Spatially and Temporally Resolved Ambient PM2.5 in Relation to Preterm Birth.
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ABSTRACT:
SUBMITTER: Cowell W
PROVIDER: S-EPMC8708619 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Evidence of associations between exposure to ambient air pollution and health outcomes are sparse in the South Asian region due to limited air pollution exposure and quality health data. This study investigated the potential impacts of ambient particulate matter (PM) on respiratory disease hospitalization in Kandy, Sri Lanka for the year 2019. The Generalized Additive Model (GAM) was applied to estimate the short-term effect of ambient PM on respiratory disease hospitalization. As the second analysis, respiratory disease hospitalizations during two distinct air pollution periods were analyzed. Each 10 μg/m3 increase in same-day exposure to PM2.5 and PM10 was associated with an increased risk of respiratory disease hospitalization by 1.95% (0.25, 3.67) and 1.63% (0.16, 3.12), respectively. The effect of PM2.5 or PM10 on asthma hospitalizations were 4.67% (1.23, 8.23) and 4.04% (1.06, 7.11), respectively (p < 0.05). The 65+ years age group had a higher risk associated with PM2.5 and PM10 exposure and hospital admissions for all respiratory diseases on the same day (2.74% and 2.28%, respectively). Compared to the lower ambient air pollution period, higher increased hospital admissions were observed among those aged above 65 years, males, and COPD and pneumonia hospital admissions during the high ambient air pollution period. Active efforts are crucial to improve ambient air quality in this region to reduce the health effects.
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Project description:Particulate lead (Pb) is a primary air pollutant that affects society because of its health impacts. This study investigates the source sectors of Pb associated with ambient fine particulate matter (PM2.5) over central-western Taiwan (CWT) with new constraints on the Pb-isotopic composition. We demonstrate that the contribution of coal-fired facilities is overwhelming, which is estimated to reach 35 ± 16% in the summertime and is enhanced to 57 ± 24% during the winter monsoon seasons. Moreover, fossil-fuel vehicles remain a major source of atmospheric Pb, which accounts for 12 ± 5%, despite the current absence of a leaded gasoline supply. Significant seasonal and geographical variations in the Pb-isotopic composition are revealed, which suggest that the impact of East Asian (EA) pollution outflows is important in north CWT and drastically declines toward the south. We estimate the average contribution of EA outflows as accounting for 35 ± 15% (3.6 ± 1.5 ng/m3) of the atmospheric Pb loading in CWT during the winter monsoon seasons.
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Project description:Fine-particulate pollution is a major public health concern in China. Accurate assessment of the population exposed to PM2.5 requires high-resolution pollution and population information. This paper assesses China's potential population exposure to PM2.5, maps its spatiotemporal variability, and simulates the effects of the recent air pollution control policy. We relate satellite-based Aerosol Optical Depth (AOD) retrievals to ground-based PM2.5 observations. We employ block cokriging (BCK) to improve the spatial interpolation of PM2.5 distribution. We use the subdistrict level population data to estimate and map the potential population exposure to PM2.5 pollution in China at the subdistrict level, the smallest administrative unit with public demographic information. During 8 April 2013 and 7 April 2014, China's population-weighted annual average PM2.5 concentration was nearly 7 times the annual average level suggested by the World Health Organization (WHO). About 1322 million people, or 98.6% of the total population, were exposed to PM2.5 at levels above WHO's daily guideline for longer than half a year. If China can achieve its Action Plan on Prevention and Control of Air Pollution targets by 2017, the population exposed to PM2.5 above China's daily standard for longer than half a year will be reduced by 85%.
