Elsevier

Environmental Science & Policy

Volume 33, November 2013, Pages 273-282
Environmental Science & Policy

The climate impact of travel behavior: A German case study with illustrative mitigation options

https://doi.org/10.1016/j.envsci.2013.06.009Get rights and content

Highlights

  • We estimate the climate impact of German travel behavior.

  • The climate impact is equally dominated by car and air transport.

  • The rich have the largest impacts, but the larger middle class has a greater share.

  • A few long trips by air are responsible for a large share of the total climate impact.

  • A comprehensive mitigation is needed covering technology and behavioral changes.

Abstract

Global greenhouse gas mitigation should include the growing share of emissions from transportation. To help understand the mitigation potential of changing travel behavior requires disaggregating the climate impacts of transportation by transport mode, distance, and travel behavior. Here we use disaggregated data on travel behavior to calculate the climate impact of Germans traveling nationally and internationally in 2008 and develop some illustrative mitigation options. We include all relevant long-lived greenhouse gases and short-lived climate forcers and use global temperature change for 50 years of sustained emissions as the emission metric. The total climate impact is determined almost entirely by car (∼46%) and air travel (∼45%), with smaller contributions from public transportation. The climate impact from the highest income group is 250% larger than from the lowest income group. However, the middle classes account for more than two thirds of the total impact. The relatively few trips beyond 100 km contribute more than half of the total impact because of the trip distance and use of aircraft. Individual behavioral changes, like shifting transport modes or reducing distance and frequency, can lead to useful emission reductions. However, a comprehensive package of mitigation options is necessary for deep and sustained emission reductions.

Introduction

Transport is one of the key contributors to past and future climate change. Historical emissions from transportation contributed about 9% of the temperature change in 2000, while this share may increase to 20% in 2100 (Skeie et al., 2009). Sustained year 2000 emissions from transportation account for 23% of the total radiative forcing in 2100 (Unger et al., 2009). Any realistic effort to keep the global mean surface temperature from exceeding the proposed 2 °C threshold, needs to involve the transportation sector (GEA, 2012). While many studies have focused on the equivalent greenhouse gas emissions from transportation (IPCC, 2007), relatively few have focused on the actual climate impact (exceptions include Berntsen and Fuglestvedt (2008), Shindell et al. (2011), Unger et al. (2009)).

The climate impact for transport modes have typically been investigated for global or regional average assumptions (Berntsen and Fuglestvedt, 2008, Fuglestvedt et al., 2008, Skeie et al., 2009). These studies find that road transport dominates, with aviation as the second largest contributor. Shipping has a short term cooling effect. A rather different perspective on transportation is obtained by considering the specific Climate Impact (sCI, normalized by person kilometer) of different types of transport (Borken-Kleefeld et al., 2010, Chester and Horvath, 2009). For global emissions, Borken-Kleefeld et al. (2010) found that rail and coaches have the lowest sCI, while air travel has the highest sCI for short time horizons, and car is equal to air or higher for longer time horizons (Borken-Kleefeld et al., 2010). These studies provide valuable information on the scale of the mitigation required, but provide little specific information on where to target mitigation measures, particularly for behavioral interventions.

The climate impact of transportation is expected to differ with different travel behavior, both at the national level and for individual behavior. Surveys of travel behavior are performed on a regular basis in several countries, for instance, Germany (Follmer et al., 2010), Switzerland (Infanger et al., 2002), Norway (Vågane et al., 2011), and the USA (Buehler, 2010). Linked with emission factors, the travel behavior is translated to emissions. Nicolas and David (2009) for instance analyzed the CO2 emissions from passenger travel in France, and Brand and Preston (2010) constructed GHG emission profiles from individual travel of a sample living in Oxfordshire, UK. However, all these studies focused on CO2 only, or at best included other long-lived greenhouse gases (although Brand and Preston (2010) included an aviation impact multiplier), and they only assessed emissions and not climate impacts.

