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Article

Spatiotemporal Variations of City-Level Carbon Emissions in China during 2000–2017 Using Nighttime Light Data

1
Department of Land Management, Zhejiang University, Hangzhou 310058, China
2
Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing 210044, China
3
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
4
Department of Urban and Environmental Sociology, Helmholtz Centre for Environmental Research-UFZ, Permoserstraße 15, D-04318 Leipzig, Germany
5
School of Life and Environmental Sciences, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, CA 92866, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(18), 2916; https://doi.org/10.3390/rs12182916
Received: 26 August 2020 / Revised: 4 September 2020 / Accepted: 7 September 2020 / Published: 8 September 2020
China is one of the largest carbon emitting countries in the world. Numerous strategies have been considered by the Chinese government to mitigate carbon emissions in recent years. Accurate and timely estimation of spatiotemporal variations of city-level carbon emissions is of vital importance for planning of low-carbon strategies. For an assessment of the spatiotemporal variations of city-level carbon emissions in China during the periods 2000–2017, we used nighttime light data as a proxy from two sources: Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) data and the Suomi National Polar-orbiting Partnership satellite’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). The results show that cities with low carbon emissions are located in the western and central parts of China. In contrast, cities with high carbon emissions are mainly located in the Beijing-Tianjin-Hebei region (BTH) and Yangtze River Delta (YRD). Half of the cities of China have been making efforts to reduce carbon emissions since 2012, and regional disparities among cities are steadily decreasing. Two clusters of high-emission cities located in the BTH and YRD followed two different paths of carbon emissions owing to the diverse political status and pillar industries. We conclude that carbon emissions in China have undergone a transformation to decline, but a very slow balancing between the spatial pattern of high-emission versus low-emission regions in China can be presumed. View Full-Text
Keywords: spatiotemporal variations; carbon emissions; DMSP-OLS; NPP-VIIRS spatiotemporal variations; carbon emissions; DMSP-OLS; NPP-VIIRS
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MDPI and ACS Style

Sun, Y.; Zheng, S.; Wu, Y.; Schlink, U.; Singh, R.P. Spatiotemporal Variations of City-Level Carbon Emissions in China during 2000–2017 Using Nighttime Light Data. Remote Sens. 2020, 12, 2916. https://doi.org/10.3390/rs12182916

AMA Style

Sun Y, Zheng S, Wu Y, Schlink U, Singh RP. Spatiotemporal Variations of City-Level Carbon Emissions in China during 2000–2017 Using Nighttime Light Data. Remote Sensing. 2020; 12(18):2916. https://doi.org/10.3390/rs12182916

Chicago/Turabian Style

Sun, Yu, Sheng Zheng, Yuzhe Wu, Uwe Schlink, and Ramesh P. Singh. 2020. "Spatiotemporal Variations of City-Level Carbon Emissions in China during 2000–2017 Using Nighttime Light Data" Remote Sensing 12, no. 18: 2916. https://doi.org/10.3390/rs12182916

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