Particulate Research Articles

Association of ambient particulate matter (PM2.5) with reduced sex ratio at birth after the implementation of a rapid transit system in Taipei, Taiwan

ABSTRACT Sex ratio at birth (SRB) is a simple, noninvasive way to monitor the reproductive health of a population. Apparently only a few studies have assessed the relationship between ambient air pollution and SRBs. The studies that investigated this relationship have yielded inconsistent results. Ambient air pollution levels, including particulate matter (PM2.5) levels, have decreased in Taipei city after a mass rapid transit (MRT) system commenced operations in 1996. The aim of this study was to determine whether the changes in levels of PM2.5 after the implementation of the MRT system in Taipei may have influenced the concurrent alterations noted in the SRB. In order to assess this potential association, annual numbers of male and female births were obtained from Taiwan’s Department of Household Registration, Ministry of Interior Affairs from 1992 to 2023. Mean yearly SRBs were calculated for 4 time periods, 1992–1995, 1996–2004, 2005–2015, and 2016–2023. Linear logistic regression was employed to evaluate the variation in officially reported PM2.5 levels during those periods and alterations in the ratios. The ratios for time periods 1 to 4 were 52.61%, 52.22%, 51.78%, and 51.67%, respectively. Compared to Period 1 (pre-MRT), the odds ratios for Periods 2, 3, and 4 were 0.98 (0.97–0.99), 0.97 (0.96–0.98), and 0.96 (0.95–0.98), respectively. The trend toward the decreased SRB was found to be gradual but significant.

A review of particulate matter (PM) in Indonesia: trends, health impact, challenges, and options.

This study reviews particulate matter (PM) research in Indonesia, focusing on current trends, health impacts, challenges, and future research directions. As the largest archipelago country, Indonesia faces severe pollution annually due to rapid urbanization, industrial activities, vehicle emissions, and forest fires. PM levels often exceed WHO and NAAQS standards, especially in urban areas and during forest fire seasons, posing significant health risks to vulnerable populations. Most PM studies have been conducted in major cities, primarily concentrated on Java Island. While there are several studies in Sumatra and Borneo, they commonly focus on the effects of peatland fires, and research in the eastern part of Indonesia remains limited. Substantial gaps in PM studies have been highlighted, including limited monitoring infrastructure, technology, data inconsistencies, and socio-economic challenges. Recent studies emphasize the need for more research on size-segregated PM, including ultrafine particles (UFPs), to fully understand their behavior in the atmosphere, sources, distribution, and health impacts. Chemical analysis and source apportionment studies are also crucial but currently limited due to equipment and analytical challenges. To improve PM management, the study proposes strategic options, including adopting advanced monitoring technologies along with low-cost samplers, increasing funding and technical training, enhancing coordination among stakeholders, and fostering international collaboration. Furthermore, public awareness campaigns and community-based monitoring are essential for effective air quality management.

Performance evaluation of an online monitor based on X-ray fluorescence for detecting elemental concentrations in ambient particulate matter

