Levels Of Particulate Matter Research Articles

Human health impacts attributable to inhalation exposure of particulate matter (PM10 and PM2.5) during the Holi festival

Objective The present study focuses on residential areas of Delhi to identify the elevated levels of ambient PM10 and PM2.5 due to biomass burning followed by the coloring activity in the Holi festival celebrated at the end of the winter season. This study also focuses on the health risk assessment and mortality among different age groups due to the change in particulate matter levels during the Holi festival in Delhi, India. Materials and Methods Secondary data of particulate matters have been procured from the Central Pollution Control Board (CPCB), Delhi Pollution Control Committee (DPCC), and Indian Institute of Tropical Meteorology (IITM), Pune for the period of the pre-, during, and post-Holi period for the year 2018-2020 at four selected residential locations in Delhi, India. The health impacts of particle inhalation were quantified using the AirQ + models. Results The results indicated the levels of PM10 and PM2.5 rise about 3-4 times higher during the Holi festival than on normal days, resulting in health risks and causing an excess number of mortality and Asthma cases in Delhi. Such cases were also found to be higher in 2018, followed by 2019 and 2020 at all the selected locations in Delhi. Conclusions The study linked the increasing particulate levels in the Holi festival with the increased health risk through short-term exposure of the population. The excess number of cases (ENCs) of mortality, all causes of mortality among adults (age > 30 years) associated with short-term exposure to particulate were also identified.

The Impact of Acute Peri-operative Particulate Matter Exposure on Endoscopic Sinus Surgery Outcomes: A Preliminary Multi-site Investigation.

Environmental exposures have been postulated to play an important role in the pathophysiology of chronic rhinosinusitis (CRS). Particulate matter (PM) is one of the most widely studied ambient air pollutants, but its peri-operative impact on CRS is unknown. To determine the effect of acute, peri-operative PM exposure on outcomes after endoscopic sinus surgery (ESS). Participants with CRS who self-selected ESS were prospectively enrolled. The 22-item SinoNasal Outcome Test (SNOT-22) and Medical Outcomes Study Questionnaire Short-Form 6-D (SF-6D) health utility values scores were recorded. Using residence zip codes, a secondary analysis of patient exposure to PM <2.5 μm and <10 μm (PM2.5 and PM10, respectively) was performed for the month of surgery utilizing data from Environmental Protection Agency air quality monitors. Spearman's correlation coefficients (ρ), 95% confidence intervals (CIs), and effect estimates (β) were used to determine the magnitudes of association. Simple, multivariate regression analysis was also completed. One hundred and seven patients from four geographically unique institutions across the US were enrolled with a follow-up of 6 months. Patients with higher peri-operative PM2.5 exposure had less improvement in their SNOT-22 scores after ESS compared to those with less exposure using both univariate analysis (ρ = 0.26, 95% CI: 0.08, 0.43; P = .01) and after covariate adjustment with multivariate analysis (B = 1.06, 95% CI: 0.001, 2.14, P = .05). Similar associations were not found with SF-6D outcomes or with PM10 as an exposure of interest. No significant correlations were found between peri-operative PM levels and Lund-Kennedy endoscopy scores post-operatively. Preliminary data from this pilot study reveal that PM exposure at the time of ESS may negatively associate with post-operative improvement in sinonasal quality-of-life. Larger, population-based studies with more standardized PM exposure windows are needed to confirm the clinical significance of the present findings.

