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The impact of air pollution is one of the hotspots attracting continuous scholarly attention, but the comprehensive statistical and visual analysis reviews are few. Employing the method of bibliometric analysis, this paper took the relevant literature from 1996 to April 2022 on the Web of Science as the research object. Through the methods of keyword co-occurrence analysis and burst analysis, the spatiotemporal evolution trend, cooperation network, outstanding scholars, knowledge base, and research focus of air pollution impact research are visually presented. Via constructing a common word matrix of high-frequency words, clustering analysis is used to aggregate high-frequency keywords into 24 clusters. By the strategic coordinate analysis method, the relationships within and between clusters were revealed. The main findings include (1) research on the impact of air pollution mainly focusing on human health; (2) the six keywords with the highest centrality are California, hydrocarbons, dioxide, generation, Asia, and diesel; (3) these 11 clusters may be developed into future research hotspots: particulate matter, nitrogen oxides, mortality, ozone, pollution, air quality, asthma, children, epidemiology, aerosols, and polycyclic aromatic hydrocarbons; and (4) seven topics are research hot: daily mortality, long-term exposure, coronary heart disease, concentration, North China plain, traffic-related air pollution, and air pollution., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Assessment of the health and economic impacts of PM2.5 pollution is of great importance for urban air pollution prevention and control. In this study, we evaluate the damage of PM2.5 pollution using Beijing as an example. First, we use exposure-response functions to estimate the adverse health effects due to PM2.5 pollution. Then, the corresponding labour loss and excess medical expenditure are computed as two conducting variables. Finally, different from the conventional valuation methods, this paper introduces the two conducting variables into the computable general equilibrium (CGE) model to assess the impacts on sectors and the whole economic system caused by PM2.5 pollution. The results show that, substantial health effects of the residents in Beijing from PM2.5 pollution occurred in 2013, including 20,043 premature deaths and about one million other related medical cases. Correspondingly, using the 2010 social accounting data, Beijing gross domestic product loss due to the health impact of PM2.5 pollution is estimated as 1286.97 (95% CI: 488.58-1936.33) million RMB. This demonstrates that PM2.5 pollution not only has adverse health effects, but also brings huge economic loss.

• A novel spatial general equilibrium model was constructed and the impact of air pollution on urban residents' welfare in China was studied. • Empirical study shows air pollution significantly reduces urban residents' welfare and migration cost reduces the negative impact of air pollution on the welfare of urban residents. • Policy suggestions suggested that air pollution should be balanced against the welfare of residents, and should not be cleaned up by "one size fits all" in the early stages of economic development. Air pollution and its effects are important issues of human society. However, few literatures on the effect of air pollution on urban residents' welfare considered the cost of migration. This paper constructs a novel spatial general equilibrium model and studies the impact of air pollution on urban residents' welfare in 274 cities at and above the prefectural level in China from 2007 to 2017, and investigates the role of migration costs. The theoretical analysis and empirical research show that air pollution has a significant negative impact on the welfare of residents. Further, the simulation results indicate that the reduction of migration cost and the improvement of air quality accounts for roughly 24.65% improvement of resident's welfare from 2007 to 2017 in China. Another conclusion is that there is an inverted U-shaped relationship between resident's welfare and air pollution. On another side, migration costs play a moderating role in the impact path of air pollution on residents' welfare. When the migration costs fall, it will help residents to move out of cities with poor air quality and improve the resident's welfare. The policy suggestions are as follows: (1) In the process of sustainable development, local governments need to coordinate the phased characteristics between air pollution and residents' welfare, effectively improve the livable degree of city and urban economic sustainability, and prevent the brain drain caused by excessive migration of residents. (2) Local governments should lower the migration costs between cities by deepening the reform of the household registration system, so as to promote the free flow of labor and ultimately improve the welfare of residents. [ABSTRACT FROM AUTHOR]

