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Air pollution poses a great danger to human health and economic development, and understanding people's willingness to pay for improved air quality (WTPA) impacts environmental protection. This paper investigates WTPA based on the perspective of subjective well-being (SWB) and analyzes the mediating role of social interaction on the relationship between the two. This paper distinguishes social interactions into online and offline interactions and analyzes whether the mediating effect of the two different interactions on SWB and WTPA exists separately. Using data from the 2018 China General Social Survey (CGSS), we find that SWB has a significant positive effect on WTPA, individuals with higher well-being have higher pro-environmental willingness; there is no age, education level, sex of the person, or regional heterogeneity in the effect of SWB on WTPA; offline social interactions play a partially mediating role between SWB and WTPA, while online social interactions failed to mediate between the two. This paper's policy implication is that improving residents' subjective well-being is both an important development goal and an essential way to resolve the conflict between economic development and environmental protection. [ABSTRACT FROM AUTHOR]

Imported air pollution has a significant impact on urban air quality. Relevant studies have shown that many urban air pollution events are not resourced by local emissions but are imported by air pollution from surrounding areas transported across regions. The prevention and control of air pollution is very necessary. However, the existing supervision of urban air quality mostly relies on ground monitoring stations, which are extremely limited in time and space, and cannot satisfy continuous time-space air pollution research. Therefore, aiming at the problem of urban air pollution control, this paper used MERRA-2 reanalysis data and ground monitoring data to establish a "Time-Longitude-Latitude" three-dimensional pollution curve, and then a genetic algorithm was used to optimize its fitting. This study finally reconstructed the imported air pollution transmission route. This paper takes an air pollution event that occurred in Xuzhou City, China, on 12 January 2020, as an example. Through the analysis of aerosol optical depth (AOD), particulate matter (PM), wind speed, and other factors, we found the source, transmission route, and impact time of this pollution. We have verified the correctness and accuracy of the reconstructed contamination transport paths. It is proved that the method is universal and it can quickly and accurately restore the air pollution transmission route and identify the urban imported air pollution transmission entrance. This method will also provide strong data support for the division of responsibilities of environmental protection departments in various regions for severe air pollution transmission events and provide effective governance ideas for the prevention and control of imported air pollution in recipient cities. [ABSTRACT FROM AUTHOR]

Affected by the epidemic and other factors, the global economy is in a downturn, and countries around the world are under unprecedented debt pressure. How will this affect environmental protection? Taking China as an example, this paper empirically studies the impact of changes in local government behavior on urban air quality under fiscal pressure. This paper uses the generalized method of moments (GMM) to find that fiscal pressure has significantly reduced PM2.5 emissions, with a unit increase in fiscal pressure will increase PM2.5 by about 2%. The mechanism verification shows that three channels affect PM2.5 emissions: (1) fiscal pressure has prompted local governments to relax the supervision of existing pollution-intensive enterprises. (2) Local governments reduce environmental regulations for attracting more pollution-intensive enterprises. (3) Local governments tend to reduce environmental protection investment to save fiscal expenses. The paper's conclusions provide new policy ideas for promoting environmental protection in China, as well as served as a case for analyzing current changes in environmental protection in other countries. [ABSTRACT FROM AUTHOR]

This paper studies the relationship between the coal-to-gas program and air pollution in China and provides micro-evidence of the mechanism from the perspective of households. Using daily air pollution and meteorological data between January 1, 2016, and January 1, 2020, we assessed the effect of the coal-to-gas program on air pollution by introducing the regression discontinuity designs in time (RDiT). We found that the coal-to-gas program significantly improved air quality and brought significant economic benefits. In the short term, the coal-to-gas program can lead to more than 10 units of reduction in SO2, PM2.5, and AQI in the treatment group, while it can lead to more than 50 units in the long term. Using the difference-in-differences approach, we found that the coal-to-gas program has significantly reduced air pollution. Combined with the micro-panel data of the China Health and Retirement Longitudinal Study from 2011 to 2018, we found that the coal-to-gas program changes the household heating energy choices and that the probability of coal-fired heating of households in pilot areas is decreasing. The study suggests that non-clean energy in households should be further replaced to continue improving air quality. [ABSTRACT FROM AUTHOR]

To cope with the coronavirus disease (COVID-19), national or sub-national regions have carried out many powerful anti-pandemic measures such as locking down, which may improve their regional air quality. This paper examines the relation between regional air pollution and work resumption from a novel post-pandemic perspective. Using a unique panel dataset on China's detailed industrial electricity consumption, this paper does not find a positive relation between post-COVID-19 work resumption and regional air pollution during China's early-stage recovery. This result is obtained after controlling for province and date fixed effects, as well as local weather conditions. However, the positive relations are found in a particular sub-sample of large industrial enterprises and a particular sub-sample of April. These findings indicate that large industrial enterprises may recover first, and the resumption is progressing gradually. Finally, several policy implications are provided, which are essentially helpful for other countries' post-pandemic recovery. [ABSTRACT FROM AUTHOR]

Public investments in subway systems are often motivated by improving local air quality. Recent studies, however, have reached different conclusions on the air quality benefits of subway investment. To reconcile these findings, this paper examines the air quality effects of all 359 subway line openings in China between 2013 and 2018. The machine learning method adopted in this paper substantially improves the consistency and precision of the estimates by purging seasonality, volatility, and the nonlinear effects of meteorological conditions in air quality data. The empirical results suggest an insignificant short-term effect and a significant long-term effect, which is expected as the adjustment of commuting mode takes time. Using the causal forest approach, the heterogeneity analysis find that a city that is experiencing rapid economic growth from a lower income level and currently has fewer subway lines is more likely to experience statistically significant improvements in air quality from a subway opening. These findings help reconcile the different findings in the literature and shed light on air pollution reduction as one of the objectives of public transit investment. [ABSTRACT FROM AUTHOR]

Protecting people from air pollution is an important task for developing countries. Over the past several decades, different types of policies have been enacted in developing countries to improve air quality, with policy impact analysis being conducted as well. As for China, while there is some existing literature on the impact of short-term action on air quality, there is much less research to investigate the roles of long-term air quality control mechanism on air quality change. This paper uses the "2 + 26" city cluster in China as a case study area to particularly analyze the roles played by short-term campaigns that compose the Winter Action Plan and a long-term mechanism referred to as the environmental accountability system in pollution control. Based on econometric and descriptive statistical analyses, it is found that the implementation of the Winter Action Plan has significantly improved the air quality, and the environmental accountability system seems to have exerted an impact, as cities with better air quality appear to establish a more stringent environmental accountability system. The paper provides the following insights for other developing countries: short-term campaigns can quickly reduce pollution and protect human health, while long-term mechanisms are needed to ensure sustainable environmental protection. [ABSTRACT FROM AUTHOR]

