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This paper looks at the relationship between enterprise size and pollution abatement costs using firm-level datasets in China, where size-dependent distortions may exist in the distribution of enterprises of different sizes. We find that the pollution abatement costs decrease with enterprise size. Compared to the smallest size, the magnitudes of marginal decreases in pollution abatement costs per 1000 CNY of industrial output in the largest size are 3.29 CNY, 0.54 CNY and 2.60 CNY for gas, SO 2 and dust, respectively. Moreover, we further explore the potential mechanisms for the decrease of pollution abatement costs from three perspectives: environmental protection-related investment, regulation intensity, and technological capability. Our findings suggest that the decrease in the intensity of environmental protection-related investment for large enterprises may be directly reduce the intensity of pollution abatement costs. Although large enterprises have low intensity of pollution abatement costs, this does not mean that they are subject to weaker environmental regulation. More importantly, we find that large enterprises may have more adoption of abatement technologies. For SO 2 and dust, the pollutant removal efficiency of the largest enterprises is 4.92% and 1.82% higher than that of the smallest enterprises, respectively. Our results are robust to different specifications. These findings help us enact appropriate policies for enterprises based on their size, thereby improving the efficacy of pollution abatement and achieving the optimal level of pollution abatement for the entire society., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The health effects of air pollution remain a public concern worldwide. Using data from the Global Burden of Disease 2019 report, we statistically analyzed total mortality, disability-adjusted life years (DALY), and years of life lost (YLL) attributable to air pollution in eight East African countries between 1990 and 2019. We acquired ambient ozone (O 3 ), PM 2.5 concentrations and household air pollution (HAP) from the solid fuel from the State of Global Air report. The multilinear regression model was used to evaluate the predictability of YLLs by the air pollutants. We estimated the ratio rate for each health burden attributable to air pollution to compare the country's efforts in the reduction of air pollution health burden. This study found that the total number of deaths attributable to air pollution decreased by 14.26% for 30 years. The drop came from the reduction of 43.09% in mortality related to Lower Respiratory tract Infection (LRI). However, only five out of eight countries managed to decrease the total number of deaths attributable to air pollution with the highest decrease observed in Ethiopia (40.90%) and the highest increase in Somalia (67.49%). The linear regression model showed that HAP is the pollutant of the most concern in the region, with a 1% increase in HAP resulting in a 31.06% increase in regional YLL (R 2  = 0.93; p < 0.05). With the increasing ground-level ozone, accompanied by the lack of adequate measures to reduce particulate pollutants, the health burdens attributable to air pollution are still a threat in the region., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Extreme PM 2.5 pollution has become a significant environmental problem in China in recent years, which is hazardous to human health and daily life. Noticing the importance of investigating the causes of extreme PM 2.5 pollution, this paper classifies cities across China into eight categories (four groups plus two scenarios) based on the generalized extreme value (GEV) distribution using hourly station-level PM 2.5 concentration data, and a series of multi-choice models are employed to assess the probabilities that cities fall into different categories. Various factors such as precursor pollutants and socio-economic factors are considered after controlling for meteorological conditions in each model. It turns out that SO 2 concentration, NO 2 concentration, and population density are the top three factors contributing most to the log ratios. Moreover, in both left- and right-skewed cases, the influence of a one-unit increase of SO 2 concentration on the relative probability of cities falling into different groups shows an increasing trend, while those of NO 2 concentration show a decreasing trend. At the same time, the higher the extreme pollution level, the bigger the effect of SO 2 and NO 2 concentrations on the probability of cities falling into normalized scenarios. The multivariate logit model is used for prediction and policy simulations. In summary, by analyzing the influences of various factors and the heterogeneity of their influence patterns, this paper provides valuable insights in formulating effective emission reduction policies., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

In China, despite the fact that the atmospheric environment quality has continued to improve in recent years, the PM 2.5 pollution still had not been controlled fundamentally and its driving mechanism was complex which remained to be explored. Based on the 1-km ground-level PM 2.5 datasets of China from 2000 to 2020, this study combined spatial autocorrelation, trend analysis, geographical detector, and multi-scale geographically weighted regression (MGWR) model to explore the spatial-temporal evolution of PM 2.5 in Shanxi Province and revealed its complex driving mechanism behind this process. The results reflected that (1) there was a pronounced spatial clustering of PM 2.5 concentration within Shanxi Province, with PM 2.5 concentrations decreasing from southwest to northeast. From 2000 to 2020, the levels of PM 2.5 pollution demonstrated a decline over time, with its concentrations decreasing by 9.15 µg/m 3 overall. The Hurst exponent indicated a projected decrease in PM 2.5 concentrations in the central and northern areas of Shanxi Province, contrasting with an anticipated increase in other regions. (2) The geographical detector indicated that all drivers had significant influences on PM 2.5 concentrations, with meteorological factors exerting the greatest effects then followed by human activity and vegetation cover showing the least effects. (3) Both gross domestic product and population density exhibited positive correlations with PM 2.5 concentration, while vegetation fractional cover, wind speed, precipitation, and elevation exerted negative influences on PM 2.5 concentration all over the space. This study enriched the research content and ideas on the driving mechanism of PM 2.5 and provided a reference for similar studies., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Adıyaman, a city recently affected by an earthquake, is facing significant air pollution challenges due to both anthropogenic activities and natural events. The sources of air pollution have been investigated using meteorological variables. Elevated southerly winds, especially prominent in spring and autumn, significantly contribute to dust transport, leading to a decline in local air quality as detected by the HYSPLIT model. Furthermore, using Suomi-NPP Thermal Anomaly satellite product, it is detected and analyzed for crop burning activities. Agricultural practices, including stubble burning, contribute to the exacerbation of PM 10 pollution during the summer months, particularly when coupled with winds from all directions except the north. In fall and winter months, heating is identified as the primary cause of pollution. The city center located north of the station is the dominant source of pollution throughout all seasons. The study established the connection between air pollutants and meteorological variables. Furthermore, the Spearman correlation coefficients reveal associations between PM 10 and SO 2 , indicating moderate positive correlations under pressure conditions (r = 0.35, 0.52). Conversely, a negative correlation is observed with windspeed (r = -0.35, -0.50), and temperature also exhibits a negative correlation (r = -0.39, -0.54). During atmospheric conditions with high pressure, PM 10 and SO 2 concentrations are respectively 41.2% and 117.2% higher. Furthermore, pollutant concentration levels are 29.2% and 53.3% higher on days with low winds. Last, practical strategies for mitigating air pollution have been thoroughly discussed and proposed. It is imperative that decision-makers engaged in city planning and renovation give careful consideration to the profound impact of air pollution on both public health and the environment, particularly in the aftermath of a recent major earthquake., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The aim of this study was to investigate the associations between cardiorespiratory fitness (CRF), long-term air pollution exposure and biochemical markers of oxidative status and inflammation. This is a cross-sectional investigation focusing on biochemical markers of oxidative status and inflammation. Participants were Caucasian (N = 1188; age 18-65 years) who lived for at least 5 years in a high air-polluted (Moravian-Silesian; MS) or low air-polluted (South Bohemia; SB) region of the Czech Republic. Healthy runners and inactive individuals were recruited. A multiple regression analysis was used to explain the relationship between multiple independent variables (CRF, trunk fat mass, sex, socioeconomic status, and region (MS region vs. SB region) and dependent variables (oxidative status, inflammation). CRF, trunk fat mass, age and sex significantly predicted almost all selected markers of oxidative status and inflammation (except GSSG, GSH/GSSG and BDNF). Participants living in the MS region presented significantly higher GPx (by 3.1%) and lower BDNF values (by 4.5%). All other investigated biochemical markers were not significantly influenced by region. We did not find meaningful interactions between long-term air-pollution exposure versus markers of oxidative status and inflammation. However, we showed various significant interactions with sex, age, CRF and body composition. The significant association of living in the high air polluted MS region with the BDNF level warrants further attention., (© 2024. The Author(s).)

