳͳ

Average hinterland emissions between “Rotterdam and Dortmund”: Road emissions:

269 kg CO2e/TEU

Æ 56% (modal split)

Rail emissions:

55 kg CO2e/TEU

Æ 11% (modal split)

Barge emissions:

180 kg CO2e/TEU

Æ 33% (modal split)

‫ ݏ݊݋݅ݏݏ݅݉ܧ׎‬ൌ ൬ʹ͸ͻ ൈ

ͷ͸ ͳͳ ͵͵ ൰ ൅ ൬ͷͷ ൈ ൰ ൅ ൬ͳͺͲ ൈ ൰ ൌ ૛૚૟݇݃‫݁ʹܱܥ‬Ȁܶ‫ܷܧ‬ ͳͲͲ ͳͲͲ ͳͲͲ

3.5.6 Port related emissions In order to obtain port emissions data, a semi-structured questionnaire have been conducted. However, due to a lack of responses an average figure of 17.5 kg CO2 per TEU has been used. This figure is the global average of APM Terminals and similar

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to the values from the ports of Rotterdam (Geerlings and Van Duin, 2011) and Felixstowe (Port of Felixstowe, 2010).

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3.6 Investigation of port characteristics and hinterland connectivity The second research question has been addresses by examining data regarding particular port characteristics and hinterland connectivity. This has been done by using secondary data from the websites of container terminal operators and port authorities. In addition, online tools such as Google Earth and Ecotransit have been used. Google Earth served to determine the motorways that lead directly to a port. By zooming in on the particular motorway it has also been possible to figure out the number of road lanes. Ecotransit helped to find out if a port provides an electrified rail connection or not.

3.7 CO2 reduction measures for JWP’s Maritime Supply Chain In order to address the third research question, findings from first and second research question have been analysed with regard to possible CO2 reduction opportunities. Furthermore, some suggested decarbonisation measures are based on those introduced previously in the literature review.

3.8 Research reliability The research methodology is reliable when the researcher or an external person repeats applied methodology and gets same results (Hussey and Hussey, 1997). The quantification of CO2 emissions depends on particular instruments, calculation approaches, emission factors and assumptions. Hence, the results can vary under various circumstances.

3.9 Research validity

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Research validity means that the results represent ‘a real picture of what is being studied’ (Hussey and Hussey, 1997 p.173). This book concentrates on deepwater ports and hence on CO2 emissions from ultra large 13,000 TEU container vessels. However, also average 8,000 TEU container ships, operating between Asia and Europe, have been considered. Carbon emissions have been estimated by using established carbon auditing methods, instruments and distance calculation tools. Furthermore, assumptions with practical orientation have been applied, such as the average vessel

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speed, average number of port calls and anchoring time in port. Thus, the validity of this research can be evaluated as high.

3.10 Conclusion This chapter described the applied methodology in order to address the three research questions. Particular emphasis has been placed on carbon auditing methods, since this is the most important part in the context of the overall objective. The results from the

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research are presented in following chapter.

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4. CHAPTER – FINDINGS AND RESULTS 4.1 Introduction This chapter outlines the findings obtained from the implemented research. The results will be used in order to answer the research questions (RQ) which are listed bellow, as a reminder. RQ1: How much CO2 emissions are produced by container transport passing through the investigated deepwater ports and what regions can be reached more environmentally friendly through Jade-Weser-Port rather than through Rotterdam, Zeebrugge, Antwerp and Trieste? RQ2: What are the general port characteristics and the quality of hinterland connections? RQ3: What are the possible measures for reduction of CO2 emissions of maritime supply chains or door-to-door container transport passing through the Jade-WeserPort? Each of the following three sections will address one research question. The chapter will end with a brief summary.

4.2 Research Question 1 The findings concerning first research question will be presented separately for ocean, road, rail and barge transport. Subsequently average hinterland and total maritime supply chain emissions will be outlined. Thereby, average hinterland emission results are based on the modal split from each port. Total maritime transport chain emissions

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consist of ocean freight, port and average hinterland emissions.

4.2.1 CO2 emissions from ocean transport Table 4.1 illustrates the distances between Shanghai and the investigated ports. Due to Wilhelmshaven or JWP is located at the greatest distance from Shanghai, the CO2 emissions are the highest compared to other deepwater ports. The reverse applies to Trieste due to its geographical proximity to Asia.

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Table 4.1 Distances between Shanghai and the investigated deepwater ports

Shanghai

Zeebrugge Rotterdam 10,869 nm 10,933 nm

Antwerp Wilhelmshaven Trieste 10,937 nm 11,122 nm 8,954 nm

Diagram 4.1 compares CO2 emissions from 8,000 and 13,000 TEU vessel operating at a speed of 19 knots and having the same capacity utilization of 70 per cent. See also appendix 1 for more details. Thereby it is recognisable that larger vessel emits by around 51 percent less carbon emissions per TEU. Furthermore, with increasing vessel capacity (8,000 Æ 13,000 TEU) the difference of carbon emissions over the same distance, here between Trieste and Wilhelmshaven, decreases by 125 kg CO2e per TEU (366 kg CO2 Æ 241 kg CO2) (diagram 4.1). Diagram 4.1 CO2 emissions from 8,000 and 13,000 TEU ships operating at a speed of 19 knots (kg CO2e/TEU)

+366 kg CO2

+51%

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+241 kg CO2

Diagram 4.2 shows that an increase in cruising speed from 19 to 24 knots would result in around 53 percent higher CO2 emissions per TEU. 24 knots was the average operating speed before the global financial crisis in 2008.

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Diagram 4.2 Comparison of CO2 emissions from a 13,000 TEU ship operating at speeds of 19 and 24 knots (kg CO2e/TEU) .

+53.5% +53.2%

4.2.2 CO2 emissions from road transport Diagram 4.3 illustrates CO2 emissions associated with road transport from each port to the 15 selected hinterland locations. The diagram shows that Trieste provide considerably higher emissions for 10 out of 15 locations as emphasized bellow by red circles. Furthermore, emissions from the northern Ports are quite similar in the Dortmund-Munich range, as highlighted with the black border. Thereby, Antwerp shows the lowest emissions compared to Zeebrugge, Rotterdam and Jade-Weser-Port. Another fact is that the Eastern European cities Poznan, Warsaw and Prague can be reached most environmentally friendly from Wilhelmshaven by road. The green table fields bellow highlight from which port the particular location can be reached by road

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under minimum carbon emissions.

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Diagram 4.3 CO2 emissions from road transport (in kg CO2e/TEU)

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Hannover Berlin Cassel (Kassel) Erfurt Leipzig Dortmund Cologne (Köln) Frankfurt a.M. Mannheim Stuttgart Nuremberg (Nürnberg) Munich (München) Prague (CZ) Poznan (PL) Warsaw (PL)

Zeebrugge Rotterdam 500 418 757 673 474 423 624 591 707 656 312 269 284 274 455 452 483 472 605 594 655 652 810 806 918 884 984 901 1271 1188

Antwerp Wilhelmshaven 419 215 676 453 394 354 543 402 626 433 232 257 204 333 375 448 402 520 524 634 574 588 729 784 837 668 904 681 1190 968

Trieste 1046 1001 902 829 862 1022 995 826 794 677 620 463 741 1229 1066

4.2.3 CO2 emissions from rail transport In terms of rail transport, again Trieste records the highest CO2 emissions for most hinterland locations as emphasized in diagram 4.4 by red circles. Considering the cities in the Dortmund-Munich range, which are emphasised by the black border, it appears that Jade-Weser-Port (Wilhelmshaven) provides the highest bars for all those

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locations compared to other North-Range-Ports. This was not the case for road emissions. Furthermore, Wilhelmshaven is no longer the most environmentally friendly solution for Prague and Warsaw but rather Port of Trieste as highlighted by the green table fields bellow.

