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Environmentally persistent free radicals (EPFRs) play an important role in aerosol effects on air quality and public health, but their atmospheric abundance and sources are poorly understood. We measured EPFRs contained in PM2.5 collected in Fairbanks, Alaska, in winter 2022. We find that EPFR concentrations were enhanced during surface-based inversion and correlate strongly with incomplete combustion markers, including carbon monoxide and elemental carbon (R2 > 0.75). EPFRs exhibit moderately good correlations with PAHs, biomass burning organic aerosols, and potassium (R2 > 0.4). We also observe strong correlations of EPFRs with hydrocarbon-like organic aerosols, Fe and Ti (R2 > 0.6), and single-particle mass spectrometry measurements reveal internal mixing of PAHs, with potassium and iron. These results suggest that residential wood burning and vehicle tailpipes are major sources of EPFRs and nontailpipe emissions, such as brake wear and road dust, may contribute to the stabilization of EPFRs. Exposure to the observed EPFR concentrations (18 ± 12 pmol m-3) would be equivalent to smoking ∼0.4-1 cigarette daily. Very strong correlations (R2 > 0.8) of EPFR with hydroxyl radical formation in surrogate lung fluid indicate that exposure to EPFRs may induce oxidative stress in the human respiratory tract.

First-ever measurements of particulate matter (PM2.5, PM10, and TSP) along with gaseous pollutants (CO, NO2, and SO2) were performed from June 2019 to April 2020 in Faisalabad, Metropolitan, Pakistan, to assess their seasonal variations; Summer 2019, Autumn 2019, Winter 2019-2020, and Spring 2020. Pollutant measurements were carried out at 30 locations with a 3-km grid distance from the Sitara Chemical Industry in District Faisalabad to Bhianwala, Sargodha Road, Tehsil Lalian, District Chiniot. ArcGIS 10.8 was used to interpolate pollutant concentrations using the inverse distance weightage method. PM2.5, PM10, and TSP concentrations were highest in summer, and lowest in autumn or winter. CO, NO2, and SO2 concentrations were highest in summer or spring and lowest in winter. Seasonal average NO2 and SO2 concentrations exceeded WHO annual air quality guide values. For all 4 seasons, some sites had better air quality than others. Even in these cleaner sites air quality index (AQI) was unhealthy for sensitive groups and the less good sites showed Very critical AQI (> 500). Dust-bound carbon and sulfur contents were higher in spring (64 mg g-1) and summer (1.17 mg g-1) and lower in autumn (55 mg g-1) and winter (1.08 mg g-1). Venous blood analysis of 20 individuals showed cadmium and lead concentrations higher than WHO permissible limits. Those individuals exposed to direct roadside pollution for longer periods because of their occupation tended to show higher Pb and Cd blood concentrations. It is concluded that air quality along the roadside is extremely poor and potentially damaging to the health of exposed workers.

Exposure to ambient air pollution has significant adverse health effects; however, whether air pollution is associated with urological cancer is largely unknown. We conduct a systematic review and meta-analysis with epidemiological studies, showing that a 5 μg/m3 increase in PM2.5 exposure is associated with a 6%, 7%, and 9%, increased risk of overall urological, bladder, and kidney cancer, respectively; and a 10 μg/m3 increase in NO2 is linked to a 3%, 4%, and 4% higher risk of overall urological, bladder, and prostate cancer, respectively. Were these associations to reflect causal relationships, lowering PM2.5 levels to 5.8 μg/m3 could reduce the age-standardized rate of urological cancer by 1.5 ~ 27/100,000 across the 15 countries with the highest PM2.5 level from the top 30 countries with the highest urological cancer burden. Implementing global health policies that can improve air quality could potentially reduce the risk of urologic cancer and alleviate its burden.

In California, wildfire risk and severity have grown substantially in the last several decades. Research has characterized extensive adverse health impacts from exposure to wildfire-attributable fine particulate matter (PM2.5), but few studies have quantified long-term outcomes, and none have used a wildfire-specific chronic dose-response mortality coefficient. Here, we quantified the mortality burden for PM2.5 exposure from California fires from 2008 to 2018 using Community Multiscale Air Quality modeling system wildland fire PM2.5 estimates. We used a concentration-response function for PM2.5, applying ZIP code-level mortality data and an estimated wildfire-specific dose-response coefficient accounting for the likely toxicity of wildfire smoke. We estimate a total of 52,480 to 55,710 premature deaths are attributable to wildland fire PM2.5 over the 11-year period with respect to two exposure scenarios, equating to an economic impact of $432 to $456 billion. These findings extend evidence on climate-related health impacts, suggesting that wildfires account for a greater mortality and economic burden than indicated by earlier studies.

Methane is a major contributor to anthropogenic greenhouse gas emissions. Identifying large sources of methane, particularly from the oil and gas sectors, will be essential for mitigating climate change. Aircraft-based methane sensing platforms can rapidly detect and quantify methane point-source emissions across large geographic regions, and play an increasingly important role in industrial methane management and greenhouse gas inventory. We independently evaluate the performance of five major methane-sensing aircraft platforms: Carbon Mapper, GHGSat-AV, Insight M, MethaneAIR, and Scientific Aviation. Over a 6 week period, we released metered gas for over 700 single-blind measurements across all five platforms to evaluate their ability to detect and quantify emissions that range from 1 to over 1,500 kg(CH4)/h. Aircraft consistently quantified releases above 10 kg(CH4)/h, and GHGSat-AV and Insight M detected emissions below 5 kg(CH4)/h. Fully blinded quantification estimates for platforms using downward-facing imaging spectrometers have parity slopes ranging from 0.76 to 1.13, with R2 values of 0.61 to 0.93; the platform using continuous air sampling has a parity slope of 0.5 (R2 = 0.93). Results demonstrate that aircraft-based methane sensing has matured since previous studies and is ready for an increasingly important role in environmental policy and regulation.

Because humans spend about one-third of their time asleep in their bedrooms and are themselves emission sources of volatile organic compounds (VOCs), it is important to specifically characterize the composition of the bedroom air that they experience during sleep. This work uses real-time indoor and outdoor measurements of volatile organic compounds (VOCs) to examine concentration enhancements in bedroom air during sleep and to calculate VOC emission rates associated with sleeping occupants. Gaseous VOCs were measured with proton-transfer reaction time-of-flight mass spectrometry during a multiweek residential monitoring campaign under normal occupancy conditions. Results indicate high emissions of nearly 100 VOCs and other species in the bedroom during sleeping periods as compared to the levels in other rooms of the same residence. Air change rates for the bedroom and, correspondingly, emission rates of sleeping-associated VOCs were determined for two bounding conditions: (1) air exchange between the bedroom and outdoors only and (2) air exchange between the bedroom and other indoor spaces only (as represented by measurements in the kitchen). VOCs from skin oil oxidation and personal care products were present, revealing that many emission pathways can be important occupant-associated emission factors affecting bedroom air composition in addition to direct emissions from building materials and furnishings.

We examined associations between prenatal fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) exposures and child respiratory outcomes through age 8-9 years in 1279 ECHO-PATHWAYS Consortium mother-child dyads. We averaged spatiotemporally modeled air pollutant exposures during four fetal lung development phases: pseudoglandular (5-16 weeks), canalicular (16-24 weeks), saccular (24-36 weeks), and alveolar (36+ weeks). We estimated adjusted relative risks (RR) for current asthma at age 8-9 and asthma with recent exacerbation or atopic disease, and odds ratios (OR) for wheezing trajectories using modified Poisson and multinomial logistic regression, respectively. Effect modification by child sex, maternal asthma, and prenatal environmental tobacco smoke was explored. Across all outcomes, 95% confidence intervals (CI) included the null for all estimates of associations between prenatal air pollution exposures and respiratory outcomes. Pseudoglandular PM2.5 exposure modestly increased risk of current asthma (RRadj = 1.15, 95% CI: 0.88-1.51); canalicular PM2.5 exposure modestly increased risk of asthma with recent exacerbation (RRadj = 1.26, 95% CI: 0.86-1.86) and persistent wheezing (ORadj = 1.28, 95% CI: 0.86-1.89). Similar findings were observed for O3, but not NO2, and associations were strengthened among mothers without asthma. While not statistically distinguishable from the null, trends in effect estimates suggest some adverse associations of early pregnancy air pollution exposures with child respiratory conditions, warranting confirmation in larger samples.

