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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.)

Objective: To investigate associations between air particulate matter of ≤2.5 μm in diameter (PM 2.5 ) and ovarian cancer., Design: County-level ecological study., Setting: Surveillance, epidemiology, and end results from a collection of state-level cancer registries across 744 counties. Data from the Environmental Protection Agency's network for PM 2.5 monitoring was used to calculate trailing 5- and 10-year PM 2.5 county-level values. County-level data on demographic characteristics were obtained from the American Community Survey., Population: A total of 98 751 patients with histologically confirmed ovarian cancer as a primary malignancy from 2000 to 2016., Methods: Generalised linear regression models were developed to estimate the association between PM 2.5 and PM 10 levels, over 5- and 10-year periods of exposure, and ovarian cancer risk, after accounting for county-level covariates., Main Outcome Measures: Risk ratios for associations between ovarian cancer (both overall and specifically epithelial ovarian cancer) and PM 2.5 levels., Results: For the 744 counties included, the average PM 2.5 level from 1990 through 2018 was 11.75 μg/m 3 (SD = 3.7) and the average PM 10 level was 22.7 μg/m 3 (SD = 5.7). After adjusting for county-level covariates, the overall annualised ovarian cancer incidence was significantly associated with increases in 5-year PM 2.5 (RR = 1.11 per 10 units (μg/m 3 ) increase, 95% CI 1.06-1.16). Similarly, when the analysis was limited to epithelial cell tumours and adjusted for county-level covariates there was a significant association with trailing 5-year PM 2.5 exposure models (RR = 1.12 per 10 units increase, 95% CI 1.08-1.17). Likewise, 10-year PM 2.5 exposure was associated with ovarian cancer overall and with epithelial ovarian cancer., Conclusions: Higher county-level ambient PM 2.5 levels are associated with 5- and 10-year incidences of ovarian cancer, as measurable in an ecological study., (© 2023 John Wiley & Sons Ltd.)

Objectives: Small-for-gestational-age (SGA) and large-for-gestational-age (LGA) births are major adverse birth outcomes related to newborn health. In contrast, the association between ambient air pollution levels and SGA or LGA births has not been investigated in Japan; hence, the purpose of our study is to investigate this association., Methods: We used birth data from Vital Statistics in Japan from 2017 to 2021 and municipality-level data on air pollutants, including nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), photochemical oxidants, and particulate matter 2.5 (PM 2.5 ). Ambient air pollution levels throughout the first, second, and third trimesters, as well as the whole pregnancy, were calculated for each birth. The association between SGA/LGA and ambient levels of the air pollutants was investigated using crude and adjusted log-binomial regression models. In addition, a regression model with spline functions was also used to detect the non-linear association., Results: We analyzed data from 2,434,217 births. Adjusted regression analyses revealed statistically significant and positive associations between SGA birth and SO 2 level, regardless of the exposure period. Specifically, the risk ratio for average SO 2 values throughout the whole pregnancy was 1.014 (95% confidence interval [CI] 1.009, 1.019) per 1 ppb increase. In addition, regression analysis with spline functions indicated that an increase in risk ratio for SGA birth depending on SO 2 level was linear. Furthermore, statistically significant and negative associations were observed between LGA birth and SO 2 except for the third trimester., Conclusions: It was suggested that ambient level of SO 2 during the pregnancy term is a risk factor for SGA birth in Japan., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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.)

This work presents the first comprehensive assessment of PM pollution sources in Dushanbe, Tajikistan. A total of 138 PM 2.5 samples were collected during 2015-2016 and 2018-2019 and were analyzed through gravimetric, ED-XRF, and multi-wavelength absorption techniques. The results show that PM 2.5 concentrations were substantially higher than the European annual limit value and WHO Air Quality Guidelines annual average value, with an average of 90.9 ± 68.5 μg m -3 . The PMF application identified eight sources of pollution that influenced PM 2.5 concentration levels in the area. Coal burning (21.3%) and biomass burning (22.3%) were the dominant sources during the winter, while vehicular traffic (7.7%) contributed more during the warm season. Power plant emissions (17.5%) showed enhanced contributions during the warm months, likely due to high energy demand. Cement industry emissions (6.9%) exhibited significant contribution during the cold period of 2018-2019, while soil dust (11.3%) and secondary sulphates (11.5%) displayed increased contribution during the warm and cold months, respectively. Finally, waste burning (1.5%) displayed the lowest contribution, with no significant temporal variation. Our results highlight the significant impact of anthropogenic activities, and especially the use of coal burning for energy production (both in power plants and for residential heating), and the significant contribution of biomass burning during both warm and cold seasons., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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.)

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.)

Objective: The aim of the study is to examine whether preoprerative exposure to air pollution is associated with mortality after a major cancer surgery., Methods: All patients who underwent major cancer surgeries after hospitalization between January 1, 2016, to December 31, 2020, were included., Results: In total, 244,766 patients who underwent major cancer surgeries were included. Both 0.001-ppm increase in sulfur dioxide and 0.1-ppm increase in carbon monoxide were associated with a 7% increase in 90-day mortality rate after a major cancer surgery. Furthermore, a 0.001-ppm increase in sulfur dioxide, 0.1 ppm increase in carbon monoxide, and 1 μg/m 3 increase in particulate matter 2.5 were associated with a 4%, 3%, and 1% increase in 1-year all-cause mortality rate after a major cancer surgery., Conclusions: Preoperative exposure to air pollution was associated with an increased risk of mortality in patients after major cancer surgery., Competing Interests: Song and Oh have no relationships/conditions/circumstances that present potential conflict of interest., (Copyright © 2023 American College of Occupational and Environmental Medicine.)

Protecting people from air pollution is an important task for developing countries. Over the past several decades, different types of policies have been enacted in developing countries to improve air quality, with policy impact analysis being conducted as well. As for China, while there is some existing literature on the impact of short-term action on air quality, there is much less research to investigate the roles of long-term air quality control mechanism on air quality change. This paper uses the "2 + 26" city cluster in China as a case study area to particularly analyze the roles played by short-term campaigns that compose the Winter Action Plan and a long-term mechanism referred to as the environmental accountability system in pollution control. Based on econometric and descriptive statistical analyses, it is found that the implementation of the Winter Action Plan has significantly improved the air quality, and the environmental accountability system seems to have exerted an impact, as cities with better air quality appear to establish a more stringent environmental accountability system. The paper provides the following insights for other developing countries: short-term campaigns can quickly reduce pollution and protect human health, while long-term mechanisms are needed to ensure sustainable environmental protection., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The effects of air pollution on health are gaining increasing research interest with limited data on skin alterations available. It was suggested that air pollution is a trigger factor for sensitive skin (SS). However, this data was based on surveys with a lack of experimental data. SS is related to altered skin nerve endings and cutaneous neurogenic inflammation. TTe present study was to assess the in vitro effect of particulate matter (PM) on epidermis and nerve ending homeostasis. PM samples were collected according to a validated protocol. Reconstructed human epidermis (RHE, Episkin®) was exposed to PM and subsequently the supernatants were transferred to a culture of PC12 cells differentiated into sensory neurons (SN). Cell viability, axonal growth and neuropeptide-release were measured. The modulation of the expression of different inflammatory, keratinocytes differentiation and neurites growth markers was assessed. PM samples contained a high proportion of particles with a size below 1 μm and a complex chemical composition. Transcriptomic and immunohistochemical analyses revealed that PM altered keratinocytes terminal differentiation and induced an inflammatory response. While viability and functionality of the SN were not modified, their outgrowth was significantly decreased after incubation with PM-exposed Episkin® supernatants. This was closely related to the modification of nerve growth factor/semaphorin 3A balance. This study showed that air pollutants have negative effects on keratinocytes and sensory nerve endings including inflammatory responses. These effects are probably involved in the SS pathophysiology and might be involved in inflammatory skin disorders., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

This study investigates the impact of ambient air pollution on housing prices in Warsaw, Poland, by examining spatial dependencies. The high concentration of particulate matter (PM 10 , PM 2.5 and PM 1 ) is expected to reduce real estate values. Using a hedonic model with approximately 15,000 observations and a spatial error model, we did not find evidence of this impact. Standard and premium housing submarkets differ in price determinants, but both are insensitive to environmental issues. This could be explained by the lack of comprehensive intra-urban historical information on air pollution, which limits investors' rationality and their ability to properly value real estate based on environmental issues. Additionally, measurement and aggregation issues, along with low pollution variability within the city, may contribute to the insignificance of this information in real estate sales prices. Our empirical research confirms a strong link between air pollution and weather conditions within the city, where low temperatures and low-speed southern winds worsen contamination levels, while high temperatures and westerly winds improve air quality. Furthermore, we find that incorporating pollution data using PM yearly mean concentration works better in modelling than the PCA-reduced air pollution index., (© 2024. The Author(s).)