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Diagram 4.4 CO2 emissions from rail transport (in kg CO2e/TEU)

Hannover Berlin Cassel (Kassel) Erfurt Leipzig Dortmund Cologne (Köln) Frankfurt a.M. Mannheim Stuttgart Nuremberg (Nürnberg) Munich (München) Prague (CZ) Poznan (PL) Warsaw (PL)

Zeebrugge Rotterdam Antwerp Wilhelmshaven Trieste 120 92 100 55 230 180 150 160 120 220 120 100 100 89 200 150 140 140 120 210 170 160 150 110 210 73 55 56 79 240 57 49 45 100 230 98 90 86 130 190 110 110 100 150 170 120 130 130 170 150 150 140 140 160 140 170 180 180 190 98 250 220 240 190 130 280 240 260 210 280 410 380 390 350 300

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4.2.4 CO2 emissions from barge transport Diagram 4.5 outlines CO2 emissions from barge transport to the six cities which are connected by inland waterways to the ports of Zeebrugge, Rotterdam and Antwerp. Thereby Rotterdam represents the most environmentally friendly solution. Inland navigation from Zeebrugge to almost all hinterland locations, excepting Dortmund, produces approximately twice as much carbon emissions, compared to other ports. This can be explained by the fact that Dortmund and Zeebrugge can only be served by “class IV” Europeships which provide around 8 times lower capacity and hence emit more CO2 per TEU than a Jowi-class vessel that operates on “>class V” waterways and serves Rotterdam and Antwerp.

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Diagram 4.5 CO2 emissions from barge transport (in kg CO2e/TEU)

Comparing CO2e figures in the bars from diagram 4.5 with those from rail transport for the same destinations (diagram 4.4) it becomes obvious that waterway transport emits several times more CO2e per TEU than rail. Diagram 4.6 exemplifies the difference between barge and rail emissions on the example of Dortmund. This phenomenon will be explained in more detail in subsection 5.2.4.

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Diagram 4.6 Comparison of rail and barge emissions (kg CO2e/TEU) on the example of Dortmund

+411% +393% +327%

4.2.5 Average hinterland emissions The average hinterland emissions (diagram 4.7) are calculated by using individual modal split data from each port (table 4.2) and previously presented CO2 emissions data from road, rail and barge. The complete calculation table can be found in appendix 5. Table 4.2 Modal slit from each deepwater port

Thereby, Wilhelmshaven shows better results compared to those from road and rail. If looking at green fields in bellow table it becomes apparent that Jade-Weser-Port performs best, since only three out of 15 hinterland locations can be reached more

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environmentally friendly through other deepwater ports. Thereby, neither Rotterdam nor Zeebrugge provide minimum carbon emissions for any inland location. It is also clearly visible that in case of 12 cities Trieste presents poorest results emphasised by red circles. However, the Italian port shows best result for Munich, what was also the case in terms of road and rail emissions. These findings will be analysed in more detail in subsection 5.2.5.

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Diagram 4.7 Average CO2 emissions from hinterland transport (in kg CO2e/TEU)

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Hannover Berlin Cassel (Kassel) Erfurt Leipzig Dortmund Cologne (Köln) Frankfurt a.M. Mannheim Stuttgart Nuremberg (Nürnberg) Munich (München) Prague (CZ) Poznan (PL) Warsaw (PL)

Zeebrugge Rotterdam Antwerp Wilhelmshaven 347 364 371 135 524 587 597 287 304 242 225 221 432 517 482 261 490 575 554 272 217 216 210 168 193 202 170 216 313 335 304 289 334 352 323 335 411 449 418 402 454 509 475 374 552 704 646 487 648 775 746 429 700 793 807 446 923 1055 1069 659

Trieste 948 907 818 754 784 928 904 750 720 614 563 419 668 1115 974

4.2.6 Total maritime supply chain emissions Diagram 4.8 outlines total CO2 emissions consisting of ocean, port and average hinterland emissions. Thereby, ocean emissions are based on the values from a 13,000

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TEU ship, since this vessel size is of particular relevance for deepwater ports. Port emissions are assumed to be 17.5 kg CO2e per TEU as described previously in the research methodology (subsection 3.5.6). Diagram 4.8 Total average maritime supply chain emissions (in kg CO2e/TEU)

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Ocean transport Port emissions

Zeebrugge Rotterdam Antwerp Wilhelmshaven Trieste 1245 1247 1248 1268 1027 17,5 17,5 17,5 17,5 17,5

Total average CO2 emissions (in kg CO2e/TEU) Hannover 1609 1629 1636 Berlin 1786 1852 1863 Cassel (Kassel) 1566 1507 1491 Erfurt 1695 1781 1747 Leipzig 1752 1839 1819 Dortmund 1479 1481 1476 Cologne (Köln) 1456 1466 1435 Frankfurt a.M. 1575 1600 1569 Mannheim 1596 1617 1589 Stuttgart 1673 1714 1683 Nuremberg (Nürnberg) 1717 1774 1740 Munich (München) 1814 1968 1911 Prague (CZ) 1910 2040 2012 Poznan (PL) 1962 2058 2072 Warsaw (PL) 2185 2320 2334

1421 1572 1507 1547 1557 1454 1502 1575 1621 1688 1660 1773 1715 1731 1945

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1993 1952 1863 1799 1828 1973 1948 1794 1764 1659 1608 1464 1713 2160 2019 67

In terms of Trieste, large gaps between the bars disappeared, compared to diagrams 4.3, 4.4 and 4.7. The green and red fields in the table above illustrate the lowest and highest CO2 emissions, respectively. Thereby, it appears that not a single hinterland location can be reached most environmentally friendly through Rotterdam and that this port shows poorest results together with Trieste. The black circles in diagram 4.8 illustrate those cities where the difference between CO2 emissions of North-Range-Ports is quite low. Thus, it can be assumed that these hinterland locations are located in the area where there is an overlapping of hinterlands from different ports (see also subsection 2.4.2). This overlapping area is depicted by the red corridor in figure 4.1. In this region JWP provides similar CO2 emissions as other deepwater ports. Figure 4.1 Corridor that represents the overlapping of hinterlands from considered deepwater ports

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Notes: Red locations are connected to rail, road and inland waterway; Yellow locations are connected to rail and road.

Source: Google Maps, 2011

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Locations that are situated above the red border represent the region in which JadeWeser-Port appears to be most environmentally friendly solution. The opposite applies to area underneath the corridor. For a summary, diagram 4.9 illustrates only those cities that can be reached under minimum CO2 emissions from Jade-Weser-Port. Thereby one can see that in terms of Dortmund and Prague, Wilhelmshaven shows almost the same carbon values as some of its competitors. Thus, in order to answer the first research question, one can state that north-eastern part of Germany (i.e. Hannover, Berlin, Erfurt and Leipzig) and northern region of Eastern Europe (i.e. Poznan and Warsaw) can be reached more environmentally friendly through JWP compared to other European deepwater ports. Diagram 4.9 Hinterland locations that can be reached most environmentally through Jade-Weser-Port

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4.3 Research Question 2 The strengths of a port do not only consist of its environmental performance within a maritime supply chain. Rather, a deepwater port should also provide good maritime accessibility, sufficient draft and suitable terminal equipment to serve E-class or Emma Maersk-class ships. Furthermore, as already mentioned in the literature review, ports that want to be competitive should integrate in global supply chains. For this

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reason it was also investigated if a port provides a logistics zone or even industry area within or around port boundaries. Competitiveness of a port is also associated with capacity for further expansion and good hinterland accessibility. The tables bellow summarise the results concerning general port characteristics (table 4.3) and connections to hinterland transport modes (table 4.4). For clarification, section 4.3 will only present research findings. These will then be evaluated and discussed in next chapter. This section is subdivided into five

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subsections, namely one for each of the five investigated deepwater ports.

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Source: based on Port of Rotterdam, 2011; ECT, 2011; APM Terminals, 2011; Jade-Weser-Port, 2011; Jade-Weser-Port, 2009; Port of Antwerp, 2011; Port of Antwerp, 2009; DP World, 2011; Port of Zeebrugge, 2011; PSA Zeebrugge, 2011; Trieste Marine Terminal, 2011

Table 4.3 General port characteristics from the investigated ports

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Source: based on Port of Rotterdam, 2011; Port of Antwerp, 2011; Port of Zeebrugge, 2011; Jade-Weser-Port, 2009; Andree, 2008; Eurostat, 2011

Table 4.4 Hinterland transport mode connections from the investigated ports

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4.3.1 Jade-Weser-Port in Wilhelmshaven Jade-Weser-Port is expected to start its operations in August 2012 using 1000 meters of its quay. The full quay length of 1725 meters is expected to be ready in August 2013. Figure 4.2 illustrates a simulated picture from the completed container terminal. Figure 4.2 Simulated picture from completed Jade-Weser-Port

Source: Jade-Weser-Port, 2011 JWP has a natural water depth of 18 meters and can accommodate container vessels with a tide independent draft of 16.5 meters. Furthermore the port provides a turning basin of 700 meters that enables uncomplicated and rapidly docking for the world’s largest container vessels. The quay will be equipped with 16 gantry cranes with an outreach of 25 container rows. Jade-Weser-Port will consist of a 160 hectares (ha) large logistics zone and a container terminal with an area of 130 ha providing an annual container handling

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capacity of 2.7 million TEU. Just behind the port there is an area of 400 ha for further expansion. Figure 4.3 illustrates the layout and summarizes some general characteristics from JWP. Furthermore the picture depicts the terminal’s connection to rail and motorway. However, the road that connects JWP with the motorway A29 currently has only one lane in each direction over a distance of approximately three kilometres, whereafter the road becomes wider by one additional lane per direction.

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Figure 4.3 Layout from Jade-Weser-Port

Source: Jade-Weser-Port, 2011 Although Jade-Weser-Port is connected to the German railway network, the rail-track is not electrified over a distance of 53.14 km. Furthermore, between Wilhelmshaven and Oldenburg there are two single-track sections with five and seven kilometres length. It is expected that container hinterland transport will be equally split between road and rail.

Port of Rotterdam The port of Rotterdam is spread over a length of around 40 kilometres along the

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Meuse River. The three deepwater terminals ECT Delta, Euromax and APM Terminal are located at sea-side port entrance at Maasvlakte 1 (figure 4.4). Thereby Euromax is currently being developed. Rotterdam provides a maximum draft of 22.55 meters which is the greatest compared to other European deepwater ports. All terminals together have a total quay length of 7,070 meters, a terminal area of 4,562 ha and a container handling capacity of 10 million TEU.

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Figure 4.4 Deepwater Terminals from Port of Rotterdam at Maasvlakte 1

Source: Google Earth, 2011 Rotterdam’s total port area is greater than 10,000 ha of which 5,252 ha are industrial sites. With the currently developing “Maasvlakte 2”, the port will add additional area of 2,000 ha wherefrom industry and logistics zones will make up 1,000 ha. Furthermore Maasvlakte 2 will raise Rotterdam’s container handling capacity to a total of 18 million TEU. Figure 4.5 illustrates the simulated picture showing Maasvlakte 1 and 2 after completion. Rotterdam provides also superior hinterland accessibility. The port is surrounded by a network of numerous motorways, whereby motorway A15 with 2 lanes in each direction leads directly to Maasvlakte 1. The three

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deepwater terminals are also connected to electrified multi-track railway network.

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Figure 4.5 Simulated picture showing Maasvlakte 1 and 2

Source: Port of Rotterdam, 2011 Besides rail there is also superior connection to the European inland waterway network by “class VI” waterways that can be served by extra large “Jowi-Class” inland container ships with a capacity of 470 TEU as described previously in subsection 2.5.5.

4.3.2 Port of Antwerp Similar to Rotterdam, Antwerp’s logistics zones and container terminals are built along the banks of a river over a length of approximately 20 kilometres. Two container terminals, namely Deurganck Terminal and Antwerp Gateway, provide a draft of 15.5 to 16 meters (figure 4.6). Thereby, Deurganck Terminal is still being developed and will become approximately twice as large as it is actually. At the current status the two deepwater terminals provide a total quay length of 3,430 meters

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equipped with 22 gantry cranes having an outreach between 18 and 22 container rows.

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Figure 4.6 Deepwater Terminals from Port of Antwerp

Source: Google Earth, 2011 The road “R2” that consists of 2 lanes in each direction connects both terminals with motorway “A12” through a tunnel system as illustrated in figure 4.7. Within an area of 30 km there is a network of more than ten motorways.

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Figure 4.7 Tunnels that connect Antwerp’s deepwater terminals with motorway A12

Source: Google Earth, 2011

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Furthermore Antwerp provides a connection to the European railway and inland waterway network. Both transport modes have similar characteristics as already described for Rotterdam Port. Alongside the port there is a huge logistics zone and industry area, within which there are warehousing spaces of 5.4 million m² for nearly all types of goods such as chemical, tobacco, sugar and many others. Currently the port is developing two multimodal logistic parks, namely “Waasland” and “Schijns” on the left and right bank of the river, respectively. However, during the research one main drawback was figured out: Although Antwerp has two deepwater terminals the approach channel provides a tide-independent draft of only 13.10 meters or 15 meters when using tide. Thus, Antwerp loses its theoretical status as deepwater port, since vessels with a draft of 15.5 meters cannot access the port.

4.3.3 Port of Zeebrugge Port of Zeebrugge is situated directly at the Belgian coast and provides good maritime accessibility through its advantageous location and a draft of 16 meters. The port has two deepwater container terminals which are operated by PSA Zeebrugge and APM

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terminals as depicted in figure 4.8.

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Figure 4.8 Deepwater Terminals from Port of Zeebrugge

Source: Google Earth, 2011 Both terminals provide together an area of 91 ha and a quay length of 1.5 km, whereby one should mention that PSA’s terminal is still being developed and will

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raise the port’s capacity significantly after completion as can be seen in figure 4.9.

