Modeling the relationships among urban passenger travel carbon dioxide emissions,transportation demand and supply,population density,and proxy policy variables |
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| Institution: | 1. The Ohio State University, 2070 Neil Ave., Rm 470, Columbus, OH 43210, United States;2. The Ohio State University, 1958 Neil Ave., Rm 204C, Columbus, OH 43210, United States;3. US Census Bureau, 305 10th St S, Apt 4418, Arlington, VA 22202, United States;4. The Ohio State University, 1958 Neil Ave., Rm 404, Columbus, OH 43210, United States;1. College of Transportation, Jilin University, No.5988 Renmin Street, Nanguan District, Changchun, 130022, China;2. College of Engineering, Zhejiang Normal University, No.688 Yingbin Road, Wucheng District, Jinhua, 321001, China;3. China Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Province, Zhejiang Normal University, No.688 Yingbin Road, Wucheng District, Jinhua, 321001, China;1. Department of Meteorology, University of Reading, Reading, RG6 6BB, UK;2. Department of Geography, King''s College London, London, WC2R 2LS, UK;3. Centre for Ecology and Hydrology, Wallingford, Oxfordshire, OX10 8BB, UK;4. Forest Research, Centre for Forestry and Climate Change, Alice Holt Lodge, Farnham, Surrey, GU10 4LH, UK;5. Scuola di Ingegneria, Università degli Studi della Basilicata, 85100, Potenza, Italy;1. College of Public Administration, Huazhong Agricultural University, Wuhan 430070, PR China;2. School of Geography, University of Leeds, Leeds LS2 9JT, United Kingdom;3. British Geological Survey, Keyworth, Nottingham NG12 5GG, United Kingdom;1. Potsdam Institute for Climate Impact Research, Potsdam 14473 Germany;2. Dept. of Geo- and Environmental Sciences, University of Potsdam, Potsdam 14476, Germany |
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| Abstract: | To support the development of policies that reduce greenhouse gas (GHG) emissions by encouraging reduced travel and increased use of efficient transportation modes, it is necessary to better understand the explanatory effects that transportation, population density, and policy variables have on passenger travel related CO2 emissions. This study presents the development of a model of CO2 emissions per capita as a function of various explanatory variables using data on 146 urbanized areas in the United States. The model takes into account selectivity bias resulting from the fact that adopting policies aimed at reducing emissions in an urbanized area may be partly driven by the presence of environmental concerns in that area. The results indicate that population density, transit share, freeway lane-miles per capita, private vehicle occupancy, and average travel time have a statistically significant explanatory effect on passenger travel related CO2 emissions. In addition, the presence of automobile emissions inspection programs, which serves as a proxy indicator of other policies addressing environmental concerns and which could influence travelers in making environmentally favorable travel choices, markedly changes the manner in which transportation variables explain CO2 emission levels. |
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| Keywords: | Urban passenger transportation Carbon dioxide emissions Environmental policy Statistical modeling Selectivity bias |
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