Cities represent a significant and growing portion of global carbon dioxide (CO2) emissions. Quantifying urban emissions and trends over time is needed to evaluate the efficacy of policy targeting emission reductions as well as to understand more fundamental questions about the urban biosphere. A number of approaches have been proposed to measure, report, and verify (MRV) changes in urban CO2 emissions. Here we show that a modest capital cost, spatially dense network of sensors, the Berkeley Environmental Air Quality and CO2 Network (BEACO2N), in combination with Bayesian inversions, result in a synthesis of measured CO2 concentrations and meteorology to yield an improved estimate of CO2 emissions and provide a cost-effective and accurate assessment of CO2 emissions trends over time. We describe nearly 5 years of continuous CO2 observations (2018-2022) in a midsized urban region (the San Francisco Bay Area). These observed concentrations constrain a Bayesian inversion that indicates the interannual trend in urban CO2 emissions in the region has been a modest decrease at a rate of 1.8 ± 0.3%/year. We interpret this decrease as primarily due to passenger vehicle electrification, reducing on-road emissions at a rate of 2.6 ± 0.7%/year.

BACKGROUND: Epidemiological findings regarding the association of particulate matter ≤2.5 μm (PM2.5) exposure with hypertensive disorders in pregnancy (HDP) are inconsistent; evidence for HDP risk related to PM2.5 components, mixture effects, and windows of susceptibility is limited. We aimed to investigate the relationships between HDP and exposure to PM2.5 during pregnancy. METHODS AND FINDINGS: A large retrospective cohort study was conducted among mothers with singleton pregnancies in Kaiser Permanente Southern California from 2008 to 2017. HDP were defined by International Classification of Diseases-9/10 (ICD-9/10) diagnostic codes and were classified into 2 subcategories based on the severity of HDP: gestational hypertension (GH) and preeclampsia and eclampsia (PE-E). Monthly averages of PM2.5 total mass and its constituents (i.e., sulfate, nitrate, ammonium, organic matter, and black carbon) were estimated using outputs from a fine-resolution geoscience-derived model. Multilevel Cox proportional hazard models were used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of PM2.5 constituents. The distributed lag model was applied to estimate the association between monthly PM2.5 exposure and HDP risk. This study included 386,361 participants (30.3 ± 6.1 years) with 4.8% (17,977/373,905) GH and 5.0% (19,381/386,361) PE-E cases, respectively. In single-pollutant models, we observed increased relative risks for PE-E associated with exposures to PM2.5 total mass [adjusted hazard ratio (HR) per interquartile range: 1.07, 95% confidence interval (CI) [1.04, 1.10] p < 0.001], black carbon [HR = 1.12 (95% CI [1.08, 1.16] p < 0.001)] and organic matter [HR = 1.06 (95% CI [1.03, 1.09] p < 0.001)], but not for GH. The population attributable fraction for PE-E corresponding to the standards of the US Environmental Protection Agency (9 μg/m3) was 6.37%. In multi-pollutant models, the PM2.5 mixture was associated with an increased relative risk of PE-E ([HR = 1.05 (95% CI [1.03, 1.07] p < 0.001)], simultaneous increase in PM2.5 constituents of interest by a quartile) and PM2.5 black carbon gave the greatest contribution of the overall mixture effects (71%) among all individual constituents. The susceptible window is the late first trimester and second trimester. Furthermore, the risks of PE-E associated with PM2.5 exposure were significantly higher among Hispanic and African American mothers and mothers who live in low- to middle-income neighborhoods (p < 0.05 for Cochrans Q test). Study limitations include potential exposure misclassification solely based on residential outdoor air pollution, misclassification of disease status defined by ICD codes, the date of diagnosis not reflecting the actual time of onset, and lack of information on potential covariates and unmeasured factors for HDP. CONCLUSIONS: Our findings add to the literature on associations between air pollution exposure and HDP. To our knowledge, this is the first study reporting that specific air pollution components, mixture effects, and susceptible windows of PM2.5 may affect GH and PE-E differently.

Wildfires are a significant threat to human health, in part through degraded air quality. Prescribed burning can reduce wildfire severity but can also lead to an increase in air pollution. The complexities of fires and atmospheric processes lead to uncertainties when predicting the air quality impacts of fire and make it difficult to fully assess the costs and benefits of an expansion of prescribed fire. By modeling differences in emissions, surface conditions, and meteorology between wildfire and prescribed burns, we present a novel comparison of the air quality impacts of these fire types under specific scenarios. One wildfire and two prescribed burn scenarios were considered, with one prescribed burn scenario optimized for potential smoke exposure. We found that PM2.5 emissions were reduced by 52%, from 0.27 to 0.14 Tg, when fires burned under prescribed burn conditions, considerably reducing PM2.5 concentrations. Excess short-term mortality from PM2.5 exposure was 40 deaths for fires under wildfire conditions and 39 and 15 deaths for fires under the default and optimized prescribed burn scenarios, respectively. Our findings suggest prescribed burns, particularly when planned during conditions that minimize smoke exposure, could be a net benefit for the impacts of wildfires on air quality and health.

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 < 5 μg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with

Future climate change can cause more days with poor air quality. This could trigger more alerts telling people to stay inside to protect themselves, with potential consequences for health and health equity. Here, we study the change in US air quality alerts over this century due to fine particulate matter (PM2.5), who they may affect, and how they may respond. We find air quality alerts increase by over 1 mo per year in the eastern United States by 2100 and quadruple on average. They predominantly affect areas with high Black populations and leakier homes, exacerbating existing inequalities and impacting those less able to adapt. Reducing emissions can offer significant annual health benefits ($5,400 per person) by mitigating the effect of climate change on air pollution and its associated risks of early death. Relying on people to adapt, instead, would require them to stay inside, with doors and windows closed, for an extra 142 d per year, at an average cost of $11,000 per person. It appears likelier, however, that people will achieve minimal protection without policy to increase adaptation rates. Boosting adaptation can offer net benefits, even alongside deep emission cuts. New adaptation policies could, for example: reduce adaptation costs; reduce infiltration and improve indoor air quality; increase awareness of alerts and adaptation; and provide measures for those working or living outdoors. Reducing emissions, conversely, lowers everyones need to adapt, and protects those who cannot adapt. Equitably protecting human health from air pollution under climate change requires both mitigation and adaptation.

Electrifying freight trucks will be key to alleviating air pollution burdens on disadvantaged communities and mitigating climate change. The United States plans to pursue this aim by adding vehicle charging infrastructure along specific freight corridors. This study explores the coevolution of the electricity grid and freight trucking landscape using an integrated assessment framework to identify when each interstate and drayage corridor becomes advantageous to electrify from a climate and human health standpoint. Nearly all corridors achieve greenhouse gas emission reductions if electrified now. Most can reduce health impacts from air pollution if electrified by 2040 although some corridors in the Midwest, South, and Mid-Atlantic regions remain unfavorable to electrify from a human health standpoint, absent policy support. Recent policy, namely, the Inflation Reduction Act, accelerates this timeline to 2030 for most corridors and results in net human health benefits on all corridors by 2050, suggesting that near-term investments in truck electrification, particularly drayage corridors, can meaningfully reduce climate and health burdens.

