DecouplingtheEnvironmentalImpacts ofTransportfromEconomicGrowth Economicgrowthrequiresanefficienttransportsystem,andtransportactivity continuestocauselargeadverseimpactsontheenvironment,humanhealthand theeconomy.Butisanegativeimpactoftransportontheenvironmentanecessary consequenceofeconomicgrowth?Thisvolumeoffersacomprehensivediscussion ofrecentresearchonthelinksbetweentransportdemandandeconomicgrowth.It providesanin-depthdiscussionofenvironmentalandeconomiceffectsofapackage ofinstrumentsfordecouplingenvironmentallyimpactsoftransportfromeconomic growth–andhowtoovercomeobstaclestotheirimplementation.
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ISBN92-64-02712-2 972006121P
DecouplingtheEnvironmentalImpactsofTransportfromEconomicGrowth
Thisbookillustratesthatdecouplingtheenvironmentalimpactsoftransportfrom economicgrowthisachievable,throughtheefficientuseofcharges,fees,taxes andothereconomicinstruments.Theseeconomicapproachescancomplement regulatorymeasurestoencourageashifttowardsmoreenvironmentally-friendly modesoftransport,suchasfromroadtocertainformsofrailtransport.Other factorswhichcouldhelptodecoupletransportimpactsfromeconomicgrowth areimprovementsinfreighttransportlogistics,anddematerialisation.Allofthese approachesshouldbeappliedwithparticularattentiontothecircumstancesand characteristicsofindividualcountries;someinstrumentsthatfitwellinonecountry mightnotbewelladaptedtoothers.
Decoupling theEnvironmental Impactsof Transportfrom EconomicGrowth
OUPL HDEC ROWT G ENVIR IC H T ROW ONOM MIC G ENTEC CONO TE E M N N G E O IN M IR COUPL IRON GENV NT DE GENV ENVI IN UPLIN ONME L G O IR P IN V C L U N P E OU H E HD ECO H DEC GROWT ROWT WTHD OUP GROWT NOMIC MICG ICGRO HDEC NOMIC G ECO M T O IN O C L W E P N ECONO O T U O R C EN CO E M G NVI E D N T IC O T H N N WT E NVIR ONME ONOM ONME IC GRO LING E ENVIR NTEC ONOM E E ENVIR ECOUP C T D G M E N N H G IN E T L O P ROW OUPLIN NVIR IRONM MIC G DECOU T DEC LINGE GENV P NVI ECONO NMEN E IN U T O L G O N IR P E IN C V L ONM H EN COU OUP HDE ENVIR H DEC THDE GROWT ROWT OUP GROWT NOMIC MICG GROW IC HDEC NOMIC G ECO M T O IN O C L W E P N ECONO O O OU NT R I C E C E M G E D N T H ENV NT VIRO NOMIC NMEN ONME GROWT ING EN ENVIR TECO NVIRO NOMIC N COUPL O E E E E C T G D M E N N H IN G E PL IRO ROWT ONM OUPLIN MIC G GENV DECOU T DEC ENVIR ECONO NMEN OUPLIN PLING C U MENT NVIRO E N E O O D H C IR T H E ENV THD GROW ROWT NOMIC MICG GROW G ECO NOMIC ECONO UPLIN O O C C E E D NT ENT ONME ING IRONM ENVIR COUPL GENV IN TH DE L W P O U R G IC M DECO O N T ECO NMEN O
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Decoupling the Environmental Impacts of Transport from Economic Growth
ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT
ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT The OECD is a unique forum where the governments of 30 democracies work together to address the economic, social and environmental challenges of globalisation. The OECD is also at the forefront of efforts to understand and to help governments respond to new developments and concerns, such as corporate governance, the information economy and the challenges of an ageing population. The Organisation provides a setting where governments can compare policy experiences, seek answers to common problems, identify good practice and work to co-ordinate domestic and international policies. The OECD member countries are: Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, Mexico, the Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. The Commission of the European Communities takes part in the work of the OECD. OECD Publishing disseminates widely the results of the Organisation’s statistics gathering and research on economic, social and environmental issues, as well as the conventions, guidelines and standards agreed by its members.
This work is published on the responsibility of the Secretary-General of the OECD. The opinions expressed and arguments employed herein do not necessarily reflect the official views of the Organisation or of the governments of its member countries.
Also available in French under the title: L’impact environnemental des transports COMMENT LE DÉCOUPLER DE LA CROISSANCE ÉCONOMIQUE
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FOREWORD AND ACKNOWLEDGEMENTS
Foreword and Acknowledgements
T
his report presents the results of a project begun in 2002 by the OECD Working Group on Transport. The project aims to help OECD member countries develop efficient and effective policies for decoupling the environmental impacts of transport from economic growth. Where it can be achieved, efficient decoupling will contribute to more sustainable transport patterns. The project was also designed to contribute to the implementation of the transport chapter of the OECD Environmental Strategy for the First Decade of the 21st Century, in particular Objective 2 (decoupling environmental pressures from economic growth). The project has involved three key stages: i) a review of the main factors responsible for transport activity (e.g. economic growth, changes of mobility patterns, modal share) and other factors affecting transport demand (e.g. speed, and information/communication technologies (ICT); ii) an analysis of selected decoupling measures and instruments already in use, based on country case studies; and iii) an overview of available policy options for achieving additional decoupling in the future. This report has been written by Nadia Caïd of the OECD Environment Directorate. Comments provided both by the delegates of the OECD Working Group on Transport and OECD Secretariat colleagues are also gratefully acknowledged. The contributions by Austria, Germany, Italy, Japan, Norway, Spain, Sweden, Switzerland and the United States were instrumental in completing the work. Particular thanks are also due to the following: Robert Thaler, Eva Gleissemberger, Andreas Niederl, Karl Steininger, Max Herry and Norbert Sedlacek, Veronika Gaube and Heinz Schandl (Austria); Philip Kurys (Canada); Elisabeth Langella and Christiane Aveline (France); Axel Friedrich, Hedwig Verron and Jacques Leonardi (Germany); Aldo Ravazzi, Gloria Visconti and Alberto Frondaroli (Italy); Yasuto Kawarabayashi, Katsuhiro Yamaguchi and Yoji Kawakami (Japan); Martin Kroon (The Netherlands); Ole Hagen (Norway); Angel Aparicio and Alfredo Sanchez Vicente (Spain); Sven Huhammar (Sweden); Harald Jenk, Matthias Rinderknecht and Markus Maibach (Switzerland); Brigid DeCoursey and Robert Larson (United States).
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Table of Contents Executive Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9
Chapter 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
13
1. Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Decoupling: the concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Some caveats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
14 15 17
Chapter 2. Transport and the Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21
1. 2. 3. 4. 5. 6. 7. 8.
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . General links between transport and economic activity . . . . . . . . . Factors influencing transport demand . . . . . . . . . . . . . . . . . . . . . . . . Passenger transport. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Freight transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elasticities. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Transport infrastructure and economic growth . . . . . . . . . . . . . . . . Elasticity of growth to transport infrastructure investments . . . . .
22 22 24 28 30 32 37 39
Chapter 3. Transport and the Environment. . . . . . . . . . . . . . . . . . . . . . . . . .
43
1. 2. 3. 4. 5. 6.
Transport externalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Overview of transport externalities in Europe . . . . . . . . . . . . . . . . . Energy consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CO2 emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CO emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Trends across selected air pollutants . . . . . . . . . . . . . . . . . . . . . . . . .
44 50 52 52 55 56
Chapter 4. Decoupling Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
59
1. Economic indicators of transport versus GDP . . . . . . . . . . . . . . . . . . 2. Environmental impacts of transport versus GDP. . . . . . . . . . . . . . . .
60 62
Chapter 5. Policy Instruments for Decoupling . . . . . . . . . . . . . . . . . . . . . . .
65
1. 2. 3. 4. 5. 6.
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . General approaches for decoupling . . . . . . . . . . . . . . . . . . . . . . . . . . Economic instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Regulatory instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Investment instruments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Institutional arrangements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
66 66 70 76 81 83
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7. Educational instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8. Overview of “soft” measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9. Synergies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
84 85 85
Chapter 6. National Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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1. 2. 3. 4. 5. 6. 7. 8. 9.
Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Austria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Italy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Heavy goods vehicle fee – Switzerland. . . . . . . . . . . . . . . . . . . . . . . . Congestion charging – London . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
88 88 89 90 91 91 92 92 94
Chapter 7. Conclusion: Towards a Decoupling Strategy . . . . . . . . . . . . . . .
97
1. Overview of available instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 2. Conclusions and recommendations for policy action . . . . . . . . . . . 101 Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 List of boxes 5.1. Transport fuel taxation – Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 5.2. Overview of existing congestion pricing policies . . . . . . . . . . . . . . . . 77 7.1. Decoupling in Eastern Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 List of tables 2.1. Transport ranking of top five freight sectors by value per tonne and tonne-miles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. External trade by mode of transport in the EU25, 2004 . . . . . . . . . . . 2.3. Trips by purpose in Great Britain, Germany and the USA . . . . . . . . . 2.4. Estimated long-term transport elasticities . . . . . . . . . . . . . . . . . . . . . 2.5. Overall results: various elasticities . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6. Vehicle travel elasticities with respect to user costs . . . . . . . . . . . . . 2.7. Output elasticities derived from aggregated production functions . 2.8. Output elasticities derived from aggregate production functions . . 3.1. Total external costs of road transport in 2000 by cost category and transport mode (EU17) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Range of reported external costs in cost-of-driving studies in the US . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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3.3. CO2 emissions from the transport sector, million tonnes CO2 (excluding international bunkers) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Growth rate of GDP, passenger and freight transport in the US, 1970 to 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Growth rate of GDP, passenger and freight transport in the EU, 1970-2003. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1. Road pricing categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2. Benefits of road-pricing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3. Selected road pricing schemes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4. Summary of results from Dutch CO2 benchmarking study . . . . . . . . 5.5. Impact of telecommuting on mass transit congestion in Tokyo, 2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6. Main results of studies on the impact of “soft” measures on transport demand. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1. Instruments for decoupling: overview . . . . . . . . . . . . . . . . . . . . . . . . .
53 60 60 75 75 79 80 83 86 99
List of figures 2.1. 2.2. 2.3. 2.4. 2.5. 2.6. 2.7. 2.8. 2.9. 2.10. 3.1. 3.2. 3.3. 3.4. 3.5.
Major sectoral contributions to US GDP, 2003 . . . . . . . . . . . . . . . . . . . Modal share of types of goods transported in the EU15, 2003. . . . . . Growth in world trade, GDP and transport, 1980-2000 . . . . . . . . . . . . Motorisation level and wealth in selected OECD countries, 1970-2000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Modal split of passenger transport in the EU, the USA and Japan, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Passenger transport trends by modes in the US, EU and Japan, 1970-2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Trends of road freight intensity and GDP per capita in the OECD area, 1970-2000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Modal split of freight transport in the EU, the USA and Japan, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Freight transport trends by modes in the US, the EU15 and Japan, 1970-2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Links between transport infrastructure investment and economic growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . US greenhouse gas emissions by economic sector, 2003 . . . . . . . . . . Energy consumption of transport and all sectors in the US, Japan and Europe, 1970-2002. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CO2 emissions by source in Austria . . . . . . . . . . . . . . . . . . . . . . . . . . . CO2 emissions by sectors in the US, Japan and the EU, 1970-2002. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CO2 emissions by modes of transport in the EU15, 1970-2005 . . . . .
23 24 25 28 29 30 31 31 33 38 47 53 54 55 56
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3.6. CO emissions of the transport sector, road transport and all sectors in the US and the EU, 1970-2002 . . . . . . . . . . . . . . . . . 3.7. Trends in CO2, CO, NOx and VOC emissions from road transport and rail transport in the US, 1970-2002. . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Comparison of trends of total transport, GDP growth, road freight transport and air passenger transport in the US and the EU, 1970-2003, 1970 = 100 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Trends in CO2, CO, NOx and VOC emissions from road transport and GDP growth in the US, 1970 to 2002, 1970 = 100. . . . . . . . . . . . . . 4.3. Comparison of trends of CO2, CO, NOx and VOC emissions rom road transport and GDP growth in the EU, 1970 to 2002, 1970 = 100 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1. Strategies for decoupling freight transport from economic growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2. Revenues from environmentally related taxes in % of GDP . . . . . . . 5.3. Revenues from environmentally related taxes in % of total tax revenue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4. Environmentally related taxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5. Tax rates on petrol and diesel in OECD member countries . . . . . . . . 5.6. Potential emissions reduction through pricing . . . . . . . . . . . . . . . . . .
8
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63 67 71 71 72 73 76
DECOUPLING THE ENVIRONMENTAL IMPACTS OF TRANSPORT FROM ECONOMIC GROWTH – ISBN 92-64-02712-2 – © OECD 2006
ISBN 92-64-02712-2 Decoupling the Environmental Impacts of Transport from Economic Growth © OECD 2006
Executive Summary
T
his report presents the results of a project that was begun by the OECD Working Group on Transport in 2002. The overall objective of the project is to help OECD member countries develop efficient and effective policies for decoupling the environmental impacts of transport from economic growth. Where it can be achieved, efficient decoupling will contribute to more sustainable transport patterns.
Links between transport and the economy In 2003, transportation-related goods and services contributed $1 156 billion, or about 11%, to US GDP. Transportation continued to rank fourth (after housing, health care, and food) in terms of total demand for US goods and services. The modal split has changed considerably in recent years in the three regions analysed. Road transport has increased, while rail and inland waterways have declined. This has been mainly caused by the changing structure of industry and type of goods produced in the various sectors has changed. Mass commodities, more suitable for rail and inland waterway transport, have broadly become less important to the economy. In the last few decades, growth in income, improvements in technology and infrastructure, and increasing time being available for leisure trips, have allowed people to travel more often and further. Increasing levels of disposable income have a strong effect on traffic growth, because car ownership will increase up to a relatively high level before saturation effects are observed. However, the amount of traffic is also influenced by prices, speed and quality of transport, and also by personal preferences and priorities. A comparison between the US, the EU and Japan, reveals broad similarities in terms of size, modal shares and overall trends of passenger transport. Modal split is dominated by passenger cars in the US (87%), the EU (76%) and Japan (63%), while the other modes have minor shares of less than 10%, except for aviation in the US (10%) and railways in Japan (20%) of total passenger-km. The modal split for freight transport is relatively similar in the EU and Japan, with a high share going to two major modes – short-sea shipping: 41% in Japan and 39% in the EU15; and road freight: 44% in the EU and 55% in Japan. The US
9
EXECUTIVE SUMMARY
has a more balanced modal share, with rail taking the highest share (39%), followed by road (31%) and pipelines, inland navigation and short-sea shipping (7-8%). Price sensitivity tends to increase if alternative routes, modes and destinations are of good quality and affordable. For example, highway tolls tend to be more price-sensitive if there is a parallel free roadway. Also, driving is less pricesensitive in the automobile-dependent areas where transport alternatives are very difficult to use. Numerous studies suggest that fuel price changes have a significant negative effect on car fuel demand, since a 10% increase in fuel price results in a 7% reduction in car fuel demand. Another significant result is the sensitivity of car fuel demand, car travel demand, and car stocks to changes in income. An increase of 10% in income will lead respectively to a 12% increase in both car fuel demand and travel demand, and to a 10% increase in car ownership. It may take many years for the full effect of a price change to take place. Studies estimate that short-term elasticities (two-years) are typically one-third of long-term elasticities (15 years or more). Others concluded that about 30% of the response to a price change takes place within 1 year, and that virtually all takes place within less than 13 years. In the early stages of development of a country, transportation infrastructure is an important contributor to economic growth. Transport investments stimulate growth from the demand side, and also contribute to the economic transformation of regions and urban areas affected, on the supply side. In the case of well-developed economies, transportation infrastructure investments can lead to negative results for economic growth. For example, transport investments in one region could lead to competitiveness problems in another.
Transport and the environment In OECD countries, road transport is responsible for most of the transport sector’s impact on human health and the environment. It accounts for over 80% of all transport-related energy consumption, for most of the accidents and the majority of air pollutant emissions, noise and habitat degradation. Maritime transport, although generally associated with lower environmental impacts, raises concerns regarding oil pollution from major accidents. More recently, there has been a growing concern over global environmental impacts from air traffic, which has been increasing particularly rapidly for tourism. Air transport currently represents about 11% of transport-related energy consumption. The estimation of total external costs (excluding congestion costs) amounted to 650 billion euros for 2000, or about 7.3% of the total GDP in EU17. Climate change was the most important cost category, with 30% of total costs. Air
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EXECUTIVE SUMMARY
pollution and accident costs amounted to 27% and 24% respectively. Noise and life-cycle processes each accounted for 7% of the total costs. The most important contributing mode is clearly road transport, generating 83% of the total cost. Two-thirds of the costs are caused by passenger transport and onethird by freight transport. Transport-related energy consumption in the US increased from 516 million tonnes in 1971 to 745 million tonnes in 2002 (growth of 44%), at the same time that total energy consumption in all sectors was increasing by 47%. Growth in transport-related energy consumption was much stronger in the EU, where the increase was 133% between 1970 and 2002. Growth in the energy consumption of all sectors was relatively weaker, increasing by only 121% over this period. In 1970 in the US, CO2 emissions from the transport sector represented 24% of the total, while in 2002 it increased to 31%. Between 1970 and 2002, CO2 emissions from the transport sector increased by 69%: from 1 037 MT to 1 761 MT. In the EU, this share was 12% of the total in 1970; by 2002, it had increased to 26%. Between 1970 and 2002, CO 2 emissions from the transport sector increased sharply by 126%, from 370 MT to 837 MT. In Japan in 1970, the share was 13%; in 2002, it reached 20%. Between 1970 and 2002, CO2 emissions from the transport sector increased by 163%, from 96 MT to 253 MT. In 2002, the level of CO2 emissions of the road transport was 4 349% higher than for rail transport.
Decoupling trends Since 1980, the US experienced a relative decoupling of both passenger and freight transport versus GDP. The EU also experienced a very weak decoupling of freight transport versus GDP, while passenger transport growth went very much along with GDP growth. When the focus is placed on air passenger and road freight, the results are different. Growth in these two modes has been much more rapid than that of GDP. Between 1970 and 2003, air passenger increased by 328%, while GDP was increasing by only 178%. Between 1970 and 2003, the increase in air passenger transport was some 1260% in the EU. Growth in road transport was less sharp, but still high (increasing by 223%). In the two regions analysed here, therefore neither a relative nor an absolute decoupling of certain modes of transport has occurred. If only road transport is considered, there has been an overall (relative and/ absolute) decoupling of road transport-related emissions of CO2, CO, NOx and VOC. During the past three decades, CO2 emissions grew by 95% in the US and 156% in Europe, whereas GDP grew by almost 169% and 187% respectively. However, these overall figures disguise some important differences. In the US, most of the decoupling took place in the early 1980s, and has fluctuated since then. In Europe, the relative decoupling has been very “weak” throughout this period.
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Main recommendations There is not a predetermined policy path for achieving decoupling. Approaches that suit one country will therefore not necessarily be appropriate for another country. Measures involving low investment costs and short implementation periods (e.g. improving rail service quality or the overall accessibility of rail and public transport) should be promoted in the early stages of any decoupling strategy. These measures will quickly reduce environmental pressure without involving excessive economic cost. The existing limited level of public acceptance of pricing measures for road transport could also be improved by offering better alternatives in other modes. Road passenger and road freight are the overwhelmingly dominant modes, and their environmental impacts and related externalities are the highest. In designing policies to decouple these impacts, there is a need to focus on the high growth modes where the impacts from activity growth outpace the level of improvement made per unit of transportation service. Road pricing measures should also be an important (and early) element of the decoupling strategy. The more intensively road transport pricing measures are implemented, the better the incentives for the rail and public transport options will be. For achieving public support for road pricing policies, it may also be appropriate to recycle some of the revenues raised back to affected parts of the economy or to promote new investments in more environmentally sustainable transport modes (e.g. public transport). Problem awareness is another essential part of gaining public acceptance of measures that lead to increases in road transport costs. It is necessary to raise public awareness not only with respect to transport-related environmental and health impacts, but also in terms of the advantages created for local products and urban living. Infrastructure investment policies have the lowest priority from a decoupling perspective. Only at the stage where pricing measures in the road sector reach a relatively high level are new rail and public transport infrastructure investments likely to be appropriate. Implementation of all of the above-mentioned measures is most dependent on decisions made at the national level. However, improvements in rail freight transport are only likely to be possible in the context of international co-operation, especially in Europe. This is likely the case, for example, for both combined transport infrastructure and the harmonisation of rail regulations.
