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

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]

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]

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

Air pollution affects people's life and health, and controlling air pollution requires the collection of polluting gas information. Unmanned aerial vehicles (UAVs) have been used for environmental detection due to their characteristics. However, the limitation of onboard energy sources of UAVs will limit the coverage of the detection area and the number of gas samples collected, which will affect the assessment of pollution levels. In addition, to truly and completely reflect the distribution of atmospheric pollutants, it is necessary to sample the entire three-dimensional space. This paper proposes a three-dimensional space path planning method suitable for UAV atmospheric environment detection, which can generate a full-coverage path with optimal coverage density under energy constraints. Simulation results show that the proposed method can effectively improve the coverage density compared with other path generation methods. Field experiments show that the proposed method is reliable and accurate in the application of UAV atmospheric environment space detection. [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]

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]

Most of these papers focused on the characterization and mitigation of air pollutants in the rural areas, and few of them considered the air pollutants from urban area. With rapid development of modern agriculture, a multitude and a large amount of air pollutants were generated by agricultural activities, which are becoming more and more serious issues with regards to air pollution [[1]]. (3) Residential combustion Compared with industrial sources, rural residential combustion is more harmful to air quality and human health under the same emission values of air pollutants. Strategies on the Air Emission Control for Rural Areas With the rapid development of modern agriculture, the impact of pollutants emitted by agricultural activities on the atmosphere is gradually non-negligible, and more and more relevant studies have been conducted to reduce the threat of agricultural air pollution [[1]]. [Extracted from the article]

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]

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]

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]

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]

China's approach to air pollution control has been shown successful in East Asian countries and even elsewhere in the world. The analysis of the evolution and control of air pollution in China over the past 75 years can be used as a reference for developing countries suffering from air pollution resulting from urbanization. Based on the sorting and mining of relevant indicators, data and policy texts from the areas of population, economy, space and social urbanization, the findings suggest that the presence of air pollution and its changing forms indeed have complex interactive relationships with the process of urbanization. Specifically: (1) the feature of air pollution has changed from "single pollutant and pollution source to multiple pollutants and pollution source, local pollution to regional pollution, light pollution to heavy compound pollution" as a result of urbanization, the emphasizing of construction and the neglect of governance, the emphasizing of economics and the neglect of ecology, and the emphasizing of immediate interests over long-term interests; (2) the interactive relationship between air pollution and urbanization has also gone through three stages from being irrelevant each other to "urbanization determines air pollution" and then "air pollution restricts urbanization"; (3) this has forced air pollution control to shift from the traditional "treating symptoms" to "high-quality urbanization", thus promoting air pollution and urbanization to move "from confrontation to unification". Therefore, air pollution control is not a simple technical issue; one of the keys lies in exploring how to adjust the urbanization model, so as to achieve the "win–win" of urbanization and air pollution control. [ABSTRACT FROM AUTHOR]

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

The impact of air pollution on human health is becoming increasingly severe, and economic losses are a significant impediment to economic and social development. This paper investigates the impact of air pollutants on the respiratory system and its action mechanism by using information on inpatients with respiratory diseases from two IIIA (highest) hospitals in Wuhan from 2015 to 2019, information on air pollutants, and meteorological data, as well as relevant demographic and economic data in China. This paper describes the specific conditions of air pollutant concentrations and respiratory diseases, quantifies the degree of correlation between the two, and then provides a more comprehensive assessment of the economic losses using descriptive statistical methods, the generalized additive model (GAM), cost of illness approach (COI), and scenario analysis. According to the findings, the economic losses caused by PM2.5, PM10, SO2, NO2, and CO exposure are USD 103.17 million, USD 70.54 million, USD 98.02 million, USD 40.35 million, and USD 142.38 million, for a total of USD 454.46 billion, or approximately 0.20% of Wuhan's GDP in 2019. If the government tightens control of major air pollutants and meets the WHO-recommended criterion values, the annual evitable economic losses would be approximately USD 69.4 million or approximately 0.03% of Wuhan's GDP in 2019. As a result, the relevant government departments must strengthen air pollution control to mitigate the impact of air pollution on population health and the associated economic losses. [ABSTRACT FROM AUTHOR]

This paper aimed to study how industrial air pollution impacts crop yield by investigating the relationship between output and changes in factors. A translog production function was estimated in the context of stochastic frontier analysis using data collected from a field survey in the case of corn. The interaction between the factors as well as the impact of industrial air pollution on the relationship between factors was analyzed using numerical simulation, followed by the estimation of economic losses of corn yield in the polluted area. Results show that industrial air pollution causes a decrease in crop yield for two reasons. First, industrial air pollution changes the output elasticities of production factors and reduces its absolute amount. Second, industrial air pollution causes the relationship between labor and capital, labor and chemicals, capital and seeds to change from substitutable to complementary; it also resulted in an opposite result for the relationship between capital and chemicals. The paper presents a new explanation of how industrial air pollution affects agricultural production from an economic perspective. [ABSTRACT FROM AUTHOR]