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Figure 4.9 PSA’s container terminal data from first and final construction phase

Source: adapted from PSA Zeebrugge, 2011 Zeebrugge is connected to three different transport modes, similar to Rotterdam and Antwerp, whereas the inland waterways can only accommodate smaller Class-IV vessels as depicted in figure 4.10 by means of orange lines. Below figure also shows that Zeebrugge is located quite far away from the main waterway route that leads into the German hinterland. Rotterdam, on the other hand, provides the best location in order to serve the industrial areas in Ruhr Region and Southern Germany by barge as

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emphasised by the black circles. Zeebrugge’s disadvantageous inland waterway connection is probably one reason why barge transport accounts for merely one percent in the port’s modal split. However, container transport by rail accounts for around 40 percent. Besides rail there is also good road connection through two fourlane roads, i.e. E403 and N34a, which come together at port entrance as has been illustrated in figure 4.8.

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Figure 4.10 Rotterdam’s, Antwerp’s and Zeebrugge’s connection to the European inland waterway network

Source: Promotie Binnenvaart Vlaanderen, 2011 However, Zeebrugge has hardly industry within the port area but rather huge “Roll-on Roll-off” (Ro-Ro) facilities. The logistics zone comprises only 8 ha and consists of a few typical logistics services such as consolidation, cross-docking and CFS operations. However for future expansion there is land available around the port.

4.3.4 Port of Trieste The Italian Port of Trieste in the Northern Adriatic Sea has the major advantage that the distance to Shanghai is by roughly 2000 nautical miles shorter compared to northern considered ports. Trieste Marine Terminal (figure 4.11) provides a natural draft of 18 meters and is the smallest container terminal compared to other deepwater

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ports. Furthermore, the quay cranes have quite short outreach with maximum 17 rows, so that the terminal cannot serve an Emma Maersk-class ship with a width of 22 container rows.

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Trieste Port is stretched over around 10 kilometres along the coast. However, since the port is surrounded by densely built city, there is hardly land available for further expansion. Figure 4.11 Trieste Marine Terminal

Source: Google Earth, 2011 However, Trieste has an industrial port that is connected with the container terminal by rail and a 4-lane motorway. Furthermore, within a radius of 30 kilometres there is a network of numerous motorways indicating good port accessibility by road. Trieste also provides electrified multi-track rail connection that is assumed to have 12 percent share of total hinterland transport. However, this assumption is based on the modal split from Italy, due to a lack of data from the port’s hinterland container traffic.

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4.4 Research Question 3 Results concerning the third research question can be derived both from the findings of previous two research questions and from the literature review. To begin with ocean transport, it was found that a 13.000 TEU vessel emits by around 51% less CO2 emissions per TEU compared to an average 8,000 TEU ship (diagram 4.1). Furthermore, better vessel capacity utilization means that total ship emissions

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would be allocated to a larger number of TEUs, resulting in reduced average carbon emissions per container. It was also found that ocean going vessels burn dirty residual oil that produces by far more air pollutants compared to cleaner fuels. From these findings one can derive four measures for reduction of ocean transport emissions which are summarized in bellow figure. Figure 4.12 Measures for reduction of ship emissions

A container vessel stays approximately 30 hours in port. If one considers that there are on average 7 port calls between Shanghai and the investigated ports (8 stops in case of Zeebrugge), one gets an average total duration of 210 hours a vessel spends in port. During that time a 13.000 TEU vessel emits more than 300 tonnes CO2e (appendix 1). To avoid air pollution from vessels while anchoring, it is recommended to connect ships to on-shore electricity. Since JWP can accommodate only four E-class or Emma Maersk-class ships at one time, associated with the quay length of 1,725 meters, the terminal operator should implement an appointment system for vessels in order to reduce port congestion and the associated ship emissions near the terminal. The appointment system can also be applied to trucks to avoid landside congestion. Also energy efficient terminal equipment or the mixing of diesel fuel with biodiesel can contribute to CO2 reduction in port. To sum up, following measures can help reducing port emissions.

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Figure 4.13 Measures for reduction of port emissions

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Although JWP is directly connected to motorway A29, first three kilometres of the road that leads into the terminal consists of only one lane in each direction. This could result in road congestions in times of high container traffic volumes. To avoid or reduce congestions and the associated higher CO2 emissions from trucks, the road should be widened in order to get two lines in each direction. It was also found that JWP’s rail connection is the worst from all investigated ports since more than 53 kilometres of the railway are not electrified and there are single-track sections of 5 and 7 kilometres. Considering JWP’s objective to move 50 percent of its hinterland container traffic by rail, there is a need to develop its rail connection in order to provide continuous double-track electrified rail track over the full distance between Wilhelmshaven and Oldenburg. Hinterland emissions can also be reduced by implementing port centric logistics. This concept enables to reduce hinterland container movement by emptying the containers in the port. Figure 4.14 summarizes CO2 reduction measures for hinterland transport through Wilhelmshaven. Figure 4.14 Measures for reduction of hinterland emissions

4.5 Summary This chapter introduced the results from the three research questions. First research question was answered by indicating those hinterland regions that can be reached more environmentally friendly through Jade-Weser-Port, namely Northern Germany and North East Europe. Findings from second research question were summarized in Copyright © 2014. Diplomica Verlag. All rights reserved.

tables 4.3 and 4.4 illustrating general port features and characteristics of hinterland transport mode connections, respectively. Third research question was addressed by suggesting measures for CO2 reduction of ocean freight, port handling and hinterland transport. Next chapter will discuss above findings in more detail.

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5. CHAPTER – ANALYSIS 5.1 Introduction Chapter 5 will analyse the findings from previous chapter. For remembrance, the overall objective of this research has been carbon auditing of container transport from Far East into the hinterland from Jade-Weser-Port in comparison with other European deepwater ports. Thereby first research question served to compare the ports on the basis of CO2 emissions. Since the competitiveness of a port consists of more than its environmental performance, second research questions examined particular container terminal features and hinterland connectivity of the ports. Third research question has helped to indicate opportunities for decarbonisation of maritime doo-to-door container transport passing through the deepwater port of Wilhelmshaven (JWP). The three research questions have been illustrated at the beginning of previous chapter as a reminder. This chapter will analyse the findings from each research question separately end will conclude with a brief summary.

5.2 Research question 1 The analysis of first research question is subdivided into six subsections discussing the findings separately for ocean, road, rail, barge, average hinterland and total maritime supply chain emissions.

5.2.1 CO2 emissions from ocean transport The results from subsection 4.2.1 showed that an 8,000 TEU vessel emits by around 51 percent more carbon emissions per TEU compared to a 13,000 TEU ship, although the larger vessel itself produces more CO2 emissions on the same trip. The reason for this phenomenon is that the minor additional carbon emissions (ca. 7.5%) of bigger Copyright © 2014. Diplomica Verlag. All rights reserved.

vessel are allocated to 62.5 percent more TEUs (appendix 1). Thus larger container vessels enable better exploitation of economies of scale what also indicates why shipping lines in recent times order even larger container vessels, headed by Maersk’s “triple E” class ships with a capacity of 18,000 TEU.