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Project description:Direct residential and transportation energy consumption (RTC) contributes significantly to ambient fine particulate matter with a diameter smaller than 2.5 μm (PM2.5) in China. During massive rural-urban migration, population and pollutant emissions from RTC have evolved in terms of magnitude and geographic distribution, which was thought to worsen PM2.5 levels in cities but has not been quantitatively addressed. We quantify the temporal trends and spatial patterns of migration to cities and evaluate their associated pollutant emissions from RTC and subsequent health impact from 1980 to 2030. We show that, despite increased urban RTC emissions due to migration, the net effect of migration in China has been a reduction of PM2.5 exposure, primarily because of an unequal distribution of RTC energy mixes between urban and rural areas. After migration, people have switched to cleaner fuel types, which considerably lessened regional emissions. Consequently, the national average PM2.5 exposure concentration in 2010 was reduced by 3.9 μg/m3 (90% confidence interval, 3.0 to 5.4 μg/m3) due to migration, corresponding to an annual reduction of 36,000 (19,000 to 47,000) premature deaths. This reduction was the result of an increase in deaths by 142,000 (78,000 to 181,000) due to migrants swarming into cities and decreases in deaths by 148,000 (76,000 to 194,000) and 29,000 (15,000 to 39,000) due to transitions to a cleaner energy mix and lower urban population densities, respectively. Locally, however, megacities such as Beijing and Shanghai experienced increases in PM2.5 exposure associated with migration because these cities received massive immigration, which has driven a large increase in local emissions.
| S-EPMC5517109 | biostudies-literature
Project description:BackgroundStudies suggested that PM2.5 exposure could lead to adverse reproductive effects on male animals. However, the underlying mechanism is still not clear. Besides, animals in the majority of previous studies were exposed to PM2.5 through intratracheal instillation which should be improved. In addition, limited amount of research has been conducted in China where the PM2.5 concentration is higher and the PM2.5 components are different. The aim of this work is to explore the effects of concentrated ambient PM2.5 (CAP) on mice sperm quality and testosterone biosynthesis.MethodsA total of 12 male C57BL/6 mice were exposed to filtered air (FA) or CAP for 125 days using the Shanghai Meteorological and Environmental Animal Exposure System. The mice sperm concentration, sperm motility, DNA fragmentation index, high DNA stainability and plasma testosterone were analyzed. Testicular histology and sperm morphology were observed through optical microscope. Testosterone biosynthesis related gene expressions were analyzed using real-time PCR, including cytochrome P450 CHOL side-chain cleavage enzyme (P450scc), steroidogenic acute regulatory protein (StAR), 3β-hydroxysteroid dehydrogenase (3β HSD), 17β-hydroxysteroid dehydrogenase, cytochrome P450 aromatase (P450arom), estrogen receptor (ER), androgen receptor (AR) and follicle stimulating hormone receptor (FSHR).ResultsExposure to CAP resulted in disturbance of various stages of spermatogenesis and significant higher percentage of abnormal sperm (FA vs. CAP: 24.37% vs. 44.83%) in mice testis. CAP exposure significantly decreased sperm concentration (43.00 × 106 vs. 25.33 × 106) and motility (PR: 63.58% vs. 55.15%; PR + NP: 84.00% vs. 77.08%) in epididymis. Plasma testosterone concentration were significantly declined (0.28 ng/ml vs. 0.69 ng/ml) under CAP exposure. Notably, the levels of testosterone biosynthesis related genes, StAR, P450scc, P450arom, ER and FSHR were significantly decreased with CAP exposure.ConclusionConcentrated ambient PM2.5 exposure altered mice sperm concentration, motility and morphology, which might be mediated primarily by the decline in testosterone concentration and testosterone biosynthesis process.
| S-EPMC6885350 | biostudies-literature
Project description:Rapid urbanization and consuming lifestyles have intensified air pollution in urban areas. Air pollution in megacities has imposed severe environmental damages to human health. Proper management of the issue necessitates identification of the share of emission sources. Therefore, numerous research works have studied the apportionment of the total emissions and observed concentrations among different emissions sources. In this research, a comprehensive review is conducted to compare the source apportioning results for ambient air PM2.5 in the megacity of Tehran, the capital of Iran. One hundred seventy-seven pieces of scientific literatures, published between 2005 and 2021, were reviewed. The reviewed research are categorized according to the source apportioning methods: emission inventory (EI), source apportionment (SA), and sensitivity analysis of the concentration to the emission sources (SNA). The possible reasons for inconsistency among the results are discussed according to the scope of the studies and the implemented methods. Although 85% of the reviewed original estimates identify that mobile sources contribute to more thant 60% of Tehran air pollution, the distribution of vehicle types and modes are clearly inconsistent among the EI studies. Our review suggests that consistent results in the SA studies in different locations in central Tehran may indicate the reliability of this method for the identification of the type and share of the emission sources. In contrast, differences among the geographical and sectoral coverage of the EI studies and the disparities among the emission factors and activity data have caused significant deviations among the reviewed EI studies. Also, it is shown that the results of the SNA studies are highly dependent on the categorization type, model capabilities and EI presumptions and data input to the pollutant dispersion modelings. As a result, integrated source apportioning in which the three methods complement each other's results is necessary for consistent air pollution management in megacities.Supplementary informationThe online version contains supplementary material available at 10.1007/s40201-023-00855-0.