One of the increasingly common methods to counteract the increased fuel consumption of vehicles is start-stop technology. This paper introduces a methodology which presents the process of measuring and creating a computational model of CO 2 emissions using artificial intelligence techniques for a vehicle equipped with start-stop technology. The method requires only measurement data of velocity, acceleration of vehicle, and gradient of road to predict the emission of CO 2 . In this paper, three methods of machine learning techniques were analyzed, while the best prediction results are shown by the gradient boosting method. For the developed models, the results were validated using the coefficient of determination, the mean squared error, and based on visual evaluation of residual and instantaneous emission plots and CO 2 emission maps. The developed models present a novel methodology and can be used for microscale environmental analysis., (© 2023. The Author(s).)

Purpose: To examine the association between ambient air pollution and dry eye symptoms (DES) during the COVID-19 pandemic and explore whether air pollution had increased the risk of DES to a greater extent than other risk factors., Methods: A nationwide cross-sectional survey was conducted from June 20, 2022 to August 31, 2022. The Ocular Surface Disease Index-6 (OSDI-6) questionnaire was used to assess the presence of DES. Logistic regression models were employed to analyze the associations between DES and air pollution variables, including air quality index (AQI), fine particulate matter (PM 2.5 ), PM 10 , sulfur dioxide (SO 2 ), carbon monoxide (CO), nitrogen dioxide (NO 2 ), ozone (O 3 ) and residing near industrial zones. We explored the interactions of air pollutants and other risk factors in the additive models by calculating the synergy index (SI). Standardized regression coefficients were calculated to compare the relative importance of risk factors for DES., Results: A total of 21,909 participants were included in the analysis. Residing near industrial zones was significantly correlated with a higher risk of DES (Odds ratio (OR): 1.57, 95 % confidence interval (CI): 1.38-1.79). No significant associations were found between DES and air pollutants except SO 2 (OR: 1.05, 95 % CI: 1.02-1.09, per standard deviation increment in SO 2 concentration). The restricted cubic spline analyses revealed a linear concentration-response relationship between SO 2 and DES. The interaction analyses suggested synergetic interactions of SO 2 with depression and problematic internet use. Among the risk factors, depression, anxiety and problematic Internet use contributed more to the increased risk of DES., Conclusion: The association between ambient air pollutants and DES may have been mitigated during the pandemic due to increased time spent indoors. Despite this, our findings support the deleterious health impact of air pollutants. Future urban planning should plan industrial zones further away from residential areas., 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 B.V. All rights reserved.)

Air pollution, a pervasive environmental threat that spans urban and rural landscapes alike, poses significant risks to human health, exacerbating respiratory conditions, triggering cardiovascular problems, and contributing to a myriad of other health complications across diverse populations worldwide. This article delves into the multifarious impacts of air pollution, utilizing cutting-edge research methodologies and big data analytics to offer a comprehensive overview. It highlights the emergence of new pollutants, their sources, and characteristics, thereby broadening our understanding of contemporary air quality challenges. The detrimental health effects of air pollution are examined thoroughly, emphasizing both short-term and long-term impacts. Particularly vulnerable populations are identified, underscoring the need for targeted health risk assessments and interventions. The article presents an in-depth analysis of the global disease burden attributable to air pollution, offering a comparative perspective that illuminates the varying impacts across different regions. Furthermore, it addresses the economic ramifications of air pollution, quantifying health and economic losses, and discusses the implications for public policy and health care systems. Innovative air pollution intervention measures are explored, including case studies demonstrating their effectiveness. The paper also brings to light recent discoveries and insights in the field, setting the stage for future research directions. It calls for international cooperation in tackling air pollution and underscores the crucial role of public awareness and education in mitigating its impacts. This comprehensive exploration serves not only as a scientific discourse but also as a clarion call for action against the invisible but insidious threat of air pollution, making it a vital read for researchers, policymakers, and the general public., Competing Interests: Declaration of Competing Interest We, the authors of this review, hereby declare that there are no financial or non-financial conflicts of interest related to the content of this manuscript. Our work has been conducted and presented with full academic integrity, free from any undisclosed influences or conflicts that could affect the objectivity or credibility of our research and findings., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: Fetal overgrowth has detrimental effects on both the mother and the fetus. The global issue of ambient air pollution has been found to contribute to fetal overgrowth through various pathways. This study aimed to identify the association between prenatal exposure to ambient air pollution and the risk of fetal overgrowth., Methods: We identified articles between January 2013 and February 2024 by searching the Web of Sciences(WoS), PubMed, Proquest, Scopus, and Google Scholar databases. Quality assessment was performed using the Newcastle Ottawa scale. This review was provided based on the PRISMA guideline and registered with PROSPERO, "CRD42023488936"., Results: The search generated 1719 studies, of which 22 cohort studies were included involving 3,480,041 participants. Results on the effects of air pollutants on fetal overgrowth are inconsistent because they vary in population and geographic region. But in general, the results indicate that prenatal exposure to air pollutants, specifically PM 2.5 , NO 2 , and SO 2 , is linked to a higher likelihood of fetal overgrowth(macrosomia and large for gestational age). Nevertheless, the relationship between CO and O 3 pollution and fetal overgrowth remains uncertain. Furthermore, PM 10 has a limited effect on fetal overgrowth. It is essential to consider the time that reproductive-age women are exposed to air pollution. Exposure to air pollutants before conception and throughout pregnancy has a substantial impact on the fetus's vulnerability to overgrowth., Conclusions: Fetal overgrowth has implications for the health of both mother and fetus. fetal overgrowth can cause cardiovascular diseases, obesity, type 2 diabetes, and other diseases in adulthood, so it is considered an important issue for the health of the future generation. Contrary to popular belief that air pollution leads to intrauterine growth restriction and low birth weight, this study highlights that one of the adverse consequences of air pollution is macrosomia or LGA during pregnancy. Therefore governments must focus on implementing initiatives that aim to reduce pregnant women's exposure to ambient air pollution to ensure the health of future generations., 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.)

Objective: Air pollution has been linked to multiple psychiatric disorders, but little is known on its long-term association with schizophrenia. The interaction between air pollution and genetic susceptibility on incident schizophrenia has never been reported. We aimed to explore the associations between long-term air pollution exposure and late-onset schizophrenia and evaluate whether genetic susceptibility could modify the association., Methods: This population-based prospective cohort study included 437,802 middle-aged and elderly individuals free of schizophrenia at baseline in the UK Biobank. Land use regression models were applied in the estimation of the annual average concentrations of nitrogen dioxide (NO 2 ), nitrogen oxides (NO x ), fine particulate matter (PM 2.5 ), and inhalable particulate matter (PM 10 ) at residence. The associations between air pollutants and schizophrenia were evaluated by using Cox proportional hazard models. A polygenic risk score of schizophrenia was constructed for exploring potential interaction of air pollutants with genetic susceptibility., Results: An interquartile range increase in PM 2.5 , PM 10 , NO 2 , and NO x was associated with the hazard ratios (HR) for incident schizophrenia at 1.19, 1.16, 1.22, and 1.09, respectively. The exposure-response curves for the association of air pollution with incident schizophrenia were approximately linear. There are additive interactions of air pollution score (APS), PM 10 , NO 2 , and NO x with genetic risk. Specifically, compared with participants with low genetic susceptibility and low APS, the HR was 3.23 for individuals with high genetic risk and high APS, among which 0.49 excess risk could be attributed to the additive interaction, accounting for 15 % of the schizophrenia risk., Conclusion: This large-scale, prospective cohort study conveys the first-hand evidence that long-term air pollution exposure could elevate schizophrenia incidence in later life, especially for individuals with higher genetic risks. The findings highlight the importance of improving air quality for preventing the late-onset schizophrenia in an aging era, especially among those with high genetic risks., 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 B.V. All rights reserved.)

The prevalence in allergic diseases has increased considerably in the past decades. An important trigger of the symptoms of allergic rhinitis (hay fever) is the pollen of wind-pollinating plants. This pollen is developed by plants and is released into the air where it gets exposed to environmental influences and air pollution. We investigated the chemical changes to pollen that occur after release from the flower in a rural (Veluwe) and an urban (Amsterdam) site in the Netherlands using Fourier Transform Infrared (FTIR) spectroscopy. During the spring/summer of 2020 (during the COVID pandemic) the pollen of nine taxa (Alnus, Betula, Fagus, Fraxinus, Pinus, Plantago, Poaceae, Quercus and Salix) were collected directly from flowers and the air (using a mobile sampler). FTIR spectra were obtained for multiple individual pollen grains for each taxa. The spectra obtained from airborne pollen collected at the rural vs. urban sites did not show any statistical difference. This is possibly a result of a reduced difference in pollutant concentrations between the two sites due to the COVID-19-lockdown measures were in place. However, consistent differences in the FTIR spectra recovered from airborne vs. flower pollen were recorded for all pollen taxa. After the release from the flower the chemical composition of the pollen changed: (i) polysaccharides are converted to monosaccharides; (ii) protein concentration and/or nitration/oxidation level is altered; (iii) lipids are modified and/or reduced in concentration. These changes may alter the allergenicity of the pollen and suggest that further work on the allergenic nature of airborne pollen is required., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: WIlliam Gosling reports financial support was provided by the Netherlands Organisation for Scientific Research (NWO). 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 B.V. All rights reserved.)

