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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]

The market-oriented reform of China's power market has gradually transformed power prices from government pricing to market regulation, which not only promotes the production efficiency of industrial enterprises, but also inhibits the excessive consumption and waste of power by residential power users. This paper uses the data from 2006–2018 combined with the precious industrial power price data and macroeconomic data of 100 cities in China, takes the marketization reform of the power market in 2015 as a quasi-natural experiment, and uses the difference-in-differences model to empirically study the causal relationship between power market reform and air pollution for the first time. The study found that power market reform can reduce air pollution, and this conclusion is also supported by a number of robustness tests. Mechanism analysis shows that power market reform can reduce air pollution by improving power market efficiency, promoting technological progress, and reducing power consumption. Heterogeneity analysis shows that power market reform can suppress air pollution more significantly in eastern regions, regions with severe air pollution, and regions with larger populations. This paper not only provides new research perspectives and research ideas for air pollution prevention and control, but also provides empirical evidence for the positive externalities of power market reform. [ABSTRACT FROM AUTHOR]

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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]

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]

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]

An important task in the construction of China's ecological civilization, the selection and implementation of policy instruments fully reflect the actual effectiveness of the government's efforts to control air pollution. Based on the content analysis method, this study examines the changing process of air pollution control policy instruments in southwest China from 2010 to 2021 in terms of implementation, synergy, and integration of policy instruments. The results show that, in terms of the degree of mandatory, the frequency of using policy instruments generally increased with time, but the overall balance of the instrument portfolio was poor. In terms of the degree of synergy, a gradual shift occurred from government-led to government-society governance. However, the concept and modes of inter-governmental linkage and cross-regional collaborative governance need to be improved. As for the degree of systemic, a clear trend of instrument integration and more frequent information interaction was found. Emergency-oriented characteristics appear strong, but a regular governance mechanism is lacking. Therefore, this paper provides policy suggestions and academic considerations for further improving the effectiveness of air pollution management in southwest China from three aspects: optimizing the policy tool system, deepening the regional joint prevention and control mechanism of air pollution, and promoting intelligent air pollution management. [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]

In this paper, complex network theory has been applied to reveal the transport patterns and cooperative regions of fine particulate matter (PM 2.5) over China from 2015 to 2019. The results show that the degrees, weighted degrees, and edge lengths of PM 2.5 cities follow power law distributions. We find that the cities in the Beijing–Tianjin–Hebei–Henan–Shandong (BTHHS) region have a strong ability to export PM 2.5 pollution to other cities. By analyzing the transport routes, we show that a mass of links extends southward from the BTHHS to the Yangtze River Delta (YRD) regions with 1 or 2 d time lags. Hence, we conclude that earlier emission reduction in the BTHHS region and early warning measures in the YRD region will provide better air pollution mitigation in both regions. Moreover, significant links are concentrated in wintertime, suggesting the impact of the winter monsoon. In addition, all cities have been divided into nine clusters according to their spatial correlations. We suggest that the cities in the same clusters should be regarded as a whole to control the level of air pollution. This approach is able to characterize the transport and cluster for other air pollutants, such as ozone and NOx. [ABSTRACT FROM AUTHOR]

The effectiveness of national policies for air pollution control has been demonstrated, but the relative effectiveness of short-term emission reduction measures in comparison with national policies has not. Here we show that short-term abatement measures during important international events substantially reduced PM2.5 concentrations, but air quality rebounded to pre-event levels after the measures ceased. Long-term adherence to strict emission reduction policies led to successful decreases of 54% in PM2.5 concentrations in Beijing, and 23% in atmospheric nitrogen deposition in China from 2012 to 2020. Incentivized by "blue skies" type campaigns, economic development and reactive nitrogen pollution are quickly decoupled, showing that a combination of inspiring but aggressive short-term measures and effective but durable long-term policies delivers sustainable air quality improvement. However, increased ammonia concentrations, transboundary pollutant flows, and the complexity to achieving reduction targets under climate change scenarios, underscore the need for the synergistic control of multiple pollutants and inter-regional action. In response to the rebound of air pollution during large events in China, the authors propose that a combination of ambitious short-term measures and enduring long-term pollution control policies is a sustainable solution for improving air quality. [ABSTRACT FROM AUTHOR]

In recent years, air pollution has received serious concerns from researchers, media, and the public sectors, but air pollution from agricultural production activities has not received enough attention. This paper focuses on agricultural air pollution in central China, which is aggravated by the ongoing rural labor migration trend. With a set of panel data released from Hubei and Hunan provinces in China, we adopt the mediating effect model to explore the relationship between rural labor migration and air pollution caused by agricultural activity in China. First, we use the inventory analysis method and principal component analysis method to calculate the comprehensive index of the air pollution of agriculture in 152 counties and districts from Hubei and Hunan provinces, and we empirically test the impact of labor migration on air pollution with a mediating effect model as well as carry out regional heterogeneity analysis on the pollution effect of these two provinces mentioned above. The analysis above indicates that the increase of labor migration has intensified the comprehensive index of air pollution caused by agricultural activity by changing the supply of labor force in the agricultural sector, the budget line of rural residents, and the scale of agricultural production and crop planting structure, but there is a difference in the indirect total effect between the two provinces mentioned above according to our regional heterogeneity analysis. This study is a necessary extension to studies on alleviating and controlling air pollution in China. [ABSTRACT FROM AUTHOR]

Due to the country's rapid economic growth, the problem of air pollution in China is becoming increasingly serious. In order to achieve a win-win situation for the environment and urban development, the government has issued many policies to strengthen environmental protection. PM2.5 is the primary particulate matter in air pollution, so an accurate estimation of PM2.5 distribution is of great significance. Although previous studies have attempted to retrieve PM2.5 using geostatistical or aerosol remote sensing retrieval methods, the current rough resolution and accuracy remain as limitations of such methods. This paper proposes a fine-grained spatiotemporal PM2.5 retrieval method that comprehensively considers various datasets, such as Landsat 8 satellite images, ground monitoring station data, and socio-economic data, to explore the applicability of different machine learning algorithms in PM2.5 retrieval. Six typical algorithms were used to train the multi-dimensional elements in a series of experiments. The characteristics of retrieval accuracy in different scenarios were clarified mainly according to the validation index, R2. The random forest algorithm was shown to have the best numerical and PM2.5-based air-quality-category accuracy, with a cross-validated R2 of 0.86 and a category retrieval accuracy of 0.83, while both maintained excellent retrieval accuracy and achieved a high spatiotemporal resolution. Based on this retrieval model, we evaluated the PM2.5 distribution characteristics and hourly variation in the sample area, as well as the functions of different input variables in the model. The PM2.5 retrieval method proposed in this paper provides a new model for fine-grained PM2.5 concentration estimation to determine the distribution laws of air pollutants and thereby specify more effective measures to realize the high-quality development of the city. [ABSTRACT FROM AUTHOR]