BackgroundPrior studies suggested that air pollution exposure may increase the risk of Parkinson's Disease (PD). We investigated the long-term impacts of traffic-related and multiple sources of particulate air pollution on PD in central California.MethodsOur case-control analysis included 761 PD patients and 910 population controls. We assessed exposure at residential and occupational locations from 1981 to 2016, estimating annual average carbon monoxide (CO) concentrations - a traffic pollution marker - based on the California Line Source Dispersion Model, version 4. Additionally, particulate matter (PM2.5) concentrations were based on a nationwide geospatial chemical transport model. Exposures were assessed as 10-year averages with a 5-year lag time prior to a PD diagnosis for cases and an interview date for controls, subsequently categorized into tertiles. Logistic regression models were used, adjusting for various factors.ResultsTraffic-related CO was associated with an increased odds ratio for PD at residences (OR for T3 vs. T1: 1.58; 95% CI: 1.20, 2.10; p-trend = 0.02) and workplaces (OR for T3 vs. T1: 1.91; 95% CI: 1.22, 3.00; p-trend

The short-term adverse effects of ambient fine particulate matter (PM 2.5) and ozone (O 3) on anxiety disorders (ADs) remained inconclusive. We applied an individual-level time-stratified case-crossover study, which including 126,112 outpatient visits for ADs during 2019–2021 in Guangdong province, China, to investigate the association of short-term exposure to PM 2.5 and O 3 with outpatient visits for ADs, and estimate excess outpatient visits in South China. Daily residential air pollutant exposure assessments were performed by extracting grid data (spatial resolution: 1 km × 1 km) from validated datasets. We employed the conditional logistic regression model to quantify the associations and excess outpatient visits. The results of the single-pollutant models showed that each 10 μg/m3 increase of PM 2.5 and O 3 exposures was significantly associated with a 3.14 % (95 % confidence interval: 2.47 %, 3.81 %) and 0.88 % (0.49 %, 1.26 %) increase in odds of outpatient visits for ADs, respectively. These associations remained robust in 2-pollutant models. The proportion of outpatient visits attributable to PM 2.5 and O 3 exposures was up to 7.20 % and 8.93 %, respectively. Older adults appeared to be more susceptible to PM 2.5 exposure, especially in cool season, and subjects with recurrent outpatient visits were more susceptible to O 3 exposure. As our study subjects were from one single hospital in China, it should be cautious when generalizing our findings to other regions. Short-term exposure to ambient PM 2.5 and O 3 was significantly associated with a higher odds of outpatient visits for ADs, which can contribute to considerable excess outpatient visits. • Exposure to ambient PM 2.5 and O 3 was associated with an increased odds of outpatient visits for anxiety disorders. • PM 2.5 and O 3 exposures were attributable to considerable excess outpatient visits. • Older adults were more susceptible to PM 2.5 exposure, especially in cool season. • Subjects with recurrent outpatient visits were more susceptible to O 3 exposure. [ABSTRACT FROM AUTHOR]

With deteriorating air pollution and climate change, generating power with cleaner technologies to meet energy demand of economic development has become a crucial policy consideration globally. Biomass power generation, despite being cleaner than coal power generation, still emits certain air pollutants that can impact ambient air quality. On the other hand, biomass power plants might mitigate air pollution by reducing open-field crop burning. With this counteracting in play, it is unclear which effect is dominant and how biomass power generation affects ambient air quality eventually. We build a unique spatially high-resolution dataset for 20-km-radius circles, considering both regions with biomass power plants and those without, to explore the impacts of biomass power generation on air quality in nearby regions. By applying panel and canonical difference-in-differences models with various model specifications and estimation strategies, we demonstrate that biomass power generation in China significantly reduces ambient annual concentrations of PM2.5, PM10, SO2, and CO. The impacts on NO2 reduction could only be observed in summer, when open-field burnings decreased substantially. The impacts on PM2.5 could be observed in both summer and fall. No seasonal pattern is observed for the reductions in PM10, SO2, and CO concentrations. [ABSTRACT FROM AUTHOR]

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

This paper aims to evaluate the statistical association between exposure to air pollution and forced expiratory volume in the first second (FEV1) in both asthmatic and non-asthmatic children and teenagers, in which the response variable FEV1 was repeatedly measured on a monthly basis, characterizing a longitudinal experiment. Due to the nature of the data, an robust linear mixed model (RLMM), combined with a robust principal component analysis (RPCA), is proposed to handle the multicollinearity among the covariates and the impact of extreme observations (high levels of air contaminants) on the estimates. The Huber and Tukey loss functions are considered to obtain robust estimators of the parameters in the linear mixed model (LMM). A finite sample size investigation is conducted under the scenario where the covariates follow linear time series models with and without additive outliers (AO). The impact of the time-correlation and the outliers on the estimates of the fixed effect parameters in the LMM is investigated. In the real data analysis, the robust model strategy evidenced that RPCA exhibits three principal component (PC), mainly related to relative humidity (Hmd), particulate matter with a diameter smaller than 10 μm (PM10) and particulate matter with a diameter smaller than 2.5 μm (PM2.5). [ABSTRACT FROM AUTHOR]

Indoor air pollution is becoming a rising public health problem and is largely resulting from the burning of solid fuels and heating in households. Burning these fuels produces harmful compounds, such as particulate matter regarded as a major health risk, particularly affecting the onset and exacerbation of respiratory diseases. As exposure to polluted indoor air can cause DNA damage including DNA sd breaks as well as chromosomal damage, in this paper, we aim to provide an overview of the impact of indoor air pollution on DNA damage and genome stability by reviewing the scientific papers that have used the comet, micronucleus, and γ-H2AX assays. These methods are valuable tools in human biomonitoring and for studying the mechanisms of action of various pollutants, and are readily used for the assessment of primary DNA damage and genome instability induced by air pollutants by measuring different aspects of DNA and chromosomal damage. Based on our search, in selected studies (in vitro, animal models, and human biomonitoring), we found generally higher levels of DNA strand breaks and chromosomal damage due to indoor air pollutants compared to matched control or unexposed groups. In summary, our systematic review reveals the importance of the comet, micronucleus, and γ-H2AX assays as sensitive tools for the evaluation of DNA and genome damaging potential of different indoor air pollutants. Additionally, research in this particular direction is warranted since little is still known about the level of indoor air pollution in households or public buildings and its impact on genetic material. Future studies should focus on research investigating the possible impact of indoor air pollutants in complex mixtures on the genome and relate pollutants to possible health outcomes. [ABSTRACT FROM AUTHOR]

Low-cost sensors are becoming an important component of air quality monitoring. They are used in various outdoor areas beyond the protective enclosure of air quality monitoring stations. Therefore, they are exposed to a wide range of environmental conditions. In this study, we investigated the operation status and performance of an air quality monitor consisting of low-cost sensors for measuring PM2.5 and CO under extreme air pollutant concentrations. Over deployment periods of three haze episodes in Beijing, China, and two bushfire episodes in the Blue Mountains, Australia, the monitors collected air quality data for community and research users. During the extreme air pollution episodes, the operation of the monitors was not affected by the extremely high PM2.5 and CO concentrations. They showed the greatest overestimation of PM2.5 measurements in comparison with the reference instruments during the Beijing summer haze period. The regression slopes between the monitors and reference instruments were 2.24 for the summer haze period, 1.58 for the spring haze period, and 1.54 for the summer haze period. Under the extreme air pollution conditions in the Blue Mountains, monitors overestimated PM2.5 in the winter bushfire period but underestimated it in the summer bushfire period. The absolute values of the PM2.5 and CO concentrations from the monitors may vary from the reference instruments; however, they captured the trends and rapid elevation of air pollutants under extreme air pollution conditions. The results of this study demonstrate that low-cost air quality monitors can be used under extreme conditions in different areas for specified purposes such as community, citizen applications, air pollution management, and scientific research. [ABSTRACT FROM AUTHOR]

