Spatio-temporal variations and influencing factors of energy-related carbon emissions for Xinjiang cities in China based on time-series nighttime light data

This essay combines the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) nighttime light data and the Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light data into a "synthetic DMSP" dataset, from 1992 to 2020, to retrieve the spatio-temporal variations in energy-related carbon emissions in Xinjiang, China. Then, this paper analyzes several influencing factors for spatial differentiation of carbon emissions in Xinjiang with the application of geographical detector technique. Results reveal that (1) total carbon emissions continued to grow, while the growth rate slowed down in the past five years. (2) Large regional differences exist in total carbon emissions across various regions. Total carbon emissions of these regions in descending order are the northern slope of the Tianshan (Mountains) > the southern slope of the Tianshan > the three prefectures in southern Xinjiang > the northern part of Xinjiang. (3) Economic growth, population size, and energy consumption intensity are the most important factors of spatial differentiation of carbon emissions. The interaction between economic growth and population size as well as between economic growth and energy consumption intensity also enhances the explanatory power of carbon emissions' spatial differentiation. This paper aims to help formulate differentiated carbon reduction targets and strategies for cities in different economic development stages and those with different carbon intensities so as to achieve the carbon peak goals in different steps.