Abstract. Knowledge of the chemical composition of particulate matter (PM) is essential for understanding its source distribution, identifying potential health impacts of toxic elements, and developing efficient air pollution abatement strategies. Traditional methods for analysing PM composition, such as collection on filter substrates and subsequent offline analysis with, for example, inductively coupled plasma mass spectrometry (ICP-MS), are time-consuming and prone to measurement errors due to multiple preparation steps. Emerging near-real-time techniques based on non-destructive energy dispersive X-ray fluorescence (EDXRF) offer advantages for continuous monitoring and source apportionment. This study characterizes the Horiba PX-375 EDXRF monitor by applying a straightforward performance evaluation including (a) limit of detection (LoD), (b) identification and quantification of uncertainty sources, and (c) investigation and comparison of measurement results from three contrasting sites in Luxembourg (urban, semi-urban, rural). We used multi-element reference materials (ME-RMs) from UC Davis for calibration and performed measurements during spring and summer 2023. The LoDs for toxic elements like Ni, Cu, Zn, and Pb were below 3 ng m−3 at 1 h time resolution. Higher LoDs were observed for lighter elements (e.g. Al, Si, S, K, Ca). Expanded uncertainties ranged between 5 % and 25 % for elemental concentrations above 20 ng m−3 and were maximal for concentrations below 10 ng m−3, reaching 60 %–85 %. Elemental analysis revealed S and mineral elements (Fe, Si, Ca, Al) as dominant contributors to PM10. Although the PM mass contribution of toxic trace elements (e.g. Zn, Cu, As) was generally very low, they were found to be enriched at the urban site Belvaux and the semi-urban site Remich compared to the more rural site Vianden. Our results explained on average 51 %–74 % of the gravimetric PM10 mass at the three sites. The study highlights the suitability and importance of the continuous PX-375 particle monitor for future air quality monitoring and source apportionment studies, particularly under changing emission scenarios and air pollution abatement strategies.

Particulate matter estimation using satellite datasets: a machine learning approach.

In the present work, it is the first time an interpretable machine learning model has been developed for the estimation of Particulate Matter 10µm (PM10) concentrations over India using Aerosol Optical Depth (AOD) from two different satellites, i.e. INSAT-3D and Moderate Resolution Imaging Spectroradiometer (MODIS) for the period of 7years (2014 to 2020). Ground datasets of AOD are taken from the Aerosol Robotic Network (AERONET) for the validation of satellite-retrieved AOD. The observation of particulate matter (PM) data is acquired from the Central Pollution Control Board (CPCB) station across India. Analysis has been performed on a monthly basis for the given time period. The result shows that AOD products of MODIS exhibit good correlation with AERONET AOD whereas INSAT-3D AOD is not well correlated with AERONET AOD. However, after applying an error envelope and threshold-based filtering technique, we have found that INSAT-3D shows significant correlation with ground-level AOD with approximate correlation of 0.66 for Jaipur and 0.57 for Kanpur exhibiting almost similar performance as MODIS-derived AOD. Satellite AOD data together with ground PM concentration data is used to train the machine learning model (random forest) for the estimation of the PM distribution across India for the year 2020. An encouraging correlation of R-squared (R2) value 0.78 has been observed between the estimated and observed PM10 concentrations. The model demonstrates effective training, mitigating huge overestimation and underestimation. However, despite closely tracking the trends of estimated PM10 with observed PM10, few instances of overestimation persist. This suggests the need for an expanded training dataset to further refine and enhance the model's accuracy. Finally, the machine learning model used for PM10 estimation is found to be optimal for a calibrated satellite AOD product.

Global Trends and Hotspots in the Research of the Effects of PM2.5 on Asthma: A Bibliometric and Visualized Analysis.

Fine particulate matter (PM2.5) has been identified as a significant environmental and public health challenge, particularly due to its association with respiratory diseases like asthma. With the global rise in urbanization and industrialization, PM2.5-related asthma research has grown substantially over the past two decades. This study aims to provide a comprehensive bibliometric analysis to map global research trends, highlight key contributors, and identify emerging hotspots in the relationship between PM2.5 and asthma. We performed a bibliometric analysis using the Web of Science Core Collection database, covering research from January 2004 to September 2024. The selected studies were analyzed using CiteSpace and VOSviewer to assess publication trends, global collaborations, and research hotspots through visualized networks and co-occurrence analyses. A total of 2035 publications were identified, demonstrating a steady increase in research output over the past two decades. The United States and China emerged as dominant contributors, frequently collaborating with countries like Canada, Australia, and South Korea. Key research areas focused on air quality, particulate matter exposure, and asthma exacerbation, with an increasing emphasis on indoor air pollution and long-term exposure risks. Institutional collaborations were led by prominent universities such as the University of California System and Harvard University. Additionally, research on vulnerable populations, particularly children, and the impact of early-life exposure to PM2.5 has gained attention in recent years. The global research landscape on PM2.5 and asthma has expanded significantly, with growing attention to interdisciplinary approaches that combine environmental science and public health. Future studies should focus on the global burden of air pollution, particularly in low- and middle-income countries, and address the long-term health impacts of PM2.5 exposure, especially in vulnerable populations.

