Owing to global climate change and increased environmental pollution, China faces the dual responsibility of reducing CO₂ emissions and controlling PM_2.5 pollution. This study compares the spatial characteristics of PM_2.5 concentrations and CO₂ emissions using 10 km × 10 km grid data. The increase and decrease of CO₂ emissions and PM_2.5 concentrations are divided into four quadrants, which indicates four different conditions. Then, spatial autocorrelation method is conducted to analysis the spatial relationships. The empirical results show that (1) In the four quadrants, the increase of CO₂ emissions and the decrease of PM_2.5 concentrations accounted for the highest proportion (25.9%). (2) The spatial differences in CO₂ emissions are large, but the PM_2.5 concentrations show strong spatial aggregation. (3) China’s three major urban agglomerations contain more than half of the areas in which both CO₂ emissions and PM_2.5 concentrations increased, and the Pearl River Delta urban agglomeration exhibits the best synergistic reduction effect. By contrast, the Beijing–Tianjin–Hebei urban agglomeration has the worst synergistic reduction of CO₂ emissions and PM_2.5 concentrations. (4) At the urban level, as a typical city in the Beijing–Tianjin–Hebei urban agglomeration, Tianjin's overreliance on heavy chemical industries has led to co-increases in its CO₂ emissions and PM_2.5 concentrations. Shaoxing and Jiangmen, in the Yangtze River Delta and Pearl River Delta urban agglomeration, are among the few cities where CO₂ emissions and PM_2.5 concentrations have both been reduced. Finally, this paper suggests some policy implications of these findings.