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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]

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]

China's cross-border pollution problem has attracted a growing level of attention from the domestic and international community. The elimination of environmental pollution greatly depends on professional environmental protection companies. China's environmental protection industry has sustained a rapid growth with 26.9% annual growing rate of output value since 2011. To effectively discover the potential investment fields and regions, this study examines the spatial distribution of 53 A-Share Listed Environmental Companies (ASLEC) in China and their 927 subsidiaries. Methods of hot spot analysis, Pearson's correlation analysis and coarsened exact matching were employed in our paper to reveal the spatial distribution characteristics of environmental protection industry and their main influencing indicators. Results show that ASLEC invested over US$ 13 billion distributed in 210 cities in China in 2017. Treatment of wastewater and municipal solid waste related to traditional water supply, drainage and sanitation are the main businesses of the environmental protection industry in China. This is because these businesses belong to conventional urban municipal works with low technological requirement and high economic return. Therefore, the government should support those environmental protection businesses with fine technology, such as air pollution prevention and industrial waste control. Our study also reveals that there is a strong and positive correlation between municipal indicators and environmental protection investment. This indicates that the municipal works attract much more investment of environmental protection companies than heavy industries. The eastern region of China remains a hot spot for investment whereas the investment in the western region increased significantly in 2017. The potential of future development will be located in the central and western regions. For serious air pollution and large-scale industrial transfer from eastern regions to the central and western regions in China, there is lack of industrialization environmental protection capacity to fulfill the ambitious national pollution reduction target. This opportunity implies to attract more investments from international environmental protection companies. [ABSTRACT FROM AUTHOR]

The human movement and economic activities have been drastically reduced due to the Coronavirus Disease 2019 (COVID‐19) outbreak, leading to the sharp decreases of pollutant emissions and remarkable air quality improvement. Nevertheless, however, the changes of gaseous pollutant concentrations and health effects across China during the COVID‐19 lockdown period remained poorly understood. Here, a random forest model was applied to assess the impact of COVID‐19 lockdown on pollutant concentrations and potential health effects. The results suggested that estimated NO2, SO2, and CO concentrations in China during January 23–March 31, 2020 decreased by 13.68%, 25.71%, and 7.42%, respectively compared with the same periods in 2018–2019. Nonetheless, the predicted 8‐h O3 concentrations across China suffered from 1.29% increases during this period. The avoided premature all‐cause, cardiovascular disease (CVD), respiratory disease (RD), and chronic obstructive pulmonary disease (COPD) mortalities induced by NO2 decrease during COVID‐19 lockdown period reached 3,954 (3,076–4,832), 635 (468–801), 612 (459–765), and 920 (653–1,186) cases. However, the increases of all‐cause, CVD, RD, and COPD mortalities due to O3 increase during COVID‐19 lockdown period achieved 462 (250–674), 79 (29–129), 40 (−25–105), and 52 (−34–138) cases. The natural experiment demonstrated the drastic emission reduction measures could significantly decrease the NO2, SO2, and CO concentrations, while they significantly elevated the O3 concentration. It is highly imperative to propose more coordinated air pollution control strategies to control O3 pollution. Plain Language Summary: The human movement and economic activities have been drastically reduced due to the outbreak of COVID‐19, and thus the air pollutant concentrations might suffer corresponding variation. Although some recent studies have assessed the effects of COVID‐19 lockdown on air quality, most of these studies only used the observed data at many monitoring sites, which generally show low spatial resolution. Moreover, these sites mainly focus on the urban areas, which cannot reflect the real air quality change status. To date, the changes of air pollutant concentrations and associated health effects at a high spatial resolution in China still remained unknown. The natural experiment provided an unprecedented chances to assess the response of air quality and health benefits (costs) to emission reduction, which provide scientific basis for air pollution prevention. This paper will appeal to a wide general readership and be of exceptional interest to the environmental health specialist. Key Points: The impacts of Coronavirus Disease 2019 lockdown on gaseous pollutants across China were investigatedThe 8‐h O3 level displayed slight increase, while other pollutants showed dramatic decreasesCOVID‐19 saved 3,954 lives due to NO2 decrease, but it claimed 462 lives linked with O3 increase [ABSTRACT FROM AUTHOR]

PM2.5 is the key reason for the frequent occurrence of smog; therefore, identifying its key driving factors has far-reaching significance for the prevention and control of air pollution. Based on long-term remote sensing inversion of PM2.5 data, 21 driving factors in the fields of nature and humanities were selected, and the random forest model was applied to study the influencing factors of PM2.5 concentration in the Beijing–Tianjin–Hebei urban agglomeration (BTH) from 2000 to 2016. The results indicate: (1) The main factors affecting PM2.5 concentration not only include natural factors such as sunshine hours (SSH), relative humidity (RHU), elevation (ELE), normalized difference vegetation index (NDVI), wind speed (WIN), average temperature (TEM), daily temperature range (TEMR), and precipitation (PRE), but also human factors such as urbanization rate (URB), total investment in fixed assets (INV), and the number of employees in the secondary industry (INDU); (2) The concentration of PM2.5 changed into an inverted S-shape with the increase in SSH and WIN, and into an S-shape with the increase in RHU, NDVI, TEM, PRS, URB and INV. As for ELE and TEMR, it fluctuated and decreased with the increase in ELE, while it increased and then decreased with the increase in TEMR. However, its change was less pronounced with the increase in PRE and INDU; (3) The influence of natural factors is higher than that of human factors, but the role of human factors has been continuously strengthened in recent years. The adjustment and control of PM2.5 pollution sources from the perspective of human factors will become an effective way to reduce PM2.5 concentrations in the BTH. [ABSTRACT FROM AUTHOR]

A surge in the size of the automobile population has caused vehicular emissions to become a major source of urban atmospheric pollution. Elevating standards is an effective method of controlling vehicular emissions and improving air quality. Light-duty vehicles are the major contributors to HC and CO emissions as they constitute a large proportion of all vehicles. Consequently, controlling light-duty vehicular emissions has been the primary means of air pollution prevention in China. This paper first reviews the progress of emission control standards in mainland China. Second, it analyzes features of the China 6 emissions standards, namely the continuation of European standards, the harmony of global technology regulations, and fusion with the standards of the USA. This is followed by a description and discussion of the status of research on mainstream after-treatment technologies such as the gasoline particulate filter, lean-NOx trap, and selective catalytic reduction. Finally, this study argues that the technical routes for implementing three-way catalysts, gasoline particulate filters, and onboard refueling vapor recovery in gasoline vehicles and diesel oxidation catalysts, diesel particulate filters, and selective catalyst reduction in diesel vehicles meet China 6 standards. Moreover, onboard diagnostics-based control of light vehicle emissions is introduced, and the development directions of vehicle gasoline (the reduction in sulfur, olefin, and aromatic content and vapor pressure control in summer) and vehicle diesel (an increase in the Cetane number and reduction in the forecasted polycyclic aromatic content) are discussed. State-of-the-art outlook for light-duty vehicle emission control standards in China [ABSTRACT FROM AUTHOR]

