Fine mapping and multidimensional analysis of carbon emission reduction in China

Abstract

With the escalating impacts of global climate change, carbon peaking and carbon neutrality have become pressing issues of mutual concern for nations worldwide. Accurately measuring carbon emissions at regional and municipal levels in order to design differentiated reduction policies and promote carbon neutrality has become a challenging problem. To tackle this challenge, we developed a 250 m resolution grid map of carbon footprint data and constructed a national-level database (comprised of 2,800 county-level units) to analyze China’s carbon footprint from multiple angles such as overall characteristics, urban agglomerations, county-level units, population density, per capita disposable income, and more. This research provides fresh insights for studying multi-scale footprint spatial pattern dynamics. Our findings indicate that (1) The 250 m resolution Carbon Footprint Database developed in this study covers the national, provincial, county, urban, and rural areas, enabling dynamic research on multi-scale footprint spatial patterns; (2) The top 5% of areas with the highest carbon footprints account for approximately 1/5 of total carbon footprints in China, and approximately 1/4 of areas account for more than 50% of total carbon footprints; (3) The potential for reducing carbon emissions in China’s rural areas has been underestimated by over 10%, while those in the western regions are growing rapidly due to poverty alleviation efforts; (4) An inverted U-shaped “environmental Kuznets curve” emerges between disposable income and emissions intensity, with different regions exhibiting different consumption patterns. This study offers a novel approach for formulating reduction policies at different levels throughout the country.