In this study, the levels of sulfur dioxide (SO 2 ) and nitrogen dioxide (NO 2 ) were measured indoors and outdoors using passive samplers in Tymar village (20 homes), an industrial area, and Haji Wsu (15 homes), a non-industrial region, in the summer and the winter seasons. In comparison to Haji Wsu village, the results showed that Tymar village had higher and more significant mean SO 2 and NO 2 concentrations indoors and outdoors throughout both the summer and winter seasons. The mean outdoor concentration of SO 2 was the highest in summer, while the mean indoor NO 2 concentration was the highest in winter in both areas. The ratio of NO 2 indoors to outdoors was larger than one throughout the winter at both sites. Additionally, the performance of machine learning (ML) approaches: multiple linear regression (MLR), artificial neural network (ANN), and random forest (RF) were compared in predicting indoor SO 2 concentrations in both the industrial and non-industrial areas. Factor analysis (FA) was conducted on different indoor and outdoor meteorological and air quality parameters, and the resulting factors were employed as inputs to train the models. Cross-validation was applied to ensure reliable and robust model evaluation. RF showed the best predictive ability in the prediction of indoor SO 2 for the training set (RMSE = 2.108, MAE = 1.780, and R 2 = 0.956) and for the unseen test set (RMSE = 4.469, MAE = 3.728, and R 2 = 0.779) values compared to other studied models. As a result, it was observed that the RF model could successfully approach the nonlinear relationship between indoor SO 2 and input parameters and provide valuable insights to reduce exposure to this harmful pollutant., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Tropospheric ozone is an air pollutant at the ground level and a greenhouse gas which significantly contributes to the global warming. Strong anthropogenic emissions in and around urban environments enhance surface ozone pollution impacting the human health and vegetation adversely. However, observations are often scarce and the factors driving ozone variability remain uncertain in the developing regions of the world. In this regard, here, we conducted machine learning (ML) simulations of ozone variability and comprehensively examined the governing factors over a major urban environment (Ahmedabad) in western India. Ozone precursors (NO 2 , NO, CO, C 5 H 8 and CH 2 O) from the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis and meteorological parameters from the ERA5 (European Centre for Medium-Range Weather Forecast's (ECMWF) fifth-generation reanalysis) were included as features in the ML models. Automated ML (AutoML) fitted the deep learning model optimally and simulated the daily ozone with root mean square error (RMSE) of ~2 ppbv reproducing 84-88% of variability. The model performance achieved here is comparable to widely used ML models (RF-Random Forest and XGBoost-eXtreme Gradient Boosting). Explainability of the models is discussed through different schemes of feature importance, including SAGE (Shapley Additive Global importancE) and permutation importance. The leading features are found to be different from different feature importance schemes. We show that urban ozone could be simulated well (RMSE = 2.5 ppbv and R 2  = 0.78) by considering first four leading features, from different schemes, which are consistent with ozone photochemistry. Our study underscores the need to conduct science-informed analysis of feature importance from multiple schemes to infer the roles of input variables in ozone variability. AutoML-based studies, exploiting potentials of long-term observations, can strongly complement the conventional chemistry-transport modelling and can also help in accurate simulation and forecast of urban ozone., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The goal of the current study is to evaluate the heavy metal rainfall contamination in the vicinity brought on by the Erbil Steel Factory in Iraq during the study period. The study's findings revealed the concentration of all studied heavy metals in the precipitation near and around the factory is significantly higher than that of the rural area of Barzan village which is used as a control site. The average concentration of the metals is in descending order manganese (Mn) > lead (Pb) > iron (Fe) > arsenic (As) > cobalt (Co) > selenium (Se) > mercury (Hg) > and cadmium (Cd) for the polluted site. The geo-accumulation index (I-geo) of the heavy metal Mn in the rainfall around the steel factory site is 6.28 > 5 which indicates extreme contamination. While the Igeo values of Cd, As, and Fe are 4.87, 4.54, and 4.04 > 4 that indicate heavy to extreme contamination, for Pb, 3.80 > 3 indicates moderate to heavy contamination, Cd 1.68 > 1 indicates moderate contamination, Hg 0.46 > 0 indicates uncontaminated to moderate contamination, and Se - 0.36 < 0 indicates uncontaminated. The pollution load index (PLI) of the rainwater around the steel factory site is 13.46 > 1, demonstrating that the area is highly metal-contaminated., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Aerosolized microorganisms have become an important factor in assessing air quality. To determine the characteristics of bacterial bioaerosols in air and rainwater, as well as calculate the recovery rate of bacteria after rains in Ho Chi Minh City, our study was performed using the SKC Biostage sampler for airborne bacteria and Plate Count Agar (PCA) medium for bacterial concentration. Subsequently, the study determined the bacterial community composition at the phylum and order levels using the 16S rRNA (16S metabarcoding) method. Before the rain, bacterial concentrations in the air ranged from 263.39 ± 21.00 to 277.39 ± 78.99 CFU/m 3 , and in rainwater 264.89 ± 51.17 to 285.72 ± 28.00 CFU/m 3 . Following rains, the bacterial concentrations decreased to their lowest levels within the first 1-2 h and gradually increased thereafter, reaching their peak after 9 h for heavy rain and after 12 h for light and moderate rains. The bacterial bioaerosols recovery rate was determined to be 100% for light and moderate rains and 94.6% for heavy rain. The change in bacterial concentration after rainfall showed a positive correlation with temperature (r = 0.85) and CO 2 concentration (r = 0.70) and a negative correlation with relative humidity (r =  - 0.79). Bacterial composition analysis revealed that the Actinobacteria, Firmicutes, and Proteobacteria phyla were dominant and characteristic of the humid tropical climate in Vietnam. Notably, Firmicutes were the most prevalent phylum both before and after rains. The increased prevalence of certain bacterial orders, particularly Staphylococcus, could contribute to the spread of pathogens, particularly foodborne pathogens. In addition to rain, relative humidity contributed to reducing bacterial bioaerosols concentration and their recovery rate after the rain., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: While economics is growing in Indonesia, its Happiness Index remains steady. Regarding the average concentration of dissolved particles, Indonesia is ranked sixth globally. Many factors can affect happiness. Environmental conditions, especially air quality, are considered to influence individual happiness. Therefore, this research investigates the impact of air quality and health on happiness., Methods: Data used in this study is the microdata of Indonesia's Happiness Survey (SPTK) in 2021. With more than 70,000 respondents, the study uses Ordered Probit as an analysis method with subjective happiness as the dependent variable. The independent variables used in this study are air quality, age, gender, housing area per capita, marital status, and health status. All independent variables except age are categorical. The variable of interest, air quality, is coded "1" if the IKU achieves the Strategic Plan's target of 84.2 and "0" otherwise. IKU is a regional air quality index that combines two substances., Results: At a significance level of 5%, there is a positive relationship between subjective happiness and air quality. In other words, if air quality (IKU) meets the Strategic Plan target (≥ 84.2), then a person is more likely to have a higher level of happiness. It can be explained more with the marginal effect. The marginal effect concludes that if the target is achieved, the probability of having a lower level of happiness decreases by up to 2.8%, and a very high level of happiness rises by 5.1%. Regarding health status, the rarer someone gets sick, the happier she/he is., Conclusion: The study finds that air pollution could lower happiness, while better health increases happiness. Therefore, it is important to meet the target of IKU and to improve public health. Some good practices can be adopted to achieve this goal., (© 2024. The Author(s).)

The aim of this paper is to investigate the effectiveness of combining mobile technologies and sensors to detect harmful particles in the air and address the problem of air pollution caused by traffic and exhaust emissions. The paper contains a systematic literature review of information technology research related to pollution detection in order to point out the main obstacles in the field and propose solutions. Furthermore, the paper presents the development of an Android smartphone-based real-time monitoring system that utilizes an external analog sensor board to acquire and evaluate physical measurements. The proposed system is calibrated for CO gas measurements, and it is compared with a commercial gas analyzer instrument. Results imply that the developed system is capable of detecting concentration levels in the air and that the accuracy is within the range of the industrial device's accuracy. [ABSTRACT FROM AUTHOR]

Pollution of air, water, and soil is a pressing global issue with significant implications for environmental and human health. This research paper explores the various methods and technologies employed for the monitoring and remediation of pollutants in these three crucial environmental compartments. It discusses the challenges associated with pollution, the importance of effective monitoring, and the diverse strategies available for pollutant remediation. By synthesizing current research and technologies, this paper aims to provide insights into the state-of-the-art approaches for addressing pollution and promoting environmental sustainability [ABSTRACT FROM AUTHOR]

