[Spatio-temporal Differentiation of County Carbon Budget and Territorial Space Optimization Zoning Strategy in Gansu Province from the Perspective of Carbon Neutrality]

Under the background of comprehensively practicing the overall system concept of the "living community" in the new era, incorporating the carbon neutral development goal into the territorial spatial planning and construction and establishing the territorial spatial pattern and optimization strategy in line with the actual development of Gansu Province are of great significance for promoting the comprehensive green low-carbon transformation and high-quality development of regional economy and society. Taking counties in Gansu Province as an example, based on the perspective of carbon neutrality research, the land use carbon budget of 87 counties in Gansu Province in 2010, 2015, and 2021 was calculated and analyzed. GIS spatial analysis and social network analysis were used to further explore their spatial differentiation characteristics and the overall characteristics of the carbon emission spatial correlation network. At last, combined with the main function zoning, the low-carbon oriented land space optimization zoning was carried out, and differentiated low-carbon development strategies were proposed. The results were as follows： ① Carbon emissions in Gansu Province showed an upward trend, but the increase rate decreased, showing a spatial distribution of "high in the central and eastern part of the country, low in the southwest." Construction land was the main carbon source. The carbon uptake showed a spatial distribution of "high in the south and low in the north, high in the west and low in the east." Woodlands were the main carbon sinks. The net carbon emissions showed an increasing trend, and approximately 58.62% of the counties in the province were in a carbon imbalance situation. ② In 2021, the spatial network of county carbon emissions was closely related, showing a "core-edge" pattern. The Chenguan District and Qilihe District were in the core position of the network and received more correlation relationships in the network. The network contacts in Longzhong area were frequent, followed by the contacts in Longdongnan area. ③ Based on carbon emissions, carbon sequestration, and ecological carrying capacity coefficients and using the results of spatial correlation of social networks as role positions, the province was divided into four carbon-neutral sub-districts. At the same time, superimposed analysis of the main function zoning, the county area of the province was reconstructed into seven territorial space zones, and the differentiated regional low-carbon optimization development strategy was proposed for each zone.