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This paper quantitatively investigates the compositions of the gaseous pollutants in the ambient air of a secondary fiber paper mill. Total volatile organic compounds (TVOC), formaldehyde (HCHO), sulfur compounds (H2S), and hydrocarbon compounds (CxHy) were analyzed on six sampling sites with photo-ionisation detector, acetylacetone spectrophotometric method, and gas detector. The results revealed that, the high levels of TVOC and CxHywere detected at the wet end of paper machine and the office area, respectively; all the H2S contents on the six sites exceeded the limit (0.06 mg m−3) seriously; the HCHO concentrations at other five sites were out of the limit (0.10 mg m−3) except for the wastewater treatment plant. Furthermore, the necessary discussions about the possible pollution sources were considered on the process flow, the chemical agents used, and the ambient conditions in the paper mill. For the sake of air pollution control in paper mills, these remarkable results and analysis lay some technical basis in the following researches that should attract more attentions. [ABSTRACT FROM AUTHOR]

China is currently focusing on the cooperative control of air pollution and CO2 emissions, as well as the mitigation of economic policy uncertainty (EPU). By using panel data from 282 cities spanning from 2003 to 2017 and a newly constructed city-level EPU index, a spatial Durbin, two-way fixed-effects model is employed, with the aim of estimating the impact of EPU on the synergistic emissions intensity (SEI) of air pollutants and CO2. Additionally, this paper investigates the potential channels through which EPU influences SEI. It also explores how pressures related to environmental protection and economic development affect the impact of EPU on SEI. The results indicate that a unit increase in EPU will result in a rise in the SEI of local cities, adjacent cities, and total cities by 930.9%, 69,162.7%, and 70,093.6%, respectively. Moreover, the channel analysis suggests that EPU exacerbates SEI by undermining the upgrading of the industrial structure, augmenting industrial structure distortion, and escalating labor market distortion. Furthermore, the effect of EPU on SEI may be lessened by an increase in environmental protection pressure, while an increase in economic development pressure may exert a positive influence. Finally, this paper concludes by recommending that policymakers should prioritize the maintenance and stability of economic policies, facilitate the advancement of the industrial structure, enhance the efficiency of labor resource allocation, and underscore the significance of managing urban air pollution and CO2 emissions. [ABSTRACT FROM AUTHOR]

Earthquakes can cause serious damage to buildings, roads and other infrastructure. The large amount of dust and particulate matter generated when these structures collapse and are damaged can quickly enter the air, leading to a decline in air quality. At the same time, earthquakes may cause secondary disasters such as fires and landslides, which will also produce large amounts of soot and particulate matter, which will have a negative impact on air quality. Therefore, earthquake disaster risk assessment studies are carried out to identify potentially hazardous areas and facilities in advance in order to reduce the air pollution problems that may be caused by earthquakes. Existing research on earthquake disaster risk assessment mainly evaluates earthquake risk from the perspective of geology or seismology, but there are few studies based on multidisciplinary assessment that integrates geology, seismology, engineering and social sciences into socioeconomic factors. To this end, based on remote sensing and GIS technology, this paper takes Qinghai Province, a seismically active area, as the research area, and integrates land use data, natural environment data, social environment data and seismic parameter zoning data to construct a comprehensive assessment model for earthquake disaster vulnerability and risk. The results showed that there were 5 very high-risk areas, 7 high-risk areas, 10 medium-risk areas, 11 low-risk areas and 12 very low-risk areas in Qinghai Province. The high-risk areas are mainly distributed in the central and western parts of Qinghai Province, where the earthquake breeding environment is sufficient, the scale of active faults is huge and the adaptability of the carrier is low. The results of an earthquake disaster risk assessment can provide a reference for the government to formulate environmental protection policies. According to the assessment results, the government can formulate targeted measures to strengthen air pollution control and improve air quality. [ABSTRACT FROM AUTHOR]

With the continuous acceleration of urbanization, air pollution has become an increasingly serious threat to public health. Strengthening the detection and control of pollutants has become a focal point in current society. In light of the increasing amount of literature in the field of air pollution control with every passing year, numerous reviews have been compiled; however, only a limited number employ bibliometric methods to comprehensively review and summarize research trends in this field. Herein, this study utilizes two bibliometric analysis tools, namely, CiteSpace (6.1.R6) and VOSviewer (1.6.20), to conduct a visual and comprehensive analysis of air pollution literature spanning 2000 to 2023. By doing so, it establishes a knowledge framework for research on air pollution control. Simultaneously, collaborative network analysis, reference co-citation network analysis, keyword co-occurrence network analysis, and keyword prominence are employed to undertake an exhaustive and profound visual examination within this domain. Results indicate that, over time, the number of relevant papers has exponentially increased, while interdisciplinary cooperation trends have gradually formed. Additionally, this study describes key areas of current research, including air pollution control residue treatment, regional joint air pollution control, and air pollution control mechanism analysis. Finally, challenges faced by researchers in this field and their different perspectives are discussed. To better integrate research findings on air pollution control, we explore the correlations among data and systematically present their developmental trends. This confirms the interdisciplinary nature of air pollution control research, in the hope of its guiding air pollution control in the future. [ABSTRACT FROM AUTHOR]

Despite their key role in integrated waste management, direct (incineration) and indirect (gasification/pyrolysis) waste combustion processes are still opposed by some of the general public due to the past emission levels of air pollutants. In fact, although the release of air pollutants (especially dioxin) to the atmosphere from waste combustion processes has gradually decreased over the years, thanks to the introduction of stricter regulations and more advanced removal technologies, there is still an unsolved problem regarding the public acceptance of waste-to-energy facilities. The aim of this paper is to provide an overview of the state-of-the-art air pollution control (APC) technologies used in waste combustion facilities. Air pollution control technologies are designed to reduce or eliminate the emissions of harmful pollutants into the atmosphere. These technologies are important for safeguarding public health, protecting ecosystems, complying with regulations, and promoting a more sustainable and resilient future for both local and global communities. This paper will highlight the complexity behind emission control and the efforts made by this sector over the years. This paper will also propose suggested configurations based on the interactions/complementarity between different APC technologies and recent findings to improve their performance. [ABSTRACT FROM AUTHOR]

Air pollution poses a grave threat to human health and everyday life. Accurate air-quality prediction plays a crucial role in effectively preventing and controlling air pollution. A multi-graph spatial-temporal attention network is proposed to predict the air quality in a given area by analyzing the interconnections between stations and the individual characteristics of each station. Firstly, this paper constructs multi-scale spatial-temporal graphs from spatial and temporal perspectives to effectively capture the interconnections between stations, thereby comprehensively understanding the spatial-temporal relationships among them. Secondly, incorporating the nonlinear temporal correlation of station data, this paper proposes a temporal multi-graph attention-fusion module to integrate information from both neighboring stations and the station itself. Finally, predictions are made using a spatial-temporal graph network. The experiments in this paper were based on air-quality data from Beijing and Tianjin, and the following experimental results were obtained. (1) The proposed model outperforms the baselines significantly in both single-step and multi-step prediction tasks. (2) The ablation study confirms that the graph constructed in this paper contributes to improving the performance of the model. (3) Comparing the performance of attention components, the proposed attention mechanism exhibits better performance than other attention mechanisms. [ABSTRACT FROM AUTHOR]