Since China's clean air action, PM 2.5 (particulate matter with an aerodynamic equivalent diameter of 2.5 µm or less) air quality has improved, while ozone (O 3) pollution has become more severe. Here we apply a coupled meteorology–chemistry model (WRF-Chem: Weather Research and Forecasting model coupled to Chemistry v3.7.1) to quantify the responses of aerosol–radiation interaction (ARI) to anthropogenic emission reductions from 2013 to 2017, including aerosol–photolysis interaction (API) related to photolysis rate change and aerosol–radiation feedback (ARF) related to meteorological field change and their contributions to O 3 increases over eastern China in summer and winter. Sensitivity experiments show that the decreased anthropogenic emissions play a more prominent role in the increased daily maximum 8 h average (MDA8) O 3 in both summer (+ 1.96 ppb vs. + 0.07 ppb) and winter (+ 3.56 ppb vs. - 1.08 ppb) than the impacts of changed meteorological conditions in urban areas. The decreased PM 2.5 caused by emission reductions can result in a weaker impact of ARI on O 3 concentrations, which superimposes its effect on the worsened O 3 air quality. The weakened ARI due to decreased anthropogenic emissions aggravates the summer (winter) O 3 pollution by + 0.81 ppb (+ 0.63 ppb), averaged over eastern China, with weakened API contributing 55.6 % (61.9 %) and ARF contributing 44.4 % (38.1 %), respectively. This superimposed effect is more significant for urban areas during summer (+ 1.77 ppb). Process analysis indicates that the enhanced chemical production is the dominant process for the increased O 3 concentrations caused by weakened ARI in both summer and winter. This study innovatively reveals the adverse effect of weakened aerosol–radiation interaction due to decreased anthropogenic emissions on O 3 air quality, indicating that more stringent coordinated air pollution control strategies should be implemented for significant improvements in future air quality. [ABSTRACT FROM AUTHOR]

• The principle of difference information and the principle of minimum information are discussed. • The proposed method can deal with the environment problem in other regions. • The unequal adjacent accumulation multivariate grey model is used to forecast the public concern about air pollution. In grey theory, the principle of difference information holds that difference is information. To mine the difference information between data, the unequal accumulation is proposed in this paper. The unequal accumulation reduces the loss of difference information and improves the forecasting performance of the grey model. Based on the unequal accumulation, the unequal adjacent discrete multivariable grey model is proposed. According to the comparison with other models, the proposed model has good forecast performance and algorithm efficiency. To further prove the practical significance of the model, it is used to predict the public concern about air pollution in three cities of China. The results show that the public concern about air pollution in cities with different air pollution conditions is quite different. Environmental protection departments could pay attention to the public concern about air pollution to better control air pollution. [ABSTRACT FROM AUTHOR]

Air pollution treatment has become the priority in environmental management for Chinese government. However, environmental problems are closely related to people's interests, it is far from enough to rely solely on the government. Public participation is a significant factor for environment protection; only under the common promotion of the whole society can we do a good job in environmental governance. Thus, this research analyses whether public participation can affect the emission behavior of enterprises by analyzing province panel data of China. The results show that direct and indirect public participation both have a significant positive impact on the control of industrial air pollution by strengthening the supervision of environmental law enforcement. Besides, we also find that indirect public participation can influence the formulation of environmental policies. The research helps to understand the current situation of public participation in developing countries. Results suggest the importance of public participation in environment governance, but the level of public participation in China is still in its infancy and needs to be further improved. [ABSTRACT FROM AUTHOR]

• The causal impact of green space on air pollution remains understudied. • Here, the Normalized Difference Vegetation Index (NDVI) was used to assess green space level in each county of China. • Two-stage least squares estimation (2SLS) and multiplex IV was employed to verify the robustness. • The increased greenspace significantly decreases the PM 2.5 concentration and other air pollutants. • Green spaces show a more pronounced air pollution reduction effect in southern or higher administrative-level cities. Can green vegetation absorb air pollutants and control regional air pollution? The existing research has not reached a consistent conclusion on this issue. Using the multi-level data in China, this paper provides empirical evidence of the causal impact of greenspace on PM 2.5 through the abundant fixed effect and controls. Besides, this paper applied the soil humidity, Normalized Difference Vegetation Index (NDVI) last month, NDVI in the same month last year, and NDVI prefecture-level city average as the instrumental variables, respectively, to test the robustness of the estimation. The results show that increased greenspace significantly decreases the PM 2.5 concentration and other air pollutants. In further analysis, we found that the decreasing effect turns significant when NDVI exceeds 0.3. In addition, there are regional heterogeneities in the impact of greenspace on air pollution. Greenspaces show a more pronounced air pollution reduction effect in southern or higher administrative-level cities. This paper suggests that increasing greenspace is an economical and effective way to achieve co-management of multiple air pollutants. [ABSTRACT FROM AUTHOR]

In order to investigate the causes of complex air pollution in coastal cities in the Bohai Rim of China, a one-month intensive field observation combined with model simulation was carried out in a typical city named Dongying in September 2022. The results showed that two PM2.5 and O3 complex pollution episodes occurred in Dongying in the observation period, with the primary pollutant being O3. Atmospheric photochemical reactions occurring under unfavorable meteorological conditions led to the production of O3 while at the same time facilitating the generation of nitrate, sulfate, and other secondary components of PM2.5 by enhancing the atmospheric oxidizing capacity, which promoted the formation of complex air pollution. It was worth noting that in the context of high pollutants emission, the occurrence of complex air pollution was more sensitive to the variation in meteorological conditions than to the change in pollutants emission. To continuously improve air quality and protect human health in Dongying, it is recommended that an effective regional joint air pollution prevention and control mechanism with neighboring cities should be established in the premise of effective local pollutants reduction, and special attention should be paid to the adverse effect of the air mass transportation from Bohai Bay. [ABSTRACT FROM AUTHOR]

The "Air Pollution Prevention and Control Action Plan" is regarded as China's war against air pollution, which is also noted as China's Clean Air Action (CAA policy). Although abundant studies have focused on the impact of CAA policy on social activities, such as air quality, pollutants emission, and economic output, limited studies explore its impact on enterprise competitiveness from a more micro perspective. Improving total factor productivity (TFP) is essential to achieve economic efficiency and sustainable development. Identifying the impact and influence mechanism of the CAA policy on TFP is important for China to realize the coordinated development of environment and economy and promote high-quality economic development. Based on the difference-in-differences model, this paper evaluates the impact of the CAA policy on enterprise productivity. The empirical analysis shows that there is a significantly negative effect from the CAA policy to the TFP of polluting enterprises, indicating that the CAA policy has decreased enterprise productivity. Our finding is robust, after conducting several robustness tests, such as replacing different dependent indicators, adopting different policy measurement variables, considering other policy interventions and using propensity score matching. Besides, this paper also discusses the possible heterogeneities. This paper adds additional empirical evidence to understand the relationship between air pollution control and enterprise competitiveness. The conclusions of this paper have important practical significance for China to further promote air pollution control and perfect the environmental control system. • We analyze the impact of China's Clean Air Action on enterprise competitiveness. • There is a negative effect from the Clean Air Action policy to enterprise total factor productivity. • Possible heterogeneities have been discussed from several aspects. • This paper adds additional empirical evidence to understand China's Clean Air Action. [ABSTRACT FROM AUTHOR]