Prolonged exposure to PM 2.5 is associated with increased mortality. However, reducing air pollution concentrations does not necessarily reduce the related burden of deaths. Here, we aim to estimate the variations in PM 2.5 -related mortality due to contributions from key factors - PM 2.5 concentration, population exposure, and healthcare levels - for 177 countries from 2000 to 2018 at the 1-km grid scale according to the Global Mortality Exposure Model (GEMM) model. We find that global reductions in PM 2.5 -related deaths mainly come from high and upper-middle income countries, where lowered air pollutant concentration and better healthcare can offset mortality burdens caused by increasing exposed populations. Changes in population exposure to PM 2.5 contribute the most (54 %) to change in global related deaths over the examined period, followed by changes in healthcare (-42 %) and pollution concentrations (4 %). The impacts vary across countries and regions within them due to other drivers, which are significantly influenced by development status. Policies aiming at reducing PM 2.5 associated health risks need to account for country-specific balances of these key socioeconomic drivers., 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 B.V. All rights reserved.)

Background: Previous observational studies have indicated associations of physical activity (PA) and air pollution with mortality. A few studies have evaluated air pollution and PA interactions for health. Still, the trade-off between the harmful effects of air pollution exposure and the protective effects of PA remains controversial and unclear., Objective: This study aimed to investigate the joint association of air pollution and PA with mortality risks., Methods: This prospective cohort study included 322,092 participants from 2006 to 2010 and followed up to 2021 in the UK Biobank study. The concentrations of air pollutants (2006-2010), including particulate matter (PM) with diameters <=2.5 mm (PM 2.5 ), <=10 mm (PM 10 ), and between 2.5 and 10 mm (PM 2.5-10 ), and nitrogen oxides (NO 2 and NO x ) were obtained. Information on PA measured by the International Physical Activity Questionnaire short form (2006-2010) and wrist-worn accelerometer (2013-2015) were collected. All-cause and cause-specific mortalities were recorded. Cox proportional hazard models were used to investigate the associations of air pollution exposure and PA with mortality risks. The additive and multiplicative interactions were also examined., Results: During a mean follow-up of 11.83 years, 16629 deaths were recorded. Compared with participants reporting low PA, higher PA was negatively associated with all-cause [hazard ratio (HR), 0.74; 95% CI, 0.71-0.78], cancer (HR, 0.85; 95% CI, 0.80-0.90), CVD (HR, 0.79; 95% CI, 0.71-0.87), and respiratory disease-specific mortality (HR, 0.51; 95% CI, 0.44-0.60). Exposure to PM 2.5 (HR, 1.05; 95% CI, 1.00-1.09) and NO x (HR, 1.06; 95% CI, 1.02-1.10) was connected with increased all-cause mortality risk, and significant PM 2.5 -associated elevated risks for CVD mortality and NO x -associated elevated risks for respiratory disease mortality were observed. No obvious interaction between PA and PM 2.5 or NO x exposure was detected., Conclusions: Our study provides additional evidence that higher PA and lower air pollutant levels are independently connected with reduced mortality risk. The benefits of PA are not significantly affected by long-term air pollution exposure, indicating PA can be recommended to prevent mortality regardless of air pollution levels. Our findings highlight the importance of public health policies and interventions facilitating PA and reducing air pollution in reducing mortality risks and maximizing health benefits. Future investigation is urgently needed to identify these findings in areas with severe air pollution conditions., 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.)

Background: As a complementary means to urban public transit systems, public bike-sharing provides a green and active mode of sustainable mobility, while reducing carbon-dioxide emissions and promoting health. There has been increasing interest in factors affecting bike-sharing usage, but little is known about the effect of ambient air pollution., Method: To assess the short-term impact of daily exposure to multiple air pollutants (PM 2.5 , PM 10 , NO 2 , and O 3 ) on the public bike-sharing system (PBS) usage in Seoul, South Korea (2018-2021), we applied a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model (DLNM). The model was adjusted for day of the week, holiday, temperature, relative humidity, and long-term trend. We also conducted stratification analyses to examine the potential effect modification by age group, seasonality, and COVID-19., Results: We found that there was a negative association between daily ambient air pollution and the PBS usage level at a single lag day 1 (i.e., air quality a day before the event) across all four pollutants. Our results suggest that days with high levels of air pollutants (at 95th percentile) are associated with a 0.91% (0.86% to 0.96%) for PM 2.5 , 0.89% (0.85% to 0.94%) for PM 10 , 0.87% (0.82% to 0.91%) for O 3 , and 0.92% (0.87% to 0.98%) for NO 2 , reduction in cycling behavior in the next day compared to days with low levels of pollutants (at 25th percentile). No evidence of effect modification was found by seasonality, age nor the COVID-19 pandemic for any of the four pollutants., Conclusions: Our findings suggest that high concentrations of ambient air pollution are associated with decreased rates of PBS usage on the subsequent day regardless of the type of air pollutant measured., 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.)

Air pollution shares the attributes of multi-factorial influence and spatiotemporal complexity, leading to air pollution control assistance models easily falling into a state of failure. To address this issue, we design a framework containing improved data fusion method, novel grey incidence models and air pollution spatiotemporal analysis to analyze the complex characteristics of air pollution under the fusion of multiple factors. Firstly, we improve the existing data fusion method for multi-factor fusion. Subsequently, we construct two grey spatiotemporal incidence models to examine the spatiotemporal characteristics of multi-factorial air pollution in network relationships and changing trends. Furthermore, we propose two new properties that can manifest the performance of grey incidence analysis, and we provide detailed proof of the properties of the new models. Finally, in the Jing-Jin-Ji region, the novel models are used to study the network relationships and trend changes of air pollution. The findings are as follows: (1) Two highly polluted belts in the region require attention. (2) Although the air pollution network under multi-factorial fusion obeys the first law of geography, the network density and node density exhibit significant variations. (3) From 2013 to 2021, all pollutants except O 3 show improvement. (4) Recommendations for responses are presented based on the above-mentioned results. (5) The parameter analyses, model comparisons, Monte Carlo experiments and model feature summaries illustrate that the proposed models are practical, interpretable and considerably outperform various prevailing competitors with remarkable universality., 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.)

Background: Diabetic retinopathy (DR), one of the most common microvascular complications of diabetes mellitus (DM), is a major contributor of vision impairment and blindness worldwide. Studies have shown that air pollution exposure is adversely associated with DM. However, evidence is scarce regarding how air pollution exposure affects DR. This study aimed to investigate the association between ambient air pollution exposure and DR risk., Methods: The study population was based on the Fujian Eye Study (FJES), an ophthalmologic, epidemiologic survey investigating the eye health condition of residents in Fujian Province from 2018 to 2019. Daily average concentrations of ambient air pollutants (PM 2.5 , PM 10 , SO 2 , NO 2 , and O 3 ) were acquired from a high-resolution air quality dataset in China from 2013 to 2018. We used a logistic regression model to examine the associations between DR risk and long-term air pollution at various exposure windows., Results: A total of 2405 out of the 8211 participants were diagnosed with diabetes, among whom 183 had DR. Ambient air pollution, especially particulate matter (i.e., PM 2.5 and PM 10 ) and NO 2 were positively associated with DR prevalence among all the study subjects. Ambient SO 2 and O 3 concentrations were not associated with DR prevalence. PM 2.5 and NO 2 seemed to be borderline significantly associated with increased prevalence of DR in subjects with DM, especially under the model adjusted for sex, age, BMI, SBP, and DBP., Conclusions: These findings showed that long-term exposure to ambient particulate matter and NO 2 was associated with a high DR risk in Fujian province, where ambient air pollution is relatively low., 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.)

