Assessing of the county-level synergy between CO2 emissions and PM2.5 pollution in Shandong Province, China

Synergistic control of carbon dioxide (CO2) emissions and particulate matter (PM2.5) pollution can provide environmental, economic and health benefits. However, no literature explores the spatial differences in synergistic effects at the county level, which is not conducive to accurate decision-making and the effectiveness of synergistic management. Therefore, this paper quantifies the spatial differences of CO2 and PM2.5 synergy using the quadrant method, Tapio decoupling index, Spatial auto-correlation analysis, and geographically weighted regression model based on environmental, population (POP), and gross domestic product (GDP) data from 2016 to 2017, taking 137 counties and districts in Shandong Province as the study area. The results revealed that: (1) Only 32.12% of counties achieve a simultaneous decrease in CO2 emissions and PM2.5 concentrations. (2) Only 36 counties have achieved a strong decoupling of CO2 emissions from GDP and POP, and PM2.5 concentrations from GDP and POP. (3) There is a significant spatial auto-correlation in the spatial distribution of CO2 emissions and PM2.5 concentrations, and CO2 high-high clusters are obviously smaller in area than the PM2.5. (4) Spatial differences in the synergistic characteristics between CO2 and PM2.5 are roughly divided by Weifang and Linyi, with positive and negative shifts in the direction of synergy between counties on either side, and smaller differences in the degree of synergy between counties with similar geographical locations. Based on the results, this paper makes recommendations to improve the effectiveness of synergistic governance.