Accurate prediction of the Particulate Matter 2.5 (PM 2.5) plays a crucial role in the accurate management of air pollution and prevention of respiratory diseases. However, PM 2.5 as a time series is extremely difficult to accurately predict. In this paper, a Hybrid Integration (HIG) algorithm that combines data pre-processing, time-series decomposition, signal decomposition, a prediction module, a matching strategy, and a hybrid integrated optimization algorithm is proposed. First, the optimal parameters for the four individual models were selected by integrating multiple evaluation perspectives. Additivity was then determined by Seasonal and Trend decomposition using LOWESS (STL), followed by refinement decomposition using signal decomposition. The four new sequences were reconstructed using Range Entropy (RangeEn) and mapped to the models. Additionally, Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) methods were optimized using the HIG algorithm. The results show that the HIG-RNN and HIG-LSTM are more advantageous than the ordinary method in terms of reasonable weight assignment. Finally, an innovative confusion test method was developed to test the stability of the prediction direction. To ensure generalizability, validation was performed using PM 2.5 data from two regions of China. The results show that the method significantly improves the prediction performance and provides a powerful tool for policy formulation and management. [Display omitted] • A hybrid integration (HIG) algorithm is proposed. • Prediction results were evaluated using the original COI and improved ICOI. • Creative time-frequency analysis bypasses traditional time series constraints. • RangeEn can assess entropy series for regularity to avoid excessive decomposition. • A pioneer confusion test for model direction consistency check was developed. [ABSTRACT FROM AUTHOR]

In China, hazy weather is most serious in the Beijing-Tianjin-Hebei region. Therefore, how to prevent the hazy weather in this region has become an important task of China's current environmental management. However, in order to prevent the hazy weather in the Beijing-Tianjin-Hebei region, the priority is to analyze the causes of its hazy weather. The paper comprehensively analyzes the causes of the hazy weather in the Beijing-Tianjin-Hebei region with literature analysis, field research and other methods and gives the main causes. These include: i) there is a large number of civilian vehicles as well as large emissions of automobile exhaust, ii) economic development mode is simple and extensive, iii) highly-polluted secondary industry accounts for a large proportion, iv) industrial distribution and regional self-purification capacity do not match, v) regional industrial planning is unreasonable, etc. It is hoped that it can be helpful for China's prevention and control of regional hazy weather. [ABSTRACT FROM AUTHOR]

Background With the rapid development of the global economy and the acceleration of urbanization, air pollution has become a major environmental problem threatening human health. There is limited evidence on the acute effects of air pollution on chronic obstructive pulmonary disease (COPD). Methods From 2014 to 2019, we collected data on daily admissions for COPD patients from a city in China. We used the generalized additive model together with distributed lag models to fit the associations of air pollutants with hospital admissions. Results We observed significant increments in the number of daily admissions (0.086–0.109%) for COPD for a unit range increase in air quality index, PM 2.5 and PM 10 over four lag days. The impact of air pollution on the number of daily admissions was mainly reflected in the COPD patients who were hospitalized through outpatient departments and tertiary hospitals. Discussion Short-term exposure to outdoor air pollution may induce the occurrence or exacerbation of COPD patients; therefore, government departments should strengthen the management of air pollution, improve supervision and control mechanisms, pay attention to the quality of medical services, and reduce the adverse effects of air pollution on patients' health. [ABSTRACT FROM AUTHOR]

Beijing, the capital of China, has experienced rapid industrialization, urbanization and motorization in recent decades. Consequently, air pollution in Beijing, especially fine particulate matter (PM 2.5 ) pollution, has gradually become a severe environmental issue, due to the continuing growth in energy consumption and the resulting multiple pollutant emissions. In response to the increasingly serious PM 2.5 pollution, Beijing's government implemented a series of policies, measures and regulations on air pollution prevention and control and took some concrete actions to improve air quality. In this paper, firstly, we summarize China's ambient air quality standards, China's policies and regulations on air pollution prevention and control. Secondly, we illustrate historical evolution and current status of air pollution in Beijing. Finally, we introduce control measures and actions in Beijing and its surrounding areas. The paper aims to help environmental scientists and policy makers around the world understand the past and current air pollution in Beijing and control strategies and actions taken by Beijing's government. [ABSTRACT FROM AUTHOR]

Efficient filtration provides a healthy and comfortable residential environment. Based on the performance testing for filter materials commonly used in China, the mass balance equation of controlling the indoor PM2.5 concentration was set up, and the filter selection criterion was discussed. An optimal section was suggested by taking into account the economic cost, filter price, and indoor air quality. [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]

The Bohai Sea (BS) region, an area of China that is severely polluted with atmospheric polycyclic aromatic hydrocarbons (PAHs), has received wide attention in recent decades. To characterize the variations of the concentrations and sources of PAHs from June 2014 to May 2019, 15 PAH congeners (Σ15PAHs) were measured in atmospheric samples (N = 228) collected at 12 sites around the BS, and the health risk and direct medical costs associated with lung cancer caused by exposure to PAHs were also estimated. The annual daily average concentration of Σ15PAHs was 56.78 ± 4.75 ngm-3 , which was dominated by low molecular weight PAHs (LMW-PAHs) containing three rings (58.7 ± 7.8 %). During the 5-year sampling period, the atmospheric Σ15PAHs concentration reduced by 17.5 % for the whole BS region, with an especially large drop of 51.7 % observed in the tightly controlled area of Tianjin (TJ), which was mainly due to a decrease in the concentration of high molecular weight PAHs (HMW-PAHs) containing five or six rings. Generally, the concentration of Σ15PAHs was highest in winter and lowest in summer, which can mainly be attributed to the change in LMW-PAH concentration. Based on the positive matrix factorization (PMF) model, PAHs in the BS region were mainly ascribed to coal combustion and biomass burning. The PAH contributions of coal combustion and motor vehicles showed different trends for the BS region (PAHs from coal combustion rose by 7.2 % and PAHs from motor vehicles fell by 22.4 %) and for TJ (PAHs from coal combustion fell by 12.6 % and PAHs from motor vehicles rose by 6.9 %). The incidence of lung cancer (ILCR) caused by exposure to atmospheric PAHs decreased by 74.1 % and 91.6 % from 2014 to 2018 in the BS region and in TJ, respectively. This was mainly due to the decrease in the concentration of highly toxic HMW-PAHs and was reflected in USD 10.7 million of savings in direct medical costs of lung cancer caused by exposure to PAHs, which represent a decrease of 46.1 % compared to the corresponding costs before air pollution prevention and control was implemented around the BS. There was an even higher reduction in medical costs of 54.5 % in TJ. Hence, this study proves that implementing pollution prevention and control not only effectively reduced the concentration of pollutants and the risks caused by them, but it also significantly reduced the medical costs of diseases caused by the corresponding exposure. [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]

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]