As a key project of China's western development, the West-East Natural Gas Transmission Project (WENGT) has effectively alleviated China's uneven energy distribution and supply-demand issues. It has promoted the optimization of China's energy structure and sustainable development in the new era, helping to achieve the goal of "double carbon". Based on pollution data from Chinese industrial enterprises from 2000 to 2012, this paper analyzes the impact of the West-East Natural Gas Pipeline Project on the air pollution emissions of industrial enterprises using a difference-in-difference model and explores the moderating role of local government environmental regulations. The findings indicate that the project significantly reduced air pollutant emissions from industrial enterprises in cities along the route, with a more pronounced reduction effect in areas with higher environmental regulation intensity. Additionally, the emission reduction effect varied among different types of enterprises and regions, with private enterprises showing the smallest reduction impact and the eastern coastal region exhibiting the most significant effect. This paper delves into the relationship between sustainable cross-regional energy development and air pollution emissions from industrial enterprises, providing a theoretical basis for energy conservation and emission reduction policies in China. [ABSTRACT FROM AUTHOR]

This study aimed at investigating the harm from ecosystem services (ESs) according to agricultural land conversion (ALC) by using meta-analysis. The results of meta-regression showed that spatiotemporal effects had significant influences on some ES losses, and the maximum spatial impacts were relevant to Asia and Europe. Moreover, the results of ALC rate coefficients in meta-regression indicated that three large losses of ES were related to soil erosion (0.314), air pollution (0.202), and climate change (0.161). Therefore, the ALC should be done at a suitable conversion rate to reduce ES losses. Accordingly, administrators are suggested to consider careful research planning for the ALC in the process of economic development. Other strategies highlighted the importance of ALC–ES interactions for human well-being, such as measuring the pricing of goods and services based on land resources, continuously monitoring illegal ALC, and imposing taxes on unplanned ALC. [ABSTRACT FROM AUTHOR]

This systematic review assessed to evaluate the potential correlation between oral health and air pollution. To the best of the authors' knowledge, this is the first systematic review endeavoring to compare air pollution and oral health. A systematic search was performed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) statement and employed the PICO(S) approach (Patient or Population, Intervention, Control or Comparison, Outcome, and Study types). The search was limited to English-language articles, and publications within a 15-year timeframe were included in the electronic search. A comprehensive search was conducted across PubMed, Scopus, Embase, and Web of Science databases, spanning the years 2008 to 2023, resulting in a total of 4983 scientific articles. A final selection of 11 scientific papers was made based on their study type and the specific air pollutants examined. The selected papers analyzed various air pollutants associated with health-related diseases, including Ozone, Nitrogen Dioxide, Nitrogen Monoxide, Carbon Monoxide, sulfur dioxide, and particulate matter. Three out of eleven of the reviewed studies assert a strong correlation between air pollutants and oral diseases, specifically periodontitis. However, the exact biological mechanisms underlying this correlation do not seem to be fully understood, indicating the need for further comprehensive investigation in this regard. Dentists can contribute to the collective effort by educating their patients about the oral health implications of air pollution, thereby supporting initiatives aimed at promoting environmental and health sustainability. [ABSTRACT FROM AUTHOR]

Air pollution is a growing concern due to severe threats to public health and the environment. The need for reliable air quality monitoring solutions has never been more critical. This research paper introduces an innovative approach to addressing this challenge by deploying a low-cost Internet of Things (IoT) air monitoring station and providing a blockchain technology solution to enhance environmental data transparency, reliability, and accessibility. Our paper adopts a concept of merging IoT and blockchain technologies and collecting some parameters that help to assess air quality by using three sensors, DHT11, MQ7, and MQ135, to collect temperature, humidity, carbon monoxide, and carbon dioxide parameters, respectively, to measure the gases and thus indicate the air quality within the surrounding area. Collecting and sharing these types of valuable data will be very important for various stakeholders, such as governmental bodies, researchers, and the public. This approach is consistent with the principles of sustainable development, facilitating informed decision-making and promoting eco-friendly policies. This research explores the technical architecture of the IoT air monitoring stations, offering a promising solution for addressing air pollution concerns while promoting sustainable development goals. The proposed system is a model for leveraging emerging technologies to advance environmental monitoring and create smarter, livable cities. This approach aligns with the principles of sustainable development and eco-friendly initiatives. This research offers a promising model for enhancing environmental monitoring efforts and advancing the creation of smarter, more sustainable urban environments. The proposed IoT, cloud platform and blockchain-based system not only addresses pressing air pollution challenges but also sets a benchmark for leveraging emerging technologies in environmental science. [ABSTRACT FROM AUTHOR]

Research on the quality of the air in rural areas is essential for determining base emissions of air pollutants, evaluating the effects of dust pollutants particular to rural areas, modeling the dispersion of pollutants, and developing appropriate pollution mitigation systems. The absence of a systematic review based on the assessment of air quality levels in agricultural settings based on integrated weather variables and air pollutants in the literature draws attention to the deficiencies and the necessity of further research in this area. Hence, our study aimed to develop an Arduino monitoring system with related sensors to acquire some air pollutants and weather parameters. Additionally, we proposed an innovative solution to compare air quality levels by suggesting a new criterion called an integrated indicator for air quality assessment (IAQA). It was created based on the weighted average method to combine the investigated air pollutants and weather parameters. This criterion was evaluated while conducting field measurements in 29 environmentally different agricultural regions located within the Kingdom of Saudi Arabia. To determine the integrated indicator, all the values of the variables were normalized between 0 and 1. The agricultural setting with the lowest integrated indicator was the best environmentally. The lowest and highest values of the integrated indicator ranged from 37.03% and 66.32%, respectively, with an arithmetic average of 48.24%. The developed criterion can change its value depending on the change in the weight value of the variables involved, and it is suitable for application to any other agricultural or non-agricultural setting to evaluate the pollution level in the air. Although similar research has been published, this paper presents novelty findings based on integrated values of air pollutants and weather variables for defining a new criterion called IAQA. Additionally, this paper presents original results for air pollutants and weather aspects in different agricultural settings. [ABSTRACT FROM AUTHOR]

Air pollution poses a great danger to human health and economic development, and understanding people's willingness to pay for improved air quality (WTPA) impacts environmental protection. This paper investigates WTPA based on the perspective of subjective well-being (SWB) and analyzes the mediating role of social interaction on the relationship between the two. This paper distinguishes social interactions into online and offline interactions and analyzes whether the mediating effect of the two different interactions on SWB and WTPA exists separately. Using data from the 2018 China General Social Survey (CGSS), we find that SWB has a significant positive effect on WTPA, individuals with higher well-being have higher pro-environmental willingness; there is no age, education level, sex of the person, or regional heterogeneity in the effect of SWB on WTPA; offline social interactions play a partially mediating role between SWB and WTPA, while online social interactions failed to mediate between the two. This paper's policy implication is that improving residents' subjective well-being is both an important development goal and an essential way to resolve the conflict between economic development and environmental protection. [ABSTRACT FROM AUTHOR]

Simple Summary: Dairy farming is a significant source of pollutant gas emissions, contributing to climate change and air quality degradation. Understanding these emissions in milk production promotes productive efficiency and sustainable resource use. The aim of this paper is to provide a comprehensive analysis of ammonia and greenhouse gas emissions in dairy farming, utilizing bibliometric analysis methods. Articles featuring experimental data collection were selected, exclusively in English. The databases considered were Scopus and Web of Science. The analyses were conducted using Bibliometrix version 4.0.0 and VOSviewer version 1.6.20 tools to create knowledge maps visualizing information on research countries, institutions, author collaborations, and keyword networks. The search yielded 187 articles related to major pollutant gases such as methane, ammonia, carbon dioxide, nitrous oxide, and hydrogen sulfide. This study provided valuable insights into gas emission sources, air quality, environmental sustainability, and animal welfare, as well as identifying gaps and critical points in research on the topic. Ammonia and greenhouse gas emissions in dairy farming are crucial for climate change mitigation and sustainable agriculture. This research can contribute to academic interests while enhancing agricultural practices and informing environmental policies. The relevance of this research will persist with the growing demand for sustainable practices, as more researchers and organizations recognize the importance of gas emissions and mitigation research. A deeper understanding of gas emissions in milk production is crucial for promoting productive efficiency, sustainable resource use, and animal welfare. This paper aims to analyze ammonia and greenhouse gas emissions in dairy farming using bibliometric methods. A total of 187 English-language articles with experimental data from the Scopus and Web of Science databases (January 1987 to April 2024) were reviewed. Publications notably increased from 1997, with the highest number of papers published in 2022. Research mainly focuses on ammonia and methane emissions, including quantification, volatilization, and mitigation strategies. Other gases like carbon dioxide, nitrous oxide, and hydrogen sulfide were also studied. Key institutions include the University of California–Davis and Aarhus University. Bibliometric analysis revealed research evolution, identifying trends, gaps, and future research opportunities. This bibliometric analysis offers insights into emissions, air quality, sustainability, and animal welfare in dairy farming, highlighting areas for innovative mitigation strategies to enhance production sustainability. This research contributes to academia, enhancing agricultural practices, and informing environmental policies. It is possible to conclude that this research is a valuable tool for understanding the evolution of research on gas emissions in dairy cattle facilities, providing guidance for future studies and interventions to promote more sustainable production. [ABSTRACT FROM AUTHOR]