Objective: To explore the association between green space, multiple ambient air pollutants and depressive/anxiety symptoms and the mediating role of physical activity (PA) in Chinese adolescents., Method: A school-based health survey was conducted in eight provinces in China in 2021. 22,868 students aged 14.64 (±1.77) years completed standard questionnaires to record details of depressive, anxiety symptoms and PA. We calculated the average normalized difference vegetation index (NDVI) in circular buffers of 200 m, 500 m and 1000 m and estimated the concentrations of PM 10 , PM 2.5 , CO, NO 2 , O 3 , SO 2 around the adolescents' school addresses., Results: The exposure-response curves showed that the lower the NDVI value, the higher the risk of depressive and anxiety symptoms. CO, PM 2.5 and SO 2 and air pollution score were associated with increased risk of depressive and anxiety symptoms. NDVI in all circular buffers decreased the risk of depressive and anxiety symptoms at low levels of PA, but the associations were not significant at high levels of PA. In the subgroup analysis, PM 10 , PM 2.5 , CO, NO 2 , SO 2 , AQI and air pollution score increased the risk of depressive and anxiety symptoms at low PA levels, but the associations were not significant at high levels of PA. Mediation analysis indicated that the mediating effect of PA on the association between NDVI, NDVI-200 m NDVI-500 m, CO, PM 10 , PM 2.5 , SO 2 , AQI and depressive/anxiety symptoms was statistically significant（p < 0.05）., Conclusion: Middle-high level PA could reduce the strength of association between air pollution and depressive and anxiety symptoms. Meanwhile, the association between green space/air pollution and depressive/anxiety symptoms was partly mediated by PA., 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 this study, a hybrid model, the convolutional neural network-support vector regression model, was adopted to achieve prediction of the NO 2 profile in Nanjing from January 2019 to March 2021. Given the sudden decline in NO 2 in February 2020, the contribution of the Coronavirus Disease-19 (COVID-19) lockdown, Chinese New Year (CNY), and meteorological conditions to the reduction of NO 2 was evaluated. NO 2 vertical column densities (VCDs) from January to March 2020 decreased by 59.05% and 32.81%, relative to the same period in 2019 and 2021, respectively. During the period of 2020 COVID-19, the average NO 2 VCDs were 50.50% and 29.96% lower than those during the pre-lockdown and post-lockdown periods, respectively. The NO 2 volume mixing ratios (VMRs) during the 2020 COVID-19 lockdown significantly decreased below 400 m. The NO 2 VMRs under the different wind fields were significantly lower during the lockdown period than during the pre-lockdown period. This phenomenon could be attributed to the 2020 COVID-19 lockdown. The NO 2 VMRs before and after the CNY were significantly lower in 2020 than in 2019 and 2021 in the same period, which further proves that the decrease in NO 2 in February 2020 was attributed to the COVID-19 lockdown. Pollution source analysis of an NO 2 pollution episode during the lockdown period showed that the polluted air mass in the Beijing-Tianjin-Hebei was transported southwards under the action of the north wind, and the subsequent unfavorable meteorological conditions (local wind speed of < 2.0 m/sec) resulted in the accumulation of pollutants., 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 © 2023. Published by Elsevier B.V.)

Despite concerted efforts in emission control, air pollution control remains challenging. Urban planning has emerged as a crucial strategy for mitigating PM 2.5 pollution. What remains unclear is the impact of urban form and their interactions with seasonal changes. In this study, base on the air quality monitoring stations in the Yangtze River Delta urban agglomeration, the relationship between urban spatial indicators (building morphology and land use) and PM 2.5 concentrations was investigated using full subset regression and variance partitioning analysis, and seasonal differences were further analysed. Our findings reveal that PM 2.5 pollution exhibits different sensitivities to spatial scales, with higher sensitivity to the local microclimate formed by the three-dimensional structure of buildings at the local scale, while land use exerts greater influence at larger scales. Specifically, land use indicators contributed sustantially more to the PM 2.5 prediction model as buffer zone expand (from an average of 2.41% at 100 m range to 47.30% at 5000 m range), whereas building morphology indicators display an inverse trend (from an average of 13.84% at 100 m range to 1.88% at 5000 m range). These results enderscore the importance of considering building morphology in local-scale urban planning, where the increasing building height can significantly enhance the disperion of PM 2.5 pollution. Conversely, large-scale urban planning should prioritize the mixed use of green spaces and construction lands to mitigate PM 2.5 pollution. Moreover, the significant seasonal differences in the ralationship between urban spatical indicatiors and PM 2.5 pollution were observed. Particularly moteworthy is the heightened association between forest, water indicators and PM 2.5 concentrations in summer, indicating the urban forests may facilitate the formation of volatile compunds, exacerbating the PM 2.5 pollution. Our study provides a theoretical basis for addressing scale-related challenges in urban spatial planning, thereby forstering the sustainable development of cities., 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 Ltd.)

Despite the known link between air pollution and cause-specific mortality, its relation to chronic kidney disease (CKD)-associated mortality is understudied. Therefore, we investigated the association between long-term exposure to air pollution and CKD-related mortality in a large multicentre population-based European cohort. Cohort data were linked to local mortality registry data. CKD-death was defined as ICD10 codes N18-N19 or corresponding ICD9 codes. Mean annual exposure at participant's home address was determined with fine spatial resolution exposure models for nitrogen dioxide (NO 2 ), black carbon (BC), ozone (O 3 ), particulate matter ≤2.5 μm (PM 2.5 ) and several elemental constituents of PM 2.5 . Cox regression models were adjusted for age, sex, cohort, calendar year of recruitment, smoking status, marital status, employment status and neighbourhood mean income. Over a mean follow-up time of 20.4 years, 313 of 289,564 persons died from CKD. Associations were positive for PM 2.5 (hazard ratio (HR) with 95% confidence interval (CI) of 1.31 (1.03-1.66) per 5 μg/m 3 , BC (1.26 (1.03-1.53) per 0.5 × 10 - 5 /m), NO 2 (1.13 (0.93-1.38) per 10 μg/m 3 ) and inverse for O 3 (0.71 (0.54-0.93) per 10 μg/m 3 ). Results were robust to further covariate adjustment. Exclusion of the largest sub-cohort contributing 226 cases, led to null associations. Among the elemental constituents, Cu, Fe, K, Ni, S and Zn, representing different sources including traffic, biomass and oil burning and secondary pollutants, were associated with CKD-related mortality. In conclusion, our results suggest an association between air pollution from different sources and CKD-related mortality., 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.)

China's carbon emission trading policy plays a crucial role in achieving both its "3060" dual carbon objectives and the United Nations Sustainable Development Goal 13 (SDG 13) on climate action. The policy's effectiveness in reducing pollution and mitigating carbon emissions holds significant importance. This paper investigated whether China's carbon emission trading policy affects pollution reduction (PM 2.5 and SO 2 ) and carbon mitigation (CO 2 ) in pilot regions, using panel data from 30 provinces and municipalities in China from 2005 to 2019 and employing a multi-period difference-in-differences (DID) model. Furthermore, it analyzed the heterogeneity of carbon market mechanisms and regional variations. Finally, it examined the governance pathways for pollution reduction and carbon mitigation from a holistic perspective. The results indicate that: (1) China's carbon emission trading policy has reduced CO 2 emissions by 18% and SO 2 emissions by 36% in pilot areas, with an immediate impact on the "carbon mitigation" effect, while the "pollution reduction" effect exhibits a time lag. (2) Higher carbon trading prices lead to stronger "carbon mitigation" effect, and larger carbon market scales are associated with greater "pollution reduction" effects on PM 2.5 . Governance effects on pollution reduction and carbon mitigation vary among pilot regions: Carbon markets of Beijing, Chongqing, Shanghai, and Tianjin show significant governance effects in both "pollution reduction" and "carbon mitigation", whereas Guangdong's carbon market exhibits only a "pollution reduction" effect, and Hubei's carbon market demonstrates only a "carbon mitigation" effect. (3) Currently, China's carbon emission trading policy achieves pollution reduction and carbon mitigation through "process management" and "end-of-pipe treatment". This study could provide empirical insights and policy implications for pollution reduction and carbon mitigation, as well as for the development of China's carbon emission trading market., 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.)

Fine particulate matter (PM 2.5 ) harms human health and hinders normal human life. Considering the serious complexity and obvious regional characteristics of PM 2.5 pollution, it is urgent to fill in the comprehensive overview of regional characteristics and interannual evolution of PM 2.5 . This review studied the PM 2.5 pollution in six typical areas between 2014 and 2022 based on the data published by the Chinese government and nearly 120 relevant literature. We analyzed and compared the characteristics of interannual and quarterly changes of PM 2.5 concentration. The Beijing-Tianjin-Hebei region (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) made remarkable progress in improving PM 2.5 pollution, while Fenwei Plain (FWP), Sichuan Basin (SCB) and Northeast Plain (NEP) were slightly inferior mainly due to the relatively lower level of economic development. It was found that the annual average PM 2.5 concentration change versus year curves in the three areas with better pollution control conditions can be merged into a smooth curve. Importantly, this can be fitted for the accurate evaluation of each area and provide reliable prediction of its future evolution. In addition, we analyzed the factors affecting the PM 2.5 in each area and summarize the causes of air pollution in China. They included primary emission, secondary generation, regional transmission, as well as unfavorable air dispersion conditions. We also suggested that the PM 2.5 pollution control should target specific industries and periods, and further research need to be carried out on the process of secondary production. The results provided useful assistance such as effect prediction and strategy guidance for PM 2.5 pollution control in Chinese backward areas., 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.)