Developing air quality management systems to control the impacts of air pollution requires reliable data. However, current initiatives do not provide datasets with large spatial and temporal resolutions for developing air pollution policies in Brazil. Here, we introduce the Brazilian Atmospheric Inventories (BRAIN), the first comprehensive database of air quality and its drivers in Brazil. BRAIN encompasses hourly datasets of meteorology, emissions, and air quality. The emissions dataset includes vehicular emissions derived from the Brazilian Vehicular Emissions Inventory Software (BRAVES), industrial emissions produced with local data from the Brazilian environmental agencies, biomass burning emissions from FINN – Fire INventory from the National Center for Atmospheric Research (NCAR), and biogenic emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN) (10.57760/sciencedb.09858, Hoinaski et al., 2023a; 10.57760/sciencedb.09886, Hoinaski et al., 2023b). The meteorology dataset has been derived from the Weather Research and Forecasting Model (WRF) (10.57760/sciencedb.09857, Hoinaski and Will, 2023a; 10.57760/sciencedb.09885, Hoinaski and Will, 2023c). The air quality dataset contains the surface concentration of 216 air pollutants produced from coupling meteorological and emissions datasets with the Community Multiscale Air Quality Modeling System (CMAQ) (10.57760/sciencedb.09859, Hoinaski and Will, 2023b; 10.57760/sciencedb.09884, Hoinaski and Will, 2023d). We provide gridded data in two domains, one covering the Brazilian territory with 20×20 km spatial resolution and another covering southern Brazil with 4×4 km spatial resolution. This paper describes how the datasets were produced, their limitations, and their spatiotemporal features. To evaluate the quality of the database, we compare the air quality dataset with 244 air quality monitoring stations, providing the model's performance for each pollutant measured by the monitoring stations. We present a sample of the spatial variability of emissions, meteorology, and air quality in Brazil from 2019, revealing the hotspots of emissions and air pollution issues. By making BRAIN publicly available, we aim to provide the required data for developing air quality policies on municipal and state scales, especially for under-developed and data-scarce municipalities. We also envision that BRAIN has the potential to create new insights into and opportunities for air pollution research in Brazil.​​​​​​​ [ABSTRACT FROM AUTHOR]

During the winter of 2019, the global outbreak of COVID-19 prompted extensive research on urban air pollution under lockdown measures. However, these studies predominantly focused on winter conditions, thereby limiting investigations into changes in urban air pollutants during other seasons that were also subject to lockdown restrictions. Shanghai, China, has undergone two COVID-19 lockdown periods in two seasons: winter 2019 and spring 2022. The seasonal variations and human activities were represented by meteorological factors and nighttime light brightness in this paper, respectively. The reduction in human-related emissions during the two lockdown periods was estimated based on the targets outlined in China's Air Pollution Prevention and Control Action Plan. The results showed significant reductions in NO2 and PM particles during the two lockdown periods, both accompanied by a notable increase in O3 concentration. In comparison to the winter lockdown, there was an approximate 40% decrease in the NO2 and PM2.5 concentrations in the spring, while the O3 concentration exhibited an increase of 48.81%. Furthermore, due to shifting wind patterns during the two lockdowns from winter to spring, the high-pollution core areas shifted 20–25 km southeastward in the spring. The PM particles and NO2 concentrations exhibited a considerable impact from human activities, whereas the O3 concentration was affected mostly by seasonal change and interactions among air pollutants. Compared to the corresponding non-lockdown condition, the concentration of CO decreased during the winter lockdown; however, it increased during the spring lockdown. The different change in CO concentration during the two lockdown periods was found to have a lower effect on the O3 concentration than that caused by changes in meteorological factors and nitrogen oxide (NO, NO2) concentrations. In summary, the impact of COVID-19 lockdown periods on urban air pollutants was more pronounced in spring compared to winter, and the interactions among air pollutants also underwent alterations. [ABSTRACT FROM AUTHOR]

During rapid urbanization, microclimate environment deterioration through events such as haze pollution and heat waves has continuously occurred in cities, which greatly affects the living environment, production activities, and health of urban residents. Therefore, it is particularly necessary to explore methods for controlling and optimizing the urban microclimate environment. In this paper, based on the mechanism of the effect of urban spatial structure at street-level on the distribution of atmospheric particulate matter, an indicator system that can be employed to comprehensively describe and quantify urban morphological structure at street-level was constructed from eight aspects: the spatial morphology of street-valleys, intensity of land use and development, geometric structure of buildings, inhomogeneity of buildings, roughness of the underlying surface, distribution of ecological landscapes, 3D architectural landscape morphology, and ventilation potential. Furthermore, using satellite remote sensing images and vector thematic maps of Shanghai, indicator factors were quantified by applying GIS technique. The intrinsic mechanism of the influence of the urban morphology on the diffusion and transport of atmospheric particulate matter was comprehensively analyzed by combining statistical methods and data mining algorithm, and eight key dominant factors were identified that can be considered to improve the urban ventilation conditions and help control urban air pollution, namely, the land use intensity, urban canopy resistance, vegetation cover, spatial congestion rate, comprehensive porosity, height-to-gross floor area ratio, building density, and average building volume ratio. As such, according to the quantitative analysis results for various combinations of the dominant factors, a spatial optimization strategy at street-level that can help improve the urban air quality was proposed in terms of identifying the pathways through which urban spatial elements affect the distribution of particulate matter, i.e., controlling the source–flow diversion–flow convergence process. [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]

Atmospheric chemistry research has been growing rapidly in China in the last 25 years since the concept of the "air pollution complex" was first proposed by Professor Xiaoyan TANG in 1997. For papers published in 2021 on air pollution (only papers included in the Web of Science Core Collection database were considered), more than 24 000 papers were authored or co-authored by scientists working in China. In this paper, we review a limited number of representative and significant studies on atmospheric chemistry in China in the last few years, including studies on (1) sources and emission inventories, (2) atmospheric chemical processes, (3) interactions of air pollution with meteorology, weather and climate, (4) interactions between the biosphere and atmosphere, and (5) data assimilation. The intention was not to provide a complete review of all progress made in the last few years, but rather to serve as a starting point for learning more about atmospheric chemistry research in China. The advances reviewed in this paper have enabled a theoretical framework for the air pollution complex to be established, provided robust scientific support to highly successful air pollution control policies in China, and created great opportunities in education, training, and career development for many graduate students and young scientists. This paper further highlights that developing and low-income countries that are heavily affected by air pollution can benefit from these research advances, whilst at the same time acknowledging that many challenges and opportunities still remain in atmospheric chemistry research in China, to hopefully be addressed over the next few decades. [ABSTRACT FROM AUTHOR]

The application of new energy systems for industrial production to advance air pollution prevention and control has become an irreversible trend. This development includes hybrid systems consisting of reversible solid oxide cells (RSOC) and a Li-ion battery; however, at present the energy dispatching of such systems has an unstable factor in the form of poor heat/electricity/gas controllability. Therefore, the system studied in this paper uses the Li-ion battery as the energy supply/storage case, and uses the RSOC to supply power for the Li-ion battery charge or the Li-ion battery supply power to the RSOC for hydrogen production by water electrolysis. In this hybrid system, Li-ion battery thermoelectric safety and RSOC hydrogen production stability are extremely important. However, system operation involves the switching of multiple operating conditions, and the internal thermoelectric fluctuation mechanism is not yet clear. Therefore, in this paper we propose a separate control with a dual mode for hybrid systems. Active disturbance rejection control (ADRC) with a simple structure is used to achieve Li-ion battery module thermoelectric safety and control the hydrogen production/consumption of the RSOC module in the hybrid system. The results show that the required Li-ion battery thermoelectric safety and RSOC hydrogen consumption/production requirements can be met using the proposed controller, leading to a hybrid system with high stability control. [ABSTRACT FROM AUTHOR]