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It was also found that a raise in speed from 19 to 24 knots leads to approximately 53 percent higher carbon emissions (diagram 4.2). The latter used to be common operating speed before global financial crisis in 2008. The speed of 19 knots is socalled slow steaming speed and is widely used at present time to keep fuel consumption and costs per TEU at minimum level. Carbon emissions were calculated on the basis of engine power and load factor. Since the engine load factor is based on an “X3-equation” (formula 2.2), it increases accordingly with rising vessel speed (diagram 5.1) and hence leads to higher carbon emissions. This also means that further speed reduction would result in even lower CO2 emissions. For example, if one changes the speed from 19 to 16 knots in the Excel carbon auditing tool (appendix 1), one gets even lower CO2e value per TEU by 25.5 percent. This underpins also theoretical finding during the literature review concerning strong CO2 savings associated with reduction of vessel speed (section 2.5.1).

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Diagram 5.1 Increase of engine load factor with rising vessel speed (knots)

However, reduced speed increases the travelling time from Shanghai to Wilhelmshaven by 110 hours (appendix 1). This means that more vessels would be needed to provide the same service. Theoretically, more vessels emit more CO2 emissions. However, according to a survey one fleet with 14 ships emitted by 50%

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less CO2 emissions than a fleet with 10 ships operating at higher average speed by 5.5 knots (Business and the Environment, 2008).

5.2.2 CO2 emissions from road transport Road emissions are directly related to the distance. Hence, the nearer a hinterland location is located to the port the less CO2 emissions are produced. For remembrance, CO2 emissions were calculated by multiplying tkm-data by Defra’s conversion factor for an averagely loaded “>33t articulated truck” (UK average). However, as mentioned in the literature review, emission factors can vary significantly depending on a wide range of parameters. For instance, by considering road gradient the transport from Trieste to Germany could result in higher CO2 emissions because a truck would have to pass high proportion of mountainous roads in contrast to North Range ports that are located in lowland areas. Furthermore, the more containers a port handles the higher is utilization of road capacities. In terms of very large ports, such as Rotterdam and Antwerp there is increased risk of road congestion around the port since high amount of hinterland traffic must be moved on available infrastructure. However, one can expect that over medium term trucks will become more environmentally friendly through European regulations such as required minimum EURO emission standards for new vehicles. For example, from 1 January 2011 all new trucks must provide EURO V emission standard. This would, ceteris paribus, lead to lower truck emission factors as illustrated bellow in table 5.1. However, with raising hinterland traffic and the associated increase in road congestions, total road emissions might increase. Furthermore, truck remains the most environmentally unfriendly surface transport mode due to its limited capacity of 40 tonnes in most

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European countries.

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Table 5.1 Emission factors for EURO I–V vehicles (>34-40 tonnes) CO2

NOx

SO2

PMdir

EURO I

(g/tkm) 72

(mg/tkm) 683

(mg/tkm) -

(mg/tkm) 21

EURO II

69

755

-

10

EURO III

72

553

90

12

EURO IV

70

353

-

2

EURO V

66

205

-

2

Notes: EC = energy consumption; CO2 = carbon dioxide; NOx = nitrous oxides; SO2 = sulfur dioxide; PMdir = particulates;

Source: IFEU (2008)

5.2.3 CO2 emissions from rail transport In terms of rail emissions, Jade-Weser-Port provides the poorest results in the Dortmund-Munich range in diagram 4.4 compared to other northern deepwater ports. This can be explained by the fact that JWP is not connected to electrified railway over a distance of around 53 kilometres, whereas remaining ports provide better rail connections. However, as explained in the literature review, emissions from electric-hauled rail freight can vary significantly depending on energy mix for electricity generation. After the recent Fukushima nuclear disaster, there has been fundamental change in Copyright © 2014. Diplomica Verlag. All rights reserved.

Germany’s nuclear policy. As a result from public pressure, the German government decided to phase out nuclear power by 2022 (German Federal Environment Agency, 2011). Thus, CO2 emissions from rail transport can change depending on the energy source that will replace nuclear power. According to German Federal Environment Agency (2011) nuclear power plants will be replaced by new gas and coal power

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stations. Thus CO2 emissions of rail transport in Germany might increase significantly over medium term.

CO2 emissions from barge transport Waterway transport from Zeebrugge produces around twice as high emissions compared to that from Rotterdam and Antwerp. This can be explained by the fact that Zeebrugge can only be served by class IV Europeships which are several times smaller compared to Jowi-class vessels operating from Rotterdam and Antwerp as described in the literature review (subsection 2.5.5). However, although a Jowi-class ship can accommodate five times more TEUs than a train, barge emissions are considerably higher per TEU compared to rail (diagram 4.6). Possible reason is that majority of European railway network is electrified, whereas inland ships are powered by marine diesel fuel containing more air pollutants. Nevertheless, one can expect that barge emissions might decrease until 2015, due to IMO’s sulphur reduction regulations in “SOx Emission Control Areas” (SECAs) as described in the literature review. This regulation also applies to European inland waterways. Barge transport plays a minor role in comparison of CO2 emissions since Trieste and Jade-Weser-Port are not connected to inland waterways. However, inland navigation is important for estimation of average hinterland carbon emissions, which are discussed in following subsection.

5.2.4 Average hinterland emissions When looking at the CO2 calculation results, there are two extremes, namely, JadeWeser-Port that showed best results in 12 out 15 inland locations, and Trieste as the exact opposite. This difference can be connected to the particular modal split

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characters from these two ports. For remembrance, the individual modal split from each port has been illustrated in table 4.2. In Wilhelmshaven rail accounts for 50 percent and hence positively influences average hinterland emissions. On the other hand, Trieste is assumed to handle 88 percent via road freight. However, one should bear in mind that modal split data from these two ports are based on assumptions. This means that actual rail proportion on Trieste’s hinterland traffic might be higher whereas Wilhelmshaven’s 50 percent rail share in modal split might become lower

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after JWP started its operations. In this case Wilhelmshaven would probably end up in poorer CO2 emission results. As described in subsection 4.2.4 inland waterway emissions are much higher than rail. Hence, high proportion of barge from Rotterdam and Antwerp negatively influences hinterland emissions from these two ports, compared to high proportion of rail in case of Zeebrugge and Wilhelmshaven. Thus, although Zeebrugge shows two times higher barge emissions, it has hardly impact on the average hinterland CO2 values, since Zeebrugge’s inland waterway transport accounts for merely 1 percent.

5.2.5 Total maritime supply chain emissions Total maritime supply chain emissions are based on previously discussed average hinterland, ocean and port related emissions. In terms of port emissions an average value of 17.5 kg CO2e/TEU has been estimated. This figure is based on the global average from APM Terminals and on emissions from Port of Felixstowe and Port of Rotterdam. However, emissions from Rotterdam’s deepwater terminals Delta and APM have been by around 1 kg CO2e per TEU below the average value of 17.29 (table 2.5). Moreover, APM Terminals (2011) aim to reduce its global average by 15 percent to 14.96 kg by 2012. One can therefore assume that JWP’s average carbon emissions per TEU could be lower than the assumed average value of 17.5. the reason is that a new port is expected to implement energy efficient state of the art terminal equipment and container yard operations. However, the probable difference of let say 2 to 5 kg CO2 per TEU will hardly affects total emissions associated with maritime door-to-door container movement between Far East and Europe . It was found that Trieste performed better in terms of total emissions compared to average hinterland emissions. This is because Trieste provides shorter distance to Copyright © 2014. Diplomica Verlag. All rights reserved.

