Identifying spatiotemporal characteristics and driving factors for road traffic CO2 emissions

Abstract

Road traffic is an important contributor to CO2 emissions. Previous studies lack enough spatiotemporal resolution in emission calculation at the road level and ignore the impact of the built environment on road traffic emissions. Therefore, this study develops a bottom-up methodology based on the traffic trajectory data to analyze the CO2 emission characteristics of road traffic with a high level of spatial-temporal resolution in Shenzhen. Then, the effects of built environment factors on road traffic emissions are investigated using multiscale geographically weighted regression. The results show a highly detailed map of CO2 emissions with high temporal (hour) and space (road) resolutions. The emission characteristics reflect the spatial non-equilibrium in road traffic CO2 emissions. In addition, six factors, including population density, number of workplaces, number of dwellings, density of main road, access to metro stations, and access to bus stops, have a significant effect on road traffic CO2 emissions. Finally, the policy suggestions are proposed for the reduction of road traffic CO2 emissions.

Xiao Zhou

Postdoctoral Researcher
2021 - 2023

My research interests include sustainable development, marine spatial planning, and environmental policy analysis

Han Wang

Grad Student
2020 - 2023

Interested in all things cool.

Zhou Huang

Associate professor

Associate professor of GIScience

Yi Bao

Postdoctoral Researcher
2023 - present
PhD Student
2018 - 2023

My research interests include Geographical Information Systems, Remote Sensing, Urban Data Mining, Deep Learning

Yu Liu

Professor
1997 - present

Professor of GIScience