Particulate Matter Air Pollution Research Articles

Impact of particulate-matter air pollution on 25-hydroxyvitamin D levels: a mendelian randomisation study

ObjectivesIn observational studies, the 25-hydroxyvitamin D (25(OH)D) level in body has been found to be closely related to particulate matter (PM) air pollution. In this study, we used the two-sample mendelian randomisation (MR) method to investigate and discuss the potential causal relationship and mode of influence. Study designMR study. MethodsPM data (PM10, PM2.5-10, PM2.5, PM2.5 absorbance) came from the UK Biobank database, and 25(OH)D data came from European Bioinformatics Institute (EBI) database. The analysis was conducted utilising three prominent methods (inverse-variance-weighted [IVW], MR–Egger, weighted median, weighted mode, and simple mode). The primary emphasis was placed on IVW, accompanied by heterogeneity and horizontal pleiotropy tests. Furthermore, sensitivity analysis was undertaken. ResultsThe MR analysis revealed a significant association between exposure to PM10 and a decrease in levels of 25(OH)D (odds ratio [OR]: 0.878, 95% confidence interval [CI]: 0.789–0.977). However, no significant relationship was observed between PM2.5 exposure and 25(OH)D (OR: 0.943, 95%CI: 0.858–1.037). Further analysis indicated that the main contributor to the decline in 25(OH)D levels is linked to PM2.5-10 exposure (OR: 0.840, 95%CI: 0.751–0.940) and PM2.5 absorbance (OR: 0.875, 95%CI: 0.824–0.929). No heterogeneity and horizontal pleiotropy existed. ConclusionsThe MR results suggest that PM (PM10, PM2.5-10 and PM2.5 absorbance) exposure lowers vitamin D (VD) levels, but PM2.5 was not found to have a significant effect on VD in humans.

A review of air pollution as a driver of cardiovascular disease risk across the diabetes spectrum.

The prevalence of diabetes is estimated to reach almost 630 million cases worldwide by the year 2045; of current and projected cases, over 90% are type 2 diabetes. Air pollution exposure has been implicated in the onset and progression of diabetes. Increased exposure to fine particulate matter air pollution (PM2.5) is associated with increases in blood glucose and glycated hemoglobin (HbA1c) across the glycemic spectrum, including normoglycemia, prediabetes, and all forms of diabetes. Air pollution exposure is a driver of cardiovascular disease onset and exacerbation and can increase cardiovascular risk among those with diabetes. In this review, we summarize the literature describing the relationships between air pollution exposure, diabetes and cardiovascular disease, highlighting how airborne pollutants can disrupt glucose homeostasis. We discuss how air pollution and diabetes, via shared mechanisms leading to endothelial dysfunction, drive increased cardiovascular disease risk. We identify portable air cleaners as potentially useful tools to prevent adverse cardiovascular outcomes due to air pollution exposure across the diabetes spectrum, while emphasizing the need for further study in this particular population. Given the enormity of the health and financial impacts of air pollution exposure on patients with diabetes, a greater understanding of the interventions to reduce cardiovascular risk in this population is needed.

Public Health Relevance of US EPA Air Quality Index Activity Recommendations

Reducing exposure to fine particulate matter (<2.5 μm [PM2.5]) air pollution improves cardiopulmonary morbidity and mortality. However, the public health relevance of air quality index (AQI) activity guidelines under present-day environmental conditions in the US has not been critically assessed. To evaluate the public health relevance of following PM2.5 AQI activity guidance in preventing serious atherosclerotic cardiovascular disease (ASCVD) and pulmonary events among adults in the US. This cross-sectional modeling study involved the general adult population and sensitive individuals as designated by the US Environmental Protection Agency (EPA), including adults with preexisting ASCVD or lung disease (asthma or chronic obstructive pulmonary disease). The study was conducted between August 1, 2023, and January 31, 2024. Daily AQI strata for PM2.5 and the corresponding activity recommendations. The main outcome was the number needed to treat (NNT) per day by following activity guidance across daily AQI strata to prevent 1 serious ASCVD or pulmonary event among relevant populations. To calculate PM2.5-induced excess disease event rates per day, estimated baseline disease-specific daily event rates for each group were multiplied by the increase in risks due to PM2.5 levels at each AQI stratum. The number of events prevented per day was calculated by multiplying each excess disease event rate by the percentage in exposure reduction plausibly incurred by following population-specific activity guidance at each AQI level. The NNT is the reciprocal of the number of events prevented. The NNT to prevent ASCVD events was high for the general population and for patients with ASCVD across all AQI strata. The range of values was comparatively lower to prevent pulmonary events among adults with lung disease. During most days (96%) when activity recommendations were promulgated due to elevated PM2.5 (AQI, 101-200), the NNT to prevent a serious disease event remained very high for the general population (>18 million), patients with ASCVD (approximately 1.6-5 million), and adults with lung disease (approximately 66 000-202 000). These findings suggest that existing PM2.5 AQI activity recommendations are of questionable public health relevance in present-day conditions and merit consideration for updating to improve their potential effectiveness.