Shanghai by around 2,000 nautical miles. However, Trieste’s emissions could be even lower if one would take emission data from an average 8,000 TEU vessel instead of a 13,000 TEU ship. The reason is that the difference in sea emissions between Trieste and JWP would be greater by 125 kg CO2e per TEU as explained previously in subsection 4.2.1. If, in addition, the actual share of rail in Trieste’s modal split would become higher, than Jade-Weser-Port would probably lose its environmental predominance in Eastern European region to the Italian port. Furthermore, Trieste 90

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might become more attractive to shipping lines in near future, when the regulation concerning sulphur reduction to 0.1 percent in SECAs will come into effect. This is because carriers could avoid SOx Emission Control Areas by using Adriatic ports.

5.3 Research question 2 This section fill analyse the findings concerning port characteristics and hinterland connections. Thereby results will not be discussed separately for each port as it was the case in previous chapter but rather will be directly compared. As a reminder, the findings have been summarised in tables 4.3 and 4.4. Rotterdam is the largest European port and provides, with 22.55 meters, the greatest draft from all investigated ports. Thus, one can expect that Rotterdam will be able to accommodate Triple-E container ships with 18,000 TEU. However, since there are no reliable published draught data of such a ship, one cannot make a statement concerning the ability of other ports to accommodate Triple-E vessels. Nevertheless, one can assume that Antwerp will not be accessible for container ships with more than 15 meters draft due to the insufficient access channel. After several years of dredging, Antwerp’s approach channel provides a tide-independent draught of only 13.10 meters or maximum 15 meters using tide. However, since Antwerp is an inland port it is located closer to European industrial areas such as the German Ruhr Area. Thus, this port showed best results in terms of road and rail emissions compared to the neighbouring ports of Rotterdam and Zeebrugge. However, there is a trade-of with maritime accessibility because of the long-lasting manoeuvring along Scheldt River with its tight curves. Different from Antwerp, the remaining ports provide good access for ships since its deepwater container terminals extend into the sea avoiding complicated manoeuvring.

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Trieste’s geographical location in the North Adriatic Sea enables to cut the journey from Far East to Europe by 2000 nm and several days, and thus to reduce fuel consumption. However, vessels have to make great deviation from the main shipping route to achieve the port as illustrated in figure 5.1. Furthermore, although Trieste provides the geographical requirements to accommodate an E-class ship, the port is equipped with insufficient gantry cranes with an outreach of maximum 17 container

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rows. Hence, Trieste is not able to serve the whole width of an Emma Maersk or Eclass class ship with 22 container rows (Maersk Maritime Technology, 2011). Figure 5.1 Deviation from main shipping route in order to achieve Port of Trieste

Source: ASX Marine, 2011 As described in the literature review (subsection 2.4.3), supply chain integration is an important port competitive factor. In order to provide value added services, such as warehousing, distribution and container freight station (CFS) operations, ports should be able to accommodate logistics and industry companies. Thereby, Antwerp and Rotterdam provide largest clusters of service providers, industry and trade businesses around the port. Furthermore both ports are investing heavily in their expansion programmes, such as Maasvlakte 2 in Rotterdam and two logistics parks in Antwerp Copyright © 2014. Diplomica Verlag. All rights reserved.

as described in previous chapter. Trieste, on the other hand has no possibility to expand on the land-side, since the port is surrounded by densely built city. Indeed, current development plans are associated with water-side expansion, which is usually more expensive because initially new land must be created on water. Wilhelmshaven, on the other hand, has free area of 400 hectares for further expansion directly behind the port. Furthermore, Jade-Weser-Port will provide a logistics park of 160 hectares within the terminal, so that the port fulfils one certain condition for supply chain 92

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integration. Another prerequisite for successful integration is the connection to advanced hinterland transport networks. Rotterdam, Antwerp and Zeebrugge have the advantage that they are connected to inland waterways. This enables the evasion to additional transport mode in terms of overburdened road and/or rail. However, in contrast to Rotterdam and Antwerp, for Zeebrugge barge transport is less important. It was found that Jade-Weser-Port provides the poorest road and rail connections. Since good quality of hinterland accessibility is a major competitive factor, there is particular need in development of present infrastructure. In fact, the motorway A29 is currently being extended over a distance of more than 2 kilometres as depicted by the red line in figure 5.2. The development of A29 is expected to be completed by the end of 2011 (Jade-Weser-Port, 2011). Thus, at the time when JWP will start its operations the port will be connected directly to a four-lane motorway. Figure 5.2 Extension of motorway A29 up to Jade-Weser-Port

Source: Google Earth, 2011 However, there is still insufficient rail lane connection, particularly because of the two single-track sections of 5 and 7 kilometres between Wilhelmshaven and Oldenburg. Moreover, the railroad track of around 53 kilometres must be electrified, in order to reduce CO2 emissions. As described in the literature review, electrically powered locomotives produce a fraction of emissions from diesel powered trains. However, Copyright © 2014. Diplomica Verlag. All rights reserved.

electricity production is related to particular energy mix, which could change negatively in Germany as a result of the country’s nuclear phase-out by 2022.

5.4 Research question 3 This section will discuss the proposed CO2 reduction measures for ship, port and hinterland emissions.

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5.4.1 Analysis of measures for reduction of ocean emissions Measure: Application of larger container ships The findings showed that larger ships emit less CO2 per TEU. Hence it seems logical that shipping lines should implement vessels with higher capacity. Thus carriers can cut both shipping costs and CO2 emissions per TEU due to exploitation of economies of scale. However, new ultra large container vessels are connected to very high investments. For example, a Triple E-class ship costs around 190 million USD (Maersk Line, 2011). One should also consider that reductions in costs and carbon emissions can only be achieved if the additional ship capacity is used accordingly. Furthermore, vessels of such size are less flexible since they can only call suitable ports and operate on particular routes due to channel restrictions. Measure: Enhancement of ship capacity utilization Since total ship emissions are allocated to the number of carried TEUs, one can expect that the more TEUs are carried the lower is the CO2e value per TEU. Hence, shipping lines should try to enhance the utilization of ship capacity. For example, as illustrated in the literature review, container vessels that operate on the Asia-Europe trade lane provide an average utilization value of 70%. This corresponds to 9,100 TEU in case of a 13,000 TEU ship. An increase by 5% would lead to the use of additional 650 TEUs and accordingly to the allocation of total ship emissions to a larger number of containers. Measure: Travel speed reduction The reduction in speed leads to significant reduction in fuel consumption and the

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associated carbon emissions. However, it also negatively affects travel time and departure frequency so that additional vessels are needed to provide the same service as explained in subsection 5.2.1. Nevertheless, after the recent financial crisis, many shipping lines have reduced the average operating speed from 24 to 19 knots. Some shipping lines, such as CSAV, operate even at so-called “ultra slow steaming” with 16 knots (Brick, 2011).

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Measure: Use of cleaner fuels Ocean going vessels are major contributors to emissions of SOx, NOx and particulate matter. Thereby, approximately 70 percent of ship emissions occur within a distance of 400 km from the coasts (Eyring et al. 2007). Especially for people leaving close to ports there is increased health risk, because of high concentration of noxious gases emitted by combustion of heavy fuel oil (Eyring et al., 2010). The use of cleaner fuels would reduce both air pollutants and health risks including the associated healthcare costs. However, cleaner fuels are usually more expensive. Thus, governments should create incentives in order persuade carriers to reduce speed and to use less polluting fuels, such as has been done by creating SOx Emission Control Areas (SECAs).