Short-term and long-term effects of exposure to PM10

IntroductionA dust storm is a harmful event in the environment and human health resulting from certain chemicals in the air that transcend predefined levels. Developing countries, such as Iran, suffer from this basic threat (dust particles) to health. The purpose of the research was to evaluate the effects of PM10 particulate matter on mortality related to cardiovascular diseases (CVD) in the year 2022–2023 in Andimeshk City, with the AirQ + programmed. Material and methodThe recommended approach for evaluating effects on health, as recognized by the world health organization (WHO), uses the Air Quality Health Impact Assessment Software (Air Q 2.2.3). The polluted air information required for model runs was obtained from the Environmental Department of Khuzestan. The Khuzestan Meteorological Organization gave information on the levels of particulate matter for both dusty and non-dusty days. The mortality numbers came from the Iranian Statistics Centre and the Health Ministry. The data was collected in a volumetric manner for the year 2022–2023. ResultThe lowest PM10 concentration reported in a year in Andimeshk city belonged to January 9 (14.19 μg/m3), while the most polluted day of the year was November 6 (5634.61 μg/m3). The total monthly concentration of PM10 for April, May, June, July, August, September, October, November, December, January, and February respectively, 2917.9, 3227.82, 3175.89, 2966.24, 3520.46, 3393.1, 4671.07, 13121.26, 3042.63, 1851.67, 2627.52, and 6758.12 μg/m3. ConclusionThe results of this study showed that the studied area is a polluted city in terms of the concentration of dust particles. So, during a year, only 8 days, PM10 concentration did not exceed the standard. One of the main reasons for air pollution in Andimshek city is the neighborhood of Khuzestan province with Iraq and Saudi Arabia, which have dry areas and dust storms.

Machine learning insights into PM2.5 changes during COVID-19 lockdown: LSTM and RF analysis in Mashhad.

This study seeks to investigate the impact of COVID-19 lockdown measures on air quality in the city of Mashhad employing two strategies. We initiated our research using basic statistical methods such as paired sample t-tests to compare hourly PM2.5 data in two scenarios: before and during quarantine, and pre- and post-lockdown. This initial analysis provided a broad understanding of potential changes in air quality. Notably, a low reduction of 2.40% in PM2.5 was recorded when compared to air quality prior to the lockdown period. This finding highlights the wide range of factors that impact the levels of particulate matter in urban settings, with the transportation sector often being widely recognized as one of the principal causes of this issue. Nevertheless, throughout the period after the quarantine, a remarkable decrease in air quality was observed characterized by distinct seasonal patterns, in contrast to previous years. This finding demonstrates a significant correlation between changes in human mobility patterns and their influence on the air quality of urban areas. It also emphasizes the need to use air pollution modeling as a fundamental tool to evaluate and understand these linkages to support long-term plans for reducing air pollution. To obtain a more quantitative understanding, we then employed cutting-edge machine learning methods, such as random forest and long short-term memory algorithms, to accurately determine the effect of the lockdown on PM2.5 levels. Our models' results demonstrated remarkable efficacy in assessing the pollutant concentration in Mashhad during lockdown measures. The test set yielded an R-squared value of 0.82 for the long short-term memory network model, whereas the random forest model showed a calculated cross-validation R-squared of 0.78. The required computational cost for training the LSTM and the RF models across all data was 25min and 3s, respectively. In summary, through the integration of statistical methods and machine learning, this research attempts to provide a comprehensive understanding of the impact of human interventions on air quality dynamics.

Temporal variation of the PM2.5/PM10 ratio and its association with meteorological factors in a South American megacity: Metropolitan Area of Lima-Callao, Peru.