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ISBN 92-64-02712-2 Decoupling the Environmental Impacts of Transport from Economic Growth © OECD 2006
Chapter 1
Introduction
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INTRODUCTION
1. Background Decoupling environmental pressures from economic growth is one of the main objectives of the OECD Environmental Strategy for the First Decade of the 21st Century, adopted by OECD Environment Ministers in 2001. It was also an explicit objective of OECD work on sustainable development, in that the OECD Ministerial meeting of 2001 called on the OECD to … “develop [ ] agreed indicators that measure progress across all three dimensions of sustainable development, including decoupling of economic growth from environmental degradation with a view to incorporating these into OECD’s economic, social and environmental peer review processes, and filling gaps in the statistical and scientific data…”. This report presents the results of a project that was begun by the OECD Working Group on Transport in 2002, in response to the above mandates. The overall objective of the paper is to help OECD member countries develop efficient and effective policies for decoupling the environmental impacts of transport from economic growth. Where it can be achieved, efficient decoupling will contribute to more sustainable transport patterns. This task is addressed by clarifying the concept of decoupling; by illustrating recent decoupling trends and their environmental effects; and by discussing experiences with particular policy approaches whose implementation could lead to further decoupling. The report addresses the decoupling problem largely through the lens of non-technological options, instruments and policies, including their direct and indirect effects on demand for passenger and freight transport. The project has involved three broad phases. Phase 1 involved a review of economic factors that drive transport demand, including relative prices and an examination of the correlation between transport demand and economic activity (OECD, 2004). The key drivers for transport growth (primarily road transport) have also been analysed, focussing on factors which stimulate growth of those particular modes of transport that, in turn, contribute the most to growth in emissions into the environment. A key question concerns the direction of any causality that may have been observed. Phase I therefore examines available evidence concerning this causality, especially in the area of new transport infrastructure investments.
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Available regional statistics (e.g. Europe, Japan and the US) provide only a crude outline of historic developments in transport demand, and more localised perspectives are therefore necessary. These localised perspectives can be obtained from more targeted research at both macro and micro levels, as well as from comparative studies across countries. Phase 2 therefore involved a series of thematic case studies in individual countries, with the objective being to develop insights about decoupling processes at a more local level. Phase 3 placed the accent on potential policy options for enhancing the level (and shape) of future decoupling activities in the transport sector. This part of the work looked at the desired objectives (e.g. particular modal splits; more demand-side management, etc.). For each objective, the most promising instruments that seemed to be available were then reviewed, and a package of possible approaches was developed. Transition issues (phasing) and political economy (acceptability) dimensions were also discussed. This report is divided into seven main parts. This chapter introduces the topic and some of the underlying concepts. Chapter 2 focuses on the key interrelations between economic growth and transport development and the main factors driving transport demand. Chapter 3 analyses the externalities associated with transport activity, including the major environmental impacts. Chapter 4 gives an overview of some decoupling indicators. Chapter 5 reviews some policy instruments for decoupling. Chapter 6 presents the main results from decoupling country case studies and Chapter 7 presents conclusions aimed at developing a strategic approach to decoupling.
2. Decoupling: the concept* Broadly, the term “decoupling” refers to breaking the link between “environmental bads” and “economic goods” (OECD, 2002). In particular, it compares pressures on the environment to changes in economically-relevant variables to which the environmental pressures are causally linked. For example, at the national level, the growth rate of emissions of sulphur dioxide may be compared with the growth rate of GDP; at a sectoral level, the growth rate of emissions of carbon dioxide from energy use may be compared to the growth rate of total primary energy supply. The notion of decoupling is therefore fundamentally linked to the Pressure-State-Response (PSR) scheme used by the OECD (OECD, 1994). The PSR model implies that economic pressures generate changes in the state of the environment, which in turn may lead to environmental policy responses, when undesirable trends in that state are observed. Decoupling indicators also describe
* Most of the material used in this section is derived from an earlier OECD report on the topic of decoupling (see OECD, 2002).
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changes in environmental pressures over time, and compare them to changes in economic “driving forces” over the same period of time. Decoupling indicators may also serve as one element of policy discussions aimed at changing the shape and the rate of future changes in these variables. From an environmental perspective, it is the change in total environmental pressure that is of most concern. If an economic variable displays positive growth, absolute decoupling (sometimes referred to as “strong” decoupling) is said to occur when the growth rate of the environmentally relevant variable is zero or negative – i.e. total pressure on the environment is either stable or falling. Relative decoupling (sometimes referred to as “weak” decoupling), on the other hand, occurs when the growth rate of the environmentally relevant variable is positive, but is less than the growth rate of the underlying economic variable. Causality is another relevant issue. The notion that the rate of change of environmental variables are either “coupled”, “weakly decoupled”, or “absolutely decoupled” to economic variables, assumes a priori that these variables are causally linked. This link may even be assumed to be one-to-one, such that a given percentage increase in one variable will lead to the same percentage increase in the other (elasticity of one). If such is the case, the success of a policy could be measured in terms of the extent to which growth in the environmental variable is reduced, in percentage terms, below that of the economic variable (the reduction of elasticity below one). The problem with this approach however, is that not all variables are causally linked. Further, even if variables are causally linked, the response of one variable to the other may not be equivalent in percentage terms (elasticity could be lower or greater than one) even in the absence of the policy intervention, depending on the nature of the causality relationship more specifically: ●
It is possible for variables to be correlated, but not be causally linked. In this case, the variables may appear to be “coupled”, when in fact they are not. The correlation (or lack thereof) of two variables is not proof of causality.
●
Similarly, it is possible for a causality relationship to exist between two variables (they are “coupled”), even when elasticity is less than one.
Strong decoupling is rather rare in practice, although OECD countries have recently seen absolute declines in the emissions of some local air pollutants, ozone-depleting CFCs and lead emissions – all at the same time as economic growth was continuing. Weak decoupling is somewhat more common in some areas – for example, in the water and energy consumption fields.
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3. Some caveats How much decoupling is enough? In considering this question, it is noted that the decoupling concept has no automatic link to the environment’s capacity to sustain, absorb, or resist pressures of various kinds (deposition, discharges, harvests). In effect, the simple fact that decoupling of a transport-related variable is being observed does not necessarily mean that the assimilative capacity of the environment is not being exceeded. In a growing economy, relative decoupling will imply that environmental pressures are still rising. Equally, if economic activity is falling, neither relative nor absolute decoupling will necessarily imply a positive development for society as a whole. For some environmental pressures, however, “strong” de-coupling will be desirable – especially where environmental outcomes are likely to provide a strong constraint to future economic activity. For example, absolute decoupling will be particularly important for those environmentally harmful substances, the concentrations of which are already (or are projected to soon surpass) levels which environmental media can safely absorb (e.g., ozone depleting substances, CO2, many persistent organic pollutants). For other cases – where some minor environmental degradation can be countenanced – the situation is not so clear, and the most we can say is that “weak” decoupling might be sufficient. Some important points to underline when thinking about the “optimal” level of decoupling are: ●
“More” decoupling will not be systematically a good thing. This is because achieving additional decoupling can be assumed to cost too much to the economy. At some point, the additional economic cost of more decoupling will exceed the additional environmental benefits associated with it.
●
We also know that an evaluation of the costs and benefits of protecting the environment should, in principle, help us get to the “right” level of protection. In effect, we need environmental indicators (for the benefits side) and we need economic indicators (for the cost side), but in order to do a cost-benefit comparison, decoupling indicators, that link these two fields do not necessarily help us in the search for efficiency.
●
At root, if we were able to internalise the environmental activities associated with economic activity (i.e. to “get the prices right”), we would find the optimal level of environmental protection – but we would not necessarily need indicator of decoupling to locate this position.
This being the case, why are indicators of decoupling of interest to policy-makers? The answer probably lies in the fact that the full environmental costs of transport are very difficult to estimate and that their power as
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conveyors of concise and understandable information about links between environmental problems and their economic sources. By visualising trends in both sets of variables together, images emerge about priorities for future analysis and, possibly, for future policy action.
Links to policy Decoupling may actually result from various factors, only some of which are related to environmental policy (such as regulating emissions from a particular pollution source). For example, structural changes in the economy itself may also lead to decoupling (e.g. changes in consumption preferences or in technological processes). The cause of the decoupling may also relate more to economic policy (e.g. tax shifts that expand GDP without increasing environmental pressures). Unbundling the specific reasons for an observed amount of decoupling in a given context will not be easy. In turn, this can make it difficult to develop specific policy recommendations aimed at promoting further decoupling. The end result is that the links between policy action and observed decoupling are not necessarily very meaningful. For example, two jurisdictions could have identical environmental policies – in the sense that they both fully internalise all environmental externalities; but each could still indicate vastly different decoupling results, depending on their economic policies, technological capacities, or geographic characteristics. The most important underlying policy issue is therefore whether the environmental externalities are being properly internalised – not whether or not a particular indicator of decoupling is rising or falling. Most of the discussion of decoupling that follows will focus on the economic and social drivers of demand for transport services. However, there are several other factors which ultimately influence transport decisions and development patterns, in particular, the structure of the family and other demographic variables. Even though this report does not explicitly discuss these “other” variables very extensively, it is recognised that non-transport policies which affect these variables are also very important for the decoupling debate.
Aggregation issues On the surface, graphs displaying a rising GDP, juxtaposed with diminishing pollutant emissions, seem to convey a very clear and simple message – that the “environmental intensity” of economic activity is improving. But a closer look suggests that this simple message may be more complicated than first thought. Perhaps there is no causal link between the variables being compared in the graph. Perhaps the environmental intensity is falling, but the overall
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1. INTRODUCTION
environmental pressure is still rising. Broadly, the underlying drivers of transport activities and their environmental consequences have many dimensions. This complicates enormously the specific policy response. Consequently, the more aggregated the indicator of decoupling, the more difficult it will be to “unbundle” those elements that are of most interest to policy-makers. Aggregation across both economic sectors and environmental problems will be particularly problematic. For example, it is difficult to imagine an appropriate policy that could emerge from an indicator of decoupling of greenhouse gas emissions plus loss of biodiversity from GDP growth. Disaggregated indicators of decoupling will therefore probably be the most interesting, and it will make most sense to develop comparisons between individual sectors of the economy with individual environmental problems. For that reason, this report focuses on the transport sector (and its various modal components), as well as on the environmental problems most directly linked to the transport sector. An attempt is also made in the report to be as disaggregated as possible in the analysis of individual trends in the transport sector or its related environmental impacts. Two broad types of decoupling might be of particular interest in the transport sector, and both types are reflected in the analysis presented in this report. First, transport variables could be linked to economic variables. For example, the total amount of transport might increase/decrease, in comparison to GDP. Second, transport variables could be linked to the environmental results they engender. The environmental variables involved here could include such things as emissions, material flows, renewal rates for natural resources, or land use pressures.
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ISBN 92-64-02712-2 Decoupling the Environmental Impacts of Transport from Economic Growth © OECD 2006
Chapter 2
Transport and the Economy
This chapter begins with a discussion of the general links between transport and economic activity. The factors influencing transport demand are analysed in the second section. The chapter then focuses on recent trends in passenger and freight transport. The responses of transport to economic changes are analysed in the section dealing with elasticities. The relation between growth in transport infrastructure and economic growth in general is analysed in the last two parts of the chapter.
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1. Introduction It is generally acknowledged that well-developed economies require an efficient transport system. The development of transport has itself strongly influenced economic development: e.g., road and rail networks have laid the basis for the concentration and specialisation of production processes. Improvements in transport infrastructure have facilitated the expansion of trade and intensified competition among countries and economic regions. Such developments usually occurred in parallel with growth in the economy, and the transport sector has generated an increasing share of employment and income. Apart from these well-accepted effects of transport, there is an increasing body of work that raises concern about the nature, size and implications of the marginal benefits of transport, in particular, questions about additional growth effects associated with expanded transport networks. The chapter contains seven components. It begins with a discussion of the general links between transport and economic activity. The factors influencing transport demand are analysed in the second section. The chapter then focuses on recent trends of passenger and freight transport. The responses of transport to economic changes are analysed in the section dealing with the elasticities. The relation between growth in transport infrastructure and economic growth in general is analysed in the two last part of the chapter.
2. General links between transport and economic activity In 2003, transportation-related goods and services contributed $1 156 billion, or about 11%, to US GDP. Transportation continued to rank fourth (after housing, health care, and food) in terms of total demand for goods and services (Figure 2.1). Between 1992 and 2003, transportation’s final demand grew faster than overall GDP, increasing to 11% of the total. Table 2.1 presents the ranking of commodities by value of freight transported and tonne-miles in 2000. The most important sectors in terms of value were those involving commodities with high value-added, such as electronics and electrical equipment, motorised vehicles, machinery and textile and leather products. These types of commodities have generally a lower demand of transport in terms of tonne-miles (in this survey, less than 7%), while they represent more than 38% of the total value transported.
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Figure 2.1. Major sectoral contributions to US GDP, 2003
Housing 25% Other 27%
Healthcare 17% Education 8% Transportation 11%
Food 12%
Source: Bureau of Transportation Statistics (2004), Transportation Statistics Annual Report.
Table 2.1. Transport ranking of top five freight sectors by value per tonne and tonne-miles Top 5 sectors by value
Top 5 sectors by ton-miles
2000
2000
Value (million dollars)
Sector
Electronic, electrical and office equipment
Tonne Tonne-miles Sector (thousands) (millions)
890 803
49 592
Motorised and other vehicles
748 550
133 088
Machinery
484 152
63 390
30 269 Coal
Tonne-miles (millions)
1 239 862
22 875
687 279
59 029 Cereal grains
561 089
53 835
264 239
967 978
149 951
135 937
328 058
259 834
121 330
345 940
158 586
120 151
8 397 210 11 667 919
3 137 898
479 117
24 270
Base metal in primary 11 337 or semi-finished forms
Textiles, leather, etc.
466 429
51 232
31 789 Wood products
8 397 210 11 667 919
Value (million dollars)
34 535 Non metallic mineral products
Pharmaceutical products
Total of all freight sector
Tonne (thousand)
3 137 898 Total
Source: BTS Commodity Flow Survey Data (2002).
On the other hand, products that have a high demand in terms of tonnemiles and low per unit values, such as fossil fuels (coal, liquid fuels), basic chemicals, cereals and food products, etc. represented more than 42% of total tonne-miles.
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Figure 2.2 compares total freight activity in terms of tonnes and tonnekilometres. It illustrates that, for road freight, the share of cement and building materials is about 21% in terms of tonne-km, while in terms of tonnes, these sectors contribute 45%. This suggests that these particular goods are transported for rather shorter distances. The opposite is true for agricultural products and food, machinery and manufactured articles transported in containers; their respective shares in tonne-km are higher than in tonnes. Figure 2.2. Modal share of types of goods transported in the EU15, 2003 Percentage of tonne-km, excluding short-sea shipping Food, agriculture Ores, iron and steel Chemicals, fertilisers
Solid fuels Metal products Machinery, products
Oil and oil products Cement, construction materials
35 30 25 20 15 10 5 0
Road
Rail
Inland waterways
Source: EC (2005), Energy and Transport in Figures, Statistical Pocketbook, 2005.
3. Factors influencing transport demand The main factors stimulating growth in freight transport in the EU are primarily the integration of the European market, the liberalisation of the transport market (for road, but not yet for rail transport), while at the same time the cost of freight (including fuel prices) have remained relatively low (EU, 2006). These conditions facilitated the development of more complex trading networks, taking advantage of the removal of cross-border barriers and different labour costs among regions. This has resulted in increased distances between resource extraction, manufacturing and distribution facilities. Consequently, the category “machinery and manufactured articles” has experienced the strongest growth in total tonnes transported. Changes in customer requirements (for more tailored and specialised goods), as well as changes in consumer preferences have also contributed to additional, more frequent movements, and longer distances
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traveled. The result has been more transport activity, without necessarily a higher volume of goods being produced. The modal split has also changed considerably in recent years. Road transport has increased, while rail and inland waterways have declined. This has been mainly caused by the changing structure of industry and type of goods produced in the various sectors has changed. Mass commodities, more suitable for rail and inland waterway transport, have broadly become less important to the economy (Baum and Kurte, 2000). In Germany, for example, the amount of coal transported declined from 135 million tonnes in 1960, to 102 million tonnes in 1990. The amount of fertilisers fell from 19 to 17 million tonnes over the same period. Another explanation is that some new production concepts, such as “just-in-time procurement”, place more accent on flexibility and speed. Compared to road traffic, rail and waterway traffic are much slower and require multi-modal solutions. Therefore, these last modes are coming to be used less frequently. Figure 2.3 juxtaposes demand for freight transport with economic growth and trade. It suggests that growth in global trade (in terms of value) has been higher than growth of global GDP. These patterns are also consistent with a continuous increase in movements of goods and overall transport activity. Most freight movement (in terms of tonne-kilometers) is made by ocean freight, which is also the dominant mode for freight transport among the main economic regions of the OECD. In the past, ocean freight has experienced strong growth and Figure 2.3. Growth in world trade, GDP and transport, 1980-2000 Global trade
World GDP
1980
300
1990
2000
250
250
200
200 150 150 100 100 50
e
ys
lin pe Pi
wa
In
lan
d
wa te r
fre
ig h
go
ht ig
ar
n ea
Oc
d Ro a
t
0
Ai rc
2000
fre
1997
ht
1991 1994
ig
1988
fre
0 1982 1985
Ra il
50
Source: World Bank Database (2004).
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it is still the dominant mode in intercontinental freight movements. However, the highest growth rates in world freight volumes are now observed for road freight and aviation. Regional data confirm the global picture. Table 2.2 shows trade-related transport activity in 2004 in the EU and how the different modes contribute to extra and intra-EU25 trade in terms of both value (billion euros) and weight (million tonnes). For example, concerning exports to the extra-EU regions, the most important mode is by far maritime transport, with shares of 47% (value) and 72% (weight). The second rank is held by air transport, contributing 26% of total value (in billion euros). The “value intensity” (value per tonne) is also the highest for air transport among all modes. Table 2.2. External trade by mode of transport in the EU25, 2004 Value (billion euros)
Weight (million tonnes)
Extra-EU25
Extra-EU25 Intra-EU25 import
Export
Import
Export + import
Intra-EU25 import
Export
Import
Export + import
393.8 45%
465.3 49.1
859.1 47.1%
225.9 11.2%
308.5 76.5%
1121.6 70.5%
1430 71.7%
284.5 18.1%
Road
144.1 16.5%
115.6 12.2%
259.7 14.2%
957.5 47.6%
52.8 13.1%
48 3%
100.8 5.1%
489.9 31.1%
Rail
15.4 1.8%
9.7 1%
25.1 1.4%
72.7 3.6%
20.1 5%
69.2 4.3%
89.3 4.5%
96.7 6.1%
Inland waterway
3.3 0.4%
3.3 0.3%
6.5 0.4%
15.4 0.8%
6.8 1.7%
18.2 1.1%
24.9 1.3%
70.3 4.5%
Pipeline
2 0.2%
51.4 5.4%
53.4 2.9%
27 1.3%
3.4 0.9%
275.61 14%
279.1 14%
121.1 7.7%
257 29.4%
216.7 22.9%
473.7 26%
47.1 2.3%
5.1 1.3%
4.7 0.3%
9.8 0.5%
1.1 0.1%
Other including short-sea shipping
59 6.7%
86.4 9.1%
145.4 8%
664.9 33.1%
5.3 1.3%
54.4 3.4%
59.7 3%
511.1 32.5%
Total
874.5
948.4
1 822.9
2 010.6
402
1 591.7
1 993.6
1 574.6
Sea
Air
Source: EC (2005).
In the last few decades, growth in income, improvements in technology and infrastructure, and increasing time being available for leisure trips have allowed people to travel more often and further. The choice of modes of travel also depends heavily on the above factors. Numerous studies suggest that increasing levels of disposable income have a strong effect on traffic growth, because car ownership will increase up to a relatively high level before saturation effects are observed. However, the amount of traffic is also influenced by prices, speed and quality of transport, and also by personal preferences and priorities.
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At the level of the individual, the demand for passenger transport is influenced by the following factors inter alia: ●
journeys that bring people to work, education and training – in economic terms supplying labour to production;
●
journeys that allow access for individuals to consumption opportunities, such as shopping and tourism;
●
journeys that allow access for individuals to other individuals (e.g. visiting friends and relatives); and
●
journeys that provide other values to individuals (e.g. travelling on a preserved steam railway).
A survey in the UK (Table 2.3) identified shopping, commuting and personal business as the three most significant reasons for travelling; accounting for 20%, 19% and 18% respectively of journeys per person per year (SACTRA, 1999). Surveys in Germany and the US broadly confirm these results, although they are not entirely comparable because the specific methodologies differ. Table 2.3. Trips by purpose in Great Britain, Germany and the USA Percentage Great Britain
USA
Germany
1994
1994 21.3
Trip purpose
Work
1975-76
1985-86
1994-96
22.0
19.3
18.6
21.6
Business
4.0
4.3
4.7
41.5
7.5
Shopping
17.6
21.7
19.7
24.8
26.9
Other personal business
10.4
12.8
18.4
12.1
Social – visiting friends
15.0
17.6
18.3
Entertainment/leisure
7.0
6.3
6.6
Holidays
8.0
7.4
3.9
0.2
10.0
10.6
8.0
8.0
Education, incl. escorts
36.1
Notes: These figures are indicative only, since definitions in Great Britain, Germany and USA are not comparable. Source: UK Department of Transport (1996); US Department of Transport (1996); German Enquête Commission “Mobility and Climate” (1994).