The interflat cross-contamination of air pollutants such as coronavirus disease 2019 (COVID-19) in built environments has become a growing concern. This study investigates the effect of the geometrical details of building facades on wind-induced airborne pollutant transmission routes in high-rise buildings. Parametric studies of different external-shading elements of buildings, wind speeds, and wind directionality are considered. A high-resolution computational fluid dynamics (CFD) using a realizable k-epsilon turbulence closure model is employed to analyze the airflow field. For the windward single-sided ventilation case, the reentry ratio from the source room to the other unit under prevailing, 45°, and 90° wind directions are quantified, and the possible interflat cross-contamination routes are simulated. The transmission route is highly dependent on a building's architectural features, wind speed, wind directionality, and location of the source room. The result shows that external shading plays a crucial role in mitigating or accelerating airborne pollutant transmissions. A building with horizontal shadings restricts vertical cross-contamination between flats, but it allows horizontal interflat cross-contamination. However, buildings with vertical shadings reduce the risk of horizontal cross-contamination but increase the probability of vertical cross-contamination. The egg-crate shading minimizes the risk of both horizontal and vertical cross-contamination. A smooth facade building is highly susceptible to cross-contamination for a wide range of wind directionality. Therefore, this study is helpful for architecture and building science for the analysis of airborne pollutants, for tracing the routes of cross-contamination in residential buildings, and for reducing the risk of transmission of respiratory diseases such as COVID-19. [ABSTRACT FROM AUTHOR]

One of the main global problems related to the environment is air pollution which not only affects the environment and the ecosystem but also affects human health. Many countries of the world did research on how to reduce air pollution so that the concentrations do not exceed the permissible thresholds which are set at that level so that neither human health nor the environment are exposed to further damage. One of the issues regarding air pollution is the concentrations of PM particles 2.5 and 10, PM particles are a big problem in developing countries such as the Republic of North Macedonia. The research paper was focused in processing the data that has been collected for daily averages of PM 2,5 and PM10 particles that contribute in air pollution. All analyzes and processing of the results are done in compliance with the current laws of the Republic of North Macedonia and with Directive 2008/50/EC, all for µg/m3. In the city of Skopje, numerous exceedances of the permissible thresholds of PM particles 2.5 and 10 were recorded at the two measurement stations where the results were obtained for the months of January, February, March, April, May and June of 2023. [ABSTRACT FROM AUTHOR]

Accumulating animal studies have demonstrated associations between ambient air pollution (AP) and metabolic dysfunction-associated fatty liver disease (MAFLD), but relevant epidemiological evidence is limited. We evaluated the association of long-term exposure to AP with the risk of incident MAFLD in Northwest China. The average AP concentration between baseline and follow-up was used to assess individual exposure levels. Cox proportional hazard models and restricted cubic spline functions (RCS) were used to estimate the association of PM2.5 and its constituents with the risk of MAFLD and the dose–response relationship. Quantile g-computation was used to assess the joint effects of mixed exposure to air pollutants on MAFLD and the weights of the various pollutants. We observed 1516 cases of new-onset MAFLD, with an incidence of 10.89%. Increased exposure to pollutants was significantly associated with increased odds of MAFLD, with hazard ratios (HRs) of 2.93 (95% CI: 1.22, 7.00), 2.86 (1.44, 5.66), 7.55 (3.39, 16.84), 4.83 (1.89, 12.38), 3.35 (1.35, 8.34), 1.89 (1.02, 1.62) for each interquartile range increase in PM2.5, SO42−, NO3−, NH4+, OM, and BC, respectively. Stratified analyses suggested that females, frequent exercisers and never-drinkers were more susceptible to MAFLD associated with ambient PM2.5 and its constituents. Mixed exposure to SO42−, NO3−, NH4+, OM and BC was associated with an increased risk of MAFLD, and the weight of BC had the strongest effect on MAFLD. Exposure to ambient PM2.5 and its constituents increased the risk of MAFLD. [ABSTRACT FROM AUTHOR]

The presence of pollutants in the earth's atmosphere has a direct impact on human health and the environment. So that pollutants such as carbon monoxide (CO) and particulate matter (PM) cause respiratory diseases, cough headache, etc. Since the amount of pollutants in the air is related to environmental and urban factors, the aim of the current research is to investigate the relationship between the concentration of CO, PM2.5 and PM10 with urban-environmental factors including land use, wind speed and wind direction, topography, traffic, road network, and population through a Land use regression (LUR) model. The concentrations of CO, PM2.5 and PM10 were measured during four seasons from 26th of March 2022 to 16th of March 2023 at 25 monitoring stations and then the information about pollutant measurement points and Land use data were entered into the ArcGIS software. The annual average concentrations of CO, PM2.5 and PM10 were 0.7 ppm, 18.94 and 60.76 µg/m3, respectively, in which the values of annual average concentration of CO and PMs were outside the air quality guideline standard. The results of the health risk assessment showed that the hazard quotient values for all three investigated pollutants were lower than 1 and therefore, they were not in adverse conditions in terms of health effects. Among the urban-environmental factors affecting air pollution, the traffic variable is the most important factor affecting the annual LUR model of CO, PM2.5 and PM10, and then the topography variable is the second most effective factor on the annual LUR model of the aforementioned pollutants. [ABSTRACT FROM AUTHOR]

Impaired cognitive health is the leading cause of various disabilities and disorders. Air pollution has been dramatically increasing over the last few decades and has been identified as a potential risk factor for impaired cognitive health. This study investigates the effect of air pollutants, particulate matter (PM2.5, PM10), sulfur dioxide (SO2), and ground-level ozone, on global cognitive health. The data on environmental pollutants and cognitive health were recorded from PubMed, Web of Science, Scopus, and Google Scholar. Initially, 790 articles were identified after screening for duplicates and applying the inclusion and exclusion criteria, 21 studies were included, and data was synthesized to get a pooled result. The overall results revealed that increased exposure to PM2.5 was positively and significantly associated with cognitive decline (OR 1.49; 95% CI 1.11, 1.99; p = 0.01). The risk of cognitive impairment due to PM10 (OR 1.30; 95% CI 1.00–1.70, p = 0.05), and SO2 (OR 1.39; 95% CI 1.27–1.51; p < 0.01) exposure were also significantly heightened. The study findings show that overall exposure to particulate matter PM2.5, PM10, and SO2 was associated with an increased risk of a decrease in global cognitive functions. The findings suggest that reducing levels of air pollutants could be a strategic approach to mitigate cognitive health risks in populations worldwide. [ABSTRACT FROM AUTHOR]

We have undertaken a systematic review and meta-analysis to investigate the association between maternal exposure to air pollutants and outcomes of in vitro fertilization (IVF). Studies were identified through a comprehensive online search. After standardizing all air pollution concentrations to 10 μg/m3, we analyzed the levels of six air pollutants (PM2.5, PM10, O3, NO2, CO, and SO2) by applying a random effects model. A total of five articles met inclusion criteria upon final reviewing. Exposure to PM10, NO2, and CO was linked to the risk of ectopic pregnancy, while exposure to O3 was found to have a reverse association with biochemical pregnancy. Additionally, our analysis indicated a negative association between exposure to PM10, NO2, CO, and SO2 and live birth rates, as well as between NO2 exposure and intrauterine pregnancy. Our study emphasized the relationship between exposure to ambient air pollution and negative effects on pregnancy outcomes for women undergoing IVF. [ABSTRACT FROM AUTHOR]

