Spatial-temporal correlation effects and persistent synergistic control benefits of fine particulate matter and carbon emissions in China.

The synergistic reduction of air pollutants and carbon dioxide (CO2) emissions is a key component in achieving China's strategy of pollution and carbon reduction. This study quantitatively evaluates the spatiotemporal linkages between PM2.5 and CO2 emissions, as well as the benefits of sustained synergistic control, across over 360 Chinese cities from 2005 to 2020. We employed spatiotemporal analysis, coupled coordinateness modeling, the Hurst index, and generalized linear mixed modeling (GLMM). The results indicate that PM2.5 concentrations decreased at an annual rate of 1.5 μg/m³/year from 2005 to 2020, while CO2 emissions increased at an annual growth rate of 2.3 × 10⁵ t/year (p < 0.05). Spatiotemporal association analysis revealed that the coupling degree of PM2.5 and CO2 emissions increased from 0.64 to 0.81, while the coordination degree decreased from 0.40 to 0.32, exhibiting significant latitudinal zonation and spatial clustering. In terms of synergistic control effectiveness, over 95% of the cities experienced "pollution reduction and carbon enhancement" during the study period, with no cities achieving simultaneous reduction of both PM2.5 and CO2 emissions. Further analysis of the persistence of synergistic control showed that as coupling and coordination levels increased, the city-specific synergistic control efficiency index (CI) decreased. Notably, 86.3% of cities showed persistent trends in their future CIs. The GLMM regression results suggest that the effective integration of scientific and technological innovation, infrastructure development, and economic growth will be pivotal in advancing the successful implementation of China's pollution and carbon reduction strategy.