The Metropolitan Area of Lima-Callao (MALC) is a South American megacity that has suffered a serious deterioration in air quality due to high levels of particulate matter (PM2.5 and PM10). Studies on the behavior of the PM2.5/PM10 ratio and its temporal variability in relation to meteorological parameters are still very limited. The objective of this study was to analyze the temporal trends of the PM2.5/PM10 ratio, its temporal variability, and its association with meteorological variables over a period of 5years (2015-2019). For this, the Theil-Sen estimator, bivariate polar plots, and correlation analysis were used. The regions of highest mean concentrations of PM2.5 and PM10 were identified at eastern Lima (ATE station-41.2µg/m3) and southern Lima (VMT station-126.7µg/m3), respectively. The lowest concentrations were recorded in downtown Lima (CDM station-16.8µg/m3 and 34.0µg/m3, respectively). The highest average PM2.5/PM10 ratio was found at the CDM station (0.55) and the lowest at the VMT station (0.27), indicating a predominance of emissions from the vehicular fleet within central Lima and a greater emission of coarse particles by resuspension in southern Lima. The temporal progression of the ratio of PM2.5/PM10 showed positive and highly significant trends in northern and central Lima with values of 0.03 and 0.1 units of PM2.5/PM10 per year, respectively. In the southern region of Lima, the trend was also significant, showcasing a value of 0.02 units of PM2.5/PM10 per year. At the hourly and monthly level, the PM2.5/PM10 ratio presented a negative and significant correlation with wind speed and air temperature, and a positive and significant correlation with relative humidity. These findings offer insights into identifying the sources of PM pollution and are useful for implementing regulations to reduce air emissions considering both anthropogenic sources and meteorological dispersion patterns.

Particle analysis of surgical lung biopsies from deployed and non-deployed US service members during the Global War on Terrorism.

The role that inhaled particulate matter plays in the development of post-deployment lung disease among US service members deployed to Southwest Asia during the Global War on Terrorism has been difficult to define. There is a persistent gap in data addressing the relationship between relatively short-term (months to a few years) exposures to high levels of particulate matter during deployment and the subsequent development of adverse pulmonary outcomes. Surgical lung biopsies from deployed service members and veterans (DSMs) and non-deployed service members and veterans (NDSMs) who develop lung diseases can be analyzed to potentially identify residual deployment-specific particles and develop associations with pulmonary pathological diagnoses. We examined 52 surgical lung biopsies from 25 DSMs and 27 NDSMs using field emission scanning electron microscopy (FE-SEM) with energy dispersive x-ray spectroscopy (EDS) to identify any between-group differences in the number and composition of retained inorganic particles, then compared the particle analysis results with the original histopathologic diagnoses. We recorded a higher number of total particles in biopsies from DSMs than from NDSMs, and this difference was mainly accounted for by geologic clays (illite, kaolinite), feldspars, quartz/silica, and titanium-rich silicate mixtures. Biopsies from DSMs deployed to other Southwest Asia regions (SWA-Other) had higher particle counts than those from DSMs primarily deployed to Iraq or Afghanistan, due mainly to illite. Distinct deployment-specific particles were not identified. Particles did not qualitatively associate with country of deployment. The individual diagnoses of the DSMs and NDSMs were not associated with elevated levels of total particles, metals, cerium oxide, or titanium dioxide particles. These results support the examination of particle-related lung disease in DSMs in the context of comparison groups, such as NDSMs, to assist in determining the strength of associations between specific pulmonary pathology diagnoses and deployment-specific inorganic particulate matter exposure.

Analyzing Air Pollution in Urban Delhi: A Quantitative Assessment of Particulate Matter (PM) Concentrations

Air pollution poses significant challenges to urban environments, with particulate matter (PM) concentrations being a major concern due to their adverse effects on public health and the environment. This research paper aims to quantitatively assess PM concentrations in urban Delhi, focusing on spatial, temporal, and seasonal variations across diverse urban microenvironments. The research design involved mobile air quality monitoring using real-time PM sensors mounted on a vehicle, coupled with Geographic Information System (GIS) analysis to map pollution hotspots and assess correlations with urban features. The key findings of the study reveal significant spatial variability in PM concentrations, with industrial zones and busy intersections emerging as hotspots for pollution. Seasonal variations in PM levels, with elevated concentrations during winter months and lower levels during the monsoon season, underscore the influence of meteorological factors on air quality dynamics. The study also identifies correlations between PM concentrations and respiratory disease cases, highlighting the adverse health effects of air pollution. The implications of these findings extend to air quality management strategies and public health interventions, emphasizing the need for targeted measures to mitigate pollution levels and protect public health in urban environments.