Due to variations in economic scale, economic structure, and technological advancement across different Chinese provinces and cities, the cost of air pollution reduction differs significantly. Therefore, the total reduction cost can be decreased by capitalizing on these regional discrepancies in reduction cost to carry out cooperative emission reduction. In this paper, taking NO x reduction in North China as an example, a regional cooperative reduction game (CRG) model was constructed to minimize the total cost of emission reduction while achieving future emission reduction targets. The fair allocation of benefits from cooperation plays a crucial role in motivating regions to participate into the cooperation. A comprehensive mechanism of benefits allocation was proposed to achieve fair transferred compensation. The mechanism combines the consumption responsibility principle based on input-output theory and the Shapley value method based on game theory. Compared to the cost before the optimized collaboration, the CRG model will save 20.36% and 13.71% of the total reduction cost in North China, respectively, under the target of 17.68% NO x reduction by 2025 and 66.44% NO x reduction by 2035 relative to 2020. This method can be employed in other regions to achieve targets for air pollution reduction at minimum cost, and to motivate inter-regional cooperation with this practical and fair way of transferred compensation. [Display omitted] • A regional cooperative reduction game model for air pollution was constructed. • We projected NO x reduction cost savings in North China under two future scenarios. • An integrated approach was used to allocate cooperative benefits with fairness. • The model helps achieve air pollution reduction targets at the minimum cost. [ABSTRACT FROM AUTHOR]

Protecting human health from fine particulate matter (PM) pollution is the ambitious goal of clean air actions, but current control strategies largely ignore the role of source-specific PM toxicity. Here, we proposed health-oriented control strategies by integrating the unequal toxic potencies of the most polluting industrial PMs. Iron and steel industry (ISI)-emitted PM2.5 exhibit about one order of magnitude higher toxic potency than those of cement and power industries. Compared with the current mass-based control strategy (prioritizing implementation of ultralow emission standards in the power sector), the proposed health-oriented control strategy (priority control of the ISI sector) could generate 5.4 times higher reduction in population-weighted toxic potency-adjusted PM2.5 exposure among polluting industries in China. Furthermore, the marginal abatement cost per unit of toxic potency-adjusted mass of ISI-emitted PM2.5 is only a quarter of that of the other two sectors under ultralow emission scenarios. We highlight that a health-oriented air pollution control strategy is urgently required to achieve cost-effective reductions in particulate exposure risks. Health-oriented emissions reduction in China focusing on the iron and steel industry can reduce costs by 1.56 billion dollars while lowering the population-weighted toxic potency-adjusted exposure risk. [ABSTRACT FROM AUTHOR]

Air pollution is a hotspot of wide concern in Chinese cities. With the worsening of air pollution, urban agglomerations face an increasingly complex environment for air quality monitoring, hindering sustainable and high-quality development in China. More effective methods for predicting air quality are urgently needed. In this study, we employed seven single models and ensemble learning algorithms and constructed a hybrid learning algorithm, the LSTM-SVR model, totaling eight machine learning algorithms, to predict the Air Quality Index in six major urban agglomerations in China. We comprehensively compared the predictive performance of the eight algorithmic models in different urban agglomerations. The results reveal that, in areas with higher levels of air pollution, the situation for model prediction is more complicated, leading to a decline in predictive accuracy. The constructed hybrid model LSTM-SVR demonstrated the best predictive performance, followed by the ensemble model RF, both of which effectively enhanced the predictive accuracy in heavily polluted areas. Overall, the predictive performance of the hybrid and ensemble models is superior to that of the single-model prediction methods. This study provides AI technological support for air quality prediction in various regions and offers a more comprehensive discussion of the performance differences between different types of algorithms, contributing to the practical application of air pollution control. [ABSTRACT FROM AUTHOR]

With the advancement of urbanization in China, effective control of pollutant emissions and air quality have become important goals in current environmental management. Nitrogen dioxide (NO2), as a precursor of tropospheric ozone and fine particulate matter, plays a significant role in atmospheric chemistry research and air pollution control. However, the uneven ground monitoring stations and low temporal resolution of polar-orbiting satellites set challenges for accurately assessing near-surface NO2 concentrations. To address this issue, a spatiotemporal refined NO2 retrieval model was established for China using the geostationary satellite Himawari-8. The spatiotemporal characteristics of NO2 were analyzed and its contribution factors were explored. Firstly, seven Himawari-8 channels sensitive to NO2 were selected by using the forward feature selection based on information entropy. Subsequently, a 2DCNN-LSTM network model was constructed, incorporating the selected channels and meteorological variables as retrieval factors to estimate hourly NO2 in China from March 2018 to February 2020 (with a resolution of 0.05°, per hour). The performance evaluation demonstrates that the full-channel 2DCNN-LSTM model has good fitting capability and robustness (R2 = 0.74, RMSE = 10.93), and further improvements were achieved after channel selection (R2 = 0.87, RMSE = 6.84). The 10-fold cross-validation results indicate that the R2 between retrieval and measured values was above 0.85, the MAE was within 5.60, and the RMSE iwas within 7.90. R2 varied between 0.85 and 0.90, showing better validation at mid-day (R2 = 0.89) and in spring and fall transition seasons (R2 = 0.88 and R2 = 0.90). To investigate the cooperative effect of meteorological factors and other air pollutants on NO2, statistical methods (beta coefficients) were used to test the factor interpretability. Meteorological factors as well as other pollutants were analyzed. From a statistical perspective, PM2.5, boundary layer height, and O3 were found to have the largest impacts on near-surface NO2 concentrations, with each standard deviation change in these factors leading to 0.28, 0.24, and 0.23 in standard deviations of near-surface NO2, respectively. The findings of this study contribute to a comprehensive understanding of the spatiotemporal distribution of NO2 and provide a scientific basis for formulating targeted air pollution policies. [ABSTRACT FROM AUTHOR]

To abate the severe air pollution, the Chinese government released the Action Plan of Air Pollution Prevention and Control (APAPPC) in 2013. This paper regards the APAPPC as a quasi-experiment and uses the DID method to investigate the impact of environmental regulation on the growth of green total-factor productivity of China's industries. This article employs the non-radial directional distance function (NDDF) and the global Malmquist index to measure the total-factor carbon productivity of China's industries. Further regressions suggest that the implementation of the APAPPC has significantly promoted the growth of the total-factor carbon productivity in the air pollution-intensive industries, and its marginal effect has steadily increased with time. This result is still valid after using a series of counterfactual tests and robustness tests. The further mechanism study shows that the APAPPC has significantly promoted R&D investment, especially in instruments and equipment, which has effectively promoted technical efficiency and technological advancement. It indicates that stringent and well-designed environmental regulations should lead to a "win-win" situation of environmental improvement and economic development by encouraging enterprises to upgrade their technology and equipment. • This paper uses a typical case in China to demonstrate the porter's hypothesis. • This paper uses the DEA method to measure the total-factor carbon productivity of China's industries. • The Action Plan of Air Pollution Prevention and Control in China has significantly promoted the growth of total-factor carbon productivity. • The regulation promotes productivity by propelling enterprises to increase R&D investment and update their technical equipment. [ABSTRACT FROM AUTHOR]