Several studies have linked air pollution to COVID-19 morbidity and severity. However, these studies do not account for exposure levels to SARS-CoV-2, nor for different sources of air pollution. We analyzed individual-level data for 8.3 million adults in the Netherlands to assess associations between long-term exposure to ambient air pollution and SARS-CoV-2 infection (i.e., positive test) and COVID-19 hospitalisation risks, accounting for spatiotemporal variation in SARS-CoV-2 exposure levels during the first two major epidemic waves (February 2020-February 2021). We estimated average annual concentrations of PM 10 , PM 2.5 and NO 2 at residential addresses, overall and by PM source (road traffic, industry, livestock, other agricultural sources, foreign sources, other Dutch sources), at 1 × 1 km resolution, and weekly SARS-CoV-2 exposure at municipal level. Using generalized additive models, we performed interval-censored survival analyses to assess associations between individuals' average exposure to PM 10 , PM 2.5 and NO 2 in the three years before the pandemic (2017-2019) and COVID-19-outcomes, adjusting for SARS-CoV-2 exposure, individual and area-specific confounders. In single-pollutant models, per interquartile (IQR) increase in exposure, PM 10 was associated with 7% increased infection risk and 16% increased hospitalisation risk, PM 2.5 with 8% increased infection risk and 18% increased hospitalisation risk, and NO 2 with 3% increased infection risk and 11% increased hospitalisation risk. Bi-pollutant models suggested that effects were mainly driven by PM. Associations for PM were confirmed when stratifying by urbanization degree, epidemic wave and testing policy. All emission sources of PM, except industry, showed adverse effects on both outcomes. Livestock showed the most detrimental effects per unit exposure, whereas road traffic affected severity (hospitalisation) more than infection risk. This study shows that long-term exposure to air pollution increases both SARS-CoV-2 infection and COVID-19 hospitalisation risks, even after controlling for SARS-CoV-2 exposure levels, and that PM may have differential effects on these COVID-19 outcomes depending on the emission source., 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.)

Background: Currently, air pollution is suggested as a risk factor for depressive episodes. Our study aimed to consider multiple air pollutants simultaneously, and continuously evaluate air pollutants using comprehensive air quality index (CAI) with depressive episode risk., Methods: Using a nationally representative sample survey from South Korea between 2014 and 2020, 20,796 participants who underwent health examination and Patient Depression Questionnaire-9 were included in the study. Six air pollutants (PM 10 , PM 2.5 , O 3 , CO, SO 2 , NO 2 ) were measured for the analysis. Every air pollutant was standardized by air quality index (AQI) and CAI was calculated for universal representation. Using logistic regression, short- and medium-term exposure by AQI and CAI with the risk of depressive episode was calculated by odds ratio and 95 % confidence interval (CI). Furthermore, consecutive measurements of CAI over 1-month time intervals were evaluated with the risk of depressive episodes. Every analysis was conducted seasonally., Results: There were 950 depressive episodes occurred during the survey. An increase in AQI for short-term exposure (0-30 days) showed higher risk of depressive episode in CO, while medium-term exposure (0-120 days) showed higher risk of depressive episode in CO, SO 2 , PM 2.5 , and PM 10 . During the cold season, the exposure to at least one abnormal CAI within 1-month intervals over 120 days was associated with a 68 % (95 % CI 1.11-2.54) increase in the risk of depressive episode., Conclusions: Short- and medium-term exposure of air pollution may be associated with an increased risk of depressive episodes, especially for cold season., 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 B.V. All rights reserved.)

Background: Disruption of thyroid function can profoundly affect various organ systems. However, studies on the association between air pollution and thyroid function are relatively scarce and most studies have focused on the long-term effects of air pollution among pregnant women., Objectives: This study aimed to explore the associations between short-term exposure to air pollution and thyroid function in the general population., Methods: Data from the Korea National Health and Nutrition Examination Survey (2013-2015) were analyzed (n = 5,626). Air pollution concentrations in residential addresses were estimated using Community Multiscale Air Quality models. The moving averages of air pollution over 7 days were set as exposure variables through exploratory analyses. Linear regression and quantile g-computation models were constructed to assess the effects of individual air pollutants and air pollution mixture, respectively., Results: A 10-ppb increase in NO 2 (18.8-μg/m 3 increase) and CO (11.5-μg/m 3 increase) was associated with 2.43% [95% confidence interval (CI): 0.42, 4.48] and 0.19% (95% CI: 0.01, 0.36) higher thyroid-stimulating hormone (TSH) levels, respectively. A 10-μg/m 3 increase in PM 2.5 and a 10-ppb increase in O 3 (19.6-μg/m 3 increment) were associated with 0.87% (95% CI: 1.47, -0.27) and 0.59% (95% CI: 1.18, -0.001) lower free thyroxine (fT4) levels, respectively. A simultaneous quartile increase in PM 2.5 , NO 2 , O 3 , and CO levels was associated with lower fT4 but not TSH levels., Conclusions: As the subtle changes in thyroid function can affect various organ systems, the present results may have substantial public health implications despite the relatively modest effect sizes. Because this was a cross-sectional study, it is necessary to conduct further experimental or repeated-measures studies to consolidate the current results., 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.)

Background: The connections between fine particulate matter (PM 2.5 ) and coarse particulate matter (PM 2.5-10 ) and daily mortality of viral pneumonia and bacterial pneumonia were unclear., Objectives: To distinguish the connections between PM 2.5 and PM 2.5-10 and daily mortality due to viral pneumonia and bacterial pneumonia., Methods: Using a comprehensive national death registry encompassing all areas of mainland China, we conducted a case-crossover investigation from 2013 to 2019 at an individual level. Residential daily particle concentrations were evaluated using satellite-based models with a spatial resolution of 1 km. To analyze the data, we employed the conditional logistic regression model in conjunction with polynomial distributed lag models., Results: We included 221,507 pneumonia deaths in China. Every interquartile range (IQR) elevation in concentrations of PM 2.5 (lag 0-2 d, 37.6 μg/m 3 ) was associated with higher magnitude of mortality for viral pneumonia (3.03%) than bacterial pneumonia (2.14%), whereas the difference was not significant (p-value for difference = 0.38). An IQR increase in concentrations of PM 2.5-10 (lag 0-2 d, 28.4 μg/m 3 ) was also linked to higher magnitude of mortality from viral pneumonia (3.06%) compared to bacterial pneumonia (2.31%), whereas the difference was not significant (p-value for difference = 0.52). After controlling for gaseous pollutants, their effects were all stable; however, with mutual adjustment, the associations of PM 2.5 remained, and those of PM 2.5-10 were no longer statistically significant. Greater magnitude of associations was noted in individuals aged 75 years and above, as well as during the cold season., Conclusion: This nationwide study presents compelling evidence that both PM 2.5 and PM 2.5-10 exposures could increase pneumonia mortality of viral and bacterial causes, highlighting the more robust effects of PM 2.5 and somewhat higher sensitivity of viral pneumonia., 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.)