The influence of machine learning technologies is rapidly increasing and penetrating almost in every field, and air pollution prediction is not being excluded from those fields. This paper covers the revision of the studies related to air pollution prediction using machine learning algorithms based on sensor data in the context of smart cities. Using the most popular databases and executing the corresponding filtration, the most relevant papers were selected. After thorough reviewing those papers, the main features were extracted, which served as a base to link and compare them to each other. As a result, we can conclude that: (1) instead of using simple machine learning techniques, currently, the authors apply advanced and sophisticated techniques, (2) China was the leading country in terms of a case study, (3) Particulate matter with diameter equal to 2.5 micrometers was the main prediction target, (4) in 41% of the publications the authors carried out the prediction for the next day, (5) 66% of the studies used data had an hourly rate, (6) 49% of the papers used open data and since 2016 it had a tendency to increase, and (7) for efficient air quality prediction it is important to consider the external factors such as weather conditions, spatial characteristics, and temporal features. [ABSTRACT FROM AUTHOR]

This paper aims to detail the relationships between urbanization, industrialization, the innovation ability of cities and local air quality in 284 cities in China using annual data. For the empirical outputs, the panel quantile regression analysis, which considers the heterogeneous nature of the data set, is employed. Initial findings indicate that (i) urbanization and industrialization negatively affect local air quality. (ii) Innovation capability of cities has a direct and improving impact on local air quality. Then, the paper estimates the moderating role of cities' ability to innovate in the polluting effect of urbanization and industrialization on local air quality. Remarkably, empirical evidence indicates that (iii) the innovation ability of cities also moderates the polluting impact of urbanization and industrialization on local air pollution. Based on the findings, the paper confirms the importance of both direct and moderator effects of the innovative environment in cities in tackling air pollution. [ABSTRACT FROM AUTHOR]

With rapid urbanization, the economic agglomeration within cities is associated with severe air pollution. Urban spatial structure adjustment has been recognized as an effective strategy for improving air quality. However, the research on how to mitigate air pollution originating from economic agglomeration through urban spatial structure adjustment is unclear. Therefore, based on panel data for municipal cities in the Yangtze River Delta (YRD) region during 2008–2018, this study empirically tests the transmission mechanisms among economic agglomeration, urban spatial structure, and air pollution. We use the combination of the social network analysis (SNA) and two-stage least squares (2SLS) methods to verify the effect of economic agglomeration on air pollution. Economic agglomeration's indirect effect on air pollution through urban spatial structure is further tested using mediating effect model and cross-section comparisons. When exploiting an exogenous order rank of node city importance for instrument variable (IV), our finding shows that increasing economic agglomeration by 10% increases air pollution by 12%. In addition, in market forces, monocentricity brings about economic agglomeration's pollution effect, while polycentricity leads to agglomeration's environmental benefits improvement. However, a government-led exogenous polycentricity greatly mitigates economic agglomeration's pollution effect, while in cities with monocentricity, agglomeration slightly increases air pollution. Compared with market power, our paper stresses government intervention in promoting urban spatial structure in terms of polycentric development could be more helpful for improving agglomeration's environmental benefits in China's YRD region. [ABSTRACT FROM AUTHOR]

Foreign direct investment and environmental pollution have been a prominent topic in China's economic development. Therefore, this paper investigates the relationship between foreign direct investment and environmental pollution, and makes practical policy recommendations to support the harmonious development of economy and environment based on the study findings. In this paper, the spatial econometric approach framework with the spatial weight matrix of the Delaunay method is used to examine the influence of foreign direct investment on the level of urban air quality. It uses air quality index as an indicator to measure air pollution comprehensively. Based on the spatial autocorrelation with the aggregation and radiation effects of foreign direct investment, the results show that the distribution of air pollution has considerable spatial impact in terms of spatial nonequilibrium. Through the empirical analysis, our finding reveals that the increase in GDP, the share of secondary industry, and population growth are the important elements affecting the change in air quality. [ABSTRACT FROM AUTHOR]

This paper examines the effects of interventions to reduce air pollution during two international events on air quality in Beijing and its neighbor cities. Air quality data were gathered from China's Ministry of Environmental Protection, meteorological data from the China Meteorological Administration and economic data from the China Statistical Yearbook. The paper uses fixed-effect panel data models to empirically evaluate air quality improvement in Beijing and other affected cities before, during, and after the 2008 Olympic Games and the 2014 Asia-Pacific Economic Cooperation summit. Results show substantial improvement in air quality in Beijing and neighboring cities during the two events. However, some of the air quality improvement achieved reverted within a year after the games and within a week after the summit. Furthermore, the improvement achieved during the summit completely reverted and air quality deteriorated severely five days after the summit. It is also found that air quality in China, at least in the cities included in this study, gradually improved over the past 15 years or so. The findings suggest that sustainable interventions and incentive-based programs to reduce emissions from industry production and traffic are the key to maintaining the air pollution reduction achieved during the events. [ABSTRACT FROM AUTHOR]

Background: Air pollution is an important factor affecting residents' health. Methods: Based on the health data of 9959 residents from 28 provinces in China in the 2017 Chinese General Social Survey (CGSS), this paper uses a hierarchical linear model (HLM) to scientifically analyze the impact of air pollution on residents' health and to explore the moderating role of air pollution in various factors influencing residents' health. Results: Air pollution has significant negative effects on residents' health (coef. −0.103, p < 0.01), while frequency of exercise (coef. 0.070, p < 0.01), education level (coef. 0.012, p < 0.1) and income level (coef. 0.383, p < 0.01) have positive effects on residents' health. Air pollution has a negative moderating effect on the positive impact of exercise frequency on residents' health (coef. −0.015, p = 0.004). Conclusions: Air pollution causes serious damage to residents' health and it is necessary to control air pollution. Increasing residents' income, education level and exercise frequency can help improve residents' health level. Air pollution significantly reduce the positive impact of exercise frequency on residents' health. In order to effectively improve their own health, it is a better choice for residents to exercise when the air quality is good. [ABSTRACT FROM AUTHOR]

In China, blue sky defense is a crucial part of ecological environment governance. Objective environmental governance performance needs to be perceived by the public to more truly affect the public's evaluation of the government's environmental governance. This paper focuses on the public's subjective perception of air pollution and evaluation of the local government's environmental governance. Based on the Chinese General Social Survey data, the matched economic indicators, and air pollution data, we conduct a diachronic study on the public's evaluation of local governments' environmental protection work, and we analyze the relationship between the subjective perception of air pollution, the objective air pollution data, and the evaluation of local governments' environmental protection work. The results showed the following: (1) People's evaluation of local governments' environmental protection work significantly improved from 2013 to 2021. The objective indicator improved, while the subjective perception declined. (2) The subjective perception of air pollution has a significant negative impact on the evaluation of local governments' environmental protection work and needs to be better considered to improve air quality. At the same time, the effect of the objective indicator is insignificant. [ABSTRACT FROM AUTHOR]

Large-scale air pollution has an impact on the health and travel of residents in China. First, this article uses the gravity model and finds that China's air quality presents a typical spatial correlation network. The network structure has changed from complex to simple, indicating that China's air quality is gradually improving. Second, this paper uses spatial simultaneous equations to study the effect of air quality on residents' health. The results show that an increase in the air quality index of local and surrounding provinces will have a significant impact on the health of residents. The absolute and relative air quality affects the lives of residents. The decline in the health of residents from the previous period will prompt the government to adopt various pollution reduction policies, which will improve air quality in the current period. Based on the empirical research conclusions, this article makes policy recommendations. [ABSTRACT FROM AUTHOR]

