Spatiotemporal dynamics of energy-related carbon emissions and their influencing factors in the Yangtze River Delta region of China based on nighttime light data

Abstract

Abstract Owing to China's massive area and vastly differing regional variations in the types and efficiency of energy, the spatiotemporal distributions of regional carbon emissions vary widely. Regional carbon emissions study is becoming more crucial for determining the future course of sustainable development worldwide. In this work, two types of nighttime light data were integrated to expand the study's temporal coverage. On this basis, the distribution of energy-related carbon emissions (CE) in the Yangtze River Delta (YRD) region of China was estimated using the linear regression model at a multispatial scale. Then the spatiotemporal dynamics of CE were explored based on the estimated results. The four major factors' impact on CE in the YRD was assessed using the geographic detector (geodetector) model. The findings showed that the growth rate of CE in the YRD displayed three stages, and the total CE fluctuated upward. The spatial pattern of CE demonstrated a step-like decline from east to west. However, the Gini coefficient indicated that the differences in CE between cities gradually decreased since the CE had a strong spatial positive correlation in the YRD. Multiple factors affected the spatial variation of CE in the YRD, with economic level and population as the "critical" influencing elements, which determined the absolute amount of CE. The findings can provide scientific support for CE simulation in other similar regions.