A new long-term emission inventory called the Inversed Emission Inventory for Chinese Air Quality (CAQIEI) was developed in this study by assimilating surface observations from the China National Environmental Monitoring Centre (CNEMC) using the ensemble Kalman filter (EnKF) and the Nested Air Quality Prediction Modeling System (NAQPMS). This inventory contains the constrained monthly emissions of NOx, SO2, CO, primary PM2.5, primary PM10, and NMVOCs in China from 2013 to 2020, with a horizontal resolution of 15 km × 15 km. This paper documents detailed descriptions of the assimilation system and the evaluation results for the emission inventory. The results suggest that CAQIEI can effectively reduce the biases in the a priori emission inventory, with the normalized mean biases ranging from -9.1% to 9.5% in the a posteriori simulation, which are significantly reduced from the biases in the a priori simulations (-45.6% to 93.8%). The calculated RMSEs (0.3 mg/m³ for CO and 9.4-21.1 µg/m³ for other species, on the monthly scale) and correlation coefficients (0.76-0.94) were also improved from the a priori simulations, suggesting that CAQIEI can reasonably reproduce the magnitude and variation of emissions of different air pollutants in China. Based on CAQIEI, we estimated China's total emissions (including both natural and anthropogenic emissions) of the 6 species in 2015 to be as follows: 25.2 Tg of NOx, 17.8 Tg of SO2, 465.4 Tg of CO, 15.0 Tg of PM2.5, 40.1 Tg of PM10, and 46.0 Tg of NMVOCs. From 2015 to 2020, the total emissions reduced by 54.1% for SO2, 44.4% for PM2.5, 33.6% for PM10, 35.7% for CO, and 15.1% for NOx, but increased by 21.0% for NMVOCs. Larger emission reductions were achieved during the 2018-2020 action plan than during the 2013-2017 action plan for most species. In particular, NOx and NMVOC emissions were shown to increase during the 2013-2017 action plain, and there were obvious emission increases in the Fengwei Plain area over the Central China region. However, NOx and NMVOC emissions declined during the 2018-2020 action plan, and the emissions over the Fengwei Plain area also decreased. This suggests that the emission control policies were improved in the 2018-2020 action plan. We also compared CAQIEI with previous inventories, which verified our inversion results in terms of total emissions of NOx, SO2 and NMVOCs, and more importantly identified the potential uncertainties in our current understanding of China's air pollutant emissions. Firstly, CO emissions in China may be substantially underestimated by current inventories, with the CO emissions estimated by CAQIEI (426.8 Tg) being more than twice the amount in previous inventories (120.7-237.7 Tg). Significant underestimations for other air pollutant emissions may also exist over western and northeastern China. In addition, the NMVOC emissions were shown to be substantially underestimated over northern China but overestimated in southern China. Secondly, the emission reduction rates during 2015-2018 estimated by CAQIEI are generally smaller than those estimated by previous inventories, especially for NOx, PM10 and NMVOCs, suggesting that the mitigation effects of the air pollution control may be overestimated currently. In particular, China's NMVOC emissions were shown to have increased by 26.6% from 2015 to 2018, especially over the North China Plain by 38.0%), Northeast China (by 38.3%), and Central China (60.0%). In contrast, the emissions reduction rate of CO may be underestimated. Overall, our emissions inventory sheds new light on the complex variations of air pollutant emissions in China during its two recent clean air action periods, which could significantly improve our understanding of air pollutant emissions and related changes in air quality in China. [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]

The main objective of this paper is to analyze the impacts of Fluoranthene and Benzo (a) Anthracene PAHs pollutants on the health of peoples residing in Ghaziabad area of National Capital Region. This paper gives some relevant reactions of Triveni wood in Yagya process for control of air pollution. Practical work was carried for a duration of approx. 2 years. Sampling of Fluoranthene and Benzo (a) Anthracene PAHs was carried on every fortnight and data was collected. The present study is very useful to regulatory authorities and administration to understand problems of air pollution in the concerning areas and helpful in prevention of Air Pollution. In Ghaziabad City, the sampling locations were selected based on land used pattern, i.e., residential area, commercial and industrial area during four seasons viz. summer, Monsoon, Post monsoon and Winter. Fluoranthene and Benzo (a) Anthracene level and their variation were observed during these seasons. The result of concentration of Fluoranthene and Benzo (a) Anthracene is minimum in Govindpuram residential area of Ghaziabad and maximum concentration observed in Sahibabad industrial area, which shown in Figure 1 (Results and Discussion) in year Jan 2016–Dec 2017. The conclusion of this study is that the concentration of Benzo(a)anthracene (110.1 ng/m3) found greater than Fluoranthene (98.8 ng/m3) in all sites. [ABSTRACT FROM AUTHOR]

Traffic and production restrictions are two important emergency measures for controlling urban air pollution. The lockdown policies implemented during the COVID-19 pandemic period are nearly equivalent to the policies of traffic and production restriction, which provides a rare opportunity to quantitatively evaluate the effectiveness of these emergency measures. Taking Wuhan, China as the study area, this paper firstly verified the changes in six air pollutants and analyzed their change rules in different lockdown periods using statistical methods. Then the structural breakpoints in air pollutants were detected via regression discontinuity design model. To comprehensively understand the effects of restrictions on air pollution, the influences of meteorological conditions on air pollution were also investigated. The results illustrated that the concentrations of PM2.5, PM10 and NO2 decreased significantly during lockdown period. By comparing with the RDD coefficients of PM2.5 (−34.46), PM10 (−37.11) and NO2 (−19.15), the lockdown had little effect on CO (−0.32). The traffic and production restrictions had no apparent effects on SO2. Although O3 showed an increasing trend, the increase was not limited to the lockdown period, meaning that the traffic and production restrictions had less effect on the increasing trend of O3 concentration. Moreover, the structural breakpoints were verified in four air pollutants (PM2.5, PM10, NO2, and CO), and the structural breakpoints were caused by lockdown instead of the Spring Festival. The results also indicated that the meteorological conditions were not the main reasons for the changes in air pollutants during the lockdown period. This paper reveals how the traffic and production restrictions affect urban air pollution and provides a strong implementation basis for the air pollution control policy. Implications: The traffic and production restrictions are two important emergency measures for controlling heavy urban air pollution. However, these two measures have never been implemented in a large area like a city for a long enough period, so the effectiveness of these two measures has never been estimated quantitatively at a city level. The lockdown policies implemented during the COVID-19 pandemic are nearly equivalent to the policies of traffic and production restriction, which provides a rare opportunity to quantitatively evaluate the effectiveness of these emergency measures. Thus, this study measured the effectiveness of production and traffic restrictions on different air pollutants. This study provides the following implications: (1) the dominant factors for air pollution changes during the lockdown are traffic and production restriction instead of meteorological conditions; (2) the production and traffic restriction policies are effective for reducing concentrations of PM2.5, PM10 and NO2, while having less effect on O3 and CO concentrations; (3) the sharp changes in air pollutants in 2020 are unlikely to be caused by the Spring Festival. These findings are crucial for making more comprehensive policies for protecting urban air quality. [ABSTRACT FROM AUTHOR]

While the problem of Delhi's air pollution is well recognized, as is the class bias of the judiciary in targeting certain sources of air pollution over others, what is less will understood are the unintended consequences of air pollution interventions on indoor and outdoor air quality. This paper shows how the National Green Tribunal has targeted one source of air pollution in recommending waste-to-energy technologies that deprive waste pickers of their livelihoods. The pandemic-related lockdown provides an opportunity to assess the impacts of livelihood deprivation on fuel use. Using data collected from surveys of waste pickers, this paper shows that decreases in income are related to an increase in reliance on solid fuels. Therefore, we argue that air pollution interventions designed to control air pollution from poor waste management have the unintended consequence of increasing air pollution from a different source (biomass burning for cooking) that specifically impacts waste pickers by increasing their exposure to indoor air pollution, while also undermining the government's urban air pollution mitigation efforts overall. [ABSTRACT FROM AUTHOR]

