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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]

This study reviewed the status quo of research on machine learning (ML), including deep learning, in the rail industry. This study conducted a scientometric analysis and critical review of 640 papers selected from 12,675 web-crawled papers. The extensive and complex networks of topics, researchers, and countries were analyzed using the Louvain method, a co-occurrence keyword analysis, a degree centrality analysis, and other network analysis methods. The results indicate that the majority of studies of ML in the rail industry focused on maintenance activities and traffic management, and mainly targeted rolling stock, rails, and passengers. Overhead contact systems, including catenaries, are a high-demand objective for ML-based maintenance. Although analyses of tunnels and stations remain rare, passenger flow prediction, station air quality estimation, shield tunneling performance improvement, and ground settlement are areas of high importance. Geographically, China, the US, and the United Kingdom lead ML studies in the rail industry, and the level of collaboration is higher among European countries than among countries on other continents. Future challenges include ensuring the security and stability of ML, along with considering novel mindsets, the black-box effect, improvements in ML techniques, and resource overload when introducing ML technologies. [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]

Based on panel data of 282 prefecture-level and above cities in China from 2013 to 2020, this paper investigates the impact and transmission paths of the "LFD" land disposal model on urban air quality at the theoretical and empirical levels using dynamic fixed-effects and dynamic spatial Durbin models. The results show that the way land is allocated in a city has a lagging and long-term impact on air quality not only locally but also in neighboring cities. The type of land supply by local governments to different sectors is an important pathway to influence urban air quality. Extended analysis shows that land market reforms in China can significantly reduce urban air quality index (AQI) and effectively mitigate urban air quality, with long-term effects. This paper provides a theoretical and scientific basis for correcting the mismatch of land resources and promoting urban ecological environment in China. [ABSTRACT FROM AUTHOR]

In China, the local government's "land for development" strategy has led to a large number of urban construction land allocated to the industrial field, which has promoted the rapid development of industry and economy in the short term but also brought serious environmental quality losses. This paper systematically sets out how land misallocation works on urban air quality and employs the spatial Durbin model (SDM) to conduct an empirical analysis on the panel data of 283 China cities at or above the prefecture level. The result shows that, stimulated by financial maximization and political promotion, in order to obtain more fiscal revenue and growth performance, local governments prefer to allocate a large number of urban construction land to industry and related fields, which leads to the underestimation of industrial land price and the misallocation of land resources. Land misallocation has exerted significant inhibiting effects on the air quality of local and their surrounding cities through inhibiting the upgrading of industrial structure. Further analysis reveals that the bigger the city, the lesser the inhibition effects of land misallocation on upgrading of industrial structure and urban air quality and vice versa. The conclusions of this paper can provide a useful reference for local governments to optimize land allocation, promote economic restructuring, and environmental quality upgrading. [ABSTRACT FROM AUTHOR]

Air quality is an important factor affecting human health. This paper aims to explore the key determinants of urban air quality in China and their synergistic mechanism based on a hybrid model integrating weighted gray relation analysis (WGRA) and qualitative comparative analysis (QCA). First, text mining technology is introduced to excavate factors related to urban air quality, and WGRA method is employed to determine the key influencing factors. Second, taking 42 representative cities in China as samples to apply QCA method, we attempt to investigate the complex causal mechanism between key determinants of urban air quality and air quality index (AQI). Results show that: (1) Since the consistency level of a single conditional variable is not greater than 0.9, a single factor that influences urban air quality cannot constitute the necessary condition to worsen or improve the urban air quality. (2) Synergistic effect mechanisms of key factors influencing urban air quality are obtained, including four configuration paths that bring about high AQI and four configuration paths that inhibit the generation of high AQI. [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]

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]

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]

With the rapid development of the real estate industry in China, urban air quality is inevitably affected. By using data of Chinese cities located in the Yangtze River Delta from 2009 to 2018, this paper is aim at examining the casual impact of house prices on air quality. By considering the endogenous problems, in this study, first, the birth rate of the previous six years and the area of state-owned land supply per capita in the previous year are taken as instrumental variables of house price. Second, the two-stage least squares method is used to assess the causal impact of house price on air quality. The findings of this study show that there is no significant relationship between urban house prices and air quality, and these results are obtained without considering the endogenous problem. While, after considering the endogenous problem, urban house prices showed a significant negative effect on overall air quality, especially for low administrative level cities. The increase in house prices has hindered the improvement of air quality mainly through the blind-scale expansion of real estate development investments and the inhibitory effect of innovation. [ABSTRACT FROM AUTHOR]