Since its establishment in 1948, the State of Israel has been oriented towards economic development and industrialization, with a transportation sector increasingly focused on private cars. In 1961, initial awareness of environmental risks led to the adoption of the Abatement of Nuisances Law, which served as the platform for air pollution policy for several decades, even as population growth and growth of the industrial sector, including fossil fuel power plants, led to a continuous increase in air pollution. In the early 2000s, the environmental movement in Israel criticized local air pollution policy as being out of date and started to promote a new Clean Air Law. The law, which was adopted in 2008 and came into force in 2011, was a watershed in air pollution policy in Israel. It includes ambient air quality values for 28 contaminants, emission permits for the industrial sector based on best available techniques (BAT), an enforcement system, and a unified and transparent monitoring system. This paper reviews the history of air pollution policy in Israel from 1948, through the 1961 and 2008 landmark legislations and their strengths and weaknesses, to the present. The paper ends with recommendations for future air pollution policy in Israel. [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]

Artificial rain, a technology primarily used for drought relief, has recently been used for combating regional air pollution. However, there are limited available measurement data to confirm the effectiveness of this control practice. In this study, we summarize control theories and indirect but relevant observations/findings, including air pollutant reduction after natural rain events and roadside sprinkling. A brief review of artificial rain basics is also provided. Our work shows that artificial rain appears to be a promising management strategy for air pollution control. However, field measurements are needed to further assess the cost-effectiveness of the practice, as well as the other benefits or challenges it may create. [ABSTRACT FROM AUTHOR]

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

The adverse effects of polluted air on human health have been increasingly appreciated worldwide. It is estimated that outdoor air pollution is associated with the death of 4.2 million people globally each year. Accumulating epidemiological studies indicate that exposure to ambient fine particulate matter (PM2.5), one of the important air pollutants, significantly contributes to respiratory mortality and morbidity. PM2.5 causes lung damage mainly by inducing inflammatory response and oxidative stress. In this paper, we reviewed the research results of our group on the effects of PM2.5 on chronic obstructive pulmonary disease, asthma, and lung cancer. And recent research progress on epidemiological studies and potential mechanisms were also discussed. Reducing air pollution, although remaining a major challenge, is the best and most effective way to prevent the onset and progression of respiratory diseases. [ABSTRACT FROM AUTHOR]

For the first time, periodontitis risk associated with long-term air pollution has been assessed in the Taiwan population by Lin, H.-J. and colleagues [[1]]. 10.3390/atmos12080947 7 Wu C.-C., Fang W.-H., Wang C.-C., Lai C.-H., Chen W.-L. 10.3390/atmos12081073 5 Chen H.-L., Zhang R., Tsai S.C.-S., Chou R.-H., Hsu Y.-C., Fan H.-C., Muo C.-H., Hsu C.Y., Chang K.-H. Ambient Air Pollution Exposure and Risk of Developmental Delay in Children and Teenagers in Taiwan. [Extracted from the article]

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]

During the last few decades, European legislation has driven progress in reducing air pollution in Europe through emission mitigation measures. In this paper, we use a chemistry transport model to assess the impact on ambient air quality of the measures considered for 2030 in the for the scenarios with existing (WEM2030) and additional measures (WAM2030). The study estimates a general improvement of air quality for the WAM2030 scenario, with no non-compliant air quality zones for NO2, SO2, and PM indicators. Despite an improvement for O3, the model still estimates non-compliant areas. For this pollutant, the WAM2030 scenario leads to different impacts depending on the indicator considered. Although the model estimates a reduction in maximum hourly O3 concentrations, small increases in O3 concentrations in winter and nighttime in the summer lead to increases in the annual mean in some areas and increases in other indicators (SOMO35 for health impacts and AOT40 for impacts on vegetation) in some urban areas. The results suggest that the lower NOx emissions in the WEM and WAM scenarios lead to less removal of O3 by NO titration, especially background ozone in winter and both background and locally produced ozone in summer, in areas with high NOx emissions. [ABSTRACT FROM AUTHOR]