Growth in household transportation demand is also constrained by time budgets. The time spent in travel by individuals has been shown to be approximately constant at one hour per day for the past forty years, even while income, motorisation and infrastructure supply have each increased substantially. Household transportation expenditure as a percentage of total final consumption has also not changed much in the EU over the same period, remaining at 13% on average, even while GDP was increasing rapidly (EU, 2006). US data also shows a constant percentage. In 2004, households spent an
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average of USD 7 800 on transportation, or about 18% of total expenditure. Vehicle purchases were the largest component of these expenditures. Age plays an important role in the share of household transportation expenditures. Transportation as a share of household expenditures was highest in “young” households. In 1996, households in the under-25 age bracket spent, on average, 22% of their total household expenditures on transportation. This percentage decreased gradually as age increased, reaching its lowest point (13%) in households in the 75-and-over age bracket (BTS, 1999).
4. Passenger transport Figure 2.4 shows the motorisation level (i.e. the number of cars per 1 000 inhabitants and GDP in OECD regions over the period 1970-2000). It underlines the large differences in motorisation levels between the US (highest), the EU, and Japan (lowest). At the same level of GDP per inhabitant, the US has the highest number of cars per inhabitants, followed by the European region, and finally, Japan. The high values for the US can be explained by several factors: the large physical area of the US; the lack of alternatives to car transport; the abundant supply of road transport infrastructure; and the lower relative price of fuel which exists there. Figure 2.4. Motorisation level and wealth in selected OECD countries, 1970-2000 USA
EU15
Japan
Cars per 1 000 inhabitants 900 800 700 600 500 400 300 200 100 0 10 000
15 000
20 000
25 000
30 000 35 000 GDP per capita (in 1995 US$ PPP)
Source: BTS (2006); EC (2004); MLIT Japan (2003).
A comparison between the US, the EU and Japan, reveals broad similarities in terms of size, mode shares and overall trends of passenger transport (Figure 2.5). Modal split is dominated by passenger cars in the US (87%), the EU (76%) and Japan (63%), while the other modes have minor shares
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Figure 2.5. Modal split of passenger transport in the EU, the USA and Japan, 2003 Passenger car
Bus/coach
Railways
Tram, metro
Waterborne
Air
% 100 8% 1% 1% 6% 8%
90 80 70
10% 0% 3%
7% 0% 3% 20%
60
7%
50 76%
40
87% 63%
30 20 10 0
EU15
USA
Japan
Source: EC (2005).
of less than 10%, except for aviation in the US (10%) and railways in Japan (20%) of total passenger-km. Figure 2.6 shows historical trends by mode in the US, the EU and Japan for the past three decades: travel by car clearly dominates the overall growth. In the US, aviation and passenger car transport have the highest growth rates. Between 1970 and 2003, passenger car distances increased by 120%, while air transport increased by 330%. In terms of billion pkm, passenger car transport is very much larger than air transport; while in terms of growth, air transport is the fastest growing mode. In the EU, car passenger transport also overwhelmingly dominates the modal share (76% in 2000). Again, the share of air transport in the modal split grew from 1.5% in 1970 to 8% in 2003, largely at the expense of public transport. For example, the share of rail transport fell from 10.1% in 1970 to 6% in 2003. Passenger transport in the EU has experienced important increases in recent years, mainly due to increases in income levels and overall expansion of the economy. Since 1980, it increased by 80%. This trend towards more individual motorised transport can be partly explained by the declining size of households. In 1970, for example, there were 5.5 million single-person households in Germany; in 1994, there were 12.7 million. The share of air transport in Japan grew from 1.3% in 1970 to 7% in 2003. During the same period, public transport (rail, bus and shipping) lost part of its share. The share of rail fell from 41% to 20%. Again, transport by car dominates the modal share with some 63%, and this has increased over the past decade.
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Figure 2.6. Passenger transport trends by modes in the US, EU and Japan, 1970-2003 Billion pkm Passenger cars
8 000
Rail
Bus
Passenger transport trends by modes in the United States 1970-2003 (billion pkm)
5 000
Aviation
4 500
7 000
4 000
6 000
3 500
5 000
3 000
4 000
2 500
3 000
2 000 1 500
2 000
1 000
1 000 0 1970
Train/metro
Passenger transport trends by modes in the European Union 1970-2003 (billion pkm)
500 75
80
85
90
95
2000
0 1970
03
75
Private cars Bus
80
85
90
95
2000 03
Taxis Railway
Aviation
Passenger transport trends by modes in Japan 1970-2003 (billion pkm)
900 800 700 600 500 400 300 200 100 0 1970
75
80
85
90
95 2000
Source: EC (2005); BTS (2006); Compendium of Statistics on Energy Economics, Japan (2003).
5. Freight transport Figure 2.7 illustrates the road freight intensity in terms of tkm per capita and GDP for the period 1970 to 2000 for the US, Japan, and the EU. The data again underline the strong correlation between freight transport and economic growth. For a given level of GDP per capita, road freight intensity is comparable
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Figure 2.7. Trends of road freight intensity and GDP per capita in the OECD area, 1970-2000 United States road freight
European Union road freight
Japan road freight
Cars per 1 000 inhabitants 7 000 6 000 5 000 4 000 3 000 2 000 1 000 0 10 000
15 000
20 000
25 000
30 000 35 000 GDP per capita (in 1995 US$ PPP)
Source: BTS (2006); EC (2004); MLIT Japan (2003).
between the US and Europe, while Japan has a much lower relative freight transport demand. The highest intensity for road freight has been observed for the US, with 6 100 tkm per capita (in 2000). The modal split for freight transport (Figure 2.8) is relatively similar in the EU and Japan, with a high share going to two major modes – short-sea shipping: 41% in Japan and 39% in the EU15; and road freight: 44% in the EU and 55% in Figure 2.8. Modal split of freight transport in the EU, the USA and Japan, 2003 Road
Rail
Oil pipeline
Short-sea
Inland navigation
% 100 90
7%
80
14%
39%
70
41%
8%
60
0% 4%
3% 3% 10%
50 40
39%
30 44%
20
0
55%
31%
10 EU15
USA
Japan
Source: EC (2005).
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Japan. The US has a more balanced modal share, with rail taking the highest share (39%), followed by road (31%) and pipelines, inland navigation and shortsea shipping (7-8%). Figure 2.9 shows that freight transport trends in the US over the past three decades have changed considerably. There has been strong growth in rail as well as in road freight since 1985, due to the stronger integration of the North American market, whereas during the 1970s and early 1980s (i.e. during the second oil crises), rail and road had each experienced slower growth rates. Rail transport in the US today maintains a high modal share (39%), followed by road freight (31%). Strong growth of transport activity in Japan has not affected all modes of transport to the same extent. The share of road transport in the total of freight transport (in terms of per cent of total tonne-km) increased between 1970 and 2003 from 39% to 55%. During the same period, the share of rail decreased from 18% to 4%, while short sea remained stable (around 41% since 1985). In the EU, the share of road freight transport increased from 31% to 44% in terms of total tkm, while short sea shipping remained stable (around 39% since 1980). During the same period, the share of rail decreased from 22% to 10%, and inland waterways declined from 8% to 3% (European Commission, 2005).
6. Elasticities Factors which could affect the sensitivity of changes in transport activity to changes in prices include: the type of price change; the type of trip and traveller; and the quality and price of alternative routes, modes and destinations.
Type of price change Different types of transport charges can have different impacts on travel behaviour. For example, parking charges and road tolls may affect travel routes and destinations. A time-variable fee may shift some trips to other times. Fuel price increases tend to affect the type of vehicles purchased more than vehicle mileage charges.
Type of trip and traveller Trips for commuting tend to be less elastic than shopping or recreational trips (because they are more “necessary”). Weekday trips may have very different elasticities than weekend trips. Travellers with higher incomes tend to be less sensitive to price changes than lower-income travellers, as are travellers on business, relative to people travelling for personal activities.
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Figure 2.9. Freight transport trends by modes in the US, the EU15 and Japan, 1970-2002 Billion tkm Intercity truck Short-sea ships Inland waterways
2 500
Rail
Road Short-sea ships Inland waterways
Pipelines
Freight transport trends by modes in the United States 1970-2003 (billion tkm)
Rail Pipelines
Freight transport trends by modes in the European Union 1970-2003 (billion tkm)
1 800 1 600
2 000
1 400 1 200
1 500
1 000 800
1 000
600 400
500
200 0 1970
75
80
85
90
95
2000
0 1970
03
Road
75
80
85
90
95
2000 03
Rail
Short-sea Freight transport trends by modes in Japan 1970-2003 (billion tkm)
350 300 250 200 150 100 50 0 1970
75
80
85
90
95 2000
Source: EC (2005); BTS (2006); Compendium of Statistics on Energy Economics, Japan (2003).
Quality and price of alternatives Price sensitivity tends to increase if alternative routes, modes and destinations are of good quality and affordable. For example, highway tolls tend to be more price-sensitive if there is a parallel free roadway. Also, driving is less
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price-sensitive in the automobile-dependent areas where transport alternatives are very difficult to use. Price sensitivities are usually measured using demand price elasticities, which are defined as the percentage change in demand of a good or service caused by a percentage change in its price or other characteristics, such as service quality or road capacity. For example, an elasticity of –0.5 for vehicle use with respect to vehicle operating expenses means that a 10% increase in these expenses results in a 5% reduction in vehicle mileage or trips. If prices decline, travel usually increases, because lower-value trips will become more affordable. If prices increase, travel usually declines, as consumers choose to abandon some lower-value trips, or to shift to cheaper modes or destinations. Table 2.4 summarises some results of empirical studies on transport elasticities. The numbers in parenthesis indicate the best available value for elasticity, as estimated by the authors. These results show that fuel price change have a significant negative effect on car fuel demand, since a 10% increase in fuel price results in a 7% reduction in car fuel demand. Another significant result is the sensitivity of car fuel demand, car travel demand, and car stocks to changes in income. An increase of 10% in income will lead respectively to a 12% increase in both car fuel demand and travel demand, and to a 10% increase in car ownership. Table 2.4. Estimated long-term transport elasticities Estimated component
Taxation (other Population density than fuel tax)
Fuel price
Income
–0.20 to 0.0 (–0.1)
0.75 to 1.25 (1.0)
–0.08 to – 0.04 (–0.06)
–0.7 to –0.2 (–0.4)
Mean fuel intensity (fuel efficiency)
–0.45 to – 0.35 (–0.4)
–0.6 to 0.0 (0.0)
–0.12 to – 0.10 (–0.11)
–0.3 to –0.1 (–0.2)
Mean driving distance (per car per year)
–0.35 to – 0.05 (–0.2)
–0.1 to 0.35 (0.2)
0.04 to 0.12 (0.06)
–0.75 to 0.0 (–0.4)
–1.0 to – 0.4 (– 0.7)
0.05 to 1.6 (1.2)
–0.16 to – 0.02 (– 0.11)
–1.75 to –0.3 (–1.0)
–0.55 to – 0.05 (– 0.3)
0.65 to 1.25 (1.2)
–0.04 to 0.08 (0.0)
–1.45 to –0.2 (–0.8)
Car stock (vehicle ownership)
Car fuel demand Car travel demand
Source: Johansson and Schipper (1997).
The scale of the price change is also an important variable, because driving distances are actually quite elastic with respect to total costs. Other individual price components of driving (fuel, parking, and tolls) are considered inelastic because they each represent a small portion of the user’s total costs. For example, since fuel is only about 15% of a transport user’s total costs, a –0.2 elasticity of driving distance with respect to fuel price represents an elasticity of –1.3 with
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respect to transport user’s total costs. This implies that if all user costs were converted into variable charges, each 1% increase in the price would reduce driving by 1.3%. The time period used to apply policy instruments is also very important for determining real transport elasticities. Transport elasticities tend to increase over time, because consumers have more opportunities to take prices into effect when making long-term decisions. For example, if consumers anticipate low automobile use prices, they are more likely to choose an (automobiledependent) suburban home, but if they anticipate significant increases in driving costs, they might place a greater premium on having alternatives, such as access to transit and shops, within convenient walking distance. Income is another relevant issue that should be raised in the context of the analysis of real transport elasticities. Indeed, two distinct income groups should be analysed. Various analyses show that high revenue groups will favour high money cost/low time cost options over modes with lower costs and longer travel times (Brueckner, 2005). Therefore, small changes in the price of transport modes will have little impact on the choices made by high revenue groups. On the other hand, low revenue groups will be more sensitive to price changes, and less sensitive to time. Therefore, small price changes can have large impacts on the choice of their transport modes (i.e. low revenue groups will have a much more elastic demand for transport with respect to price). For this reason, it may take many years for the full effect of a price change to take place. Studies cited by Button (1993) estimate that short-term elasticities (two-years) are typically one-third of long-term elasticities (15 years or more) (Table 2.5). Dargay and Gately (1997) have concluded that about 30% of the response to a price change takes place within 1 year, and that virtually all takes place within less than 13 years. Dargay and Goodwin (1995) also argued that the common practice of using static (instead of dynamic) elasticity values overestimates welfare losses from increased user prices and congestion, because it ignores society’s ability to respond to changes over time. Giuliano and Dargay (2006) compare travel patterns in the UK and US. They find that UK residents own fewer automobiles and make fewer and shorter motor vehicle trips than their US counterparts, due to a combination of lower real incomes, higher vehicle fees (particularly fuel taxes) and better travel options (better walking and cycling conditions, better public transport services, and more local shops). Based on a major review of elasticity studies Goodwin, Dargay and Hanly (2004) conclude that: ●
Fuel consumption elasticities are greater than traffic elasticities – mostly by factors of 1.5 to 2.
●
Long run elasticities are greater than those in the short run – mostly by factors of 2 to 3.
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Table 2.5. Overall results: various elasticities Dependent Variable
Short term
Long term
–0.25
–0.64
Fuel consumption (total) Mean elasticity Standard deviation Range Number of estimates
0.15 –0.01, –0.57
0.44 0, –1.81
46
51
–0.08
–1.1
Fuel consumption (per vehicle) Mean elasticity Standard deviation Range Number of estimates
n.a. –0.08, –0.08
n.a. –1.1, –1.1
1
1
–0.10
–0.29
Vehicle kilometres (total) Mean elasticity Standard deviation Range Number of estimates
0.06 –0.17, –0.05
0.29 –0.63, –0.10
3
3
–0.10
–0.30
Vehicle kilometres (per vehicle) Mean elasticity Standard deviation Range Number of estimates
0.06 –0.14, –0.06
0.23 –0.55, –0.11
2
3
–0.08
–0.25
Vehicle stock Mean elasticity Standard deviation Range Number of estimates
0.06 –0.21, –0.02 8
0.17 –0.63, –0.10 8
Source: Goodwin, Dargay and Hanly (2003).
●
Income elasticities are greater than price elasticities – mostly by factors of 1.5 to 3.
They also conclude that if the real (inflation adjusted) price of fuel rises by 10% and stays at that level, the result is a dynamic process of adjustment, such that the following will occur:
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●
Traffic volume falls about 1% within a year, and to 3% in the long-run (5 years).
●
Fuel consumption falls about 2.5% within a year, and to a 6% longer run reduction.
●
Efficiency of fuel use rises by about 1.5% within a year, and around 4% in the longer-run.
●
Total vehicle ownership falls by less than 1% in the short-run, and 2.5% in the longer-run.
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They also conclude that if real income goes up by 10%, the number of vehicles, and the total amount of fuel they consume, will both rise by nearly 4% within about a year, and by over 10% in the longer-run. Traffic volumes (i.e. total vehicle travel) also increases about 2% within a year and 5% in the longer run, indicating that the additional vehicles are driven less than average mileage. Table 2.6. Vehicle travel elasticities with respect to user costs Cost component
Short run effect
Long run effect
Out-of-pocket price Fuel (work)
– Low
– Low to medium
Fuel (non-work)
– Medium
– Medium to high
Highway tolls
– Medium
– High
Parking fees
–Low
– High
Riding time
– Low
– Medium
Parking search
– Low
– High
Congestion
– Low
– High
Time costs
Cost of alternatives Transit fare
+ Low
+ Low
Transit access time
+ Low
+ Low
Elasticities: low = 0 to 0.5; medium = 0.5 to 1.0; high = 1.0+. Source: Moore and Thorsnes (1994).
7. Transport infrastructure and economic growth In the early stages of development of a country, transportation infrastructure is an important contributor to economic growth. Transport investments stimulate growth from the demand side, and also contribute to the economic transformation of regions and urban areas affected, on the supply side. Investments in transportation systems (roads, railways, and canals) have a long history of contributing to economic development. They reduce the cost of transport between regions; they also play an important role in reducing regional disparities and in improving the competitiveness of regions, by facilitating trade, the movement of labour, and economies of scale. Figure 2.10 illustrates these relationships. It highlights that: ●
Realising the benefits of economic growth will depend on the presence of positive (“allocative”) externalities in various markets (e.g. economies of scale, size, scope, agglomeration, density and network). The combined effect of these impacts will result in additional economic growth, usually measured as changes in employment, output, and productivity (Berechman, 2001).
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Figure 2.10. Links between transport infrastructure investment and economic growth Infrastructure investment Investment multiplier Travel effects Network accessibility
Primary effects travel time and costs, traffic volume
Welfare gains
Activity, spatial distribution
Externalities
Pecuniary
Environment
Relative prices and land rent
Allocative externalities
Transport network economies
Labour market
Agglomeration: Firms cost reduction spatial and organisational changes
Economic growth
Source: Berechman (2001).
●
Improving transport accessibility alone will not be sufficient to generate growth. Improved accessibility reduces travel time, but does not necessarily lead to higher travel volumes or to greater economic growth.
Long-term economic growth can also occur in the absence of transport investment, especially where transport services are not a bottleneck. Other variables like technological innovations, improved labour productivity, investment in business plant and equipment, human capital improvement, can also drive the growth process (Sen et al., 1998). In the case of well-developed economies, transportation infrastructure investments can lead to negative results for economic growth. For example, transport investments in one region could lead to competitiveness problems in another. If the benefits to the first region are less than the disbenefits to the second, overall economic activity will decline (Boarnet, 1998; Sen et al., 1998).
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The net economic effects of transport infrastructure investments should be captured in a general equilibrium analysis. Transport improvements initiate a wide range of economic effects and feedbacks in various interacting markets. Transport infrastructure and service improvements lead to lower costs, thereby increasing accessibility for market actors (input suppliers, labour, and customers). Market expansion and (possibly) market integration will then follow, as opportunities for exporting and importing goods increase (Lakshmanan, 2002). Export expansion lead to higher levels of output, which allow higher sales and improved efficiency, both via the restructuring of the economy (as firms enter and exit) and by promoting leaner production processes (which lowers the costs of production and raises productivity). Lower transport costs and increased accessibility also enlarge the markets for labor and other factor inputs. Firms can now draw labor from a broader area, and with a greater range of attributes. Similar effects in land and other factor markets are likely to ensue. However, in an integrated market, some negative feedback effects associated with expanded production are likely to appear, which may dampen the initial positive impacts of the infrastructure improvements noted above. For example, expanded production will also raise the demand for labor and land. Wages and rents will increase, thereby offsetting part of the initial lower costs and gains in competitiveness. Wage rises, if persistent, could also have migration consequences. Finally, higher production levels may lead to new congestion in the networks, and ultimately, to a rise in transport costs.
8. Elasticity of growth to transport infrastructure investments The significant increase in public infrastructure transport investments (particularly in highway infrastructure) in some OECD countries in the post-war years, followed by sharp declines in these investments in the early 1970s and 1980s, stimulated considerable empirical work on the link between infrastructure investment and economic performance. Conceptually, this “output elasticity” indicates the expected percentage change in overall production associated with a 1% increase of a particular transport infrastructure variable. Very high elasticities have been shown in some time series analyses – several of these elasticities are higher than 0.50 (Table 2.7). However, these elasticities do not provide sufficient evidence that a causal link between transport infrastructure investments and economic growth actually exists. Using timeseries analysis can result in “false correlations” – many factors will grow smoothly over time, and selecting any two of them will always show a strong statistical link. For example, time lags between investments in infrastructure and economic growth will also affect the reliability of this interpretation. Aschauer (1990) provided a different approach to this question, in seeking to justify the large public investments on transport infrastructure which were occurring in different US States at that time. Output and productivity levels (in
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Table 2.7. Output elasticities derived from aggregated production functions Data sets based on time-series Output elasticity United States Netherlands
0.29-0.64 0.48
Japan
0.15-0.39
Germany
0.53-0.68
Canada
0.63-0.77
Belgium
0.54-0.57
Australia France, UK, Finland, Norway, Sweden
0.34-0.70 Wide range between highest and lowest value: i.e. between 0.1 and 0.8
Source: Johansson et al. (1996).
both space and time) were compared to greater or lower levels of infrastructure investment. He broadly concluded that growth generates latent demand for more transport; unless the public sector responds with new infrastructure investments, the result will be a constraint on future growth. His approach came to be called the aggregate investment approach, since infrastructure is considered a direct injection into the economy, stimulating short-term demand as well as increased capacity, both of which raise long term growth potential. The econometric model used by Aschauer initially showed that the output growth elasticity to infrastructure investments was very large. However, when his method was reviewed in detail by other analysts, it was concluded that the same data could be interpreted in the opposite direction – that transport investment was the result of growth, not the cause of it. Several specialists now consider that Aschauer’s work probably exaggerated the size of the “output elasticity”, and they suggest values in the range of 0.1 (Lau and Sin, 1997) (Table 2.8), even though they acknowledge that highway investments may be more important contributors to growth than other types of infrastructure improvement. A recent study (Preston, 2005) has shown that there are both theoretical and practical reasons to expect that road transport investments might have modest beneficial effects on the wider economy in well-developed countries, although in certain circumstances, negative effects could be anticipated. Indeed, Preston concludes that an elasticity of 0.1 might be appropriate in the short-run, falling to zero in the longer-term.