The paper presents a specific method of environmental impact assessment applied in Strategic Environmental Assessment (SEA) for the National Emission Reduction Plan (NERP) in the Republic of Serbia, based on air quality. The specificity of the approach is in the application of a semiquantitative method of multicriteria evaluation based on air dispersion modeling and the integration of SEA goals, indicators and criteria for assessing the impact of the NERP on the quality of air and other environmental elements in this method. When predicting changes in air quality for the planning horizon to 2028, the physical, geographical and climatic characteristics of the area were taken into account, as well as technical measures to reduce SO2 emissions, since this was the dominant pollutant from the Serbian coal-fired power plants studied by the NERP. Air pollution modeling was carried out using the AERMOD software package based on the data collected, and the quantitative results obtained were used in a multicriteria evaluation as part of the SEA. The results of the research indicated the importance of applying this approach in order to significantly increase objectivity in the SEA process, since it is an important element of decision making at the strategic level. In addition, a comparative presentation of the modeling results before and after application of the NERP was an important part of the SEA process, and it provided a clear insight into expected changes in the air quality. This is a key argument for making appropriate policy decisions on spatial, energy, environmental and socio-economic development in the Republic of Serbia, which, like other developing countries, is sluggishly following global trends in energy transition. [ABSTRACT FROM AUTHOR]

The Upper Hunter Valley is a major coal mining area in New South Wales (NSW), Australia. Due to the ongoing increase in mining activities, PM10 (air-borne particles with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. The present study was initiated to quantitatively examine the spatial and temporal variability of PM10 pollution in the region. An earlier paper of this study identified two air quality subregions in the valley. This paper aims to provide a holistic summarisation of the relationships between elevated PM10 pollution in two subregions and the local- and synoptic-scale meteorological conditions for spring and summer, when PM10 pollution is relatively high. A catalogue of twelve synoptic types and a set of six local meteorological patterns were quantitatively derived and linked to each other using the self-organising map (SOM) technique. The complex meteorology–air pollution relationships were visualised and interpreted on the SOM planes for two representative locations. It was found that the influence of local meteorological patterns differed significantly for mean PM10 levels vs. the occurrence of elevated pollution events and between air quality subregions. In contrast, synoptic types showed generally similar relationships with mean vs. elevated PM10 pollution in the valley. Two local meteorological patterns, the hot–dry–northwesterly wind conditions and the hot–dry–calm conditions, were found to be the most PM10 pollution conducive in the valley when combined with a set of synoptic counterparts. These synoptic types are featured with the influence of an eastward migrating continental high-pressure system and westerly troughs, or a ridge extending northwest towards coastal northern NSW or southern Queensland from the Tasman Sea. The method and results can be used in air quality research for other locations of NSW, or similar regions elsewhere. [ABSTRACT FROM AUTHOR]

To explore the relationship between air pollution and total factor productivity and new pathways, This paper examines the impact of air pollution on total factor productivity of A-share listed companies in Shanghai and Shenzhen between 2015 and 2019. It investigates this relationship by considering two pathways: investor sentiment and government attention. The findings indicate that air pollution suppresses total factor productivity of firms. However, air pollution stimulates investor sentiment, which in turn increases R&D investment and total factor productivity, reducing to some extent the dampening effect of air pollution on total factor productivity. There exists a notable positive correlation between air quality and government attention, acting as a mediating variable. This implies that air pollution has the potential to capture the attention of governmental entities, leading to the implementation of appropriate measures aimed at managing and mitigating the occurrence of air pollution caused by industrial enterprises.And the relevant governments should formulate a series of policies to meet the different needs of different enterprises. These two approaches have varying impacts depending on the type of enterprises, thus governments should develop laws to cater to the various demands of different types of enterprises. [ABSTRACT FROM AUTHOR]

Syndemics, the adverse interaction of two or more coterminous diseases or other negative health conditions, have probably existed since human settlement, plant and animal domestication, urbanization, and the growth of social inequality beginning about 10–12,000 years ago. These dramatic changes in human social evolution significantly increased opportunities for the spread of zoonotic infectious diseases in denser human communities with increased sanitation challenges. In light of a growing body of research that indicates that anthropogenic air pollution causes numerous threats to health and is taking a far greater toll on human life and wellbeing than had been reported, this paper proposes the possibility that air pollution is now the primary driver of infectious disease syndemics. In support of this assertion, this paper reviews the growth and health impacts of air pollution, the relationship of air pollution to the development and spread of infectious diseases, and reported cases of air pollution-driven infectious disease syndemics, and presents public health recommendations for leveraging the biosocial insight of syndemic theory in responding to infectious disease. [ABSTRACT FROM AUTHOR]

Chronic Obstructive Pulmonary Disease (COPD) poses a significant global healthcare challenge. It is a progressive lung disease that causes breathing difficulties and can significantly impact a person's quality of life. COPD is primarily caused by smoking, but other factors, such as air pollution and genetic predisposition, can also contribute to its development. This paper introduces a novel Context-Aware Framework for the Diagnosis and Personalized Management of COPD. We discuss the limitations of traditional COPD management, highlighting the importance of early detection and remote monitoring. Early detection and remote monitoring are crucial in managing COPD as they allow for timely interventions and better disease management. In this paper, we propose a framework based mostly on contextual data and other parameters of COPD as put forth by the World Health Organization (WHO) in the form of the International Classification of Functioning, Disability, and Health. Ontologies drive this architecture and incorporate dynamic contextual information from patient environments, user profiles, and sensor data. In addition to the various obvious data items like patient personal details (gender, contact, medical history) and COPD risks and symptoms, the COPD ontology also considers the details about the caregiver and healthcare professional. This is in addition to the contextual data processed separately using the Context Ontology. The ontology we constructed using Protégé serves as the framework for the structured representation and logical inference of contextual information. By harnessing dynamic contextual data, our ontology enables real-time decision-making tailored to individual patient requirements. It empowers healthcare professionals to make informed choices and deliver timely interventions, enhancing healthcare services by offering proactive care to detect early signs of health deterioration and suggest preventive measures. This approach improves patient experiences and optimizes resource allocation within the healthcare system. To uphold ethical standards and prioritize the needs of patients, we emphasize the significance of safeguarding data, obtaining informed permission, and recognizing data ownership. The ontologybased approach presented in this study offers a scalable and flexible framework that can be readily incorporated into existing healthcare systems, redefining the management of COPD in response to evolving demands. Security poses one of the biggest threats in context-based environments due to the different data formats acquired by the diverse sensors. Another essential consideration is confidentiality because the data in hand is sensitive patient information. [ABSTRACT FROM AUTHOR]

New digital interventions have shown potential in managing asthma and improving patients' quality of life compared with conventional interventions. Our objective was to conduct an exhaustive survey of the application of digital health technologies in evaluating, treating, and self-managing psychological and psychopathological elements linked to asthma. We analyzed a compendium of research papers pertaining to asthma, encompassing themes such as outdoor air pollution, early life wheezing disorders, atopic dermatitis, digital strategies for asthma self-management, psychiatric conditions and asthma, familial impacts on pediatric asthma, and the utilization of mobile health apps for managing asthma. We scrutinized six chosen studies to evaluate the capacity of digital health technologies to enhance the management and treatment outcomes of psychological factors related to asthma. The studies under review indicate that eHealth interventions, mixed reality instruments, mHealth technology-augmented nurse-led interventions, and smartphone apps incorporating Bluetooth-enabled sensors for asthma inhalers can markedly enhance self-management of symptoms, quality of life, and mental health outcomes, particularly in children and adolescents with asthma. Nonetheless, additional research is required to ascertain their efficacy and practicability across diverse populations and environments. Customized interventions that cater to the unique needs and preferences of asthma patients and associated psychological elements are vital to ensure the persistent and equitable adoption of these technologies. We underscore the significance of addressing psychological elements in the management and treatment of asthma and advocate for ongoing research and development in this domain. [ABSTRACT FROM AUTHOR]