This paper aims to provide scientific support for decision-making in the field of improving air quality by evaluating pollution reduction measures included in the current Spanish policy framework of the 1st National Air Pollution Control Programme (NAPCP). First, the health impacts of air quality are estimated by using the concentrations estimated by multiscale air quality modeling and the recommended concentration–response functions (CRF), specifically as a result of exposure to particulate matter (PM), nitrogen dioxide (NO2), and ozone (O3). Second, the associated external costs are calculated by monetization techniques. Two scenarios are analyzed: a package including existing measures (WM2030) and a package with additional measures (WAM2030). Compared with the baseline scenario, an improvement was found in the health effects of NO2, PM10, and PM2.5, while for O3 there was a slight worsening, mainly due to the increase in the O3 metric used (SOMO35), which increases over some urban areas. Despite this, the monetary valuation of the total effects on health as a whole shows external benefits due to the adoption of measures (WM2030), compared with the reference scenario (no measures) of more than € 17.5 billion and, when considering the additional measures (WAM2030), benefits of about € 58.1 billion. [ABSTRACT FROM AUTHOR]

In recent years, air pollution has become one of the main factors harming the livable environment for human beings. Governments have recognized the importance of controlling air pollution and reached a consensus that regional joint control of air pollution is an effective means of dealing with environmental degradation. In this work, we focus on the impact of fine particulate matter and nitrogen compounds on the air quality of 14 prefecture-level cities in China's Hunan Province using the insights of complex networks, and further propose a joint treatment scheme for these two pollutants. Multiscale temporal networks are constructed based on the height cross-correlation coefficient, which allows us to assess the variable network structures concerning different time scales. We use four network properties to assess the network structures for the pollutants. Through the Jensen-Shannon divergence of the probability distribution of these network attributes, it is found that NO2 affects AQI more in a short time interval than in a longer time interval. The correlation of both NO2 and PM2.5 among the 14 cities in about 15 days can best reflect the air quality in Hunan Province. In addition, instead of NO2, PM2.5 has become the culprit of air pollution in Hunan Province. The co-movement of the pollutants among the 14 cities is significant. The co-movement of the PM2.5 pollutants can last 45 days, while that of NO2 pollutants will gradually decrease over time. Furthermore, by using spectral clustering based on the network node correlation, we classify the 14 cities into five regions and two regions for PM2.5 and NO2, respectively. It provides a feasible implementation guide for the environmental governance of regional cooperation. [ABSTRACT FROM AUTHOR]

With rapid economic development, the problem of air pollution has become increasingly prominent. Countries have paid attention to PM2.5, one of the main air pollutants, and have gradually addressed this issue. Based on the 2015–2019 air quality data, meteorological data, and aerosol optical depth data from Harbin, China, this study investigated the relationship between PM2.5, a number of influencing factors, and their temporal changes using a machine-learning method. It can be seen from the analysis that the random forest model can predict PM2.5 concentration. In this model, the mean RH and AOD have a high impact on PM2.5 concentration, but there was negligent correlation with PM2.5. The results indicated that the level of PM2.5 pollution continuously decreased from 2015 to 2019, and there were significant seasonal differences in PM2.5 concentration and its variations. In 2019, due to the impact of heating and adverse meteorological conditions, PM2.5 pollution during the heating period increased significantly. This study provides theoretical and data support for the analysis of PM2.5 pollution in Harbin and formulation of air pollution control policies. [ABSTRACT FROM AUTHOR]

To date, research regarding the changes of the sulfur and nitrogen rates in Wuhan during the summer is limited. In this study, we analyzed the air quality in Wuhan, China, using water-soluble ion, gaseous precursor, and weather data. A Spearman correlation analysis was then performed to investigate the temporal changes in air quality characteristics and their driving factors to provide a reference for air pollution control in Wuhan. The results indicate that SO2 in the atmosphere at Wuhan undergoes secondary conversion and photo-oxidation, and the conversion degree of SO2 is higher than that of NO2. During the summers of 2016 and 2017, secondary inorganic atmospheric pollution was more severe than during other years. The fewest oxidation days occurred in summer 2020 (11 days), followed by the summers of 2017 and 2014 (25 and 27 days, respectively). During the study period, ion neutralization was the strongest in summer 2015 and the weakest in August 2020. The aerosols in Wuhan were mostly acidic and NH4+ was an important neutralizing component. The neutralization factors of all cations showed little change in 2015. K+, Mg2+, and Ca2+ level changes were the highest in 2017 and 2020. At low temperature, high humidity, and low wind speed conditions, SO2 and NO2 were more easily converted into SO42− and NO3−. [ABSTRACT FROM AUTHOR]