A growing literature on the pollution haven hypothesis has surged for decades. In this paper, we employ a city-level data set of 150 Chinese cities in 2014, and take spatial spillovers into account by using spatial econometric models, to investigate whether foreign capital inflows drive environmental degradation in China. The results suggest that foreign direct investment is negatively related to air pollution in China, indicating evidence of pollution halo hypothesis. Moreover, foreign direct investment has significant spatial technological spillovers, improving air quality in China. This study also finds that there is no evidence of an inverted U-shaped curve between income and air pollution. As income levels increase, air quality continues to worsen. The development of the tertiary industry is found to have a positive effect on air pollution. Densely populated cities tend to demand for better environmental quality. From the above analysis, it follows that policies handles are urgently needed to improve air quality in China. [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]

China has been conducting a series of actions on air quality improvement for the past decades, and air pollutant emissions have been changing swiftly across the country. Provinces are an important administrative unit for air quality management in China; thus a reliable provincial-level emission inventory for multiple years is essential for detecting the varying sources of pollution and evaluating the effectiveness of emission controls. In this study, we selected Jiangsu, one of the most developed provinces in China, and developed a high-resolution emission inventory of nine species for 2015–2019, with improved methodologies for different emission sectors, best available facility-level information on individual sources, and real-world emission measurements. Resulting from implementation of strict emission control measures, the anthropogenic emissions were estimated to have declined 53 %, 20 %, 7 %, 2 %, 10 %, 21 %, 16 %, 6 %, and 18 % for sulfur dioxide (SO 2), nitrogen oxides (NO x), carbon monoxide (CO), non-methane volatile organic compounds (NMVOCs), ammonia (NH 3), inhalable particulate matter (PM 10), fine particulate matter (PM 2.5), black carbon (BC), and organic carbon (OC) from 2015 to 2019, respectively. Larger abatement of SO 2 , NO x , and PM 2.5 emissions was detected for the more developed region of southern Jiangsu. During the period from 2016 to 2019, the ratio of biogenic volatile organic compounds (BVOCs) to anthropogenic volatile organic compounds (AVOCs) exceeded 50 % in the month of July, indicating the importance of biogenic sources for summer O 3 formation. Our estimates in annual emissions of NO x , NMVOCs, and NH 3 were generally smaller than the national emission inventory, MEIC (the Multi-resolution Emission Inventory for China), but larger for primary particles. The discrepancies between studies resulted mainly from different methods of emission estimation (e.g., the procedure-based approach for AVOC emissions from key industries used in this work) and inconsistent information of emission source operation (e.g., the penetration and removal efficiencies of air pollution control devices). Regarding the different periods, more reduction of SO 2 emissions was found between 2015 and 2017 and of NO x , AVOCs, and PM 2.5 between 2017 and 2019. Among the selected 13 major measures, the ultra-low-emission retrofit in the power sector was the most important contributor to the reduced SO 2 and NO x emissions (accounting for 38 % and 43 % of the emission abatement, respectively) for 2015–2017, but its effect became very limited afterwards as the retrofit had been commonly completed by 2017. Instead, extensive management of coal-fired boilers and the upgrade and renovation of non-electrical industry were the most important measures for 2017–2019, accounting collectively for 61 %, 49 %, and 57 % reduction of SO 2 , NO x , and PM 2.5 , respectively. Controls on key industrial sectors were the most effective for AVOC reduction in the two periods, while measures relating to other sources (transportation and solvent replacement) have become more important in recent years. Our provincial emission inventory was demonstrated to support high-resolution air quality modeling for multiple years. Through scenario setting and modeling, worsened meteorological conditions were found from 2015 to 2019 for PM 2.5 and O 3 pollution alleviation. However, the efforts on emission controls were identified to largely overcome the negative influence of meteorological variation. The changed anthropogenic emissions were estimated to contribute 4.3 and 5.5 µ g m -3 of PM 2.5 concentration reduction for 2015–2017 and 2017–2019, respectively. While O 3 was elevated by 4.9 µ g m -3 for 2015–2017, the changing emissions led to 3.1 µ g m -3 of reduction for 2017–2019, partly (not fully though) offsetting the meteorology-driven growth. The analysis justified the validity of local emission control efforts on air quality improvement and provided a scientific basis to formulate air pollution prevention and control policies for other developed regions in China and worldwide. [ABSTRACT FROM AUTHOR]

With the rapid development of economy, air pollution occurs frequently, which has a huge negative impact on human health and urban ecosystem. Air quality index (AQI) can directly reflect the degree of air pollution. Accurate AQI trend prediction can provide reliable information for the prevention and control of air pollution, but traditional forecasting methods have limited performance. To this end, a dual-scale ensemble learning framework is proposed for the complex AQI time series prediction. First, complete ensemble empirical mode decomposition adaptive noise (CEEMDAN) and sample entropy (SE) are used to decompose and reconstruct AQI series to reduce the difficulty of direct modeling. Then, according to the characteristics of high and low frequencies, the high-frequency components are predicted by the long short-term memory neural network (LSTM), and the low-frequency items are predicted by the regularized extreme learning machine (RELM). At the same time, the improved whale optimization algorithm (WOA) is used to optimize the hyper-parameters of RELM and LSTM models. Finally, the hybrid prediction model proposed in this paper predicts the AQI of four cities in China. This work effectively improves the prediction accuracy of AQI, which is of great significance to the sustainable development of the cities. • A dual-scale ensemble framework is proposed for air quality index prediction. • CEEMDAN technology is adopted to obtain multiple intrinsic mode functions. • An improved WOA algorithm based on dimension learning-based hunting is proposed. • Long short-term memory network is used to predict high-frequency components. • Regularized extremum learning machine is used to predict low-frequency components. [ABSTRACT FROM AUTHOR]

China is expected to have a total installed photovoltaic capacity of 1300 GW in 2050, accounting for 39% of the national electricity consumption. However, air pollutants consisting of gases and particulates have attenuation effects on the solar radiation reaching the photovoltaic panels. This work purports to assess the influence of air pollutants on the photovoltaic power potential. We calculated the hourly point-of-array irradiance (POAI) in China for 2010–2020 with a spatial resolution of 0.1° × 0.1° using the PV_LIB model and assessed the effect of air pollutants on POAI. The results indicated that the annual average POAI in China for 2010–2020 ranged from 118 to 286 Wm−2. The Air Pollution Control Action Plan (APPCAP) has played a certain role in photovoltaic power potential, and POAI has increased in areas where surface concentrations of air pollutants have declined. Especially in North China, the surface concentrations of CO, NO2, PM10, PM2.5, and SO2 decreased throughout the APPCAP period with −0.446, −4.985, −35.610, −30.700, and −26.251 μgm−3, respectively, corresponding to an increase in POAI of up to 4.917 Wm−2. The surface concentrations of CO, NO2, PM10, PM2.5, and SO2 were negatively correlated with POAI, with correlation coefficients of −0.764, −0.854, −0.204, −0.110, and −0.664, respectively. Surface concentrations of air pollutants (CO, NO2, PM10, PM2.5, and SO2) and clear-sky POAI in 2018 showed a High-Low clustering in Northeast China and North China. This study demonstrates the role of China's air pollution control policy in enhancing photovoltaic power potential. [ABSTRACT FROM AUTHOR]