Previous studies have often focused on the direct benefits of environmental regulations on health. This paper quantifies the impact of environmental regulations on the cost of prevention for urban residents. The purpose of this study is to examine how environmental regulations affect urban commercial health insurance purchases. Air pollution monitoring stations in China capture exogenous air quality changes to overcome potential endogenous problems. Evidence shows that an increase in the operating days of air pollution monitoring stations will reduce the purchase of commercial health insurance in the city. The mechanism is that the operation of air pollution monitoring stations is conducive to improving local air quality and alleviating residents' health prevention needs. Heterogeneity analysis shows that the impact of air pollution monitoring station operation on the cost of prevention is less effective in more developed cities. Finally, we demonstrate that the number of claims for commercial health insurance dropped with the operation of air pollution monitoring stations. The results show that the benefits of improved air pollution do not only include the direct benefits of increased health, but also include the potential benefits of reduced prevention costs. Ultimately, the results further indicate the importance of air pollution control. [ABSTRACT FROM AUTHOR]

Both meteorological changes and emission control have significant impacts on PM 2.5 concentration and regional transport contribution, where it is important to clarify the relationship among them for air pollution control. In this paper, the WRF-CAMx coupled with a set of simulation scenarios was employed for decomposing the contributions of meteorological conditions, emission, and regional transport considering transport matrix to PM 2.5 concentration in the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions during 2013–2017. The results show that the local contributions occupied the primary position in PM 2.5 concentrations in the BTH and YRD regions, reaching 57.9% and 58.1% in 2017, respectively. In terms of regional transports, they were mainly from Shandong Peninsula (SP) and Fen Nutrient Plain (FNP) for BTH, while Central triangle Region (CTR) and SP for YRD. Analysis of typical representative months suggested that in January, the concentration of local contribution reached peak. In addition, the results also show that when the intensity of emission reduction increased, the proportion of local contribution increased significantly while the local absolute contribution concentration decreased correspondingly. The meteorological conditions had little impact on transport matrix dominated by local contribution, whereas, the more favorable the meteorological diffusion conditions, the lower the contribution ratio of the out-of-region transport and the lower the contribution concentration. Moreover, the variation of meteorological conditions was more significant to the transport contribution outside the region. These findings can be helpful for formulating reasonable strategies of regional joint prevention and control and providing a valuable preference for other areas of China. [Display omitted] • The transport matrix of PM 2.5 was established using the WRF-CAMx model. • Emission reduction dominated the total decrease in PM 2.5. • Local emissions contributed 57.9% and 58.1% of PM 2.5 in BTH and YRD. • Meteorological conditions had a significant impact on the regional transport. [ABSTRACT FROM AUTHOR]

Currently, air pollution is primarily characterized by PM 2.5 and O 3. Therefore, the co-control of PM 2.5 and O 3 has become an important task of atmosphere pollution prevention and control in China. However, few studies have been conducted on the emissions from vapor recovery and processes, which is an important source of VOCs. This paper analyzed the VOC emissions of three vapor process technologies in service stations and first proposed key pollutants for priority control based on the coordinated reactivity of O 3 and SOA. The concentration of VOCs emitted from the vapor processor was 3.14–9.95 g m−3, compared to 631.2–717.8 g m−3 for uncontrolled vapor. Alkanes, alkenes, and halocarbons accounted for a high proportion of the vapor both before and after control. Among the emissions, i -pentane, n -butane, and i -butane were the most abundant species. Then, the species of OFP and SOAP were calculated through the maximum incremental reactivity (MIR) and fractional aerosol coefficient (FAC). The average source reactivity (SR) value of the VOC emissions from three service stations was 1.9 g g−1, while the OFP ranged from 8.2 to 13.9 g m−3 and SOAP ranged from 0.18 to 0.36 g m−3. By considering the coordinated chemical reactivity of O 3 and SOA, a comprehensive control index (CCI) was proposed for the control of key pollutant species that have multiplier effects on environment. For adsorption, trans -2-butene and p -xylene were the key co-control pollutants, while toluene and trans -2-butene were the most important for membrane and condensation + membrane control. A 50% emission reduction of the top two key species that emission account for 4.3% averagely will reduce O 3 by 18.4% and SOA by 17.9%. [Display omitted] • The organized emissions of VOCs from three vapor processors were studied in service stations. • The species composition of VOCs before and after control were analyzed. • The OFP and SOAP were calculated to evaluate the secondary pollution. • The co-control of key pollutants based on SOA and O 3 has great environmental benefits. [ABSTRACT FROM AUTHOR]

Production restriction is an environmental regulation adopted in China to curb the air pollution of industrial enterprises. Frequent production restrictions may cause economic losses for enterprises and further hinder their green transformation. Polluting enterprises are faced with the dilemma of choosing environmental protection or economic development. Using panel data on industrial enterprises in China from 2016 to 2019, this paper evaluates the impact of production restrictions on both enterprises' environmental and economic performance with regression models. The results show that production restrictions significantly drop the concentrations of SO2 and NOx emitted from polluting enterprises. Meanwhile, production restrictions have significant negative effects on operating income, financial expenses, net profit, and environmental protection investment. The mechanism analysis reveals that production restrictions mitigate air pollutant concentrations by increasing the number of green patents and improving total factor productivity, which also verifies the Porter hypothesis. However, there is a masking mediating effect of environmental investment, which indicates that the reduction of environmental investment hinders the enterprise's efforts to control air pollution. In addition, heterogeneous analysis shows that the economic shock on microenterprises is larger than that on small enterprises. Implementing production restrictions for microenterprises may be a way to eliminate their backwards production capacity. • Production restriction dropped air pollutants of polluting enterprises. • Production restriction has negative effects on business performance of enterprises. • TFP and green innovation are the mediating variables of pollution reduction. • The reduction of environmental investment hinders the pollution control. • The shocks to the business performance of microenterprises are larger. [ABSTRACT FROM AUTHOR]

Air pollution has become a global public health risk factor as rapid urbanization advances. To observe the air pollution situation, air monitoring stations have been established in many cities, which record six air pollutants. Previous studies have identified cities exhibiting similar air pollution characteristics by combining principal component analysis (PCA) with cluster analysis (CA). However, spatial and temporal effects were neglected. In this paper, we focus on the combination of GTWPCA and STCA, which fully incorporates spatio-temporal effects. It is then applied to air pollution data from the top 10 urban agglomerations in China during 2016–2021. Key experimental findings include: 1. GTWPCA provides a more detailed interpretation of local variation than PCA. 2. Compared with CA, STCA highlights the coupling effect in the spatial and temporal dimensions. 3. The combination of GTWPCA and STCA captures similar air pollution characteristics from spatio-temporal perspectives, which has the potential to help environmental authorities take further action to control air pollution. • Proposed new framework combining GTWPCA and STCA. • Identified the main air pollutants at spatial and temporal locations. • Captured similar air pollution behavior over space and time. [ABSTRACT FROM AUTHOR]