(1) Background: To better carry out air pollution control and to assist in accurate investigations of air pollution, in this study, we fully explore the spatial distribution characteristics of air pollution complaint results and provide guidance for air pollution control by combining regional air monitoring data. (2) Methods: By selecting the air pollution complaint information in Beijing from 2019 to 2020, in this study, we extract the names and addresses of complaint points, as well as the complaint times and types by adopting the BERT (bidirectional encoder representations from transformers) + CRF (conditional random field) model deep learning method. Moreover, through further filtering and processing of the complaint points' address information, we achieve address matching and spatial positioning of the complaint points, and realize the regional spatial representation of air pollution complaints in Beijing in the form of a heat map. (3) Results: The experimental results are compared and analyzed with the ranking data of total suspended particulate (TSP) concentration of townships (streets) in Beijing during the same period, indicating that the key areas of air pollution complaints have a high correlation with the key polluted township (street) areas. The distribution of complaints and the types of complaints in each township (street) differ according to the population density in each township (street), the level of education, and economic activity. (4) Conclusions: The results of this study show that the public, as the intuitive perceiver of air pollution, is sensitive to the air pollution situation at a smaller spatial scale; furthermore, complaints can provide guidance and reference for the direction of air pollution control and law enforcement investigations when coupled with geographical features and economic status. [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]

Air pollution has become a serious problem threatening human health. Effective prediction models can help reduce the adverse effects of air pollutants. Accurate predictions of air pollutant concentration can provide a scientific basis for air pollution prevention and control. However, the previous air pollution-related prediction models mainly processed air quality prediction, or the prediction of a single or two air pollutants. Meanwhile, the temporal and spatial characteristics and multiple factors of pollutants were not fully considered. Herein, we establish a deep learning model for an atmospheric pollutant memory network (LSTM) by both applying the one-dimensional multi-scale convolution kernel (ODMSCNN) and a long-short-term memory network (LSTM) on the basis of temporal and spatial characteristics. The temporal and spatial characteristics combine the respective advantages of CNN and LSTM networks. First, ODMSCNN is utilized to extract the temporal and spatial characteristics of air pollutant-related data to form a feature vector, and then the feature vector is input into the LSTM network to predict the concentration of air pollutants. The data set comes from the daily concentration data and hourly concentration data of six atmospheric pollutants (PM2.5, PM10, NO2, CO, O3, SO2) and 17 types of meteorological data in Xi'an. Daily concentration data prediction, hourly concentration data prediction, group data prediction and multi-factor prediction were used to verify the effectiveness of the model. In general, the air pollutant concentration prediction model based on ODMSCNN-LSTM shows a better prediction effect compared with multi-layer perceptron (MLP), CNN, and LSTM models. [ABSTRACT FROM AUTHOR]

Ambient air quality in the present-day Czech Republic (CR), one of the two succession countries of Czechoslovakia post-1993, was perceived as a major problem with severe human health and environmental consequences, particularly between the 1970s and 1990s [[1]]. Regional and Urban Background Ambient Air Pollution The ambient air concentrations from regional stations are important as reference sites, providing ambient air quality levels for comparison to impact areas, such as cities and industrial regions. Major air pollution problems are highlighted, main hotspots and air pollutants are indicated, and air pollution impacts on both human health and the environment are discussed. Low-Cost Air Quality Sensors With an ever-increasing need to control ambient air pollution in cities and industrial areas, we have recently witnessed a boom in demand for low-cost air quality sensors. [Extracted from the article]

Current European legislation aims to reduce the air pollutants emitted by European countries in the coming years. In this context, this article studies the effects on air quality of the measures considered for 2030 in the Spanish National Air Pollution Control Programme (NAPCP). Three different emission scenarios are investigated: a scenario with the emissions in 2016 and two other scenarios, one with existing measures in the current legislation (WEM2030) and another one considering the additional measures of NAPCP (WAM2030). Previous studies have addressed this issue at a national level, but this study assesses the impact at the street scale in three neighborhoods in Madrid, Spain. NO2 concentrations are modelled at high spatial resolution by means of a methodology based on computational fluid dynamic (CFD) simulations driven by mesoscale meteorological and air quality modelling. Spatial averages of annual mean NO2 concentrations are only estimated to be below 40 µg/m3 in all three neighborhoods for the WAM2030 emission scenarios. However, for two of the three neighborhoods, there are still zones (4–12% of the study areas) where the annual concentration is higher than 40 µg/m3. This highlights the importance of considering microscale simulations to assess the impacts of emission reduction measures on urban air quality. [ABSTRACT FROM AUTHOR]

In the period of 2005 to 2016, multiple air pollution control regulations have entered into effect in the United States at both the Federal and state level. In addition, economic changes have also occurred primarily in the electricity generation sector that substantially changed the emissions from this sector. This combination of policy implementations and economics has led to substantial reductions in PM2.5, its major constituents, and source specific PM2.5 concentrations across the New York State, particularly those of sulfate, nitrate, and primary organic carbon. However, secondary organic carbon and spark-ignition vehicular emission contributions have increased. Related studies of changes in health outcomes, the excess rates of emergency department visits and hospitalizations for a variety of cardiovascular and respiratory diseases and respiratory infections have increased per unit mass of PM2.5. It appears that the increased toxicity per unit mass was due to the reduction in low toxicity constituents such that the remaining mass had greater impacts on public health. [ABSTRACT FROM AUTHOR]