Air Pollution and Retail Vegetable Market Prices: Empirical Evidence from Korea

Abstract Air pollution can lead to people engaging in avoidance actions. People may limit their time spent outdoors to minimize the health hazards linked with air pollution. Consequently, when severe air pollution causes these behavioral changes, both outdoor and indoor stores may experience the impacts of air pollution. This study estimated the impact of air pollutant on retail vegetable prices (i.e., the total impact of air pollutants on the demand and supply of vegetables) for large discount stores, supermarkets, department stores, and traditional markets in Korea. To this end, we examine the weekly data of 590 Korean retailers during the period from 2015 to 2019, employing both static and dynamic panel approaches. The results indicate that an increase in air pollutants, such as particulate matter, carbon monoxide, nitrogen dioxide, sulfur dioxide, would lead to a decrease in vegetable prices in the short run and the long run across all types of stores we considered, meaning that deteriorating air pollutant levels could potentially result in decreases in vegetable prices not only in outdoor stores but also in indoor stores. Therefore, we suggest that initiatives to reduce air pollution and improve air quality should be further strengthened to prevent the adverse effects of air pollution on the food market.

Neutral Polysaccharide from Platycodonis Radix-Ameliorated PM2.5-Induced Lung Injury by Inhibiting the TLR4/NF-κB p65 Pathway and Regulating the Lung and Gut Microbiome.

Platycodonis radix (PR) has been reported to play a protective role in lung injury. However, much less is known about the protective effect and mechanism of its main component PR polysaccharides (PRPs) in particulate matter (PM2.5)-induced lung injury. Here, a neutral polysaccharide (MW: 244.56 kDa) was isolated from PR, mainly composed of Rha, Ara, Gal, Glc, Xyl, and Man. PRPs significantly improved PM2.5-induced pulmonary edema, oxidative damage, and cell apoptosis and downregulated inflammatory factor levels in bronchoalveolar lavage fluid. Mechanistically, PRPs reduced intestinal mucosal barrier damage, thereby lowering serum lipopolysaccharide levels and inhibiting the overactivation of the TLR4/NF-κB signaling pathway in the lung tissue. Notably, PRPs could optimize the composition of pulmonary and intestinal microbiota. Oral administration of PRPs resulted in enrichment of short-chain fatty acid (SCFA)-producing bacteria, thereby upregulating the levels of acetate, butyrate, and isovalerate. Taken together, PRPs have great potential in preventing and repairing the lung injury caused by PM2.5.

The impact of climate change on respiratory health: current understanding and knowledge gaps.

To present an overview of the impact of climate change upon human respiratory health. Climate change is directly impacting air quality. Particulate matter clearly increases mortality rates. Ozone, a longstanding suspect in climate-related injury, turns out not to have the major impact that had been projected at current levels of exposure. The key factors in global warming have been clearly identified, but while these factors collectively cause deleterious changes, a close look at the literature shows that it is unclear to what extent each factor individually is a driver of a specific process. This article summarizes some of those studies. A better understanding of which components of climate change most impact human health is needed in order to re-define environmental standards. PM2.5 needs to be broken down by chemical composition to study the differential impacts of different sources of PM2.5. The detection and study of climate-related changes in respiratory infectious diseases is in a state of relative infancy.

Trends and the Role of Gene-Environment Interactions in Idiopathic Membranous Nephropathy in Northern China.