Previous studies analysing the effects of air pollution on work efficiency did not pay much attention to indoor impacts. This paper attempts to fill this gap by using technical data from Chinese Basketball Association (CBA) players. For the first time, we present personal work efficiency using a comprehensive evaluation index, the player efficiency rating (PER). The information is then combined with daily air quality data. We find that air pollution reduces work productivity: for every 10% increase in the air quality index (AQI), the average PER decreases by 0.4221, and the effects vary by air pollutant. Heterogeneity analysis shows that at the level of competition venues, the negative impact of air pollution on work efficiency can be weakened at home, while the rising temperature in the competition city can amplify the negative impact of air pollution on work efficiency. At the level of individual players, older players and foreign players are less affected by air pollution. Moreover, we find that air pollution affects work efficiency by reducing total work output and work accuracy. Our research constructs a comprehensive evaluation index for work efficiency, enriches research on the influence of air pollution on work efficiency, and provides a policy basis for identifying groups that are sensitive to air pollution, which might help with air pollution control policy making. [ABSTRACT FROM AUTHOR]

Due to the spillover nature of air pollution, the territorial separate governance mode is ineffective in combating pollution, making Joint Prevention and Control of Air Pollution (JPCAP) among multiple regions the only viable option. However, determining the appropriate scopes and priorities for JPCAP is known to be a challenging and significant issue. To address this, we propose a new two-stage hybrid model. In the first stage, making use of long-term, wide area monitoring data provided by the air pollution monitoring network, we propose a new method for subdividing large regions into sub-regions by using data mining techniques. In the second stage, we propose a comprehensive decision-making framework to evaluate the priorities of JPCAP sub-regions from three different perspectives, namely, the impact of a sub-region on the pollution level of the entire target region, as well as the urgency and elasticity of sub-regional air pollution control. A case study is conducted on 27 cities of the Yangtze River Delta region of China. The case study demonstrates the validity and practicality of the proposed two-stage hybrid model. This work provides a viable tool for the effective implementation of air pollution control in China and other regions of the world. [ABSTRACT FROM AUTHOR]

With the quick advancement of new generation information technologies like the Internet, big data, cloud computing, artificial intelligence, and blockchain, digitalization is emerging as a crucial tool for restructuring factor resources, reshaping the economic landscape, and altering competitiveness. However, there is no literature on the impact and mechanism of digitalization on environmental pollution management. Thus, this study measured the level of digital development in each province using principal component analysis based on panel data of 30 Chinese provinces during 2006–2019. On this basis, the impact of digitalization on haze and its mechanisms were explored using regression models and mediating effect models, respectively. The findings demonstrate that (1) haze pollution may be reduced through digital progresses, and there is an inverse U-shaped non-linear link between them, that is, as digital technology is refined, its impact on haze pollution shifts from facilitation to suppression; (2) digital development can reduce haze pollution by promoting technological innovation and improving the efficiency of environmental management; and (3) there is regional heterogeneity in the influence of digitalization on air pollution. In heavily polluted areas, the suppression effect of digital technology on air pollution is more than three times that of other areas. The goal of this study is to investigate how digitalization affects haze pollution and its mechanisms, as well as to offer some scientific guidance for China's efforts to build a "Digital China" under the banner of digitalization. [ABSTRACT FROM AUTHOR]

Background: Atrial fibrillation (AF) is the most common arrhythmia, resulting in serious cardiovascular diseases. Air pollution may cause heart rate disturbance, but there is no clear or consistent evidence that short-term exposure to air pollution leads to an increased risk of hospitalisation for symptomatic episodes of AF. This study aimed to assess the impact of short-term exposure to air pollution on inpatient numbers. Methods: The inpatient records of AF cases in nine cities of the Sichuan Province, China and air pollution and meteorological data from 183 monitoring stations from 2017 to 2018 were collected. The impact of short-term exposure to air pollution on AF inpatients was evaluated using a time-stratified crossover case study design. The economic burden of AF attributable to air pollution was also estimated. Results: A total of 5,958 patients with AF from 123 medical institutions were included in the analysis. Air pollutants had a significant impact on the number of patients with AF. The number increased by 2.5% (95% confidence interval [CI] = 1.006 to 1.044) and 1.8% (95% CI = 1.003–1.033) for every 10 µg/m3 increase in PM2.5, PM10, concentration, respectively. Moreover, the number increased by 12.7% (95% CI = 1.006 to 1.262) for every 10 µg/m3 increase of SO2 concentration. For every 0.1 μg/m3 increase in CO concentration, the number of inpatients with AF increased by 3.9% (95% CI = 1.010–1.070). People aged 65 years or older and women were more likely to be affected by air pollutants. The AF in 430 and 209 inpatients were attributable to PM2.5 and PM10, respectively. The total hospitalization expenses attributed to excessive exposure to PM2.5 and PM10 were 13.98 million CNY and 6.68 million CNY, respectively. Furthermore, the out-of-pocket expenses were 6.81 million CNY and 3.28 million CNY, respectively. Conclusions: This study showed a strong correlation between air pollution and AF. Hence, there is a need to reduce air pollution to control health risks. [ABSTRACT FROM AUTHOR]

Since the 2000s, China has enforced regional collaboration as a way of resolving cross-diffused air pollution and jurisdictional limitations. It is, however, a hotly debated issue as to whether authority-driven regional collaboration can be sustained and effective, and no consensus has been achieved by the theoretical discussion. Despite extensive empirical research on the topic, most studies judged the sustainability of collaborations by analyzing the environmental outcomes within a short period after their initiation. To provide more comprehensive empirical evidence to the open question, this paper introduces the criterion of adaptivity to determine whether collaboration is sustainable. Taking the changing collaboration in Beijing-Tianjin-Hebei and its surroundings as a quasi-natural experiment, Difference-in-Difference model and Triple Difference Model are used to verify the adaptivity from two aspects. Results show that authority-driven collaboration adjustment yields better environmental outcomes. Additionally, the better environmental outcome is observed in original collaborators, implying that local governments can learn by doing and form interdependence through repeated collaborative actions. The adaptive collaboration, however, has two limitations. First, the collaboration mechanism is formed primarily based on performance evaluation and target assessment instruments, without showing adaptivity in reducing soft control indicators of air pollution. Second, the different regulation pressure between non-collaborating and collaboration cities results in undesirable spillover effects within a range of 40–100 km. This study not only contributes to empirical and theoretical studies on regional collaboration but also provides support to the improvement of the collaboration system in practice. • Process-adaptivity is introduced as the criterion to evaluate collaboration. • Authority-driven collaboration generates positive environmental outcomes. • Authority-driven collaboration is adaptive but limited to mandatory indicators. • Regional collaboration brings out negative spillovers within 40–100 km. [ABSTRACT FROM AUTHOR]