Along with China's modern industrialization, challenges on smog crisis are raising dramatically in the past decade. The sources of municipal smog are multiple and complex, one of which is construction dust emission due to the rapid urbanization. In literature, there are studies focusing on the end-pipe treatment of construction dust; however, very little research has been conducted from the perspective of dust mitigation in developing countries. To fill in this research gap, this paper investigates the current situation of construction dust prevention and control in China, with the aim of providing insights for mitigating dust pollution caused by the construction industry. Through a combination of the content analysis, on-site observation, questionnaire survey and interviews with experienced professionals, a total of 11 related regulations are thoroughly reviewed, and the main sources of construction dust production are identified. A case study is further presented to demonstrate the prevailing dust control measures on site. Recommendations are proposed in order to increase the awareness of related stakeholders, including formulation of targeted regulations, establishment of an appropriate charging scheme, development of a feasible monitoring system, and enhancement of training and dissemination. [ABSTRACT FROM AUTHOR]

The benefit allocation of fair and justice is an inevitable guarantee for the long-term operation of the joint prevention and control of air pollution (JPCAP). The ignorance of interest demands of various governance subjects in the existing benefit allocation mechanism results in the widespread "free rider" behavior in the joint control and unsatisfactory effects of JPCAP. Given this, it is imperative to build a reasonable benefit allocation model. The innovation of this paper is proposing a benefit allocation model of JPCAP to achieve the symmetry between control costs and benefits based on environmental justice. The control objectives and total benefits of JPCAP are calculated through the adjustment of optimal removal rates. The interest demands of various control subjects and benefit compensation scheme are clarified by adopting an improved Shapley method, which comprehensively considers factors affecting environmental justice. An empirical analysis is conducted on SO 2 governance in Beijing-Tianjin-Hebei (BTH) and its surrounding areas. The results show that the benefit allocation model based on environmental justice can not only accurately evaluate the benefits of joint control, but also effectively achieve the symmetry between control costs and benefits. This study provides a scientific and reasonable theoretical basis for the benefit allocation of SO 2 control and can be extended to the researches and practices of other air pollutants control. • An optimization model is developed by considering removal costs and health benefits. • A benefit allocation model is established based on environmental justice. • The superiority of the benefit allocation model is demonstrated by sensitivity analysis. [ABSTRACT FROM AUTHOR]

Aerosol acidity plays a key role in regulating the chemistry and toxicity of atmospheric aerosol particles. The trend of aerosol pH and its drivers is crucial in understanding the multiphase formation pathways of aerosols. Here, we reported the first trend analysis of aerosol pH from 2011 to 2019 in eastern China, calculated with the ISORROPIA model based on observed gas and aerosol compositions. The implementation of the Air Pollution Prevention and Control Action Plan led to -35.8 %, -37.6 %, -9.6 %, -81.0 % and 1.2 % changes of PM 2.5 , SO42- , NHx , non-volatile cations (NVCs) and NO3- in the Yangtze River Delta (YRD) region during this period. Different from the drastic changes of aerosol compositions due to the implementation of the Air Pollution Prevention and Control Action Plan, aerosol pH showed a minor change of -0.24 over the 9 years. Besides the multiphase buffer effect, the opposite effects from the changes of SO42- and non-volatile cations played key roles in determining this minor pH trend, contributing to a change of +0.3 8 and -0.35 , respectively. Seasonal variations in aerosol pH were mainly driven by the temperature, while the diurnal variations were driven by both temperature and relative humidity. In the future, SO2 , NOx and NH3 emissions are expected to be further reduced by 86.9 %, 74.9 % and 41.7 % in 2050 according to the best health effect pollution control scenario (SSP1-26-BHE). The corresponding aerosol pH in eastern China is estimated to increase by ∼0.19 , resulting in 0.04 less NO3- and 0.12 less NH4+ partitioning ratios, which suggests that NH3 and NOx emission controls are effective in mitigating haze pollution in eastern China. [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]

In order to analyze the primary sources of air pollutants in Chang-Zhu-Tan region, this article selected the environmental monitoring data and meteorological data in the winter of 2019 to calculate the backward airflow trajectories with the Chang-Zhu-Tan region as the starting point by using the backward trajectory model. Combined with the ground concentration monitoring data, cluster analysis, potential source contribution factor (PSCF) analysis, and concentration weighted trajectory (CWT) analysis were carried out to determine the pollutant transportation paths and sources of the potential source area. The results show that air mass transportation mainly comes from three directions: northwest, northeast, and southwest China. The airflow in northwest China moves faster and cleaner, while the airflow from the northeast and southwest moves slowly and carries a high concentration of pollutants. PSCF and CWT analyses show that the critical potential sources are mainly located in this area and some cities next to the study area. This study has important practical significance for the environmental research of Chang-Zhu-Tan region and can provide theoretical reference for regional joint prevention and control of air pollution. [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]

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]

Collaborative governance plays an important role in air pollution prevention (APP). This paper aims to evaluate the policy effects of collaborative governance for APP in the Yangtze River Delta (YRD) region, analyze the collaborative mechanism from the perspective of institutional collective action (ICA) theory, and discuss its implications for improving the policy effects and regional collaboration. First, the causal relationship between collaborative environmental governance and air pollutant reduction is confirmed using the regression discontinuity design (RDD). However, it is also established that regional APP policies initiated by the Regional Cooperation Office of Yangtze River Delta (RCOYRD) did not have a long-term effect on reducing air pollutants. Second, initiative heterogeneity and administrative hierarchy heterogeneity of policy effects between cities are analyzed. It demonstrates that the mechanism formulated by RCOYRD has very limited impact on the reduction of transaction costs and collaborative risks of collaborative environmental governance. Third, clear division of responsibilities, balanced cost-benefit sharing, and coordinated enforcement between local governments are needed to improve the policy effects of collaborative governance for APP. • Institutional collective action (ICA) framework was adopted to analyze cross-regional issues. • The causal relationship between collaborative governance and air pollutant reduction was confirmed with RDD method. • The collaborative governance for air pollution prevention did not have long-term policy effect. • Collaboration risk and transaction cost are key factors affecting regional coordination. [ABSTRACT FROM AUTHOR]