A comprehensive review of urban vegetation as a Nature-based Solution for sustainable management of particulate matter in ambient air.

Air pollution is one of the most pressing environmental threats worldwide, resulting in several health issues such as cardiovascular and respiratory disorders, as well as premature mortality. The harmful effects of air pollution are particularly concerning in urban areas, where mismanaged anthropogenic activities, such as growth in the global population, increase in the number of vehicles, and industrial activities, have led to an increase in the concentration of pollutants in the ambient air. Among air pollutants, particulate matter is responsible for most adverse impacts. Several techniques have been implemented to reduce particulate matter concentrations in the ambient air. However, despite all the threats and awareness, efforts to improve air quality remain inadequate. In recent years, urban vegetation has emerged as an efficient Nature-based Solution for managing environmental air pollution due to its ability to filter air, thereby reducing the atmospheric concentrations of particulate matter. This review characterizes the various mitigation mechanisms for particulate matter by urban vegetation (deposition, dispersion, and modification) and identifies key areas for further improvements within each mechanism. Through a systematic assessment of existing literature, this review also highlights the existing gaps in the present literature that need to be addressed to maximize the utility of urban vegetation in reducing particulate matter levels. In conclusion, the review emphasizes the urgent need for proper air pollution management through urban vegetation by integrating different fields, multiple stakeholders, and policymakers to support better implementation.

Assessment of seasonal variations in particulate matter accumulation and elemental composition in urban tree species

Outdoor air pollution in urban areas, especially particulate matter (PM), is harmful to human health. Urban trees and shrubs provide crucial ecosystem services such as air pollution mitigation by acting as natural filters. However, urban greenery comprises a particular biodiversity, and different plant species vary in their capacity to accumulate PM. Twenty-two plant species were analyzed and selected according to their leaf traits, the different fractions of PM accumulated on the leaves (large - PML, coarse - PMC, and fine - PMF) and their chemical composition. The study was conducted in four city zones: urban traffic (UT), urban background (UB), industrial (IND), and rural (RUR), comparing winter (W) and summer (S) seasons. The average PM levels in the air and accumulated on the leaves were higher in W than in S season. During both seasons, the highest PM accumulated on the leaves was recorded at the UT zone. Nine species were selected as the most suitable for accumulating PML, seven as the most efficient for accumulating PMC, and six for accumulating PMF. The leaf area and leaf roundness were correlated negatively with PM accumulation. The evergreen species L. nobilis was indicated as suitable for dealing with air pollution based on PM10 and PM2.5 values recorded in the air. Regarding the PM element and metal composition, L. nobilis, Photinia x fraseri, Olea europaea, Quercus ilex and Nerium oleander were selected as species with notable elements and metal accumulation. In summary, the study identified species with higher PM accumulation capacity and assessed the seasonal PM accumulation patterns in different city zones, providing insights into the species interactions with PM and their potential for monitoring and coping with air pollution.

Assessment of Indoor Particulate Matter and Teacher's Perceived Indoor Climate in Government Schools of Bilaspur District, Chhattisgarh, India: A Cross-Sectional Study.

Indoor air pollution (IAP) affects the long-term health, cognitive growth, and academic performance of children. Since children spend most of their time at school, quantifying IAP in classrooms is an important parameter for air pollution. To assess the average particulate matter (PM) levels inside and outside of classrooms along with their associated factors and teacher's perceived indoor climate. Cross-sectional survey in nine government-run schools. PM2.5 and PM10 were measured inside the classroom and outdoors simultaneously during summers, using an Atmos monitor for two consecutive days, along with several school and classroom characteristics. Perception about indoor air quality was captured from teachers (n = 15) using a validated questionnaire. Mean values of PM using mixed effect linear regression. Perceived indoor air quality is presented using percentages. Mean indoor PM2.5 and PM10 was 52.5 µg/m3 and 65 µg/m3. Indoor and outdoor PM levels were highly correlated, but the indoor-outdoor ratio of PM concentrations was more than 1. Teachers were mostly bothered by dust, dirt, and noise in the schools. Indoor air quality was higher than World Health Organization (WHO) standards but within the national standards. Need further research to find the exact cause for higher indoor PM levels compared to outdoor PM levels.