Chinese officials play an important role in air pollution control. This paper used a sample of 282 prefecture-level cities in China to discuss the impact of promotion incentives of officials on air pollution from the perspectives of heterogeneity, mechanism and spatial effects. We found that the promotion incentives of officials reduced air pollution, and GDP per capita had positive moderating effects. The effects of promotion incentives were more significant in cities with less air pollution, in the central and western regions, for officials with higher education levels, or years after 2007. The promotion incentives could promote the development of green finance and green technology innovation, both of which were conducive to mitigating air pollution. Using the dynamic spatial Durbin model (DSDM), we found that the promotion incentives had negative spatial spillover effects. The promotion incentives in surrounding cities reduced air pollution in the local city; however, it had only short-run effects and no long-run effects. • The promotion incentives of officials could significantly reduce air pollution. • The effects of promotion incentives on air pollution have heterogeneity. • Green finance and green technology innovation have positive mediating effects. • Promotion incentives have negative spatial spillover effects in the short-run and no long-run effects. [ABSTRACT FROM AUTHOR]

Central environmental inspection (CEI), an innovative incentive mechanism to position the central authority to complement local regulators of pollution mitigation in China, may play a vital role in air pollution control. This paper describes an investigation that drew upon daily air quality data from 282 prefecture-level and above cities and employed an event-study design to scrutinize the impact of policy shock on air pollution mitigation. Our main finding is that CEI significantly reduced the Air Quality Index (AQI) and concentrations of PM 2.5 , PM 10 , SO 2 , NO 2 , and CO. Only O 3 increased during the on-site inspection probably due to the opposite effect with high NO X concentrations relative to VOCs. When NO X is reduced, ozone therefore increases. However, according to dynamic evidence, CEI failed to bring about long-term enduring sustained reductions. A probable explanation is that local officials has informed the pollution-contributing firms in advance, which consequently decreased their emissions by a small amount in the month prior to the inspection and then allowed emissions to return to historic levels after the inspectors departed. Notably, while PM 2.5 , NO 2 , and CO increased above their normal levels, this pattern did not apply to SO 2 , suggesting that some firms, with the exception of the power sector, recovered from previously lost production by subsequently increasing production. We also found evidence from the analysis of the VIIRS Night-Time Light data that the unsustainable improvement in environmental performance was indeed achieved by the firms' restrictions on production. Moreover, the data also provide strong evidence that more heavily polluted cities and inland areas of China were more responsive to the enforcement of CEI, perhaps as the result of an emphasis on heavy industry in those locations. This report concludes by proposing further policy implementations for the future optimization of China's environmental governance and sustained environmental performance. • China's central authority is deepening the inspection reform for environmental performance. • The Central Environmental Inspection mitigates China's air pollution effect. • There is a pollution rebound in the aftermath of the on-sited inspection. • Performance of the policy is largely due to limitations on production activities. [ABSTRACT FROM AUTHOR]

Plant growth and crop harvest are impacted by both climate change and air pollution. However, their relative importance in crop yields remains elusive, especially in heavily polluted regions. Here we develop crop yield prediction models, based on a large volume of historical crop data, as well as climate and pollution records in China since 1980. A long‐term surface ozone concentration data set is developed from a machine‐learning model and various observations. An assessment of four climate and pollution factors reveals the critical role of particulate and ozone pollution in regulating interannual variations of crop yields in China. During 2010–2018, we find that the particulate pollution mitigation outweighs the negative impacts of concurrent climate change, resulting in 0.5%–1.9% net yield increases nationwide, despite of the ozone increases in the North China Plain. Looking to the future, the impacts of climate change, particularly from surface temperature increase, will dominate over pollution factors and profoundly reduce future maize and rice yields by 0.6 to 2.8% 10 yr−1 by 2050. Our findings call for attention on the threat to future global food security from the absence of pollution mitigation and the persistence of global warming. Plain Language Summary: We capitalize on 39‐year historical records of crop yields, climate variables, and pollution data to develop a robust crop yield prediction model. Utilizing this model, we show a critical role of particulate pollution in determining annual crop yields. Moreover, our analyses reveal that the recent abatement of anthropogenic emission in China results in a net crop gain, which masks the crop loss due to the increased temperature and precipitation. In the next 30 years, temperature dominant climate effects will emerge to steer the future trend of crop yields. The present study demonstrates the co‐benefit of the recent air pollution control policy from agriculture and food perspectives. However, this benefit will eventually be diminished after the air pollution becomes alleviated in the full scale, while persisting or even exacerbated global warming will pose larger threat on the future food security. Key Points: Robust crop yield prediction models are developed to assess climate change and air pollution impacts on agricultureDuring 2010–2018, the particulate pollution mitigation outweighs the negative impacts of concurrent climate change in ChinaExacerbated global warming will lead to crop yield reduction in spite of pollution alleviation in the future scenarios [ABSTRACT FROM AUTHOR]

This study investigated the regional transport of particulate matter (PM2.5) leading to air pollution in Fuzhou, in the west bank of the Taiwan Strait (WBTS), which has a relatively good air quality with a lower aerosol optical depth than that of East China. The continental polluted aerosol zone over the coast of East China was identified as an aerosol transport belt, and the daily aerosol dynamics observed by MODIS remote sensing indicated the southward transport of fine particulate matter to the WBTS along the coast. The external air pollutants from regional transport contributed 84% of the PM2.5 detected in Fuzhou, while only 16% due to local emissions of air pollutants. The northerly winds of the cold front drove the southward transport of polluted air masses along the coast of the northwest Pacific from the Yangtze River Delta (YRD) to the WBTS. The vertical mixing of air pollutants from the upper boundary layer to the surface layer could be conducive to regional‐transport‐induced haze pollution in this coastal area of the WBTS. Fuzhou is considered a receptor region of PM2.5 transport in Eastern China, and the source region is mainly from the YRD. The results of this study have significant implications on determining the source of pollution and controlling local air quality for good air quality regions. This study also shed some light on using multi‐satellites to fill the surface observation gaps in coast or nearshore areas, and to confirm the characteristics and passways of aerosol transport. Key Points: The southward transport of air pollutants built up a source‐receptor relationship in East Aisa Monsoon regionThe transport of exogenous PM2.5 accounts for more than 80% during a severe haze pollution in FuzhouThe unstable atmospheric boundary layer leads to the downward mixing of PM2.5 to the surface in clean areas [ABSTRACT FROM AUTHOR]

[Display omitted] • China's air pollution mainly presents a spatial pattern of high-high agglomeration and low-low agglomeration. • New-type urbanization significantly reduces local air pollution. • Industrial structure, technological innovation and energy structure are important transmission mechanisms. • The impact of new-type urbanization on air pollution has regional heterogeneity. To alleviate the ecological and environmental problems caused by rapid urban development, China has formulated and implemented the new-type urbanization strategy. However, there is insufficient empirical research on the specific relationship between new-type urbanization and air pollution. Therefore, based on the panel data of 30 provinces in China from 2005 to 2018, this paper constructs a comprehensive evaluation index system of new-type urbanization using the five dimensions of population, economy, space, society, and green. The spatial Durbin model and the spatial mediating model are used to discuss the spatial effect, transmission mechanism, and regional heterogeneity of new-type urbanization on air pollution. The results show that China's air pollution mainly presents a spatial pattern of high-high agglomeration and low-low agglomeration, and there are spatial fluctuations. The construction of new-type urbanization significantly reduces local air pollution, and the industrial structure optimization, technological innovation, and energy structure adjustment are considered as important transmission mechanisms. However, under the fiscal decentralization and political tournament system in China, the policy implementation deviation may weaken the emission reduction effect of new-type urbanization, which is not conducive to regional environmental governance. From the sub-regional level, the impact of new-type urbanization on air pollution has regional heterogeneity. A robustness test confirms the reliability of our research conclusions. This study also proposes some policy suggestions that the government can utilize in grasping the policy focus of new-type urbanization construction to discover effective ways of controlling air pollution. [ABSTRACT FROM AUTHOR]

