Spatiotemporal variations of urban CO2 emissions in China: A multiscale perspective
Linyi Li and
Applied Energy, 2018, vol. 211, issue C, 218-229
Timely and accurate understanding of spatiotemporal variations of urban CO2 emissions is important in the interaction between human activities and the environment. However, studies that consider spatiotemporal variations of urban CO2 emissions at multiple scales are still lacking. In this study, we combined the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime light images, statistical energy consumption data, and urban area data to assess spatiotemporal variations of urban CO2 emissions in 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 CO2 emissions during the study period. At the national scale, urban areas that experienced High-growth of CO2 emissions accounted for 22.16% of the total urban areas in 2012. High-growth of urban CO2 emissions covered 18.09% of the total urban areas in the eastern region. Relatively-high-growth of urban CO2 emissions accounted for 46.14% of the total urban areas in the central region. Around 5766 km2 of urban areas experienced Relatively-high-growth of urban CO2 emissions, accounting for 39.04% of the total urban areas in the western region. The Beijing–Tianjin–Tangshan (BTT) and Sichuan–Chongqing (SC) had the most extensive Low-growth, accounting for approximately 8.97% and 6.15% of their total urban areas. It should be pointed out that about 7815 km2 (11.58%) of peri-urban areas experienced High-growth of CO2 emissions. Meanwhile, we have also found that urban CO2 emissions had significant positive correlations with urban GDP (Gross Domestic Product) and urban population in China at multiple scales. Our findings can provide useful information for local authorities to guide their policies in CO2 emissions mitigation.
Keywords: Urban CO2 emissions; Spatiotemporal variations; DMSP-OLS; Multiscale analysis; China (search for similar items in EconPapers)
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