Spatiotemporal variations of urban CO2 emissions in China: A multiscale perspective

Spatiotemporal variations of urban CO2 emissions in China: A multiscale perspective •Urban CO2 emissions from national down to urban agglomeration scales were explored.•About 13,859 km2 of urban areas experienced High-growth of CO2 emissions.•The DMSP-OLS data can effectively evaluate urban CO2 emissions.•Urban CO2 emissions presented different spatiotemporal variations within different scales.•Urban GDP and urban population exerted a positive impact on urban CO2 emissions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Energy Elsevier

Spatiotemporal variations of urban CO2 emissions in China: A multiscale perspective

Spatiotemporal variations of urban CO2 emissions in China: A multiscale perspective

Applied Energy 211 (2018) 218–229 Contents lists available at ScienceDirect Applied Energy journal homepage: www.elsevier.com/locate/apenergy Spatiotemporal variations of urban CO emissions in China: A multiscale perspective a, b c d Kaifang Shi , Yun Chen , Linyi Li , Chang Huang Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China CSIRO Land and Water, Canberra 2601, Australia School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China HIGHLIGHTS Urban CO emissions from national down to urban agglomeration scales were explored. About 13,859 km of urban areas experienced High-growth of CO emissions. The DMSP-OLS data can effectively evaluate urban CO emissions. Urban CO emissions presented different spatiotemporal variations within different scales. Urban GDP and urban population exerted a positive impact on urban CO emissions. ARTICLE I NFO ABSTRACT Keywords: Timely and accurate understanding of spatiotemporal variations of urban CO emissions is important in the Urban CO emissions 2 interaction between human activities and the environment. However, studies that consider spatiotemporal Spatiotemporal variations variations of urban CO emissions at multiple scales are still lacking. In this study, we combined the Defense DMSP-OLS Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime light images, statistical Multiscale analysis energy consumption data, and urban area data to assess spatiotemporal variations of urban CO emissions in China China from national scale down to regional and urban agglomeration scales between 1997 and 2012. The results reveals that China has been experiencing strikingly spatiotemporal variations of urban CO emissions during the study period. At the national scale,...
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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0306-2619
D.O.I.
10.1016/j.apenergy.2017.11.042
Publisher site
See Article on Publisher Site

Abstract

•Urban CO2 emissions from national down to urban agglomeration scales were explored.•About 13,859 km2 of urban areas experienced High-growth of CO2 emissions.•The DMSP-OLS data can effectively evaluate urban CO2 emissions.•Urban CO2 emissions presented different spatiotemporal variations within different scales.•Urban GDP and urban population exerted a positive impact on urban CO2 emissions.

Journal

Applied EnergyElsevier

Published: Feb 1, 2018

References

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