Background: Rapid economic growth in China has resulted in a commensurate increase in energy consumption, which in turn has seen an increase in environmental pollution problems. Past research has tended to focus on energy and environmental efficiency analyses and has rarely examined the media influence on environmental protection efforts. Further, most studies have used static models and ignored the dynamic changes over time. Methods: To go some way to filling this research gap, this study developed a modified undesirable Dynamic DEA model that included air quality index (AQI) and CO2 indicators to explore the relationships between energy, the environment, and media report efficiencies in 31 Chinese cities from 2013 to 2016. Results: It was found that: (1) Chongqing, Guangzhou, Nanjing and Shanghai had efficiencies of 1, but Lanzhou, Shijiazhuang, Taiyuan, Xining and Yinchuan needed significant improvements; (2) Chongqing, Guangzhou, Kunming, Nanning and Shanghai had relatively high media efficiencies, but the other cities had low efficiencies and required improvements; (3) the CO2 emissions efficiencies in most cities were better than the air quality index efficiencies; and 4. the media reports in most cities were found to have a more positive impact on the CO2 emissions efficiency than on the AQI efficiency. Conclusions: Environmental awareness enhances civilian health and promotes economic growth. Therefore, as the news media should be responsible for promoting environmental protection, they need to increase their environmental pollution coverage. It was found that the environmental pollution media report quality and especially air pollution reports needed improvements, and greater media coverage on environmental pollution and awareness was needed. [ABSTRACT FROM AUTHOR]

Most developing countries in the world face the common challenges of reducing air pollution and advancing the process of sustainable development, especially in China. Air pollution research is a complex system and one of the main methods is through numerical simulation. The air quality model is an important technical method, it allows researchers to better analyze air pollutants in different regions. In addition, the SCB is a high-humidity and foggy area, and the concentration of atmospheric pollutants is always high. However, research on this region, one of the four most polluted regions in China, is still lacking. Reviewing the application of air quality models in the SCB air pollution has not been reported thoroughly. To fill these gaps, this review provides a comprehensive narration about i) The status of air pollution in SCB; ii) The application of air quality models in SCB; iii) The problems and application prospects of air quality models in the research of air pollution. This paper may provide a theoretical reference for the prevention and control of air pollution in the SCB and other heavily polluted areas in China and give some1inspirations for air pollution forecast in other countries with complex terrain. [Display omitted] • Current situation of air pollution in the Sichuan Basin of China is reviewed. • The development and classification of air quality models are summarized. • Application of air quality models in the study of Sichuan Basin air pollution are discussed. • Problems in the application and future research directions of air quality models are provided. [ABSTRACT FROM AUTHOR]

Background: Air pollution has been associated with an increase in cardiovascular diseases incidence. To evaluate whether air pollution can accelerate atherogenic processes, we assessed the effects of air pollution on important surrogate markers of atherosclerosis [brachial flow-mediated dilation (FMD) and carotid intima-media thickness (IMT)].Methods: A total of 1656 Han Chinese (mean age 46.0 + 11.2 years; male 47%) in Hong Kong, Macau, Pun Yu, Yu County and the 3-Gorges Territories (Yangtze River) were studied between 1996 and 2007 [Chinese Atherosclerosis in the Aged and Young Project (the CATHAY Study)]. Cardiovascular risk profiles were evaluated. Particulate matter with an aerodynamic diameter <2.5 µm (PM2.5) parameters were computed from satellite sensors. Brachial FMD and carotid IMT were measured by ultrasound.Results: Health parameters [age, gender, body mass index, waist : hip ratio (WHR) and glucose)] were similar in lowest and highest PM2.5 exposure tertiles, systolic and diastolic blood pressures and triglycerides were higher (P < 0.001) and low-density cholesterol (LDL-C) was lower in the top PM2.5 tertile (P < 0.001). Brachial FMD [7.84 ± 1.77, 95% confidence interval (CI) 7.59-8.10%, vs 8.50 ± 2.52, 95% CI 8.23-8.77%, P < 0.0001) was significantly lower and carotid IMT (0.68 ± 0.13 mm, 95% CI 0.67-0.69 mm vs 0.63 mm ± 0.15 mm 95% CI 0.62-0.64 mm; P < 0.0001) was significantly thicker in the top PM2.5 tertile compared with the lowest tertile. On multiple regression, FMD was inversely related to PM2.5 (beta = 0.134, P = 0.015) independent of gender, age and blood pressure (model R2 = 0.156, F-value = 7.6, P < 0.0001). Carotid IMT was significantly correlated with PM2.5 exposure (beta = 0.381, P < 0.0001) independent of age, location, gender, WHR, blood pressure and LDL-C (model R2 = 0.408, F-value = 51.4, P-value <0.0001).Conclusions: Air pollution is strongly associated with markers of early atherosclerosis, suggesting a potential target for preventive intervention. [ABSTRACT FROM AUTHOR]

Long-term exposure to fine particulate matter (PM 2.5) poses a great threat to public health in China. To this end, the Chinese government promulgated the Air Pollution Prevention and Control Action Plan (the Action Plan) in 2013. However, the health benefits of the Action Plan have not been well explained. In this paper, the underlying causes of changes in premature mortality attributable to PM 2.5 pollution and the response of this mitigation policy in China were explored using sensitivity analysis. The simulated annual average PM 2.5 concentration reduced by 24.9% over mainland China from 2008 to 2016. Subsequently, national premature mortality would decrease by 14.4% from 1.14 million (95% CI: 0.54, 1.55) in 2008 to 0.98 million (95% CI: 0.44, 1.38) in 2016. Specifically, premature mortality reduced by 209,600 cases (−18.3%) owing to PM 2.5 reduction during 2008–2016, of which 188,500 cases were from 2014 to 2016 due to the Action Plan in 2013. Note that the health benefits were limited when compared with air quality improvements, mainly due to that the IER functions have a stable curve at higher concentration intervals. Meanwhile, premature mortality would have increased by 14.2% from 2008 to 2016 owing to demographic changes, substantially weakening the impact of the decrease in PM 2.5 and baseline mortality. The effectiveness of China's new air pollution mitigation policy was proved through the research. However, considering the non-linear response of mortality to PM 2.5 changes and the aggravation of demography trends, stronger emission control steps should be further taken to protect public health in China. Image 1 • Trends of PM 2.5 and attributable mortality before and after control policies were contrasted. • Underlying causes of changes in PM 2.5 -related deaths were analyzed comprehensively. • The influence of different factors on PM 2.5 -related deaths were analyzed in detail. • The implementation of the Action Plan has brought substantial health benefits. • Demographic and baseline mortality also play a part in changes in PM 2.5 -related deaths. [ABSTRACT FROM AUTHOR]

Air pollution are known to have negative impacts on human health and the ecosystem, and it also contributes to climate change. Hence, prevention and control of air pollution is an urgent need in China, and air pollution prediction can provide reliable information for this process. Therefore, it is essential to establish effective air pollution prediction with an early warning model. Currently, one widely used air pollution prediction technology is the error correction model. However, this traditional method does not use data preprocessing technology. Therefoere, this paper presents an improved hybrid model named CEEMD-SLM-ECM (Complementary Set Empirical Mode Decomposition-Statistical Learning Model-Error Correction Model), which used the CEEMD data preprocessing technology together with statistical learning models. Furthermore, selected AQI (air quality index) data of 17 port cities in the 21st Century Maritime Silk Road Economic Belt were selected to test the forecasting ability of the proposed model. Data analysis shows that the CEEMD-SLM-ECM model has much higher accuracy compared with the traditional error correction model. So, the CEEMD-SLM-ECM is a very effective predictive model that can provide accurate prediction for air quality early warning. • A new improved error correction model CEEMD-SLM-ECM is established. • Data preprocessing is helpful for improving the prediction accuracy. • CEEMD-SLM-ECM is effective for AQI forecasting. [ABSTRACT FROM AUTHOR]