Addressing air quality challenges: Comparative analysis of Barcelona, Venezuela, and Guayaquil, Ecuador

This study presents a willingness-to-pay (WtP) questionnaire that was designed, validated, and applied to assess perceptions of air quality and self-reported health in two middle-income South American cities: Barcelona and its neighboring cities (Venezuela) and Guayaquil (Ecuador). These cities lack air quality monitoring and control measures. The questionnaire is a reliable tool to assess air quality based on citizens' perceptions, and the results reveal that both populations perceive low air quality and accurately identify emission sources and air pollutants (industrial emissions and particulate matter in Barcelona and vehicular emissions and carbon monoxide in Guayaquil).The study also evaluated the efforts made by both cities to improve air quality using the United Nations Environment Programme to strengthen air quality in South America. Based on this evaluation, strengths were identified for enhancing air quality in both cities. The study finds that in Barcelona and its surroundings, investment is needed to improve urban transport, waste management, and update the environmental legislation regarding air quality at the national level. In contrast, Guayaquil has already taken some measures to improve air quality, but more investment in public transport and measures to lower vehicle emissions are needed.

Hemolytic Properties of Fine Particulate Matter (PM2.5) in In Vitro Systems.

Epidemiological studies have suggested that inhalation exposure to particulate matter (PM) air pollution, especially fine particles (i.e., PM2.5 (PM with an aerodynamic diameter of 2.5 microns or less)), is causally associated with cardiovascular health risks. To explore the toxicological mechanisms behind the observed adverse health effects, the hemolytic activity of PM2.5 samples collected during different pollution levels in Beijing was evaluated. The results demonstrated that the hemolysis of PM2.5 ranged from 1.98% to 7.75% and demonstrated a clear dose-response relationship. The exposure toxicity index (TI) is proposed to represent the toxicity potential of PM2.5, which is calculated by the hemolysis percentage of erythrocytes (red blood cells, RBC) multiplied by the mass concentration of PM2.5. In a pollution episode, as the mass concentration increases, TI first increases and then decreases, that is, TI (low pollution levels) < TI (heavy pollution levels) < TI (medium pollution levels). In order to verify the feasibility of the hemolysis method for PM toxicity detection, the hemolytic properties of PM2.5 were compared with the plasmid scission assay (PSA). The hemolysis results had a significant positive correlation with the DNA damage percentages, indicating that the hemolysis assay is feasible for the detection of PM2.5 toxicity, thus providing more corroborating information regarding the risk to human cardiovascular health.

Abstract 833: No association between air pollution and lung cancer incidence in a 2 million South Korean cohort