Idiopathic membranous nephropathy (iMN) has become one of the most prevalent primary glomerular diseases, with a marked increase in prevalence over the past two decades in northern China. Fine particulate matter (PM2.5) is considered to be associated with this rising prevalence. In this study, we aim to evaluate the trends of iMN in relation to improved air quality and conduct a cross-sectional study in Hebei province (northern China, near Beijing) to investigate the role of gene-environment interactions in its development. This study established two cohorts. Cohort 1 included 22,937 pathology reports from Peking University First Hospital (2002-2021) to assess iMN prevalence. Cohort 2 comprised 5,635 iMN patients from 11 cities in Hebei Province (2009-2013). DNA samples from 374 iMN patients and 1,259 controls were genotyped for SNPs rs4664608 (PLA2R1) and rs2187668 (HLA-DQA1). Patients were stratified by air pollution risk levels. The annual percentage change (APC) and average annual percentage change (AAPC) were estimated using a join-point regression model. Gene-environment interactions were analyzed using logistic regression and epinet-calculation. In Cohort 1, 5,586 patients with iMN were identified, representing 24.3% of the 22,937 patients from 2002 to 2021. The general population showed a significant increase in iMN proportion with an APC of +12.7% per year from 2002 to 2014 (95% CI: 10.3 to 17.5, p < 0.001), followed by a decline with an APC of -5.6% per year from 2014 to 2021 (95% CI: -9.6 to -2.6, p < 0.001).In Hebei Province, the iMN frequency rose significantly with an APC of +17.6% per year from 2002 to 2016 (95% CI: 14.5 to 28.6, p < 0.001), peaking at 60%, and then declined with an APC of -5.5% per year from 2016 to 2021 (95% CI: -13.1 to -1.2, p = 0.02). Cohort 2 highlighted significant regional variation in iMN incidence across Hebei Province. Geographic exposure to pollution was identified as an independent risk factor for iMN (RR 1.49, 95% CI 1.38-1.56, p<0.001). Gene-environment interaction analysis revealed that patients with risk alleles in the PLA2R1 gene and exposure to risk environments had a markedly increased risk of developing iMN (OR=38.72, 95% CI 11.95-125.46, p<0.01). The annual growth rate of iMN in northern China appears to be slowing down. Gene-environment interactions may have contributed to the previously observed increase in iMN prevalence.

Exposure to air pollution and the risk of type II diabetes mellitus: a time-series study

BackgroundEnvironmental factors have been identified as primary risk factors for type 2 diabetes mellitus (T2DM). However, studies on the association between environmental factors and T2DM have mainly focused on morbidity and mortality, which do not fully reflect the disease burden stemming from air pollution. Therefore, we aimed to evaluate the correlation between air pollution and T2DM, including hospital length of stay (LOS) and costs.MethodsWe collected data on patients with T2DM from three healthcare institutions in Xinxiang from 2016–2021. Data on particulate and gaseous pollutants in Xinxiang and daily meteorological data were collected from national databases. The distribution lag nonlinear model was used to evaluate the correlation between air pollution and the number of inpatients with T2DM, LOS, and hospital costs. Subgroup analyses were conducted to identify potential modifying factors.ResultsOverall, 13,797 patients with T2DM were included in our analysis. Within the cumulative lag of 7 days, with every increase of 1 mg/m3 of carbon monoxide (CO) and 10 μg/m3 of 2.5 microns particulate matter, nitrogen dioxide and ozone exhibited significant associations with an increase in diabetes hospitalization risk. CO exhibited adverse effects on LOS on most lag days. Moreover, hospital costs were significantly associated with the attributable fraction of LOS and hospital costs attributed to diabetes.ConclusionsExposure to air pollutants increased T2DM risk, imposing significant economic and social burdens in Xinxiang, China. Implementing policies to reduce air pollutant exposure may decrease T2DM admissions, costs, and LOS.

What Goes Around Should Not Move Around: Immobilizing Microplastics as a New Approach for Analytical Ring Trials.