The emissions from the different transport modes consist not only of CO2 and a few other long-lived greenhouse gases (LLGHGs in the Kyoto Protocol: CO2, CH4, N2O, SF6, HFCs, and PFCs), but also air pollutants that influence the radiative balance of the atmosphere. The short lived climate forcers (SLCFs: Black carbon (BC), organic carbon (OC), SO2, NOx, VOC, CO, contrail, and aircraft induced cirrus) affect climate either directly (e.g., BC) or indirectly through chemical reactions (e.g., NOx). Due to different radiative efficiencies and lifetimes, these emissions cannot be directly compared without the use of emission metrics (Fuglestvedt et al., 2003, Fuglestvedt et al., 2010). The most common emission metrics are integrated radiative forcing (Absolute Global Warming Potential, AGWP) and temperature (Absolute Global Temperature change Potential, AGTP), and in normalized form these become the GWP, as used in the Kyoto Protocol, and GTP. In the case of transportation, studies have shown the importance of SLCFs relative to LLGHGs. For GWP with a time horizon of 100 years, the SLCFs account for roughly 20% of the total impact for most vehicles (Peters et al., 2011).

In this article, we use the latest results from the comprehensive national travel survey in Germany, referred to here as Follmer et al. (2010), as an example to demonstrate how the climate impact can be estimated from travel behavior. The novelty of our study is threefold; (1) we analyze the climate impact in terms of temperature perturbation and not just emissions, (2) we disaggregate the climate impacts by aggregated measures of travel mode and behavior, and (3) we provide illustrative mitigation measures of changing behavior that reduce the climate impact of transportation. We consider both national and international travel by Germans in 2008. Travel behavior is differentiated by income class and trip length. This differentiated understanding of the underlying behavioral characteristics provides the basis for more targeted and, hence, potentially more effective mitigation actions.

Section snippets

Materials and methods

The total climate impact CI for group of people g from travel is calculated as the product of the travel volume (TV), an aggregated measure of all individual trips, with a transport mode m times an average emission factor EF for species s times a suitable emission metric (AM) for this species, summed over all species emitted and all transport modes used in the period:CIg=ΣmΣsTVm,g×EFm,s,g×AMs

In general, different socio-economic groups, g, may use different technologies (hence EF), but we assume

Climate impact by household economic status

Fig. 1 shows the average trips, travel volume, and the climate impact of travel behavior per person per year according to their household economic status defined by Follmer et al. (2010). The average German travels 1250 trips per year, where the high income group goes on 7% more and the low income group 14% less trips than the average. All groups travel about the same number of trips with public transport, while the high income population drives more often than the low income population. Only

Conclusion

When all relevant LLGHGs and SLCFs are included, the total climate impact from passenger transportation is due to only two modes, and for effective mitigation, car (∼46%) and air travel (∼45%) need to be addressed. We found that high income people travel much more (elasticity of 0.56) and have a much higher climate impact (elasticity of 0.75) than low income people. For air travel, the elasticity increases to 1.17 indicating that the use of air travel grows faster than income. However, to

Acknowledgments

This research was partly funded by the Norwegian Research Council Project “Transport and Environment – Measures and Policies (TEMPO)” and scholarship from the International Institute for Applied Systems Analysis (IIASA) Young Scientists Summer Program (YSSP). We thank Jan S. Fuglestvedt (CICERO) for useful comments. We also thank the valuable comments given by two anonymous referees.

Borgar Aamaas is a Research Fellow at Center for International Climate and Environmental Research–Oslo (CICERO). He has previously published papers on emission metrics, transportation emissions, and black carbon. He holds a Master Degree in Meteorology and Oceanography from the University of Oslo.

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    Borgar Aamaas is a Research Fellow at Center for International Climate and Environmental Research–Oslo (CICERO). He has previously published papers on emission metrics, transportation emissions, and black carbon. He holds a Master Degree in Meteorology and Oceanography from the University of Oslo.

    Jens Borken-Kleefeld is a Research Scholar at the International Institute for Applied Systems Analysis (IIASA) in the program on Mitigation of Air Pollution and Greenhouse Gases. His main focus of work is on environmental impact assessment applied particularly to the transport sector. He holds a PhD in technology impact assessment. His research interests include indicators for sustainable mobility, decision making, short-term climate forcers and long-term scenarios.

    Glen Peters is a Senior Research Fellow at the Center for International Climate and Environmental Research–Oslo (CICERO). He conducts research on the development and assessment of effective global climate policy. Key areas of research are the role of international trade in climate policy (carbon footprints, carbon leakage, and competitiveness concerns), sustainable consumption, emission metrics, and the carbon cycle.

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