A chemical transport model (CTM) is an essential tool for air quality prediction and management, widely used in air pollution control and health risk assessment. However, the current models do not perform very well in reproducing the observations of some major chemical components, for example, sulfate, nitrate, ammonium and organic carbon. Studies have suggested that the uncertainties in the model chemical mechanism, source emission inventory and meteorological field can cause inaccurate simulation results. Still, the emission source profile (used to create speciated emission inventories for CTMs) of PM 2.5 has not been fully taken into account in current numerical simulation. Based on the characteristics and variation rules of chemical components in typical PM 2.5 sources, different simulation scenarios were designed and the sensitivity of simulated PM 2.5 components to the source chemical profile was explored. Our findings showed that the influence of source profile changes on simulated PM 2.5 components' concentrations cannot be ignored. Simulation results of some components were sensitive to the adopted source profile in CTMs. Moreover, there was a linkage effect: the variation in some components in the source profile would bring changes to the simulated results of other components. These influences are connected to chemical mechanisms of the model since the variation in species allocations in emission sources can affect the potential composition and phase state of aerosols, chemical reaction priority, and multicomponent chemical balance in thermodynamic equilibrium systems. We also found that the perturbation of the PM 2.5 source profile caused variation in simulated gaseous pollutants, which indirectly indicated that the perturbation of source profile would affect the simulation of secondary PM 2.5 components. Our paper highlights the necessity of paying enough attention to the representativeness and timeliness of the source profile when using CTMs for simulation. [ABSTRACT FROM AUTHOR]

Developing air quality management systems to control the impacts of air pollution requires reliable data. However, current initiatives do not provide datasets with large spatial and temporal resolutions for developing air pollution policies in Brazil. Here, we introduce the Brazilian Atmospheric Inventories -- BRAIN, the first comprehensive database of air quality and its drivers in Brazil. BRAIN encompasses hourly datasets of meteorology, emissions, and air quality. We provide grid ded data in two domains, covering the Brazilian territory with 20x20 km of spatial resolution and another covering Southern Brazil with 4x4 km. The emissions dataset includes vehicular emissions derived from the Brazilian Vehicular Emissions Inventory Software (BRAVES), industrial emissions produced with local data from the Brazilian environmental agencies, biomass burning emissions from FINN - Fire Inventory from the National Center for Atmospheric Research (NCAR), and biogenic emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN). The meteorology dataset has been derived from Weather Research and Forecasting Model (WRF). The air quality dataset contains the surface concentration of 216 air pollutants produced from coupling meteorological and emissions datasets with the Community Multiscale Air Quality Modeling System (CMAQ). This paper describes how the datasets were produced, their limitations, and their spatiotemporal features. To evaluate the quality of the database, we compare the air quality dataset with 244 air quality monitoring stations, providing the model's performance for each measured pollutant by the monitoring stations. We present a sample of the spatial variability of emissions, meteorology, and air quality in Brazil from 2019, revealing the hotspots of emissions and air pollution issues. By making BRAIN publicly available, we aim to provide the required data for developing air quality policies on municipality and state scales, especially for not developed and data-scarce municipalities. We also envision that BRAIN has the potential to create new insights and opportunities for air pollution research in Brazil. [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]

The criteria-based sand and dust weather determination method has the problem ofbeing a cumbersome and time-consuming process when processing a large amount of raw data, and cannot avoid the problems of repeatability and reproducibility. On the basis of statistical analysis of the air automatic monitoring data in the cities affected by sand and dust, this paper proposes a k-means optimization algorithm (MDPD-k-means) based on maximum density and percentage distance, which can quickly filter the characteristic data of sand and dust in a short time, and identify the days affected by sand and dust. This method effectively improves the data processing efficiency, solves the problems of poor reproducibility and large artificial error of traditional methods, and can support the business application of sand and dust data elimination. This paper uses the method to identify the sand and dust data of 10 cities in Shaanxi Province from 2016 to 2022, determines a total of 1107 sand and dust days, and points out that the number of days affected by sand and dust is increasing year by year. After excluding the effect of sand and dust, the urban PM10 concentration decreases by 18.42~1.41% respectively, which provides important data information for accurately evaluating the effectiveness of air pollution prevention and control. [ABSTRACT FROM AUTHOR]

In order to achieve prevention and control of air pollution through energy consumption adjustment in advance, the paper proposes an Fuzzy Cognitive Map (FCM) of various energy resources affecting air quality, an incremental prediction algorithm of FCM and gradient descending method used to learn the FCM based on the small sample data on various energy consumptions and concentration of air pollutants. The FCM as an interpretable prediction method not only can predict future air quality more accurately, but also can analyze and interpret the affecting of various energy types on the future air quality. As the time delay of various energy consumptions affecting concentration of air pollutants, the quantitative time sequence influencing relationships (causality) in the FCM is mined directly from these data, and the air quality affected by various types of energy consumptions is predicted based on the FCM. Accordingly, the energy types affecting air pollution can be obtained for prior decision of energy consumption structure adjustment. The experimental results in Beijing-Tianjin-Hebei show that the FCM modeling is better than Support Vector Regression (SVR), Linear Regression (LR), Principal Component Analysis (PCA)-based forecasting, Convolutional Neural Networks (CNN) and Long-Short Term Memory (LSTM) methods in predicting air quality affected by energy resources, meanwhile according to the interpretable prediction results of the FCM, we obtain some interesting results and suggestions on energy consumption types in Beijing-Tianjin-Hebei regions in advance. Implications: At present, China's air pollution control has entered the deep-water area, and the biggest challenge is how to adjust the energy (consumption) structure. Therefore, this study completed the two important tasks: (1) driven by small sample data of energy consumptions, the paper provides an interpretable prediction model and method with better performance to achieve prevention and control of air pollution through energy consumption adjustment in advance; (2) according to the interpretable prediction results, the paper obtains some interesting results used to guide energy consumption adjustment in Beijing-Tianjin-Hebei regions. This study will provide beneficial suggestions and strategies for air pollution prevention and control in Beijing-Tianjin-Hebei, will help improve the air quality and energy consumption structure in Beijing-Tianjin-Hebei, and also can be extended to other regions. [ABSTRACT FROM AUTHOR]

Due to the high ability and flexibility of meta-heuristic algorithms (MAs), they can widely be used in many applications to solve different problems. Recently, real-world engineering applications of these optimization algorithms have attracted researchers' attention. This paper applies particle swarm optimization (PSO) as an effective population-based MAs to design the baghouse (BH). BH filters are among the most commonly used devices in air pollution control systems in mining and food manufacturers and power plants. Designing the BH depends on several parameters such as its capacity or airflow (Nm3/h), air-to-cloth ratio (a ∕ c), cam velocity, and installation limitations. Generally, industrial designers select the number and length of bags and their arrangement based on the experimental observations to meet the parameters mentioned above. The minimum cost or total weight of equipment is utilized for proposing a competitive price for suppliers. In this paper, a PSO algorithm is used to minimize the total cost by finding the best possible design (the number, length, and arrangement of bags). In addition, a real example of installed BH in a pelletizing plant is given and compared with PSO results to investigate the efficiency of the proposed algorithm. The results suggest that PSO can find a better design with minimum total cost than an installed BH filter, and therefore, PSO is applicable to industrial designers. [ABSTRACT FROM AUTHOR]

Prediction of air pollutant concentrations is currently one of the most important methods for the prevention and control of urban air pollution in most countries, and accurate and timely prediction of pollutant concentrations is of great significance for urban pollution control. Using Taiyuan, China, as a case study, this study examines how to predict hourly air pollutant concentrations over longer periods of time while ensuring their accuracy. In this paper, an air pollutant concentration prediction method based on improved inverse distance interpolation and Informer model (EIDW-Informer), and hour-by-hour prediction of PM2.5, NO2, and O3 concentrations in Taiyuan, China is carried out. In this study, historical data from seven environmental monitoring stations in Taiyuan City were used to build multidimensional environmental vectors and calculate the similarity between sample points. Then, the missing values in the dataset were interpolated according to the similarity and distance weights, and the long series prediction was performed by Informer. The experimental results show that the EIDW-Informer method has advantages in hour-by-hour prediction compared to LSTM, CNN-LSTM, and Attention-LSTM models, which improves by 20%, 27%, and 43% on 1 h, 8 h, and 72 h time scales, respectively. [ABSTRACT FROM AUTHOR]