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Table 2.8. Output elasticities derived from aggregate production functions Pooled data sets used Coefficient
Level of analysis
Infrastructure variable Productivity variable
Aschauer (1989)
0.39
National
Public capital
National output
Munnell (1990)
0.33
National
Public capital
National output
Aschauer (1989)
0.24
National
Core public capital
National output
Lynde and Richmond (1991)
0.20
National
Public capital
National output
Hulten and Schwab (1991)
0.03
National
Public capital
National output
Moomaw and Williams (1991)
0.25
State
Highway density
Total factor
Costa, Ellson, Martin (1987)
0.20
State
Public capital
Output
Munnell (1990)
0.15
State
Public capital
Gross state product
Munnell (1990)
0.06
State
Highway density
Gross state product
Garcia-Milà and McGuire (1992)
0.04
State
Highway density
Gross state product
Deno (1998)
0.31
Metro area
Highway density
Personal income
Duffy-Deno and Eberts (1989)
0.08
Metro area
Public capital
Manufacturing output
Eberts (1986)
0.03
Metro area
Core public capital
Manufacturing value added
Source: US Department of Transportation, Federal Highway Administration (1992).
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ISBN 92-64-02712-2 Decoupling the Environmental Impacts of Transport from Economic Growth © OECD 2006
Chapter 3
Transport and the Environment
This chapter begins with a discussion of transport’s externalities (accidents; air pollution; climate change; noise; nature, landscape and urban effects). An overview of transport externalities in Europe is presented in the second section. The chapter then focuses on recent trends in energy consumption in the transport sector together with CO2 and CO emissions.
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1. Transport externalities External costs for road transport should be included in the costs faced by road users. If they are not taken into account by the individual motorist/ trucker, demand for road travel will not change in relation to these real costs preventing the market from reacting properly. And the volume of traffic will exceed the optimum level that would pertain with internalisation of all relevant costs, resulting in important market inefficiencies. Many trips would be avoided or made by more environmentally friendly means of transport, if transport users were requested to pay the full social costs of their actions through policies that generate appropriate price signals. For example, the marginal costs of transportation services provided by different modes should reflect the marginal social costs associated with each mode (RFF, 2003). Transport activity continues to cause large adverse impacts on environment, human health and the economy, despite considerable progress in reducing some traditional air pollutants in many OECD countries. Major environmental impacts are due to greenhouse gas emissions, local air pollution, noise, congestion. Transport activity also involves significant externalities associated with accidents, as well as the depletion of non-renewable resources (mainly fossil fuel). The placing of monetary values on the externalities associated with transport has a number of distinct benefits associated with it (ECMT, 1994). Not the least of these is that it enables important trade-offs between internal and external effects to use a common “numéraire”. The practical issue is one of deciding on evaluation methods. The science of placing appropriate monetary values on many of the major externalities associated with transport have progressed a long way in recent years. But a major difficulty with evaluation of transport-induced externalities, and in particular those associated with environmental effects, is that their impacts can be quite diverse. For ease of understanding the evaluation problem, it is helpful to separate the effects into three spatial/temporal categories: ●
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There are local effects on residents and workers, and to property, in the area immediately adjacent to the transport activity. Noise nuisance is the most apparent problem, but there are also local air pollutants, such as lead and particulates, which can which can have adverse effects for health, while sulphur and other emissions can damage buildings.
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●
There are transboundary effects which can impact on adjacent areas. These include low level ozone, which can spread across wide parts of urban areas, and “acid rain gases, such as nitrogen oxides”, which can harm woodland and lakes some distance from the site of the emission. These transboundary effects by their nature tend to impact in the medium term rather immediately.
●
There are global effects on the atmospheric composition. The main concerns are “greenhouse gas” emissions, such as carbon dioxide.
This diversity complicates policy initiation, especially concerning the level of decision-making which should implement the policy. But even before this stage is reached, it poses problems for evaluating the scale of the problem. For example, the longer term effects of carbon dioxide (CO2) emissions are difficult to forecast (and hence, to value). In OECD countries, road transport is responsible for most of the transport sector’s impact on human health and the environment. It accounts for over 80% of all transport-related energy consumption, for most of the accidents and the majority of air pollutant emissions, noise and habitat degradation (OECD, 2001). Maritime transport, although generally associated with lower environmental impacts, continuously raises concern due to oil pollution from major accidents. More recently, there has been a growing concern over global environmental impacts from air traffic, which has been increasing particularly rapidly for tourism and leisure trips. Air transport currently represents about 11% of transport-related energy consumption.
Accidents Road accidents are by far the main contributors to transport health effects, as measured by disability-adjusted life years (DALYs) and related costs, including damage to vehicles and other property; police and emergency service expenditure; legal, insurance and funeral costs; medical treatment; compensation for pain, grief and suffering to those involved in accidents or to their relatives, and loss of output. The value of material accidents is usually assumed to be equivalent to the monetary costs of the damage. As regards the costs for death and injuries, estimates typically cover direct costs (medical care, transportation costs, etc.); indirect costs (production losses); and (occasionally) the value of the lost life to the community. In the US, there were about 44 900 fatalities related to transportation in 2003 (15.4 fatalities per 100 000 residents) (BTS, 2006). Approximately 95% of all transportation fatalities in 2003 were highway-related. Most of the people who died were occupants of passenger cars or light trucks. Air, rail, transit, water, and pipeline transportation resulted in comparatively few deaths per 100 000 residents.
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While transportation accidents amounted to 6% of deaths among those under age 65 between 1991 and 2000, these fatalities represented 10% of the total years of potential life lost (YPLL) during this period. Each year, a far larger number of people are injured than killed in transportation-related accidents. For example in the US, an estimated 2.9 million people suffered some kind of injury involving passenger and freight transportation in 2003. Most of these injuries (about 99%) resulted from highway crashes. Injury rates for some highway modes declined between 1993 and 2003. However, rates for light-truck occupants increased by 7%, from 48 per 100 million passenger-miles of travel (pmt) to 51 per 100 million pmt. Motorcycling became safer in terms of injuries per-mile ridden until 1999; but since then, the injury rate has increased from 429 per 100 million pmt to 554 per 100 million pmt (by 2003). Bus injuries have consistently fluctuated between 10 per 100 million pmt and 15 per 100 million pmt.
Air pollution The transport sector is a major source of air pollution at the local, regional and global levels. It is also the dominant source of air pollution in urban areas. Carbon monoxide (CO), carbon dioxide (CO2), nitrogen oxides (NOx), particulate matter (PM), lead (Pb) and volatile organic compounds (VOCs) are the main air pollutants emitted from transport activities. In 2002, transportation vehicles, ships, aircraft, and locomotives emitted 58% of US carbon monoxide (CO), 45% of its nitrogen oxides (NOx), 3% of its volatile organic compounds (VOCs), 4% of its particulates, 8%, of its ammonia, and 5% of its sulfur dioxide (BTS, 2006). With the exception of ammonia emissions (which grew 54%), other transport-related air emissions declined between 1992 and 2002. Most of these declined by at least 30%; however, NOx emissions decreased initially only 8% but then fell by 18% (by 2002). In 2002, highway vehicles emitted almost all of the transport sector share of CO, 78% of the sector’s NOx, and 77% of all its VOC emissions. Marine vessels and railroad locomotives contribute 11% and 9%, respectively, of transportation’s NOx emissions. Other vehicles, such as recreational boats, airport service vehicles, and road maintenance equipment, contributed 22% of the transport sector’s VOC emissions. In the EU, emissions of acidifying substances, particulate matter, and ozone precursors from transport fell by 30-40% from 1990 to 2003 (excluding international aviation and maritime transport) (EEA, 2006). This decrease would appear to be linked to EU legislation. Regulations first targeted road vehicles from the end of the 1980s; standards for two-wheelers, barges, diesel
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trains and mobile machinery have also come into force recently. In total, maritime sources contributes about 20% of NOx and 77% of SOx emissions from the transport sector in the EU. By banning the use of lead in gasoline, the United States and Europe have virtually eliminated transportation related emissions of lead. It has been calculated that as a result of this ban and other lead control measures, such as restrictions on the use of lead in paint, lead levels in children’s blood are down more than 80% from levels experienced in the late 1970s (Jacobs, 1999). Exposure to air pollution can cause adverse health effects – most acutely in children, asthmatics, and the elderly – and can damage vegetation and structures (WHO, 1999). Within the transport sector, road traffic is the most important contributor to urban air pollution, and most of the substances emitted have been linked to health problems ranging from minor irritation to carcinogenic qualities (INFRAS, 2004).
Climate change The transportation sector represented 27% of total US GHG (greenhouse gas) emissions in 2003 (Figure 3.1). Transportation emissions of GHGs also grew 20% since 1993, while total US emissions rose by only 10% (BTS, 2006). Figure 3.1. US greenhouse gas emissions by economic sector, 2003 US territories 1% Agriculture 8%
Industry 29%
Commercial 18%
Residentiel 17%
Transportation 27%
Source: BTS (2006).
Carbon dioxide (CO2) emissions accounted for 85% of the total in 2003. Nearly all (95%) of these emissions are generated by the combustion of fossil fuels, with transportation being responsible for 30% of these. Transportation CO2 emissions grew overall by 19% between 1993 and 2003.
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Heavy-duty truck emissions grew the most over this period (51%), while aircraft emissions rose the least (2%). Aircraft emissions did rise 15% between 1993 and 2000, but then declined 11% from 2000 through 2003. Highway vehicles emitted 82% of all transport-related US CO2 emissions in 2003, increasing 23% between 1993 and 2003. Passenger cars and light-duty vehicles generated 76% of highway CO2 emissions. In the EU15, transport accounts for about 21% of total greenhouse gas emissions (excluding international aviation and maritime transport). While GHG emissions of many sectors are decreasing, the contribution from transport continues to grow. Since 1990, these emissions have increased by around 23%. In addition to the transport modes covered by the Kyoto Protocol, international aviation and maritime shipping also produce significant GHG emissions. Aviation is growing faster than any other transport mode and CO2 emissions from that source grew by 62% in the EU15 between 1990 and 2003. Aviation now accounts for 14% of transport based EU15 CO2 emissions (including international aviation). Maritime transport is responsible for 13% of the world’s total transport GHG emissions at the moment. Projections foresee a growth of 35-45% in absolute levels between 2001 and 2020, based on expectations of continued growth in world trade (Eyring et al., 2005). Global CO2 emissions from transport, mainly from motor vehicles, are projected to increase by approximately 83% from 1995 to 2020, and to almost double from 1990 levels (IEA, 2005). In OECD countries, CO2 emissions from motor vehicles are projected to increase by approximately 44% from 1995 to 2020 (by 59% from 1990). The contribution of the transport sector to total CO2 emissions in OECD countries is therefore projected to increase from approximately 20% in 1995, to 30% in 2020. Since neither maritime transport nor the international share of aviation is covered by the Kyoto Protocol, pressure to reduce emissions has hitherto been weaker in these sectors than for road transport (where, for example, industry has committed itself to voluntary reductions). However, with its recent Communication on aviation and climate change impacts (EC, 2005), this situation may be changing slightly in the EU context.
Noise Transport noise, particularly from road traffic and aircraft movement, is the major source of external acoustic nuisance in urban areas. In OECD Europe, about 30% of the population are exposed to road traffic noise levels above 55 dB(A), and some 13% above 65 dB(A) (EEA, 2004). Traffic noise remains a major environmental problem as transport activity continues to grow. The economic value of noise impacts across a country in monetary terms will depend upon the degree of urbanisation and the geographical structure of the country.
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Nature, landscape and urban effects Land use for transport is both a factor in generating transport activity (infrastructure-induced mobility) and a contributor to environmental stress. Transport infrastructure, mainly in terms of roads, consumes about 25-30% of land in urban areas, and almost 10% in rural areas in OECD countries. The road network occupies 93% of the total land area used for transport in the EU. Rail is responsible for 4% of land take, and airports for less than 1%. The development and extension of transport infrastructure entails numerous effects on soils (e.g. compaction; soil sealing; and landscape separation effects, leading to habitat fragmentation and destruction, with negative effects on biodiversity (EEA, 2004). Between 1990 and 1998, it is estimated that 30 000 ha of land (about 10 ha every day) were taken for motorway construction in the EU15. Land fragmentation is extremely difficult to reverse. It therefore needs to be fully considered in the original decision to construct new transport infrastructure. The principal policy question is how to enjoy the benefits of high quality transport access while, at the same time, preserving large enough land parcels for biodiversity and social and recreational functions. In this regard, tools such as Strategic and Environmental Impact Assessments (SEA and EIA) need to be utilised to their full potential.
Congestion Congestion costs arise from the inefficient use of existing infrastructure. These costs affect primarily transport users, but also add to the cost of goods and services, which ultimately affect the general public. Thus, congestion represents a market failure since a road space is a scarce resource and is not (typically) priced in the market. The principal problem arising from congestion costs is the time lost by transport users. A consequence of traffic congestion is also an increase of air pollution which damages human health. The former externality affects other transport users, while the latter affects both travellers and the general public. Analysis has estimated that 70-80% of total congestion costs in passenger transport are due to agglomeration traffic, while the remaining share of costs is occurring within long distance travel. The external costs of road traffic congestion are estimated to be approximately 63 billion euro in 2004, which corresponds to about 0.8% of European GDP (INFRAS, 2004).
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Life-cycle issues Transport externalities also include both “upstream” and “downstream” processes. The former involve externalities associated with bringing transportrelated assets to the market (e.g. externalities associated with the mining of fossil fuels used in the transport sector). An example of the latter would be the externalities associated with disposing of used motor vehicles.
2. Overview of transport externalities in Europe Table 3.1 illustrates estimated total and average external costs of road for the year 2000 in EU17 (Switzerland and Norway included). The data are expressed in million euros per year for total passenger and freight, and in euro per 1 000 pkm or tkm for the average cost of passenger and freight. According to a study by INFRAS/IWW (2004) total external costs (excluding congestion costs) amounted to 650 billion euros for 2000, or about 7.3% of the total GDP, in EU17. Climate change was the most important cost category, with 30% of total costs. Air pollution and accident costs amounted to 27% and 24% respectively. Noise and life-cycle processes each accounted for 7% of the total costs. The costs for nature and landscape and additional urban effects were seen to be of minor importance (5%). The most important contributing mode is clearly road transport, generating 83% of the total cost. This is followed by air transport (14%), railways (2%) and waterways (0.4%). Two-thirds of the costs are caused by passenger transport and one-third by freight transport. Another element that should be taken into account is that externalities change over time. For example, one forecast of traffic demand to 2010 shows a dramatic increase of total annual congestion costs of 142% – to 80.2 billion euros (INFRAS, 2000). On the other hand, improved engine design has had a substantial effect in reducing emissions in recent years. Road transport carbon dioxide emissions are still increasing, but emissions of local air pollutants from vehicles (e.g. SOx, NOx) are forecast to be further reduced in the future. Table 3.2 provides an overview of both the range and the size of estimated external costs of transport from various US and European studies. These are expressed in cents per passenger or vehicle-mile travelled, whether the cost category truly varies with distance, or is a fixed-cost component that is averaged over some standard distance. Low and high values reported here are, respectively, the second lowest and the second highest estimates reported in the articles surveyed.
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Million euro/year Road Total
Car
MC
LDV
HDV
Pass total
156 439 (24%)
114 191
965
21 238
8 229
10 964
136 394
45 644 (7%)
19 220
510
1 804
7 613
11 264
Air pollution
174 617 (27%)
46 712
8 290
433
20 431
Climate change (high)
195 714 (30%)
64 812
3 341
1 319
Climate change (low)
27 959 (4%)
9 259
477
Nature and landscape
20 014 (3%)
10 596
Life cycle process
47 376 (7%)
Urban effects
Accidents Noise
Freight total
Aviation Pass
Water borne
Pass
Freight
Freight
Freight
19 194
262
0
590
0
0
21 533
18 877
1 354
782
2 903
195
0
88 407
55 444
108 838
2 351
2 096
3 875
360
1 652
13 493
29 418
69 472
42 911
2 094
800
74 493
5 438
506
188
1 928
4 203
9 925
6 130
299
114
10 642
777
72
276
233
2 562
4 692
11 105
7 254
202
64
1 211
87
91
19 319
1 585
335
5 276
16 967
21 240
22 243
1 140
608
1 592
170
383
10 472 (2%)
5 782
147
127
1 220
2 634
6 112
3 797
426
137
0
0
0
650 275
280 640
15 114
25 491
58 824
164 346
321 301
223 114
7 828
4 487
84 664
6 250
2 632
Notes: Climate change costs for the climate change low scenario with a shadow value of 20 €/t CO2; Climate change costs of life-cycle processes are calculated with the shadow value of the climate change of “high” scenario (140 €/t CO2) Source: INFRAS (2004).
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TRANSPORT AND THE ENVIRONMENT
Total
Bus
Rail
3.
DECOUPLING THE ENVIRONMENTAL IMPACTS OF TRANSPORT FROM ECONOMIC GROWTH – ISBN 92-64-02712-2 – © OECD 2006
Table 3.1. Total external costs of road transport in 2000 by cost category and transport mode (EU17)
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Table 3.2. Range of reported external costs in cost-of-driving studies in the US Cents per passenger/vehicle-mile
Climate change
Low
High
0.3
1.1
Congestion
4
15
Air pollution
1
14
Noise Accident (external)
0.1
6
1
10
Source: Gomez-Ibanez (1997).
3. Energy consumption Total energy consumed by transport in selected OECD countries, and in selected components of the transport sector, is illustrated in Figure 3.2. Transport-related energy consumption in the US increased from 516 million tonnes in 1971 to 745 million tonnes in 2002 (growth of 44%), at the same time that total energy consumption in all sectors was increasing by 47% (from 15 372 MT to 22 643 MT). Growth in transport-related energy consumption was much stronger in the EU, where the increase was 133% between 1970 and 2002 (from 154 MT to 359 MT). Growth in the energy consumption of all sectors was relatively weaker, increasing by only 121% over this period (from 7 177 MT to 15 891 MT). In Japan, the growth was even higher than in the US or the EU, although from a much lower starting point. Between 1970 and 2002, consumption in the transport sector increased by 160% (from 40 MT to 104 MT), and in all sectors by 360% (from 1 650 MT to 7 603).
4. CO2 emissions According to the International Energy Agency (2005), between 1990 and 2002, CO2 emissions from fuel combustion across all sectors increased by 576 million tonnes, with annual growth rates averaging 1.4%. Annual growth rates were quite variable over this timeframe (between –0.2 and 2.4%). Table 3.3 shows that CO2 emissions from transport increased by 24% in the OECD area and by 28% in the world between 1970 and 2002. The share of total CO2 emissions from fuel combustion also increased during the same period both in the OECD area and in the world. In Austria, the share of CO2 emissions of the industry sector was 40%; in 1980 it decreased, reaching 31% in 1998. The share of CO2 emissions of the transport sector grew continuously (Figure 3.3). It was 17% in 1980 and reached 23% in 1998 (a growth rate of 45%).
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Figure 3.2. Energy consumption of transport and all sectors in the US, Japan and Europe, 1970-2002 Million tonnes United States
EU15
Energy consumption of the transport sector
Japan Energy consumption of all sectors
800
25 000
700 20 000
600 500
15 000
400 10 000
300 200
5 000
100
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 1986 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 8 19 6 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
0
0
Energy consumption of road transport
Energy consumption of air transport
600
90 80
500
70
400
60 50
300
40 30
200
20
100
10
0
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 8 19 6 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 1986 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
0
Source: OECD Environmental Transport Database (2006).
Table 3.3. CO2 emissions from the transport sector, million tonnes CO2 (excluding international bunkers) Region
1990
1995
2000
2002
Δ 2002/1990
OECD
2 747
3 026
3 342
3 412
24%
World
3 871
4 295
4 810
4 965
28%
Source: IEA (2005).
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Figure 3.3. CO2 emissions by source in Austria 1980
% 40
1998
40%
35 31%
30 25
15
23%
22%
20
19% 14%
17%
16%
9%
10 5%
5 0
2% 2% Thermoelectric power plant
Small consumer
Industry
Road traffic
Other traffic
Other
Source: BMLFUW (2003).
