Quantifying the spatiotemporal dynamics and impact factors of China's county-level carbon emissions using ESTDA and spatial econometric models

Abstract

China currently has the largest total CO2 emissions and is one of the countries that has made the most efforts to cut these. Anthropogenic emissions from county-level districts play a pivotal role in meeting carbon neutral due to the favorable breakdown of reduction targets into sub-national units, whereas limited work has been done related to those features and determinants. Here, we attempted to quantify the spatiotemporal dynamics of county carbon emissions and their drivers in China between 2000 and 2020 using an exploratory space-time data analysis (ESTDA) and spatial econometric method based on a remote sensing image inversion dataset. The results showed that emissions per capita and per unit of GDP in Chinese counties took on drastically opposite stances amid a trend of increasing carbon emissions. Meanwhile, their carbon emissions exhibited a pronounced regional disparity and spatially positive autocorrelation, characterized by sharp spatial heterogeneity and clustering. Local indicators of spatial association implied that the patterns of county carbon emissions had certain spatial integration, and that locally correlated forms were represented by deep path dependence and spatial locking effects. Besides, a range of panel regression models provided evidence of endogenous interactions of county carbon emissions, notably where every 1% increase in the neighboring emissions induced a local emissions increase by at least 0.4%. Various factors employed not only exerted a direct impact on local carbon emissions, but had spatial spillover effects on neighboring districts. Of these, economic level and industrial structure presented a significantly positive relationship with carbon emissions, while population clustering, financial input and technological advance had clear inhibitory effects. Our findings cast fresh light on the importance of the socioeconomic diversity of a district and its neighbors for government policy decisions related to carbon abatement at the county level.