Revisiting the environmental Kuznets curve for city-level CO2 emissions : based on corrected NPP-VIIRS nighttime light data in China

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Article number121575
Number of pages14
Journal / PublicationJournal of Cleaner Production
Online published12 May 2020
Publication statusPublished - 20 Sep 2020


With the increasing trend of global warming, the Chinese government faces tremendous pressure to reduce CO2 emissions. The purpose of this study is to accurately measure CO2 emissions at the city scale in China and examine the environmental Kuznets curve, thereby providing a reference for decision-making. Corrected NPP-VIIRS nighttime light data were used to accurately estimate carbon dioxide emissions at the provincial and city scales in China. Then, based on the STRIPAT model, 291 cities in China were used to verify the environmental Kuznets curve. Our results show that on the provincial scale, the R2 between the estimated value and the statistical value of carbon dioxide reaches 0.85. Western cities in China emit more CO2, as do economically developed cities and industry- and mining-dominated cities. There are two CO2 emission hot spots in the north and one cold spot in the south. It was found that the environmental Kuznets curve on the city scale exists. This study has practical value in utilizing NPP-VIIRS data for the estimation of city CO2 emissions. The results also have academic value for determining factors that contribute to carbon dioxide emissions and can provide a reference for relevant decision makers. This study could be considered the first to simulate CO2 emissions at the provincial and city levels in China based on a NPP-VIIRS nighttime light model to explore the associated geographical distribution characteristics and potential influencing factors.

Research Area(s)

  • China, City level, CO2 emissions, Corrected NPP-VIIRS data, Environmental Kuznets curve (EKC), Spatial econometric model

Citation Format(s)