Under the background of climate change, the haze days in China have increased significantly, which seriously hinders the sustainable development of society and arouses wide attention from the public. However, the researches on the effect of air pollution on the stock yield of heavy pollution enterprise in key control cities are quite limited, This paper collects the Air Quality Index (AQI) from key control cities above prefecture level in China as well as the stock yield data of these cities’ heavy pollution enterprises in December from 2014 to 2016 and through multi-discontinuities regression model, testes the effect of air pollution on the stock yield of heavy pollution enterprise. The results show that: (1) Heavy air pollution (AQI = 300) has negative influence on the stock yield. (2) There exists time effect of air pollution on stock yield. Since the year 2014, heavy air pollution has exerted significantly negative influence on the stock yield in that 2013 may be the “first year” when the Chinese society began to take air pollution seriously. This paper gives a brief discussion on the cause of it and suggests that severe air pollution should be strictly controlled. Only by facing air pollution seriously, can we eliminate air pollution with collective wisdom and concerted efforts and achieve the sustainable development of city. Being the first study to look into the effect of air pollution on stock yield in key control cities in China, this paper provides empirical reference for government supervision departments, stock investors as well as enterprises. [ABSTRACT FROM AUTHOR]

To improve the air pollution of China fundamentally, effective measures should be proposed based on the thorough understanding of the characteristics of air pollution. Based on spatial econometrics, this paper investigates the characteristics and analyzes the determinants of the spatial concentration of PM pollution in China. Results show that: (1) PM pollution is highly concentrated in Central and Eastern China, covering 17 regions which accounts for 75% of the total population and GDP (gross domestic product). (2) The PM values in China show a significant spatial correlation. Provinces such as Shandong, Henan, Anhui, and Hubei are high in PM2.5 concentration. Meanwhile, these provinces are high in population density, GDP, and coal consumptions and have a large amount of civilian cars. (3) PM pollution shows spatial spillover effects. A 1% increase in the PM values of neighboring provinces will lead to a 0.78% increase in that of one province. (4) An upward U-shaped relationship is observed between the density of per capita GDP and PM, and the PM value is far from the turning point of growth. With the further growth of the density of per capita GDP, the PM value is expected to increase rapidly and continuously. (5) Based on the characteristics of spatial concentration and spatial spillover, this paper proposes several prevention-control measures for haze pollution, such as stressing on the treatment of air pollution in severely polluted provinces, avoiding moving pollution industries to neighboring areas, performing joint prevention and control nationwide. Air pollution may only be rooted by transforming the pattern of economic growth. [ABSTRACT FROM AUTHOR]

Regional planning plays an important role in controlling air pollution in urban agglomerations with spatial spillover characteristics. This paper empirically examines the control effect of the Development Plan for the City Cluster in the Yangtze River Delta (Plan). We first use a spatial autoregression (SAR) model to analyze the spatial and temporal effects of air pollution in 41 cities in the Yangtze River Delta (YRD) from 2011 to 2018. We then use a difference-in-difference (DID) model to investigate the implementation effect of the Plan. Finally, we combine the SAR and DID models and study the Plan 's spatial effect of pollution between cities. Our empirical findings reveal the spatial correlation of air pollution between cities in the YRD and show that the Plan has significantly reduced the annual average fine particulate matter (PM 2.5) concentration. This paper enriches the literature about effects of socio-economic plans and provides an empirical reference for collaborative management of air pollution in city clusters. • A spatial autoregression (SAR) model was used to analyze the spatial and temporal effects of air pollution. • The control effect of the Development Plan for the City Cluster in the Yangtze River Delta (Plan) was empirically examined. • Empirical findings reveal the Plan has significantly reduced the annual average fine particulate matter (PM 2.5) concentration. [ABSTRACT FROM AUTHOR]