Although green technology innovation is an important means to balance the environment and economy, few studies have analyzed the employment effects of green technology innovation in developing countries. Therefore, this paper employs the panel data of 286 prefecture-level cities in China from 2006 to 2017 to empirically test the impact of various green technology innovations on urban employment. Meanwhile, from the perspectives of air quality and industrial structure optimization, the influencing mechanism of green technology innovation on employment is deeply analyzed. The results reveal that all kinds of green technology innovation can significantly increase the employment level of the city, and the promotion effect is strongest in the 2nd year after the patent application. According to the results of heterogeneity analysis, key cities of environmental protection and non-resource cities are more likely to generate positive employment effects through green technology innovation. Finally, the mediation effect test model confirms that green technology innovation can promote employment by improving air quality and causing industrial structure optimization. [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 explores the short-run impact of work resumption, extensively launched on February 10, 2020 in China, on air quality after the subsiding of COVID-19. Utilizing the data of 1012 air-quality monitoring sites in 233 cities derived from the Real-time Release Air Quality Platform and the difference-in-differences method, we find that alternative measures of air quality index in non-Hubei provinces increase significantly, compared with those in Hubei province which was temporarily not allowed work resumption due to the severity of epidemic. Specifically, our results reveal a rise in AQI of 11.28 per cent, in PM2.5 of 12.47 per cent, in PM10 of 10.49 per cent, and in NO2 of 23.64 per cent, relative to the baseline mean. Moreover, the deterioration of air quality is found to be caused by intracity rather than intercity migration. [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]

In this paper, multi-source observation, such as aircraft, ground-based remote sensing, and satellite-retrieved data, has been utilized to compare and analyze the vertical characteristics of aerosol optical properties and the planetary boundary layer height (HPBL) over the North China Plain (NCP) region during May–June 2016. Aircraft observations show the vertical profiles of aerosol absorption coefficients (σabs), scattering coefficients (σsca), and extinction coefficients (σext) gradually decrease with altitude, with their maximum values near HPBL. The vertical profiles of σext depended most on the vertical distribution of measured σsca, indicating a significant contribution of scattering aerosols. In addition, the prominent characteristic of the inverse relationship between σext and moisture profile could serve as a reference for predicting air quality in the NCP region. The lower layer pollution during the field experiment was likely caused by the accumulation of fine-mode aerosols, characterized by the vertical distribution of the Ångström exponent and the Aerosol Robotic Network (AERONET) products. Typically, HPBL derived from aircraft and surface Micro Pulse Lidar (MPL) was approximate, while the predicted HPBL by meteorological data indicates an underestimation of ~192 m. Aerosol optical depth (AOD) calculated from aircraft and ground-based remote sensing (such as MPL and AERONET) experienced a strong correlation, and both of them exhibited a similar tendency. However, the AOD retrieved from satellites was significantly larger than that from aircraft and ground-based remote sensing. Overall, the inversion algorithm, cloud identification algorithm, representativeness of the space, and time of the observation may lead to an overestimation or underestimation of AOD under certain circumstances. This study may serve as a re-evaluation of AOD retrieved from multi-source observations and provide a reference to uncover the actual atmospheric environment in the NCP regions. [ABSTRACT FROM AUTHOR]

Drawing on fine particulate matter (PM2.5) from satellite raster data and matching with the county-level socio-economic data from 2008 to 2015 in China, this paper investigates the impacts of the establishment of National Key Ecological Functional Zones (NKEFZ) on environmental quality by employing the difference-in-differences method, which was stablished in June 2011. The results indicate that the establishment of the NKEFZ significantly decreased the concentration values of PM2.5, a drop of about 20% during the study period, after the paper controls for other factors affecting air quality. The robustness tests using the maximum and medium concentration values of PM2.5 show similar results. Through further analysis, the paper finds that the establishment of NKEFZ can improve the ecological utilization efficiency of land. [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]