Abstract Background: Accumulating evidence has consistently suggested long-term exposure to air pollution as a risk factor of lung cancer incidence. Our previous study of long-term exposure to particulate matter air pollution and lung cancer incidence in a South Korean cohort showed no association with hazard ratios greater than one. This inconsistent finding with those from previous cohort studies could be due to limited exposure assessment relying on district averages and a relatively small sample size of 80 thousand people. The present study aimed to overcome the two major limitations and re-analyzed the association for long-term exposure to particulate matter ≤ 10 µm and 2.5 µm in diameter (PM10 and PM2.5), nitrogen dioxide (NO2), and ozone. Specifically, we improved our exposure assessment for individual exposure using 100-meter grid addresses, and increased the population size to 2 million people based on the National Health Insurance Database (NHID) composed of the entire South Korean population. Methods: Our study population included 1,976,265 people who aged 30 years or older, had no history of cancer for 2002-2006, underwent health screening for 2005-2007, and resided in the Seoul Metropolitan Area. We defined lung cancer incidence as the first diagnosis based on the International Classification of Diseases 10th revision code and identified the incidence for 10 years of follow-up from 2007 through 2016. We estimated individual long-term exposure to PM10, PM2.5, NO2, and ozone as five-year average concentrations on each year at 100-meter grid addresses of participants’ homes by using previously-validated exposure prediction models. Finally, we applied time-varying Cox proportional hazard model to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for a 10 µg/m3 or 10 ppb increase of each of the four pollutants after adjusting for individual- and area-level characteristics. Results: Out of 1,976,265 people, 15,707 people (0.79%) developed new cases of lung cancer for 10 years of follow-up. In all analyses for long-term exposure to four pollutants and lung cancer incidence, we did not find an association (PM10: HR= 0.999 [95% CI=0.956 - 1.044]; PM2.5: 0.890 [0.787 - 1.006]; NO2: 1.002 [0.967 - 1.037]; ozone: 1.027 [0.978 - 1.077]). Our stratified analyses by individual and area-level characteristics as well as 79 districts showed that the null findings in the total population were not derived by specific subpopulations. Conclusion: Despites the considerable improvement in exposure assessment and population size, our findings are contradictory to previous evidence. In addition to the possibility of no association, our null findings could be due to a relatively short period of exposure, the lack of histological information, and exposure measurement error resulting from indoor-outdoor difference and time activity. Future studies should overcome these limitations and re-examine the association. Citation Format: Sun-Young Kim, Jeongho Park, Ok-Jin Kim, Miyoun Shin, Sungchan Kang, Seung-sik Hwang, Youngwook Kim, Young-Jae Cho. No association between air pollution and lung cancer incidence in a 2 million South Korean cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 833.

Air-pollutant particulate matter 2.5 (PM2.5)-induced inflammation and oxidative stress in diseases: Possible therapeutic approaches

Today, air pollution is one of the greatest threats to organismal healthspan. The environmental air of earth is contaminated with a wide variety of artificially generated pollutants like fine particulate matter (PM2.5) emitting from industry, fuel engine vehicles, biomass combustion, fumes from blasting, crop residue burning, and wildfire. The air pollutant PM2.5 induces massive oxidative stress and inflammation, the major contributors in initiation and progression of numerous diseases including pulmonary, cardiovascular, renal, hepatic, reproductive, neurological, mental, and accelerated biological aging. The provocative question is the following: how can we solve this air pollution associated problem? As it is not realistic to clean the environment at once from artificially generated toxic pollution, initiatives have been undertaken to develop novel therapeutic approaches to control air-pollutant-induced oxidative stress and inflammation and associated devastating diseases. The primary goal of this review article is to discuss systematically the key findings of numerous recent preclinical studies documenting first, the role of air pollutant PM2.5 in augmentation of inflammation, oxidative stress, and associated diseases; and second, the efficacies of different natural and synthetic compounds in amelioration of PM2.5-induced oxidative stress, inflammation, pyroptosis, and associated pathologies. Further investigation on the safety of these compounds will be helpful to select effective and non-toxic compound(s) for clinical trial and drug development.

Early-Life Exposure to Air Pollution and Childhood Asthma Cumulative Incidence in the ECHO CREW Consortium