Figure 3.4 presents trends in CO2 emissions from the transport sector, road transport and all sectors in the US, the EU and Japan. In 1970 in the US, CO2 emissions from the transport sector represented 24% of the total, while in 2002 it increased slightly – reaching 31%. Between 1970 and 2002, CO2 emissions from the transport sector increased by 69%: from 1 037 MT to 1 761 MT. In the EU, this share was 12% of the total in 1970; by 2002, it had increased to 26%. Between 1970 and 2002, CO2 emissions from the transport sector increased sharply by 126%, from 370 MT to 837 MT. In Japan in 1970, the share was 13%; in 2002, it reached 20%. Between 1970 and 2002, CO2 emissions from the transport sector increased by 163%, from 96 MT to 253 MT, although at a substantially lower rate than in the EU and the US. Figure 3.5 presents trends in CO2 transport emissions by mode in the EU15. It underlines, again, the important increase in the share of CO2 emissions from road transport. It is clear that CO2 emissions from maritime and air transport (neither of which are covered by the Kyoto Protocol) are also increasing rapidly. Future strategies for decoupling the environmental impacts of transport from economic growth should therefore, at a minimum, focus attention on these very sensitive sectors.
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Figure 3.4. CO2 emissions by sectors in the US, Japan and the EU, 1970-2002 Million of tonnes United States
EU15
CO2 emissions of transport sector
Japan CO2 emissions of all sectors
2 000
6 000
1 800 5 000
1 600 1 400
4 000
1 200 3 000
1 000 800
2 000
600 400
1 000
200 19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 1986 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 8 19 6 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
0
0
CO2 emissions of road transport 1 600 1 400 1 200 1 000 800 600 400 200
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 1986 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
0
Source: OECD Environmental Transport Database (2006).
5. CO emissions Figure 3.6 presents trends in CO emissions from the transport sector, road transport, and all sectors in the US and the EU. In 1970 in the US, the share of CO emissions in the total was about 85%; in 2002, it decreased to 77%. Between 1970 and 2002, CO emissions in the US from the transport sector decreased by 50%: from 159 MT to 79 MT. These trends were reversed in the EU. In 1980, 76% of total CO emissions were coming from the transport sector, while in 2003 this had increased to 82%.
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Figure 3.5. CO2 emissions by modes of transport in the EU15, 1970-2005 Air
Maritime
Rail
Road
Inland
1 000 tonnes 1 600 000 1 400 000 1 200 000 1 000 000 800 000 600 000 400 000 200 000 0
1970
1975
1980
1985
1990
1995
2000
2005
Source: OECD Environmental Transport Database (2006).
6. Trends across selected air pollutants Figure 3.7 presents emissions of selected environmental problems according to road and rail sources in the US. It again underlines the important share of CO2 emissions, especially from the road sector. It also illustrates that the total of these four emissions is decreasing for rail transport, but is increasing for the road sector. Indeed, in 2002, the level of CO2 emissions of the road transport was 4349% higher than for rail transport. It would appear that technology-based policies that have targeted CO, NOx, and SO2 have been successful in promoting additional decoupling (EEA, 2005).
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Figure 3.6. CO emissions of the transport sector, road transport and all sectors in the US and the EU, 1970-2002 Thousand tonnes United States
EU15
CO emissions of transport sector
CO emissions of all sectors
160
180
140
160 140
120
120
100
100
80
80
60
60
40
02
00
20
98
20
96
19
94
19
92
19
90
19
88
19
19 02
86
19 00
84
19 98
80
19
19
02
00
20
98
20
96
19
94
19
92
19
90
19
88
19
19
19
19
19
19
86
0 84
0 82
20
80
20
82
40
CO emissions of road transport 140 120 100 80 60 40 20
20
20
19
96
94
19
92
19
19
90
19
88
19
86
19
84
19
82
19
19
80
0
Source: OECD Environmental Transport Database (2006).
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Figure 3.7. Trends in CO2, CO, NOx and VOC emissions from road transport and rail transport in the US, 1970-2002 Thousand tonnes CO2
CO
NOx
VOC
CO2, CO, NOx and VOC emissions of road transport 2 000 000 1 800 000 1 600 000 1 400 000 1 200 000 1 000 000 800 000 600 000 400 000 200 000 0 1970
1974
1978
1982
1986
1990
1994
1998
2002
1998
2002
CO2, CO, NOx and VOC emissions of rail transport 60 000 50 000 40 000 30 000 20 000 10 000 0 1970
1974
1978
1982
1986
1990
1994
Source: OECD Environmental Transport Database (2006).
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ISBN 92-64-02712-2 Decoupling the Environmental Impacts of Transport from Economic Growth © OECD 2006
Chapter 4
Decoupling Indicators
This chapter begins with a discussion of the economic indicators of transport versus GDP. In the second section the analysis focuses on the environmental impacts of transport versus GDP.
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DECOUPLING INDICATORS
1. Economic indicators of transport versus GDP Since 1980, US experienced a relative decoupling of both passenger and freight transport versus GDP. Between 1970 and 2000, GDP increased by 160%; passenger transport also increased gradually, but slightly less than GDP, resulting in an overall increase of 120%. Freight transport increased by more than 100%, which was less than both GDP and passenger transport growth. Table 4.1. Growth rate of GDP, passenger and freight transport in the US, 1970 to 2003 In per cent 1970-80
1980-90
1990-2000
2000-03
GDP (2 000 USD constant)
37
37
38
6
Passenger (pkm)
31
33
25
7
Freight (tkm)
35
11
19
4
Source: BTS (2006).
The EU also experienced a very weak decoupling of freight transport versus GDP, while passenger transport growth went very much along with GDP growth (Table 4.2). Table 4.2. Growth rate of GDP, passenger and freight transport in the EU, 1970-2003 In per cent 1970-80
1980-90
1990-2000
2000-03
GDP (2 000 USD constant)
78
27
24
Passenger (pkm)
39
35
40
4
Freight (tkm)
41
18
48
16
4
Source: EC (2005).
When the focus is placed on air passenger and road freight, the results are different (Figure 4.1). Growth in these two modes has been much more rapid than that of GDP. Between 1970 and 2003, air passenger increased by 328%, while GDP was increasing by only 178%. Between 1970 and 2003, the increase in air passenger transport increased by some 1260% in the EU. Growth
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in road transport was less sharp, but still high (increasing by 223%). In the two regions analysed here, therefore neither a relative nor an absolute decoupling of certain modes of transport has occurred. Figure 4.1. Comparison of trends of total transport, GDP growth, road freight transport and air passenger transport in the US and the EU, 1970-2003, 1970 = 100 Total passenger transport
03 20
00
95
20
19
90
Air passenger
Trends of GDP growth, road freight transport and air passenger in the United States
Trends of GDP growth, road freight transport and air passenger in the European Union
500
1 600
450
1 400
400
1 200
350 300
1 000
250
800
200
600
150
03 20
00 20
95 19
90 19
85 19
80 19
19
70 19
03 20
00 20
95 19
19
19
19
19
90
0 85
0 80
200
75
50
75
400
100
70
85
Road freight
19
19
20
20
19
19
19
19
19
19
GDP
19
0 80
0
19
50
70
50
19
100
03
100
00
150
95
150
90
200
85
200
80
250
75
250
70
300
75
Trends of GDP growth, total freight and total passenger in the European Union
300
19
GDP
Total freight transport
Trends of GDP growth, total freight and total passenger in the United States
Source: OECD Environmental Transport Database (2006).
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2. Environmental impacts of transport versus GDP If only road transport is considered, there has been an overall (relative and/or absolute) decoupling of road transport-related emissions of all four gases considered here (Figure 4.2). During the past three decades, CO2 emissions grew by 95% in the US and 156% in EU, whereas GDP grew by almost 169% and 187% respectively. Figure 4.2. Trends in CO2, CO, NOx and VOC emissions from road transport and GDP growth in the US, 1970 to 2002, 1970 = 100 GDP
CO2 from road transport
GDP 300
250
250
200
200
150
150
100
100
50
50
0
0
GDP
CO from road transport
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 1986 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 1986 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
300
NOx from road transport
GDP
250
250
200
200
150
150
100
100
50
50
0
0
VOC from road transport
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 1986 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
300
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 1986 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
300
Source: OECD Environmental Transport Database (2006).
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However, these overall figures disguise some important differences. In the US, most of the decoupling took place in the early 1980s, and has fluctuated since then. In Europe, the relative decoupling has been very “weak”. In Europe, the Euro IV and (upcoming) Euro V emission standards for heavy-duty vehicles have encouraged the industry to develop and market low-emission technology vehicles. Increasing VOC emissions from trucks partly neutralised this trend until the mid-1990s, but have since also declined. Figure 4.3. Comparison of trends of CO2, CO, NOx and VOC emissions from road transport and GDP growth in the EU, 1970 to 2002, 1970 = 100 GDP
CO2 from road transport
GDP 300
250
250
200
200
150
150
100
100
50
50
0
0
GDP
CO from road transport
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 1986 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 1986 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
300
NOx from road transport
GDP
250
250
200
200
150
150
100
100
50
50
0
0
VOC from road transport
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 1986 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
300
19 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 1986 8 19 8 9 19 0 9 19 2 9 19 4 9 19 6 9 20 8 0 20 0 02
300
Source: OECD Environmental Transport Database (2006).
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Most new technologies developed for road vehicles can also be applied to sea and inland vessels, as well as to diesel locomotives. However a certain lead time is needed for these applications (EEA, 2006). New technologies that improve fuel efficiency continue to be applied in road transport; for example, the wider use of lightweight materials, advanced transmissions, and low resistance tyres and lubricants. The wider use of hydrogen, possibly in combination with fuel cells, may eventually reduce CO 2 emissions (provided of course, that the required hydrogen is produced using low-CO2 energy sources). However large scale introduction of these technologies is still a long way off. Road transport-related emissions of CO have been absolutely decoupled from GDP in the US since 1970. In Europe, this decoupling was “relative” between 1970 and 1988, but has been “absolute” since then. Similarly, road transport-related emissions of NOx have been decoupled from GDP in the US and the EU. In the US, this decoupling was absolute during the whole period 1970-2002, whereas in Europe, NOx emissions from road transport were coupled with GDP and only began to decline since 1992 as a result of the introduction of catalytic converters on passenger cars. Decoupling has therefore been absolute since then. Road transport-related emissions of VOCs have also been absolutely decoupled from GDP for the US and Europe since 1970. In the US, these emissions fell by 27%, while GDP was increasing by 169%. As with NOx, most of this decline can be attributed to emission abatement technologies, such as particle filters, exhaust gas recirculation, and catalytic converter.
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ISBN 92-64-02712-2 Decoupling the Environmental Impacts of Transport from Economic Growth © OECD 2006
Chapter 5
Policy Instruments for Decoupling
This chapter begins with a general discussion of some of the generic approaches that are often advocated for promoting decoupling. The second section then focuses on the various policy instruments that are available to promote decoupling (economic instruments, regulatory instruments, investment instruments, institutional arrangements, educational instruments and “soft” measures), focussing on what each of these approaches might bring to the policy “table”.
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1. Introduction As noted earlier, the best approach to decoupling the environmental effects of transport from economic growth lies in the full internalisation of environmental externalities into policy decisions affecting the transport sector. If these externalities could be properly internalised, it would be possible to arrive at the optimal level of decoupling. For this reason, policies that explicitly serve to internalise transport externalities (and in an efficient manner) are the most desirable. Economic instruments tend to go in this direction, and will therefore often be of prime interest to the policy discussion. But economic instruments are not always practical; and other approaches can often be employed as well. This chapter explores the various possibilities which exist. This chapter contains two major components. It begins with a general discussion of some of the generic approaches that are often advocated for promoting decoupling. The second section then focuses on the various policy instruments that are available to promote decoupling (economic instruments, regulatory instruments, investment instruments, institutional arrangements, educational instruments and “soft” measures), focussing on what each of these approaches might bring to the policy “table”.
2. General approaches for decoupling Schleicher-Tappeser, Hey and Steen (1998) identified three broad strategies for decoupling transport impacts and economic growth: ●
Dematerialisation of the economy as a whole.
●
Reducing the spatial range of material flows.
●
Optimisation of transport organisation.
The links between these strategies, the policies that support them, and the decoupling results they generate, are illustrated in Figure 5.1.
Dematerialisation Dematerialisation involves a shift away from economies based on the increasing consumption of raw materials. Dematerialisation can be the result of both technological innovations and structural changes in the use of these
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Figure 5.1. Strategies for decoupling freight transport from economic growth Policy approaches
Basic strategies
Key factors for decoupling
Dematerialisation of the economy
Material intensity of the economy
Reduction of the spatial range of material flows
Spatial structure of production
Substitutions of products by services Miniaturisation Increased durability Lifestyleoriented policies
Market-oriented policies
Regulationoriented policies
Enhancement of regional consumer markets Strengthening of regional production networks
Transport distance
Handling requirements
Globalisation of large companies Slowing down deterritorialisation Transport market organisation
Transport volume
Transport efficiency
Optimisation of transport organisation
Organisation of transport
Source: OECD (2004a).
materials (Malenbaum, 1978). The redesigning of products to reduce resource use or to increase the lifespan of products; or shifts from products to services can both lead to increased dematerialisation of the economy. Technological innovations lead to an increase in the efficiency of material use, through improvements in processes or product design. Structural changes in the composition of economic activities also have an impact on resource use, including: i) changes in input structure (shifts in the relative shares of production factors); ii) changes in the structure of production (shifts in the relative share of economic sectors); and iii) changes in the structure of consumption (shifts in the composition of consumption due to changes in life-style). Technological innovation and structural change are, of course, sensitive to a mix of other variables, including resource prices, government policies, and consumer preferences.
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The case study of Austria (see below) demonstrated that material throughput in the Austrian economy during the twenty years from 1970 to 1990 increased by approximately one-third over that period (OECD, 2004a). At the same time, economic growth and biophysical growth (in terms of direct material input) both increased – in effect, the relative efficiency of material use increased. However, the absolute amount of material use did not decrease, because the relative gains in efficiency were offset by increases in the total use of materials. These increases were mainly caused by few “strategic” material flows, including steel, cement, wood, paper, sand gravel and crushed stone (Schandl et al. 2002). According to one estimate, dematerialisation could result in a 15-20% reduction in freight volumes in the period between 1995 and 2020 (Schleicher-Tappeser et al., 1998). Further reductions could be achieved by raising the durability of products, so that they last longer. However, there is a trade-off here between lasting quality and the need to take advantage of technological innovations as they emerge. The latter can also give rise to new opportunities for dematerialisation, and consequently, for decoupling.
Changes in the spatial structure of production and consumption Since transport demand is a derived demand, it is important to understand the factors that are ultimately responsible for that demand. Spatial organisation influences both transport distances and the modal split. For example, changes in the location of production lead to changes in the production structure, making additional transport necessary to maintain the same level of production. On a global level, international trade and foreign direct investment volumes have increased in recent decades, and regional production clusters (with strong intra-regional links) have gained in importance (Schleicher-Tappeser et al. 1998). These structural changes have reinforced the demand for transport. Increasing division of labour is responsible for rising transport demand ceteris paribus. Increasing requirements of flexibility, reliability, and speed, which result from changes in production methods, such as the introduction of just-in-time production, higher utilisation ratios, etc., favour flexible transport modes (e.g. road transport), or fast transport modes (e.g. air transport). Changes in the spatial structure of consumption are mainly driven by changing individual preferences and rising per capita incomes. For example, people increasingly wish to live near green belts, which will ultimately change suburban travel patterns (ÖROK, 2005). Motorised road passenger transport demand per capita tends to be lower in regions characterised by high population densities. Rural regions exhibit considerably higher motorisation rates than urban areas. For example, the motorisation rate in Burgenland in 2000, the most peripheral federal province of Austria, was 68% higher than that in the federal Province of Vienna, which is a single urban agglomeration (ÖROK, 2002).
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This high motorisation rate reflects the degree of car dependency in rural regions. Low population densities generally do not allow for profitable public transport within an acceptable time schedule. The lack of job opportunities in rural areas, which is partly the result of structure of the economy, will lead to increased commuter traffic. On the other hand, large agglomerations also lead to considerable leisure transport, because in modern urban contexts, many people feel the need to relax in the countryside.
Optimisation of transport organisation The reasons for the different ways transport is organised will vary for freight transport and passenger transport. Within freight transport, the organisation of transport activity is more closely related with the organisation of the total supply chain. Strong interlinkages will therefore exist with the processes of dematerialisation and spatial structure (see above). In the freight area, the organisation of transport depends largely on the development of general logistic strategies. The main trends are (SchleicherTapesser et al., 1998): ●
The downsizing of production and the regrouping of distributors.
●
The spatial reordering of relationships between companies; the building up of “strategic networks”, and the development and implementation of a global supply network.
●
The development of “JIT” (Just in time) and “MRP” (material resource planning) systems: These lead to more flexible and quick transportation of small loads; they also shrink the distances between suppliers and users to a strategically optimal size, and (sometimes) to the reorganisation of the suppliers themselves. All of this tends to increase centralisation.
Supply strategies that relate to new logistic strategies (e.g. JIT and MRP) (Crowley 1995; Brösse and Spielberg 1992) imply a more flexible scheduling of deliveries. The result is that smaller quantities are transported more frequently. Information and communication (ICT) plays an important role in logistics and supply-chain planning. Logistics can benefit from ICT through better route planning, which reduces the number of vehicle-km. However, the Internet and E-commerce may also stimulate “just in time” deliveries, since the e-customer wishes to receive his order as soon as possible, and may increase haulage distances, since it creates more global trade. The major problems in the organisation of freight transport are: ●
A high percentage of empty runs (in Europe currently around 30-40% of all Heavy Good Vehicle (HGV) trips are empty runs).
●
Modest load factors, due to less than optimal vehicle sizes for different transport tasks, and to the lack of vehicle fleet management systems.
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●
In some cases, non-optimised route management.
●
Productivity problems within the rail transport sector.
●
Poor co-operation between transport sectors (combined transport performance represents only 14% of total road transport).
●
Poor co-operation within a given transport sector, especially road transport. Within the passenger sector, two main themes should be distinguished:
●
Business and commuter trips.
●
Leisure, holiday and shopping trips.
Each of these has different transport needs, and therefore, different demands related to the organisation of transport activity. Recent trends associated with these two areas are also different – personal trips are growing faster than work-related trips, and this trend is expected to intensify in the future. For example, people are spending more time on leisure travel, as a larger proportion of people become retired. Flexible working patterns and increased incomes are also opening up new opportunities for leisure travel. Tourism also continues to grow (WSP Civils Ltd., 2003). Within the passenger sector, a key target for decoupling activity is to manage the different kinds of mobility (business trip or leisure trips). Mobility management means intervening in existing passenger transport chains to improve the overall use of the transport system and to raise the use of environmentally-friendly transport modes (public transport, rail, walking and cycling), without reducing total mobility.
3. Economic instruments Taxation For several years, OECD has maintained a database of environmentallyrelated taxes (which includes “unrequited payments to general government revenues, levied on a tax base that is deemed to be of particular relevance for the environment”). This database indicates that revenues from such taxes in OECD countries constitute roughly 2.5% of GDP (with a relatively wide range among all countries of 1%-5%) (Figure 5.2). These taxes also represent approximately 7% of total tax revenue (OECD average) (Figure 5.3). Note that although some countries seem to be expanding their use of these taxes over time, the OECD average seems to be declining. In 2003, Turkey had the highest share of total tax revenue raised through environmentally-related taxes. It is also worth noting that the share decreased significantly after 1995 in both Greece and Portugal – the two countries that had raised the largest share of total tax revenue on environmentally-related taxes in 1995.
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st r Au alia s B elg tria Cz ec C iu h an m Re a d De pub a nm lic Fin ark l F an Ge ran d rm ce G any Hu reec ng e Ic ary el Ire and lan It d J aly Lu apa xe Ko n m re bo a Ne M urg t Ne he exic w rlan o Ze d a s No lan rw d a Sl ov P Pola y ak or nd Re tug p u al b Sp lic Sw Sw ain e Un itze den rla ite d T n Un Kin urk d e W ited gdo y e m Ar igh Stat ith ted es m a et ve ic ra av ge er ag e
Au st r Au alia s B elg tria Cz ec C iu h an m Re a d De pub a nm lic Fin ark l F an Ge ran d rm ce G any Hu reec ng e Ic ary el Ire and lan It d J aly Lu apa xe Ko n m re bo a Ne M urg t Ne he exic w rlan o Ze d a s No lan rw d a Sl ov P Pola y ak or nd Re tug pu al b Sp lic Sw Sw ain e Un itze den rla ite d T n U Ki urk d Ar nite ngd ey d om ith S W met tate eig ic s ht av ed er a av ge er ag e
Au
5.
1995
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POLICY INSTRUMENTS FOR DECOUPLING
Figure 5.2. Revenues from environmentally related taxes in % of GDP
Per cent of GDP 6 1999
1999
2003
5
4
3
2
1
0
Source: OECD/EEA Database on Instruments for Environmentally Policy (2006).
Figure 5.3. Revenues from environmentally related taxes in % of total tax revenue
Per cent of total tax revenue 18 2003
16
14
12
10
8
6
4
2
0
Source: OECD/EEA Database on Instruments for Environmentally Policy (2006).
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Many of these environmentally-related taxes directly address activities located in the transportation sector (Figure 5.4). Figure 5.4. Environmentally related taxes Electricity 3% Heating and process fuels 5%
Waste 1%
Motor vehicles 26%
Transport fuels 65%
Source: OECD/EEA Database on Instruments for Environmentally Policy (2006).