Microplastics have gained importance as pervasive environmental particulate pollutants. Their analysis demands precise quantification methods, with interlaboratory comparisons (ILCs) being crucial for performance assessment. Typically, ILCs follow a parallel design: participants each analyze their own sample specimen, often with significant variability due to challenges in producing identical subsamples of the particulate analyte, inseparably masking the relevant uncertainty sources the ILC intends to measure. We provide a filtration-immobilization approach for particles ≤100 μm, creating permanently immobilized microplastics samples. This enables serial ILC designs where participants sequentially measure the same sample. Demonstrating the concept using 5 polymers immobilized on 10 μm pore-sized silicon filters, we expose the specific measurement uncertainty being 77% lower than the total combined uncertainty observed in a parallel ILC (relative standard deviations: 5 and 23%, respectively). Particle immobilization opens further applications in sample archiving and creation of durable reference samples also for other fields of particulate matter research beyond microplastics.

Assessment of particulate matter concentrations and air quality index during road construction-related activities in Ghana

Road construction involves activities that emit pollutants, including particulate matter, which harms humans. This study determined and compared particulate matter (PM1.0, PM2.5 and PM10) levels and air quality index (AQI) at unpaved roads, asphalt overlay, chip-sealed and asphalt-producing sites in Ghana and the health risks posed by their exposure. It was conducted in the Ashanti and Ahafo Regions, Ghana and was cross-sectional using the low-cost sensor, PCE-RCM16. Data collection took place, January-May, 2020. The asphalt-producing, asphalt overlay, chip-sealed and unpaved road sites had mean PM10 concentrations of 12.7-fold, 7.4-fold, 6.1-fold and 2.6-fold respectively of the 2021 World Health Organisation (WHO) air quality guideline (AQG) daily limit, 45 μg m−3. The mean PM2.5 concentrations were 30.4-fold, 17.2-fold, 14.1-fold and 6.1-fold greater than the daily AQG limit, 15 μg m−3 respectively. The mean PM1.0 values were of grave concern. Using the AQI, the asphalt-producing and asphalt overlay sites were considered “hazardous”, chip-sealed site was “very unhealthy” and the unpaved sites were “unhealthy for sensitive groups”. Type of activity influenced pollution levels (p < 0.01). All the sites were polluted above the WHO limits. Authorities should ensure the wearing of personal protective equipment, strict adherence to the WHO AQG and apply appropriate sanctions to offending firms/workers.

Antibiotic resistance of bioaerosols in particulate matter from indoor environments of the hospitals in Dhaka Bangladesh

The emergence and spread of antibiotic resistance in microorganisms pose significant challenges to public health, especially in hospitals. This study investigated the existence or occurrence of bacterial bioaerosol and their antibiotic resistance patterns in particulate matter (PM) collected from hospitals in the greater Dhaka region, Bangladesh. The real-time particulate matter concentrations (PM1.0, PM2.5, and PM10) were measured in four hospitals and two ambient locations. Air sampling was conducted using a filter-based method with a low-volume air sampler, while AEROCET-531 S (USA) was employed to monitor particulate matter concentrations. Bacterial bioaerosol concentration was determined using a culture-based method, and eleven bacterial species, including nine individual species, i.e., Staphylococcus aureus, Pseudomonas aeruginosa, P. stutzeri, Bacillus cereus, Acinetobacter schindleri, Proteus vulgaris, B. subtilis, Escherichia coli, and B. aerius, were isolated. Antibiotic susceptibility testing was conducted using the Kirby-Bauer disk diffusion method with 21 antibiotics. Bacterial isolates were detected using partial sequencing of the 16 S rRNA gene. Bioaerosol concentration ranged from 194.65 ± 22.48 CFU/m3 to 948.39 ± 84.14 CFU/m3, showing significant correlations with PM1.0 and PM2.5 concentrations (R2 = 0.80 and 0.85, respectively). All bacterial isolates collected from the hospitals exhibited resistance against four or more antibiotics, indicating multidrug resistance (MDR). Notably, the bacterial isolates displayed the highest resistance rate against ampicillin (90.90%), azithromycin (81.81%), erythromycin (81.81%), cefixime (81.81%), and cotrimoxazole (54.54%), among the tested antibiotics. Except B. aerius, all other bacterial isolates were associated with hospital-acquired infections (HAIs). These findings highlight the high rates of antibiotic resistance, underscoring the pressing requirement for infection control measures and continuous surveillance strategies in hospital settings. These findings emphasize the necessity for global hospital infection control strategies focusing airborne multidrug-resistant microorganisms.