| S-EPMC10163186 | biostudies-literature
Project description:We quantify the contributions of long-range and regionally transported aerosols to ambient primary PM2.5 and PM10 in a representative United States industrialized/urban atmosphere via detailed elemental analysis and chemical mass balance (CMB) modeling after identifying their presence using a variety of publicly available satellite data/information, software products, and synoptic-scale aerosol models. A year-long study in Houston, Texas identified North African dust as the principal long-range global source of primary particulate matter (PM). CMB estimated transatlantic dust from the Sahara-Sahel region to be dominant in the summer months contributing an average of 3.5 μg m-3 to PM2.5 and 7.9 μg m-3 to PM10 during May-August, i.e., the active Saharan dust season. Biomass burning was the chief source of regionally transported PM impacting air quality on different occasions throughout the year depending on the fire location. Four major biomass combustion events affecting air quality in Texas were calculated to contribute an average of 1.3 μg m-3 to PM2.5 and 1.4 μg m-3 to PM10 in corresponding samples whose origins were tracked to Canada, southeastern states of USA, and Central America using fire maps, HYSPLIT back trajectories, and the Navy Aerosol Analysis and Prediction System global aerosol model. Elemental concentrations and signature ratios revealed significant mixing of potassium, rare earth metals, and vanadium from proximal and distal crustal (natural) sources with anthropogenically emitted PM. This demonstrates the need to isolate the non-mineral components of these metals to employ them as tracers for primary PM emitted by biomass burning, petroleum refineries, and oil combustion. Transboundary contributions to primary PM2.5 were 1.5 μg m-3 and 3.1 μg m-3 to PM10 adding 16% to annual average mass concentration of both size fractions demonstrating that local sources were primarily responsible for ambient air quality with non-trivial contributions from international and interstate sources. Rigorously identifying and quantifying aerosol sources assists in improving air quality management policies designed to protect public health and comply with ever-decreasing federal PM standards that allow state agencies to exclude contributions that are not reasonably controllable or preventable from regulatory decisions and actions.
| S-EPMC10022636 | biostudies-literature
Project description:BackgroundThe metabolomic signatures of short- and long-term exposure to PM2.5 have been reported and linked to inflammation and oxidative stress. However, little is known about the relative contribution of the specific PM2.5 species (hence sources) that drive these metabolomic signatures.ObjectivesWe aimed to determine the relative contribution of the different species of PM2.5 exposure to the perturbed metabolic pathways related to changes in the plasma metabolome.MethodsWe performed mass-spectrometry based metabolomic profiling of plasma samples among men from the Normative Aging Study to identify metabolic pathways associated with PM2.5 species. The exposure windows included short-term (one, seven-, and thirty-day moving average) and long-term (one year moving average). We used linear mixed-effect regression with subject-specific intercepts while simultaneously adjusting for PM2.5, NO2, O3, temperature, relative humidity, and covariates and correcting for multiple testing. We also used independent component analysis (ICA) to examine the relative contribution of patterns of PM2.5 species.ResultsBetween 2000 and 2016, 456 men provided 648 blood samples, in which 1158 metabolites were quantified. We chose 305 metabolites for the short-term and 288 metabolites for the long-term exposure in this analysis that were significantly associated (p-value < 0.01) with PM2.5 to include in our PM2.5 species analysis. On average, men were 75.0 years old and their body mass index was 27.7 kg/m2. Only 3% were current smokers. In the adjusted models, ultrafine particles (UFPs) were the most significant species of short-term PM2.5 exposure followed by nickel, vanadium, potassium, silicon, and aluminum. Black carbon, vanadium, zinc, nickel, iron, copper, and selenium were the significant species of long-term PM2.5 exposure. We identified several metabolic pathways perturbed with PM2.5 species including glycerophospholipid, sphingolipid, and glutathione. These pathways are involved in inflammation, oxidative stress, immunity, and nucleic acid damage and repair. Results were overlapped with the ICA.ConclusionsWe identified several significant perturbed plasma metabolites and metabolic pathways associated with exposure to PM2.5 species. These species are associated with traffic, fuel oil, and wood smoke. This is the largest study to report a metabolomic signature of PM2.5 species' exposure and the first to use ICA.