Air pollution is an important factor affecting human health and daily life. The Chinese government is making vigorous efforts to control air pollution. The upgrading of the industrial structure is a problem-solving tool in the environment and economic growth cases. This paper aims to explore the relationships among environmental regulation, the upgrading of the industrial structure and air pollution. The PVAR (Panel Vector Auto Regression) model and moderating effect model are used to conduct empirical analysis based on panel data of 30 provinces in China from 2004 to 2020. The analysis of the results provides the following findings. Firstly, environmental regulations can significantly reduce emissions, but the deterioration of air quality does not have a significant impact on the improvement of environmental regulations. Secondly, industrial structure upgrading can reduce air pollution, but the worsening of the air quality will hinder the upgrading of industrial structures. Thirdly, environmental regulation can promote industrial structure upgrading. Lastly, industrial structure upgrading is a moderating variable and can positively moderate the impact of environmental regulations on air pollution. [ABSTRACT FROM AUTHOR]

To deal with severe air pollution arising from rapid development, a series of air pollution control policies have been implemented in China. Previous literature has explored the short-term economic impacts of air pollution control, but the long-term economic impacts, which can better reflect the effectiveness of air pollution control, have received less attention. This paper has constructed an integrated assessment framework combining a multi-sectoral computable general equilibrium (CGE) model, air quality estimation module, and health impact module, to explore the short-term (2016) and long-term (2030) impacts of air pollution control on China's economy, by setting 2015 as the base year. The possible future air pollution reduction scenarios were set based on the Thirteenth Five-Year Plan (FYP13) proposed by the Chinese government. Our results have shown that air pollution control would harm China's economy and such adverse effects would be increased by stricter pollution reduction targets. Taking the health benefits of air pollution control into account can effectively alleviate the GDP losses, and even reverse them into economic benefits in the long term. Compared with business-as-usual (BAU) scenario (no policy constraints on SO2 and NOx emissions), the impact of air pollution control on GDP in the TAC_VIII scenario (emission reduction targets of 20% for SO2 and NOx are set every five years after 2015) would change from a loss of 1.20% in 2016 to an increase of 0.28% in 2030. Our results can provide policy implications for the optimization of China's air emissions control in the future. [ABSTRACT FROM AUTHOR]

This paper estimates the causal effect of air pollution on firm innovation based on a nationwide sample of Chinese manufacturing firms. Using thermal inversion as instrument variable (IV), we demonstrate that air pollution significantly hurts firm innovation performance: a 1% increase in air pollution (PM2.5) in the past year, from its mean value, amounts to a 1.5% decrease in the number of invention patents compared to the average between 1999 and 2013. We also provide the casual estimate using regression discontinuity design (RDD) by exploiting the exogenous variation in pollution level caused by China's Huai River policy: the decrease in firms' invention patents is approximately 2.2% in the regions north of the Huai River Line. The underlying mechanism analyses reveal that poor air quality has detrimental effects on labor productivity, firms' human capital accumulation, and financing ability. These findings highlight the substantial costs associated with air pollution, which are greater than previously thought, as it hinders innovation, a crucial driver of long-term economic growth. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Governments have implemented many regulations to solve traffic congestion and pollutant emissions. Traffic restriction (TR) policy is the most common and widely used traffic regulation. However, it is difficult to alleviate traffic pollution through TR policies. Only a few studies focus on TR policies in multiple cities. In this paper, we classify traffic restrictions by geographical factors and evaluate the impact of different policies based on PSM-DID first. Then, we classify the mixed restrictions and test their effects on air pollution. The results show that TR policy improves air quality regardless of the season. Moreover, the effect of TR policy is not affected by the superposition of the type of traffic restriction. For cities implementing the same TR policy, geographic factors can lead to different outcomes. This finding provides a reference for governments in reducing air pollution. • Traffic restrictions significantly affected air quality in different regions of China. • Cities implemented traffic restrictions have improved air quality in adjacent cities. • Effect of traffic restrictions does not depend on the number of mixed restrictions. [ABSTRACT FROM AUTHOR]

Although the PM2.5 concept was put forward in 1997, it came into Chinese people's sight in 2011, and became a household name in 2013 in China. Previous studies did not involve this indicator, so we need to re-examine and compare the effects of objective air quality data and subjective perception on Life satisfaction (LS). The data were collected from Xi'an, a megacity of Northwest China. Particles smaller than 2.5 μm in diameter (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and Air quality index (AQI) acquired from air quality stations were used to calculate pollutant concentrations near the vicinity of subjects' home by Geographical information system (GIS) software. In this paper, the ordinal logistic regression models are used to explain ratings of LS in terms of the objective air pollution data, social and economic variables. The results indicate that the objective air pollution data has significant and negative effects on LS of the surveyed respondents. However, when the subjective perception of air pollution is considered in the regression models, it shows that the subjective perception of air pollution has a significant negative impact on LS, while the effects of PM2.5, NO2, SO2, and AQI on the LS become insignificant. Furthermore, the research significances and policy suggestions are discussed in this paper. [ABSTRACT FROM AUTHOR]

Previous papers that study the relationship between air pollution and happiness have not paid much attention to subjective air pollution. This paper attempts to explore the influence of subjective air pollution on happiness, the heterogeneity of the effects, and people's subjective willingness for improving air quality. We match the data of Chinese General Social Survey with local air quality and mainly based on the method of regression discontinuity. Our study shows that the public's subjective air pollution perception has significant negative effects on their happiness. The negative effects on happiness of unhealthy people and middle-aged/old people are greater than that of healthy people and young people. Moreover, residents who are relatively vulnerable to the harm of air pollution appear to be more willing to pay for the improvement of air quality. These results indicate that in order to improve air quality more rationally and effectively, not only should the government concentrate on the improvement of objective air quality but also pay attention to the public's subjective feelings, as well as taking the subjective needs of local residents into consideration in the process of air pollution control. [ABSTRACT FROM AUTHOR]

Social lockdowns improved air quality during the COVID-19 pandemic. Governments had previously spent a lot of money addressing air pollution without success. This bibliometric study measured the influence of COVID-19 social lockdowns on air pollution, identified emerging issues, and discussed future perspectives. The researchers examined the contributions of countries, authors, and most productive journals to COVID-19 and air pollution research from January 1, 2020, to September 12, 2022, from the Web of Sciences Core Collection (WoS). The results showed that (a) publications on the COVID-19 pandemic and air pollution were 504 (research articles) with 7495 citations, (b) China ranked first in the number of publications (n = 151; 29.96% of the global output) and was the main country in international cooperation network, followed by India (n = 101; 20.04% of the total articles) and the USA (n = 41; 8.13% of the global output). Air pollution plagues China, India, and the USA, calling for many studies. After a high spike in 2020, research published in 2021 declined in 2022. The author's keywords have focused on "COVID-19," "air pollution," "lockdown," and "PM25." These keywords suggest that research in this area is focused on understanding the health impacts of air pollution, developing policies to address air pollution, and improving air quality monitoring. The COVID-19 social lockdown served as a specified procedure to reduce air pollution in these countries. However, this paper provides practical recommendations for future research and a model for environmental and health scientists to examine the likely impact of COVID-19 social lockdowns on urban air pollution. [ABSTRACT FROM AUTHOR]