The lockdown during the coronavirus disease 2019 (COVID-19) pandemic provides a scarce opportunity to assess the efficiency of air pollution mitigation. Herein, the monitoring data of air pollutants were thoroughly analyzed together with meteorological parameters to explore the impact of human activity on the multi-time scale changes of air pollutant concentrations in Guiyang city, located in Southwest China. The results show that the COVID-19 lockdown had different effects on the criteria air pollutants, i.e., PM2.5 (diameter ≤ 2.5 μm), PM10 (diameter ≤ 10 μm), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) concentrations. The lockdown caused a significant drop in NO2 concentration. During the first-level lockdown period, the NO2 concentration declined sharply by 8.41 μg·m−3 (45.68%). The decrease in NO concentration caused the "titration effect" to weaken, leading to a sharp increase in O3 concentration. Although human activities resumed partially and the "titration effect" enhanced certainly during the second-level lockdown period, the meteorological conditions became more conducive to the formation of O3 by photochemical reactions. Atmosphere oxidation was enhanced to promote the generation of secondary aerosols through gas–particle transitions, thus compensating for the reduced primary emission of PM2.5. The implication of this study is that the appropriate air pollution control policies must be initiated to suppress the secondary generation of both PM2.5 and O3. [ABSTRACT FROM AUTHOR]

This study assessed the spatial disposition of air pollutants and their relationship with meteorological parameters in urban slum settlements of Lagos city. The gaseous pollutants were quantified using a gas analyzer, and the PM2.5 concentration and meteorological parameters were determined using an Air Metric Sampler and Wind Mate, respectively. SPSS for Windows and ArcGIS were used for data analysis. The results revealed that the seasonal variations in SO2, NO2, CO2, and PM2.5 showed a higher level of air pollutant concentration during the dry season than during the wet season. During the wet season, a significant correlation was observed between PM2.5 and temperature at the 1% level (0.957 **), and VOC and SO2 (0.907 *) at the 5% level; during the dry season, significant correlations were observed between NO2 and SO2 at the 1% level (0.9477 **), and PM2.5 and relative humidity (0.832 *) at the 5% level. Atmospheric pressure (72%), temperature (60%), and relative humidity (98.4) were the primary meteorological factors affecting air pollutants such as VOC, CO2, and SO2. The spatial dispersal of air pollutants revealed a high Z score and a moderate p-value, indicating hot spot locations throughout the five selected slum settlements. It is recommended that regular monitoring based on quantifiable economic costs that are beneficial to the well-being of the populace be investigated, and policy-based initiatives for air pollution control based on scientific evidence be advocated for. [ABSTRACT FROM AUTHOR]

As cities are growing in size and complexity, the estimation of air pollution exposure requires a detailed spatial representation of air pollution levels, rather than homogenous fields, provided by global- or regional-scale models. A critical input for city-scale modeling is a timely and spatially resolved emission inventory. Bottom–up approaches to create urban-scale emission inventories can be a demanding and time-consuming task, whereas local emission rates derived from a top–down approach may lack accuracy. In the frame of this study, the UrbEm approach of downscaling gridded emission inventories is developed, investing upon existing, open access, and credible emission data sources. As a proof-of-concept, the regional anthropogenic emissions by Copernicus Atmospheric Monitoring Service (CAMS) are handled with a top–down approach, creating an added-value product of anthropogenic emissions of trace gases and particulate matter for any city (or area) of Europe, at the desired spatial resolution down to 1 km. The disaggregation is based on contemporary proxies for the European area (e.g., Global Human Settlement population data, Urban Atlas 2012, Corine, OpenStreetMap data). The UrbEm approach is realized as a fully automated software tool to produce a detailed mapping of industrial (point), (road-) transport (line), and residential/agricultural/other (area) emission sources. Line sources are of particular value for air quality studies at the urban scale, as they enable explicit treatment of line sources by models capturing among others the street canyon effect and offer an overall better representation of the critical road transport sector. The UrbEm approach is an efficient solution for such studies and constitutes a fully credible option in case high-resolution emission inventories do not exist for a city (or area) of interest. The validity of UrbEm is examined through the evaluation of high-resolution air pollution predictions over Athens and Hamburg against in situ measurements. In addition to a better spatial representation of emission sources and especially hotspots, the air quality modeling results show that UrbEm outputs, when compared to a uniform spatial disaggregation, have an impact on NO2 predictions up to 70% for urban regions with complex topographies, which corresponds to a big improvement of model accuracy (FAC2 > 0.5), especially at the source-impacted sites. [ABSTRACT FROM AUTHOR]