Most of the previous researches estimate influencing factors impact on air quality average without considering the heterogeneity of influential factors on different levels of air quality. In order to detect the different effects of influencing factors on air quality index (AQI) between lower-AQI and higher-AQI cities, this study applies a spatial quantile regression model (SQRM) to investigate heterogeneity of influential factors on AQI, while accounting for spatial autocorrelation of AQI. The results show that heterogeneity effects of windspeed, terrain slope, urbanization sprawl and spatial autocorrelation on AQI are large across the entire AQI spectrum, while heterogeneity effects of precipitation, temperature, relative humidity, terrain fluctuation and urbanization intensity on AQI are not obvious. The spatial positive autocorrelation of AQI in higher-AQI cities is greater than that in lower-AQI cities. Compared with higher-AQI cities, the negative impact of terrain slope on AQI is lager in lower-AQI cities. One unit increase in wind speed contributes AQI to decrease 9.31 to 5.64 then to 5.39 for lower, medium and higher-AQI cities. One unit increase in urbanization sprawl would lead AQI increase 25.6 to 15.6 then to 10.5 for lower, medium and higher-AQI cities. The heterogeneity analysis of meteorological, topographic and socioeconomic factors effects on air quality are of guiding significance for realizing the differentiation of policy measures for air pollution prevention and control. Image 1 • Nighttime light data is used to construct urbanization indicators. • SQRM detects heterogeneity of influential factors on lower and higher AQI cities. • Spatial positive autocorrelation of AQI is not balanced across entire AQI spectrum. • Wind speed contributes to air quality to different extent in cities of China. • Effects of urbanization breadth and intensity on AQI are positive and negative. This paper detects the heterogeneity of influencing factors on AQI between lower-AQI and higher-AQI cities in China. [ABSTRACT FROM AUTHOR]

Theoretical predictions on the impact of environmental regulations on firm value in stock market are inconclusive. This paper examines whether and how stock market reacts to environmental regulations in China. We find that overall market-wide reactions are inconclusive while the cross-sectional tests show that stocks in polluting industries significantly and robustly underperform other stocks. Moreover, the worsening effect of environmental regulations on firm value is more pronounced among firms without political connections and firms located in rons with more effective judicial enforcement as the investors expect that these regulations will be effectively enforced. Our results show that China's green campaign does have value implications for stock markets. • China's Air Pollution Prevention and Control Action Plan affects shareholder value. • High-polluting stocks significantly underperform low-polluting stocks. • Stocks without political connections in high-polluting industries show lower returns. • Better judicial enforcement makes the differences in shareholder value stronger. [ABSTRACT FROM AUTHOR]

Air quality in China is characterized by significant spatial and temporal differences, which are directly related to local meteorological conditions. This study used air quality monitoring data, namely, the air pollution index (API) and air quality index (AQI) between 2005 and 2018, together with meteorological data and identified key meteorological factors that affected the spatial and temporal variation of air quality using a random forest algorithm. The spatial and temporal differences in the threshold values of different meteorological factors affecting the concentrations of PM2.5, PM10, SO2, CO, NO2, and O3 were identified. The AQI has the advantages of facilitating higher index values than the API. The air quality showed an improvement from 2005 to 2018. Wind direction and precipitation were the most important meteorological factors affecting the air quality in northern and southern China, respectively, which to some extent reflected the causes and degradation mechanisms of air pollution in the two regions. There were significant spatial and temporal differences in the effects of meteorological factors on the concentrations of different pollutants. The influence of atmospheric pressure on pollutant concentration differed between the east and west. Precipitation and relative humidity in most cities had significant impacts on PM2.5 and PM10. The influence of relative humidity was most significant for SO2 and it also had a great influence on O3, while wind speed had a great influence on NO2. The results of the study confirm the meteorological sensitivity of air quality and provide support for the implementation of regional air pollution prevention and control initiatives. [ABSTRACT FROM AUTHOR]

BACKGROUND: Research on the relationship between long-term exposure to particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5) and poor cognitive function is lacking in developing countries, especially in highly polluted areas. OBJECTIVES: We evaluated associations of long-term exposure to PM2.5 with poor cognitive function in a diverse, national sample of older adults in China. METHODS: This analysis included data on 13,324 older adults (5,879 who were 65–79 years of age, 3,052 who were 80–89 years of age, 2,634 who were 90–99 years of age, and 1,759 who were =100 years of age) with normal cognitive function at baseline from March 2002 to September 2014, with 64,648 person-years of follow-up. We used a geographic information system analysis to estimate the annual average satellite-derived PM2.5 concentration for the geocoded location of the participants’ baseline residences. Poor cognitive function was defined as a score of less than 18 on the Chinese version of the Mini-Mental State Examination (MMSE). Competing risk models were performed to explore the association of PM2.5 with poor cognitive function. RESULTS: Each 10-µg/m³ increase in PM2.5 was associated with a 5.1% increased risk of poor cognitive function [adjusted hazard ratio (HR): 1.051; 95% confidence interval (CI): 1.023, 1.079]. Compared to the lowest quartile of PM2.5 (<41.4µg/m³), adjusted HR values were 1.20 (95% CI: 1.09, 1.33), 1.27 (95% CI: 1.15, 1.41), and 1.21 (95% CI: 1.09, 1.34) for the second (≤41.4-50.3 ug/m³), third (≥50.3-60.7µg/m³), and fourth (≥60.7µg/m³) quartiles of PM2.5, respectively (푝 for trend <0.001). Subgroup analyses suggested stronger associations between PM2.5 and poor cognitive impairment in men than women. The association was positive in the 65- to 79- and ≥100-y age group but not significant and positive in the other two age groups with similar results. CONCLUSION: PM2.5 was identified as a risk factor for poor cognitive function in Chinese older adults. Improving air quality may reduce the future population burden of poor cognitive function, especially in areas with high air pollution. [ABSTRACT FROM AUTHOR]

Given the increase in energy consumption and the advancement of urbanization, the expected level for the prevention and control of air pollution has not been achieved, and urban air quality has deteriorated significantly. Environmental air ecological compensation has become an important method to control air pollution to realize sustainable economic and societal development. The object, method, and standard for compensation were discussed based on the case study of the environmental air ecological compensation mechanism in the Hubei Province of China. Results show that the compensation mechanism solves the negative externality of the environment caused by the fuzzy air property rights to a certain extent. Besides, the mechanism addresses the dilemma caused by the fragmented management of the local government to the collective action and promotes the transformation from the traditional pollution control mode of the regulated enterprises to the governance mode to strengthen government regulation. [ABSTRACT FROM AUTHOR]