Exposure to outdoor air pollution contributes to childhood asthma development, but many studies lack the geographic, racial and ethnic, and socioeconomic diversity to evaluate susceptibility by individual-level and community-level contextual factors. To examine early life exposure to fine particulate matter (PM2.5) and nitrogen oxide (NO2) air pollution and asthma risk by early and middle childhood, and whether individual and community-level characteristics modify associations between air pollution exposure and asthma. This cohort study included children enrolled in cohorts participating in the Children's Respiratory and Environmental Workgroup consortium. The birth cohorts were located throughout the US, recruited between 1987 and 2007, and followed up through age 11 years. The survival analysis was adjusted for mother's education, parental asthma, smoking during pregnancy, child's race and ethnicity, sex, neighborhood characteristics, and cohort. Statistical analysis was performed from February 2022 to December 2023. Early-life exposures to PM2.5 and NO2 according to participants' birth address. Caregiver report of physician-diagnosed asthma through early (age 4 years) and middle (age 11 years) childhood. Among 5279 children included, 1659 (31.4%) were Black, 835 (15.8%) were Hispanic, 2555 (48.4%) where White, and 229 (4.3%) were other race or ethnicity; 2721 (51.5%) were male and 2596 (49.2%) were female; 1305 children (24.7%) had asthma by 11 years of age and 954 (18.1%) had asthma by 4 years of age. Mean values of pollutants over the first 3 years of life were associated with asthma incidence. A 1 IQR increase in NO2 (6.1 μg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.25 [95% CI, 1.03-1.52]) and children younger than 11 years (HR, 1.22 [95% CI, 1.04-1.44]). A 1 IQR increase in PM2.5 (3.4 μg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.31 [95% CI, 1.04-1.66]) and children younger than 11 years (OR, 1.23 [95% CI, 1.01-1.50]). Associations of PM2.5 or NO2 with asthma were increased when mothers had less than a high school diploma, among Black children, in communities with fewer child opportunities, and in census tracts with higher percentage Black population and population density; for example, there was a significantly higher association between PM2.5 and asthma incidence by younger than 5 years of age in Black children (HR, 1.60 [95% CI, 1.15-2.22]) compared with White children (HR, 1.17 [95% CI, 0.90-1.52]). In this cohort study, early life air pollution was associated with increased asthma incidence by early and middle childhood, with higher risk among minoritized families living in urban communities characterized by fewer opportunities and resources and multiple environmental coexposures. Reducing asthma risk in the US requires air pollution regulation and reduction combined with greater environmental, educational, and health equity at the community level.

Real-time in situ monitoring of dust particle growth in a low-pressure nanodusty plasma based on laser-induced photodetachment

Particulate matter air pollution in the form of ultrafine dust is a growing global concern. In this Letter, we will use a nanodusty Ar/HMDSO plasma as a model system for a heavily contaminated gas and we present the development of a technique for real-time in situ measurements of the dust particle size. The method is based on laser-induced photodetachment of bound electrons from the surface of dust particles. These photo-released electrons are measured as an increase in the free electron density of the plasma using microwave cavity resonance spectroscopy. We show that instead of reconstructing the entire resonance profile, the temporal response of a single microwave frequency was enough to perform the measurements. More specifically, the decay timescale of the cavity response can be interpreted as the re-charging timescale of the dust particles. Then, using a stochastic model, this timescale can be modeled, which eventually retrieves the dust particle size. We found good agreement between the predicted dust particle size and the average dust particle size obtained from ex situ scanning electron microscopy measurements. This method allows for the real-time monitoring of the dust particle size and a controlled production of nanometer-scale dust particles, which gives opportunities both for fundamental dusty plasma physics and models, as well as for applications in monitoring ultrafine dust air pollution.

Causal relationship between particulate matter and COVID-19 risk: A mendelian randomization study

BackgroundObservational studies have linked exposure to fine (PM2.5) and coarse (PM10) particulate matter air pollution with adverse COVID-19 outcomes, including higher incidence and mortality. However, some studies questioned the effect of air pollution on COVID-19 susceptibility, raising questions about the causal nature of these associations. To address this, a less biased method like Mendelian randomization (MR) is utilized, which employs genetic variants as instrumental variables to infer causal relationships in observational data. MethodWe performed two-sample MR analysis using public genome-wide association studies data. Instrumental variables correlated with PM2.5 concentration, PM2.5 absorbance, PM2.5-10 concentration and PM10 concentration were identified. The inverse variance weighted (IVW), robust adjusted profile score (RAPS) and generalized summary data-based Mendelian randomization (GSMR) methods were used for analysis. ResultsIVW MR analysis showed PM2.5 concentration [odd ratio (OR) = 3.29, 95% confidence interval (CI) 1.48–7.35, P-value = 0.0036], PM2.5 absorbance (OR = 5.62, 95%CI 1.98–15.94, P-value = 0.0012), and PM10 concentration (OR = 3.74, 95%CI 1.52–9.20, P-value = 0.0041) increased the risk of COVID-19 severity after Bonferroni correction. Further validation confirmed PM2.5 absorbance was associated with heightened COVID-19 severity (OR = 6.05, 95%CI 1.99–18.38, P-value = 0.0015 for RAPS method; OR = 4.91, 95%CI 1.65–14.59, P-value = 0.0042 for GSMR method) and hospitalization (OR = 3.15, 95%CI 1.54–6.47, P-value = 0.0018 for RAPS method). No causal links were observed between particulate matter exposure and COVID-19 susceptibility. ConclusionsOur study established a causal relationship between smaller particle pollution, specifically PM2.5, and increased risk of COVID-19 severity and hospitalization. These findings highlight the importance of improving air quality to mitigate respiratory disease progression.