• A dynamic general equilibrium model about air pollution in china was established. • Empirical impacts of environmental regulation on air pollution in china were analysed. • Reasons about recent decline in china's air pollution were provided. In recent years, the average concentration of PM 2.5 in China's air pollution has generally declined, but literature discussing reasons for the decline are scarce. This study provides an explanation of the reasons for the decline in China's air pollution through theoretical model construction and simulation. Firstly, a DGE (Dynamic General Equilibrium) model, including time and space dimensions, is used to describe the mechanism for energy structure adjustment and environmental regulation affecting air pollution in China. Secondly, the parameters of the theoretical model are adjusted for simulation. The simulation results show that the government environmental control has positive policy effect, both in reducing air pollution and in promoting economic growth, while energy structure adjustment only works in curbing air pollution. Further simulations found that the effectiveness of government environmental control depends on whether there are regional differences in policy implementation and the choice of policy paths. Thirdly, panel data from 286 cities at prefecture level and above in China from 2010 to 2018 verified the simulation. The empirical results verified the availability of government environmental control and energy structural adjustment in improving air quality. From the analysis of heterogeneity, the government environmental control showed better air pollution control effect in big cities, and the policy effect of government environmental control was gradually improving over time. The following policy implications are proposed: research on alternative energy sources, adjustment of energy structure, and the coordinated development of government environmental control in various regions are the main strategies for improving air quality. Adopting the "fast first and then slow" governance policy, designing the "north first and then south," and "heavy first and lighter" air pollution control measures can achieve better control effects. Figure 1 Research framework [Display omitted] [ABSTRACT FROM AUTHOR]

With the acceleration of industrialization and urbanization, the problem of air pollution in China has become increasingly serious. Particulate matter (PM) is a representative indicator of pollutants, and it is of great significance to carry out targeted treatment by studying its periodicity of concentration. In this paper, as a data mining information technology, the Empirical Mode Decomposition-Wavelet Analysis (EMD-WA) model is used to conduct a multi-scale periodic study of the PM 2.5 concentration time sequence in the Yangtze River Delta region in China and it is found that: (1) through the decomposition and reconstruction of the EMD-WA model, the period characteristics of four scales from short to long can be obtained, which are seasonal, short, medium and long period terms respectively; (2) the PM 2.5 concentration in the Yangtze River Delta region shows obvious multi-scale periodicity for the four scales, which includes a seasonal cycle of 46 days (about 1.5 months), a short cycle of 101 days (about 3.5 months), a medium cycle of 294 days (about 10 months), and a long cycle of 671 days (about 22.5 months), respectively. (3) The results are consistent in terms of season, short and middle cycle scales, in north (Jiangsu), east (Shanghai), south (Zhejiang) and west (Anhui) of the Yangtze River Delta region, but there are significant differences in the terms of long cycle scales. (4) The PM 2.5 concentration still shows obvious periodicity within 240 h during severe haze in the Yangtze River Delta region. This paper provides a framework for the government to make policies on energy conservation, emission reduction and air pollution control, and also provides a strong basis for haze prediction. [ABSTRACT FROM AUTHOR]

Under the premise that the total emissions of PM (particulate matter) of air pollution is established, the allocation of PM emission rights in various provinces of China is the feasible way to governance the ash haze. In this paper, a data envelopment analysis (DEA) model that takes into account the objectives of efficiency and equity is constructed. On the basis of evaluating the PM emission performance of various provinces in China, the corresponding allocation steps are put forward. Then, the results of the DEA model and information entropy are compared. The research shows that: (1) under the same constraint conditions, the emission right of PM is allocated with DEA model, which leads to lower cost, less fluctuation of distribution amount and higher overall national performance. (2) the population Gini coefficient method is used to evaluate and it is found that the Gini coefficient value is smaller according to the distribution results of DEA model, indicating that the PM emission right amount is more fairly distributed among provinces. The functions of this paper are as follows: (1) a new double-objective DEA model is constructed, which is suitable for multi-agent performance evaluation with multiple objectives; (2) a scheme to allocate PM among provinces is proposed, which can provide reference for the practice of haze reduction in China [ABSTRACT FROM AUTHOR]