We investigated the association between ambient air pollutant exposure and periodontal health using data from 17,271 adults in the Korea National Health and Nutrition Examination Survey (2012–2015). Participants’ periodontal status was categorized based on their community periodontal index (CPI) scores. Using multiple logistic regression models, we examined the relationship between air pollutant levels and poor periodontal status at various lag periods. After adjusting for potential confounders, PM10 exposure was associated with a poor periodontal status (short-term: 0–1 and 0–2 lag days; medium-term: 0–1 and 0–2 lag months). SO2 exposure showed similar associations (short-term, 0–2 to 0–7 lag days; medium-term, 0–4 to 0–6 lag months). Only increased medium-term O3 exposure (0–2 to 0–6 lag months) was associated with a poor periodontal status. NO2 exposure was inversely associated with poor periodontal status for both short- and medium-term durations. [ABSTRACT FROM AUTHOR]

Air pollution stands as an environmental risk to child mental health, with proven relationships hitherto observed only in urban areas. Understanding the impact of pollution in rural settings is equally crucial. The novelty of this article lies in the study of the relationship between air pollution and behavioural and developmental disorders, attention deficit hyperactivity disorder (ADHD), anxiety, and eating disorders in children below 15 living in a rural area. The methodology combines spatio-temporal models, Bayesian inference and Compositional Data (CoDa), that make it possible to study areas with few pollution monitoring stations. Exposure to nitrogen dioxide (NO2), ozone (O3), and sulphur dioxide (SO2) is related to behavioural and development disorders, anxiety is related to particulate matter (PM10), O3 and SO2, and overall pollution is associated to ADHD and eating disorders. To sum up, like their urban counterparts, rural children are also subject to mental health risks related to air pollution, and the combination of spatio-temporal models, Bayesian inference and CoDa make it possible to relate mental health problems to pollutant concentrations in rural settings with few monitoring stations. Certain limitations persist related to misclassification of exposure to air pollutants and to the covariables available in the data sources used. [ABSTRACT FROM AUTHOR]

\nHIGHLIGHTSThis research examines particulate matter with a diameter of 2.5 micrometers (PM2.5) and ozone (O3) variation across the climatic mesoregions of Alagoas. Mean PM2.5 and O3 concentrations across three mesoregions were as follows: East (5.91; 44.22 μg.m−3), Hinterland (6.90; 44.18 μg.m−3), and Arid (7.03; 44.23 μg.m−3). Spatial and temporal variations were observed, with PM2.5 concentrations highest in the northwest (NW) and O3 concentrations in the east (E), influenced by local sources, weather, and transportation. Differences between rainy and dry years were noted, attributed to biomass burning and dust particle transport. This study establishes a baseline for understanding air quality, lacking monitoring stations, aiding policymaking. It provides insights into PM2.5 and O3 dynamics, with PM2.5 concentrations highest in the NW and lower O3 concentrations in the E. Temporal variations emphasize the need for dynamic monitoring. Positive correlations between PM2.5 and O3 highlight complex relationships. Practical implications include proactive policymaking and the necessity for monitoring stations. Rigorous statistical methodologies inform model selection, enhancing environmental data understanding. Despite changes in land use, studies on extreme probability distributions are limited, emphasizing the need for robust methodologies for environmental data analysis to address air pollution challenges effectively in Alagoas. Spatio-temporal variability of the airborne pollutant criteria measured in Alagoas.Database of air pollutants of the state of Alagoas.Significant difference in the concentration of air pollutants between the dry and rainy seasons.Correlation between air pollutantsSpatio-temporal variability of the airborne pollutant criteria measured in Alagoas.Database of air pollutants of the state of Alagoas.Significant difference in the concentration of air pollutants between the dry and rainy seasons.Correlation between air pollutants [ABSTRACT FROM AUTHOR]

At present, under the influence of environmental pollution, the color of architectural painting gradually darkens, loses luster, and even cracks when the pigment falls off, which seriously affects the long-term preservation of architectural painting. In order to study the damage mechanism of dust particles to the color of the architectural painting, this study took the archery tower at the West Gate as the research object, monitored the temperature and humidity of the indoor environment, and analyzed the composition of the dust by ICP-MS, IC, and XRD. The experimental results showed notable fluctuations in the indoor humidity in inner the archery tower at the West Gate during the monitoring period from January to March, which were not conducive to the preservation of wood-colored paintings. The 24-h average PM2.5 and PM10 concentrations, measured over 2 days in January, were beyond the National Ambient Air Quality Standard norms, and PM contains a large amount of soluble salts such as sulfate and nitrate, causing serious salt erosion and damage to the color painting layer. Through the simulation experiment of the color painting layer, it was revealed that the dust particles deposited on the surface of the color painting layer change the spectral characteristics of the color painting layer, and then cause the color layer to lose its original hue, fade become blurred, or darken. It was anticipated that this research would serve as a valuable reference for the preventive protection of the color painting layer of the archery tower at West Gate. [ABSTRACT FROM AUTHOR]

The study examines the relationship between air quality, meteorological factors, and COVID-19 cases in Cheras, Kuala Lumpur, and Kelapa Gading, North Jakarta. Analyzing data from 2020 and 2021, the research found notable correlations: COVID-19 cases in Cheras were positively associated with relative humidity (RH) and carbon monoxide (CO) but negatively with ozone (O₃) and RH in different years. In Kelapa Gading, COVID-19 cases were positively correlated with pollutants like sulfur dioxide (SO₂) and CO, while ambient temperature (AT) showed a negative correlation. The enforcement of social restrictions notably reduced air pollution, affecting COVID-19 spread. Predictive models for PM2.5 levels using robust regression techniques showed strong performance in Kuala Lumpur (R² > 0.9) but exhibited overfitting tendencies in Jakarta, suggesting the need for a longer study period for more accurate results. [ABSTRACT FROM AUTHOR]

Heavy metal and Persistent Organic Pollutants (POPs) pollution stemming from industrialization, intensive agriculture, and other human activities pose significant environmental and health threats. These contaminants persist in the air, soil, and water, particularly in industrialized nations, adversely affecting human health and ecosystems. While physical and chemical methods exist for detoxifying contaminated soil, they often have drawbacks such as high cost and technical complexity. Bioremediation, utilizing plants and microbes, offers a promising solution. Certain microorganisms like Streptomyces, Aspergillus and plant species such as Hibiscus and Helianthus show high metal adsorption capacities, making them suitable for bioremediation. However, plants' slow growth and limited remediation efficiency have been challenges. Recent advancements involve leveraging plant-associated microbes to enhance heavy metal removal. Additionally, nanotechnology, particularly nano-bioremediation, shows promise in efficiently removing contaminants from polluted environments by combining nanoparticles with bioremediation techniques. This review underscores bioremediation methods for heavy metals using plants and microbes, focusing on the role of Plant Growth Promoting Rhizobacteria (PGPR) in promoting phytoremediation. It also explores the implementation of nanotechnologies for eliminating metals from polluted soil, emphasizing the significance of soil microbiomes, nanoparticles, and contaminant interactions in developing effective nano-remediation strategies for optimizing agriculture in contaminated fields. [ABSTRACT FROM AUTHOR]