Substantial increase in population exposure to multiple environmental burdens in sub-Saharan Africa (2000-2019)

In the face of increasing global environmental uncertainties, sub-Saharan Africa stands as a highly vulnerable region with a massive population marked with poverty and inequalities. Moreover, different environmental risk factors can coexist simultaneously as multiple environmental burdens (MEBs); however, population exposure to MEB remains unexamined. Here, using open-access spatial data and critical thresholds, we quantify population exposure to four key environmental risk factors: hazardous fine particulate matter (PM2.5) levels, extreme temperature increase, prolonged severe droughts, and green deficit (scarcity of green trees). Further, we explore the concept of MEB, where these risk factors converge. We derive exposure for 2000 and 2019 at the pixel (1 km grid cell) level. We also check how population change, environmental change, and their interaction contribute to the total change in exposure. We found substantial changes in the population exposed from 2000 to 2019, i.e. an increase of ∼460 million people to hazardous PM2.5 levels, ∼16 million to extreme temperature increase, ∼13 million to prolonged severe droughts, and ∼246 million to green deficit. Population exposure to at least three of these four environmental risk factors (3EB) has increased by ∼246 million. In this increase in exposure to 3EB, the contribution of environmental change is higher (48%), than that of interaction and population change (36% and 15%, respectively). Notably, there are striking disparities in population exposure, its change, and the contributing effects among countries and regions of sub-Saharan Africa.

Investigation Of Emissions And Fuel Consumption In Diesel-Engine Vehicles During Idle Conditions

Idling engines when automobiles are not moving leads to inefficient fuel consumption and may harm human health and the environment. No scientific reports have evaluated the effects of idling diesel engines on the public and fuel wastage in Malaysia; thus, a study is required. This work aims to study the characteristics of emissions, heat dissipation, and fuel wastage due to the operations of diesel-engine vehicles under idle operations concerning human health and the environment. The study was conducted by measuring the emissions during idling conditions using various instruments, namely a gas analyser, particulate matter monitor, temperature sensor, and fuel meter at selected locations where heavy vehicles were commonly found left with idling engines. It was found that the idling-vehicle emissions in the vicinity of pedestrians were far higher than the limits set in Malaysia Ambient Air Quality Standard 2020, implying an unhealthy practice. The particulate matter levels were also 15 to 200 times more than the standard limit. This silent hazard would be detrimental to the public, leading to various health problems. Furthermore, it would lead to hefty medical bills for the government. The heat emission was also high, leading to discomfort and health issues for passersby. From an economic point of view, the fuel waste from idling diesel engines was exorbitantly high, thus suggesting that the authorities should regulate the practice of idling engines. Keywords: diesel engine, fuel wastage, heat emission, idling engines, pollutant

Statistical Substantiation of the Revising of Readings by the CityAir Station of PM2.5 Concentration Levels in the Atmospheric Boundary Layer of the City

As a marker characterizing air pollution in the surface layer of the atmosphere of modern cities, the concentration level of particulate matter with a diameter of 2.5 microns or less (Particulate Matter, PM2.5) is often used. The paper discusses the practice of using a relatively cheap optical sensor, which is part of the CityAir station, to measure the concentration of PM2.5 in an urban environment. The article proposes a statistically justified correction of the primary data obtained by CityAir stations on the values of the concentration of suspended particles PM2.5 in the surface layer of the atmosphere of Krasnoyarsk. For the construction of regression models, measurements obtained from E-BAM analyzers located at the same observation posts as the corrected sensors were considered as a reference. For the analysis, primary data was used 1) from 9 automated observation posts of the regional departmental information and analytical system of data on the state of the environment of the Krasnoyarsk Territory (KVIAS); 2) from the 21st CityAir station of the monitoring system of the Krasnoyarsk Scientific Center of the Siberian Branch of the Russian Academy of Sciences. The paper demonstrates that when correcting sensor readings, it is necessary to take into account meteorological indicators. In addition, it is shown that the regression coefficients significantly depend on the season. Supervised learning methods are compared for solving the problem of correcting the readings of inexpensive sensors. Additional information on the results of data analysis, which was not included in the text of the article, is available on the electronic resource https://asm.krasn.ru/.