Over the past four decades, China have experienced rapid economic growth but also a widening urban-rural income gap and deteriorating air quality. Based on the panel data of 30 provinces in China from 2006 to 2017, this paper investigates the effect of narrowing the urban-rural income gap on carbon emission reduction and pollution control by using OLS method. The empirical results indicate that: the narrowing of the urban-rural income gap has a positive impact on pollution control, while there are regional differences in the impact on carbon emission reduction. In the perspective of the whole country and central and western regions, the narrowing of the urban-rural income gap is conducive to carbon emission reduction. However, the narrowing of the urban-rural income gap increases carbon emissions in the eastern regions where economic development is at high level. This paper provides a theoretical basis and policy reference for promoting urban-rural integration and construction of ecological civilization. [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]

Air quality forecasting is of great importance in environmental protection, government decision-making, people's daily health, etc. Existing research methods have failed to effectively modeling long-term and complex relationships in time series PM2.5 data and exhibited low precision in long-term prediction. To address this issue, in this paper a new lightweight deep learning model using sparse attention-based Transformer networks (STN) consisting of encoder and decoder layers, in which a multi-head sparse attention mechanism is adopted to reduce the time complexity, is proposed to learn long-term dependencies and complex relationships from time series PM2.5 data for modeling air quality forecasting. Extensive experiments on two real-world datasets in China, i.e., Beijing PM2.5 dataset and Taizhou PM2.5 dataset, show that our proposed method not only has relatively small time complexity, but also outperforms state-of-the-art methods, demonstrating the effectiveness of the proposed STN method on both short-term and long-term air quality prediction tasks. In particular, on singe-step PM2.5 forecasting tasks our proposed method achieves R2 of 0.937 and reduces RMSE to 19.04 µg/m3 and MAE to 11.13 µg/m3 on Beijing PM2.5 dataset. Also, our proposed method obtains R2 of 0.924 and reduces RMSE to 5.79 µg/m3 and MAE to 3.76 µg/m3 on Taizhou PM2.5 dataset. For long-term time step prediction, our proposed method still performs best among all used methods on multi-step PM2.5 forecasting results for the next 6, 12, 24, and 48 h on two real-world datasets. [ABSTRACT FROM AUTHOR]

This study investigates the unsymmetrical effect from air quality (AQ) to stock return (SR) in China's different industries. Depending on quantile-on-quantile (QQ) test, it draws the important results in following aspects. For tourism, iron and steel, and automobile industries, their coefficient values between AQ and SR turn into negative from positive with deteriorating AQ. Conversely, the coefficients in the wind power, hydro power, thermal power, environmental protection, and medical equipment industries turn positive from negative. Some contributions are thus drawn when compared to existing literatures. Government industrial policy is regarded as an important supplement in explaining mechanism from AQ to SR, except investor sentiment. Industrial heterogeneity is seriously treated in this paper due to different industries have different responses to AQ. Besides, the QQ test is able to capture nexus between AQ and SR in specific quantiles through embedding non-parametric estimation into conventional quantile approach. Therefore, investors should avoid biased trading decisions under different air qualities. Meanwhile, government intervention is paid special attention when appearing serious air pollution. [ABSTRACT FROM AUTHOR]

The air quality is generally graded into five levels in a simple way or released by the Air Pollution Index (API) which does not take the fine particulate matter (PM2.5) emission into account. The fuzzy algorithm in this paper solves the mutability aroused by the grading approach by counting in the six items of pollutants pertaining to Short-lived climate forcers (SLCFs). Firstly, six items of air pollutants as well as driving factors of human activities are introduced. Secondly, based on the relevant observation data from the China Air Quality Online Monitoring Platform (CAQOMP), 18 experimental cities covering North China, East China, Central China, and South China are selected in this paper for air quality comparison and analysis in the application of the fuzzy algorithm. Thirdly, this paper looks into the air quality ranking of experimental 18 cities from a regional perspective. North China's air quality is not optimistic owing to being in a location near the coal producer and sand-sourced Outer Mongolia. Central China's air quality is more impacted by high-speed economic development and urbanization during the last couple of years. O3 emission is not well controlled across China. It turns out that the ranking by using the fuzzy algorithmic method is more scientific and holistic than API. [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]

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]

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]