The weekend effect, i.e., the concentration of air pollutants is different from weekends to weekdays, has been explored since the 1970 s. In most studies, the weekend effect is referred to the change of O 3 , i.e., lower emission of NO x on weekends leads to a higher concentration of O 3 . Determining whether it is true can provide insight into the strategy of air pollution controlling. In this study, we explore the weekly cycle of cities of China based on the weekly cycle anomaly (WCA), which is proposed in this paper. The advantage of using WCA is that we can avoid the influence of other change components such as the daily cycle and the seasonal cycle. The p values of the significant tests from all cities are analyzed for obtaining a whole picture of the weekly cycle of air pollution. The result shows that the concept of the weekend effect is not proper for cities in China, as many cities reach the valley phase of the emission on weekdays but not weekends. Thus, researches should not pre-assume that the weekend is the low emission scenario. We focus on the anomaly of O 3 on the peak and the valley of the emission scenario estimated by the NO 2 concentration. Through the analysis of the distribution of the p values of all cities, we show that almost all cities in China have weekly cycle of O 3 corresponding to the weekly cycle emission of NO x , i.e., O 3 of the peak time of NO 2 is less than valley time. The cities of the strong weekly cycle are located in four regions, i.e., the Beijing-Tianjing-Hebei region, the Shandong Peninsula Delta, the Yangtze River Delta, and the Pearl River Delta, and these regions are also the regions with relatively severe pollution levels. [ABSTRACT FROM AUTHOR]

Economic development and fast growing urbanization in China have caused severe air pollution, with frequent pollution episodes endangering the health of inhabitants and disturbing social activities, and as an expanding metropolis, Chengdu has suffered ever since. The concentration variations of main air pollutants, such as PM10, PM2.5 and NO2, often show periodicity because of meteorological impact and anthropic activities, and display orientation discrepancies due to influences of wind speed (WS), frequency and pollutant sources. These features have complicated the mechanisms of pollution episodes and deepened the difficulty in pollution control evaluation. The WS has significant influences on the periodicity and orientation variations in pollutant concentrations, and quantifying the influence of which is of high significance and provides sustainable foundations for pollution alleviation strategies. Different time-scale cycles (i.e., Diurnal, weekly, seasonal and annual), along with the WS, wind frequency, wind and spatial orientations in urban areas, were analyzed in this paper. Results show that the periodicity of diurnal, seasonal and annual cycles is remarkable, and weekly cycle is obvious by adding the influence of the WS in 16 orientations. The WS has direct impacts on pollutants varying in the range of 1.5–2.5 m/s, and has a remarkable diffusion effect on pollutants once above 2.5 m/s. Over heavy pollution hours in diurnal, weekly, annual cycles and transitional seasons, the WS had more significant influences on pollutants, and whereas the wind frequency is not the main impact factor for orientation variations. For Chengdu, the northeast orientation is suitable to construct a wind panel with a remarkable diffusion effect on pollutants, while air pollutions in the northwest and southwest orientations were severe with the WS below 1.5 m/s, and pollution diffusion in the north-northwest orientation was the worst. This work can provide guidance and reference for urban planning optimization and air environment protection in cities with air quality control considerations impacted by city wind. [ABSTRACT FROM AUTHOR]

Ultraviolet (UV)-based photocatalysis has been the subject of numerous investigations focused on mitigating undesirable pollutants in the gas phase. Few works report on applications beyond the proof of the concept. Even less is known about the current state of the art of UV photocatalysis in the context of animal agriculture. A growing body of research published over the last 15 years has advanced the knowledge and feasibility of UV-A photocatalysis for swine and poultry farm applications. This review paper summarizes UV-A photocatalysis technology's effectiveness in mitigating targeted air pollutants in livestock and poultry farms. Specifically, air pollutants include odor, odorous VOCs, NH3, H2S and greenhouse gases (CO2, CH4, N2O). We trace the progression of UV-A photocatalysis applications in animal farming since the mid-2000 and developments from laboratory to farm-scale trials. In addition, this review paper discusses the practical limitations and outlines the research needs for increasing the technology readiness and practical UV application in animal farming. [ABSTRACT FROM AUTHOR]

It is of great practical significance to analyze the hot issues, research frontiers, and trends concerning the relationship between air pollution and public health and to adopt reasonable strategies to control air pollution and prevent health hazards for follow-up research in this field. Unlike traditional literature reviews, this paper adopts a visual, flexible, and scientifically systematic approach to the analysis, which makes these analysis results more intuitive and comprehensive. Based on the core collection of the Web of Science and CNKI databases, this paper uses CiteSpace software to draw and comment on the maps of Chinese and English keywords, publishing time, author, country, and research institutions in this field. The results show the following: (1) The number of studies on the relationship between air pollution and health has increased year by year; researchers have formed sub cooperation networks, and the trend of cooperation and exchange has become more and more obvious in recent years; the impact of air pollution on health is a hot topic in the world. (2) Research hot topics mainly focus on the selection of air pollutants, health economic consequences of air pollution and the global burden of disease it causes, health indicators, research samples, which are gradually being refined, the synergistic governance of air pollution, and climate change. (3) The analysis of research frontiers and trends reveals that, first, the study of air pollutants in the English literature has undergone a refinement from nitrogen dioxide to fine particulate matter, and the sources of air pollutants in the Chinese literature have undergone changes in the petrochemical industry, indoor formaldehyde pollution, and haze. Second, atmospheric pollution has a significant negative impact on health, increasing the incidence of respiratory and cardiovascular diseases, and even causing death. Third, sustained exposure to pollution then causes greater damage to health and will be a key direction for future research. Fourth, the literature not only studies the correlation but also emphasizes the causal inference between air pollution and health and measures the economic costs associated with health. Finally, air pollution and climate change need to be governed synergistically. The article points out that the three areas of sustained pollution exposure, indirect consequences of negative health effects of air pollution, and air pollution and climate change may be the future focus of the field. [ABSTRACT FROM AUTHOR]

Air pollution is a global environmental issue, and there is an urgent need for sustainable remediation techniques. Thus, phytoremediation has become a popular approach to air pollution remediation. This paper reviewed 28 eco-friendly indigenous plants based on both the air pollution tolerance index (APTI) and anticipated performance index (API), using tolerance level and performance indices to evaluate the potential of most indigenous plant species for air pollution control. The estimated APTI ranged from 4.79 (Syzygium malaccense) to 31.75 (Psidium guajava) among the studied indigenous plants. One of the selected plants is tolerant, and seven (7) are intermediate to air pollution with their APTI in the following order: Psidium guajava (31.75) > Swietenia mahogany (28.08) > Mangifera indica L. (27.97) > Ficus infectoria L. (23.93) > Ficus religiosa L. (21.62) > Zizyphus Oenoplia Mill (20.06) > Azadirachta indica A. Juss. (19.01) > Ficus benghalensis L. (18.65). Additionally, the API value indicated that Mangifera indica L. ranges from best to good performer; Ficus religiosa L. and Azadirachta indica A. Juss. from excellent to moderate performers; and Cassia fistula L. from poor to very poor performer for air pollution remediation. The Pearson correlation shows that there is a positive correlation between API and APTI (R2 = 0.63), and this implies that an increase in APTI increases the API and vice versa. This paper shows that Mangifera indica L., Ficus religiosa L., and Azadirachta indica A. Juss. have good potential for sustainable reduction in air pollution for long-term management and green ecomanagement development. [ABSTRACT FROM AUTHOR]