The COVID-19 pandemic has reinforced an interest in the relationship between air pollution and respiratory viral infections, indicating that their burden can be increased under poor air quality. This paper reviews the pathways through which air pollutants can enhance susceptibility to such infections and aggravate their clinical course and outcome. It also summarizes the research exploring the links between various viral infections and exposure to solid and gaseous pollution in Poland, a region characterized by poor air quality, especially during a heating season. The majority of studies focused on concentrations of particulate matter (PM; 86.7%); the other pollutants, i.e., BaP, benzene, CO, NO x , O 3 , and SO 2, were studied less often and sometimes only in the context of a particular infection type. Most research concerned COVID-19, showing that elevated levels of PM and NO 2 correlated with higher morbidity and mortality, while increased PM 2.5 and benzo[a]pyrene levels were related to worse clinical course and outcome in hospitalized, regardless of age and dominant SARS-CoV-2 variant. PM 10 and PM 2.5 levels were also associated with the incidence of influenza-like illness and, along with NO 2 concentrations, with a higher rate of children's hospitalizations due to lower respiratory tract RSV infections. Higher levels of air pollutants also increased hospitalization due to bronchitis (PM, NO x , and O 3 ) and emergency department admission due to viral croup (PM 10 , PM 2.5 , NO x , CO, and benzene). Although the conducted studies imply only correlations and have other limitations, as discussed in the present paper, it appears that improving air quality through reducing combustion processes in energy production in Poland should be perceived as a part of multilayered protection measures against respiratory viral infections, decreasing the healthcare costs of COVID-19, lower tract RSV infections, influenza, and other respiratory viral diseases prevalent between autumn and early spring, in addition to other health and climate benefits., 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: Sickle cell disease (SCD) is a genetic disorder and symptoms may be sensitive to environmental stressors. Although it has been hypothesized that exposure to outdoor air pollution could trigger acute SCD events, evidence is limited., Methods: We obtained SCD administrative data on hospital encounters in South Carolina from 2002 to 2019. We estimated outdoor air pollutant (particulate matter<2.5 μm (PM 2.5 ), ozone (O 3 ), and PM 2.5 elemental carbon (EC) concentrations at residential zip codes using spatio-temporal models. Using a random bi-directional, fixed-interval case-crossover study design, we investigated the relationship between air pollution exposure over 1-, 3-, 5-, 9-, and14-day periods with SCD hospital encounters., Results: We studied 8410 patients with 144,129 hospital encounters. We did not observe associations among all patients with SCD and adults for PM 2.5 , O 3 , and EC. We observed positive associations among children for 9- and 14-day EC (OR: 1.05 (95% confidence interval (CI): 1.02, 1.08) and OR: 1.05 (95% CI: 1.02, 1.09), respectively) and 9- and 14-day O 3 (OR: 1.04 (95%CI: 1.00, 1.08)) for both., Conclusions: Our findings suggest that short-term (within two-weeks) levels of EC and O 3 and may be associated with SCD hospital encounters among children. Two-pollutant model results suggest that EC is more likely responsible for effects on SCD than O 3 . More research is needed to confirm our findings., 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.)

Background: Prenatal air pollution exposure has been associated with individual inflammatory, cardiovascular, and metabolic biomarkers in mothers and neonates. However, studies of air pollution and a comprehensive panel of biomarkers across maternal and cord blood samples remain limited. Few studies used data-driven methods to identify biomarker groupings that converge biomarkers from multiple biological pathways. This study aims to investigate the impacts of prenatal air pollution on groups of biomarkers in maternal and cord blood samples., Methods: In the Maternal And Developmental Risks from Environmental and Social Stressors (MADRES) cohort, 87 biomarkers were quantified from 45 trimester 1 maternal blood and 55 cord blood samples. Pregnancy and trimester 1-averaged concentrations of particulate matter ≤2.5 μm and ≤10 μm in diameter (PM 2.5 and PM 10 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) were estimated, using inverse distance squared weighted spatial interpolation from regulatory air monitoring stations. Traffic-related NO x was assessed using California Line Source Dispersion Model: freeway/highway roads, non-freeway major roads, non-freeway minor roads, and their sum as total NOx. Elastic Net (EN) regression within the rexposome R package was used to group biomarkers and assess their associations with air pollution., Results: In maternal samples, trimester 1-averaged PM 10 was associated with elevated inflammation biomarkers and lowered cardiovascular biomarkers. NO 2 exhibited positive associations with cardiovascular and inflammation markers. O 3 was inversely associated with inflammation, metabolic, and cardiovascular biomarkers. In cord blood, pregnancy-averaged PM 2.5 was associated with higher cardiovascular biomarkers and lower metabolic biomarkers. PM 10 was associated with lower inflammation and higher cardiovascular biomarkers. Total and major road NOx was associated with lower cardiovascular biomarkers., Conclusion: Prenatal air pollution exposure was associated with changes in biomarkers related to inflammation, cardiovascular, metabolic, cancer, and neurological function in both mothers and neonates. This study shed light on mechanisms by which air pollution can influence biological function during pregnancy., 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.)

Exposure to outdoor particulate matter (PM 2.5 ) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM 2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM 2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM 2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM 2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age., 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: Exposure to ambient air pollution is associated with a significant number of deaths. Much of the evidence associating air pollution with adverse effects is from North American and Europe, partially due to incomplete data in other regions limiting location specific examinations. The aim of the current paper is to leverage satellite derived air quality data to examine the relationship between ambient particulate matter and all-cause and cause-specific mortality in Asia., Methods: Six cohorts from the Asia Cohort Consortium provided residential information for participants, recruited between 1991 and 2008, across six countries (Bangladesh, India, Iran, Japan, South Korea, and Taiwan). Ambient particulate material (PM 2·5 ) levels for the year of enrolment (or 1998 if enrolled earlier) were assigned utilizing satellite and sensor-based maps. Cox proportional models were used to examine the association between ambient air pollution and all-cause and cause-specific mortality (all cancer, lung cancer, cardiovascular and lung disease). Models were additionally adjusted for urbanicity (representing urban and built characteristics) and stratified by smoking status in secondary analyses. Country-specific findings were pooled via random-effects meta-analysis., Findings: More than 300,000 participants across six cohorts were included, representing more than 4-million-person years. A positive relationship was observed between a 5 µg/m (Dockery et al., 1993) increase in PM 2·5 and cardiovascular mortality (HR: 1·06, 95 % CI: 0.99, 1·13). The additional adjustment for urbanicity resulted in increased associations between PM 2.5 and mortality outcomes, including all-cause mortality (1·04, 95 % CI: 0·97, 1·11). Results were generally similar regardless of whether one was a current, never, or ex-smoker., Interpretation: Using satellite and remote sensing technology we showed that associations between PM 2.5 and all-cause and cause-specific Hazard Ratios estimated are similar to those reported for U.S. and European cohorts., Funding: This project was supported by the Health Effects Institute. Grant number #4963-RFA/18-5. Specific funding support for individual cohorts is described in the Acknowledgements., 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 and Aim: The increasing prevalence of precocious puberty (PP) has emerged as a significant medical and social problem worldwide. However, research on the relationship between long-term air pollution exposure and PP has been relatively limited. We thus investigated the association between long-term air pollution exposure and the onset of PP in South Korea., Methods: We investigated a retrospective cohort using the Korea National Health Insurance Database. Six-year-old children born from 2007 to 2009 were examined (2013-2015). We included boys ≤10 years and girls aged ≤9 years who visited hospitals for early pubertal development, were diagnosed with PP per the ICD-10 (E228, E301, and E309), and received gonadotropin-releasing hormone agonist treatment. We analyzed data for boys up until 10 years old (60-month follow-up) and for girls up to 9 years old (48-month follow-up). We assessed the association between long-term air pollution exposure and the onset of PP using a Cox proportional hazard model. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) per 1 μg/m 3 increase in fine particulate matter (PM 2.5 ) and particulate matter (PM 10 ) and per 1 ppb increase in sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), and ozone (O 3 )., Results: This study included 1,205,784 children aged six years old between 2013 and 2015. A positive association was found between the 48-month moving average PM 2.5 (HR: 1.019; 95% CI: 1.012, 1.027), PM 10 (HR: 1.009; 95% CI: 1.006, 1.013), SO 2 (HR: 1.037; 95% CI: 1.018, 1.055), and O 3 (HR: 1.006; 95% CI: 1.001, 1.010) exposure and PP in girls but not boys., Conclusions: This study provides valuable insights into the harmful effects of air pollution during childhood and adolescence, emphasizing that air pollution is a risk factor that should be managed and reduced., 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.)

Background: Previous research has shown that lack of leisure activities, either outdoor or social activities, impedes cognitive function. However, the interrelationship between poor cognition and deficient activities is understudied. In addition, whether exposure to air pollution, such as PM 2.5 , can accelerate the detrimental 'inactivity-poor cognition' cycle, is worthy of investigation., Methods: We used data from the 2008, 2011, 2014, and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). We assessed the frequency of outdoor or social activities at each wave. The cognitive function was examined using a China-Modified Mini-mental State Examination. We estimated the residential exposure to fine particular matter (PM 2.5 ) via a satellite-based model. We applied cross-lagged panel (CLP) model to examine the bi-directional relationship between outdoor or social activities and cognitive function. We then examined the effect of PM 2.5 exposure with sequent cognitive function and activities using generalized estimation equation (GEE) model., Findings: Overall, we observed significant bi-directional associations between outdoor or social activities and cognitive function. Participants with better cognitive function in the last wave were more likely to engage in outdoor or social activities in the following wave (outdoor activities: β = 0.37, 95% CI [0.27,0.48], P < 0.01; social activities: β = 0.05, 95% CI [0.02,0.09] P < 0.01). Meanwhile, higher engagement in outdoor or social activities in the last wave was associated with more favorable cognitive function in the following wave (outdoor activities: β = 0.06, 95% CI [0.03,0.09], P < 0.01; social activities: β = 0.10, 95% CI [0.03,0.18], P < 0.01). Notably, an increase in PM 2.5 exposure during the preceding year was significantly associated with a declining cognitive function (β = -0.05, 95% CI [-0.08,-0.03], P < 0.01), outdoor activities (β = -0.02, 95% CI [-0.04, -0.01], P < 0.01) and social activities (β = -0.02, 95% CI [-0.02, -0.01], P < 0.01) in the current year; the lagged effects of the PM 2.5 exposure in the past year of the last wave on activities and cognitive function of the following wave were also observed., Interpretation: Our findings not only indicate the bi-directional links between the frequency of outdoor or social activities and cognitive function, but also report that PM 2.5 exposure plays a role in catalyzing the detrimental inactivity-poor cognition cycle. Future research should investigate whether the policy-driven interventions, such as clean air policies, can break the unfavorable activity-cognition cycle, and thereby promoting health from the dual gains in leisure activities and cognition., 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.)

