Air pollution in heterogenous Chinese cities: Complex network, novel driver and decoupling nexus

The study contributed to the existing researches by depicting the complex network and efficiency-related drivers of PM2.5 concentration, and by proposing two production-theoretical decomposition analysis (PDA)-based spatiotemporal decoupling models that incorporate efficiency-related factors in spatiotemporal decoupling analysis for the first time. We comprehensively used social network analysis, extended PDA and the proposed spatiotemporal decoupling models, to investigate the network and driver PM2.5 concentrations as well as the decoupling nexus with fiscal environmental expenditure (FEE) in a case of Chinese cities classified by population size and economic structure over 2007-2019. We found that first, the hierarchical network structure of PM2.5 concentration has been broken to a certain extent. Second, GDP per capita and potential intensity of PM2.5 to FEE (PPMI) were the largest positive and negative drivers to reduce PM2.5 concentrations. Third, the temporal and spatial decoupling relationships between FEE and PM2.5 were generally dominated by strong decoupling state and strong negative spatial decoupling states, respectively, where PPMI and FEE tendency were the positive drivers and significant heterogeneity of cities classified by economic structure and population size were found. The study highlights the importance of controlling air pollution by FEE according to local conditions.