The Relationship between On-Road FFCO 2 Emissions and Socio-Economic/Urban Form Factors for Global Cities: Significance, Robustness and Implications

Yang Song and Kevin R. Gurney
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Yang Song: School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011, USA
Kevin R. Gurney: School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011, USA

Sustainability, 2020, vol. 12, issue 15, 1-24

Abstract: Transportation accounts for 18% of global fossil fuel carbon dioxide (FFCO 2 ) emissions, especially in urban areas. An improved understanding of on-road FFCO 2 emissions is essential to both carbon science and mitigation policy. Previous studies have identified the driving factors and quantified their relationship to on-road FFCO 2 emissions. However, they have been primarily based on case studies conducted in individual cities, and the research results remain inconclusive due to the considerable heterogeneity of cities and associated outcomes. In order to achieve more general results and to further understand their uncertainties, this study explored the relationships between socio-economic/urban form data and self-reported on-road FFCO 2 emissions for a sample of global cities based on the adjusted Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model. The robustness and sensitivity of these relationships was evaluated by introducing artificial errors, conducting cross-validation, and examining various model specifications. Results indicated that fuel economy ( p -value < 3.1 × 10 −8 ), vehicle ownership ( p -value < 3.0 × 10 −4 ), road density ( p -value < 4.4 × 10 −3 ) and population density ( p -value < 3.1 × 10 −3 ) were statistically significant factors that correlate with on-road FFCO 2 emissions. Of these four variables, fuel economy and vehicle ownership had the most robust relationships. These results offer potential policy insights into on-road FFCO 2 emissions mitigation in cities, in addition to offering a means to generate emissions estimates without detailed bottom-up information.

Keywords: on-road emission; socio-economic/urban form factors; sensitivity analysis; global cities (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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