In the case of motor fuel taxes (Figure 5.5), there is clearly considerable variation across OECD countries (EU, Japan, Korea and Turkey are quite high and the US and Canada are relatively low). There have also been significant increases in some countries in these taxes between 2000 and 2005. Some countries maintain lower tax rates for diesel fuels.
Road pricing Economists have long advocated road pricing as an efficient and equitable way to pay roadway costs, because this approach makes users pay directly for driving on a particular roadway. Table 5.1 summarizes the various categories of road pricing, as well as their objectives. Some of these objectives involve providing revenues, others to reduce peak-period congestion, some reduce total traffic impacts (congestion, pollution, accident risks, road and parking facility costs, etc.), and some help achieve a combination of these objectives. However, even if the primarily objective is not to decrease the environmental impacts of transport, the implementation of road-pricing can sometimes lead to this effect. The actual effects of road-pricing depending on various factors, including the type of pricing, how it is structured, and the transportation and geographic conditions in which it is implemented (Victoria Transport Policy Institute, 2006). For example, a fixed road toll may have few impacts on congestion if alternative routes and modes are not available, but it may provide significant
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Figure 5.5. Tax rates on petrol and diesel in OECD member countries Petrol, 1.1.2000
Petrol, 1.1.2005
Diesel, 1.1.2000
Diesel, 1.1.2005
Per litre 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1
Ca
Au
st r A ali na Ca B ustr a da na el ia da giu Cz Fed F m ec . + ed h P . Re ro v De pub . nm lic Fin ark la F nd Ge ran rm ce Gr any Hu eec ng e Ic ary el Ire and lan It d Ja aly Lu K pan xe o Ne mb rea Ne the our w rla g Ze nd a s No land r P way Sl ov P olan ak or d Re tug pu al b Sp lic Sw Sw ain i e Un tzer den la ite d Tu nd US K r US ing key Fe do de Fe m ra de l + ra St l at e
0
Source: OECD/EEA Database on Instruments for Environmentally Policy (2006).
congestion reductions if these alternatives (e.g. ride-sharing, transit and telecommuting) are available. In these latter cases, modest fees can lead to relatively large modal shifts. Table 5.2 summarizes the benefits of various road-pricing strategies. The CANTIQUE (2001) Project of the European Commission looked at the environmental effects of road-pricing in urban areas. It concluded that road pricing can make a meaningful contribution to traffic reduction, and therefore, to reducing the congestion and environmental externalities associated with urban traffic. Figure 5.6 illustrates some “orders of magnitude” of the potential gains found by this study. Road pricing that reduces total vehicle travel can also reduce road and parking facility costs, increase road safety, protect the environment, encourage more efficient land use, and improve the environmental and social quality of an area as perceived by residents, employees, customers and visitors. Conversely, road-pricing that funds additional highway capacity can increase total automobile travel through rebound effects and so may increase downstream traffic congestion, parking costs, crashes, pollution, and sprawl. Expanding highway size and traffic volumes tends to reduce the environmental and social quality of an area of communities that it cuts through (Levine and Garb, 2000).
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Box 5.1. Transport fuel taxation – Germany One environmentally-related transport tax was introduced in Germany in 1999. This was the “Ökosteuer”, or eco-tax, and the aim was to steadily increase fuel taxation over a period of six years by 0.03 USD per year (GTZ, 2003). The tax is not only applied to fuels, but also to energy-use in general (it is also levied on electricity). The intention is to make the use of energy more expensive in order to stimulate fuel efficiency. In 2000, revenues from the fuel tax in the transport sector amounted to about USD 28 billion (about 7% of the national budget). Both drivers and the automobile industry have started to react to the tax, and fuel consumption has decreased (although this effect has clearly been aided by the rapid rise in world prices for petroleum in recent years. The introduction of this tax also had to face a strong opposition from the public. This reaction proved the need to increase public awareness for as part of the strategy for generating public support. The German experience with this fuel tax contains a number of useful lessons that can be used for developing other decoupling instruments (GTZ, 2003): ● The timing of strategies, and long term implementation and adjustments
periods is important. Fuel tax causes public discussion and resistance. Public acceptance should be built through awareness campaigns and the planning of long foreseeable adjustment periods. ● It is possible to introduce economic instruments that allow both for
revenue generation and internalisation of external costs. ● It is technically feasible to enforce a fuel tax regime. There are few
enforcement problems and low administrative costs, because these taxes are collected centrally from few sources. ● Transparent prices can contribute to achieve long term changes in
transport use. ● Fuel taxes can be implemented with significant differentiations.
Public acceptance can be raised using taxation schemes based on social and ecological differentiations.
Resource costs primarily involve the transaction costs of collecting fees, including costs to highway agencies and to users. Toll collection costs range from about 10% of total tolling revenue for electronic toll collection, up to 40% for tollbooths. Toll collection that requires motorists to stop at booths causes motorists delays and increases energy consumption and air pollution.
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Table 5.1. Road pricing categories Name
Description
Objectives
Road toll (fixed rates)
A fixed fee for driving on a particular road. To raise revenues.
Congestion pricing (time-variable)
A fee that is higher under congested conditions than uncongested conditions, intended to shift some vehicle traffic to other routes, times and modes.
To raise revenues and reduce traffic congestion.
Cordon fees
Fees charged for driving in a particular area.
To reduce congestion in major urban centers.
HOT lanes
A high-occupant-vehicle (HOV) lane that accommodates a limited number of lower-occupant vehicles for a fee.
To favor HOVs compared with a general-purpose lane, and to raise revenues compared with an HOV lane.
Distance-based fees
A vehicle use fee based on how many miles a vehicle is driven.
To raise revenues and reduce various traffic problems.
Pay-as-you-drive insurance
Prorates premiums by mileage so vehicle To reduce various traffic problems, insurance becomes a variable cost. particularly accidents.
Road space rationing
Revenue-neutral credits used to ration peak-period roadway capacity.
To reduce congestion on major roadways or urban centers.
Table 5.2. Benefits of road-pricing Revenue generation
Congestion reduction
Pollution reductions
Increased safety
Road toll (fixed rates)
3
2
1
1
Congestion pricing (time-variable)
2
3
2
1
HOT lanes
1
2
1
0
Strategy
Cordon fees
2
3
1
1
Distance-based fees
3
2
2
2
Pay-as-you-drive insurance
0
2
2
3
Road space rationing
0
3
1
1
Ratings: 3 (very beneficial) to –3 (very harmful). A “0” indicates no impact or mixed impacts.
Full cost recovery Neither total infrastructure maintenance nor the external costs of transport are fully covered by any existing mode of transport, and the level of cost coverage differs considerably from mode to mode. In general, efforts to more fully cover these costs will make all transport modes more expensive. A higher price in transport operation makes transport costs more relevant for location decisions, but a change in location can only be expected when the increase in price is high enough (Neary, 2001). For individual transport, an increase in road transport costs will provide incentives to move closer to workplaces, or to take jobs closer to home. An increase in road transport costs will also make alternative transport modes more attractive and (perhaps) decrease the motorisation rate.
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Figure 5.6. Potential emissions reduction through pricing Parking charges
% 14
13.8%
Road pricing 13.3%
12 10 8 6.8% 6 4.8% 4 2 0
1.0% Highly congested cities
Moderately congested cities
0.2%
Less congested cities
Source: CANTIQUE (2001).
But these modal shifts will only occur if reasonable alternatives to individual transport exist. Thus, the positive impacts of cost internalisation in passenger transport will be highest where road pricing is accompanied by investments in public transport and other measures that allow access to jobs, leisure and other everyday activities which are not dependent on motorised individual transport (MIT). Regarding the spatial structure of production activities, measures for increasing the costs of road transport operation will not usually have a major impact on location decisions in a given country, but they will have an impact on transport intense industries, especially the primary industry (Puwein, 2000). Transport-intensive sectors receive an incentive to change their location, in order to decrease derived transport demand. Downstream producers therefore have an incentive to be closer to upstream producers and the spatial range of production networks will diminish.
Subsidy reform Public spending has an important impact on settlement structures. Public subsidies therefore matter for transport activity (and for opportunities to promote decoupling).
4. Regulatory instruments CO2 emissions The largest and most cost effective potential CO2 abatement opportunities in the transport sector appear to lie in actions to reduce energy intensity (ECMT,
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Box 5.2. Overview of existing congestion pricing policies Singapore ● Total vehicles in city: 707 000. ● Charging area is much smaller than London and is divided into central business
districts, where scheme applies from 7.30 am to 7.00 pm, and expressways/outer ring roads, where scheme applies from 7.30 am to 9.30 am. ● Electronic Road Pricing system introduced in 1998, although a manual road
pricing system (with officers making visual checks at each entry point) was introduced in 1975. ● CashCard can be bought/topped up at retail outlets, banks, petrol stations and
automatic machines, fixed to vehicle windscreen. ● Different charges for different roads at different times automatically deducted
from Cash Card as vehicle passes under gantries. Benefits ● Immediate reduction of 24 700 cars during peak and rise of traffic speed by 22%. ● Total reduction of traffic in zone during charging period by 13% from 270 000
to 235 100. ● Reduced number of solo drivers. ● Vehicle trips shifted from peak to non-peak. ● ERP system reduced previous system’s bureaucracy.
Melbourne ● “CityLink” Toll road 22 kilometres long, linking three of Melbourne’s arterial
freeways, opened in 1999. ● Average weekday number of transactions 650 000, reaping AUD 187 million in
revenue. ● Pre-paid e-tags mounted on windscreen, read by overhead gantries; toll
statements mailed quarterly; accounts have to be topped up when balance falls below a certain level. ● Purely automatic vehicle identification technology (similar to London) – no
alternative of direct-payment toll booths. ● Motorists not equipped with e-tags who do not pay by following midday have
registration number recorded and sent to Traffic Camera Office along with digital image of the vehicle. ● Offenders fined a flat fee of $100.
Benefits ● Congestion significantly reduced in north and west Melbourne. ● Less pollution and safer conditions on local streets. ● 99.9% of vehicles captured electronically; 90% overall.
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Box 5.2. Overview of existing congestion pricing policies (cont.) Trondheim ● Charging area is approximately 4 km by 6 km. ● Fully automatic “toll ring” was introduced in 1991 and subsequently divided into
sectors. ● Charging period 6 am-6 pm, Monday to Friday. ● Unmanned electronic toll booths deduct fee from windscreen-mounted unit each
time vehicle enters toll zone or passes a toll point within the zone, rather than on daily basis. ● Limits imposed on number of charges that can be made so that people who live
close by the ring or who make very frequent crossings do not have huge bills. ● Occasional users can pay by automatic coin machine or by “swipecard” at
barriered lanes. ● Toll prices go up during peak rush hours and drivers are also charged a toll for
passing from one sector of the toll ring to another. ● Heavy Goods Vehicles pay a double toll.
Benefits ● Peak rush hour traffic immediately dropped by 10%. ● Revenues from the tolls have paid to improve roads and build bypasses to cut
traffic congestion. ● Income is also used to give commuters other options by upgrading public transit,
building bicycle paths and even providing 200 free bicycles for use downtown. ● Public opinion was initially 72% opposed, dropping to 48% two months after
launch and fell to 36% by 1996. San Diego Since 1996, a 13-km reversible high-occupant-vehicle (HOV) facility in the median of Interstate15 in San Diego has been opened to solo drivers who pay a toll using electronic transponders. Since March 1998, users of the Express Lanes have been charged a toll that varies dynamically with the level of congestion. Several variable message signs are posted in the areas prior to the entrance to the Express Lanes. These indicate the highest toll users should expect to be charged, with tolls ranging from 50 cents to $4 per one-way trip under regular conditions, and sometimes as high as $8. Depending on traffic in the Express Lanes, the fee may be lower than the posted schedule. Traffic flow is monitored in the Express Lanes to ensure that service on the HOV lanes is maintained at free-flow conditions (LOS C). Media response thus far has generally been positive. Some of the program’s revenues are used to fund a new express bus service.
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Table 5.3. Selected road pricing schemes Scheme
Coverage
Operational
Technology
Austria – Electronic Toll System All Austrian motorways Since 2004. “Ecopoints” and express roads HGVs > 3.5 tonnes.
5.8 Ghz. On board unit. 120 camera enforcement gantries; 420 tolling gantries; automatic license plate reading.
France – “Autoroute” Toll (Liber-t and TIS scheme) Spain – Autopista Tolls Portugal – Motorway Toll Italy – Autostrada Toll
Most major national motorways. Tolls all vehicles.
For many years; large growth in 1980s.
Fixed stop and start toll booths.
Germany – HGV Toll.
All federal motorways. HGVs > 3.5 tonnes.
From 2005.
GPS satellite system with OBU (7 400 miles).
Hungary – National Toll motorways.
Selected Hungarian motorway all vehicles.
Not before 2005.
Vignette or “badge” system.
Italy – Rome road charge
All central Rome roads. Since 2001. All vehicles.
OBU 5.8 Ghz transponder based; number plate recognition for enforcement; 27 gates.
Norway – Autopass
Variety of Norway’s principle motorways and roads.
Autopass technology since 2001.
Autopass contract and onboard unit required to obtain toll reduction Pass; works with all toll roads regardless of operational company.
Singapore – Urban Road pricing Central Singapore all First variable rate scheme in the roads (2.7 miles sq.). world All vehicles.
September 1998.
On-board units in vehicles with smart card; all vehicles; 44 gantries.
Sweden – Congestion charging in Stockholm
All Stockholm city centre roads. All vehicles.
Full scale experiment 2005-06; referendum 2006.
DSRC transponder technology.
Switzerland – Heavy Vehicles Fee Reduce alpine transit and shift to rail a key objective Swiss OBUs can be used in Austria, first example of interoperability
All public roads HGVs > 3.5 tonnes.
Since 2001.
On Board Unit linked to tachograph; DSRC 5.8 Ghz and GPS antennas. 100 equipped border stations. Automatic license plate reading.
UK – National Lorry Road User start Charge (LRUC) The DfT’s road user charge (LRUC) now due to begin in 2008
All UK roads HGVs > 3.5 tonnes.
Delayed 2006 starting in 2008.
GPS Satellite based system. Receiver to record vehicle’s position, tachograph to record mileage.
UK – Edinburgh
All city centre roads. All vehicles.
Residents vote in February 2005. Operational from 2006/07.
Automatic number plate; recognition cameras.
UK – Durham Congestion Charge roads
Specified city centre. All vehicles.
Since October 2002.
Payment on exit. Rising bollard control.
UK – 2003 Congestion Charge
All central London. London roads. All vehicles.
Camera enforced number plate recognition.
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2006). Significant CO2 savings might also be achieved by reducing carbon intensities, but most of these savings are only likely to occur at a higher cost. Policies promoting a less energy-intensive modal structure appear to offer only a very limited potential. These results are summarised in Table 5.4. Table 5.4. Summary of results from Dutch CO2 benchmarking study Instrument
Impact type
CO2 effect (%)
Cost-effectiveness High
CO2 emissions standards
Energy intensity – technical fuel efficiency
>5
Eco-driving
Energy intensity – on-road fuel efficiency
2-5
High
Speed limit enforcement
Energy intensity – on-road fuel efficiency
2-5
High
Energy intensity – technical and on-road fuel efficiency
<5
High
Freight logistics
Energy intensity – on-road fuel efficiency
<5
High
CO2 differentiation of vehicle taxation
Energy intensity – technical fuel efficiency
2-5
Varies
Fuel tax
Demand
>5
Medium
Carbon intensity
>5
Low
Modal shift – public
Modal shift
<2
Low
Modal shift – freight
Modal shift
<2
Medium
Tradable CO2 permits
All
<2
High
Road pricing Stimulation of biofuels
Source: COWI and ECN (2003).
Regulating NOx, VOC and PM10 emissions Emissions of these particular pollutants depend very heavily on engine technologies. Regulations aimed at these emissions will also promote technological change over the long-term, leading to increased dematerialisation of the economy, and eventually, to reduced transport demands.
Speed control and travel time sanctions for heavy duty vehicles This approach focuses on the implementation and enforcement of existing control mechanisms. Such controls increase the fairness of competition among modes, thereby increasing the chances that the more environmentally-friendly rail mode will benefit. For example, these kinds of controls have been estimated to increased road transport costs by up to 40% (University of Rome “La Sapienza” [1999]; Herry [2001]), engendering the same effects that higher road tolls or other cost measures would bring, but without the need to change existing regulations or laws.
Harmonisation of rail regulations at an international level As the Austrian case study demonstrated, harmonisation of rail regulations in Europe would be an important way of promoting the competitiveness of the rail sector (OECD, 2004a). The economy would benefit (due to clearer regulations);
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so would the environment (due to modal shifts toward rail). Even at the regional scale, this kind of harmonisation can be important (e.g. the emerging rail system of the Vienna-Bratislava Region).
5. Investment instruments Improvement of public transport infrastructure, services and operation The share of the public transport related to daily mobility is under 20%, and this share is falling (Herry and Sammer, 1999). The share of the long-distance traffic on public transport is even smaller. Some of the main reasons for this are: i) public transport is too slow; ii) it is not comfortable; and iii) it is too complicated (need to changing lines, information problems, etc.). Improving these three areas could help to increase the share of public transport. Both infrastructure and service quality improvement will be part of this process. Improving infrastructure without improving the quality of service (or vice versa) will not work. With improvements in the infrastructure and service standards of public transport, the economic sector profits by having a better infrastructure for its needed transport services. Due to better public transport conditions, potential users will partly reorganise their travelling behaviour and will use public transport instead of their cars.
Car-free tourism This measure will facilitate synergies between ecological and economic benefits. One aim is to improve the quality of life and vacations for residents and guests. Under the motto “Take a Vacation from Your Car”, travellers are invited to either arrive via public transport, or to park their vehicle for the duration of their stay. This kind of measure reconfigures transport services embedded in vacations, but it also affects the transport patterns of the inhabitants of tourism areas. Synergies can also be strengthened by linking this measure with improvements in public transport infrastructure and services (see above). This measure will have to be implemented on a regional level, in specific tourism areas.
Rail-road inter-modality and combined transport infrastructure The principal factors motivating decisions regarding the choice of freight transport modes are: i) the quality of the alternatives; ii) price performance; and iii) market-relevant quality characteristics. The most relevant quality characteristics of the market are: reliability, frequency of departure, duration of the trip; position of departure and arrival times; information available; and safety (IC, IPE, HERRY et al., 2001).
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Improvements in rail inter-modality (for example within and without the Alpine Region), as well as improvements in combined transport infrastructure (terminals, new loading technologies) provide important opportunities for future decoupling. These two measures are also strongly linked. The improvement of the combined transport infrastructure is an essential part of improvements in railroad inter-modality. Better infrastructure improves many of the abovementioned transport characteristics. The improvement of these characteristics for the combined transport leads to new transport decisions and (perhaps) to the reorganisation of transport activity. Stronger inter-modality also changes the competitive situation between the transport modes, and will ultimately promote more shifts from road to (more environmentally-friendly) rail, because rail’s overall competitiveness will now be more directly linked to the other modes. Given the strong economic links that exist among countries, achieving the environmental benefits associated with inter-modality will need action at the international level.
Interlinked freight logistics systems This measure can also directly influence transport organisation. It seeks to “hook up” transport needs in one sector with those in another. Unlinked logistical systems typically lie behind this lack of co-ordination. This measure will allow parts of the economy to improve their transport systems by optimising transport organisation. With such an approach, synergies are also possible with measures that improve service quality or infrastructure of individual modes. The economy benefits, as does the environment. Again, this measure will be best implemented at the international level, in order to extract the maximum potential from it.
Extension of rail infrastructure Extension and improvement of rail infrastructure is the basis for most of the above-mentioned approaches. Only when the rail infrastructure represents a viable economic alternative will significant shifts to this (more environmentallyfriendly) mode take place. For freight and passenger rail infrastructure improvement, internationally-co-ordinated efforts will likely be needed.
Road traffic management systems This measure could help to improve the organisation of transport (for both passengers and freight). An efficient traffic management system leads to a better use of the existing infrastructure. However, it is necessary to include all modes in this logic, and not just the road mode. A system that refers only to road without a linkage to the other modes does not contribute to an optimal use of the overall transport system.
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For the implementation of this measure, two elements need to exist. On one hand, all potential users of the transport system should have a viable way of receiving relevant information before starting their trips. This part of the management system should probably be implemented at a national level (e.g. via radio or GSM-based information systems). On the other hand, the locations being managed should be those where traffic problems most often occur (urban areas, access to urban areas, Alps crossings).
6. Institutional arrangements Tele-working This approach is based on changes in the employment sector which can simultaneously lead to improvements in work-related mobility. In principle, substitution between transport and teleworking can promote dematerialisation in terms of reducing transport demand (and therefore, transport-related emissions). In addition, if teleworking induces a decrease of private car owners, this again means reduced material input for the production of cars and other transport equipments. Teleworking may also reduce congestion in cities, making the urban economy more efficient and cleaner. But there can also be complementary and perverse effects, such as an increase of the number of non-work trips taken. For example, time saved for commuting to work might now be used to take personal trips for other reasons. Mitomo and Jitsuzumi (1999) quantified the potential effects of teleworking to reduce peak hour congestion in the transit trains of Tokyo Metropolitan Area. They considered three different scenarios of telework adoption and assumed a number of hypotheses about telework frequency (0.8 times/week) and travel behaviour of telecommuters. They concluded that the number of Japanese telecommuters in 2020 would range from a conservative estimate of 9.4 million (14% of the total workforce) to an optimistic estimate of 18.4 million (28% of the total workforce). The main findings are summarised in Table 5.5. Table 5.5. Impact of telecommuting on mass transit congestion in Tokyo, 2010 Scenarios
Numbers of commuters in peak hours (riders/h)
Congestion level1
Congestion reduction effect
No telecommuting
2 425 000
261.6
Conservative
2 258 058
243.6
–18.0
Intermediate
2 202 907
237.6
–24.0
Optimistic
2 161 387
233.2
–28.4
1. Congestion level is defined as the number of commuters in peak hours divided by the transportation capacity. Source: Mitomo and Jitsuzumi (1999).