Adapting to the situation of one principal versus several agents, the Relative Performance Evaluation (RPE) is an effective incentive tool to motivate subordinates. The Chinese central government has adopted RPE to combat intractable air pollution, which is the Urban Air Quality Ranking (UAQR) system. This study uses a series of econometric methods including regression discontinuity design to examine its effectiveness in environmental governance. The results show that (1) since the implementation of UAQR, the overall air quality of cities has improved; (2) air quality of the bottom 3 cities in the ranking will improve in the coming month compared with their counterparts; (3) while top 3 cities in the ranking do not experience such change in air quality. Therefore, this paper argues that the activating based RPE does not stimulate effective competition, whereas competency based RPE does. UAQR with credible incentive commitment can be a useful measure to motivate local authorities to strengthen air pollution reduction. In this study, the results of the empirical analysis enrich the theoretical framework of RPE, and an innovative theoretical framework is adopted to explain the UAQR system. However, as a top-down environmental monitoring system, such ranking institution could mainly eliminate centralized discharged pollutants. A sound judicial system is the fundamental guarantee for sustainable development. [ABSTRACT FROM AUTHOR]

This paper probes the impact and working mechanism of e-commerce development on prevention and control of SO2 air pollution in cities in China. The research reveals that, first, e-commerce development can significantly reduce the SO2 air pollution degree in cities in China, which helps improve air quality, and compared with e-commerce services, an e-commerce application is more effective at reducing SO2 air pollution degree and improving air quality. Second, e-commerce development can significantly reduce SO2 emissions in cities in China, decreasing SO2 emissions per unit of gross domestic product (GDP) of cities. Compared with e-commerce services, an e-commerce application has a greater effect on reducing SO2 emissions in urban unit GDP. Finally, by reducing SO2 emissions in cities in China, e-commerce can reduce SO2 emissions in unit GDP, reducing SO2 air pollution degree and improving air quality, and in comparison with e-commerce services, an e-commerce application can reduce SO2 emissions in city unit GDP more significantly, thus significantly reducing SO2 air pollution degree and improving air quality in cities in China. [ABSTRACT FROM AUTHOR]

Ever since China's "housing reform" in 1998, the level of real estate investment in its cities has continued to rise, leading to the occupation of green space, rapid population concentration, and a severe mismatching of financial resources. At the same time, urban air quality has changed drastically for the worse, with PM2.5 becoming the primary air indicator of concern for many cities in recent years. The existing literature has obtained sufficient results on the influence factors of air pollution, but rarely presents the relationship between real estate investment and air pollution, especially using multiple cities as the sample. This paper thus examines the impact of real estate investment on air quality using a sample of 261 prefecture-level cities in China over the period 1999–2016 through several econometric models. First, the two-way fixed-effect model shows an inverted U-shaped relationship between PM2.5 concentration and real estate investment, but most cities have not yet crossed the turning point, and that real estate investment negatively impacts air quality. Second, the indirect effect of real estate investment on PM2.5 concentration comes from its non-linear impact on urban green coverage, population density, and industrial structure, which has been verified by Hayes and Preacher's (Behav Res 45:627–660, 2010) mediation effect with non-linear forms. Third, heterogeneity analysis indicates that an inverted U-shaped relationship also exists in the subsamples, and that real estate investment in cities with more people, higher GDP, and greater development level is more likely to increase rather than mitigate air pollution. Therefore, cities should promote the green development of real estate and related industries by enhancing environmental awareness, guide the population flow toward the coordinated development between real estate investment and population distribution, and encourage environmentally friendly technological progress via a better rational allocation of financial resources. [ABSTRACT FROM AUTHOR]

This paper presents a simultaneous equation, knowledge and perception-based averting behavior model of health risk caused by air pollution, with application to the Jinchuan mining area, China. Three types of averting behavior are distinguished: (a) purchases of purifying equipment, plants, or masks; (b) purchases of preventive or curing medication or food; and (c) adjustment of daily outdoor activities. Two types of perceived health risk are distinguished: (a) risk due to the intensity of exposure and (b) risk caused by the hazardousness of pollutants. The estimations show that an increase in perceived air pollution of two or more days a week leads to a restriction of outdoor activities of approximately 90 min per person per week. Another result is that the average annual household expenditure on air filters, foods, or medicines is 206.25 CNY (US$ 31.73) to prevent the hazardousness of air pollution. The total willingness to pay for air quality improvement is 2.95% of annual net household income. Because air quality improving investments can only be implemented in the medium or long run, daily disclosure of air quality is an adequate short-run policy handle to assist residents to take the right kind and level of risk-reducing actions. [ABSTRACT FROM AUTHOR]

Air pollution affects climate change, food production, traffic safety, and human health. In this paper, we analyze the changes in air quality index (AQI) and concentrations of six air pollutants in Jinan during 2014–2021. The results indicate that the annual average concentrations of PM10, PM2.5, NO2, SO2, CO, and O3 and AQI values all declined year after year during 2014–2021. Compared with 2014, AQI in Jinan City fell by 27.3% in 2021. Air quality in the four seasons of 2021 was obviously better than that in 2014. PM2.5 concentration was the highest in winter and PM2.5 concentration was the lowest in summer, while it was the opposite for O3 concentration. AQI in Jinan during the COVID epoch in 2020 was remarkably lower compared with that during the same epoch in 2021. Nevertheless, air quality during the post-COVID epoch in 2020 conspicuously deteriorated compared with that in 2021. Socioeconomic elements were the main reasons for the changes in air quality. AQI in Jinan was majorly influenced by energy consumption per 10,000-yuan GDP (ECPGDP), SO2 emissions (SDE), NOx emissions (NOE), particulate emissions (PE), PM2.5, and PM10. Clean policies in Jinan City played a key role in improving air quality. Unfavorable meteorological conditions led to heavy pollution weather in the winter. These results could provide a scientific reference for the control of air pollution in Jinan City. [ABSTRACT FROM AUTHOR]

The low efficiency of environmental policy implementation is an important issue in China's environmental governance. The Environmental Protection Interview (EPI) policy is an administrative means for the central environmental protection department to urge local governments to earnestly fulfill their environmental protection responsibilities. This paper takes China's EPI policy as a quasi-natural experiment. We use panel data of 261 prefecture-level cities in China from 2009 to 2018 as research sample and use spatial difference-in-differences (SDID) model to investigate the effect and mechanism of EPI policy on air pollution. The results show that EPI policy can effectively improve air quality, EPI policy has obvious spatial spillover effects. Namely, the EPI policy can not only reduce the local air pollution, but also reduce the air pollution in neighbouring cities. The EPI policy reduces the air pollution in the neighbouring cities within a spatial attenuation boundary of 400 km.The results of mechanism test show that the EPI policy can improve air quality by promoting industrial structure upgrading and technical advancement. Moreover, the pollution reduction effect of EPI is more significant in resource-based cities. The research results of this paper provide important reference for China and other developing countries to improve air quality. [ABSTRACT FROM AUTHOR]