The complex air pollution driven by both Ozone (O 3 ) and fine particulate matter (PM 2.5 ) significantly influences the air quality in the Sichuan Basin (SCB). Understanding the O 3 formation during autumn and winter is necessary to understand the atmospheric oxidative capacity. Therefore, continuous in-site field observations were carried out during the late summer, early autumn and winter of 2020 in a rural area of Chongqing. The total volatile organic compounds (VOCs) concentration reported by a Proton-Transfer-Reaction Time-of-Flight Mass Spectrometry (PTR-ToF-MS) were 13.66 ± 9.75 ppb, 5.50 ± 2.64 ppb, and 9.41 ± 5.11 ppb in late summer, early autumn and winter, respectively. The anthropogenic VOCs (AVOCs) and biogenic VOCs (BVOCs) were 8.48 ± 7.92 ppb and 5.18 ± 2.99 ppb in late summer, 3.31 ± 1.89 ppb and 2.19 ± 0.93 ppb in autumn, and 6.22 ± 3.99 ppb and 3.20 ± 1.27 ppb in winter. A zero-dimensional atmospheric box model was employed to investigate the sensitivity of O 3 -precursors by relative incremental reactivity (RIR). The RIR values of AVOCs, BVOCs, carbon monoxide (CO), and nitrogen oxides (NO x ) were 0.31, 0.71, 0.09, and -0.36 for late summer, 0.24, 0.59, 0.22, and -0.38 for early autumn, and 0.30, 0.64, 0.33 and -0.70 for winter, and the results showed that the O 3 formation of sampling area was in the VOC-limited region, and O 3 was most sensitive to BVOCs (with highest RIR values, > 0.6). This study can be helpful in understanding O 3 formation and interpreting the secondary formation of aerosols in the winter., 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 © 2023. Published by Elsevier B.V.)

Background: Depression prevalence has surged within the labor force population in recent years. While links between air pollutants and depression were explored, there was a notable scarcity of research focusing on the workforce., Methods: This nationwide longitudinal study analyzed 27,457 workers aged 15-64. We estimated monthly mean concentrations of fine particulate matter (PM 2.5 ), its primary components, and Ozone (O 3 ) at participants' residences using spatiotemporal models. To assess the relationship between short- (1 to 3 months) and long-term (1 to 2 years) exposure to various air pollutants and depressive levels and occurrences, we employed linear mixed-effects models and mixed-effects logistic regression. We considered potential occupational moderators, such as labor contracts, overtime compensation, and total annual income., Results: We found significant increases in depression risks within the workforce linked to both short- and long-term air pollution exposure. A 10 μg/m 3 rise in 2-year average PM 2.5 , black carbon (BC), and O 3 concentrations correlated with increments in depressive scores of 0.009, 0.173, and 0.010, and a higher likelihood of depression prevalence by 0.5 %, 12.6 %, and 0.7 %. The impacts of air pollutants and depression were more prominent in people without labor contracts, overtime compensation, and lower total incomes., Conclusion: Exposures to air pollutants could increase the risk of depression in the labor force population. The mitigating effects of higher income, benefits, and job security against depression underscore the need for focused mental health interventions., 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 B.V. All rights reserved.)

The objective of this study is to evaluate long-term changes in the level of exposure to NO 2 among the population living in the urban area of Naples (south Italy). This has been achieved by integrating data from the regional reference monitoring network with information collected during the citizen science initiative called 'NO 2 , NO grazie!' conducted in February 2020 and coordinated by the Non-Governmental Organisation 'Cittadini per l'aria'. This citizen science campaign was based on low-cost passive samplers (Palmes tubes), providing the ability to obtain unprecedented high-resolution NO 2 levels. Using a Land Use Random Forest (LURF), we extrapolated the experimental data obtained from the citizen science campaign and evaluated the changes in population exposure from 2013 to 2022 and the uncertainty associated with this assessment was quantified. The results indicate that a large proportion of the inhabitants of Naples are still exposed to high NO 2 concentrations, even if strict emission containment measures are enforced. The average levels remain higher than the new interim and air quality targets suggested by the World Health Organisation. The implementation of co-created citizen science projects, where NGO and citizens actively participate alongside scientists, can significantly improve the estimation and the interpretation of official reference data., 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 Author(s). Published by Elsevier B.V. All rights reserved.)

This study examines the influence of meteorological factors and air pollutants on the performance of automatic pollen monitoring devices, as part of the EUMETNET Autopollen COST ADOPT-intercomparison campaign held in Munich, Germany, during the 2021 pollen season. The campaign offered a unique opportunity to compare all automatic monitors available at the time, a Plair Rapid-E, a Hund-Wetzlar BAA500, an OPC Alphasense, a KH-3000 Yamatronics, three Swisens Polenos, a PollenSense APS, a FLIR IBAC2, a DMT WIBS-5, an Aerotape Sextant, to the average of four manual Hirst traps, under the same environmental conditions. The investigation aimed to elucidate how meteorological factors and air pollution impact particle capture and identification efficiency. The analysis showed coherent results for most devices regarding the correlation between environmental conditions and pollen concentrations. This reflects on one hand, a significant correlation between weather and airborne pollen concentration, and on the other hand the capability of devices to provide meaningful data under the conditions under which measurements were taken. However, correlation strength varied among devices, reflecting differences in design, algorithms, or sensors used. Additionally, it was observed that different algorithms applied to the same dataset resulted in different concentration outputs, highlighting the role of algorithm design in these systems (monitor + algorithm). Notably, no significant influence from air pollutants on the pollen concentrations was observed, suggesting that any potential difference in effect on the systems might require higher air pollution concentrations or more complex interactions. However, results from some monitors were affected to a minor degree by specific weather variables. Our findings suggest that the application of real-time devices in urban environments should focus on the associated algorithm that classifies pollen taxa. The impact of air pollution, although not to be excluded, is of secondary concern as long as the pollution levels are similar to a large European city like Munich., 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 B.V. All rights reserved.)

Air pollution poses a significant threat to public health, while biogenic volatile organic compounds (BVOCs) play a crucial role in both aspects. However, the unclear relationship between BVOCs and air pollutants in the under-canopy space limits the accuracy of air pollution control and the exploitation of forest healthcare functions. To clarify the variation of BVOCs in forest therapy bases, and their impacts on ozone (O 3 ) and fine particulate matter (PM 2.5 ) at nose height, total VOCs (TVOCs) in the forest were collected during typical sunny days, while air pollutants and meteorological factors were observed simultaneously. The results showed that the branch-level emissions of P. tabuliformis were dominated by healthcare-effective monoterpenoids, with only α-pinene having relative air concentrations of over 5 % in forest air samples. The correlation between concentrations of under-canopy TVOCs and emission rates of BVOCs from P. tabuliformis was weak (p > 0.09) in all seasons. However, the correlation between concentrations of TVOCs and the concentrations of O 3 and PM 2.5 showed clear seasonal differences. In spring, TVOCs only showed a significant negative correlation with PM 2.5 in the forest (p < 0.01). In summer and autumn, TVOCs were significantly negatively correlated with both O 3 (p < 0.001) and PM 2.5 (p < 0.01). Specifically, the negative linear relationships were more pronounced for O 3 and oxygenated VOCs in autumn (R 2  = 0.40, p < 0.001) than for other relationships. The relationship between air pollutant concentrations inside and outside the forest also showed significant seasonal differences, generally characterized by a weaker correlation between them during seasons of strong emissions. Therefore, BVOCs in coniferous forests are health functions as they can provide healthcare effects and mitigate the concentration of air pollutants in the forest, and the establishment of forest therapy bases in rural areas with low NO x can be a sensible approach to promote good health, well-being, and sustainable 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 B.V. All rights reserved.)