The combined use of Lecce-University AERONET-photometer measurements and PM2.5, PM10, NO2, CO, and SO2 concentrations from different sites of Apulia-Region Air-Quality Agency represents the peculiarity of this study, which evaluates the impact of COVID-19 lockdown (LD) measures on aerosol and gaseous pollutants. Monthly-averaged columnar and surface parameters of the 2020-year were compared with corresponding monthly parameters of the ref-year obtained by averaging 2017, 2018, and 2019 measurements in order to evaluate LD measure impacts by Average Percent Departure (APD%). Photometer measurements showed that LD measures were likely responsible for the decrease in Aerosol Optical Depth (AOD). The APD% estimated between the 2020- and ref-year AOD (at 440 nm) was characterized by negative values from June to August, reaching the smallest mean value (−46%) in June. Moreover, the columnar aerosol load appeared less affected by continental urban/industrial particles than previous years in the summer of 2020. The PM-concentration-APD% calculated at ten sites was characterized by monthly trends similar to those of AOD-APD%. PM-APD% values varied from site to site and smaller values (up to −57% in June) were on average detected at urban/suburban sites than at background sites (up to −37%). The impact of LD measures on gaseous pollutants was observed from the onset of LD. [ABSTRACT FROM AUTHOR]

Due to rapid urbanization and socio-economic development, fine particulate matter (PM2.5) pollution has drawn very wide concern, especially in the Beijing–Tianjin–Hebei region, as well as in its surrounding areas. Different socio-economic developments shape the unique characteristics of each city, which may contribute to the spatial heterogeneity of pollution levels. Based on ground fine particulate matter (PM2.5) monitoring data and socioeconomic panel data from 2015 to 2019, the Beijing–Tianjin–Hebei region, and its surrounding provinces, were selected as a case study area to explore the spatio-temporal heterogeneity of PM2.5 pollution, and the driving effect of socioeconomic factors on local air pollution. The spatio-temporal heterogeneity analysis showed that PM2.5 concentration in the study area expressed a downward trend from 2015 to 2019. Specifically, the concentration in Beijing–Tianjin–Hebei and Henan Province had decreased, but in Shanxi Province and Shandong Province, the concentration showed an inverted U-shaped and U-shaped variation trend, respectively. From the perspective of spatial distribution, PM2.5 concentrations in the study area had an obvious spatial positive correlation, with agglomeration characteristics of "high–high" and "low–low". The high-value area was mainly distributed in the junction area of Henan, Shandong, and Hebei Provinces, which had been gradually moving to the southwest. The low values were mainly concentrated in the northern parts of Shanxi and Hebei Provinces, and the eastern part of Shandong Province. The results of the spatial lag model showed that Total Population (POP), Proportion of Urban Population (UP), Output of Second Industry (SI), and Roads Density (RD) had positive driving effects on PM2.5 concentration, which were opposite of the Gross Domestic Product (GDP). In addition, the spatial spillover effect of the PM2.5 concentrations in surrounding areas has a positive driving effect on local pollution levels. Although the PM2.5 levels in the study area have been decreasing, air pollution is still a serious problem. In the future, studies on the spatial and temporal heterogeneity of PM2.5 caused by unbalanced social development will help to better understand the interaction between urban development and environmental stress. These findings can contribute to the development of effective policies to mitigate and reduce PM2.5 pollutions from a socio-economic perspective. [ABSTRACT FROM AUTHOR]

Ambient air pollution is a major environmental threat to human health. The acute effects of exposure to ambient air pollution during physical exercise may depend on allergy status. The aim of the study was to assess the acute respiratory responses to air pollution exposure during physical training in young adults with and without allergies. The studied group included 71 healthy young adults (n = 16 with allergy and n = 55 without allergy). Students completed two indoor physical training trials lasting 45–60 min: when air pollutants concentrations were high (exposure trial) and low (control trial). During each trial, we monitored outdoor and indoor environmental conditions. Participants performed spirometry at baseline and directly after the exercise. Exercise during exposure trials led to a small decrease in the percentage of predicted forced expiratory volume in 1 s (FEV1 ref). Only during the control trials did the FEV1/forced vital capacity quotient (FEV1/FVC) statistically significantly increase. Moreover, just in the allergy group, there were statistically significant negative correlations between post-exercise FEV1/FVC change and 3 h average outdoor particulate matter with aerodynamic diameter <10 µm (PM10) and nitrogen dioxide (NO2) concentrations (PM10: r = −0.54, p = 0.02, NO2: r = −0.60, p = 0.02). In young and healthy adults, sports training under exposure to high levels of ambient air pollutants leads to a small decrease in FEV1. The allergy might be a modifying factor in the respiratory responses to air pollution. Post-exercise decrease in FEV1/FVC was related to pre-exercise 3 h averages of PM10 and NO2 only in people with ever-diagnosed upper-respiratory allergy. [ABSTRACT FROM AUTHOR]

