Publication Details

Category Text Publication
Reference Category Journals
DOI 10.3390/rs12182916
Licence creative commons licence
Title (Primary) Spatiotemporal variations of city-level carbon emissions in China during 2000–2017 using nighttime light data
Author Sun, Y.; Zheng, S.; Wu, Y.; Schlink, U. ORCID logo ; Singh, R.P.
Source Titel Remote Sensing
Year 2020
Department SUSOZ
Volume 12
Issue 18
Page From art. 2916
Language englisch
Supplements https://www.mdpi.com/2072-4292/12/18/2916/s1
Keywords spatiotemporal variations; carbon emissions; DMSP-OLS; NPP-VIIRS
Abstract 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.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=23849
Sun, Y., Zheng, S., Wu, Y., Schlink, U., Singh, R.P. (2020):
Spatiotemporal variations of city-level carbon emissions in China during 2000–2017 using nighttime light data
Remote Sens. 12 (18), art. 2916 10.3390/rs12182916