Since 2000, China has faced severe air pollution challenges，prompting the initiation of comprehensive emission control measures post-2013. The subsequent implementation of these measures has led to remarkable enhancements in air quality. This study aims to enhance our understanding of the long-term trends in fine particulate matter (PM 2.5 ) and gaseous pollutants of ozone (O 3 ) and nitrogen dioxide (NO 2 ) across China from 2000 to 2020. Utilizing the Community Multiscale Air Quality (CMAQ) model, we conducted a nationwide analysis of air quality, systematically quantifying model predictions against observations for pollutants. The CMAQ model effectively captured the trends of air pollutants, meeting recommended performance benchmarks. The findings reveal variations in pollutant concentrations, with initial increases in PM 2.5 followed by a decline after 2013. The proportion of the population living in high PM 2.5 concentrations (>75 μg/m 3 ) decreased to <5 % after 2015. However, during the period from 2017 to 2020, around 40 % of the population continued to live in regions that did not meet the criteria for Chinese air quality standards (35 μg/m 3 ). From 2000 to 2019, fewer than 20 % of the population met the WHO standard (100 μg/m 3 ) for MDA8 O 3 . In 2000, 77 % of the population met the NO 2 standard (<20 μg/m 3 ), a figure that declined to 60 % between 2005 and 2014, nearly reaching 70 % in 2020. This study offers a comprehensive analysis of the changes in pollutants and public exposure in 2000-2020. It serves as a foundational resource for future efforts in air pollution control and health 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 Elsevier B.V. All rights reserved.)

Introduction: Vehicle emissions have become an important source of urban air pollution, and the assessment of air pollution emission characteristics and health effects caused by specific pollution sources can provide scientific basis for air quality management., Methods: In this paper, vehicle PM 2.5 pollution in typical urban agglomerations of China (the Beijing-Tianjin-Hebei urban agglomeration (BTHUA), the triangle of the Central China urban agglomeration (TCCUA) and the Chengdu-Chongqing urban agglomeration (CCUA)) were used as research samples to evaluate the emission characteristics, health effects and economic losses of vehicle PM 2.5 pollution based on the emission inventory, air quality model and exposure-response function from 2010 to 2020., Results: The results indicated that PM 2.5 emissions from vehicles in the three urban agglomerations during 2010-2020 first showed an upward yearly trend and then showed a slow decrease in recent years. Heavy-duty trucks and buses are the main contribution vehicles of PM 2.5 , and the contribution rates of light-duty vehicles to PM 2.5 is increasing year by year. The contribution rate of PM 2.5 in Beijing decreased significantly. In addition to capital cities and municipalities directly under the central Government, the emission of pollutants in other cities cannot be ignored. The evaluation results of the impact of PM 2.5 pollution from vehicles on population health show that: the number of each health endpoint caused by PM 2.5 pollution from vehicles in the BTHUA and CCUA showed an overall upward trend, while the TCCUA showed a downward trend in recent years. Among them, PM 2.5 pollution from vehicles in the three major urban agglomerations cause about 78,200 (95% CI: 20,500-138,800) premature deaths, 122,800 (95% CI: 25,600-220,500) inpatients, and 628,400 (95% CI: 307,400-930,400) outpatients and 1,332,400 (95% CI: 482,700-2,075,600) illness in 2020. The total health economic losses caused by PM 2.5 pollution from vehicles in the three major urban agglomerations in 2010, 2015 and 2020 were 68.25 billion yuan (95% CI: 21.65-109.16), 206.33 billion yuan (95% CI: 66.20-326.20) and 300.73 billion yuan (95% CI: 96.79-473.16), accounting for 0.67% (95% CI: 0.21-1.07%), 1.19% (95% CI: 0.38%-1.88%) and 1.21% (95% CI: 0.39%-1.90%) of the total GDP of these cities., Discussion: Due to the differences in vehicle population, PM 2.5 concentration, population number and economic value of health terminal units, there are differences in health effects and economic losses among different cities in different regions. Among them, the problems of health risks and economic losses were relatively prominent in Beijing, Chengdu, Chongqing, Tianjin and Wuhan., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Song and Hao.)

This paper is aimed at developing an air quality monitoring system using machine learning (ML), Internet of Things (IoT), and other elements to predict the level of particulate matter and gases in the air based on the air quality index (AQI). It is an air quality assessor and therefore a means of achieving the Sustainable Development Goals (SDGs), in particular, SDG 3.9 (substantial reduction of the health impacts of hazardous substances) and SDG 11.6 (reduction of negative impacts on cities and populations). AQI quantifies and informs the public about air pollutants and their adverse effects on public health. The proposed air quality monitoring device is low-cost and operates in real-time. It consists of a hardware unit that detects various pollutants to assess air quality as well as other airborne particles such as carbon dioxide (CO 2 ), methane (CH 4 ), volatile organic compounds (VOCs), nitrogen dioxide (NO 2 ), carbon monoxide (CO), and particulate matter with an aerodynamic diameter of 2.5 microns or less (PM 2.5 ). To predict air quality, the device was deployed from November 1, 2022, to February 4, 2023, in certain bauxite-rich areas of Adamawa and certain volcanic sites in western Cameroon. Therefore, machine learning algorithm models, namely, multiple linear regression (MLR), support vector regression (SVR), random forest regression (RFR), XGBoost (XGB), and K-nearest neighbors (KNN) were applied to analyze the collected concentrations and predict the future state of air quality. The performance of these models was evaluated using mean absolute error (MAE), coefficient of determination (R-square), and root mean square error (RMSE). The obtained data in this study show that these pollutants are present in selected localities albeit to different extents. Moreover, the AQI values obtained range from 10 to 530, with a mean of 132.380 ± 63.705, corresponding to moderate air quality state but may induce an adverse effect on sensitive members of the population. This study revealed that XGB regression performed better in air quality forecasting with the highest R-squared (test score of 0.9991 and train score of 0.9999) and lowest RMSE (test score of 1.5748 and train score of 0. 0073) and MAE (test score of 0.0872 and train score of 0.0020), while the KNN model had the worst prediction (lowest R-squared and highest RMSE and MAE). This embryonic work is a prototype for projects in Cameroon as measurements are underway for a national spread over a longer period of time., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

This study performed a back-trajectory analysis to determine the influence of transboundary transport on the extent of aerosol pollution in South Korea, based on 5-year PM 2.5 measurements (2015-2019) in five cities covering South Korea. A transboundary transport case was selected if a back trajectory passed over a dedicated region (BOX 1 and BOX 2) in the Yellow Sea. First, we found that the frequency of transboundary transport largely increases in the high pollution case, and this pattern is almost consistent for all months and all five cities, indicating the importance of investigating the horizontal direction of air mass movement associated with PM 2.5 , which has been discussed extensively in previous studies. In this study, we also examined the altitude change and straight moving distance (defined as travel distance) of back trajectories regarding the extent of local PM 2.5 . Consequently, we found that back trajectories in high aerosol pollution showed much lower altitudes and shorter travel differences, implying a significant contribution of surface emissions and stagnant air conditions to severe aerosol pollution. As a result, the local PM 2.5 level was not significantly enhanced when the air mass passed over the Yellow Sea if transboundary transport occurred at high altitudes with rapid movement (i.e., high altitude and long travel distance back-trajectory). Based on these results, we suggest utilizing the combined information of the horizontal direction, altitude variation, and length of back trajectories to better evaluate transboundary transport., 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.)

Air pollution in China has becoming increasingly serious in recent years with frequent incidents of smog. Parts of southwest China still experience high incidents of smog, with PM 2.5 (particulate matter with diameter ≤2.5 μm) being the main contributor. Establishing the spatial distribution of PM 2.5 in Southwest China is important for safeguarding regional human health, environmental quality, and economic development. This study used remote sensing (RS) and geographical information system (GIS) technologies and aerosol optical depth (AOD), digital elevation model (DEM), normalized difference vegetation index (NDVI), population density, and meteorological data from January to December 2018 for southwest China. PM 2.5 concentrations were estimated using ordinary least squares regression (OLS), geographic weighted regression (GWR) and geographically and temporally weighted regression (GTWR). The results showed that: (1) Eight influencing factors showed different correlations to PM 2.5 concentrations. However, the R 2 values of the correlations all exceeded 0.3, indicating a moderate degree of correlation or more; (2) The correlation R 2 values between the measured and remote sensed estimated PM 2.5 data by OLS, GWR, and GTWR were 0.554, 0.713, and 0.801, respectively; (3) In general, the spatial distribution of PM 2.5 in southwest of China decreases from the Northeast to Northwest, with moderate concentrations in the Southeast and Southwest; (4) The seasonal average PM 2.5 concentration is high in winter, low in summer, and moderate in spring and autumn, whereas the monthly average shows a "V" -shaped oscillation change., 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.)