The source profile of volatile organic compounds (VOCs) is essential for establishing reactivity- and toxicity-based emission inventories and developing effective air pollution control strategies. In this paper, the establishment of VOC source profiles and the VOC emission characteristics are reviewed in the petrochemical, solvent use, and chemical industries, and the most up-to-date profiles of the three industries in China are compiled via necessary adjustment and reconstruction of the test data from the literature. Alkanes dominated and OVOCs were often neglected in the overall petrochemical industry and refined processes. They accounted for 60.6% and 3.2% in the merged profiles. Aromatics and OVOCs dominated in the industrial solvent use industry. OVOCs were the most prevalent in the printing and dyeing industries, furniture manufacturing industries, and automobile coating process, whereas aromatics were major contributors of the total VOCs in metal surface coating, shipping coating, and other surface coating industries in the merged profiles. A wide range of products and limited profile studies were obtained in chemical industry, and the compositions of VOCs varied significantly in the production of 30 products in the merged profile. The future research directions of VOC source profiles are discussed, mainly focusing on the sampling, establishment, and evaluation of VOC profiles. [ABSTRACT FROM AUTHOR]

In the era of evidence-based policies, many public health professionals use data to explain complex ideas across academic disciplines, social groups, and players with different perspectives. We are looking for strategies for public health professionals to codify ethics and intellectual humility as core elements aiming to reflect on our own limitations, to create productive dialogs, and to offer our readers actionable data-driven suggestions. In November of 2022, the American Public Health Association celebrated its 150th anniversary with an in-person attendance meeting at the Boston Convention Centers. We invited Bertha Estella, the first author of the selected paper, to share her experience in public health research, training, and practice [[1]]. [Extracted from the article]

As the ecological environment becomes more and more important, the prevention and control of air pollution has become very important because volatile organic compounds （VOCs） have a significant impact on human health and living environment. The advantages and disadvantages of several current VOCs degradation technologies are summarized, including condensation technology, adsorption technology, catalytic combustion technology, photocatalytic technology and so on. This paper mainly introduces the technical principle of VOCs degradation by low-temperature plasma technology, summarizes its influencing factors, and highlights the importance of the influence of initial reactant concentration and power supply parameters. The future development direction of low temperature plasma technology is prospected. [ABSTRACT FROM AUTHOR]

Nitrogen dioxide (NO2) is an important precursor of atmospheric aerosol. Forecasting urban NO2 concentration is vital for effective control of air pollution. This paper proposes a hybrid deep learning model for predicting daily average NO2 concentrations on the next day, based on atmospheric pollutants, meteorological data, and historical data during 2014 to 2020 in five coastal cities of Shandong peninsula, northern China. A random Forest (RF) algorithm was used to select input variables to reduce data dimensionality trained by the sequence to sequence (Seq2Seq) the model and describe how the Seq2Seq model understands each predictor variable. The hybrid model combining an RF with Seq2Seq network (RF-S2S) was evaluated and achieved a Pearson's correlation coefficient of 0.93, a Nash–Sutcliffe coefficient (NS) of 0.79, a Root Mean Square Error (RMSE) of 5.85 µg/m3, a Mean Absolute Error (MAE) of 4.50 µg/m3, and a Mean Absolute Percentage Error (MAPE) of 20.86%. Feature selection by an RF model improves the performance of the Seq2Seq model, reducing errors by 19.7% (RMSE), 20.3% (MAE), and 29.3% (MAPE), respectively. Carbon monoxide (CO) and PM10 are two common, important features influencing the prediction of NO2 concentrations in coastal areas of northern China. The results of RF-S2S models can capture general trends and disruptions more accurately than can long-short term memory (LSTM) models with and without feature selection. The decreasing tendency of NO2 from 2014 to 2020 illustrated by the empirical mode decomposition (EMD) method is one important obstacle to improving the RF-S2S prediction accuracy. An EMD-based RF-S2S model could help to perform the short-term forecast of NO2 concentrations efficiently. [ABSTRACT FROM AUTHOR]

This review is aimed at researchers in air pollution control seeking to understand the latest advancements in volatile organic compound (VOC) removal. Implementing of plasma-catalysis technology for the removal of volatile organic compounds (VOCs) led to a significant boost in terms of degradation yield and mineralization rate with low by-product formation. The plasma-catalysis combination can be used in two distinct ways: (I) the catalyst is positioned downstream of the plasma discharge, known as the "post plasma catalysis configuration" (PPC), and (II) the catalyst is located in the plasma zone and exposed directly to the discharge, called "in plasma catalysis configuration" (IPC). Coupling these two technologies, especially for VOCs elimination has attracted the interest of many researchers in recent years. The term "synergy" is widely reported in their works and associated with the positive effect of the plasma catalysis combination. This review paper investigates the state of the art of newly published papers about catalysis, photocatalysis, non-thermal plasma, and their combination for VOC removal application. The focus is on understanding different synergy sources operating mutually between plasma and catalysis discussed and classified into two main parts: the effect of the plasma discharge on the catalyst and the effect of the catalyst on plasma discharge. This approach has the potential for application in air purification systems for industrial processes or indoor environments. [ABSTRACT FROM AUTHOR]

This paper examines the impact of air pollution control policies targeting key polluting enterprises, highlighting a strategic shift towards precision pollution control that concentrates on high-emission, high-risk businesses. The paper explores the efficacy of these policies and their potential spatial spillover effects, utilizing panel data from 259 Chinese cities from 2013 to 2021. Employing the difference-in-differences (DID) model and spatial Durbin model, the study analyzes both the direct local effects and the broader spatial consequences of these regulatory measures on air quality. The findings indicate a significant reduction in air pollutant concentrations in urban areas, attributing this improvement to factors such as industrial restructuring, increased investment in science and technology, and economic growth. Spatial econometric analysis further reveals a substantial positive correlation in air quality among Chinese cities. However, estimates of the spillover effect indicate that while such policies successfully reduce pollution locally, they could unintentionally degrade air quality in adjacent areas. The study highlights the need for nuanced policy strategies to mitigate unintended spatial spillovers and enhance overall effectiveness. It recommends tailored policies that integrate environmental and socioeconomic objectives, national and regional coordination for consistent enforcement, technology-driven compliance strategies, and incentives for sustainable enterprise practices. • Assessed impact of policies on key polluters in 259 Chinese cities. • Employed DID and spatial Durbin models for in-depth policy impact analysis. • Found significant reduction in urban air pollution from policies. • Revealed spatial spillover effects, aligning with "pollution haven" hypothesis. • Proposed nuanced approaches for local and spatial policy impacts. [ABSTRACT FROM AUTHOR]

Currently, the complex bottom-up emissions inventories are in rise. Its development is essential for both understanding the sources of air pollution and designing effective air pollution control measures. Anyway, the main challenge to get the most reliable emissions evidence is the variety of contributing sources, the complexity of the technology mix and the lack of reliable emission factors. The input data bases are improving constantly, by more reliable statistics and survey-based data. Our study reveals the strengths and deficiency of currently published scientific papers on the topic of emission inventory. With that purpose, 40 crucial scientific papers were selected. We first highlight the period and geographic region, when and where the inventories were made for. We then summarize the sector-based estimates of emissions of different species contained by SNAP sectors in selected inventories. Additionally, the resolution of inventories is analysed. Finally, the last section summarizing common ways of assessing and validating inventories and their main purpose. This review shows that there is still a lot of chance to improve emissions inventories in a way to develop input data and emission factors for different technologies and activities or to develop inventories on fine grids. Those efforts will give us wider knowledge about pollution sources and will lead to accepted better air quality policy. [ABSTRACT FROM AUTHOR]

The numerical treatment of an atmospheric chemical scheme, which contains 56 species, is discussed in this paper. This scheme is often used in studies of air pollution levels in different domains, as, for example, in Europe, by large-scale environmental models containing additionally two other important physical processes—transport of pollutants in the atmosphere (advection) and diffusion phenomena. We shall concentrate our attention on the efficient numerical treatment of the chemical scheme by using Implicit Runge–Kutta Methods combined with accurate and efficient advanced versions of the Richardson Extrapolation. A Variable Stepsize Variable Formula Method is developed in order to achieve high accuracy of the calculated results within a reasonable computational time. Reliable estimations of the computational errors when the proposed numerical methods are used in the treatment of the chemical scheme will be demonstrated by presenting results from several representative runs and comparing these results with "exact" concentrations obtained by applying a very small stepsize during the computations. Results related to the diurnal variations of some of the chemical species will also be presented. The approach used in this paper does not depend on the particular chemical scheme and can easily be applied when other atmospheric chemical schemes are selected. [ABSTRACT FROM AUTHOR]

The PM2.5 (fine particulate matter with diameter ≤2.5 μm) concentration anomalies over the North China Plain (NCP) in early and late winter sometimes show a subseasonal reversal, which brings a great challenge for precise control of air pollution, and mechanisms are not well understood. This paper reveals the key role of the Barents Sea sea‐ice in this reversal. In early winter, a negative Scandinavian‐like pattern causes an anticyclonic anomaly over Northeast Asia and thus leads to the positive PM2.5 concentration anomaly over the NCP. In addition, anomalous warm advection associated with the positive North Atlantic Oscillation‐like pattern accelerates winter sea‐ice loss in the Barents Sea, especially in late winter, which increases the surface turbulent heating flux. These heating causes a negative Polar/Eurasian‐like pattern that induces a cyclonic anomaly over Northeast Asia and eventually leads to a negative PM2.5 concentration anomaly over the NCP in late winter. Vice versa. Plain Language Summary: In this study, we find that there is a significant seesaw pattern of PM2.5 concentration anomalies over the North China Plain (NCP) in early and late winter. Further results reveal that variations in Barents Sea sea‐ice play a crucial role. More specifically, a negative (positive) Scandinavian‐like pattern in early winter tends to induce an anticyclonic (a cyclonic) anomaly over Northeast Asia. This anticyclonic (cyclonic) anomaly leads to a higher (lower) PM2.5 concentration anomaly over the NCP in early winter. In addition, a North Atlantic Oscillation‐related warm (cold) temperature advection promotes (inhibits) the sea‐ice loss in the Barents Sea, especially in late winter. The Barents Sea‐ice loss (increment) in late winter tends to heat (cool) the lower‐level atmosphere and thus triggers an anticyclonic (a cyclonic) response in the upper troposphere there. The anticyclonic (cyclonic) response in the Barents Sea region as a part of the negative (positive) Polar/Eurasian‐like pattern induces a cyclonic (an anticyclonic) anomaly over Northeast Asia, which leads to a lower (higher) PM2.5 concentration anomaly over the NCP in late winter. These findings could be of great value for the subseasonal predictions of PM2.5 concentrations over the NCP in winter. Key Points: PM2.5 concentration anomaly over the North China Plain shows an visibly subseasonal reversal in early and late winter on interannual scaleThe Scandinavia‐like pattern and Polar/Eurasian‐like pattern are responsible for the seesaw pattern of PM2.5 concentration anomaliesThe sea‐ice variations in the Barents Sea play a key role in modulating such atmospheric circulations [ABSTRACT FROM AUTHOR]

Comprehensive investigation and analysis of the effects of policies on energy conservation and emission reduction or envi⁃ ronmental regulation have important reference value for the specific implementation of environmental regulation policies. Based on the provincial panel data of China from 2000 to 2019, the present study took the introduction of the Action Plan for Air Pollution Prevention and Control as a quasi-natural experiment and used the DID approach to conduct causal identification. Eight provinces or municipali⁃ ties in the three regions of Beijing-Tianjin-Hebei, the Yangtze River Delta, and the Pearl River Delta were selected as the treatment group and the other provinces as the control group. The regional differences in energy mismatch effects of environmental regulation poli⁃ cies were evaluated by comparing the sample areas in the treatment group and the control group. According to the empirical analysis, environmental regulation policies had a significant negative effect on energy mismatch, i.e., the greater the intensity of environmental regulation policies, the stricter the constraints on enterprises, and the higher the internalized cost of enterprises. The continuous im⁃ provement in energy marginal output of 'forced' enterprises made the energy mismatch index higher. Combined with typical facts, it was found that the current environmental regulation policies had a role in promoting the over-distribution of energy mismatch. Specifi⁃ cally, after 2013, when the energy mismatch index in many regions exceeded 1, they did not show a trend of approaching 1, but instead continued to rise at a fast speed. Further research showed that regional differences in environmental regulation policies led to regional differences in energy mismatch effects, which were realized through different levels of implementation intensity of local governments. That is, the stronger the implementation intensity of local governments in accordance with the central environmental regulation require⁃ ments, the higher the energy mismatch index. Finally, based on the research conclusions, this paper puts forward some suggestions for the improvement of environmental regulation policies in the next stage. First, the institutional arrangement of regional differences in en⁃ vironmental regulation policies is a 'double-edged sword'. Although it can make the regions have a target based on their local realities, it is not conducive to the construction of a large unified domestic market. Second, it is suggested that energy market reform be accelerat⁃ ed, that prices play a leading role, and that the role of the market in energy allocation be enhanced. [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]

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]

With the revision of the Air Pollution Control Act in Taiwan announced on 1 August 2018, several provisions or regulations have been added to strengthen the control of hazardous air pollutants (HAPs) from stationary sources. Therefore, this paper conducted a survey of sixty toxic volatile organic compounds (VOCs) designated as HAPs in Taiwan and also performed a comparison between some developed countries (i.e., the USA, Japan, and Korea) using the latest databases issued by the relevant agencies/organizations. Furthermore, these designated HAPs were reviewed by their carcinogenic classifications and occupational exposure limits. Finally, the regulatory measures for controlling the emissions of toxic VOCs from stationary sources in Taiwan were addressed to echo the public concerns about their human health risk. Except for trichloroacetic acid, the designated toxic VOCs in Taiwan are included in the list of HAPs in the USA. By comparison, the number of designated HAPs is obviously higher than those in Japan and Korea. Based on the carcinogen classification by the International Agency for Research on Cancer (IARC), the toxic VOCs as confirmed human carcinogens (Group 1) include benzene, benzidine, 1,3-butadiene, 1,2-dichloroproane, ethylene oxide, formaldehyde, 4,4-methylene bis(2-chloroaniline), trichloroethylene, and vinyl chloride. To achieve the purpose of protecting public health, the follow-up control actions of HAPs from stationary sources in Taiwan involved regulatory countermeasures, including the establishment of emission limits, reporting systems, reduction plans for potential high-risk areas or plants, the incentive of an air pollution fee levy, as well as an ambient air concentration monitoring network. [ABSTRACT FROM AUTHOR]

In order to explore the comprehensive assessment method of air quality of pollutant emission of energy consumption in China's urban internal industrial parks, based on the full consideration of the actual situation of air pollution control in Nanjing HX Industry Park, this paper selects 15 air quality assessment indicators. According to the national air quality standard, the air quality standard of Nanjing and the air quality standard of Nanjing HX Industry Park, the air quality assessment standard is determined about pollutant emission of energy consumption in Nanjing HX Industry Park. Through the technical treatment of the selected assessment indicators, the niche suitability model is introduced, and based on this, the spatial niche suitability model is reconstructed to comprehensively assess the air quality of pollutant emission of energy consumption in Nanjing HX Industry Park. The study found that the air quality of Nanjing HX Industry Park has been improved from level III in 2012 to level I in 2020. According to the assessment results, the differences of assessment results of different niche suitability models are discussed, which fully reflects the advantages of spatial niche assessment methods. The change law and influencing factors of the assessment results are further discussed. [ABSTRACT FROM AUTHOR]