Sulphate (SO42−) is a main component of PM2.5 in China. The chemical formation mechanisms of sulphate are complex, and many air quality models have been used to analyse these mechanisms. To improve the accuracy of Weather Research Forecast-Chemistry (WRF-Chem) on sulphate, an alternative method is proposed in this paper. Moreover, data assimilation is performed to adjust the chemical reaction rates of sulphate. Based on the original reactions, a new sulphate parameterisation scheme, which includes two hypothetical reactions and six undetermined parameters, was added. Based on the WRF-Chem/DART (Data Assistance Research Testbed) system, the near-ground concentrations of SO42−, SO2, NO2, O3 and particulate matter are assimilated to adjust the six parameters. After adjusting the parameters, the new scheme can effectively solve the underestimation of SO42− and overestimation of SO2. The simulation of SO42− improved as the mean bias changed from −13.1 µg m−3 to 3.5 µg m−3 while SO2 improved from 17.0 µg m−3 to 6.3 µg m−3. The temporal and spatial variation characteristics predicted by the new scheme are consistent with the theoretical research results, indicating that the complex mechanism of sulphate formation could be replaced by the temporal and spatial variation characteristics predicted by the new scheme and that the parameters can be adjusted by data assimilation. Furthermore, the reaction rates of the SO42− parameterisation scheme of the WRF-Chem model are improved in this study, and a new method for improving the accuracy of the air quality model is provided. [ABSTRACT FROM AUTHOR]

This paper comprehensively evaluates the dynamic effects on China's environment and economy during the COVID-19 pandemic. Results show that the COVID-19 lockdown resulted in a temporary improvement in air quality. Furthermore, nitrogen dioxide (NO2) levels in the atmosphere in China were 36% lower than in the week after last year's Lunar New Year holiday, but this also led to an economic downturn. Moreover, the aerosol optical depth (AOD) decreased significantly. During the back-to-work period, the economy recovered and there was an increase in energy consumption, and CO2, NO2 emissions sharply increased to pre-lockdown levels. In the post-lockdown period, the AOD was lower than that of the same period last year. This study can provide reference for environmental policy making, as it demonstrates to what extent the control of pollution sources can improve air quality. Precise emission reduction and regional joint prevention and control are important and effective means for the prevention and control of O3 pollution. The health and economic benefits of COVID-19 pandemic control measures are incalculable. And this can provide an effective scientific basis and theoretical support for the prevention and control of air pollution. [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]

As a mode of green transport that can effectively alleviate urban traffic congestion and improve air quality, bus transport is highly subsidized by governments at all levels in China. Thus, measuring efficiency in the bus transport sector is particularly important. However, few reports in the literature have taken exogenous environmental factors into consideration to evaluate public transport operation efficiency. This may lead to inaccurate evaluation results. This study employs the three-stage DEA model, which can eliminate the impacts of exogenous environmental factors on public bus transport operation to gain real efficiency results. Meanwhile, to further explore how exogenous environmental factors affect bus transport operations, a tobit model is used to analyse the results. The main results of this paper reveal the following: first, exogenous environmental factors have a significant impact on the operational efficiency of bus transport. It is reasonable and necessary to select the three-stage method to eliminate environmental factors for real bus operation efficiency. Second, the fluctuations of the bus transport efficiency of 30 cities decreased during 2010–2016. The western region has the highest operation efficiency, followed by the eastern and the middle regions. Third, the economic, taxi transport, and urban rail transport have a marked impact on the operational efficiency of bus transport. This paper confirms the important influence of exogenous environmental factors on the efficiency of public transport operations. In addition, this article could help improve the efficiency of urban public transport operations and promote the attractiveness of urban public transport and the amount of green travel. [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 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]

This paper uses the panel data of 245 cities in China from 2005 to 2020 to build an ambient air pollution index to measure ambient air quality. Taking China's national smart city pilot as a quasiexperiment, the impact of smart city construction on urban ambient air quality and its impact path is tested by using the multi-period double difference method. The research results show that the construction of smart cities has significantly improved the urban ambient air quality, and with the improvement of the level of smart city construction, the degree of improvement in urban ambient air quality shows a positive fluctuation trend. The mechanism test results show that the construction of smart cities improves urban ambient air quality by enhancing the level of technological innovation and marketization in the city. Heterogeneity testing shows that the ambient air quality improvement effects of smart city construction vary depending on the size of the city's population and the geographical location of the city. Furthermore, the moderating effect test shows that financial autonomy and industrial structure upgrading have a positive moderating effect on the improvement of ambient air quality in smart cities, while local government environmental regulation intensity has a reverse moderating effect. [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]