Air pollution kills nearly 1 million people per year in China. In response, the Chinese government implemented the Air Pollution Prevention and Control Action Plan (APPCAP) from 2013 to 2017 which had a significant impact on reducing PM2.5 concentration. However, the health benefits of the APPCAP are not well understood. Here we examine the spatiotemporal dynamics of annual deaths attributable to PM2.5 pollution (DAPP) in China and the contribution from the APPCAP using decomposition analysis. Despite a 36.1% increase in DAPP from 2000 to 2017, The APPCAP-induced improvement in air quality achieved substantial health benefits, with the DAPP in 2017 reduced by 64 thousand (6.8%) compared to 2013. However, the policy is unlikely to result in further major reductions in DAPP and more ambitious policies are required to reduce the health impacts of air pollution by 2030 and meet the United Nation's Sustainable Development Goal 3. Chinese government has implemented the air pollution control measure-the Air Pollution Prevention and Control Action Plan in 2013, whose effects have not been fully studied. Here the authors show that from 2013 to 2017, the plan has achieved substantial public health benefits. [ABSTRACT FROM AUTHOR]

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Machine learning and data mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a widely used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, air quality classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a new hybrid classification model based on information theory and support vector machine (SVM) using the air quality data of 4 cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from January 1, 2014 to April 30, 2016. China’s Ministry of Environmental Protection has classified the daily air quality into 6 levels, namely, serious pollution, severe pollution, moderate pollution, light pollution, good and excellent based on their respective air quality index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM machine learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), artificial neural network (ANN) and K-nearest neighbours (KNN) models in terms of accuracy as well as complexity. [ABSTRACT FROM AUTHOR]

BACKGROUND: In 2013, China released the Air Pollution Prevention and Control Action Plan (Action Plan), which set the roadmap for national air pollution control actions for the period of 2013 to 2017. A decrease in the fine particulate matter with aerodynamic diameter ≤2:5 lm (PM2:5) concentration may lead to a substantial benefit for human health. OBJECTIVE: We aimed to quantify the relative contributions four factors: emission reductions, changed meteorology, population growth, and a change in baseline mortality rates to the reduced PM2:5-related mortality (PM2:5-mortality) during the 2013-2017 period and evaluate the importance of emission controls for human health protection in China. METHODS: The integrated exposure-response function was adopted to estimate the chronic health effects of PM2:5. The annual PM2:5 concentrations were estimated from chemical transport model simulations combined with surface observations for 2013 and 2017. Relative contributions to PM2:5-mortality from emission reductions and the three factors were individually quantified through scenario analysis. RESULTS: The estimated total PM2:5-mortality in China was 1.389 million [95% confidence interval (CI): 1.005 million, 1.631 million] in 2013 but was substantially reduced to 1.102 million (95% CI: 0.755 million, 1.337 million) in 2017. Emission controls contributed 88.7% to this reduction in PM2:5-mortality, while changed meteorology, the change in baseline mortality rates, and population growth during 2013-2017 contributed 9.6, 3.8, and -2:2%, respectively. CONCLUSIONS: The implementation of the Action Plan has significantly reduced the PM2:5 concentration in regions of China where population density is high, dominating the decline in PM2:5-mortality during 2013-2017. However, the health burden of PM2:5 pollution in China is still extremely high compared with that in other developed countries. An aggressive air pollution control strategy should be implemented in densely populated areas to further reduce the health burden. [ABSTRACT FROM AUTHOR]

The implementation of the Air Pollution Prevention and Control Action Plan in China since 2013 has profoundly altered the ambient pollutants in the Beijing–Tianjin–Hebei (BTH) region. Here we show observations of substantially increased O3 concentrations (about 30 %) and a remarkable increase in the ratio of organic carbon (OC) to elemental carbon (EC) in BTH during the autumn from 2013 to 2015, revealing an enhancement in atmospheric oxidizing capacity (AOC) and secondary organic aerosol (SOA) formation. To explore the impacts of increasing AOC on the SOA formation, a severe air pollution episode from 3 to 8 October 2015 with high O3 and PM 2.5 concentrations is simulated using the WRF-Chem model. The model performs reasonably well in simulating the spatial distributions of PM 2.5 and O3 concentrations over BTH and the temporal variations in PM 2.5 , O3 , NO2 , OC, and EC concentrations in Beijing compared to measurements. Sensitivity studies show that the change in AOC substantially influences the SOA formation in BTH. A sensitivity case characterized by a 31 % O3 decrease (or 36 % OH decrease) reduces the SOA level by about 30 % and the SOA fraction in total organic aerosol by 17 % (from 0.52 to 0.43, dimensionless). Spatially, the SOA decrease caused by reduced AOC is ubiquitous in BTH, but the spatial relationship between SOA concentrations and the AOC is dependent on the SOA precursor distribution. Studies on SOA formation pathways further show that when the AOC is reduced, the SOA from oxidation and partitioning of semivolatile primary organic aerosol (POA) and co-emitted intermediate volatile organic compounds (IVOCs) decreases remarkably, followed by those from anthropogenic and biogenic volatile organic compounds (VOCs). Meanwhile, the SOA decrease in the irreversible uptake of glyoxal and methylglyoxal on the aerosol surfaces is negligible. [ABSTRACT FROM AUTHOR]

Understanding the effectiveness of air pollution control policies is important for future policy making. China has implemented strict air pollution control policies since the 11th Five-Year Plan (FYP). There is still a lack of overall evaluation of the effects of air pollution control policies on PM2.5 pollution improvement in China since the 11th FYP. In this study, we aimed to assess the effects of air pollution control policies from 2005 to 2017 on PM2.5 using satellite remote sensing. We used the satellite-derived PM2.5 of 2005–2013 from one of our previous studies. For the data of 2014–2017, we developed a two-stage statistical model to retrieve satellite PM2.5 data using the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD), assimilated meteorology, and land use data. The first stage is a day-specific linear mixed effects (LME) model and the second stage is a generalized additive model (GAM). Results show that the Energy Conservation and Emissions Reduction (ECER) policy, implemented in the 11th FYP period and focused on SO2 emissions control, had co-benefits with PM2.5 reductions. The increasing trends of PM2.5 pollution (1.88 and 3.14 µ g m -3 year -1 for all of China and the Jingjinji region in 2004–2007, p<0.005) were suppressed after 2007. The overall PM2.5 trend for all of China was -0.56 µ g m -3 year -1 with marginal significance (p=0.053) and PM2.5 concentrations in the Pearl River Delta region had a big drop (-4.81 µ g m -3 year -1 , p<0.001) in 2007–2010. The ECER policy during the 12th FYP period was basically an extension of the 11th FYP policy. PM2.5 is a kind of composite pollutant which comprises primary particles and secondary particles such as sulfate, nitrate, ammonium, organic carbon, elemental carbon, etc. Since the ECER policy focused on single-pollutant control, it had shown great limitation for PM2.5 reductions. The PM2.5 concentrations did not decrease from 2010 to 2013 in polluted areas (p values of the trends were greater than 0.05). Therefore, China implemented two stricter policies: the 12th FYP on Air Pollution Prevention and Control in Key Regions (APPC-KR) in 2012, and the Action Plan of Air Pollution Prevention and Control (APPC-AP) in 2013. The goal of air quality improvement (especially PM2.5 concentration improvement) and measures for multi-pollutant control were proposed. These policies led to dramatic decreases in PM2.5 after 2013 (-4.27 µ g m -3 year -1 for all of China in 2013–2017, p<0.001). [ABSTRACT FROM AUTHOR]