The external insulation strength of the power equipment sleeve in the substation and converter station will be reduced with the increase in altitude and atmosphere pollution. The weakness of external insulation seriously threatens the safe operation of electrical equipment. At present, there are few studies and conclusions that focus on the flashover characteristics of power equipment bushing in high-altitude polluted areas. Therefore, this paper takes the 220 kV voltage level bushing as the research object and studies the Alternating Current (AC) pollution flashover characteristics and lightning and switching impulse flashover characteristics at low pressure. The insulation configuration at high-altitude polluted areas is analyzed. Finally, the insulation configuration scheme, which is suitable for high-altitude polluted areas, is proposed. The results show that the AC pollution flashover voltages of the bushing decrease with the decrease in the atmospheric pressure and the increase in the salt density as a power exponent function. The impulse flashover voltages also decrease with the decrease in the atmospheric pressure as a power exponent function. The atmospheric pressure/pollution impact characteristic index is related to the type of voltage, the value of the atmospheric pressure, and the value of the salt density. The test bushing does not meet the insulation configuration requirements in some high-altitude polluted areas. Through the analysis and calculation of the test results, the bushing insulation configuration scheme in high-altitude polluted areas is proposed. The research results can provide a reference for the external insulation design of bushings in substations and converter stations in high-altitude polluted areas. [ABSTRACT FROM AUTHOR]

The Beijing-Tianjin-Hebei (BTH) is one of the key areas with PM 2.5 air pollution in China. Driven by the PM 2.5 target accessibility of the Interim Target-1 (IT-1) by World Health Organization (WHO) and China's carbon neutrality, this study explored and quantified the contribution of climate change and anthropogenic emission to future PM 2.5 in the region. The experiments considered future climate change scenarios RCP8.5, RCP4.5, and RCP2.6 with the baseline (Base) and reduced emission (EIT1) inventories in 2030, and RCP4.5 climate scenario with 3 emission inventories in 2050, the additional strong control emission scenario called Best-Health-Effect (BHE). Under various climate scenarios, the future air quality research modelling system projected annual PM 2.5 concentrations nearing 35 μg/m 3 in 2030. However, considering only the effect of emission reduction, the annual PM 2.5 concentrations under EIT1 emission scenario is about 35% less than under Base scenario in different key years. The future PM 2.5 concentrations are highly related to anthropogenic emission from human activities, while climate change by 2030 or 2050 has little impact on future air quality over the BTH region. The BHE emission reduction is significantly required for China to meet the new PM 2.5 guideline value of WHO in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Animal and human studies indicate that exposure to air pollution and natural environments might modulate the gut microbiota, but epidemiological evidence is very scarce., Objectives: To assess the potential impact of pre- and postnatal exposure to air pollution and green spaces on infant gut microbiota assembly and trajectories during the first year of life., Methods: MAMI ("MAternal MIcrobes") birth cohort (Valencia, Spain, N = 162) was used to study the impact of environmental exposure (acute and chronic) on infant gut microbiota during the first year of life (amplicon-based 16S rRNA sequencing). At 7 days and at 1, 6 and 12 months, residential pre- and postnatal exposure to air pollutants (NO 2 , black carbon -BC-, PM 2.5 and O 3 ) and green spaces indicators (NDVI and area of green spaces at 300, 500 and 1000 m buffers) were obtained. For the association between exposures and alpha diversity indicators linear regression models (cross-sectional analyses) and mixed models, including individual as a random effect (longitudinal analyses), were applied. For the differential taxon analysis, the ANCOM-BC package with a log count transformation and multiple-testing corrections were used., Results: Acute exposure in the first week of life and chronic postnatal exposure to NO 2 were associated with a reduction in microbial alpha diversity, while the effects of green space exposure were not evident. Acute and chronic (prenatal or postnatal) exposure to NO 2 resulted in increased abundance of Haemophilus, Akkermansia, Alistipes, Eggerthella, and Tyzerella populations, while increasing green space exposure associated with increased Negativicoccus, Senegalimassilia and Anaerococcus and decreased Tyzzerella and Lachnoclostridium populations., Discussion: We observed a decrease in the diversity of the gut microbiota and signs of alteration in its composition among infants exposed to higher levels of NO 2 . Increasing green space exposure was also associated with changes in gut microbial composition. Further research is needed to confirm these findings., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Mireia Gascon reports financial support was provided by Carlos III Health Institute Health Sciences National Library. Maria Carmen Collado reports financial support was provided by European Research Council. Maria Carmen Collado reports financial support was provided by Government of Valencia. Maria Carmen Collado reports financial support was provided by Horizon Europe. Maria Carmen Collado reports financial support was provided by Spanish Ministry of Science and Innovation. Anna Samarra reports financial support was provided by Government of Valencia. Anna Samarra reports financial support was provided by European Social Fund. Raul Cabrera Rubio reports financial support was provided by Government of Valencia. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Carbon dioxide (CO2) emissions and haze pollution are often thought to have the same origin, the burning of fossil fuels. However, their relationship is not always synergistic and may even exhibit mutual constraints. Carbon-biased technological progress has emerged as a promising approach for simultaneously achieving three goals - to reduce CO2 emissions, alleviate the haze pressure, and keep economic growth. This study empirically investigates the impact and mechanisms of carbon-biased technological progress on carbon haze collaborative governance using data from 286 Chinese cities during 2006-2021. The results indicate that: (1) Carbon biased technological progress positively influences carbon haze collaborative governance. (2) This progress achieves coordination by enhancing element allocation efficiency, carbon efficiency, and responding to public environmental demands. (3) The facilitating role of carbon biased technological progress to carbon haze collaborative governance will work better if external conditions are met. Moreover, the effectiveness of carbon-biased technological progress in promoting coordination is contingent upon high levels of marketization, government intervention, environmental regulation, and technical advancements. Local and regional governments should foster conducive conditions for carbon dioxide and haze pollution coordination, optimize the allocation and flow of carbon resources, ensure harmonization between environmental regulation policies and other sectors, and bolster international cooperation and technical knowledge exchange to collectively address global environmental challenges., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Against the backdrop of global climate change and the "dual carbon" target, cities have a significant responsibility to achieve carbon reduction targets. As a crucial urban agglomeration in northern China, effectively balancing economic growth with CO 2 emission reduction to achieve high-quality economic development remains a significant challenge that the Beijing-Tianjin-Hebei region should address both presently and in the future. The objective of this study is to utilize nighttime lighting data and energy consumption information to quantify the CO 2 emissions of diverse cities within the Beijing-Tianjin-Hebei region spanning from 2006 to 2020. The research aims to analyze the spatial progression patterns of CO 2 emissions across these urban centers, identify key determinants and their interrelations, and delve into the underlying mechanisms pivotal for advancing carbon mitigation strategies within urban agglomerations. The results indicate that: with an exception in Beijing where CO 2 emissions slightly decreased compared to 2006, CO 2 emissions increased across cities in the Beijing-Tianjin-Hebei region by 2020. High-value CO 2 emission areas are primarily concentrated in central of the study area, exhibiting negative spatial correlation characteristics. Based on its urban development positioning, it is imperative for the Beijing-Tianjin-Hebei urban agglomeration to formulate and implement carbon reduction strategies on innovative development, industrial upgrading, and ecological protection among other aspects towards coordinated low-carbon development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Prolonged exposure to air pollution has been linked to adverse respiratory health, yet the evidence concerning its association with chronic obstructive pulmonary disease (COPD) is inconsistent. The evidence of a greenness effect on chronic respiratory diseases is limited., Objective: This study aimed to investigate the association between long-term exposure to particulate matter (PM 2.5 and PM 10 ), black carbon (BC), nitrogen dioxide (NO 2 ), ozone (O 3 ) and greenness (as measured by the normalized difference vegetation index - NDVI) and incidence of self-reported chronic bronchitis or COPD (CB/COPD)., Methods: We analyzed data from 5355 adults from 7 centers participating in the Respiratory Health in Northern Europe (RHINE) study. Mean exposures to air pollution and greenness were assessed at available residential addresses in 1990, 2000 and 2010 using air dispersion models and satellite data, respectively. Poisson regression with log person-time as an offset was employed to analyze the association between air pollution, greenness, and CB/COPD incidence, adjusting for confounders., Results: Overall, there were 328 incident cases of CB/COPD during 2010-2023. Despite wide statistical uncertainty, we found a trend for a positive association between NO 2 exposure and CB/COPD incidence, with incidence rate ratios (IRRs) per 10 μg/m³ difference ranging between 1.13 (95% CI: 0.90-1.41) in 1990 and 1.18 (95% CI: 0.96-1.45) in 2000. O 3 showed a tendency for inverse association with CB/COPD incidence (IRR from 0.84 (95% CI: 0.66-1.07) in 2000 to 0.88 (95% CI: 0.69-1.14) in 2010. No consistent association was found between PM, BC and greenness with CB/COPD incidence across different exposure time windows., Conclusion: Consistent with prior research, our study suggests that individuals exposed to higher concentrations of NO 2 may face an elevated risk of developing COPD, although evidence remains inconclusive. Greenness was not associated with CB/COPD incidence, while O 3 showed a tendency for an inverse association with the outcome., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