AbstractFluoride is one of the most highly toxic soil and air pollutant prevalent in aquatic as well as terrestrial ecosystems. It seriously affects crop plant quality and productivity worldwide. Although a crop with great nutritional value; oats are susceptible to a variety of abiotic stresses. In the current study, the responses of six oat cultivars (JHO-99-1, JHO-2009, BJ-2012, KANT, JHO-822, and JHO-2000) to fluoride stress on growth measurements, photosynthetic pigments, and photosynthetic parameters have been studied. The fluoride (200 and 400 mg/kg) was added to the soil artificially, seeds were sown and the pots were kept under controlled conditions. Another set of plants without the fluoride treatment (0 mg/kg) were labeled as control. The experiment was conducted in a plant growth chamber and fluoride was artificially added to the soil prior to seeding. All six oat cultivars subjected to fluoride stress exhibited an overall decrease in plant growth when compared to the control. Further under fluoride stress, while the oat cultivars also showed a decrease in chlorophyll content and different photosynthetic parameters but on the contrary the antioxidant activities were increased. While the cultivar JHO-822 was most affected under fluoride stress, JHO-99-1 showed tolerance toward fluoride toxicity in comparison to other cultivars JHO-2009, BJ-2012, KANT, JHO-822, and JHO-2000. It is concluded that the tolerance or susceptibility of a cultivar to fluoride can be well correlated with various parameters studied in the present study. [ABSTRACT FROM AUTHOR]

Background: Despite accumulating evidence of an association between air pollution and renal disease, studies on the association between long-term exposure to air pollution and renal function are still contradictory. This study aimed to investigate this association in a large population with relatively low exposure and with improved estimation of renal function as well as renal injury biomarkers. Methods: We performed a cross-sectional analysis in the middle-aged general population participating in the Swedish CardioPulmonary bioImaging Study (SCAPIS; n = 30 154). Individual 10-year exposure to total and locally emitted fine particulate matter (PM2.5), inhalable particulate matter (PM10), and nitrogen oxides (NOx) were modelled using high-resolution dispersion models. Linear regression models were used to estimate associations between exposures and estimated glomerular filtration rate (eGFR, combined creatinine and cystatin C) and serum levels of renal injury biomarkers (KIM-1, MCP-1, IL-6, IL-18, MMP-2, MMP-7, MMP-9, FGF-23, and uric acid), with consideration of potential confounders. Results: Median long-term PM2.5 exposure was 6.2 µg/m3. Almost all participants had a normal renal function and median eGFR was 99.2 mL/min/1.73 m2. PM2.5 exposure was associated with 1.3% (95% CI 0.6, 2.0) higher eGFR per 2.03 µg/m3 (interquartile range, IQR). PM2.5 exposure was also associated with elevated serum matrix metalloproteinase 2 (MMP-2) concentration, with 7.2% (95% CI 1.9, 12.8) higher MMP-2 per 2.03 µg/m3. There was a tendency towards an association between PM10 and higher levels of uric acid, but no associations were found with the other biomarkers. Associations with other air pollutants were null or inconsistent. Conclusion: In this large general population sample at low exposure levels, we found a surprising association between PM2.5 exposure and a higher renal filtration. It seems unlikely that particle function would improve renal function. However, increased filtration is an early sign of renal injury and may be related to the relatively healthy population at comparatively low exposure levels. Furthermore, PM2.5 exposure was associated with higher serum concentrations of MMP-2, an early indicator of renal and cardiovascular pathology. [ABSTRACT FROM AUTHOR]

Background: Particulate matter exposure (PM) is a cause of aerodigestive disease globally. The destruction of the World Trade Center (WTC) exposed first responders and inhabitants of New York City to WTC-PM and caused obstructive airways disease (OAD), gastroesophageal reflux disease (GERD) and Barrett's Esophagus (BE). GERD not only diminishes health-related quality of life but also gives rise to complications that extend beyond the scope of BE. GERD can incite or exacerbate allergies, sinusitis, bronchitis, and asthma. Disease features of the aerodigestive axis can overlap, often necessitating more invasive diagnostic testing and treatment modalities. This presents a need to develop novel non-invasive biomarkers of GERD, BE, airway hyperreactivity (AHR), treatment efficacy, and severity of symptoms. Methods: Our observational case-cohort study will leverage the longitudinally phenotyped Fire Department of New York (FDNY)-WTC exposed cohort to identify Biomarkers of Airway Disease, Barrett's and Underdiagnosed Reflux Noninvasively (BAD-BURN). Our study population consists of n = 4,192 individuals from which we have randomly selected a sub-cohort control group (n = 837). We will then recruit subgroups of i. AHR only ii. GERD only iii. BE iv. GERD/BE and AHR overlap or v. No GERD or AHR, from the sub-cohort control group. We will then phenotype and examine non-invasive biomarkers of these subgroups to identify under-diagnosis and/or treatment efficacy. The findings may further contribute to the development of future biologically plausible therapies, ultimately enhance patient care and quality of life. Discussion: Although many studies have suggested interdependence between airway and digestive diseases, the causative factors and specific mechanisms remain unclear. The detection of the disease is further complicated by the invasiveness of conventional GERD diagnosis procedures and the limited availability of disease-specific biomarkers. The management of reflux is important, as it directly increases risk of cancer and negatively impacts quality of life. Therefore, it is vital to develop novel noninvasive disease markers that can effectively phenotype, facilitate early diagnosis of premalignant disease and identify potential therapeutic targets to improve patient care. Trial registration: Name of Primary Registry: "Biomarkers of Airway Disease, Barrett's and Underdiagnosed Reflux Noninvasively (BADBURN)". Trial Identifying Number: NCT05216133. Date of Registration: January 31, 2022. [ABSTRACT FROM AUTHOR]

Background: Tracheal, Bronchus, and Lung (TBL) cancer continues to represent the majority of cancer-related incidence and mortality in United States (U.S.). While air pollutants are considered essential risk factors, both global and national average concentrations of major harmful air pollutants have significantly decreased over the decades. Green space may have a beneficial effect on human health. Methods: We obtained data on national and state-level burden of TBL cancer, the annual average concentration of main air pollutants, and levels of green spaces in 2007, 2013, and 2019. According to generalized estimating equation (GEE), we examine the associations among incidence and mortality of TBL cancer, air pollutants, and greenspaces, represented by the Normalized Difference Vegetation Index (NDVI) in different age groups with models adjusted with meteorological, and socio-demographic. We observed additional effects of the interaction between the NDVI, Ozone, PM2.5, and other factors, which helped us to interpret and understand our results. Also, we collated states that witnessed net increments in forest coverage and conducted the same analysis separately. Results: In our analysis, the majority of associations between NDVI and air pollutants with TBL cancer remained significantly positive, particularly noticeable among individuals aged 20 to 54. However, our findings did not explore air pollution as a potential mediator between greenspace exposure and TBL cancer. While the associations of PM2.5 with TBL cancer remained positive, the other four pollutants showed positive but statistically insignificant associations. Our interaction analysis yielded that there were positive associations between NDVI and ozone, PM2.5, and tobacco use. Max NDVI acts as a protective factor along with high HDI. Additionally, PM2.5 and HDI also showed a negative association. In 18 states with more forest, NDVI acts as a protective factor along with higher health care coverage, better health status, and participation in physical activities. Conclusion: In the state-level of U.S., the effects of total greenspace with TBL cancer are mixed and could be modified by various socio-economic factors. PM2.5 has a direct correlation with TBL cancer and the effects can be influenced by underlying socioeconomic conditions. [ABSTRACT FROM AUTHOR]

KEY POINTS Human nasal cavity samples were collected, and presence of microplastics were evaluated. Microplastics were present, and major types were polyethylene, polyester, acrylic polymer, and polypropylene. Further research is needed regarding microplastics and its clinical impact on human nasal cavity. [ABSTRACT FROM AUTHOR]