This study is the first attempt to understand the synergistic impact of anthropogenic and biogenic emissions on summertime ozone (O3) formation in the Guanzhong (GZ) Basin where Xi'an, the oldest and the most populous city (with a population of 9 million) in northwestern China, is located. Month-long (August 2011) WRF-Chem simulations with different sensitivity experiments were conducted and compared with near-surface measurements. Biogenic volatile organic compounds (VOCs) concentrations was characterized from six surface sites among the Qinling Mountains, and urban air composition was measured in Xi'an city at a tower 100ma.s. The WRF-Chem control experiment reasonably reproduced the magnitudes and variations of observed O3, VOCs, NOx, PM2.5, and meteorological parameters, with normalized mean biases for each parameter within -21 %. Subsequent analysis employed the factor separation approach (FSA) to quantitatively disentangle the pure and synergistic impacts of anthropogenic and/or biogenic sources on summertime O3 formation. The impact of anthropogenic sources alone was found to be dominant for O3 formation. Although anthropogenic particles reduced NO2 photolysis by up to 60 %, the anthropogenic sources contributed 19.1 ppb O3 formation on average for urban Xi'an. The abundant biogenic VOCs from the nearby forests promoted O3 formation in urban areas by interacting with the anthropogenic NOx . The calculated synergistic contribution (from both biogenic and anthropogenic sources) was up to 14.4 ppb in urban Xi'an, peaking in the afternoon. Our study reveals that the synergistic impact of individual source contributions to O3 formation should be considered in the formation of air pollution control strategies, especially for big cities in the vicinity of forests. [ABSTRACT FROM AUTHOR]

The article discusses public policies towards preventing pollution and offering services to populations exposed to pollutants, including laws on air and water pollution. The use of respiratory masks and home water filters to reduce exposure to pollutants, including water filter use in Flint, Michigan and masks worn in China, is discussed.

Diesel vehicles contributed 70 % of the NOx and more than 90 % of the PM in the 2014 on-road emissions inventory in China. Attention is therefore being focused on diesel vehicles because of their significantly higher NOx and PM emission rates and vehicle miles traveled, relative to gasoline-powered cars. Xi'an city has taken many measures to reduce diesel exhaust emissions. In this present study, the main objectives were to identify potential of emission-reduction strategies-fuel-standard improvements, elimination of 'yellow-brand' vehicles, increased use of alternative fuels (CNG, LNG), and installation of DPFs in older vehicles-and to quantify the relative effectiveness of each of these potential strategies. A revised MOVES model was used to estimate PM and NOx emission inventories for selected scenarios at the county scale, for Xi'an city. The results show that, for NOx reduction, the best strategy would be fuel-standard improvements (Scenario 1), followed by (in order of effectiveness) the increased use of alternative fuels (Scenario 3), elimination of 'yellow-brand' diesel vehicles (Scenario 2), and retrofitting older vehicles by installing DPFs (Scenario 4), whereas for PM10 or PM2.5, the effectiveness sequence of control strategies was found to be Scenario 1, Scenario 3, Scenario 2, and Scenario 4. It was also found that medium-weight and heavy trucks have a larger potential for NOx and PM reductions than do other vehicle types. These results are of paramount importance, not only for Xi'an but also for other cities that are considering adopting possible strategies to mitigate air pollution from vehicles. [ABSTRACT FROM AUTHOR]

The Beijing government has made great effort to solve the air pollution problem in recent years. In this paper, the major air pollution control measures and the air quality improvement from 2008 to 2014 in Beijing were represented. With the implementation of a series of unconventional and high-air pollutant reduction measures in Beijing and the surrounding area, good air quality during both the 2008 Olympic Games and the 2014 Asia-Pacific Economic Cooperation (APEC) conference was guaranteed. Notably, a new scientific approach was applied to formulate air pollution control policy during the APEC conference. In addition to the established measures, two periods of enhanced and targeted reduction measures were implemented according to the forecast in advance. Finally, suggestions for improving air quality in Beijing were offered on the basis of the monitoring results and analyses during the APEC conference. [ABSTRACT FROM AUTHOR]

In this study, a decomposition and emissions matrix is developed to identify the roles (giver or taker) played by the sectors in the greenhouse gas emissions for the economy of Beijing in China. Our results indicate that services were the most important emitter if we consider the total (direct and indirect) emissions. In addition to Construction, Scientific studies and technical services and Finance sectors of services were the largest takers. They have a large role in boosting greenhouse gas emissions throughout the economy of Beijing. As the basis and supporter of production activities, the electricity production and the transportation sectors were the greatest givers. More emphasis should be placed on using clean energy and carbon capture and storage technologies to reduce emissions within these sectors. Based on the roles played by these sectors in greenhouse gas emissions, some policy implications were proposed for energy utilization and carbon emissions trading. [ABSTRACT FROM AUTHOR]

As part of the 12th Five-Year Plan, the Chinese government has developed air pollution prevention and control plans for key regions with a focus on the power, transport, and industrial sectors. Here, we investigate the contribution of residential emissions to regional air pollution in highly polluted eastern China during the heating season, and find that dramatic improvements in air quality would also result from reduction in residential emissions. We use the Weather Research and Forecasting model coupled with Chemistry to evaluate potential residential emission controls in Beijing and in the Beijing, Tianjin, and Hebei (BTH) region. In January and February 2010, relative to the base case, eliminating residential emissions in Beijing reduced daily average surface PM2.5 (particulate mater with aerodynamic diameter equal or smaller than 2.5 micrometer) concentrations by 14 ± 7 μg·m-3 (22 ± 6% of a baseline concentration of 67 ± 41 μg·m-3; mean ± SD). Eliminating residential emissions in the BTH region reduced concentrations by 28 ± 19 μg·m- 3 (40 ± 9% of 67 ± 41 μg·m-3), 44 ± 27 μg·m-3 (43 ± 10% of 99 ± 54 μg·m- 3), and 25 ± 14 μg·m-3 (35 ± 8% of 70 ± 35 μg·m-3) in Beijing, Tianjin, and Hebei provinces, respectively. Annually, elimination of residential sources in the BTH region reduced emissions of primary PM2.5 by 32%, compared with 5%, 6%, and 58% achieved by eliminating emissions from the transportation, power, and industry sectors, respectively. We also find air quality in Beijing would benefit substantially from reductions in residential emissions from regional controls in Tianjin and Hebei, indicating the value of policies at the regional level. [ABSTRACT FROM AUTHOR]