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These results suggest that teleworking could make a substantial contribution to relieving congestion problems in the transit trains of the Tokyo Metropolitan Area. (The figures represent a decline in congestion of between 18% and 28%). The study also evaluated the benefits of telecommuting in terms of congestion costs saved, using two different congestion disutility functions. Depending on the function and the scenario, these benefits were estimated at between 22.5 and 75.2 billion yen – equivalent to between 8% and 26% of household expenditures on public transportation. The authors also highlight that about two-thirds of these benefits would accrue to non telecommuters and just one-third to telecommuters. They conclude that “… the size of telecommuting’s positive external effects seems to be large enough to justify a degree of policy support for this new practice”.
Integration of environmentally-oriented transport and land use planning Transport distances and modes depend on the spatial organisation of the economy. Spatial policies, such as land use planning, therefore influence transport variables much more than transport policy itself does. Integrating land use policy with decoupling objectives in the transport sector is therefore important. Changes in the regulation of land-use will likely be needed to create mixed-used areas with high density and polycentrism. The positive effect can be strengthened if additional measures are taken to increase the attractiveness of urban areas, such as measures to decrease noise pollution, to improve cycling and pedestrian infrastructure.
7. Educational instruments Mobility management in enterprises The case study of Italy showed that the management of staff travel choices at the company level can offer opportunities to promote more environmentallyfriendly mobility, and to use the potential of transport rationalisation within the enterprise to achieve environmental goals (OECD, 2004b). This will involve not only shifts from motorised individual transport to more environmentally-friendly transport modes, but also real reductions of motorised individual transport. If a general increase in pedestrian, bicycle and public transport is implemented, the anticipated transport impacts can be as much as: i) a decrease in the share of those driving to work of more than 15%; ii) an increase of the share of those using public transport to go to work; and iii) an increase in the share of those cycling to work (Herry, Schuster and Thaler, 2000). The anticipated environmental effects of these measures will be an increase in the efficiency of transport-related energy consumption, protection of the climate (reduction of CO 2 emissions), and improvements in air quality
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(reduction of transport-related air pollution). With the expected decreases in motorised passenger transport, a clear reduction of CO2 by more than 30% can be reached, without reducing economic growth (Herry and Schuster, 2002). The anticipated economic impacts of the mobility management approach could include cost savings – a more energy efficient fleet and rationalisation of the transport sector; no unnecessary purchase of land for parking purposes, and better use of existing parking space; and an increase in the productivity of (less stressed) employees. The anticipated social benefits would include health protection (reduction of transport-related PM emissions and better compliance with noise protection regulations); and better traffic safety to the workplace.
8. Overview of “soft” measures Several studies have reviewed national and international evidence in order to make estimates of the overall effect of a combination of soft measures on traffic levels in UK conditions. The main findings of these studies are summarised in Table 5.6. A substantial part of the observed differences between the Halcrow results and those from the other studies relates to assumptions about intensity of implementation (not from different assessments of the inherent potential for change). Table 5.6 suggests that soft measures can be responsible for at least 4% improvements in traffic demand (and perhaps as high as 30% in specific urban locations). Halcrow suggests potential national-level improvements in the range of 4-5%. The other studies suggest a central range of –10 to –15% for “national” impacts, and –15 to –20% for “best local” impacts (Goodwin et al., 2004). “Soft” measures clearly have significant potential to promote the decoupling of environmental impacts of transport from economic growth.
9. Synergies Many of the measures discussed above show some synergy effects. One example is environmentally related tax reform, which internalises the environmental effects of transport activity, and simultaneously promotes dematerialisation of the economy as whole. These kinds of synergies should be exploited to the maximum extent feasible.
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Study
Factors included
Maximum combined potential of all included measures
Maximum potential of work and school travel plans only
National
Best local
National
Best local
NERA et al. (1997)
All telecommunications (telecommuting, teleshopping, teleconferencing, freight operations).
–6% to –16%
Not estimated
Not estimated
Not estimated
Atkins (1997)
Workplace and school travel plans, improvement to public transport and walking facilities, public transport fares, parking restraint, reallocation of road capacity, road user charging, highway and traffic control improvements, land use policies.
–15% to –20%
–25% to –32%
–4%
–9%
Halcrow (2001, 2002)
Workplace and school travel plans, visitor travel plans, bus quality partnerships, improved public transport interchange, general public transport marketing, public transport fares and ticketing, individualised marketing, car clubs, teleworking, video-conferencing, home shopping, measures to increase walking and cycling, land-use policies, local sourcing of goods, oil supplies and new automobile technology.
–5%
Not estimated
–1%
Not estimated
SWTAR (2002)
Workplace and school travel plans, bus quality partnerships, public transport interchange, public transport marketing and ticketing, public transport information, car clubs, teleworking, videoconferencing, Internet shopping, cycling, promotion of walking, land use effects.
–15% to –20%
Not estimated
–3.7%
Not estimated
Transport for Quality of Life (2003)
Workplace and school travel plans, bus quality partnerships, local rail improvements, individual marketing, car clubs, teleworking, promotion of walking and cycling.
–4% to –9%
–12% to –26%
–1% to –3%
–3% to –8%
Steer Davies Gleave (2003)
Workplace and school travel plans, bus quality partnerships. (Visitor travel plans, rail improvements, parking restraint considered but impacts not estimated. Individual travel planning estimated but largely discounted to avoid double counting.)
Not estimated
–15% to –19%
Not estimated
–12% to –15%
–8% to –17%
London-wide
–2% to –4%
London-wide
Transport for London (2003) Workplace and school travel plans, individualised marketing, car clubs, car sharing, teleworking, videoconferencing, e-shopping, promoting cycling, promoting walking, travel awareness campaigns.
POLICY INSTRUMENTS FOR DECOUPLING
Table 5.6. Main results of studies on the impact of “soft” measures on transport demand
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Chapter 6
National Case Studies
This chapter presents the main findings of the national case studies on decoupling from Austria, Germany, Italy, Japan, Spain, and Sweden. In addition to these studies, two further specific approaches to decoupling are also analysed – from Switzerland (on the Swiss Heavy Goods Vehicle Fee) and from the UK (on congestion charging in London).
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1. Background Seven countries participated in Phase 2 of this project – a phase that was aimed at better understanding efforts in OECD member countries to promote decoupling of the environmental impacts of transport from economic growth. This section of the report presents the main findings of these national case studies. In additional to these studies, two further specific approaches to decoupling are also described below – from Switzerland (on the Swiss Heavy Goods Vehicle Fee) and from the UK (on congestion charging in London). The case studies from Austria and Switzerland mainly addressed the impacts on transport of dematerialisation; changes in spatial structure of production and consumption; and transport organisation. The Japanese case study focussed on both national conditions and a regional modelling study of the Tokyo Metropolitan Area. The Italian case emphasised a corporate mobility management plan which accentuated the need for a stronger federal role in the management process, as well as a stronger framework for protecting air quality. The case study of Spain analysed the impact of the agriculture sector on transport demand. The Swedish case emphasised the relation between freight transport and economic growth. The German case study analysed the relevant logistical factors influencing energy efficiency in road freight transport, focussing on the potential for additional CO2 abatement. The case studies were all developed using the same broad Terms of Reference. These Terms of Reference contained the following main elements: ●
Transport activity and the economic importance of the transport sector.
●
Main environmental impacts associated with the transport sector.
●
Main drivers of transport growth.
●
Instruments and measures proposed for decoupling.
●
Effects of instruments and measures proposed.
2. Austria The Austrian case study pointed out the need to look simultaneously toward improvements in both public transport and non-motorised individual transport options (OECD, 2004a). The study highlighted that a key requirement for achieving decoupling is the coverage of both maintenance costs and the external costs of road transport by road users themselves. It concluded that, in addition to
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measures currently in place, a road pricing scheme for passenger transport, as well as some expansion of the existing road pricing system for trucks, could achieve this goal in an efficient manner. Road pricing was favoured because it leads to behavioural changes, including changes in transport modes and changes in journey destinations. The case study further suggested that, if current levels of taxes on road transport (fuel tax, vehicle tax, etc.) remain unchanged, the costs of car transport in Austria will on average have to increase by approximately 0.10 €/ vehicle-km to cover all external costs attributable to car transport (including external accident costs). According to one scenario for car road pricing, introducing a toll of 0.10 € per vehicle-km on the entire road network would lead to an estimated reduction in motorised individual transport (in terms of vehicle-km) of 14%. The Austrian case study also emphasised that, in order for modal shifts to take place, adequate alternatives to road transport need to be available. A preliminary step in introducing a road pricing scheme would therefore be to improve public and non-motorised individual options. The case study recommended implementing in particular those measures with low investment costs and short implementation periods. For example, early focus could be placed on improving rail service quality. It noted, however, that even though these policies are dependent on national political decisions, improvements in rail transport quality can only be put into full effect if they are implemented internationally. The case study also highlighted the importance of recycling some of the revenue raised to fund further improvements in public and non-motorised individual transport, as a way of gaining public acceptance for the pricing programme. The importance of raising public awareness about transportrelated environmental and health impacts, and the net benefits created for local production and urban living were also noted. In addition to road-pricing reforms, several other measures recommended by the Austrian case study focus on structural changes that contribute to decoupling (e.g. integration of environmental considerations into spatial planning).
3. Germany The German case study indicated that the major drivers for transport growth in that country are globalisation in general, and integration with Eastern European markets in particular (OECD, 2004e). This growth has mainly been reflected in the road sector; since the rail sector does not have the same level of competitiveness as road transport does. The study not only underlined
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the importance of reducing fuel use by increasing taxes on fuel, but also highlighted the need to continue to improve engine and truck design, freight load factors, and telematics. Some of the specific instruments recommended by the case study which have the potential to curb the negative externalities associated with freight transport are: ●
Soft measures, such as: information campaigns on more efficient technologies (e.g. telematics systems that increase the potential loads of trucks while reducing emissions per tonne-kilometre. These campaigns should emphasize the fact that return on investments can be achieved after a short period (few weeks) of implementing the measures. Transport agencies, energy agencies, environmental agencies and city authorities should all help spread information about these technologies to decision-makers in the transport industry.
●
To efficiently promote new technologies that have a high potential to save fuel, independent technology testing and evaluation of performance under real road traffic conditions are required. The results should show the net energy efficiency gains from each type of technology.
●
Free training programmes in eco-efficient driving techniques should be made available to the purchasers of new trucks.
●
Research and development should be encouraged for new fuel technologies for trucks (e.g. biodiesel), but also for onboard telematics, light vehicle design, and improved motor performance.
●
Modal change incentives should be provided to improve the competitiveness, reliability and speed of rail freight and rail-road intermodal options.
●
Fuel taxes and other fiscal instruments.
4. Italy The Italian case study examined the potential effects of implementing a mobility management plan which followed the Ministerial Decree of the 27 March 1998 on Sustainable Mobility in Urban Areas (OECD, 2004b). This plan was adopted by private and public organisations with more than 300 employers in each local unit, and by firms with more than 800 employees (globally) located in cities with more than 150 000 inhabitants. The mobility plan aims to reduce greenhouse gases through technical improvements and by renewing vehicle fleets. It also seeks to develop telematic systems for improving traffic management, and for transferring transport from private to public transport modes. The report also analysed opportunities to develop logistics for more efficient freight traffic management and toll charges in the use of transport infrastructure.
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The case study showed that the mobility plan can generate significant effects in terms of saving vehicle-kms. It also indicated a potential decrease of 24% on the basis of the willingness stated by transport users to take public transport services and other innovative solutions proposed by corporate mobility managers. Specific policy interventions recommended in the study included: 1) increasing co-ordination between mobility support structures; 2) favouring contacts among Corporate Mobility Managers; 3) planning specific professional frameworks for Corporate Mobility Managers; 4) promoting the non-taxation of expenses incurred by companies for employees’ mobility; 5) implementation of sanctions for ignoring mobility-enhancement measures; 6) raising the awareness of the workers vis-à-vis the positive impacts of new measures; and 7) diffusing a “culture” of sustainable mobility.
5. Japan The Japanese study demonstrated that policies implemented at the national level, including policies based on fuel efficiency regulation or tax incentives to encourage the use of higher fuel mileage automobiles, are not strong enough to meet the Kyoto Protocol targets related to greenhouse gas abatement (OECD, 2004c). These policies broadly encourage the introduction of high efficient automobiles, but are not strong enough to compensate the negative impacts of the constant increase of car use. Additional measures will therefore be needed. For example: i) promoting the use of public transport (i.e. provision of public transport; improvements in the convenience of public transport and commuter transport management); and ii) promoting efficient freight transport (i.e. modal shift, streamlining car freight transport). Rail construction was regarded as the most efficient regional policy for decoupling. Rail contributes to sharply reducing CO 2 emissions, while maintaining or increasing economic growth. The study also suggested that road construction will engender the most economic benefits of all the scenarios considered, but it also lead to increased CO2 emissions.
6. Spain The Spanish case study examined the environmental impacts of changing transport patterns associated with citrus fruit exports from the Valencia Region to European countries (OECD, 2005b). This region exports 60% of its products and almost 100% by road transport when the destination is a European country. Two scenarios were projected for both the medium- and long-terms (2005-10) – the first was a “current trends” scenario (Business as Usual – BAU); the second was a “more sustainable” scenario.
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One important assumption of the “sustainable” scenario was an increase in the capacity of alternative modes to road transport – mainly of rail and short-haul sea transport. The modal split was therefore able to shift to 80% road, 15% rail, and almost 5% short-haul sea transport in 2010. Under the BAU scenario, the same modal split which prevailed in 2000 and 2005 were used. Compared to 1995 levels, under the “sustainable” scenario, the reduction of NOx emissions was 58%, while under the BAU scenario; the reduction was less than 45%. Under the BAU scenario, levels of CO2 emissions increase by more than 40% between 1995 and 2020 (although the increase in total tonnes exported was below 31%). In the “sustainable” scenario, there was a 17% reduction in CO2 emissions.
7. Sweden The main conclusion of the Swedish case study was that moving towards sustainable transport will require internalising the external costs and making polluter pay (OECD, 2004e). The study also emphasised that taxation levels need to be very high compared to current levels, in order to influence long-term structural demand for transport. Higher taxation, better logistics management, and more competitive alternative modes (rail and sea) were all seen to be needed in order to increase the efficiency of the transport system. However, as in most countries, this will not be enough to curb the current growth of transport demand, or its related negative impacts on the environment. In the particular model used in the case study, internalisation of external costs was modelled only to cause a shift in modes – not to alter the total demand for freight transport. The main results of the analysis included a decrease of 3% in road transport; an increase of 5% in sea transport and a decrease of 11% in railway use. The study also concluded that internalisation of external costs will have a positive impact on the efficiency of the transport system (e.g. less traffic for basically the same amount of mobility). Applying an assumed elasticity of –0.8 for passenger transport and –0.2 for all other transport (including freight), the study found that a tax of 2.70 SEK/kg CO2 (0.3 euro/kg CO2) would be needed to reach the current CO2 targets for Sweden (–4% compared to 1990 level). McKinnon (2002) estimated that an increase in excess of 100% would be needed; Strutinsky (1995) suggested that a 5-fold increase would be needed. These estimates give an indication of what would be needed in order to curb freight growth in the longer run when other potential efficiency gains have already been harvested.
8. Heavy goods vehicle fee – Switzerland Discussions toward the Swiss distance-related fee for heavy goods vehicles started in the 1970s. In 1985, a flat fee for heavy goods vehicles was introduced.
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The main characteristics of this fee were very similar to the Eurovignette, which was introduced later in several member countries of the EU. Switzerland then wanted to conclude bilateral treaties with the EU aimed at harmonising their Heavy Goods Fee with the Eurovignette. One of the conditions for achieving this harmonisation was the need to raise the Swiss weight limit for heavy goods vehicles from 28 to 40 tonnes. Concerned about the possibility that Swiss roads would be used by too many 40-tonne trucks if the Heavy Goods Fee went in this direction, the government refused to make such a change. The possibility of changing from a flat fee with a low rate to a distance-related fee with a much higher rate showed a way out of this impasse. The following factors were proved to be essential in order for setting up the decisive step on the way to gaining acceptance for the new fee (OECD, 2005a): ●
Implementation as part of a broader policy: The fee was (and still is) an essential part of a wider policy to transfer goods from road to rail. This policy has been accepted by Swiss voters in several referenda.
●
Use of the revenue: The revenue is reinvested in the transport sector, mainly for projects in public transport, thus further supporting the policy of transferring goods from road to rail.
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Practicality of the technical solution: The technical solution is simple, reliable and suited to solving the problems resulting from the political guidelines.
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Polluter-pays principle: The calculation of the fee takes the external costs of heavy goods road transport into account. This seems to have been wellaccepted by the population.
The fee was introduced in 2001, at a rate of 1.0 Ct/tkm (medium environmental class). In parallel, the weight limit was raised from 28 to 34 tonnes. In 2005, the rate was increased to 1.6 ct/tkm and the weight limit was raised to 40 tonnes. The rate shall be increased with about another 10% by 1 January 2008. The fee depends on three factors: ●
the distance driven on the Swiss road network (all roads);
●
the maximum permitted weight of vehicle and trailer; and
●
the emissions of the vehicle (there are three emission classes).
The main effect of the new regime with the new fee on the one hand and a higher weight limit on the other was that heavy goods transport on the road has become more efficient. This increased efficiency was mainly due to the following developments: ●
Strong renovation of the truck fleet: In order to save fees, haulers bought cleaner vehicles belonging to the cheapest emission category and adjusted the size of their vehicles to the actual needs of the market. Previously, oversized vehicles were more common.
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More concentration in the hauler industry: Due to better capacities, bigger companies are now able to operate their lorries in a more efficient way. This allows truckers to avoid empty trips.
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Fewer heavy goods vehicles on the road: With the introduction of the new regime, the annual rate of increases in vehicle-kms (about 7%) fell to about 4% in 2001 and 3% in 2002. In 2003, the traffic volume of lorries remained stable. Although it is clear that an economic downturn also contributed to this change, the new fee has obviously had some effect.
No important shift of goods transport from road to rail has been noticed so far. This could be because the competitive advantage gained by rail due to the introduction of the fee was more-or-less balanced out by productivity gains in the road sector that resulted from the higher weight limit. A transfer of freight from road to rail will probably not be possible without additional efforts aimed specifically at the rail sector.
9. Congestion charging – London The basic principle of the London congestion charge is that consumers should pay for the costs they impose as an incentive to use the road network more efficiently (Litman, 2005). If road space is not priced, traffic volumes will increase until congestion limits further growth. Central London is particularly suitable for congestion pricing because of its limited road capacity (the street network in the core area has hardly expanded since the Middle Ages) and heavy travel demand results in severe congestion. London also has relatively good travel alternatives, including walking, taxi, bus, and subway services. Only about 10% of peak-period trips are made by the private automobile. For decades, transport planners have recommended congestion pricing in central London. Since 17 February 2003, motorists driving in central London on weekdays between 7:00 am and 6:30 pm were required to pay £5 (increased to £8 in July 2005). There are some exemptions, including motorcycles, licensed taxis, vehicles used by disabled people, some alternative fuel vehicles, buses and emergency vehicles. Area residents receive a 90% discount for their vehicles. The charging area is indicated by roadside signs and symbols painted on the roadway. Payments can be made at various locations or on the Internet. A network of video cameras records the license plate numbers of vehicles provides the monitoring function. Approximately 110 000 motorists a day pay the charge (98 000 individual drivers and 12 000 fleet vehicles). A growing number of these users now pay by mobile phone text message. This system has been criticized on various grounds (Litman, 2005): ●
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The fee is not based on how many miles a vehicle is driven within the charging area.
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The fee is not time-variable (i.e. it is not higher during the most congested period of the day).
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The fee does not vary by location; it would be more efficient to have higher rates on more congested roads.
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The system has relatively high overhead costs.
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Transit services (particularly the Tube) are crowded and unreliable, although this is changing as systems are upgraded.
Transport for London and various academic organisations established a five-year monitoring program to evaluate the transport, economic, social and environmental impacts of the congestion charging policy (www.tfl.gov.uk). Their results suggest that: ●
Most people who change their travel patterns due to the charge transfer to public transport, particularly bus. Some motorists who would otherwise drive through Central London during peak periods shift their route, travel time or destination. Others shift mode to taxis, motorcycles, pedal cycles, or to walking.