Air pollution is not only an environmental problem, but also an economic problem. Faced with the deteriorating air pollution, the role of financial institutions is increasingly valued. Because different air pollutants come from diverse sources, the same economic means have different impacts. To investigate this question, this paper adopts difference-in-differences to test China's green finance policy issued in 2017. The results indicate that green finance policy is capable of controlling overall situation of air pollution. As for the specific six pollutants, it shows superiority in reducing SO 2 , NO 2 and PM 2.5 , but inferiority in reducing CO, O 3 and PM 10. Besides, the control effects of green finance policy are through local companies' economic behaviors. Compared with the economically developed regions, the emission reduction effects of green finance policy in the economically underdeveloped regions are better. These findings offer references for how to control air pollution with economic means from the perspective of micro practice. • Pilot provinces have taken the lead in exploring green finance. • Air pollution is not only an environmental problem, but also an economic problem. • The green finance policy can reduce the air pollution. • The effect of green finance is better in the underdeveloped regions. [ABSTRACT FROM AUTHOR]

In recent years, air pollution has become a factor that cannot be ignored, affecting human lives and health. The distribution of high-density populations and high-intensity development and construction have accentuated the problem of air pollution in China. To accelerate air pollution control and effectively improve environmental air quality, the target of our research was cities with serious air pollution problems to establish a model for air pollution prediction. We used the daily monitoring data of air pollution from January 2016 to December 2020 for the respective cities. We used the long short term memory networks (LSTM) algorithm model to solve the problem of gradient explosion in recurrent neural networks, then used the particle swarm optimization algorithm to determine the parameters of the CNN-LSTM model, and finally introduced the complete ensemble empirical mode decomposition of adaptive noise (CEEMDAN) decomposition to decompose air pollution and improve the accuracy of model prediction. The experimental results show that compared with a single LSTM model, the CEEMDAN-CNN-LSTM model has higher accuracy and lower prediction errors. The CEEMDAN-CNN-LSTM model enables a more precise prediction of air pollution, and may thus be useful for sustainable management and the control of air pollution. [ABSTRACT FROM AUTHOR]

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A thermal internal boundary layer (TIBL) can cause the fumigation effect and reduce the dispersion capacity of air pollutants. The paper's goal is to quantify the interactions of pollutants between cities subjected to enhanced fumigation effects. To that end, an observational campaign was launched at the Shandong Peninsula of China in the winter of 2020. The campaign focused on monitoring vertical profiles of aerosols, wind field, temperature, and humidity for the boundary-layer dynamic-thermodynamic structure. The Nested Air Quality Prediction Modeling System (NAQPMS) coupled with online source-tagging model was also employed to delve into the source-receptor relationships of the cities involved in the fumigation effect. The results indicated that the presence of a TIBL structure triggered the prolonged and widespread pollution episodes. This resulted in a temperature inversion (250–1000 m in altitude) near the convergence line on surface and rendered the atmospheric boundary layer more stably stratified, i.e., a situation that was unfavorable for the diffusion of pollutants against a persistently sinking flow (with a mean velocity of roughly 0.2 m s−1) for a prolonged time. Meanwhile, TIBLs prevented the fumigation areas from interacting with adjacent inland areas (Shandong Peninsula's local contribution accounting for >90% of the PM 2.5) and facilitated inter-city transport of pollutants inside this peninsula (the transport contribution between cities reached up to 55–75%). Such distinct behaviors as observed over this coastal area render air pollution control more of an elusive issue, as is referenced to several inland cities. [Display omitted] ● Quantifying the interactions of pollutants between cities subjected to enhanced fumigation effects ● The presence of a TIBL structure triggered the prolonged and widespread pollution episodes ● TIBLs made the atmospheric boundary layer more stably stratified and unfavorable diffusion of pollutants with strong sinking flowing ● TIBLs prevented fumigation areas from interacting with adjacent inland areas and facilitated inter-city transport of pollutants inside it [ABSTRACT FROM AUTHOR]

In order to control the spread of the COVID-19 pandemic, the prevention and control measures of public health emergencies were initiated in all provinces of China in early 2020, which had a certain impact on air quality. In this study, taking Jiangsu Province in China as an example, the air pollution levels in different regions under different levels of pandemic prevention and control (PPC) measures are evaluated. The implementation of the prevention and control policies of COVID-19 pandemic directly affected the concentration of air pollutants. No matter what level of PPC measures was implemented, the air quality index (AQI) and pollutant concentrations of NO2, CO, PM10 and PM2.5 were all reduced by varied degrees. The higher the level of PPC measures, the greater the reduction was in air pollutant concentrations. Specifically, NO2 was the most sensitive to PPC policies. The concentrations of CO and atmospheric particulate matter (PM10 and PM2.5) decreased most obviously under the first and second level of PPC. The response speed of air quality to different levels of PPC measures varied greatly among different cities. Southern Jiangsu, which has a higher level of economic development and is dominated by secondary and tertiary industries, had a faster response speed and a stronger responsiveness. The results of this study reflect the economic vitality of different cities in economically advanced regions (i.e., Jiangsu Province) in China. Furthermore, the results can provide references for the formulation of PPC policies and help the government make more scientific and reasonable strategies for air pollution prevention and control. [ABSTRACT FROM AUTHOR]

For a long time, air pollution caused by unreasonable urban spatial structure and excessive urban sprawl has been a prominent environmental problem in China. From the level of all cities, three economic zones and different city scales, panel data of 194 prefecture-level cities in China from 2006 to 2017 were used to construct a dynamic panel model and to analyze the impact of urban spatial structure on SO2, industrial smoke and dust emissions. The results showed that: (1) air pollution had a time cumulative effect year by year, the air pollution of the last year could add air pollution in the script year; (2) urban space expansion could effectively curb air pollution; (3) the urban spatial structure with high population compactness made the air pollution change in an inverted "U" shape; (4) in different economic zone levels and different urban scale levels, the direction of influence and intensity of urban spatial structure on air pollution was different. In the eastern region of China, the residential land, public facilities land and traffic land in the urban structure mainly affected the air pollution. In the central region, the residential land, industrial land, traffic land and municipal land in the urban structure had a significant impact on the air pollution, while the urban scale was the main cause of the air pollution in the western region. Based on this, we recommended the reasonable planning of land use structure, establishment of a population density regulation mechanism, and paying attention to regional differences and urban size differences. This study can help managers of different economic zones and cities of different sizes to improve urban spatial structure and control air pollution in the process of urban development. [ABSTRACT FROM AUTHOR]