With the continuous progress of air pollution prevention and control in China, the study of the emission characteristics of vehicles has become increasingly important. An in situ experiment was performed in the Tianfu tunnel in Chengdu to determine the vehicle emissions of volatile organic compounds (VOCs). A total of 50 species of VOCs were quantified in the tunnel, with total concentrations in the range of 32.25–162.18 ppbv in the entrance and 52.90–233.92 ppbv in the exit, respectively. Alkanes were the most abundant group, followed by alkenes, aromatic hydrocarbons, oxygenated VOCs, alkynes and chlorocarbons. The general emission factors of the measured VOCs ranged from 141.71 mg veh−1 km−1 to 236.12 mg veh−1 km−1, and the average ± std was 177.31 ± 24.59 mg veh−1 km−1. The emission factors of diesel-fuelled vehicles, gasoline-fuelled vehicles and natural gas-fuelled vehicles were estimated based on linear regression analysis, with values of 272.39 ± 191.17 mg veh−1 km−1, 185.08 ± 12.85 mg veh−1 km−1 and 158.72 ± 3.21 mg veh−1 km−1, respectively. The results of roadside experiments indicate that the roadside ambience atmosphere contains many species characterized with vehicle emission features. Especially, there were fuel evaporation emission related substances, which were higher in content than tunnel samples. [ABSTRACT FROM AUTHOR]

Air pollution is the primary environmental cause of death globally. To improve air quality and reduce health impacts, the National Emission Ceilings Directive requires Member States of the European Union to provide National Air Pollution Control Programmes, including emission reduction measures aimed to achieve binding commitments for the years 2020 and 2030. Integrated assessment models are pivotal to assess the reduction of pollutants concentrations determined by measures implemented or foreseen for emission reduction. Here we discuss scenarios elaborated for year 2030 in the Italian National Air Pollution Control Programme, considering 2010 as reference year. The two scenarios, "With Measures" and "With Additional Measures", show a significant reduction of the pollutants concentration, namely PM2.5, NO2 and O3. The scenarios are here also used to provide an integrated approach for calculating the effect of the program on health impacts (mortality) and related costs. Avoidable attributable cases and associated costs are here reported at both the national and regional level and provide a significant framework to assess air-pollution reduction measures with an integrated approach. The procedure proposed may be therefore further developed and applied to assess the overall positive benefits (environmental, health and economic) determined by air-pollution control plans or other integrated policies targeting air quality, energy and climate goals. [ABSTRACT FROM AUTHOR]

The PM10 concentrations in the studied region (Ostravsko-karvinská agglomeration, Czech Republic) exceed air pollution limit values in the long-term and pose a significant problem for human health, quality of life and the environment. In order to characterize the pollution in the region and identify the pollution origin, Instrumental Neutron Activation Analysis (INAA) was employed for determination of 34 elements in PM10 samples collected at a height of 90 m above ground level. From April 2018 to March 2019, 111 PM10 samples from eight basic wind directions and calm and two smog situations were sampled. The elemental composition significantly varied depending on season and sampling conditions. The contribution of three important industrial sources (iron and steelworks, cement works) was identified, and the long-range cross-border transport representing the pollution from the Polish domestic boilers confirmed the most important pollution inflow during the winter season. [ABSTRACT FROM AUTHOR]

Air pollution causes more damage to health and economy than previously understood, contributing to approximately one in six deaths globally. However, pollution reduction policies remain controversial even when proven effective and cost negative, partially because of misunderstanding and growing mistrust in science. We used an expert assessment to bridge these research–policy divides in the State of Utah, USA, combining quantitative estimates from 23 local researchers and specialists on the human health and economic costs of air pollution. Experts estimated that air pollution in Utah causes 2480 to 8000 premature deaths annually (90% confidence interval) and decreases the median life expectancy by 1.1 to 3.6 years. Economic costs of air pollution in Utah totaled $0.75 to $3.3 billion annually, up to 1.7% of the state's gross domestic product. Though these results were generally in line with available estimates from downscaled national studies, they were met with surprise in the state legislature, where there had been an almost complete absence of quantitative health and economic cost estimates. We discuss the legislative and personal responses of Utah policy makers to these results and present a framework for increasing the assimilation of data into decision making via regional expert assessment. In conclusion, combining quantitative assessments from local experts is a responsive and cost-effective tool to increase trust and information uptake during time-sensitive policy windows. [ABSTRACT FROM AUTHOR]