TEMPORAL ANALYSIS AND PREDICTIVE MODELING OF AMBIENT AIR QUALITY IN HULU LANGAT DISTRICT, SELANGOR, MALAYSIA: A CHEMOMETRIC APPROACH

One of the most important environmental problems facing the globe today is air pollution. The centre area for the local populace is the Hulu Langat district, which borders Kuala Lumpur, the capital. The purpose of this study is to look at how the ambient air quality varies in Hulu Langat, Selangor. The Air Quality Division of the Malaysian Department of Environment provided five years' worth of secondary data on the air quality at Hulu Langat. The database included five primary air pollutant characteristics sulphur dioxide (SO2), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and particulate matter with a diameter of 10 microns or less (PM10), in addition to data from the Air Pollutant Index (API). Chemometric analysis was used to examine the results. According to the results, SO2, NO2 and PM10 had the greatest correlations with API readings. A statistical process known as statistical control (SPC) showed that certain PM10 values were over national recommendations and control limits. The artificial neural network method's air quality prediction model demonstrated good accuracy with real data (R2 = 0.9). The results of this investigation indicated a strong correlation between the Hulu Langat air quality data. In order to achieve sustainable environmental practices in the future, it is imperative to engage in extensive collaboration across environmental departments and relevant authorities and engage in continuous monitoring of air quality.

Leading determinants of incident dementia among individuals with and without the apolipoprotein E ε4 genotype: a retrospective cohort study

BackgroundLittle is known regarding the leading risk factors for dementia/Alzheimer’s disease (AD) in individuals with and without APOE4. The identification of key risk factors for dementia/Alzheimer’s disease (AD) in individuals with and without the APOE4 gene is of significant importance in global health.MethodsOur analysis included 110,354 APOE4 carriers and 220,708 age- and sex-matched controls aged 40–73 years at baseline (between 2006–2010) from UK Biobank. Incident dementia was ascertained using hospital inpatient, or death records until January 2021. Individuals of non-European ancestry were excluded. Furthermore, individuals without medical record linkage were excluded from the analysis. Moderation analysis was tested for 134 individual factors.ResultsDuring a median follow-up of 11.9 years, 4,764 cases of incident all-cause dementia and 2065 incident AD cases were documented. Hazard ratios (95% CIs) for all-cause dementia and AD associated with APOE4 were 2.70(2.55–2.85) and 3.72(3.40–4.07), respectively. In APOE4 carriers, the leading risk factors for all-cause dementia included low self-rated overall health, low household income, high multimorbidity risk score, long-term illness, high neutrophil percentage, and high nitrogen dioxide air pollution. In non-APOE4 carriers, the leading risk factors included high multimorbidity risk score, low overall self-rated health, low household income, long-term illness, high microalbumin in urine, high neutrophil count, and low greenspace percentage. Population attributable risk for these individual risk factors combined was 65.1%, and 85.8% in APOE4 and non-APOE4 carriers, respectively. For 20 risk factors including multimorbidity risk score, unhealthy lifestyle habits, and particulate matter air pollutants, their associations with incident dementia were stronger in non-APOE4 carriers. For only 2 risk factors (mother’s history of dementia, low C-reactive protein), their associations with incident all-cause dementia were stronger in APOE4 carriers.ConclusionsOur findings provide evidence for personalized preventative approaches to dementia/AD in APOE4 and non-APOE4 carriers. A mother’s history of dementia and low levels of C-reactive protein were more important risk factors of dementia in APOE4 carriers whereas leading risk factors including unhealthy lifestyle habits, multimorbidity risk score, inflammation and immune-related markers were more predictive of dementia in non-APOE4 carriers.