There is limited evidence concerning the association between air pollution and different outpatient visits in moderately polluted areas. This paper investigates the effects of moderate-level air pollution on outpatient visits associated with six categories of clinic department. We analyzed a total of 1,340,791 outpatient visits for the pediatric, respiratory, ear-nose-throat (ENT), cardiovascular, ophthalmology, and orthopedics departments from January 2016 to December 2018. A distributed lag nonlinear model was used to analyze the associations and was fitted and stratified by age and season (central heating season and nonheating season). We found SO 2 had the largest effect on pediatrics visits (RR = 1.105 (95%CI: 1.090, 1.121)). Meanwhile, PM 2.5 and SO 2 had greater effects on ENT visits for people under 50 years old. The results showed a strong association between O 3 and cardiovascular outpatient visits in the nonheating season (RR = 1.273, 95% CI: 1.189,1.358). The results showed every 10 μ g / m 3 increase in SO 2 was associated with a lower number of respiratory outpatient visits. Significant different associations were observed in PM 2.5 , NO 2 , CO, and O 3 on ophthalmology visits between the heating and nonheating seasons. Although no significant association has been found in existing studies, our findings showed PM 2.5 and NO 2 were significantly related to orthopedic outpatient visits for people under 60 (RR = 1.063 (95%CI: 1.032, 1.095), RR = 1.055 (95%CI: 1.011, 1.101)). This study also found that the effect-level concentrations of air pollutants for some clinic departments were lower than the national standards, which means that people should also pay more attention when the air quality is normal. [ABSTRACT FROM AUTHOR]

Air pollution emissions can exceed the environmental self-purification capacity and trigger hazardous meteorological events, which have non negligible impacts on all aspects of society. The aim of this paper is to study the relationship between China's manufacturing industry benefits and air quality, taking into account the role of government policies in the era of big data, and to study the change points in the time series relationship between industry benefits and air quality. First, we apply and analyze big data and estimate values based on the maximum deviation method. Then, gray relational analysis is used to identify change points, which occur in 2005 and 2010 for both industry benefits and air quality. The total study period is divided into three subperiods: 1998–2005, 2006–2010, and 2011–2017. We find that air pollution control policy was relatively extensive from 1998 to 2005, and that there was a negative relationship between air quality and manufacturing industry benefits. From 2006 to 2010, a positive relationship gradually appeared and, since 2011, with the popularization of big data technology in policy making and environmental governance, intergovernmental cooperation has deepened and manufacturing enterprises have been more actively involved in governance. Consequently, the positive relationship between air quality and the comprehensive benefits of the manufacturing industry has remained stable. Finally, suggestions for policy makers and manufacturing companies are made from the perspectives of system construction, integration, and differentiation, big data challenges, and enterprise innovation. [ABSTRACT FROM AUTHOR]

With the development of industry, air pollution has become a serious problem. It is very important to create an air quality prediction model with high accuracy and good performance. Therefore, a new method of CT-LSTM is proposed in this paper, in which the prediction model is established by combining chi-square test (CT) and long short-term memory (LSTM) network model. CT is used to determine the influencing factors of air quality. The hourly air quality data and meteorological data from Jan. 1, 2017 to Dec. 31, 2018 are used to train the LSTM network model. The data from Jan. 1, 2019 to Dec. 31, 2019 are used to evaluate the LSTM network model. The AQI level of Shijiazhuang of Hebei Province of China from Jan. 1, 2019 to Dec. 31, 2019 is predicted with five methods (SVR, MLP, BP neural network, Simple RNN and this paper's new method). Then, a contrastive analysis of the five prediction results is made. The experimental results show that the accuracy of this new method reaches 93.7%, which is the highest in the five methods and the maximum error of this new method is 1. The correct number of days predicted by this new method is also the highest among the five methods, which is 342 days. The new method also shows good characteristics in MAE, MSE and RMSE, which makes it more accurate for people to predict the AQI level. [ABSTRACT FROM AUTHOR]

Ridesharing has become popular over the last decade, bringing significant changes to residents' travel patterns and city traffic. Relevant to the growth and impact of ridesharing activities in populous urban areas are the side effects, such as air pollution and traffic congestion. Despite a number of studies on these side effects, few have focused on their underlying causes and explained the behavioral incentive. Drawing on the theory of averting behavior, this paper investigates the ridesharing choices of individuals who face but would prefer to avoid ambient air pollution. Such air pollution–averting behavior tends to increase the demand for ridesharing services, which further results in more motorized traffic and pollutant emissions. Utilizing trip records from DiDi company and data on air pollutants in Haikou, China, we find that an additional 10 μg/m3 of PM2.5 leads to an increase of 2.6% in the count of DiDi trip orders. Results also show that traffic congestion increases due to elevated DiDi usage and the effect varies with time. This could further worsen the air quality and bring other potential side effects. These empirical results offer unique insights into the impact of air pollution on ridesharing and traffic from the perspective of individual behavioral motivation. [ABSTRACT FROM AUTHOR]

Air pollution has become an urgent issue affecting sustainable urban development. The Chinese government has implemented a series of air pollution control policies since 2012. Exploring the effectiveness of pollution control policies is important for future policy-making and improvements in air quality. Mean and variance tests were used for evaluation on the effectiveness of pollution control policies implemented in major cities and estimates of the heterogeneity among cities based on the distribution fitting and testing of daily PM2.5 data from January 2015 to January 2020. The nonparametric kernel density estimation adopted in this paper can effectively describe the data characteristics, and this is very important for air quality monitoring and control. Our findings demonstrate that air pollution prevention and control policies have significantly improved the levels and distribution of urban air quality in China. [ABSTRACT FROM AUTHOR]

Air pollution has emerged as a substantial threat to China's sustainable development. What remains overlooked is the resource dependence on the control of air pollution. At the same time, the resource curse may be broken by the growing digital economy, which will in turn reduce air pollution. To examine this problem, a total of 225 Chinese prefecture-level cities were selected from 2011 to 2018 to investigate the associations among resource dependence, the digital economy, and air pollution, and further, explore the mediating effect of income inequality and industrial upgrading. The primary findings are enumerated as follows: First, resource dependence is positively correlated to air pollution; second, the digital economy negatively regulates the effect of resource dependence on air pollution, that is, as the digital economy grows, air pollution decreases via resource dependence as a whole. However, a noteworthy phenomenon is that the negative moderating effect is evidently heterogeneous and is especially prominent in central China and non-resource-based cities; third, income inequality and industrial upgrading play a mediating role between resource dependence and air pollution; fourth, the digital economy can significantly influence the process where resource dependence affects air pollution via income inequality and industrial upgrading. These findings indicate the direction in the development of new strategies for different regions. Alleviating resource dependence is an important way of air pollution control. In particular, the main focus on mitigating air pollution should be adjusted to the level of income inequality and industrial structure. And the empirical results call for a strong emphasis on the digital economy for higher air quality in resource-based cities. [ABSTRACT FROM AUTHOR]

