TY - JOUR
T1 - Quantifying the spillover elasticities of urban built environment configurations on the adjacent traffic CO2 emissions in mainland China
AU - Song, Weize
AU - Zhang, Xiaoling
AU - An, Kangxin
AU - Yang, Tao
AU - Li, Heng
AU - Wang, Can
N1 - Funding Information:
This project is co-funded by the Natural Science Foundation of Beijing, China (No. 9204026), National Key Research and Development Program of China project (No. 2017YFA0603602), Tsinghua University SRT projects (No. 1911T0051, No. 2011T0070), National Natural Science Foundation of China (NO. 71834005), and the Philosophy and Social Sciences Research of Higher Learning Institutions of Shanxi (No. 201801010). We thank Jianhui Cong from Shanxi University for his literature research. The authors also thank the Center for Climate Change and Environmental Policy, Chinese Academy for Environmental Planning for their CO 2 emission inventory.
Funding Information:
This project is co-funded by the Natural Science Foundation of Beijing, China (No. 9204026), National Key Research and Development Program of China project (No. 2017YFA0603602), Tsinghua University SRT projects (No. 1911T0051, No. 2011T0070), National Natural Science Foundation of China (NO. 71834005), and the Philosophy and Social Sciences Research of Higher Learning Institutions of Shanxi (No. 201801010). We thank Jianhui Cong from Shanxi University for his literature research. The authors also thank the Center for Climate Change and Environmental Policy, Chinese Academy for Environmental Planning for their CO2 emission inventory.
Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2021/2/1
Y1 - 2021/2/1
N2 - Urban built environment regulations can effectively mitigate traffic CO2 emissions. Thus, it is critical to quantify the elasticities of altering built environment configurations. To address this issue, we have built nationwide spatial autoregressive models to differentiate between localized and spillover effects across 325 Chinese cities in the years of 2005 and 2015. Our results indicate that a 1% increase in built-up areas’ size, compactness, and isolation is associated with increases of 0.35%, −0.14%, and 0.13%, respectively, in adjacent traffic CO2 emissions. The underlying reason is that the spatial configurations of built environment do not only systemically affect the probability, frequency, speed, and distance of intracity motorised travels, but also have impacts on the intercity transboundary mobility of motor vehicles. In addition, the built-up areas’ compactness effect has an antagonistic relation with the per capita GDP effect. Thus, our findings provide evidence that the built environment configuration-related measures can benefit traffic CO2 emission reductions in adjacent cities. It is therefore necessary for policymakers to make a traffic CO2 mitigation strategy at the city agglomeration level.
AB - Urban built environment regulations can effectively mitigate traffic CO2 emissions. Thus, it is critical to quantify the elasticities of altering built environment configurations. To address this issue, we have built nationwide spatial autoregressive models to differentiate between localized and spillover effects across 325 Chinese cities in the years of 2005 and 2015. Our results indicate that a 1% increase in built-up areas’ size, compactness, and isolation is associated with increases of 0.35%, −0.14%, and 0.13%, respectively, in adjacent traffic CO2 emissions. The underlying reason is that the spatial configurations of built environment do not only systemically affect the probability, frequency, speed, and distance of intracity motorised travels, but also have impacts on the intercity transboundary mobility of motor vehicles. In addition, the built-up areas’ compactness effect has an antagonistic relation with the per capita GDP effect. Thus, our findings provide evidence that the built environment configuration-related measures can benefit traffic CO2 emission reductions in adjacent cities. It is therefore necessary for policymakers to make a traffic CO2 mitigation strategy at the city agglomeration level.
KW - Built environment configurations
KW - Spatial autoregressive model
KW - Traffic CO emission
UR - http://www.scopus.com/inward/record.url?scp=85097090037&partnerID=8YFLogxK
U2 - 10.1016/j.apenergy.2020.116271
DO - 10.1016/j.apenergy.2020.116271
M3 - Journal article
AN - SCOPUS:85097090037
SN - 0306-2619
VL - 283
JO - Applied Energy
JF - Applied Energy
M1 - 116271
ER -