The growing effects of climate change on Malaysia's coastal ecology heighten worries about air pollution, specifically caused by urbanization and industrial activity in the maritime sector. Trucks and vessels are particularly noteworthy for their substantial contribution to gas emissions, including nitrogen dioxide (NO 2 ), which is the primary gas released in port areas. The application of advanced analysis techniques was spurred by the air pollution resulting from the combustion of fossil fuels such as fuel oil, natural gas and gasoline in vessels. The study utilized satellite photos captured by the Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5P satellite to evaluate the levels of NO 2 gas pollution in Malaysia's port areas and exclusive economic zone. Before the COVID-19 pandemic, unrestricted gas emissions led to persistently high levels of NO 2 in the analyzed areas. The temporary cessation of marine industry operations caused by the pandemic, along with the halting of vessels to prevent the spread of COVID-19, resulted in a noticeable decrease in NO 2 gas pollution. In light of these favourable advancements, it is imperative to emphasize the need for continuous investigation and collaborative endeavours to further alleviate air contamination in Malaysian port regions, while simultaneously acknowledging the wider consequences of climate change on the coastal ecology. The study underscores the interdependence of air pollution, maritime activities and climate change. It emphasizes the need for comprehensive strategies that tackle both immediate environmental issues and the long-term sustainability and resilience of coastal ecosystems in the context of global climate challenges., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Brick kiln emissions adversely affect air pollution and the health of workers and individuals living near the kilns; however, evidence of their impacts remains limited. We conducted a systematic review of brick kiln pollution (emissions, source contributions and personal exposures) and its effects on health. We extracted articles from electronic databases and through manual citation searching. We estimated pooled, sample-size-weighted means and standard deviations for personal exposures by job type; computed mean emission factors and pollutant concentrations by brick kiln design; and meta-analyzed differences in means or proportions for health outcomes between brick kiln workers and controls or for participants living near or far away from kilns. We identified 104 studies; 74 were conducted in South Asia. The most evaluated pollutants were particulate matter (PM; n = 48), sulfur dioxide (SO 2 ; n = 24) and carbon monoxide (CO; n = 22), and the most evaluated health outcomes were respiratory health (n = 34) and musculoskeletal disorders (n = 9). PM and CO emissions were higher among traditional than improved brick kilns. Mean respirable silica exposures were only measured in 4 (4%) studies and were as high as 620 μg/m 3 , exceeding the NIOSH recommended exposure limit by a factor of over 12. Brick kiln workers had consistently worse lung function, more respiratory symptoms, more musculoskeletal complaints, and more inflammation when compared to unexposed participants across studies; however, most studies had a small sample size and did not fully describe methods used for sampling or data collection. On average, brick kiln workers had worse health outcomes when compared to unexposed controls but study quality supporting the evidence was low. Few studies reported silica concentrations or personal exposures, but the few that did suggest that exposures are high. Further research is needed to better understand the relationship between brick kiln pollution and health among workers, and to evaluate exposure mitigation strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Many researchers have studied the role of air pollutants on cognitive function, changes in brain structure, and occurrence of dementia. Due to the wide range of studies and often contradictory results, the present systematic review was conducted to try and clarify the relationship between air pollutants and dementia. To identify studies for this review, a systematic search was conducted in Scopus, PubMed, and Web of Science databases (without historical restrictions) until May 22, 2023. The PECO statement was created to clarify the research question, and articles that did not meet the criteria of this statement were excluded. In this review, animal studies, laboratory studies, books, review articles, conference papers and letters to the editors were avoided. Also, studies focused on the effect of air pollutants on cellular and biochemical changes (without investigating dementia) were also excluded. A quality assessment was done according to the type of design of each article, using the checklist developed by the Joanna Briggs Institute (JBI). Finally, selected studies were reviewed and discussed in terms of Alzheimer's dementia and non-Alzheimer's dementia. We identified 14,924 articles through a systematic search in databases, and after comprehensive reviews, 53 articles were found to be eligible for inclusion in the current systematic review. The results showed that chronic exposure to higher levels of air pollutants was associated with adverse effects on cognitive abilities and the presence of dementia. Studies strongly supported the negative effects of PM 2.5 and then NO 2 on the brain and the development of neurodegenerative disorders in old age. Because the onset of brain structural changes due to dementia begins decades before the onset of disease symptoms, and that exposure to air pollution is considered a modifiable risk factor, taking preventive measures to reduce air pollution and introducing behavioral interventions to reduce people's exposure to pollutants is advisable., (© 2024. The Author(s).)