●
This has significantly increased traffic speeds within the zone. Average traffic speed during charging days (including time stopped at intersections) increased 37%, from 8 miles-per-hour (13 km/hr) prior to the charge up to 11 miles-per-hour (17 km/hr) after pricing was introduced. Peak period congestion delays declined by about 30%, and bus congestion delays declined by 50%. Bus ridership increased 14% and subway ridership about 1%. The latest (third-year) annual report also indicates that these improvements are continuing (www.tfl.gov.uk).
●
Taxi travel costs declined significantly (by 20-40%), due to reduced delays. Vehicles can cover more miles per hour, so taxi and bus service productivity (riders per day) and efficiency (cost per passenger-mile) have increased substantially.
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Conclusion: Towards a Decoupling Strategy
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1. Overview of available instruments Table 7.1 presents a summary of the main results of the analysis of instruments that were found, throughout the course of this project, to be the most promising approaches for decoupling the environmental impacts of transport from economic growth. It is partially derived from inputs received during several expert meetings, held in connection with the project since 2002 (2-3 workshops per year). Several smaller working group meetings were also held in connection with Phase 2 of the project, notably in Austria and Japan. The criteria deemed to be most relevant to the choice of instruments were: i) level of responsibility for implementation; ii) net investment costs; iii) period of implementation; and iv) level of public acceptance/resistance. Table 7.1 also presents an overall (normative) evaluation of each approach.
Level of responsibility for implementation A first important step is to identify who should be responsible for implementing the various measures. In that context, different types of responsibility can be defined: ●
responsibility for frameworks; and
establishing
the
incentive
●
responsibility for the implementation itself.
and
implementation
Net investment costs The required scale of investment costs necessary for implementing each measure should also be considered. Cost-benefit and revenue-raising considerations are obviously important here.
Period of implementation Because some of the measures can (or have to) be introduced stepwise, the decoupling strategy should also consider the time dimension. For example, the time needed for implementation may depend on the construction period (for infrastructure), or for subsequent installation of enforcement mechanisms.
Level of acceptance/resistance It is also important to reflect on the likely acceptability of the various decoupling measures. Acceptability will probably differ according to the type of
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Level of responsibility
Net investment costs
Full coverage of infrastructure maintenance costs
Period of implementation
Level of acceptance/resistance
Overall evaluation
– Long period: more than 10 years.
– If coverage by toll system for the whole road network: medium political acceptance.
– Coverage by other measures (fuel tax, etc.) already given for the road sector.
– International or EU (for Directives). – National (for road pricing). – Municipalities (for city tolls).
– Higher benefits than costs.
– Long period and stepwise. – First, a toll for HV road freight on motorways. – Then a toll for passenger transport. – In parallel, city tolls can be implemented.
– Political: very low. – NGOs: high. – General public: low for passenger medium for freight. – Business sector: low.
– High decoupling potential. – High political resistance. – Awareness should be developed within society. – Net financial benefit can result.
Environmentallyrelated tax reform
– National. – Harmonised system within EU would increase benefits.
– Revenue neutral.
– Start at once. – Realisation: step-by-step. – Change should be a running procedure over a long period.
– Political: medium. – NGOs: high. – General public: non opinion because of lack of information. – Business: medium.
– High decoupling potential. – Not as high resistance than other financial measures. – A step-by-step approach is recommended.
Improvement and extension of rail-road intermodality
– EU for Europe. – National states for specific programmes.
– From low (“soft” measures) to medium (telematics applications)
– Soft measures: within 5 years. – Expensive measures: long period (up to 10 years).
– Political: high. – NGOs: medium. – Business: high.
– Double benefits: improvement in road and rail. – Possible to reach decoupling in the short/medium-terms without strong efforts.
Extension of rail infrastructure
– National. – Within EU: EU also has responsabilty.
– High investment costs. – From the decision to realisation: – Political: medium, due to the high – Decoupling effect is not high – Benefits possible after at least 5 years minimum, but costs and the long period compared to “soft” measures. long period (and with high more likely to exceed 10 years. of implementation. – The need for investment user charges). – NGOs: medium, due to the new is high. infrastructure. – Necessity to overcome high – General public: medium. levels of resistance. – Business sector: medium.
Improvement of rail service quality
– National. – Efficient if improvements are made in the whole region.
– Low to medium.
– Vary from short-term (less than – Political: high, due to relatively low – Good overall: not too high 5 years) to medium-term costs. investment costs and high (up to 10 years). – NGOs: high, because acceptance. of the improvement of rail without new infrastructure. – Business sector: high.
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Road pricing
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Table 7.1. Instruments for decoupling: overview
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Improvement – Regions of public transport and municipalities. – National; for rail part infrastructure of public transport.
Net investment costs
Period of implementation
Level of acceptance/resistance
Overall evaluation
– High investment costs.
– At least 5 years, likely up to 10 years.
– Political: medium, due to the high – Higher efforts than those costs and the long period for “soft” measures are of implementation. needed. – NGOs: medium-to- high for – Will generate similar improvements in public transport; decoupling effects as those low for new infrastructure. of “soft” measures. – General public: high. – Business sector: medium.
Improvement of combined transport infrastructure
– Long period: around 10 years. – High investment costs. – National. – Return of investment only – Private operators possible over long period, or regions in few cases. and with high user – Within EU; EU should lead. charges.
– Political: medium due to high costs. – NGOs medium. – General public: neutral. – Business sector: high.
– Similar to the evaluation of extension of rail infrastructure: High investment costs. High resistance compared with “soft” measures.
Improvement of public transport: service and operation
– Regions – Depends on the specific and municipalities. measure: – National (for the rail part Low for some, e.g. new of public transport). intelligent technologies. Medium for others, e.g. dense intervals leading to higher operation costs.
– Short time for most of the measures.
– – – –
Political: high. NGOs: high. General public. Business sector: medium.
– Similar to improvement of rail quality for freight transport. – High decoupling potential for passenger transport (with low effort).
Promotion of new forms of passenger transport
– Regions and municipalities.
– Depending on the density – Short time for most of the measures. of supplier: low to medium.
– – – – –
Political: high. NGOs high. General public: high. General public: neutral. Business: neutral
– Similar to improvement of rail quality for freight transport. – High decoupling potential for passenger transport (with low effort).
Harmonisation of rail regulations in Europe
– National: responsible for implementation. – Within Europe: EU should lead.
– Cost of harmonisation: low. – If the approach includes the whole rail system (electricity, signalling, engines, etc.), the investment costs are medium to high.
– Political: medium. – General NGOs: high. – NGOs with national tendencies: low. – General public: neutral because of lack of broad information. – Business sector: high.
– Up to 10 years.
– High investment costs and long time period needed for implementation. – But also high acceptance. – Harmonisation strengthens the effects of “soft” measures for improving rail.
CONCLUSION: TOWARDS A DECOUPLING STRATEGY
Level of responsibility
7.
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group whose opinion is being asked. Politicians, bureaucrats, non-governmental organisations, the business community, and the general public are likely to be involved in this type of reflection.
Overall evaluation And finally, there is a need to consider all variables at once, when deciding on the particular way forward toward decoupling. For example, if political resistance is high, implementation within a short time frame is not likely to be feasible – so there are clearly synergies and tradeoffs involved.
2. Conclusions and recommendations for policy action Some level of decoupling is already happening in the transport sector of many OECD countries for some emissions (e.g. SO2, NOx and VOC), but not for other pollutants (e.g. CO2) or for some modes (e.g. rail) but not for others (e.g. road transport, aviation). Further opportunities for decoupling environmental impacts of transport from economic growth would also be achievable by more efficient policies aimed at internalising the full social costs of transport activities into decisions about those activities. This implies that users should pay the full costs of transport infrastructure investments (including the maintenance costs associated with these facilities), as well as the value of any externalities associated with them. For efficiency reasons, these internalisation policies should lean heavily on economic instruments (taxes, charges, fees). This is particularly true in the road transport sector, where road pricing measures for freight and passenger transport should be actively considered. Road pricing can lead to changes in transport modes, in journey destinations, and in economic location, all of which can contribute to decoupling. However, other approaches will also be appropriate in most circumstances. Regulations and “soft” measures, such as workplace and school travel planning, parking restraints, reallocation of road capacity, measures to increase walking or cycling, education, and speed or travel time controls, also have important roles to play. Given the complexity of the transport management problem, it is the efficiency and effectiveness of the entire “policy mix” that will determine the overall benefits of the policy approach that is eventually adopted. Broadly, it is likely that this package of instruments should aim to shift transport activity from road transport, and toward more environmentally sustainable forms, such as rail. Dematerialisation and further reorganisation of the technologies underlying the transport sector can also be expected to contribute to future decoupling efforts. Earlier sections of this report have also shown that efforts to decouple the environmental effects of transport activities from economic growth will be very
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Box 7.1. Decoupling in Eastern Europe Many previous studies have examined the environmental situation of the transport sector (including opportunities for decoupling) in the EU accession countries (HERRY/INFRAS, 2002). Broadly, these studies indicate that: ● Energy consumption by transport, and associated emissions of greenhouse
gases, are increasing rapidly, mainly due the growth in road transport. ● The
amount of land needed to support transport infrastructure
investments is increasing. ● The number of privately-owned cars in Central and Eastern Europe is
expected to grow significantly in the coming years. ● The external costs of transport per unit of GDP in the new EU member
states are higher than those in Western Europe, and will probably speed up in the near future. To meet these challenges, the following steps have been recommended: ● Explicitly
analyse the environmental externalities associated with
transport in these countries. ● Implement EU emission standards as quickly as possible, in order to
reduce road transport-relate air pollution. ● Revitalise the rail stock and upgrade public transport. ● Make wider use of environmentally-related tax reforms, mainly to help
restructure energy consumption, which should also have positive “rebound” effects on the transport sector. ● Undertake spatial planning initiatives, especially with neighbouring
countries, aimed at improving traffic flows.
specific to the particular circumstances facing individual policy situations. There is, in effect, no “silver bullet” for achieving decoupling. Approaches that suit one country will therefore not necessarily be appropriate for another country. Measures involving low investment costs and short implementation periods (e.g. improving rail service quality or the overall accessibility of rail and public transport) should be promoted in the early stages of any decoupling strategy. These measures will quickly reduce environmental pressure without involving excessive economic cost. The existing (limited) level of public acceptance of pricing measures for road transport could also be improved by offering better alternatives in other modes. Road pricing measures should also be an important early element of the decoupling strategy. Full cost recovery (subsidy reform), especially in the infrastructure area will be fundamental here. So will congestion pricing,
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especially in towns. The more intensively road transport pricing measures are implemented, the better the incentives for the rail and public transport options will be. If necessary to achieve public support for road pricing policies, it may also be appropriate to recycle some of the revenues raised back to affected parts of the economy or to promote new investments in environmentally sustainable transport modes (e.g. public transport). Where this is so, the recycling should be done in such a way as to minimise any distortion of the underlying incentives associated with the original road pricing scheme. It should also be done as transparently as possible, and actively seek to avoid distorting economic competition. Problem awareness is another essential part of gaining public acceptance of measures that lead to increases in road transport costs. Therefore, it is necessary to raise public awareness not only with respect to transport-related environmental and health impacts, but also in terms of the advantages created for local products and urban living. Infrastructure investment policies have the lowest priority from a decoupling perspective. These measures are likely to require much more effort than other approaches for achieving the same level of decoupling. Moreover, only at the stage where pricing measures in the road sector reach a relatively high level are new rail and public transport infrastructure investments likely to be appropriate. Implementation of all of the above-mentioned measures is most dependent on decisions made at the national level. However, improvements in rail freight transport are only likely to be possible in the context of international co-operation, especially in Europe. This is likely the case, for example, of both combined transport infrastructure and the harmonisation of rail regulations.
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Glossary Accident rate: Describes the probability of an accident per 1 000 vehicle kilometres. Average costs: Total costs in a period, divided by the quantity (output) produced/consumed in that period. Long term average costs also include a share of fixed costs (e.g. costs associated with expansion of existing infrastructure). Cost-effectiveness: Seeks to minimise the costs of achieving a given (e.g. environmental) objective/target. This principle is a “second-best” efficiency criterion, often used when a full cost-benefit analysis is not feasible. CO2: Carbon dioxide is a major greenhouse gas (i.e. it contributes to climate change). Decibel: (dB(A)) Decibel (dB) is a measure for the intensity of sound energy. According to the characteristics of human ears, the relationship between sound energy and dB is logarithmic. Several filters have been defined to achieve a better adaptation of dB measurements and the loudness impression of human beings. Efficiency: A discussion criterion often used for the allocation of scarce resources. An additional unit of these resources should only be used where marginal social cost of that usage is less than its marginal social benefit. Elasticity: Proportional change in a dependent variable (e.g. transport demand) in response to a price change (price elasticity); or reaction in total demand after a change in income (income elasticity). Externality (external cost): An external cost, also known as an externality, arises when the social or economic activities of one group of persons have an impact on another group; and when that impact is not fully accounted or compensated for by the first group. They are economic costs not normally taken into account in markets and in the decisions made by market players. (Full) fuel cycle: Complete fuel cycle; comprising discovery, depletion (mining), processing, transport, use and disposal of particular fuels.
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GLOSSARY
GDP (Gross Domestic Product): GDP is the sum of the value of all goods and services produced within a country in a given year. HC/VOC (Hydrocarbons/Volatile Organic Compounds): Contribute to ozone formation. Some (e.g. benzene, butadiene and benzo-apyrene) have been found to have impacts on human health. HDV (Heavy Duty Vehicles) and HGV (Heavy Goods Vehicle): Road tractors and road trucks above 3.5 tonnes gross weight. Internalisation: Incorporation of an externality into the market decisionmaking process through pricing or regulatory intervention. LDV (Light Duty Vehicles): Vans up to 3.5 tonnes gross weight. Life-cycle based approach: One in which up- and downstream processes of transport services are included (i.e. vehicle production and disposal, fuel cycles of the electricity production, etc.). Marginal costs: Costs related to a unitary increment in demand (e.g. an extra vehicle-kilometre driven). Long-term marginal costs include the capacity expansions needed to service increased traffic demands. MC: Motorcycle. NOx: Nitrogen oxides (e.g. formed primarily by fuel combustion) and contribute to the formation of acid rain. They also combine with hydrocarbons in the presence of sunlight to form ozone. Opportunity costs: Costs which arise when a project restricts alternative uses of a scarce resource (e.g. land-use for infrastructure prevents recreational use). The size of the opportunity cost is the value of the resource in its most productive alternative use. pkm: Passenger kilometers. PM: Particulate matter. Fine particulates (e.g. PM10, with a diameter of less than 10 μm) can contribute to chronic and acute respiratory disease and premature mortality, as they are small enough to be inhaled into the lungs. Larger particles decrease visibility and increase fouling. Productivity: Output divided by the inputs needed to produce that output often in value terms. Public good: Often used to refer to goods that are non-excludable as well as non-rival. This means it is not possible to exclude others from the good’s consumption (fresh air may be considered a public good as it is not generally possible to prevent people from breathing it. A public good is also non-rival. This means: consumption of the good by one individual does not reduce the amount of the good available for consumption by others.
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GLOSSARY
Purchasing power parity (PPP): An exchange rate that equalizes the purchasing power of different currencies in their home countries for a given basket of goods). These exchange rates are often used to compare the standard of living of two or more countries. The adjustments are meant to give a better picture than comparing gross domestic product (GDP) using market exchange rates. Shadow prices: The marginal opportunity cost of using a resource (i.e. the loss of benefits caused if this resource cannot be used for the next best purpose). Social costs: The sum of internal and external costs. SO2: Sulphur dioxide, which contributes to the formation of sulphate aerosols and is the primary pollutant in the formation of acid rain. It can also cause respiratory system damage in humans. tkm: Tonne kilometers. Traffic mode: Means of transport (road, rail, aviation, shipping, etc.). Traffic volume: Traffic activity (often expressed in terms of vehicle-kilometres, or in passenger/tonne kilometers). Value of statistical life (VSL): A measure of the social welfare loss attributed to a human fatality. Computed on the basis of average willingness of people to pay for minor changes in risk of mortality, aggregated across individuals. Variable costs: Full costs can be subdivided into fixed costs and variable costs. Variable costs are expenses that change in direct proportion to the activity of a business. Fixed costs remain constant with varying use of a transport system (e.g. capital costs for road and rail networks). vkm (vehicle-kilometre): One kilometre travelled by a single vehicle. Willingness to pay (WTP): The amount an individual is willing to pay to acquire some good or service or for that good or service. This value may be elicited from stated or revealed preference approaches.
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References ASCHAUER, D. (1989), “Is Public Expenditure Productive?”, Journal of Monetary Economics, 23. BAUM, H. and J. KURTE (2000), “Transport and Economic Development”, Paper presented at the ECMT Round Table 119, ECMT, Paris. BERECHMAN, J. (2001), “Transport Investment and Economic Development, is There a Link?”, Paper presented at the ECMT Round Table 119, ECMT, Paris. BOARNET, M. (1998), Understanding the Link between Economic Growth and Project Evaluation, Presented in Transportation Research Board Annual Conference, January 11-15, Washington. BRÖSSE, U. and R. SPIELBERG (1992), Industrielle Zulieferbeziehungen als ein Bestimmungsfaktor der Raumstruktur und der Regionalentwicklung. Unter besonderer Berücksichtigung aktueller Veränderungen der zwischenbetrieblichen Arbeitsteilung, Hannover. BRUECKNER, J.K. (2005), Transport Subsidies, System Choice, and Urban Sprawl. BTS (Bureau of Transportation Statistics) (2006), Transportation Statistics Annual Report, Washington. BTS (2004), Transportation Statistics Annual Report, Washington. BTS (2002), Commodity Flow Survey, Washington. BTS (1999), Transportation Statistics Annual Report, Washington. BMLFUW (Bundesministerium für Land-und Forstwirtschaft, Umwelt und Wasserwirtschaft) (2003), Environmental Balance of Transport. Austria 1950-2001, Data Handbook, Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft, Wien. BUTTON, K. (1993), Transport Economics, Second Edition, Edward Elgar. CANTIQUE, Concerted Action on non Technical Measures and their Impacts on Air Quality and Emissions, Funded by the EU within FP4 – Final report (ISIS, 2001). COWI and ECN (2003), International CO2 Policy Benchmark for the Road Transport Sector. CROWLEY, J. (1995), The Value Chain, Logistics and the Environment, COST 328 – Integrated Strategic Infrastructure Networks in Europe, Lausanne. DARGAY, J. and D. GATELY (1999), Income’s Effect on Car and Vehicle Ownership, World-wide: 1960-2015, Transportation Research, 1999. DARGAY, J. and D. GATELY (1997), Demand for Transportation Fuels: Imperfect Price-Reversibility?, Transportation Research B, 1997. DARGAY, J.M. and GOODWIN (1995), “Evaluation of Consumer Surplus with Dynamic Demand”, Journal of Transport Economics and Policy, Vol. 29, No. 2, May 1995, pp. 179-193.
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OECD PUBLICATIONS, 2, rue André-Pascal, 75775 PARIS CEDEX 16 PRINTED IN FRANCE (97 2006 12 1 P) ISBN 92-64-02712-2 – No. 55315 2006
DecouplingtheEnvironmentalImpacts ofTransportfromEconomicGrowth Economicgrowthrequiresanefficienttransportsystem,andtransportactivity continuestocauselargeadverseimpactsontheenvironment,humanhealthand theeconomy.Butisanegativeimpactoftransportontheenvironmentanecessary consequenceofeconomicgrowth?Thisvolumeoffersacomprehensivediscussion ofrecentresearchonthelinksbetweentransportdemandandeconomicgrowth.It providesanin-depthdiscussionofenvironmentalandeconomiceffectsofapackage ofinstrumentsfordecouplingenvironmentallyimpactsoftransportfromeconomic growth–andhowtoovercomeobstaclestotheirimplementation.
Thefulltextofthisbookisavailableonlineviatheselinks: http://www.sourceoecd.org/environment/9264027122 http://www.sourceoecd.org/transport/9264027122 ThosewithaccesstoallOECDbooksonlineshouldusethislink: http://www.sourceoecd.org/9264027122 SourceOECDistheOECD’sonlinelibraryofbooks,periodicalsandstatisticaldatabases. Formoreinformationaboutthisaward-winningserviceandfreetrialsaskyourlibrarian, orwritetousat
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ISBN92-64-02712-2 972006121P
DecouplingtheEnvironmentalImpactsofTransportfromEconomicGrowth
Thisbookillustratesthatdecouplingtheenvironmentalimpactsoftransportfrom economicgrowthisachievable,throughtheefficientuseofcharges,fees,taxes andothereconomicinstruments.Theseeconomicapproachescancomplement regulatorymeasurestoencourageashifttowardsmoreenvironmentally-friendly modesoftransport,suchasfromroadtocertainformsofrailtransport.Other factorswhichcouldhelptodecoupletransportimpactsfromeconomicgrowth areimprovementsinfreighttransportlogistics,anddematerialisation.Allofthese approachesshouldbeappliedwithparticularattentiontothecircumstancesand characteristicsofindividualcountries;someinstrumentsthatfitwellinonecountry mightnotbewelladaptedtoothers.
Decoupling theEnvironmental Impactsof Transportfrom EconomicGrowth
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