Ambient particulate matter and surrounding greenness in relation to sleep quality among pregnant women: A nationwide cohort study

BackgroundParticulate air pollution and residential greenness are associated with sleep quality in the general population; however, their influence on maternal sleep quality during pregnancy has not been assessed. ObjectiveThis cross-sectional study investigated the individual and interactive effects of exposure to particulate matter (PM) air pollution and residential greenness on sleep quality in pregnant women. MethodsPregnant women (n = 4933) enrolled in the Korean Children's Environmental Health Study with sleep quality information and residential address were included. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The average concentrations of PM (PM2.5 and PM10) during pregnancy were estimated through land use regression, and residential greenness in a 1000 m buffer area around participants' residences was estimated using the Normalized Difference Vegetation Index (NDVI1000-m). Modified Poisson regression models were used to estimate the associations between PM and NDVI and poor sleep quality (PSQI >5) after controlling for a range of covariates. A four-way mediation analysis was conducted to examine the mediating effects of PM. ResultsAfter adjusting for confounders, each 10 μg/m3 increase in PM2.5 and PM10 exposure was associated with a higher risk of poor sleep quality (relative risk [RR]: 1.06; 95% confidence interval [CI]: 1.01, 1.11; and RR: 1.09; 95% CI: 1.06, 1.13, respectively), and each 0.1-unit increase in NDVI1000-m was associated with a lower risk of poor sleep quality (RR: 0.97; 95% CI: 0.95, 0.99). Mediation analysis showed that PM mediated approximately 37%–56% of the association between residential greenness and poor sleep quality. ConclusionsThis study identified a positive association between residential greenness and sleep quality. Furthermore, these associations are mediated by a reduction in exposure to particulate air pollution and highlight the link between green areas, air pollution control, and human health.

Time-stratified case-crossover studies for aggregated data in environmental epidemiology: a tutorial.

The case-crossover design is widely used in environmental epidemiology as an effective alternative to the conventional time-series regression design to estimate short-term associations of environmental exposures with a range of acute events. This tutorial illustrates the implementation of the time-stratified case-crossover design to study aggregated health outcomes and environmental exposures, such as particulate matter air pollution, focusing on adjusting covariates and investigating effect modification using conditional Poisson regression. Time-varying confounders can be adjusted directly in the conditional regression model accounting for the adequate lagged exposure-response function. Time-invariant covariates at the subpopulation level require reshaping the typical time-series data set into a long format and conditioning out the covariate in the expanded stratum set. When environmental exposure data are available at geographical units, the stratum set should combine time and spatial dimensions. Moreover, it is possible to examine effect modification using interaction models. The time-stratified case-crossover design offers a flexible framework to properly account for a wide range of covariates in environmental epidemiology studies.

Microglial TLR4 Mediates White Matter Injury in a Combined Model of Diesel Exhaust Exposure and Cerebral Hypoperfusion.