Climate change mitigation and adaptation along with air pollution are key challenges that require a comprehensive planning approach able to promote win-win strategies and avoid transferring environmental pressures from one sector to another. The joint approach is widely advocated at the policy level while the scientific research investigates the role of co-benefits in planning processes. A methodological framework was developed with the twofold aim of (i) assessing the current integration degree between regional Air Quality Plans and Climate Plans and (ii) providing useful hints for pursuing greater air-climate integration. Its application to the Italian case study provides useful policy implications for strengthening the role of co-benefits as drivers of planning processes. Results show that a greater air-climate integration can be achieved by enhancing the role of regional authorities in supporting the implementation of local-scale plans and actions. This is especially important in contexts where an integrated planning framework is lacking and the mainstreaming within sectoral sub-regional plans turns out to be crucial., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The iron and steel industry (ISI) is a significant source of sulfur dioxide and particulate matter pollution in China. Existing research on regional environmental regulation or ISI emission reduction strategies tends to overlook spillover effects and the enterprise perspective. During the heating season, production limitations in ISI are potential policy measures for achieving structural emission reductions in heavily polluted cities in China's Jing-Jin-Ji and surrounding regions. We adopt a bottom-up modeling approach, incorporating effective production time to describe enterprise behavior and establishing a quantitative trade model based on trade theory. By modeling three types of production restriction policies outlined in policy documents, we evaluate the emission reduction effects of structure-adjustment measures using the example of reduced effective production time for steel-producing enterprises in the air pollution transmission channel in the Beijing-Tianjin-Hebei area. The results indicate the following: (1) Reducing the effective production time of ISI enterprises can help decrease domestic production value and total factor productivity in pollution-intensive industries, including but not limited to ISI. It also leads to reduced emissions of various pollutants in the implementation regions. (2) Due to interprovincial trade and input-output linkages, structural reduction measures in certain regions have implications for almost all other provinces' industrial structures. Differences in initial industrial structures, factor endowments, and geographical locations contribute to varying directions and magnitudes of industrial structural changes. Pollution-intensive industries' share tends to increase higher in less developed regions. (3) Our estimated pollution reduction is smaller compared to the literature evaluating clean air policies in similar regions using top-down strategies. This discrepancy arises because we analyze a single policy tool rather than modeling industry-wide emission fluctuations from the top down. Additionally, our modeling approach allows us to examine dynamic changes in comparative advantages. The increase in production scale for certain industries in policy-affected regions partially offsets the decline in pollution emissions. These findings enhance our understanding of structure-adjustment reduction measures' role and highlight their potential advantages and limitations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In China, population growth and aging have partially negated the public health benefits of air pollution control measures, underscoring the ongoing need for precise PM 2.5 monitoring and mapping. Despite its prevalence, the satellite-derived Aerosol Optical Depth (AOD) method for estimating PM 2.5 concentrations often encounters significant spatial data gaps. Additionally, current research still needs better representation of PM 2.5 spatiotemporal heterogeneity. Addressing these challenges, we developed a two-stage model employing the Extreme Gradient Boosting (XGBoost) algorithm. By incorporating improved spatiotemporal factors, we achieved high-precision and full-coverage daily 1-km PM 2.5 mappings across China for the year 2020 without utilizing AOD products. Specifically, Model 1 develops improved temporal encodings and a terrain classification factor (DC), while Model 2 constructs an enhanced spatial autocorrelation term (Ps) by integrating observed and estimated values. Notably, Model 2 excelled in 10-fold sample-based cross-validation, achieving a coefficient of determination of 0.948, a mean absolute error of 3.792 μg/m³, a root mean square error of 7.144 μg/m³, and a mean relative error of 14.171%. Feature importance and Shapley Additive exPlanations (SHAP) analyses determined the relative importance of predictors in model training and outcome prediction, while correlation analysis identified strong links between improved temporal encodings, PM 2.5 concentrations, and significant meteorological factors. Two-way Partial Dependence Plots (PDPs) further explored the interactions among these factors and their impact on PM 2.5 levels. Compared to traditional methods, improved temporal encodings align more closely with seasonal variations and synergize more effectively with meteorological factors. Besides, the structured nature of DC aids in model training, while the improved Ps more effectively captures PM 2.5 's spatial autocorrelation, outperforming traditional Ps. Overall, this study effectively represents spatiotemporal information, thereby boosting model accuracy and enabling seamless large-scale PM 2.5 estimations. It provides deep insights into variables and models, providing significant implications for future air pollution research., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In response to the dual challenges of air pollution control and carbon mitigation, China has strategically shifted its focus towards the synergistic reduction of air pollutants and CO 2 emissions. This study identifies the potential areas and specific air pollutant species (including CO, NO x , and SO 2 ) for co-reduction with carbon mitigation. We also reveal the driving forces behind the emissions of each air pollutant at both the national and regional scales. Our findings are as follows: (1) The potential for synergistic reduction of CO and SO 2 with CO 2 emissions has diminished in economically developed areas. There is a significant opportunity for co-reduction of SO 2 and CO 2 in the western and northern regions of China, particularly within Heilongjiang Province. (2) NOx is the key species for synergistic reduction with CO 2 emissions across China, especially in the Chengyu Plain. (3) Cleaner production and the synergistic reduction effect are the primary contributors to national air pollutant reduction in China from 2008 to 2017. Conversely, efforts in economic development and energy efficiency have led to emission increases. Energy and industrial structures have only made limited contributions to emission reductions, and carbon mitigation shows an inhibition effect on emission reductions. These results offer valuable insights for developing targeted regional strategies for deeper air pollution control, considering the specific characteristics and needs of each region. Additionally, our findings highlight the importance of addressing policy misalignments and strengthening mutual-influence mechanisms between air pollution control and carbon mitigation, ensuring that policies for carbon reduction also effectively contribute to air quality improvements., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Wildfire intensity and severity have been increasing in the Iberian Peninsula in recent years, particularly in the Galicia region, due to rising temperatures and accumulating drier combustible vegetation in unmanaged lands. This leads to substantial emissions of air pollutants, notably fine particles (PM 2.5 ), posing a risk to public health. This study aims to assess the impact of local and regional wildfires on PM 2.5 levels in Galicia's main cities and their implications for air quality and public health. Over a decade (2013-2022), PM 2.5 data during wildfire seasons were analyzed using statistical methods and Lagrangian tracking to monitor smoke plume evolution. The results reveal a notable increase in PM 2.5 concentration during the wildfire season (June-November) in Galicia, surpassing health guidelines during extreme events and posing a significant health risk to the population. Regional wildfire analyses indicate that smoke plumes from Northern Portugal contribute to pollution in Galician cities, influencing the seasonality of heightened PM 2.5 levels. During extensive wildfires, elevated PM 2.5 concentration values persisted for several days, potentially exacerbating health concerns in Galicia. These findings underscore the urgency of implementing air pollution prevention and management measures in the region, including developing effective alerts for large-scale events and improved wildfire management strategies to mitigate their impact on air quality in Galician cities., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Cesar Quishpe-Vasquez reports financial support was provided by University of Alcala. Patricia Oliva reports financial support was provided by Community of Madrid. Alejandro Casallas reports financial support was provided by European Union. Ellie Anne Lopez-Barrera reports financial support was provided by Sergio Arboleda University. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Volatile organic compounds (VOCs) emitted into the atmosphere negatively affect the environment and human health. Biotrickling filtration, an effective technology for treating VOC-laden waste gases, faces challenges in removing hydrophobic VOCs due to their low water solubility and therefore limited bioavailability to microorganisms. Consequently, the addition of (bio)surfactants has proven to be a promising strategy to enhance the removal of hydrophobic VOCs in biotrickling filters (BTFs). Yet, up to now, no single study has ever performed a mass transfer characterization of a BTF under (bio)surfactants addition. In this study, the effect of (bio)surfactant addition on the gas-liquid mass transfer characteristics of two BTFs was measured by using oxygen (O 2 ) as a model gas. Through an empirical correlation, the mass transfer coefficients (k L a) of two hydrophobic VOCs, toluene and hexane, which are of industrial and environmental significance, were estimated. One BTF was filled with expanded perlite, while the other with a mixture of compost and wood chips (C + WC). Both BTFs were operated under different liquid velocities (U L : 0.95 and 1.53 m h -1 ). Saponin, a biological surfactant, and Tween 80, a synthetic surfactant, were added to the recirculating liquid at different critical micelle concentrations (CMCs: 0-3 CMC). The higher interfacial and surface area of the perlite BTF compared to the C + WC BTF led to higher k L aO 2 values regardless of the operational condition: 308 ± 18-612 ± 19 h -1 versus 42 ± 4-177 ± 24 h -1 , respectively. Saponin addition at 0.5 and 1 CMC had positive effects on the perlite BTF, with k L aO 2 values two times higher compared to those at 0 CMC. Tween 80 exhibited a neutral or slightly positive effect on the mass transfer of both BTFs under all conditions. Overall, the CMC, along with the physical characteristics of the packing materials and the operational conditions evaluated explained the results obtained. This study provides fundamental data essential to improve the performance and design of BTFs for hydrophobic VOCs abatement., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Ore mineralizations in bedrock and their exploitation may have a negative impact on air quality of surrounding urban areas and, subsequently, on human health. This study uses lichens as bioindicators of atmospheric pollution to evaluate the spatial distribution of potentially toxic elements (PTEs) in the towns close to the massive sulfide deposits of the Iberian Pyrite Belt (IPB) in SW Spain. Altogether 89 native lichen samples of Xanthoria parietina were collected from the mining towns, control towns out of the reach of the mining activity, as well as from distal sampling sites. The samples were analyzed for 29 elements after acid digestion. The concentrations for Co, Ni, Cu, Zn, As, Rb, Mo, Cd, Sn, Sb, Cs, Ba, W, Tl, Pb, S, and Fe are significantly higher in the mining towns in comparison to the control towns. The ore mineral-associated PTEs, including Cu, Zn, As, Ba, and Pb, exhibit extreme concentrations in the urban areas close to the mining activity, and particularly in the small settlement of La Dehesa next to the mineral processing plant and the tailings pond. The distal samples confirm the decrease in the concentrations of all PTEs, and these samples present similar values as in the control areas. The results, point at increased bioaccumulation of PTEs in the lichen thalli of the adjacent urban areas, suggesting that the air quality of the adjacent urban areas is locally impacted by the massive polymetallic sulfide deposits which is enhanced by the mining activity. Therefore, monitoring the urban air quality is recommended., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Annika Parviainen reports financial support was provided by University of Granada. Annika Parviainen reports financial support was provided by Government of Andalusia. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Regular monitoring of the air pollutant nitrogen dioxide (NO 2 ), an indicator for traffic-related emissions, is a priority in urban environments. The health impacts associated with NO 2 exposure are the result of a combination of factors, including concentration, duration of exposure, and interactions with other pollutants. WHO has established air quality guidelines based on epidemiological studies., Objective: This study develops a new concept "Health Impact Pathways (HIPs)" using adversity as a probabilistic indicator of health effects. For this purpose, it integrates available toxicological and epidemiological information, using Adverse Outcome Pathways (AOPs), in order to understand chemical-biological interactions and their consequences on health., Methods: Literature review and meta-analysis of toxicological data supported by expert judgment were performed to establish: a) adversity pathways, b) quantitative criteria for scoring the observed toxicological effects (adversity indicators), c) NO 2 exposure - adversity relationship for both long-term (1-36 months) and shortterm (1-7 days). The NO 2 daily concentrations from January 2001 to December 2022, were obtained from Madrid city Air Quality network monitoring database. Adversity levels were compared with relative risk levels for all-cause and respiratory mortality estimated using linear equations from WHO 2021 guidelines., Results: Non-linear relations were obtained for all long- and short-term NO 2 related adversity indicators; for long-term effects, the best fitting was obtained with a modified Haber's law model with an exponential coefficient for the exposure time of 0.25. Estimations are presented for a set of case studies for Madrid city, covering temporal and spatial variability. A clear improvement trend along the two decades was observed, as well as high inter- and intra-station variability; the adversity indicators provided integrated information on the temporal and spatial evolution of population level risk., Discussion: The proposed HIP conceptual approach offers promising advances for integrating experimental and epidemiological data. The next step is linking the concentration-adversity relationship with population health impacts through probability estimations, the preliminary estimations confirm the need for assessing independently different population groups., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Instituto de Salud Carlos III. Published by Elsevier Ltd.. All rights reserved.)