This paper examines the impact of policy uncertainty on air pollution, using the turnover of local officials in China as a quasi-natural experiment. The results from the two-way fixed effects model show that policy uncertainty caused by the turnover of different officials produces contrasting effects on air pollution. While the turnover of the mayor has no effect on air pollution, the turnover of the municipal party committee secretary deteriorates it. Two-Stage Least Square estimation confirms these results where the age and tenure of officials were used as instrumental variables of policy uncertainty. The results are robust after endogenous treatments and robustness tests. The mechanism analysis further indicates that policy uncertainty worsens air quality by weakening environmental regulation and crowding out green innovation. Moreover, the impact is more pronounced in smaller and less developed cities. The conclusions provide policy implications for environmental governance in the period of policy uncertainty. [ABSTRACT FROM AUTHOR]

Due to the rapid urbanization and climate change, one of the pressing problems confronting Chinese cities lies in air pollution. Especially during recent years, most cosmopolitan cities in China suffer from thick smog caused by PMs. It is reported that such air pollution has close relations with traffic-related pollutants, such as NO2. Meteorological condition contributes significantly to long-range transport sources and has remarkable influences on the distribution of the above pollutants. Thus, it is necessary to quantitatively analyze such influential patterns. In this paper, taking Chengdu as an illustrative example, the meteorological and pollutant statistics in 4947 h are collected and fitted with 8 meteorological parameters of PM2.5, PM10, and NO2 through linear regression method. And data is analyzed and compared on the hourly, daily, weekly, and monthly basis, respectively. Results show that hourly and daily data focus on fluctuations that affected by multiple interferences other than meteorological influences. When hourly values of PM2.5, PM10, and NO2 exceed 175 μg/m3, 250 μg/m3, and 125 μg/m3, respectively, discrete values that cannot be explained by meteorological influences increase notably, while weekly and monthly variations illustrate more tendencies, and communicable patterns that decisively influenced by meteorology can be extracted among 3 pollutants. By comparing the results in 4 timescales, respectively, similar principal meteorological factors are involved in fitting processes. Thirdly, visibility (V), wind speed (WS), precipitation (P), and cloud condition (CC) are the most influential factors and served as main parameters in linear regressions within 4 timescales. Air temperature (AT) and dew temperature (DT) are less influential factors by daily and weekly data but are served as main parameters when it goes to hourly and monthly data and function as variables that signify tendency variances in linear regressions, while relative humidity (RH) and barometric pressure (BP) are lest influential factors and have limited effect on fitting results. This work can provide guidance and reference for urban planning optimization and air environment protection in cities with air quality control considerations impacted by local climatic conditions. [ABSTRACT FROM AUTHOR]

Accurate prediction of PM2.5 concentration is one of the key tasks of air pollution assessment, early warning, and treatment. In this paper, four monitoring sites were arranged in Jiangbei New District of Nanjing City, China. The environmental parameters such as PM2.5/PM10 concentration, temperature, and humidity were monitored from January to February 2020. A gated recurrent unit (GRU) network based on the PM2.5 concentration prediction model was established to predict PM2.5 concentration. The mean relative error (MRE), root mean square error (RMSE), and Pearson correlation coefficient were selected as the evaluation criteria for the accuracy of the GRU model. The data set was divided into a training set, a test set and a validation set at a ratio of 7:2:1, and the GRU model was used to predict the hourly value of PM2.5 concentration in the next week. The prediction results show that the Pearson correlation coefficients between the predicted values and the monitored values of the four monitoring sites have reached more than 0.9, reflecting a strong correlation. The relative average errors are around 10%. The GRU model prediction of NJAU (Nanjing Agricultural University)-Pukou Campus Site is the most accurate, and the correlation coefficient, MRE, and RMSE are 0.970, 7.85%, and 9.6049, respectively, reflecting the good prediction performance of the model. Therefore, this research supports the prediction of air quality in different cities and regions, so people can take protective measures in advance and reduce the damage caused by air pollution to human bodies. [ABSTRACT FROM AUTHOR]

This paper collects and analyzes the 1954–2017 monthly average reanalysis data from the U.S. National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), the 1954–2017 haze days observation data from the National Meteorological Information Center/China Meteorological Administration (NMIC/CMA) and the PM2.5 daily average mass concentration data in 2013–2017 from the China Air Quality Online Monitoring Platform. The atmospheric apparent heat source Q1 (negative Q1 means cold source in winter) over the Tibetan Plateau in December of 1954–2017 is estimated based on thermodynamic equations, and the East Asian winter monsoon index (EAWMI) is calculated. In addition, the discrepancies of the air quality among China's five typical regions (Beijing–Tianjin–Hebei, Fen-Wei Plain, Yangtze River Delta, Pearl River Delta and Sichuan-Chongqing regions) under the joint influence of the Q1 and EAWMI are studied. Results show that when it is a strong cold source year, abnormal downdrafts and "temperature inversion covers" occur in areas far from the high terrain, resulting in increased pollution, while the opposite is true in weak cold source years. In strong EAWMI years, there is an abnormal northerly sinking cold flow in the lower layers of mid-high latitudes, which increases the pollution in the area south of 30° N, and the opposite is true in weak EAWMI years. Affected by the combined activities of the Q1 and the EAWMI, the meteorological conditions of the five typical regions are different, and thus present different air pollution characteristics. [ABSTRACT FROM AUTHOR]

With the rapid development of industrialization and urbanization in China, the ecological environment has been damaged, especially the air quality, which has negatively impacted the productivity and lives of residents. China has taken various measures to improve air quality, and industrial upgrading is one of these measures. This article uses urban and provincial data from 2015 to 2018 and a multilevel growth model to study how industrial upgrading can improve air quality. The following conclusions are drawn through empirical analysis. If industrial upgrading is not considered, with time, air quality will gradually deteriorate. However, once the country adopts strategic measures for industrial upgrading, the combined effect of industrial upgrading and time will improve air quality. Industrial upgrading and industrial restructuring jointly reduce air pollution and have a significant impact on the improvement of air quality. Company goals for economic profit and survival will eventually lead to overall industrial upgrades that have little effect on air improvement. According to the empirical results, this paper puts forward some suggestions to improve the air quality. [ABSTRACT FROM AUTHOR]

In September 2013, China began to implement a series of policies in tackling severe air pollution. This paper aims to explore the diversity and effectiveness of its air pollution control policies at the city level. A city-level pollution control policy indicator is constructed for 35 Chinese cities during the last two air pollution control action periods from 2014 to 2017 and 2018 to 2020. Additionally, this paper employs the panel vector autoregression model (PVAR) to estimate the impact of air pollution control policies on air pollution reduction. The empirical results show that, in terms of the two main air quality indicators, PM2.5 and PM10, China's air pollution control policies have helped improve the air quality over the last several years. The study concludes that air quality improvement should depend on coordinated strategies for controlling various pollutants that involve the collaboration of government and industries. [ABSTRACT FROM AUTHOR]