Coordinated control of fine particulate matter (PM 2.5) and ozone (O 3) has become a new and urgent issue for China's air pollution control. Biogenic volatile organic compounds (BVOCs) are important precursors of O 3 and secondary organic aerosol (SOA) formation. China experienced a rapid increase in BVOC emissions as a result of increased vegetation biomass. We applied WRF-Chem3.8 coupling with MEGAN2.1 to conduct long-term simulations for impacts of BVOC emissions on O 3 and SOA during 1981–2018, using the emission factors extrapolated by localized emission rates and annual vegetation biomass. In summer 2018, BVOC emissions were 9.91 Tg (in June), which led to an average increase of 8.6 ppb (16.75 % of the total) in daily maximum 8 h (MDA8) O 3 concentration and 0.84 µgm -3 (73.15 % of the total) in SOA over China. The highest contribution to O 3 is concentrated in the Great Khingan Mountains, Qinling Mountains, and most southern regions while in southern areas for SOA. Isoprene has the greatest contribution to O 3 , while monoterpene has the largest SOA production. BVOC emissions have distinguished impacts in different regions. The Chengdu–Chongqing (CC) region has the highest O 3 and SOA generated by BVOCs, while the Beijing–Tianjin–Hebei (BTH) region has the lowest. From 1981 to 2018, the interannual variation of BVOC emissions caused by increasing leaf biomass resulted in O 3 concentration increasing by 7.38 % at an average rate of 0.11 ppb yr -1 and SOA increasing by 39.30 % at an average rate of 0.008 µgm -3 yr -1. Due to the different changing trends of leaf biomass by region and vegetation type, O 3 and SOA show different interannual variations. The Fenwei Plain (FWP), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions have the most rapid O 3 increment, while the increasing rate of SOA in CC is the highest. BTH has the smallest enhancement in O 3 and SOA concentration. This study will help to recognize the impact of historical BVOC emissions on O 3 and SOA and further provide a reliable scientific basis for the precise prevention and control of air pollution in China. [ABSTRACT FROM AUTHOR]

Air pollution in China, caused by the country's extensive economic growth model, threatens the health of residents, especially of low-income groups. The impact and influence mechanism of this pollution on physical health has not been investigated adequately at different income levels. We examine the impact of fine particulate matter on health using panel data for the period 2010–2016 from approximately 100,000 respondents surveyed by China Family Panel Studies. In analysis, we use the hierarchical regression model according to household income per capita. We also examine the effect of residents' human and physical capital on the relationship between air pollution and health. Our research shows that air pollution has an adverse effect on physical health. However, the significance of this effect is income-based: the effect on low-income groups is significant, while that on high-income groups is not. We also find that air pollution causes both direct and indirect impacts on residents' health. Indirect impacts entail reductions in human and physical capital; however, this impact is less than the direct one. Therefore, the Chinese government should implement high environmental standards and strict regulations to control air pollution. It should also invest more in low-income areas to improve accessibility of healthcare services. [ABSTRACT FROM AUTHOR]

Clean air policies in China have substantially reduced particulate matter (PM2.5) air pollution in recent years, primarily by curbing end-of-pipe emissions. However, reaching the level of the World Health Organization (WHO) guidelines may instead depend upon the air quality co-benefits of ambitious climate action. Here, we assess pathways of Chinese PM2.5 air quality from 2015 to 2060 under a combination of scenarios that link global and Chinese climate mitigation pathways (i.e. global 2°C- and 1.5°C-pathways, National Determined Contributions (NDC) pledges and carbon neutrality goals) to local clean air policies. We find that China can achieve both its near-term climate goals (peak emissions) and PM2.5 air quality annual standard (35 μg/m3) by 2030 by fulfilling its NDC pledges and continuing air pollution control policies. However, the benefits of end-of-pipe control reductions are mostly exhausted by 2030, and reducing PM2.5 exposure of the majority of the Chinese population to below 10 μg/m3 by 2060 will likely require more ambitious climate mitigation efforts such as China's carbon neutrality goals and global 1.5°C-pathways. Our results thus highlight that China's carbon neutrality goals will play a critical role in reducing air pollution exposure to the level of the WHO guidelines and protecting public health. [ABSTRACT FROM AUTHOR]

The air pollution index in northern hina rises sharply every autumn and winter. However, few relevant studies have focused on what causes this situation. In this paper, we used the daily meteorological and major air pollutants data of 21 cities in North China plain to study whether heating will aggravate air pollution. The results show that more than half of the major air pollutants in northern China come from coal-fired heating in autumn and winter. Heating will cause AQI, PM2.5, PM10 and SO 2 to increase 1.4 times, 1.9 times, 1.5 times and 0.9 times respectively compared to the seasonal average. Due to the government's control over heating prices, direct changes in coal prices are not transmitted to consumers, so direct changes in coal prices will not affect the level of air pollution. However, it is very interesting that the change in the price gap between high-quality coal and low-quality coal can effectively affect the concentration of air pollutants. This may be due to changes in the behavior of non-central heating users. During the heating season, when the price gap between high-calorie coal and low-calorie coal becomes larger, the concentration of air pollutants will increase. Therefore, it is necessary to carry out a market-oriented reform of heating prices while improving energy efficiency in the future. [ABSTRACT FROM AUTHOR]

The role of precursors' concentrations and meteorological conditions on the emerging ozone pollution problem in China has received wide attention, especially after the releasing of the Air Pollution Prevention Control and Action Plan (APPC) since 2013. With the decreasing trend of PM 2.5 nationwide, the effect of the strict control measures on increasing ozone variation has less been studied due to the challenge of complexity of nonlinear relationship among a number of factors on ozone formation. This paper evaluated the influence of both ozone precursors and meteorology on maximum daily average 8 h (MDA8) ozone at two urban sites and one rural site in Hebei province, China, from 2013 to 2017, by using a combined application of Kolmogorov-Zurbenko (KZ) filter and artificial neural network (ANN) model. Results showed that R2 was 0.80 between the measured and the simulated MDA8 ozone concentration when using meteorological factors and precursors' concentrations as input variables for ANN model. However, ANN model has limitation in estimating O 3 concentration peaks. The values of threat score (TS), probability of detection (POD) and false alarm rate (FAR) for MDA8 ozone concentration were 39%, 44% and 21%, respectively, throughout three studied sites in Hebei province. The annual average percentage change of precursor-related ozone was 0.67% from 2014 to 2017. Temperature, atmospheric pressure and boundary layer height were shown to account for 64% of the variability in long-term ozone levels. Ozone variation in Hebei province was reproduced mainly by meteorological parameters, and the contribution from precursors' concentration was smaller during the years when the APPC was implemented. [Display omitted] • Ozone level was estimated based on precursors' level and meteorological factors. • The ambient ozone concentration estimated by ANN model was acceptable. • Meteorology dominates the ozone variation in 2013–2017 in Hebei province. [ABSTRACT FROM AUTHOR]