| S-EPMC7994935 | biostudies-literature
Project description:It has been posited that populations being exposed to long-term air pollution are more susceptible to COVID-19. Evidence is emerging that long-term exposure to ambient PM2.5 (particulate matter with aerodynamic diameter 2.5 ?m or less) associates with higher COVID-19 mortality rates, but whether it also associates with the speed at which the disease is capable of spreading in a population is unknown. Here, we establish the association between long-term exposure to ambient PM2.5 in the United States (US) and COVID-19 basic reproduction ratio R0- a dimensionless epidemic measure of the rapidity of disease spread through a population. We inferred state-level R0 values using a state-of-the-art susceptible, exposed, infected, and recovered (SEIR) model initialized with COVID-19 epidemiological data corresponding to the period March 2-April 30. This period was characterized by a rapid surge in COVID-19 cases across the US states, implementation of strict social distancing measures, and a significant drop in outdoor air pollution. We find that an increase of 1 ?g/m3 in PM2.5 levels below current national ambient air quality standards associates with an increase of 0.25 in R0 (95% CI: 0.048-0.447). A 10% increase in secondary inorganic composition, sulfate-nitrate-ammonium, in PM2.5 associates with ?10% increase in R0 by 0.22 (95% CI: 0.083-0.352), and presence of black carbon (soot) in the ambient environment moderates this relationship. We considered several potential confounding factors in our analysis, including gaseous air pollutants and socio-economical and meteorological conditions. Our results underscore two policy implications - first, regulatory standards need to be better guided by exploring the concentration-response relationships near the lower end of the PM2.5 air quality distribution; and second, pollution regulations need to be continually enforced for combustion emissions that largely determine secondary inorganic aerosol formation.
| S-EPMC7651233 | biostudies-literature
Project description:Air pollution epidemiology studies of ambient fine particulate matter (PM2.5) and ozone (O3) often use outdoor concentrations as exposure surrogates. Failure to account for the variability of the indoor infiltration of ambient PM2.5 and O3, and time indoors, can induce exposure errors. We developed an exposure model called TracMyAir, which is an iPhone application ("app") that determines seven tiers of individual-level exposure metrics in real-time for ambient PM2.5 and O3 using outdoor concentrations, weather, home building characteristics, time-locations, and time-activities. We linked a mechanistic air exchange rate (AER) model, a mass-balance PM2.5 and O3 building infiltration model, and an inhaled ventilation model to determine outdoor concentrations (Tier 1), residential AER (Tier 2), infiltration factors (Tier 3), indoor concentrations (Tier 4), personal exposure factors (Tier 5), personal exposures (Tier 6), and inhaled doses (Tier 7). Using the application in central North Carolina, we demonstrated its ability to automatically obtain real-time input data from the nearest air monitors and weather stations, and predict the exposure metrics. A sensitivity analysis showed that the modeled exposure metrics can vary substantially with changes in seasonal indoor-outdoor temperature differences, daily home operating conditions (i.e., opening windows and operating air cleaners), and time spent outdoors. The capability of TracMyAir could help reduce uncertainty of ambient PM2.5 and O3 exposure metrics used in epidemiology studies.
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