This paper takes the panel data of 283 prefecture-level cities in China from 2011 to 2020 as the research sample, measures the comprehensive index of industrial structure optimization and air quality by using GRA-TOPSIS comprehensive evaluation method, explores the spatial and temporal divergence characteristics of industrial structure optimization and air quality and the spatial and temporal evolution pattern of coupled and coordinated development by using ArcGIS spatial analysis and coupled coordination degree model, and analyzes the driving factors of coupled coordination degree of industrial structure optimization and air quality by combining multi-scale geographically weighted regression model. The study found the following: (1) The overall level of China's urban industrial structure is low, and shows an obvious eastern > central > western decreasing trend; urban air quality has a strong spatial clustering and spatial locking effect. (2) During the study period, the coupling coordination degree of industrial structure optimization and air quality showed an inverted "W" shape fluctuation from 2011 to 2020. The coupling degree and coupling coordination degree in 2020 were both higher than that in 2011, and most cities were in the run-in stage and moderate coordination stage. (3) There is a consistency in the temporal evolution trend and spatial evolution pattern of industrial structure optimization and air quality coupling degree and coupling coordination degree. (4) The driving factors are ranked according to the scale of action: public transportation intensity > population density > government intervention > GDP per capita > industrialization level. At present, China is in a critical period of promoting high-quality development by ecological civilization, and it is recommended to optimize regional industrial structure, improve urban air quality, and promote coordinated urban development. [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]

In order to improve the accuracy of air pollution management and promote the efficiency of coordinated inter-regional prevention and control, this study analyzes the interaction of O3 in Qilihe District, Lanzhou City, China. Data used for analysis was obtained from 63 air quality monitoring stations between November 2017 and October 2018. This paper uses complex network theory to describe the network structure characteristics of O3 pollution spatial correlation. On this basis, the node importance method is used to mine the sub-network with the highest spatial correlation in the O3 network, and use transfer entropy theory to analyse the interaction of pollutants between regions. The results show that the O3 area of Qilihe District, Lanzhou City can be divided into three parts: the urban street community type areas in urban areas, the township and village type areas in mountain areas and the scattered areas represented by isolated nodes. An analysis of the mutual influence of O3 between each area revealed that the impact of O3 on each monitoring station in adjacent areas will vary considerably. Therefore these areas cannot be governed as a whole, and the traditional extensive management measures based on administrative divisions cannot be used to replace all other regional governance measures. There is the need to develop a joint prevention and control mechanism tailored to local conditions in order to improve the accuracy and efficiency of O3 governance. [ABSTRACT FROM AUTHOR]

To effectively solve the problem of environmental pollution, the Chinese government has implemented an environmental supervision system since 2002. The environmental supervision system mainly uses the four functions of supervision, investigation, coordination, and emergency response to strengthen environmental protection supervision and law enforcement, respond to environmental emergencies, and coordinate cross-regional pollution disputes. As an important system design for China to control environmental pollution and promote the ecological transformation of economic development, the policy effect of the environmental supervision system deserves attention. This paper uses the difference-in-differences method to investigate the impact of the top-down environmental supervision system on air quality based on the 2000–2016 data for 285 prefecture-level cities in China. The results indicate that the annual average concentration of PM2.5 decreased significantly after the implementation of the environmental supervision system. The dynamic analysis shows that PM2.5 decreased most markedly in the first year after the implementation of the policy, and then the effect gradually weakened. Mechanism analysis suggests that the environmental supervision system can break the collusion between government and enterprise, encourage enterprises to carry out technological innovation, change pollutant discharge behavior and push local governments to adjust the industrial structure, enhance environmental protection awareness to reduce the PM2.5 concentration, and improve air quality. Comparing different regions, the PM2.5 in East China, North China and Northeast China are relatively high, and the pressure for air pollution control is great. Meanwhile, we find that the environmental supervision system has a significant station effect. Compared with other cities, the cities where the environmental supervision centers are located are more deterred by the environmental supervision, and their air quality has improved to a significantly greater degree. In the future, we should further strengthen the environmental supervision of high-pollution areas and non-station cities, and pay more attention to improving the long-term effect of the environmental supervision system. [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]

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]