Fuel type preference of taxi driver and its implications for air emissions

Abstract

Natural gas became an available fuel for taxis in 2005 and had occupied a market share of 43.6% in taxi industry till 2010 in Nanjing, China. To investigate the energy replacement pattern as well as the pollutants reduction potential of the taxi industry, first, the fuel preference determinants of taxi drivers for their next taxis are analyzed. Results show that as an important alternative for the traditional gasoline, natural gas is widely accepted (75%) by taxi drivers. Different from the previous studies which focused on the early stage of cleaner fuel replacement, taxi drivers with various characteristics (such as age, working experience, and education level) are consistent with their fuel preference when they choose their next taxis. Result suggests that policies that concern consumers with specific characteristics may have little effects on the change of the market share, when the alternative fuel market has been developed well. In addition, the increased share of gas in the fuel market achieves a 7.2% reduction of energy consumption. Considering life cycle emissions, the following air pollutants, namely Greenhouse Gases (GHGs), carbonic oxide (CO), nitrogen oxide (NO_x), particulate matters (PM) and hydrocarbons (C_xH_y), gain 10.0%, 3.5%, 20.5%, 36.1%, and 26.4% of reduction respectively. Assuming all taxi fleets powered by natural gas with local policy intervention, the energy conservation and the five major air pollutant emissions could achieve the maximum reductions with 12.2%, 16.0%, 8.8%, 22.5%, 44.2%, and 49.4% correspondingly.

Keywords

fuel preference / energy replacement / environmental impacts / taxi

References

[1] Zhang Q Y, Tian W L, Zheng Y Y, Zhang L L. Fuel consumption from vehicles of China until 2030 in energy scenarios. Energy Policy, 2010, 38(11): 6860–6867

[2] Yeh S. An empirical analysis on the adoption of alternative fuel vehicles: the case of natural gas vehicles. Energy Policy, 2007, 35(11): 5865–5875

[3] Yan X Y, Crookes R J. Reduction potentials of energy demand and GHG emissions in China’s road transport sector. Energy Policy, 2009, 37(2): 658–668

[4] Silveria F C, Luken R A. Global overview of industrial energy intensity. Energy Policy, 2008, 36(7): 2658–2664

[5] Zhang L, Huang Z. Life cycle study of coal-based dimethyl ether as vehicle fuel for urban bus in China. Energy, 2007, 32(10): 1896–1904

[6] Ou X M, Zhang X L, Chang S Y, Guo Q F. Energy consumption and GHG emissions of six biofuel pathways by LCA in (the) People’s Republic of China. Applied Energy, 2009, 86(Suppl. 1): S197–S208

[7] Ou X M, Zhang X L, Chang S Y. Scenario analysis on alternative fuel/vehicle for China’s future road transport: life-cycle energy demand and GHG emissions. Energy Policy, 2010, 38(8): 3943–3956

[8] Wang H K, Chen C H, Huang C, Fu L X. On-road vehicle emission inventory and its uncertainty analysis for Shanghai, China. Science of the Total Environment, 2008, 398(1–3): 60–67

[9] Wang H K, Fu L X, Lin X, Zhou Y, Chen J C. A bottom-up methodology to estimate vehicle emissions for the Beijing urban area. Science of the Total Environment, 2009, 407(6): 1947–1953

[10] Greene D L. Motor fuel choice: an econometric analysis. Transportation Research Part A, General, 1989, 23(3): 243–253

[11] Greene D L.Survey evidence on the importance of fuel availability to the choice of alternative fuels and vehicles. Energy Studies Review, 1996, 8(3): 215–231

[12] Mau P, Eyzaguirre J, Jaccard M, Collins-Dodd C, Tiedemann K. The “neighbor effect”: simulating dynamics in consumer preferences for new vehicle technologies. Ecological Economics, 2008, 68(1): 504–516

[13] Potoglou D, Kanaroglou P S. Household demand and willingness to pay for clean vehicles. Transportation Research Part D, Transport and Environment, 2007, 12(4): 264–274

[14] Dubin J A, McFadden D L. An econometric analysis of residential electric appliance holdings and consumption. Econometrica, 1984, 52(2): 345–362

[15] Ouedraogo B. Household energy preferences for cooking in urban Ouagadougou, Burkina Faso. Energy Policy, 2006, 34(18): 3787–3795

[16] Haines P S, Guilkey D K, Popkin B M. Modeling food consumption decisions as a two-step process. American Journal of Agricultural Economics, 1988, 70(3): 543–552

[17] Braun F G. Determinants of households’ space heating type: a discrete choice analysis for German households. Energy Policy, 2010, 38(10): 5493–5503

[18] Liao H C, Chang T F. Space-heating and water-heating energy demands of the aged in the US. Energy Economics, 2002, 24(3): 267–284

[19] Vaage K. Heating technology and energy use: a discrete/continuous choice approach to Norwegian household energy demand. Energy Economics, 2000, 22(6): 649–666

[20] Goldberg P K. The effects of the corporate average fuel efficiency standards in the US. Journal of Industrial Economics, 1998, 46(1): 1–33

[21] Hewitt J A, Hanemann W M. A discrete/continuous choice approach to residential water demand under block rate pricing. Land Economics, 1995, 71(2): 173–192

[22] Olmstead S M, Hanemann W M, Stavins R N. Water demand under alternative price structures. Journal of Environmental Economics and Management, 2007, 54(2): 181–198

[23] West S E. Distributional effects of alternative vehicle pollution control policies. Journal of Public Economics, 2004, 88(3): 735–757

[24] Liu B B, Chen C, Zhang B, Bu M L, Bi J, Yu Y. Fuel use pattern and determinants of taxi drivers’ fuel choice in Nanjing, China. Journal of Cleaner Production, 2012, 33: 60–66

[25] Gao H O, Kitirattragarn V. Taxi owners’ buying preferences of hybrid-electric vehicles and their implications for emissions in New York City. Transportation Research Part A: Policy and Practice, 2008, 42(8): 1064–1073

[26] Maddala G, Flores-Lagunes A. Qualitative response models. In: Baltagi B H, ed. A Companion to Theoretical Econometrics. New Jersey: Wiley-Blackwell, 2003, 366–382

[27] Commission of the European Communities. Integrated Product Policy: Building on Environmental Life-Cycle Thinking: Communication from the Commission to the Council and the European Parliament. Brussels: Office for Official Publications of the European Communities, 2003

[28] Heijungs R, de Koning A, Suh S, Huppes G. Toward an information tool for integrated product policy: requirements for data and computation. Journal of Industrial Ecology, 2006, 10(3): 147–158

[29] Yan X Y, Crookes R J. Energy demand and emissions from road transportation vehicles in China. Progress in Energy and Combustion Science, 2010, 36(6): 651–676

[30] Ou X M, Zhang X L. Fossil energy consumption and GHG emissions of final energy by LCA in China. China’s Soft Science, 2009, S2: 208–214(in Chinese)

[31] Hu Z Y, Tan P Q, Yan X Y, Lou D M. Life cycle energy, environment and economic assessment of soybean-based biodiesel as an alternative automotive fuel in China. Energy, 2008, 33(11): 1654–1658

[32] Hanemann W M. Discrete/continuous models of consumer demand. Econometrica, 1984, 52(3): 541–561

Acknowledgements

The research is funded by the humanities and social sciences project, conducted by the Ministry of Education in China, titled “GHG based bio-energy distribution and policy optimization (13YJCZH099)” and the National Science Foundation Project of Jiangsu Province, titled “GHG based straw utilization: distribution and policy optimization (BK20130572)”.

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg