With the rapid growth of foreign direct investment (FDI), PM2.5 pollution in Chinese cities is increasing. Based on panel data for 271 Chinese cities from 2003 to 2016, this paper uses the dynamic spatial fixed-effects Durbin model to analyze the correlation between FDI and PM2.5 pollution and the effect of FDI on urban PM2.5 concentrations, as mediated by industrial structure transformation, which is clarified using Stata/SE 16.0. The results showed that PM2.5 pollution in China has significant spatial spillover effects, and the pollution haven hypothesis is applicable to Chinese cities. The industrial structure partially mediates the relationship between FDI and PM2.5. This paper proposes that local governments should promote the market-oriented reform of FDI to create a more convenient, legalized, and international environment for FDI and innovate the governance philosophy of only reducing the existing emissions. A top-level design and sound market supervision system of PM2.5 control are also needed.

The contradiction between industrial economic development and the ecological environment in Northwest China is prominent, so the green transformation of industrial economy in this region is imperative. From the perspective of industrial ecology, this study uses economic and environmental statistics from Northwest China from 2006 to 2018 as well as the Krugman specialization index and entropy index methods to calculate the degree of different types of industrial agglomeration in Northwest China. The eco-efficiency of Northwest China is calculated by the global SBM-DDF model. On this basis, the stochastic effect panel tobit regression model is used to analyze the influence and mechanism of different types of industrial agglomeration on eco-efficiency in Northwest China. The results show that the concentration of specialization has a significantly negative effect on the eco-efficiency of Northwest China at the level of 1%. Excepting Ningxia, the eco-efficiency of other provinces has been improved with the decrease of industrial specialization. The influence of the related diversification agglomeration on the eco-efficiency in Northwest China shows a U curve. The degree of industrial correlation diversification in Qinghai and Ningxia is less than the critical value 1.45, whereas Shaanxi, Gansu, and Xinjiang have crossed the inflection point. The unrelated diversification agglomeration has a negative effect on the eco-efficiency of Northwest China at the level of 1%, and the degree of industrial independent diversification in Shaanxi Province has decreased slightly, which is beneficial to the improvement of eco-efficiency. By contrast, other provinces have increased considerably. The conclusion can provide a theoretical basis for industrial green transformation path selection and related policy formulation in Northwest China.

Southwest China is a fragile terrestrial ecosystem restricted by its geological background, which leads to a contradiction between its industrial economic development and the ecological environment. In this study, to explore the influence and mechanisms of the three industrial agglomeration modes, namely, specialization, related diversification, and unrelated diversification, on the eco-efficiency of the region, linear and nonlinear regression models were applied to the data of five Southwest provinces from 2006 to 2018. Specialization agglomeration had a significant negative impact on the eco-efficiency of four provinces outside Tibet in Southwest China. With the decrease of industrial specialization, their eco-efficiency improved. The effects of related diversification agglomeration on the ecological efficiency of four provinces outside Tibet in Southwest China showed a “U” curve. The degree of industrial diversification in these provinces exceeded the critical value of 1.46, and the effect on eco-efficiency was shown. The unrelated diversification agglomeration had a negative effect on the ecological efficiency of the four provinces outside Tibet in Southwest China. The degree of industrial-unrelated diversification in Guizhou Province increased slightly, which was not conducive to the improvement of local eco-efficiency. Additionally, it decreased significantly in other provinces, which caused the improvement of local eco-efficiency. The conclusion provides a theoretical basis for industrial green transformation path selection and related policy formulation in Southwest China.

In this paper, panel data from nineteen key cities in the Sichuan–Chongqing urban agglomeration from 2003 to 2016 were used as the study sample. Using the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model, the effect of foreign direct investment (FDI) on particulate matter (PM2.5) pollution and its action mechanism in the Sichuan–Chongqing urban agglomeration were considered for both socioeconomic and natural factors. The results showed that the “pollution halo” hypothesis of FDI in the Sichuan–Chongqing urban agglomeration has been supported. There are significant positive spatial spillover effects of PM2.5 pollution in this urban agglomeration, and the introduction of FDI is conducive to alleviating PM2.5 pollution in the urban agglomeration. Similar to the “inverted U” curve proposed by the environmental Kuznets curve (EKC) hypothesis, there was a significant “inverted U” curve relationship between PM2.5 pollution and economic growth in the Sichuan–Chongqing urban agglomeration. However, there was a significant “U”-type curve relationship between the urbanization degree and the PM2.5 concentration, which indicates that the current urbanization mode may aggravate the pollution degree of PM2.5 in the urban agglomeration in the long term. Furthermore, the two natural factors of annual average temperature and annual precipitation play an important role in PM2.5 pollution and spatial spillover effect in the Sichuan–Chongqing urban agglomeration. Economic development and rationalization of the industrial structure are the main ways by which FDI affects PM2.5 pollution in the urban agglomeration. The research conclusions of this study can be of great practical significance to optimize the regional industrial layout, control PM2.5 pollution, and establish a sustainable development policy system in the Sichuan–Chongqing urban agglomeration.

Air pollution caused by coal burning not only increases the cost of environmental pollution but also harms human health. It is urgent for China to change the practice of coal-fired central heating. Therefore, the effectiveness and sustainability of the Coal to Gas and Electricity policy have become the focus of all sectors of society. In this paper, eight cities in the Beijing–Tianjin–Hebei region were taken as the experimental groups and the other eleven cities as the control groups. Based on the PSM-DID model and the time-varying DID model, a quasi-natural experimental analysis was conducted to evaluate the effect of the policy of coal to gas and electricity to improve air quality in the Beijing–Tianjin–Hebei region from 2015 to 2020 and to test the sustainability of the policy. Three research conclusions are shown below: First, during the implementation of the policy, especially in 2019, the AQI index decreased significantly. Although there was a rebound thereafter, it was still lower than before. This shows that the Coal to Gas and Electricity policy has indeed improved the air quality in Beijing, Tianjin, and Hebei during its implementation. Second, the policy had a great impact on SO2 and PM10 but was relatively weak on PM2.5 and CO. Therefore, there is an urgent need to formulate scientific and accurate policies to control different air pollutants. Third, the time-varying DID model was used to identify the dynamic sustainability effect of the Coal to Gas and Electricity policy. The results showed that the policy had a strong impact in the initial stage, but its effect was greatly reduced at the end of the implementation or near the end, when it was far less obvious than in the initial stage of the policy. Therefore, in formulating relevant measures to reduce air pollution, it is necessary to fully consider the sustainability of the policy.

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Low-carbon cities have become a new trend in regional development around the world. Whether they can improve the environment in China, especially the air quality, remains to be tested. In this paper we take low-carbon city construction as a quasi-natural experiment and empirically test the net effects, influencing factors, and dynamic effects of low-carbon city construction on air quality by constructing a multistage propensity score matching and Difference-in-Differences model. After a series of robustness tests, the following conclusions are drawn: first, low-carbon city construction reduces the regional Air Quality Index, inhalable particulate matter, fine particulate matter, and NO2 concentrations. Among them, the construction effect in 2017 was the most significant. Therefore, it is necessary to continue to promote low-carbon city policies and accurately identify different types of air pollutants to improve the overall effectiveness of low-carbon city policies. Second, temperature, humidity, wind level, and other meteorological factors, as well as gross domestic product for the proportion of secondary industry, will affect air quality. Therefore, it is necessary to comprehensively consider meteorological, economic, social, and other influencing factors in an early stage of the construction of the next batch of low-carbon cities, so as to avoid falling into the trap of “building first and managing later”. Third, the impact of secondary industry on air quality is significantly greater than that of tertiary industry. Therefore, the upgrading of industrial structure promoted by low-carbon city policy is effective in improving air quality. Fourth, the construction of low-carbon cities in western China has the most significant impact on air quality improvement. Therefore, the joint prevention and control mechanism of air pollution control in urban agglomeration should be established.

In this paper, using panel data of 28 cities in the middle reaches of the Yangtze River from 2003 to 2020 as the research sample, we built a dynamic spatial Durbin model based on the STIRPAT (stochastic impacts by regression on population, affluence, and technology) model and conducted an empirical study on the impact of the coordinated agglomeration of manufacturing and producer services on particulate matter (PM) 2.5 pollution. The results show a significant positive spatial spillover effect of PM2.5 pollution in the middle reaches of the Yangtze River. The coordinated agglomeration of manufacturing and producer services in the urban agglomerations there is conducive to reducing PM2.5 pollution. Similar to the inverted-U curve of the classic environmental Kuznets curve hypothesis, there is a significant inverted-U curve relationship between PM2.5 pollution and economic growth in urban agglomerations in the middle reaches of the Yangtze River. The proportion of coal consumption, the proportion of secondary industry, and the urbanization level are significantly and positively correlated with PM2.5 pollution in urban agglomerations in this area. Technological innovation, environmental regulation, and annual average humidity play an important role in addressing the PM2.5 pollution and spatial spillover effect. Industrial structure and technological innovation are the main ways for the coordinated agglomeration of manufacturing and producer services to affect PM2.5. The research conclusion can be of great practical significance to optimize the regional industrial layout, control PM2.5 pollution, and establish a sustainable development policy system in the middle reaches of the Yangtze River in China.