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The per capita carbon balance and carbon compensation zoning of Chinese counties from the perspective of major function-oriented zones is important for realizing the carbon peaking and carbon neutral target. In this study, the Kernel-K-means++ algorithm is used and a more comprehensive per capita carbon compensation zoning model is constructed. Based on this, combined with the major function-oriented zones, Chinese counties are divided into per capita carbon compensation-type zones. Further, spatial and temporal characteristics are detected, and suggestions for optimizing low-carbon development are put forward. The main results are as follows: (1) From 2000 to 2017, the per capita carbon emissions (PCO₂) of Chinese counties were large and showed a trend of stable expansion and a southeast–northwest pattern; (2) the per capita carbon emissions of key development zones accounted for the largest proportion of emissions; (3) there were 1410 payment zones, 170 balanced zones, and 242 compensated zones among China’s counties; and (4) 11 types of carbon compensation space optimization zones were finally formed, and low-carbon development directions and strategies were proposed for each type of area. Based on this, this study promotes regional carbon emissions management and reduction in China and provides a reference for other regions to reduce emissions.