Predicting particulate matter ( ) levels in Morocco: a 5-day forecast using the analog ensemble method.

The accurate prediction of particulate matter ( ) levels, an indicator of natural pollutants such as those resulting from dust storms, is crucial for public health and environmental planning. This study aims to provide accurate forecasts of over Morocco for 5days. The analog ensemble (AnEn) and the bias correction (AnEnBc) techniques were employed to post-process forecasts produced by the Copernicus Atmosphere Monitoring Service (CAMS) global atmospheric composition forecasts, using CAMS reanalysis data as a reference. The results show substantial prediction improvements: the root mean squared error (RMSE) decreased from 63.83 in the original forecasts to 44.73 with AnEn and AnEnBc, while the mean absolute error (MAE) reduced from 36.70 to 24.30 . Additionally, the coefficient of determination ( ) increased more than twofold from 29.11 to 65.18%, and the Pearson correlation coefficient increased from 0.61 to 0.82. The integrating reanalysis data and the utilization of the AnEn substantially improved the accuracy of 5-day forecasting in Morocco. This is the first application of this approach in Morocco and the Middle East and North Africa (MENA) and has the potential for translation into early and more accurate warnings of pollution events. The application of such approaches in environmental policies and public health decision-making can minimize the health impacts of air pollution.

Experimental and Numerical Investigation of Spray Scrubber Dust Collection Efficiency

Spray scrubbers are widely used in gas purification applications and allow fulfillment of the demands of air quality norms introduced all over the world. They effectively remove harmful gases like sulfur dioxide (SO2), nitrogen oxides (NOx), and particulate matter from industrial emissions, reducing their impact on air quality. Moreover, by capturing greenhouse gases such as carbon dioxide (CO2) in certain applications, spray scrubbers contribute to efforts to reduce climate change. Optimization of scrubber internal elements leads to reduced energy usage and lowered water mass flow while maintaining high pollutant removal efficiency. This makes them cost-effective in the long term. The demister is an additional device which is often used in scrubbing systems, and its main task is to prevent the water droplets from escaping through the upper part of the scrubbing chamber. In this article, the pollution (MgO particles) is introduced to the system upstream the scrubber inlet, the working fluid is air under atmospheric pressure, and water droplets are generated by a single nozzle placed inside the scrubber. Before the experimental part, a preliminary numerical analysis of gas velocity inside scrubber is performed and expectations of particle behavior are indicated. Then, the authors present the spray scrubber laboratory stand designed by them and carry out experimental research on it. Each element of the test stand is described in the article including the self-designed fluidizer, which effectively mixes MgO powder with air. The authors investigate the effect of their innovative construction of demister on separation efficiency and compare the results to the case without demister. The impact of water mass flow rate generated by the nozzle and gas inlet velocity on separation efficiency is presented for several investigated cases. The results show that demisters significantly improve the separation efficiency at lower water mass flow rates and successfully prevent water droplets from reaching the scrubber outlet. The measured separation efficiency was in the range of 80% for lower water mass flow rates up to 97% for the highest water flows.