The concentration changes of aerosols have attracted wide-ranging attention during the COVID-19 lockdown (CLD) period, but the studies involving aerosol optical properties (AOPs) are relatively insufficient, mainly AOD (fine-mode AOD (AODf) and coarse-mode AOD (AODc)), aerosol absorption optical depth (AAOD), and aerosol extinction coefficient (AEC). Here, the remote-sensing observations, Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) products, backward-trajectory, and potential-source-contribution models are used to assess the impact of AOPs, vertical distribution, and possible sources on the atmosphere environment in North China Plain (NCP), Central China (CC), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SB) during the CLD period. The results demonstrate that both AOD (MODIS) and near-surface AEC (CALIPSO, <2 km) decreased in most areas of China. Compared with previous years (average 2017–2019), the AOD (AEC) of NCP, CC, YRD, PRD, and SB reduced by 3.33% (10.76%), 14.36% (32.48%), 10.80% (29.64%), 31.44% (22.68%), and 15.50% (8.44%), respectively. In addition, MODIS (AODc) and MERRA-2 (AODc) decreased in the five study areas compared with previous years, so the reduction in dust activities also contributed to improving regional air quality during the epidemic. Despite the reduction of anthropogenic emissions (AODf) in most areas of China during the CLD periods, severe haze events (AODf > 0.6) still occurred in some areas. Compared to previous years, there were increases in BC, OC (MERRA-2), and national raw coal consumption during CLD. Therefore, emissions from some key sectors (raw coal heating, thermal power generation, and residential coal) did not decrease, and this may have increased AODf during the CLD. Based on backward -rajectory and potential source contribution models, the study area was mainly influenced by local anthropogenic emissions, but some areas were also influenced by northwestern dust, Southeast Asian biomass burning, and marine aerosol transport. This paper underscores the importance of emissions from the residential sector and thermal power plants for atmospheric pollution in China and suggests that these sources must be taken into account in developing pollution-mitigation plans. [ABSTRACT FROM AUTHOR]

This paper examines the impact of air pollution on the media slant of publicly listed firms in China. Using a large panel of air quality and media data at the city level, we find that lower air quality generally leads to a more negative media slant. When the air quality falls from lightly polluted to heavily polluted, the number of negative sentences in a news article increases by about 1%. Our subsample analysis shows that the effect of air pollution on media slant is similar for news articles covering large and small firms, SOE and non-SOE firms and for official and non-official newspaper articles. Furthermore, the effect of air pollution on media slant is stronger for firms in heavy polluting industries. These results suggest that air pollution affects media slant. [ABSTRACT FROM AUTHOR]

This paper complements the literature on green finance by probing whether air pollution matters for CEO compensation. Using a sample covering 240 cities in 31 provinces in China from 2005 to 2017, we document a positive association between air pollution and CEO compensation. These findings indicate that firms headquartered in areas with unhealthy air compensate their CEOs with higher pay than those headquartered in areas with better air quality. Moreover, two potential channels are validated to interpret the positive pollution‐pay linkage: income comparison and executive shortage. Finally, we show that air pollution attenuates the pay‐performance sensitivity, indirectly confirming an essential role of the living environment in determining CEO compensation. [ABSTRACT FROM AUTHOR]

Based on the panel data of various daily air pollution indicators of 288 prefecture-level cities in China from January 1, 2015 to December 31,2018, this paper takes the first round of central environmental protection inspection (CEPI) as a quasi-natural experiment, and empirically analyzes its impact on urban air pollution by using multi-period difference-in-difference (DID) method. The results show that: (1) the first round of five batches of environmental inspection and two batches of "looking back" have significantly reduced the concentration of seven pollutants; (2) The first five batches of environmental inspection have a stronger impact on reducing air pollution than "looking back"; Moreover, in the short tel·in after the inspection, it still has a significant reduction effect on air pollution; (3) The impact of central environmental protection inspection on air pollution shows strong heterogeneity in different batches of inspections, urban scale and economic development level, as well as the air quality level of cities before the inspection. The research results of this paper provide corresponding policy recommendations and decision-making basis for the Chinese central government to further deepen the reform of environmental protection supervision mechanism and promote the emissions of multiple pollutants mitigation. [ABSTRACT FROM AUTHOR]

Environmental context: Lvliang, one of the main cities on the Fenwei Plain, is a key atmospheric pollution prevention area in China. Identification of sources of aerosols is essential to improving environmental air quality in this region. The quantitative source apportionment of carbonaceous aerosols performed in this study provides a better understanding of their sources and implications for climate and air-quality management policies in the Fenwei plain. Rationale: Organic carbon (OC) and elemental carbon (EC) are major components of fine particulate matter (PM2.5), and they are of concern due to their significant impacts on human health and climate. Methodology: PM2.5 samples were collected daily during four consecutive seasons from 2018 to 2019. This paper highlights the seasonal variations, sources and transport characteristics of carbonaceous aerosol in Lvliang, China. Results: The OC and EC concentrations exhibited strong seasonal variations, with the highest in winter, mainly due to high pollution caused by winter heating in northern cities, and secondary OC (SOC) contribution. The average OC/EC ratio (1.72) in Lvliang was lower than those in most regions in China, further indicating that this region was greatly affected by primary source emissions. The highest SOC/OC ratio in summer (25.3%) was due to the positive correlation between SOC and temperature. Through the positive matrix factorisation (PMF) model, four sources of carbonaceous aerosols were identified: vehicle emissions (31.26%), coal combustion (30.83%), biomass combustion (24.36%) and dust emissions (13.55%). Potential source contribution function (PSCF) results indicated that in addition to the impact of local emissions, coal emissions from Ningxia and Shaanxi, motor vehicle emissions and biomass from Inner Mongolia and Ningxia and dust from Shaanxi and Henan Provinces were the major contributors to pollution. Discussion: These data provide key information for formulating emission reduction policies and improving air quality on the Fenwei Plain and highlights the urgent need for inter-regional prevention and control measures for the cities in Lvliang. [ABSTRACT FROM AUTHOR]