The development of adsorbents for air pollutant remediation and effective monitoring is of interest. Then, the effect of the APTES functionalization ratio on the impact of the adsorption and detection of SO2 molecules was evaluated. The higher APTES functionalization material (SBA-15_6.1APTES) shows a high uptake of 1.15 mmol g−1 at 0.001 bar and 298 K. Fluorescence, time-resolved photoluminescence, and quantum yield experiments revealed a turn-on effect specifically for SO2 molecules, indicating high selectivity, suggesting host-to-guest energy transfer. Attractively, XPS measurement provided an understanding of the mechanism, suggesting hydrogen bonding and dipole–dipole interactions as the main interactions between SO2 molecules and SBA-15_6.1APTES. DFT calculations were performed to confirm these interactions. Furthermore, this study highlights the application of SBA-15 materials with different amino modifications for SO2 treatment and provides insight into the interaction mechanism using experimental techniques. [ABSTRACT FROM AUTHOR]

Ozone (O3) is one of the most harmful and widespread air pollutants, affecting crop yield and plant health worldwide. There is evidence that O3 reduces the major limiting factor of photosynthesis, namely CO2 mesophyll conductance (gm), but there is little quantitative information of O3‐caused changes in key leaf anatomical traits and their impact on gm. We exposed two O3‐responsive clones of the economically important tree species Populus × canadensis Moench to 120 ppb O3 for 21 days. An anatomical diffusion model within the leaf was used to analyse the entire CO2 diffusion pathway from substomatal cavities to carboxylation sites and determine the importance of each structural and subcellular component as a limiting factor. gm decreased substantially under O3 and was found to be the most important limitation of photosynthesis. This decrease was mostly driven by an increased cell wall thickness and length of subcellular diffusion pathway caused by altered interchloroplast spacing and chloroplast positioning. By contrast, the prominent leaf integrative trait leaf dry mass per area was neither affected nor related to gm under O3. The observed relationship between gm and anatomy, however, was clone‐dependent, suggesting that mechanisms regulating gm may differ considerably between closely related plant lines. Our results confirm the need for further studies on factors constraining gm under stress conditions. [ABSTRACT FROM AUTHOR]

Context : Phographene and its family member structures are of the newly proposed semiconductors for detection of chemicals. That is, in this project, the potential of using α-phographene (α-POG) both for adsorption and detection of five types of the most important air pollutant gases containing SO2, AsH3, CF3H, NO2, and CO2 species were investigated. The results of the time dependent density functional theory (TD-DFT) calculations indicate that during the adsorption of NO2, and SO2 by the sorbent, big redshifts occur (up to 866.2 nm, and 936.5, respectively) resulting in considerable changes in the orbitals and the electronic structures of the systems. Moreover, the results of the thermodynamic calculations reveal that α-POG could selectively adsorb SO2, NO2, and AsH3 gases (with different orders), but it could not adsorb the two other gases.Finally, the outcome of the band gap calculations shows that between all mentioned gases, α-POG could selectively detect the presence of SO2, and then NO2; while, this nanosheet could not sense the existence of AsH3, CF3H, or CO2 gases. Methods: All of the calculations were carried out by using the Gaussian 03 quantum chemical package. In addition, the physiochemical parameters were extracted from the output files for further calculations. Studies on all saddle points and the following calculations were performed applying the B3LYP/6-311g(d,p) level of theory. [ABSTRACT FROM AUTHOR]

Presently, a significant portion of the global population resides in metropolitan areas where air pollution levels are usually high. The primary objective is to utilize satellite data to identify the concentration of pollutants, unlike the traditional method which utilizes a series of ground-based detectors. The study aims to analyze the distribution of different pollutants in the air over the Gujarat state, India. The study comprised the utilization of Sentinel 5-P data sets for mapping Carbon monoxide (CO), Nitrogen dioxide (NO2), Sulfur dioxide (SO2), Methane (CH4), and Formaldehyde (HCHO). Google Earth Engine platform was used for the processing of satellite imagery and maps were prepared using ArcGIS 10.3. The satellite data sets of different pollutants were processed and assessed for three seasons i.e., winter, summer, and monsoon to analyze the effect of climatic conditions as well on the concentration level over the study area. The concentration of CO ranges between 0.0295–0.0401 mol/m2. The average concentration of SO2 is 0.00047 mol/m2 whereas the average concentration of NO2 ranges from 0–0.00021 mol/m2 and formaldehyde concentrations values range from 0.00015 to 0.00026 mol/m2 over the year. The concentration range for methane is 1780–1940 ppb for the study area. The results exhibit that the northern part of Gujarat mainly consisting of Kutch, Banas Kantha, and Patan renders the lowest concentration of all air pollutants while the central and southern regions consisting of cities like Valsad, Surat, Bharuch, Vadodara, and Ahmedabad have recorded the peak values in all the seasons. The findings suggest that the increase in the levels of different pollutants is caused by human activities, industrialization, and urbanization. [ABSTRACT FROM AUTHOR]

Background: Different strategies have been described in order to reduce spine deep surgical site infection (SSI); however, non-intervenable items such as environmental factors remain as one of the main concerns for spine surgeons. Methods: A retrospective cohort study was designed in order to evaluate the effect of environmental factors such as temperature, humidity and particularly the air pollution index (PM 2.5) on spine surgical site infection. The files of 3609 patients who underwent spinal surgery from April 2019 to March 2022 were reviewed, and 121 patients with spine SSI were detected. Results: There was no significant relationship between mean temperature and humidity of each month with infection and type of bacteria. However, there was a significant relation between warmer season periods and infection. The rate of infection among patients was 3.25% ranged from 2.5% to 4% in colder and warmer seasons accordingly. It was determined that air pollution had a significant relationship with the infection and the type of bacteria. (p value < 0.05, R-Squared = 0.249). Conclusions: Our study revealed a 60% increase in spine SSI during warmer seasons. There was a significant correlation between air pollution and the rate of infection. These may suggest the necessity to reduce the number of elective spine surgeries during warmer seasons and when the level of air pollutant is high. [ABSTRACT FROM AUTHOR]

With the ongoing challenge of air pollution posing serious health and environmental threats, particularly in rapidly industrializing regions, accurate forecasting and effective pollutant identification are crucial for enhancing public health and ecological stability. This study aimed to optimize air quality management through the prediction of the Air Quality Index (AQI) and identification of air pollutants. Our study spans nine representative cities (Hohhot, Yinchuan, Lanzhou, Beijing, Taiyuan, Xi'an, Shanghai, Nanjing, Wuhan) in China, with data collected from January 1, 2015, to November 30, 2021. We proposed a new model for daily AQI prediction, termed VMD-CSA-CNN-LSTM, which employed advanced machine learning techniques, including convolutional neural networks (CNN) and long short-term memory (LSTM) networks, and leveraged the chameleon swarm algorithm (CSA) for hyperparameter optimization, integrated through a variational mode decomposition approach. The model was developed using data from Lanzhou, with a split ratio of 8:1:1 into training, validation, and test sets, achieving an RMSE of 2.25, MAPE of 0.02, adjusted R-squared of 98.91%, and training efficiency of 5.31%. The model was further externally validated in the other eight cities, yielding comparable results, with an adjusted R-squared above 96%, MAPE below 0.1, and RMSE below 7.5. Additionally, we employed a random forest algorithm to identify the primary pollutants contributing to AQI levels. Our results indicated that PM2.5 was the most significant pollutant in Beijing, Taiyuan, and Xi'an, while PM10 was dominant in Hohhot, Yinchuan, and Lanzhou. In Shanghai, Nanjing, and Wuhan, both PM2.5 and PM10 were critical, with ozone also identified as a major air pollutant. This study not only advances the predictive accuracy of AQI models but also aids policymakers by providing a reliable tool for air quality management and strategic planning aimed at pollution reduction. The integration of these advanced computational techniques into environmental monitoring practices offers a promising avenue for enhancing air quality and mitigating pollution-related risks. [ABSTRACT FROM AUTHOR]

The negative environmental, health, and social effects arising from U.S. military action in communities both domestically and abroad suggest that the military represents an understudied institutional source of environmental injustice. Moreover, scholars and activists have long argued that the state is an active or a tacit contributor to environmental inequality, thus providing an opportunity to link U.S. military activity with approaches to the state developed under critical environmental justice. We build on these literatures to ask: Does the presence of domestic military facilities significantly increase carcinogenic risks from air toxics? And do communities of color face additional military-associated carcinogenic risks? Multilevel analyses reveal that locales in closer proximity to a military facility and those exposed to greater military technological intensity, independent of each other, experience significantly higher carcinogenic risk from air toxics. We find that proximity to military facilities tends to intensify racial and ethnic environmental inequalities in exposure to airborne toxics, but in different ways for Latinx and Black populations. These results highlight the role of the state in perpetuating racial and environmental expendability as reflected in critical environmental justice and represent an important expansion of nationwide environmental justice studies on contributors to environmental inequality. [ABSTRACT FROM AUTHOR]

Hypoxia is characterised by tissue oxygen concentrations below 2% and occurs in several pathologies including neurodegenerative and chronic lung diseases. Air pollution and its major component, particulate matter, are also a public health concern and are directly implicated in the onset of chronic lung disease. Therefore, an understanding of the effects of hypoxia on the susceptibility of lung tissues to air pollutants is crucial. In this study we investigate the effects of hypoxia on the toxicity of diesel exhaust particles (DEP) in two lung epithelial cells: human and rat type II alveolar cells. The goal is to discern whether hypoxia exacerbates the toxic response to DEP exposure in both 24-hour and 48-hour exposures. We subjected both cell lines to increasing concentrations of DEP for 24 and 48 hours in both normoxic and hypoxic (2% oxygen) incubation conditions and measured the rate of cell death, proliferation, and pro-inflammatory cytokine and chemokine production. The results indicate that hypoxia increases DEP cytotoxicity in RLE6TN but not A549 cells, and that hypoxia decreases the production of pro-inflammatory markers induced by exposure to DEP. These results suggest an increased susceptibility to particulate matter toxicity when prolonged or chronic hypoxia is present. [ABSTRACT FROM AUTHOR]

The release of toxic gases into the atmosphere may reach concentrations that can cause undesirable health, economic, or aesthetic effects. It is therefore important to monitor the amounts of pollutants injected into the atmosphere from various sources. Most countries have a ground network with multiple measuring sites and instruments, that can measure the air quality index (AQI). However, the main challenge with the networks is the low spatial coverage. In this work, satellite data is used to calculate for the first time the spatial distribution of AQI and pollutant concentration over South Africa. The TROPOspheric Monitoring Instrument (TROPOMI) onboard Sentinel-5P data is used to calculate AQI from carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2) gases. The results that the month of June has the worst air quality distribution throughout the country, while March has the best air quality distribution. Overall, the results clearly show that TROPOMI has the capability to measure air quality at a country and city level. Implications: In this work, satellite data is used to calculate for the first time the spatial distribution of the air quality index (AQI) and pollutant concentration over South Africa. The TROPOspheric Monitoring Instrument (TROPOMI) onboard Sentinel-5P data is used to calculate AQI from carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2) gases. Currently, South Africa has a ground network of instruments that measure AQ, however, the network does not cover the whole country. In this work, we show that the use of TROPOMI can compliment the current network and provide data for the areas not covered. [ABSTRACT FROM AUTHOR]

Communities near transportation sources can be impacted by higher concentrations of particulate matter (PM) and other air pollutants. Few studies have reported on air quality in complex urban environments with multiple transportation sources. To better understand these environments, the Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS) was conducted in three neighborhoods in Southeast Kansas City, Kansas. This area has several emissions sources including transportation (railyards, vehicles, diesel trucks), light industry, commercial facilities, and residential areas. Stationary samples were collected for 1-year (October 24, 2017, to October 31, 2018) at six sites using traditional sampling methods and lower-cost air sensor packages. This work examines PM less than 2.5 μm in diameter (PM2.5), black carbon (BC), and trace metals data collected during KC-TRAQS. PM2.5 filter samples showed the highest 24-h mean concentrations (9.34 μg/m3) at the sites located within 20–50 m of the railyard. Mean 24-h PM2.5 concentrations, ranging from 7.96 to 9.34 μg/m3, at all sites were lower than that of the nearby regulatory site (9.83 μg/m3). Daily maximum PM2.5 concentrations were higher at the KC-TRAQS sites (ranging from 25.31 to 43.76 μg/m3) compared to the regulatory site (20.50 μg/m3), suggesting short-duration impacts of localized emissions sources. Across the KC-TRAQS sites, 24-h averaged PM2.5 concentrations from the sensor package (P-POD) ranged from 3.24 to 5.69 µg/m3 showing that, out-of-the-box, the PM sensor underestimated the reference concentrations. KC-TRAQS was supplemented by elemental and organic carbon (EC/OC) and trace metal analysis of filter samples. The EC/OC data suggested the presence of secondary organic aerosol formation, with the highest mean concentrations observed at the site within 20 m of the railyard. Trace metals data showed daily, monthly, and seasonal variations for iron, copper, zinc, chromium, and nickel, with elevated concentrations occurring during the summer at most of the sites. Implications: This work reports on findings from a year-long air quality study in Southeast Kansas City, Kansas to understand micro-scale air quality in neighborhoods impacted by multiple emissions sources such as transportation sources (including a large railyard operation), light industry, commercial facilities, and residential areas. While dozens of studies have reported on air quality near roadways, this work will provide more information on PM2.5, black carbon, and trace metals concentrations near other transportation sources in particular railyards. This work can also inform additional field studies near railyards. [ABSTRACT FROM AUTHOR]

Background: Metabolic Syndrome (MetS) is a widely observed metabolic disorder that is increasingly prevalent worldwide, leading to substantial societal consequences. Previous studies have conducted two separate meta-analyses to investigate the relationship between MetS and air pollutants. However, these studies yielded conflicting results, necessitating a thorough systematic review and meta-analysis to reassess the link between different air pollutants and the risk of developing MetS. Methods: We conducted a comprehensive search of relevant literature in databases including PubMed, Embase, Cochrane Library, and Web of Science up to October 9, 2023. The search was specifically restricted to publications in the English language. Following the screening of studies investigating the correlation between air pollution and MetS, we utilized random-effects models to calculate pooled effect sizes along with their respective 95% confidence intervals (CIs). We would like to highlight that this study has been registered with PROSPERO, and it can be identified by the registration number CRD42023484421. Results: The study included twenty-four eligible studies. The results revealed that an increase of 10 μg/m3 in annual concentrations of PM1, PM2.5, PM10, NO2, SO2, and O3 was associated with a 29% increase in metabolic syndrome (MetS) risk for PM1 (OR = 1.29 [CI 1.07–1.54]), an 8% increase for PM2.5 (OR = 1.08 [CI 1.06–1.10]), a 17% increase for PM10 (OR = 1.17 [CI 1.08–1.27]), a 24% increase for NO2 (OR = 1.24 [CI 1.01–1.51]), a 19% increase for SO2 (OR = 1.19 [CI 1.04–1.36]), and a 10% increase for O3 (OR = 1.10 [CI 1.07–1.13]). Conclusion: The findings of this study demonstrate a significant association between exposure to fine particulate matter (PM1, PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and the incidence of metabolic syndrome (MetS). Moreover, the results suggest that air pollution exposure could potentially contribute to the development of MetS in humans. [ABSTRACT FROM AUTHOR]