Factors Affecting Dust Retention in Urban Parks Across Site and Vegetation Community Scales

Air pollution poses a significant threat to human health, especially in urban areas. Urban parks function as natural biofilters, and examining the factors influencing dust retention—specifically PM2.5 and PM10 concentrations—across different spatial scales can enhance air quality and resident well-being. This study investigates the factors affecting dust retention in urban parks at both the site and vegetation community scales, focusing on Xi’an Expo Park. Through on-site measurements and a land use regression (LUR) model, the spatial and temporal distributions of PM2.5 and PM10 concentrations were analyzed. The indications of the findings are as follows. (1) The LUR model effectively predicts factors influencing PM2.5 and PM10 concentrations at the site scale, with adjusted R2 values ranging from 0.482 to 0.888 for PM2.5 and 0.505 to 0.88 for PM10. Significant correlations were found between particulate matter concentrations and factors such as the distance from factories, sampling area size, distance from main roads, presence of green spaces, and extent of hard pavements. (2) At the plant community scale, half-closed (30%–70% canopy cover), single-layered green spaces demonstrated the superior regulation of PM2.5 and PM10 concentrations. Specifically, two vegetation structures—the half-closed single-layered mixed broadleaf-conifer woodland (H1M) and the half-closed single-layered broad-leaved woodland (H1B)—exhibited the highest dust-retention capacities. (3) PM2.5 and PM10 concentrations were highest in winter, followed by spring and autumn, with the lowest levels recorded in summer. Daily particulate matter concentrations peaked between 8:00 and 10:00 a.m. and gradually decreased, reaching a minimum between 4:00 and 6:00 p.m. The objective of this study is to evaluate the impact of urban green spaces on particulate matter (PM) concentrations across multiple scales. By identifying and synthesizing key indicators at these various scales, the research aims to develop effective design strategies for urban green spaces and offer a robust theoretical framework to support the creation of healthier cities. This multi-scale perspective deepens our understanding of how urban planning and landscape architecture can play a critical role in mitigating air pollution and promoting public health.

Air Pollution and Myocardial Infarction—A New Smoker’s Paradox?

Background/Objectives: Ambient air pollution is a significant public health concern, known to affect cardiovascular health adversely. Research has identified both long-term and short-term cardiovascular risks associated with various air pollutants, including those linked to acute coronary syndromes. However, the observed effects are rather small, with most data sourced from highly polluted regions. Methods: This study utilized a prospective registry database, documenting 12,581 myocardial infarction (MI) events in Styria, Austria from January 2007 to December 2015. Pollutants analyzed included particulate matter (PM2.5, PM10) and gases, such as NO2, CO, SO2, O3 and NOx. We employed generalized linear models to examine the interaction of each of these pollutants on the daily incidence of MI. Additionally, we conducted separate analyses for patients with specific comorbidities: diabetes mellitus (DM), arterial hypertension (HTN), heart failure with reduced ejection fraction (HFrEF), chronic obstructive pulmonary disease (COPD) and current smokers. Results: No significant associations were identified between any of the pollutants and MI incidence, both in the overall cohort and in patient subgroups with DM, HTN, HFrEF or COPD. However, among active smokers, we observed a decreased relative risk of MI associated with elevated levels of NO2, CO, SO2 and NOx on the day of MI (p &lt; 0.01 for all pollutants). Conversely, an increased MI risk was associated with rising ozone levels (p = 0.0027). This counterintuitive finding aligns with previously published data and may suggest a new dimension to the “smoker’s paradox”. Conclusions: In regions with low pollution levels, air pollutants pose only minor or insignificant short-term risks for myocardial infarction. Active smokers exhibit an altered response to ambient air pollution.

Discrepant Global Surface Ozone Responses to Emission- and Heatwave-Induced Regime Shifts.