Background: Chronic respiratory diseases (CRDs) are among the top three causes of human mortality. The relationship between modifiable environmental risk factor of noise and risk of mortality in CRDs is unclear. We investigated the longitudinal association between environmental noise exposure and cause-specific mortality in individuals with CRDs, considering the modifying effect of air pollution., Methods: Residential noise exposure was modelled using Common Noise Assessment Methods in Europe. Information on death causes were acquired from death registry data. Cox proportional-hazards models were used to estimate effect sizes., Results: Among 41,222 participants selected from UK Biobank with CRDs in baseline, a total of 3618 death cases occurred during an average follow-up of 12 years with mortality density of 7.16 per 1000 person years. Exposure with highest noise level (> percentile 90) were associated with 22 % (Hazard ratio [HR] = 1.22, 95 % confidence interval [CI]: 1.05, 1.42), 71 % (HR = 1.71, 95 % CI: 1.14, 2.56), and 84 % (HR = 1.84, 95 % CI: 1.10, 3.07) increased risks for all-cause, respiratory disease (RD)-cause, and COPD-cause mortalities, separately. Both multiplicative and additive interactions was found between air pollution and noise with the risk of RD-cause mortality. Participants with high air pollution and noise exposure were associated with a 101 % (HR = 2.01, 95 % CI: 1.10, 3.66) increased risk of RD-cause mortality., Conclusion: It is imperative to mitigate noise exposure as a preventive measure against incident mortality in individuals with CRDs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

PM 2.5 is a main atmospheric pollutant with various sources and complex chemical compositions, which are influenced by various factors, such as anthropogenic emissions (AE) and meteorological conditions (MC). MC have a significant impacts on variations in atmospheric pollutant; therefore, emission reduction policies and ambient air quality are non-linearly correlated, which hinders the accurate assessment of the effectiveness of control measures. In this study, we conducted online observations of PM 2.5 and its chemical composition in Hohhot, China, from December 1, 2019, to February 29, 2020, to investigate how the chemical compositions of PM 2.5 respond to the variations in AE and MC. Moreover, the random forest (RF) model was used to quantify the contributions of AE and MC to PM 2.5 and its chemical composition during severe hazes and the COVID-19 pandemic lockdown period. During the clean period, MC reduced PM 2.5 concentrations by 124%, while MC incresed PM 2.5 concentrations by 49% during severe pollution episode. Inorganic aerosols (SO 4 2- , NO 3 - , and NH 4 + ) showed the strongest response to MC. MC significantly contributed to PM 2.5 (36%), SO 4 2- (32%), NO 3 - (29%), NH 4 + (28%), OC (22%), and SOC (17%) levels during pollution episodes. From the pre-lockdown to lockdown period, AE (MC) contributed 52% (48%), 81% (19%), 48% (52%), 68% (32%), 59% (41%), and 288% (-188%) to the PM 2.5 , SO 4 2- , NO 3 - , NH 4 + , OC, and SOC reductions, respectively. The variations in MC (especially the increase in relative humidity) rapidly generated meteorologically sensitive species (SO 4 2- , NO 3 - , and NH 4 + ), which led to severe winter pollution. This study provides a reference for assessing the net benefits of emission reduction measures for PM 2.5 and its chemical compositions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective: This study focuses on the association between seminal concentration of prosaposin and ambient air pollutants and whether the association affects the normal fertilization rate in vitro fertilization (IVF) treatment., Methods: The cohort of 323 couple participants aged 22-46 was recruited from Jan. 2013 to Jun. 2018. At enrollment, resident address information was obtained and semen parameters of male counterparts were evaluated according to WHO criteria. We used inverse distance weighting interpolation to estimate the levels of ambient pollutants (SO 2 , O 3 , CO, NO 2 , PM 2.5, and PM 10 ) in the surrounding area. The exposure of each participant was estimated based on the data gathered from air quality monitoring stations and their home address over various periods (0-9, 10-14, and 0-90 days) before semen sampling. The generalized linear regression model (GLM) and the Bayesian kernel machine regression (BKMR) were used to analyze the associations between pollutants, semen parameters, prosaposin, and normal fertilization. Additionally, the mediating effect of prosaposin and semen parameters on the link between pollutants and normal fertilization was investigated., Results: GLM and BKMR showed exposure to ambient air pollutants was all associated with the concentration of seminal prosaposin, among them, O 3 and CO were also associated with normal fertilization (-0.10, 95 %CI: -0.13, -0.06; -26.43, 95 %CI: -33.79, -19.07). Among the semen parameters, only the concentration of prosaposin and total motile sperm count (TMC) was associated with normal fertilization (0.059, 95 %CI: 0.047, 0.071; 0.016, 95 %CI: 0.012, 0.020). Mediation analysis showed that prosaposin played a stronger mediating role than TMC in the relationship between short-term exposure to O 3 and fertilization (66.83 %, P<0.001 versus 3.05 %, P>0.05)., Conclusion: Seminal plasma prosaposin showed a stronger meditating effect reflect the correlation between ambient air pollutants and normal fertilization rate than conventional semen parameters, which may be used as one of the indicators between pollution and fertilization in IVF., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

A significant concern in our society is the potential impact on both health and the environment of air pollutants released during the incineration of waste. Therefore, it is crucial to conduct thorough control and monitoring measures. In this context, the objective of this research was to study the evolution of particulate matter (PM 2.5 ) and associated trace elements during the period before and after the installation of an Energy Recovery Plant (ERP). For that, a descriptive and temporal analysis of PM 2.5 concentration and composition were performed on two similar areas (impact/control) using the Before-After/Control-Impact (BACI) design and two periods (before from January 01, 2018 to February 06, 2020 and after from December 10, 2020 to September 30, 2022). Results showed a decrease in the levels of PM 2.5 and associated trace elements is observed in the impact zone (IZ) and in the control zone (CZ) throughout the study period. In the case of PM 2.5 , the most notable decrease occurred in the period of the start-up of the ERP, a period that coincides with the confinement and restrictions of COVID, with a subsequent increase in both zones, without reaching the levels observed in the period prior to the start-up of the ERP. Selenium is the only trace element that increases significantly in the IZ. In conclusion, a decrease is observed for all pollutants except selenium in both zones, although less pronounced in the IZ. Since selenium already showed an upward trend in the phase prior to the start of the ERP, it is necessary to investigate its evolution and find out the possible cause., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Jesus Ibarluzea reports financial support was provided by Gipuzkoa Provincial Council. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)