Photochemical air quality models (AQMs) are a vital tool for atmospheric pollution research and have been widely used in various applications, such as air quality prediction and evaluation of pollution control strategies. Before using these models for further studies, it is essential to thoroughly evaluate their reliability and accuracy. While previous guidelines and benchmarks have primarily focused on fine particulate matter (PM 2.5) and ozone (O 3), there is still a lack of benchmarks for evaluating the model performance on primary criteria pollutants such as sulfur dioxide (SO 2), nitrogen dioxide (NO 2), carbon monoxide (CO), and particulate matter with aerodynamic diameter less than or equal to 10 μm (PM 10). The use of air quality models in China has increased significantly in the past decades. However, there is still a lack of standardized benchmarks for the performance evaluation of these models. Building upon our previous work on PM 2.5 and its chemical species, we propose a set of benchmarks for evaluating the performance of the aforementioned four air pollutants. Initially, we identified a total of 475 papers published during 2007–2019 that utilized at least one of the five commonly used AQMs in China. From these papers, we selected 164 articles that provided model performance evaluation (MPE) results of the four primary air pollutants. The three most frequently used Model Performance Evaluation (MPE) metrics were selected to analyse the impact of different model configurations on the reported statistics, including modelling region, season, and emission inventory. Lastly, three commonly used statistical indicators, including normalized mean bias (NMB), normalized mean error (NME), and correlation coefficient (R), were proposed for the validation of simulated NO 2 , SO 2 , CO, and PM 10. Two sets of benchmarks are given, including the "goal" and "criteria". The "goal" represents the best range of performance that a model can be expected to achieve, and the "criteria" represents performance that the majority of studies have achieved. We recommend R values above 0.50, 0.35, 0.45, and 0.40 for NO 2 , SO 2 , PM 10 , and CO, respectively, in order to meet the "criteria" benchmark. If the "goal" benchmark is to be achieved, the corresponding R values are 0.60, 0.55, 0.60, and 0.60. The "goal" benchmarks of NMB for NO 2 , SO 2 , PM 10 , and CO are within ±20%, ±25%, ±20%, and ±25%, respectively; while the "goal" benchmarks of NME for the four pollutants are less than 40%, 45%, 45%, and 60%, respectively. These benchmarks supplement our previous benchmarks for PM 2.5 and its components and provide a more comprehensive guideline for the air quality modelling community in China. • A set of benchmarks for evaluation of the NO 2 , SO 2 , CO and PM 10 simulation over China are proposed. • Three commonly used statistical indicators (NMB, NME, and R) were proposed for the validation of the four pollutants. • The goal benchmarks of NMB for NO 2 , SO 2 , PM 10 , and CO are <20%, <25%, <20% and <25%, respectively. [ABSTRACT FROM AUTHOR]

• Urban green spaces have direct and indirect effects on improving residents' health. • The health benefits of urban green spaces exhibit regional heterogeneity. • Economic development weakens the health benefits of urban green spaces. • Environmental regulations can enhance the health benefits of urban green spaces. Urban green spaces have long been cherished as the "lungs of the city", it can not only improve air quality and enhance residents' health. The impact of urban green spaces on air pollution and residents' health has attracted great attention. In this paper, we select 31 provinces in China as research samples and use ArcGIS software to draw spatial distribution maps of urban green spaces, air pollution, and residents' health in China, characterizing their spatiotemporal changes in order to explore whether there is a correlation among the three. On this basis, this paper utilizes panel data of Chinese provincial-level from 2010 to 2020 and conducts empirical tests through a two-way fixed effect model and a threshold regression model. The research findings are as follows: (1) Urban green spaces not only bring environmental benefits, but also health benefits, and the health benefits are greater than the environmental benefits. (2) There is a health risk of air pollution in northern China, and the health benefits of urban green spaces are not significant. Conversely, there is no health risk of air pollution in southern China, and the health benefits of urban green spaces are significant. (3) Although environmental regulations can enhance the health benefits of urban green spaces, the role of environmental regulations in enhancing the health benefits of urban green spaces may be further weakened as the economy develops. [ABSTRACT FROM AUTHOR]

In different regions of China that can range from 5 to 100 km2, various production plants and facilities such as petrochemicals, pesticides, pharmaceuticals, paper mills, thermal power plants, hazardous waste disposal sites makes chemical industrial parks with Chinese characteristics. At the same time, these chemical industry parks in various places are in urgent need of advanced monitoring, prewarning, and tracing technologies, in order to strengthen monitoring of atmospheric emissions in chemical industrial parks, and timely prevention of the leakage of exhaust gas and explosion accidents in the production process of these enterprises. Most of the Chinese chemical industry parks still use traditional air monitoring technologies that requires setting up passive air monitoring collection points at the boundary of enterprises and industrial parks and use the "point" sensor and pollution factors collected by air stations. However, the operation of traditional air monitoring equipment is affected by the prevailing wind conditions, thus the traditional air monitoring equipment and technology is of limited use to conduct monitoring. One of the authors of this manuscript, Weimin Zhang with Jiangsu China‐U.S. Environmental Monitoring Co. Ltd. (hereinafter referred to as EMCUS), with 10 years of has been testing and observing air diffusion law in chemical industrial parks for 10 years and has achieved fruitful success. The best way to truly achieve tracing and prewarning about the air pollution is to conduct timely three‐dimensional dynamic collection of chemical factors and then perform qualitative and quantitative analysis. Based on this theory, EMCUS has abandoned the traditional "point" passive monitoring theories. After a comprehensive analysis and comparison of air quality monitoring technology and equipment around the world, especially several investigations of advanced Fourier transform infrared spectroscopy (FTIR) equipment and software in the United States, EMCUS initiated the three‐dimensional monitoring technology for exhaust gas emissions which fully combined with the current situations of chemical industry parks. During the EcoPartnership project, the stepwise vertical and radial air monitoring technology was fully promoted in Chinese chemical industry parks to generate key emission data. [ABSTRACT FROM AUTHOR]

This paper presents the first development and evaluation of a reduced-complexity air quality model for China. In this study, the reduced-complexity Intervention Model for Air Pollution over China (InMAP-China) is developed by linking a regional air quality model, a reduced-complexity air quality model, an emission inventory database for China, and a health impact assessment model to rapidly estimate the air quality and health impacts of emission sources in China. The modeling system is applied over mainland China for 2017 under various emission scenarios. A comprehensive model evaluation is conducted by comparison against conventional Community Multiscale Air Quality (CMAQ) modeling system simulations and ground-based observations. We found that InMAP-China satisfactorily predicted total PM 2.5 concentrations in terms of statistical performance. Compared with the observed PM 2.5 concentrations, the mean bias (MB), normalized mean bias (NMB) and correlations of the total PM 2.5 concentrations are - 8.1 µ g m -3 , - 18 % and 0.6, respectively. The statistical performance is considered to be satisfactory for a reduced-complexity air quality model and remains consistent with that evaluated in the USA. The underestimation of total PM 2.5 concentrations was mainly caused by its composition, primary PM 2.5. In terms of the ability to quantify source contributions of PM 2.5 concentrations, InMAP-China presents similar results to those based on the CMAQ model, with variation mainly caused by the different treatment of secondary inorganic aerosols in the two models. Focusing on the health impacts, the annual PM 2.5 -related premature mortality estimated using InMAP-China in 2017 was 1.92 million, which was 250 000 deaths lower than estimated based on CMAQ simulations as a result of the underestimation of PM 2.5 concentrations. This work presents a version of the reduced-complexity air quality model over China that provides a powerful tool to rapidly assess the air quality and health impacts associated with control policy and to quantify the source contribution attributable to many emission sources. [ABSTRACT FROM AUTHOR]