Heatwaves have substantial but poorly quantified impacts on surface ozone photochemical regimes. As heatwaves of increasing severity occur, communities face more serious exposure to ozone, necessitating a more comprehensive understanding of the impact of heatwaves on the nonlinear response of ozone to its precursors for guiding policies in emission reductions. Here we estimate the spatiotemporal evolution of global ozone chemistry based on machine learning and in situ observations and show that emission changes and heatwaves alter ozone photochemical regimes, leading to diverse ozone changes across regions. Sustained emission reductions in East Asia decreased the ozone formation sensitivity to formaldehyde (HCHO) and fine particulate matter (PM2.5), counteracting the adverse high-temperature effect. Quantified results reveal that heatwaves increased the sensitivity of ozone to HCHO and PM2.5, enhancing their positive contributions and causing increased ozone trends across most regions, with a global average anomaly of 9.4 μg/m3. Meanwhile, heatwave-induced PM2.5 anomalies concentrated in wildfire-risk zones, coupled with increased HCHO, elevated downwind ozone levels. Specifically, the effects in wildfire-endangered western Canada and heatwave-exposed southeastern United States contributed to a chemically driven ozone increase of 0.18 μg/m3/month in Northern America. Our results demonstrate that more targeted and substantial regulation of volatile organic compounds will be beneficial in mitigating future intensifying climate penalty effects.

Maternal exposure to fine particulate matter before and during pregnancy, and the risk of birth defects: A population-based study

Although epidemiological evidence has linked maternal exposure to air pollution with adverse birth outcomes, the association between exposure to fine particulate matter (PM2.5) and the risk of total birth defects in highly polluted developing regions remains limited. The objective of this study was to assess the relationship between maternal exposure to PM2.5 before and during pregnancy and the occurrence of birth defects. This study included 16,080 births with birth defects and 567,483 controls born between 2014 and 2019 in 14 cities in Liaoning Province, China. The assessment of exposure was conducted using satellite-based PM2.5 data at a spatial resolution of 1 km. Participants were classified into four subgroups based on their exposure to PM2.5 before and during pregnancy. The association between maternal exposure to PM2.5, and the risk of birth defects, was estimated using logistic regression models. For each 10 μg/m³ increase in PM2.5, the odds ratios of birth defects were 1.68 (95% CI: 1.65, 1.70) and 2.41 (95% CI: 2.36, 2.45) during the preconception period and pregnancy, respectively. We observed a J-shaped association between maternal PM2.5 exposure during both the preconception period and pregnancy and the risk of total birth defects. Mothers exposed to elevated levels of PM2.5 during both the preconception period and pregnancy exhibited the highest risk of total birth defects (odds ratio: 4.43, 95% CI: 4.17, 4.71). Our findings illustrated that maternal exposure to PM2.5 before and during pregnancy was associated with increased risks of birth defects and underscored the potential health benefits of reducing air pollution exposure during the preconception period and pregnancy.

Elevated Serum Uric Acid Levels Mediate the Associations of Ambient PM2.5 and Its Components with Glaucoma

Limited epidemiological information exists on the relationships between fine particulate matter (PM2.5) components and glaucoma risk. Moreover, the potential mediation effect of serum uric acid (UA) levels remains unexplored. Data from the China Health and Retirement Longitudinal Survey (CHARLS) spanning 2011–2020 were analyzed. Cox proportional hazard models and quantile-based g-computation (qg-computation) models were applied to determine the associations of PM2.5 and its five components (including sulfate [SO₄2⁻], nitrate [NO₃⁻], ammonium [NH₄⁺], organic matter [OM], and black carbon [BC]) with glaucoma risk. A causal mediation model was applied to assess the mediation effect of serum UA. Individual exposure to PM2.5 mass and its five components was positively associated with glaucoma risk, respectively. The mixture of PM2.5 components were significantly and positively associated with glaucoma risk (hazard ratio [HR] = 1.31, 95% confidence interval [CI]: 1.18–1.45), with NH₄⁺ and BC contributing the most (proportions: 81% and 19%, respectively). These associations were modified by sex and residence. Elevated serum UA levels played a mediated role in the association between PM2.5 mass and its five chemical components and glaucoma, with mediated proportions ranging from 12% to 15%. Prolonged exposure to PM2.5 components, especially NH4+ and BC, may elevate the glaucoma risk among Chinese middle-aged and older people, and elevated serum UA levels may play a key mediating role.