Increased atmospheric PM2.5 events due to open waste burning in Qaanaaq, Greenland, summer of 2022

AbstractHigh levels of particulate matter (PM) are relevant to severe air pollution and can adversely impact human health. Maintaining healthy air quality for the residents of the Arctic region is essential to satisfy the no‐one‐left‐behind policy of the Sustainable Development Goals (SDGs) by the United Nations. In this study, we installed a PM2.5 measurement system in Qaanaaq, Greenland, and obtained the first continuous PM2.5 measurements from July 20, 2022 to August 13, 2022. We observed several increased PM2.5 events; relatively high PM2.5 levels persisted from August 8, 2022. On the same day, visible black smoke emitted from the Qaanaaq dump site originated from open waste burning. By confirming less transboundary air pollution contributions from remote aerosol source regions to Qaanaaq during the measurement period using NOAA's HYSPLIT backward trajectory analysis and NASA's MERRA‐2 aerosol re‐analysis, we confirmed that the increased PM2.5 was primarily due to local open waste burning with less contributions from transboundary air pollution. However, small contributions from biomass burning outside Greenland were plausible during the early measurement period. Additionally, NOAA's HYSPLIT dispersion calculations suggested possible aerosol depositions from local open waste burning to nearby sea areas, such as Baffin Bay. Although the hourly mean PM2.5 mass concentration was not alarmingly high during the measurement period, future studies should incorporate longer‐term continuous PM2.5 measurements along with other atmospheric chemical analyses to identify possible local air pollution sources in detail to ensure clean ambient air for the future in the Arctic. Our study provides quantitative evidence of the impact of open waste burning on air quality at a study site in Greenland, which could be crucial in developing air quality policies for this region in the Arctic.

Improvement of the anthropogenic emission rate estimate in Ulaanbaatar, Mongolia, for 2020–21 winter

Ulaanbaatar (UB), the fast-growing capital of Mongolia, is known for its world's worst level of particulate matter (PM) concentrations in winter. However, current anthropogenic emission inventories over the UB are based on data from more than fifteen years ago, and satellite observations are scarce because UB is in high latitudes. During the winter of 2020–21, the first period of the Fine Particle Research Initiative in East Asia considering the National Differences (FRIEND), several times higher concentrations of PM in UB compared to other urban sites in East Asia were observed but not reproduced with a chemical transport model mainly due to the underestimated anthropogenic emissions. Therefore, we devised a method for sequentially adjusting emissions based on the reactivity of PM precursors using ground observations. We scaled emission rates for the inert species (CO, elemental carbon (EC), and organic carbon (OC)) to reproduce their observed ambient concentrations, followed by SO2 to reproduce the concentration of SO42−, which was examined to have the least uncertainty based on the abundance of observed NH3, and finally NO and NH3 for NO3−, and NH4+. This improved estimation is compared to regional inventories for Asia and suggests more than an order of magnitude increase in anthropogenic emissions in UB. Using the improved emission inventory, we were able to successfully reproduce independent observation data on PM2.5 concentrations in UB in December 2021 from the U.S. Embassy. During the campaign period, we found more than 50% of the SO42−, NO3−, and NH4+ increased in UB due to the improvement could travel to Beijing, China (BJ), and about 20% of the SO42− could travel to Noto, Japan (NT), more than 3000 km away. Also, the anthropogenic emissions in UB can effectively increase OC, NO3−, and NH4+ concentrations in BJ when Gobi dust storms occur.

