Abstract:

The global environment issue resulting from carbon emissions has aroused worldwide concern for governments, the public and scientific communities. A precise measurement of the time-resolved and spatial distribution characteristics of carbon dioxide (CO₂) and carbon footprint as well as its long-period evolution mechanism, can help clarify the relationship between environmental carbon load and economic growth, and are critical references to the formulation of scientific carbon emission reduction targets with reasonable and differential emission reduction policies. In this study, the mainland of China is taken as the research object. According to the quantitative correlations between DMSP-OLS nighttime light image data and carbon emission statistics, the carbon emission panel data model was simulated for China's carbon emissions in the period 2000-2013, and then the spatiotemporal evolving trend and spatial distribution characteristics of carbon emissions in the 14-year research period were discussed using Theil-Sen Median trend analysis and Mann-Kendall test method. Based on the framework of exploratory spatial-temporal data analysis (ESTDA), the spatial pattern and spatiotemporal dynamic evolution of carbon footprint from 2001 to 2013 were analyzed from the perspective of spatiotemporal interaction. In the three periods, the decoupling effect between environmental carbon load and economic growth of 336 prefecture-level cities were analyzed using the improved Tapio decoupling model. The results show that the overall carbon emissions in China had been on the rise from 2000 to 2013, in which the stable-slow rise type was dominant. China's carbon footprint and carbon deficit increased year by year, and the central and western regions became the focus of the growth of carbon footprint and carbon deficit from 2001 to 2013. At different administrative city scales, the spatial distribution pattern of carbon footprint and carbon deficit show obvious administrative orientated and spatial zonal differentiation characteristics. The annual average of global Moran's I index of each level unit is 0.491, which indicates that there is a significant spatial auto-correlation feature in the carbon footprint of China's prefecture-level units. The relative length of the LISA time path is greater in the north than in the south, and it tends to increase from the coastal areas to the central and western regions. The curvature of LISA time path decreases from coastal areas to inland areas on the whole. The curvature of northeast and central regions is higher, while that of eastern and western regions is lower. There is a different trend of the decoupling effect of environmental carbon load in China. Meanwhile the expansion-connection and expansion of negative decoupling regions continuously increased and spatially agglomerated, presenting an "E"-shaped distribution pattern from the north to the south. The national average decoupling elastic value is gradually increasing, while the coefficient of variation continues to decline, and the decoupling type has a significant evolution trend. Therefore, the unbalanced trend of economic growth and carbon emissions in China will continue for a certain period.

Key words: carbon footprint, carbon emissions, nighttime light, decoupling effect, spatio-temporal dynamics, exploratory spatio-temporal data analysis