Air pollution particulate matter exposure and chronic cerebral hypoperfusion (CCH) contribute to white matter toxicity through shared mechanisms of neuroinflammation, oxidative stress, and myelin breakdown. Prior studies showed that exposure of mice to joint particulate matter and CCH caused supra-additive injury to corpus callosum white matter. This study examines the role of TLR4 (toll-like receptor 4) signaling in mediating neurotoxicity and myelin damage observed in joint particulate matter and CCH exposures. Experiments utilized a novel murine model of inducible monocyte/microglia-specific TLR4 knockout (i-mTLR4-ko). Bilateral carotid artery stenosis (BCAS) was induced surgically to model CCH. TLR4-intact (control) and i-mTLR4-ko mice were exposed to 8 weeks of either aerosolized diesel exhaust particulate (DEP) or filtered air (FA) in 8 experimental groups: (1) control/FA (n=10), (2) control/DEP (n=10), (3) control/FA+BCAS (n=9), (4) control/DEP+BCAS (n=10), (5) i-mTLR4-ko/FA (n=9), (6) i-mTLR4-ko/DEP (n=8), (7) i-mTLR4-ko/FA+BCAS (n=8), and (8) i-mTLR4-ko/DEP+BCAS (n=10). Corpus callosum levels of 4-hydroxynonenal, 8-Oxo-2'-deoxyguanosine, Iba-1 (ionized calcium-binding adapter molecule 1), and dMBP (degraded myelin basic protein) were assayed via immunofluorescence to measure oxidative stress, neuroinflammation, and myelin breakdown, respectively. Compared with control/FA mice, control/DEP+BCAS mice exhibited increased dMBP (41%; P<0.01), Iba-1 (51%; P<0.0001), 4-hydroxynonenal (100%; P<0.0001), and 8-Oxo-2'-deoxyguanosine (65%; P<0.05). I-mTLR4 knockout attenuated responses to DEP/BCAS for all markers. i-mTLR4-ko markedly reduced neuroinflammation and oxidative stress and attenuated white matter degradation following DEP and CCH exposures. This suggests a potential role for targeting TLR4 signaling in individuals with vascular cognitive impairment, particularly those exposed to substantial ambient air pollution.

Global Burden of Lung Cancer Attributable to Household Fine Particulate Matter Pollution in 204 Countries and Territories, 1990 to 2019

IntroductionHousehold particulate matter (PM) air pollution is substantially associated with lung cancer. Nevertheless, the global burden of lung cancer attributable to household PM2.5 is still uncertain. MethodsIn this study, data from the Global Burden and Disease Study 2019 are used to thoroughly assess the burden of lung cancer associated with household PM2.5. ResultsThe number of deaths and disability-adjusted life-years (DALYs) attributable to household PM2.5 was found to be 0.08 million and 1.94 million, respectively in 2019. Nevertheless, the burden of lung cancer attributable to household PM2.5 decreased from 1990 to 2019. At the sociodemographic index (SDI) district level, the middle SDI region had the most number of lung cancer deaths and DALYs attributable to household PM2.5. Moreover, the burden of lung cancer was mainly distributed in low-SDI regions, such as Sub-Saharan Africa. Conversely, in high-SDI regions, the age-standardized mortality rate and age-standardized DALY rate of lung cancer attributable to household PM2.5 exhibit the most rapid declines. The burden of lung cancer attributable to household PM2.5 is heavier for men than for women. The sex difference is more obvious in the elderly. ConclusionsThe prevalence of lung cancer attributable to household PM2.5 has exhibited a declining trend from 1990 to 2019 owing to a concurrent decline in household PM2.5 exposure.

Penalized distributed lag interaction model: Air pollution, birth weight, and neighborhood vulnerability

AbstractMaternal exposure to air pollution during pregnancy has a substantial public health impact. Epidemiological evidence supports an association between maternal exposure to air pollution and low birth weight. A popular method to estimate this association while identifying windows of susceptibility is a distributed lag model (DLM), which regresses an outcome onto exposure history observed at multiple time points. However, the standard DLM framework does not allow for modification of the association between repeated measures of exposure and the outcome. We propose a distributed lag interaction model that allows modification of the exposure‐time‐response associations across individuals by including an interaction between a continuous modifying variable and the exposure history. Our model framework is an extension of a standard DLM that uses a cross‐basis, or bi‐dimensional function space, to simultaneously describe both the modification of the exposure‐response relationship and the temporal structure of the exposure data. Through simulations, we showed that our model with penalization out‐performs a standard DLM when the true exposure‐time‐response associations vary by a continuous variable. Using a Colorado, USA birth cohort, we estimated the association between birth weight and ambient fine particulate matter air pollution modified by an area‐level metric of health and social adversities from Colorado EnviroScreen.