Determinants of Hospital Length of Stay in Respiratory Infections: Insights from Cheras, Malaysia

Respiratory virus infections pose a significant public health concern, contributing to increase morbidity and mortality rates. This study investigated the determinants of hospital length of stay (LOS) for patients with Influenza-like illness (ILI) and Severe Acute Respiratory Infection (SARI). A quantitative study was conducted in Cheras, Kuala Lumpur, Malaysia, from 1 September 2022 until 28 February 2023. Demographic data, viral infection status (influenza A, influenza B, and COVID-19), and environmental factors (temperature, humidity, wind speed, and particulate matter levels) were collected for 632 patients. The data were analysed using ordinal logistic regression in Statistical Package for Social Sciences (SPSS) version 22.0. The results revealed that older age and higher body mass index (BMI) were associated with longer hospital stays, highlighting their significance as risk factors during respiratory outbreaks. Unexpectedly, patients tested positive for the investigated viruses experienced shorter LOS, indicating potential comorbidities or co-infections. Environmental factors played a critical role, with temperature, humidity, and wind speed significantly influencing LOS. These findings provided valuable insights for healthcare resource allocation during epidemics and underscored the need for comprehensive diagnostic tools and further research to enhance prediction accuracy.

Exposure to benzene, toluene, ethylbenzene, and xylene (BTEX) at Nigeria's petrol stations: a review of current status, challenges and future directions.

In Nigeria, because of increasing population, urbanization, industrialization, and auto-mobilization, petrol is the most everyday non-edible commodity, and it is the leading petroleum product traded at the proliferating Nigeria's petrol stations (NPSs). However, because of inadequate occupational health and safety (OHS) regulatory measures, working at NPSs exposes petrol station workers (PSWs) to a large amount of hazardous benzene, toluene, ethylbenzene, and xylene (BTEX) compounds. Studies on BTEX exposures among Nigerian PSWs are scarce. Thus, constraints in quantifying the health risks of BTEX limit stakeholders' ability to design practical risk assessment and risk control strategies. This paper reviews studies on the OHS of Nigerian PSWs at the NPSs. Although knowledge, attitude, and practices on OHS in NPSs vary from one Nigeria's study setting to another, generally, safety practices, awareness about hazards and personal protective equipment (PPE), and the use of PPE among PSWs fell below expectations. Additionally, air quality at NPSs was poor, with a high content of BTEX and levels of carbon monoxide, hydrogen sulfide, particulate matter, and formaldehyde higher than the World Health Organization guideline limits. Currently, regulatory bodies' effectiveness and accountability in safeguarding OHS at NPSs leave much to be desired. Understanding the OHS of NPSs would inform future initiatives, policies, and regulations that would promote the health and safety of workers at NPSs. However, further studies need to be conducted to describe the vulnerability of PSWs and other Nigerians who are occupationally exposed to BTEX pollution. More importantly, controlling air pollution from hazardous air pollutants like BTEX is an essential component of OHS and integral to attaining the Sustainable Development Goals (SDG) 3, 7, and 11.

Deployment-related Cigarette Smoking Behaviors and Pulmonary Function Among U.S. Veterans.