5.4.2 Analysis of measures for reduction of port emissions Measure: Provide cold ironing or onshore electricity for ships Ports can actively contribute to CO2 reduction by providing onshore electricity for ships. Especially in terms of Jade-Weser-Port that is still under construction, onshore power supply system might easily be implemented. However, cold ironing should be financially attractive to both container terminals and carriers. This means that landside power must be cheaper than ship’s self-generation of electricity by auxiliary engines. Also for ports it should be worthwhile to implement cold ironing, since in practice the cost factor is still perceived as major decision criterion. For example Swedish government implemented tax cuts for on-shore electricity to make this option more attractive (CILT, 2010). Measure: Use energy efficient terminal equipment

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Energy efficient terminal equipment can help to reduce both fuel costs and carbon emissions. However, new state of the art terminal vehicles and cranes are probably quite expensive, so that ports are expected to use them over a longer period of time. However, newly emerging container terminals, such as Jade-Weser-Port have the possibility to invest in environmentally friendly terminal equipment.

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Measure: Blend diesel with biodiesel There has also been the proposal to blend diesel with biodiesel in order to cut emissions from terminal equipments. This measure appears to be cost-effective and easily to realise. However, the extensive use of biofuels is still a controversial issue in terms of environmental impact, since the cultivation of plants used for biofuel production is often associated with destruction of forests that, on the other hand, are needed to absorb carbon dioxide. Furthermore, extensive use of biofuels can negatively affect food prices because edible plants are burned in engines instead of being used for food manufacturing. Measure: Implement appointment system for vessels and trucks The implementation of an appointment system for ships seems to be an efficient tool to reduce ship emissions close to the port. Since Jade-Weser-Port has a limited quay length of 1725 meters that will be used from both ocean going and feeder vessels, there is an increased risk of port congestion. An appointment system can help to reduce or avoid congestion by informing vessels days in advance about time windows for arriving. Vessel speed at sea can then be adapted in such a way that the vessel arrives at a time of free terminal berth without having to wait close to the port. Such appointment system can also be used for trucks as it has been implemented at Ports of Los Angeles and Long Beach in order to reduce road congestion and the associated truck emissions at terminal gates (Giuliano and O'Brien, 2007).

5.4.3 Analysis of measures for reduction of hinterland emissions Measures: “Widen the motorway A29” and “modernise the railway between

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Wilhelmshaven and Oldenburg” As already mentioned in previous section JWP’s road and rail connection must be improved in order to reduce carbon emissions from hinterland transport. Although the extension of motorway A29 will probably be finished in time, rail connection should be improved urgently since it might be insufficient to handle the half of JWP’s hinterland traffic. Thereby, two single-track sections of total 12 kilometres must be extended

to

a

multi-track

railway.

Furthermore,

53

kilometres

between

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Wilhelmshaven and Oldenburg must be electrified. However, one can expect that rail development to this extent cannot be finished within one year before JWP’s start-up in August 2012. Thus, it is not clear whether the port will be able to handle 50 percent of the total hinterland container traffic by rail. However, initially the port will operate 1,000 meters and from August 2013 the whole quay length of 1725 meters. Thus there is time until 2013 to modernise the rail lane before the port will be able to operate at full capacity. Measure: Implement port centric logistics The implementation of port-centric logistics can also help to reduce hinterland emissions, because it reduces one container movement leg by emptying the containers in ports. The goods are than distributed directly from the ports. This concept has been successfully implemented by major UK retailer Sainsbury’s that operates a distribution centre in the Port of Felixstowe and hence saves 700,000 road miles annually of containerised hinterland transport (Mangan et al., 2008). Also JadeWeser-Port offers good conditions for implementation of port-centric-logistics, since 50 percent of its 160 ha logistics area is planned to be used for wholesalers, warehousing, and contract logistics operations.

5.5 Summary This chapter analysed the results from the three research questions. Thereby findings from fourth chapter were discussed under consideration of theoretical findings from literature review. Major findings from each research question are summarized in next

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chapter.

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6. CHAPTER – CONCLUSION Container shipping is the backbone of global trade. In order to accommodate increasing trade volumes with simultaneous pressure to reduce unit costs, shipping lines invest in even larger container ships. Thereby, largest vessels such as EmmaMaersk operate on major Asia-Europe trade lane. Such container ships represent challenges but also open up new possibilities for deepwater ports. Thereby the emerging Jade-Weser-Port in Wilhelmshaven might become an alternative port for carriers operating largest container vessels with a draft of more than 15.5 meters. However, also environmental issues play an increasing role in maritime business.

6.1 Summary of important research findings The overall objective of this study has been to examine CO2 emissions from container transport from Far East into the European hinterland through the deepwater ports of Rotterdam, Antwerp, Zeebrugge, Trieste and Wilhelmshaven. Thereby, a set of three complementary research questions have been used to close identified research gaps. First research question served to estimate CO2 emissions from maritime door-to-door container transport and to identify regions that can be reached more environmentally friendly through Jade-Weser-Port. Main findings have been that a 13,000 TEU vessel emits by 51 percent less CO2 emissions per TEU compared to an average 8,000 TEU ship, and that a speed reduction from 24 to 19 knots reduces CO2 emissions by around 53 percent. I was found that north-eastern part of Germany and northern region of Eastern Europe can be reached under minimum CO2 emissions via Jade-Weser-Port. Second research question should help to compare deepwater ports on the basis of particular port characteristics and hinterland connections. It was found that Antwerp

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and Trieste are less feasible to serve E-class container ships and that Jade-Weser-Port provides the worst quality of hinterland connection compared to other ports. Third research question illustrated various measures for decarbonisation of maritime door-to-door container transport chain. Thereby, emissions from ocean transport can be cut by reducing sea speed, operating larger container vessels, using cleaner fuels and increasing vessel capacity utilization. Ports can contribute to CO2 reduction by

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providing cold ironing, applying an appointment system for ships and trucks, using energy efficient terminal equipment and blending diesel with biodiesel. In order to reduce hinterland emissions from Jade-Weser-Port it was suggested to develop the port’s road and rail connection, and to implement port centric logistics. To conclude one can state that environmental issues become increasingly important. Thereby estimation of carbon emissions represents a vital instrument in order to identify CO2 reduction opportunities. Thus, Jade-Weser-Port should implement carbon auditing right from the start of its operations.

6.2 Limitations of the research and further research possibilities This book excluded CO2 emissions from pre-carriage in Far East and empty container movements. Thus, one could examine carbon footprint of a container moving between particular shipper and consignee including the replacement of empty container at export and import side. CO2 emissions have been calculated on the basis of an average payload of 10.5 tonnes per TEU. Since cargo weight can vary depending on the nature of goods, there is the opportunity to estimate emissions for light and heavy cargo or container. Since no emissions data from investigated ports could be found an average value of 17.5 kg CO2 per TEU has been used for each port. However, this figure can vary from port to port. This opens up the possibility to examine CO2 emissions from each of the investigated ports. Since Jade-Weser-Port did not start its operations yet, it was necessary to work with assumption. For example, Bremerhaven has been used as reference port for estimation

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of average port calls between Shanghai and Wilhelmshaven. Furthermore, only the direct distance between two ports has been considered. Thus, it can be suggested to estimate CO2 emissions from particular Asia-Europe sea services including changes in speed near coasts and sea channels, and the additional distances associated with deviation from the main sea route in order to call different container ports.