Ambient air pollution is one of eight global risk factors for deaths and accounts for 38.44 all causes death rates attributable to ambient PM pollution, while in Bosnia and Herzegovina, it is 58.37. We have estimated health endpoints and possible gains if two policy scenarios were implemented and air pollution reduction achieved. Real-world health and recorded PM pollution data for 2018 were used for assessing the health impacts and possible gains. Calculations were performed with WHO AirQ+ software against two scenarios with cut-off levels at country-legal values and WHO air quality recommendations. Ambient PM2.5 pollution is responsible for 16.20% and 22.77% of all-cause mortality among adults in Tuzla and Lukavac, respectively. Our data show that life expectancy could increase by 2.1 and 2.4 years for those cities. In the pollution hotspots, in reality, there is a wide gap in what is observed and the implementation of the legally binding air quality limit values and, thus, adverse health effects. Considerable health gains and life expectancy are possible if legal or health scenarios in polluted cities were achieved. This estimate might be useful in providing additional health burden evidence as a key component for a clean air policy and action plans. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM2.5) pollution has been a major concerning issue in China, and many cities have developed emergency plans for heavy air pollution. The aim of this study is to delimitate PM2.5 pollution regions of Xianyang, which is very important to the regional environmental prevention and control. The result showed that PM2.5 air pollution had significant cross-administrative characteristics in Xianyang. Using spatial clustering algorithm under adjacent matrix constrain, this study classified the air quality monitoring sites into two clusters. For each monitoring site, we generated Voronoi polygons and ultimately Xianyang was delimitated into two regions, south and north. The air pollution of the southern region was more serious with 64 days of heavy and severe pollution since 2018, while the northern region had only 10 days. The southern region consisted of four complete administrative districts and parts of three administrative districts. While the northern region consisted of six complete administrative districts and parts of three administrative districts. Visualization of the spatiotemporal characteristics of the PM2.5 air pollution in the two regions further illustrated the significant difference. We suggest when heavy pollution happens, the two regions should be considered separately. If the southern region is heavily polluted while the northern region not, only the southern region needs to implement the emergency plan to minimize the damage to society and economy. Seventy-five percent of the city area, 2.3 million people, 59% of schools, and 43% of GDP would not be impacted if air pollution was controlled by region separately. The sensitive analysis shows that clustering result is robust against different pollution degree and missing values. [ABSTRACT FROM AUTHOR]

Atmospheric aerosol pollution has significant impacts on human health and economic society. One of the most efficient way to remove the pollutants from the atmosphere is wet deposition. This study selected three typical atmospheric pollution regions in China, the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD) and the Pearl River Delta (PRD) regions, as research areas, and used the hourly precipitation and PM2.5 mass concentration data from 2015 to 2017 to investigate the removal impacts of precipitation on PM2.5. The PM2.5 mass concentration difference before and after the hourly precipitation events was used to denote as the impacts of precipitation. Hourly precipitation event was selected so that the time difference between two PM2.5 observations was short enough to limit the PM2.5 change caused by other factors. This study focused on the differences in the removal effect of precipitation on PM2.5 under different precipitation intensities and pollution levels. The results show that both precipitation intensity and aerosol amount affected the removal effect. A negative removal effect existed for both light precipitation and low PM2.5 mass concentration conditions. In contrast, a positive removal effect occurred for both high precipitation and high PM2.5 mass concentration conditions. The removal effect increased with increasing precipitation intensity and PM2.5 mass concentration before precipitation and was consistent with the change trend of wind speed at a height of 100 m. The findings of this study can help understand the mechanism of wet scavenging on air pollution, providing support for air pollution control in future. [ABSTRACT FROM AUTHOR]

This study assesses changes since 1980 in the maintenance cost of the façades of the historical 17th to 19th century buildings of the Oslo Quadrature, Norway, due to atmospheric chemical wear, including the influence of air pollution. Bottom up estimations by exposure–response functions for an SO2 dominated situation reported in the literature for 1979 and 1995 were compared with calculations for the present (2002–2014) multi-pollutant situation. The present maintenance cost, relative to the total façade area, due to atmospheric wear and soiling was found to be about 1.6 Euro/m2 per year. The exposure to local air pollution, mainly particulate matter and NOx gases, contributed to 0.6 Euro/m2 (38%), of which the cost due to wear of renderings was about 0.4 Euro/m2 (22%), that due to the cleaning of glass was 0.2 Euro/m2 (11%), and that due to wear of other façade materials was 0.07 Euro/m2 (5%). The maintenance cost due to the atmospheric wear was found to be about 3.5%, and that due to the local air pollution about 1.1% of the total municipal building maintenance costs. The present (2002–2014) maintenance costs, relative to the areas of the specific materials, due to atmospheric wear are probably the highest for painted steel surfaces, about 8–10 Euro/m2, then about 2 Euro/m2 for façade cleaning and the maintenance of rendering, and down to 0.3 Euro/m2 for the maintenance of copper roofs. These costs should be adjusted with the importance of the wear relative to other reasons for the façade maintenance. [ABSTRACT FROM AUTHOR]