Particulate Matter Emission and Air Pollution Reduction by Applying Variable Systems in Tribologically Optimized Diesel Engines for Vehicles in Road Traffic

Regardless of the increasingly intensive application of vehicles with electric drives, internal combustion engines are still dominant as power units of mobile systems in various sectors of the economy. In order to reduce the emission of exhaust gases and satisfy legal regulations, as a temporary solution, hybrid drives with optimized internal combustion engines and their associated systems are increasingly being used. Application of the variable compression ratio and diesel fuel injection timing, as well as the tribological optimization of parts, contribute to the reduction in fuel consumption, partly due to the reduction in mechanical losses, which, according to test results, also results in the reduction in emissions. This manuscript presents the results of diesel engine testing on a test bench in laboratory conditions at different operating modes (compression ratio, fuel injection timing, engine speed, and load), which were processed using a zero-dimensional model of the combustion process. The test results should contribute to the optimization of the combustion process from the aspect of minimal particulate matter emission. As a special contribution, the results of tribological tests of materials for strengthening the sliding surface of the aluminum alloy piston and cylinder of the internal combustion engine and air compressors, which were obtained using a tribometer, are presented. In this way, tribological optimization should also contribute to the reduction in particulate matter emissions due to the reduction in fuel consumption, and thus emissions due to the reduction in friction, as well as the recorded reduction in the wear of materials that are in sliding contact. In this way, it contributes to the reduction in harmful gases in the air.

Reductions in premature deaths from heat and particulate matter air pollution in South Asia, China, and the United States under decarbonization

Following a sustainable development pathway designed to keep warming below 2 °C will benefit human health. We quantify premature deaths attributable to fine particulate matter (PM2.5) air pollution and heat exposures for China, South Asia, and the United States using projections from multiple climate models under high- and low-emission scenarios. Projected changes in premature deaths are typically dominated by population aging, primarily reflecting increased longevity leading to greater sensitivity to environmental risks. Changes in PM2.5 exposure typically have small impacts on premature deaths under a high-emission scenario but provide substantial benefits under a low-emission scenario. PM2.5-attributable deaths increase in South Asia throughout the century under both scenarios but shift to decreases by late century in China, and US values decrease throughout the century. In contrast, heat exposure increases under both scenarios and combines with population aging to drive projected increases in deaths in all countries. Despite population aging, combined PM2.5- and heat-related deaths decrease under the low-emission scenario by ~2.4 million per year by midcentury and ~2.9 million by century's end, with ~3% and ~21% of these reductions from heat, respectively. Intermodel variations in exposure projections generally lead to uncertainties of <40% except for US and China heat impacts. Health benefits of low emissions are larger from reduced heat exposure than improved air quality by the late 2090s in the United States. In contrast, in South and East Asia, the PM2.5-related benefits are largest throughout the century, and their valuation exceeds the cost of decarbonization, especially in China, over the next 30 y.

Analyzing COVID-19 and Air Pollution Effects on Pediatric Asthma Emergency Room Visits in Taiwan.

(1) Background: An asthma exacerbation that is not relieved with medication typically requires an emergency room visit (ERV). The coronavirus disease 2019 (COVID-19) pandemic began in Taiwan in January of 2020. The influence of the COVID-19 pandemic on pediatric ERVs in Taiwan was limited. Our aim was to survey pediatric asthma ERVs in the COVID-19 era; (2) Methods: Data were collected from the health quality database of the Taiwanese National Health Insurance Administration from 2019 to 2021. Air pollution and climatic factors in Taipei were used to evaluate these relationships. Changes in the rates of pediatric asthma ERVs were assessed using logistic regression analysis. Poisson regression was used to evaluate the impact of air pollution and climate change; (3) Results: The rate of pediatric asthma ERVs declined in different areas and at different hospital levels including medical centers, regional and local hospitals. Some air pollutants (particulate matter ≤ 2.5 µm, particulate matter ≤ 10 µm, nitrogen dioxide, and carbon monoxide) reduced during the COVID-19 lockdown. Ozone increased the relative risk (RR) of pediatric asthma ERVs during the COVID-19 period by 1.094 (95% CI: 1.095-1.12) per 1 ppb increase; (4) Conclusions: The rate of pediatric asthma ERVs declined during the COVID-19 pandemic and ozone has harmful effects. Based on these results, the government could reduce the number of pediatric asthma ERVs through healthcare programs, thereby promoting children's health.