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This study neglected carbon auditing of refrigerated containers. Thus, one could estimate the carbon footprint of reefer containers, especially because they produce

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CO2 by their own. This might be of particular interest for the food industry.

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Policy and Management, 37(3), pp.179-194.

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

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APPENDICES APPENDIX 1 – Calculation of ocean transport emissions Average number of port calls between Shanghai and investigated ports

Assumptions for calculation of ocean emissions Criterion Maximum continuous rating (MCR) (kW) Maximum continuous rating (MCR) (kW) Engine load factor (LF) at sea

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Engine load factor (LF) in port Fuel consumption factor ( g/kWh) Fuel emission factor (EF) (kg CO2e/ton) Power emission factor (EF) (kg CO2e/kWh) Maximum speed (knots) of 13,000 TEU ships Maximum speed (knots) of 8,000 TEU ships Average speed at sea (knots) Average time (AT) in port (hours) of 13,000 TEU ships Average time (AT) in port (hours) of 8,000 TEU ships Capacity in TEU of 13,000 TEU ships Capacity in TEU of 8,000 TEU ships Capacity utilisation

Propulsion engine

Auxiliary engine

72.027 14.000 67.824 12.200 based on av. 0,13 speed at sea 0 0,17 175 190 33.974 33.974 0,55223 0,60221 24,7 25,2 19 / 24 / 16 30 24 13000 8000 70%

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

Calculation of CO2 emissions from Ocean going vessels (speed: 19, 24, 16 knots)

+62.5% capacity

+7.5% CO2e

+110 hours

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-25.5% CO2e

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

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APPENDIX 2 – Calculation of road transport emissions Distances between ports and selected hinterland locations

Hannover Berlin Cassel (Kassel) Erfurt Leipzig Dortmund Cologne (Köln) Frankfurt a.M. Mannheim Stuttgart Nuremberg (Nürnberg) Munich (München) Prague (CZ) Poznan (PL) Warsaw (PL)

Road distances (in km) Zeebrugge Rotterdam Antwerp Wilhelmshaven Trieste 543 453 455 233 1135 821 730 733 492 1086 514 459 427 384 979 677 641 589 436 899 767 712 679 470 935 339 292 252 279 1109 308 297 221 361 1080 494 490 407 486 896 524 512 436 564 862 656 644 568 688 735 711 707 623 638 673 879 875 791 851 502 996 959 908 725 804 1068 978 981 739 1333 1379 1289 1291 1050 1157

CO2 emissions from Ocean going vessels TEU weight (t)

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10,5

Emission factor (kg CO2e/tkm)

0,08778

Road CO2 emissions (in kg CO2e/TEU) Zeebrugge Rotterdam Antwerp Wilhelmshaven Trieste Hannover 500 418 419 215 1046 Berlin 757 673 676 453 1001 Cassel (Kassel) 474 423 394 354 902 Erfurt 624 591 543 402 829 Leipzig 707 656 626 433 862 Dortmund 312 269 232 257 1022 Cologne (Köln) 284 274 204 333 995 Frankfurt a.M. 455 452 375 448 826 Mannheim 483 472 402 520 794 Stuttgart 605 594 524 634 677 Nuremberg (Nürnberg) 655 652 574 588 620 Munich (München) 810 806 729 784 463 Prague (CZ) 918 884 837 668 741 Poznan (PL) 984 901 904 681 1229 Warsaw (PL) 1271 1188 1190 968 1066

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

MIN 215 453 354 402 433 232 204 375 402 524 574 463 668 681 968

MAX 1046 1001 902 829 862 1022 995 826 794 677 655 810 918 1229 1271

APPENDIX 3 – CO2 emissions from rail transport CO2 emissions from rail transport based on Ecotransit online carbon auditing tool

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Rail CO2 emissions (in kg CO2e/TEU) Zeebrugge Rotterdam Antwerp Wilhelmshaven Trieste Hannover 120 92 100 55 230 Berlin 180 150 160 120 220 Cassel (Kassel) 120 100 100 89 200 Erfurt 150 140 140 120 210 Leipzig 170 160 150 110 210 Dortmund 73 55 56 79 240 Cologne (Köln) 57 49 45 100 230 Frankfurt a.M. 98 90 86 130 190 Mannheim 110 110 100 150 170 Stuttgart 120 130 130 170 150 Nuremberg (Nürnberg) 150 140 140 160 140 Munich (München) 170 180 180 190 98 Prague (CZ) 250 220 240 190 130 Poznan (PL) 280 240 260 210 280 Warsaw (PL) 410 380 390 350 300

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

MIN 55 120 89 120 110 55 45 86 100 120 140 98 130 210 300

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MAX 230 220 200 210 210 240 230 190 170 170 160 190 250 280 410

APPENDIX 4 – CO2 emissions from barge transport CO2 emissions from barge transport based on Ecotransit online carbon auditing tool

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Inland waterway CO2 emissions (in kg CO2e/TEU) Zeebrugge Rotterdam Antwerp Dortmund 300 180 220 Cologne (Köln) 320 130 150 Frankfurt a.M. 480 220 250 Mannheim 500 230 260 Stuttgart 620 310 330 Nuremberg (Nürnberg) 760 390 410

MIN MAX 180 300 130 320 220 480 230 500 310 620 390 760

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

APPENDIX 5 – Calculation of average hinterland emissions

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Average hinterland emissions based on modal split from each port

Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

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APPENDIX 6 – Calculation of total maritime supply chain emissions Ocean transport and assumed port emissions CO2 emissions (kg CO2e/TEU) Zeebrugge Rotterdam Antwerp Wilhelmshaven Ocean transport: 19kn 13,000 TEU ship Port emissions

1245 17,5

1247 17,5

1248 17,5

Trieste

1268 17,5

1027 17,5

Total maritime supply chain emissions as sum of ocean, port and average hinterland emissions (appendix 5)

Total average CO2 emissions (in kg CO2e/TEU)

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Hannover Berlin Cassel (Kassel) Erfurt Leipzig Dortmund Cologne (Köln) Frankfurt a.M. Mannheim Stuttgart Nuremberg (Nürnberg) Munich (München) Prague (CZ) Poznan (PL) Warsaw (PL)

Zeebrugge Rotterdam Antwerp Wilhelmshaven Trieste 1609 1629 1636 1421 1993 1786 1852 1863 1572 1952 1566 1507 1491 1507 1863 1695 1781 1747 1547 1799 1752 1839 1819 1557 1828 1479 1481 1476 1454 1973 1456 1466 1435 1502 1948 1575 1600 1569 1575 1794 1596 1617 1589 1621 1764 1673 1714 1683 1688 1659 1717 1774 1740 1660 1608 1814 1968 1911 1773 1464 1910 2040 2012 1715 1713 1962 2058 2072 1731 2160 2185 2320 2334 1945 2019

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2

MIN 1421 1572 1491 1547 1557 1454 1435 1569 1589 1659 1608 1464 1713 1731 1945

MAX 1993 1952 1863 1799 1839 1973 1948 1794 1764 1714 1774 1968 2040 2160 2334

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APPENDIX 7 – Semi-structured questionnaire

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Veidenheimer, Konstantin. Carbon Dioxide Emission in Maritime Container Transport and comparison of European deepwater ports: CO2 Calculation Approach, Analysis and CO2