According to the requirements of the Healthy China Program, reasonable assessment of residents’ health risks and economic loss caused by urban air pollution is of great significance for environmental health policy planning. Based on the data of PM2.5 concentration, population density, and urbanization level of 338 Chinese cities in the year of 2015, the epidemiological relative risk (RR) was adopted to estimate the negative health effects caused by exposure to PM2.5. Meanwhile, the Value of Statistical Life (VSL) and Cost of Illness (COI) methods were used to calculate economic loss. The results show that PM2.5 pollution remains serious in 2015, which brings about many people suffering from all kinds of fearful health problems especially premature death and related diseases. The mortality and morbidity increase dramatically, and the total direct economic loss related to PM2.5 pollution in 2015 was 1.846 trillion yuan, accounting for 2.73% of total annual GDP. In addition, there was a strong correlation between urbanization level and health risks as well as economic loss, which implies that people who live in highly urbanized cities may face more severe health and economic losses. Furthermore, 338 cities were divided into four categories based on urbanization level and economic loss, of which the key areas (type D) were the regions where an increase in monitoring and governance is most needed. In the process of urbanization, policy makers should pay more attention to health costs and regional differentiated management, as well as promote the construction of healthy cities more widely.
While the progress of China’s industrialization and urbanization has made great strides, atmospheric pollution has become the norm, with a wide range of influence and difficult governance. While many previous works on NOx pollution have been developed from the perspectives of natural science and technology, few studies have been conducted from social-economic points of view, and regional differences have not been given adequate attention in driving force models. This paper adopts China’s provincial panel data from 2006 to 2015, an extended STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model, and spatial econometric models to investigate the socio-economic influential factors and spatial-temporal patterns of NOx emissions. According to the spatial correlation analysis results, the provincial NOx emission changes not only affected the provinces themselves, but also neighboring regions. Spatial econometric analysis shows that the spatial effect largely contributes to NOx emissions. The other explanatory variables all have positive impacts on NOx emissions, except for the vehicular indicator (which did not pass the significance test). As shown through the estimated consequences of direct and indirect effects, the indicators have significant positive effects on their own areas, and exacerbate NOx pollution. In terms of indirect effects, only three factors passed the significant test. An increase in gross domestic product (GDP) and energy consumption will exacerbate adjacent NOx pollution. Finally, a series of socio-economic measures and regional cooperation policies should be applied to improve the current air environment in China.