The effects of smoking on lung function among post-9/11 Veterans deployed to environments with high levels of ambient particulate matter are incompletely understood. We analyzed interim data (04/2018-03/2020) from the Veterans Affairs (VA) Cooperative Studies Program #595, "Service and Health Among Deployed Veterans". Veterans with ≥1 land-based deployments enrolled at 1 of 6 regional Veterans Affairs sites completed questionnaires and spirometry. Multivariable linear regression models assessed associations between cigarette smoking (cumulative, deployment-related and non-deployment-related) with pulmonary function. Among 1,836 participants (mean age 40.7±9.6, 88.6% male), 44.8% (n = 822) were ever-smokers (mean age 39.5 ± 9.5; 91.2% male). Among ever-smokers, 86% (n = 710) initiated smoking before deployment, while 11% (n = 90) initiated smoking during deployment(s). Smoking intensity was 50% greater during deployment than other periods (0.75 versus 0.50 packs-per-day; P < .05), and those with multiple deployments (40.4%) were more likely to smoke during deployment relative to those with single deployments (82% versus 74%). Total cumulative pack-years (median [IQR] = 3.8 [1, 10]) was inversely associated with post-bronchodilator FEV1%-predicted (-0.82; [95% CI] = [-1.25, -0.50] %-predicted per 4 pack-years) and FEV1/FVC%-predicted (-0.54; [95% CI] = [-0.78, -0.43] %-predicted per 4 pack-years). Deployment-related pack-years demonstrated similar point estimates of associations with FEV1%-predicted (-0.61; [95% CI] = [-2.28, 1.09]) and FEV1/FVC%-predicted (-1.09; [95% CI] = [-2.52, 0.50]) as non-deployment-related pack-years (-0.83; [95% CI] = [-1.26, -0.50] for FEV1%-predicted; -0.52; [95% CI] = [-0.73, -0.36] for FEV1/FVC%-predicted). Although cumulative pack-years smoking was modest in this cohort, an inverse association with pulmonary function was detectable. Deployment-related pack-years had a similar association with pulmonary function compared to non-deployment-related pack-years.

A novel framework for quantitative attribution of particulate matter pollution mitigation to natural and socioeconomic drivers

Quantifying drivers contributing to air quality improvements is crucial for pollution prevention and optimizing local policies. Despite advances in machine learning for air quality analysis, their limited interpretability hinders attribution on global and local scales, vital for informed city management. Our study introduces an innovative framework quantifying socioeconomic and natural impacts on mitigation of particulate matter pollution in 31 Chinese major cities from 2014 to 2021. Two indices, formulated based on the additivity of Shapley additive explanations, are proposed to measure driver contributions globally and locally. Our analysis explores the self-contained and interactive effects of these drivers on particulate levels, pinpointing critical threshold values where these drivers trigger shifts in particulate matter levels. It is revealed that SO2, NOx, and dust emission reductions collectively account for 51.58 % and 51.96 % of PM2.5 and PM10 decreases at the global level. Moreover, our findings unveil a significant heterogeneity in driver contributions to pollutant mitigation across distinct cities, which can be instrumental in crafting location-specific policy recommendations.

Pollution Levels in Indoor School Environment—Case Studies

Air quality in school environments is of particular interest due to the significant amount of time children spend in these settings. Children, being a particularly sensitive demographic, are exposed to various pollutants at school or kindergarten. In this regard, our studies have focused on monitoring the concentrations of three main categories of pollutants: VOCs (volatile organic compounds), VICs and PM (particulate matter). We conducted two experimental campaigns in seven classrooms within public educational institutions. The average concentration values of TVOC (total volatile organic compounds) ranged from 554 µg/m3 to 2518 µg/m3, of CO2 from 1055 ppm to 2050 ppm, of NH₃ (Ammonia) from 843.2 µg/m3 to 1403.4 µg/m3, of PM2.5 from 25.1 µg/m3 to 89.9 µg/m3, and of PM10 from 63.7 µg/m3 to 307.4 µg/m3. In most instances, the registered values exceeded the limit values set by national or international regulations. Furthermore, this study highlights the significant impact of a heat recovery ventilation system in improving indoor air quality by substantially reducing the levels of CO2 and PM. However, it also underscores the need for further measures to more efficiently reduce TVOC concentrations. The aim of our paper was to enhance the understanding of pollution levels in school environments, increase awareness of the importance of indoor air quality, and highlight the adverse effects of polluted air on the health of occupants.