Air pollution control policies in China have been experiencing profound changes, highlighting a strategic transformation from total pollutant emission control to air quality improvement, along with the shifting targets starting from acid rain and NO x emissions to PM 2.5 pollution, and then the emerging O 3 challenges. The marvelous achievements have been made with the dramatic decrease of SO 2 emission and fundamental improvement of PM 2.5 concentration. Despite these achievements, China has proposed Beautiful China target through 2035 and the goal of 2030 carbon peak and 2060 carbon neutrality, which impose stricter requirements on air quality and synergistic mitigation with Greenhouse Gas (GHG) emissions. Against this background, an integrated multi-objective and multi-benefit roadmap is required to provide decision support for China's long-term air quality improvement strategy. This paper systematically reviews the technical system for developing the air quality improvement roadmap, which was integrated from the research output of China's National Key R&D Program for Research on Atmospheric Pollution Factors and Control Technologies (hereafter Special NKP), covering mid- and long-term air quality target setting techniques, quantitative analysis techniques for emission reduction targets corresponding to air quality targets, and pathway optimization techniques for realizing reduction targets. The experience and lessons derived from the reviews have implications for the reformation of China's air quality improvement roadmap in facing challenges of synergistic mitigation of PM 2.5 and O 3 , and the coupling with climate change mitigation. [Display omitted] [ABSTRACT FROM AUTHOR]

Atmospheric oxidizing capacity (AOC) is an essential driving force of troposphere chemistry and self-cleaning, but the definition of AOC and its quantitative representation remain uncertain. Driven by national demand for air pollution control in recent years, Chinese scholars have carried out studies on theories of atmospheric chemistry and have made considerable progress in AOC research. This paper will give a brief review of these developments. First, AOC indexes were established that represent apparent atmospheric oxidizing ability (AOIe) and potential atmospheric oxidizing ability (AOIp) based on aspects of macrothermodynamics and microdynamics, respectively. A closed study refined the quantitative contributions of heterogeneous chemistry to AOC in Beijing, and these AOC methods were further applied in Beijing-Tianjin-Hebei and key areas across the country. In addition, the detection of ground or vertical profiles for atmospheric OH·, HO 2 ·, NO 3 · radicals and reservoir molecules can now be obtained with domestic instruments in diverse environments. Moreover, laboratory smoke chamber simulations revealed heterogeneous processes involving reactions of O 3 and NO 2 , which are typical oxidants in the surface/interface atmosphere, and the evolutionary and budgetary implications of atmospheric oxidants reacting under multispecies, multiphase and multi-interface conditions were obtained. Finally, based on the GRAPES-CUACE adjoint model improved by Chinese scholars, simulations of key substances affecting atmospheric oxidation and secondary organic and inorganic aerosol formation have been optimized. Normalized numerical simulations of AOIe and AOIp were performed, and regional coordination of AOC was adjusted. An optimized plan for controlling O 3 and PM 2.5 was analyzed by scenario simulation. [Display omitted] [ABSTRACT FROM AUTHOR]

China has put great efforts into air pollution control over the past years and recently committed to its most ambitious climate target. Cost and benefit analysis has been widely used to evaluate the control policies in terms of past performance, future reduction potential, and direct and indirect impacts. To understand the cost and benefit analysis for air pollution control in China, we conducted a bibliometric review of more than 100 studies published over the past two decades, including the current research progress, most commonly adopted methods, and core findings. The control target in cost and benefit analysis has shifted in three stages, from individual and primary pollution control, moving to joint prevention of multiple and secondary pollutants, and then towards synergistic control of air pollution and carbon. With the expansion of the research scope, the integrated assessment model has gradually demonstrated the necessity for long-term ex-anti policy simulation, especially for dealing with complex factors. To ensure long-term air quality, climate, public health, and sustainable economic development, substantial evidence from published studies has suggested that China needs to continue its efforts in the upstream adjustment of the energy system and industrial structure with multi-regional and -sector collaboration. This cost and benefit review paper provides decision-makers with the fundamental information and knowledge gaps in air pollution control strategies in China, and direction for facing future challenges. [Display omitted] [ABSTRACT FROM AUTHOR]

The mobility of air pollution and the free-riding phenomenon in the process of pollution control determine that joint prevention and control policies should be implemented in a larger area. As China’ s economic development shifts from high-speed growth to high-quality development, the spatial structure of economic development is undergoing profound changes. Regional integration with urban agglomerations and megalopolis as units plays an increasingly important role in promoting economic development and environmental governance. Based on the regression method of geographical regression discontinuity, this study used the panel data of prefectures and counties in China from 2005 to 2019 to study whether the regional integration of urban agglomeration was conducive to better haze reduction. The empirical results showed that: ① On the whole, the regional integration of urban agglomeration played a role in haze reduction, and the annual average PM2.5 concentration of prefectures and counties within the urban agglomeration was 11.204 μg/m³ lower than that of those outside the urban agglomeration. ② Mechanism analysis showed that structural haze reduction and technical haze reduction were important ways for regional integration to exert haze reduction effects. The former was mainly realized through industrial division and transfer between the central area and the peripheral area, and the latter was mainly realized through technology transfer and knowledge spillover under the center-periphery structure. ③ The haze reduction effects produced by regional integration had large regional differences, and the three major urban agglomerations with relatively mature development had the most significant haze reduction effects. Furthermore, the joint prevention and control policy of air pollution with urban agglomeration as the unit exerted a better effect on haze reduction. ④ The implication of this paper showed that: regional integration has produced a significant positive environmental impact and it is of great practical significance to continuously build an inter-regional environmental collaborative governance mechanism within the scope of urban agglomeration. It is necessary to actively promote the overall control of air pollution on a larger geographical scale and pay attention to the division of labor and cooperation between industries in different regions in the process of regional integration, and at the same time, increase investment in technological innovation within the region and encourage local government and enterprises to carry out research and development of pollution control and emission reduction technologies. [ABSTRACT FROM AUTHOR]

To monitor the spread of the novel coronavirus (COVID-19), India, during the last week of March 2020, imposed national restrictions on the movement of its citizens (lockdown). Although India's economy was shut down due to restrictions, the nation observed a sharp decline in particulate matter (PM) concentrations. In recent years, Delhi has experienced rapid economic growth, leading to pollution, especially in urban and industrial areas. In this paper, we explored the linkages between air quality and the nationwide lockdown of the city of Delhi using a geographic information system (GIS)-based approach. Data from 37 stations were monitored from 12 March, 2020 to 2 April, 2020 and it was found that the Air Quality Index for the city was almost reduced by 37% and 46% concerning PM2.5 and PM10, respectively. The study highlights that, in regular conditions, the atmosphere's natural healing rate against anthropogenic activities is lower, as indicated by a higher AQI. However, during the lockdown, this sudden cessation of anthropogenic activities leads to a period in which the natural healing rate is greater than the induced disturbances, resulting in a lower AQI, and thus proving that this pandemic has given a small window for the environment to breathe and helped the districts of Delhi to recover from serious issues related to bad air quality. If such healing windows are incorporated into policy and decision-making, these can prove to be effective measures for controlling air pollution in heavily polluted regions of the World. [ABSTRACT FROM AUTHOR]

While combating air pollution may seem to be a corporate responsibility, what individuals contribute can be substantial. This study explores the individual's behavioral intention to reduce the air pollution associated with vehicles, household appliances, and religious practices. An extended theory of planned behavior (TPB), past behavior included, serves as the analytical model, while the approach of partial least squares structural equation modeling (PLS-SEM) is employed in the model's estimation. The results show that subjective norms represent the primary driver of individual intentions to reduce air pollution, followed by perceived behavioral control, past behavior, and attitude, in that order. Surprisingly, advocacy on the part of the government to reduce the burning of incense and joss paper, disregarding years of social conflicts and protests, plays the most important role among all indicators within the construct subjective norms. This result holds even within the subsample of believers in religions that involve the practice of burning incense and joss paper. • Subjective norms represent the primary driver of individual intentions to reduce air pollution. • Governmental advocacy to reduce the burning of incense and joss paper plays an important role. • Individuals' attitudes towards de-carbonization and mitigating air pollution differ. [ABSTRACT FROM AUTHOR]