An application of a non-homogeneous Poisson model to study PM2.5 exceedances in Mexico City and Bogota.
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ABSTRACT:
SUBMITTER: Suarez-Sierra BM
PROVIDER: S-EPMC9225304 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundChildhood exposure to air pollution has been linked with maladaptive cognitive development; however, less is known about the association between prenatal fine particulate matter (PM2.5) exposure and childhood behavior.ObjectivesOur aim was to assess the association between prenatal PM2.5 exposure and behavioral development in 4-6 year old children residing in Mexico City.MethodsWe used data from 539 mother-child pairs enrolled in a prospective birth cohort in Mexico City. We estimated daily PM2.5 exposure using a 1 km2 satellite-based exposure model and averaged over each trimester of pregnancy. We assessed childhood behavior at 4-6 years of age using the parent-completed Behavioral Assessment Scale for Children (BASC-2) composite scores and subscales. We used linear regression models to estimate change in BASC-2 T-scores with trimester specific 5-μg/m3 increases in PM2.5. All models were mutually adjusted for PM2.5 exposures during the other trimesters, maternal factors including age, education, socioeconomic status, depression, and IQ, child's age at study visit, and season. We additionally assessed sex-specific effects by including an interaction term between PM2.5 and sex.ResultsHigher first trimester PM2.5 exposure was associated with reduced Adaptive Skills scores (β: -1.45, 95% CI: -2.60, -0.30). Lower scores on the Adaptive Skills composite score and subscales indicate poorer functioning. For PM2.5 exposure during the first trimester, decrements were consistent across adaptive subscale scores including Adaptability (β: -1.51, 95% CI: -2.72, -0.30), Social Skills (β: -1.63, 95% CI: -2.90, -0.36), and Functional Communication (β: -1.21, 95% CI: -2.21, -0.21). The association between 1st trimester PM2.5 and depression was stronger in males than females (β for males: 1.52, 95% CI: -0.41, 3.45; β for females: -0.13, 95% CI: -1.99, 1.72; p-int: 0.07).ConclusionsExposure to PM2.5 during early pregnancy may be associated with impaired behavioral development in children, particularly for measures of adaptive skills. These results suggest that air pollution impacts behavioral domains as well as cognition, and that the timing of exposure may be critical.
| S-EPMC7708408 | biostudies-literature
Project description:Fine particulate matter (PM2.5) is the leading environmental risk factor that requires regular monitoring and analysis for effective air quality management. This work presents the variability, trend, and exceedance analysis of PM2.5 measured at US Embassy and Consulate in five Indian megacities (Chennai, Kolkata, Hyderabad, Mumbai, and New Delhi) for six years (2014-2019). Among all cities, Delhi is found to be the most polluted city followed by Kolkata, Mumbai, Hyderabad, and Chennai. The trend analysis for six years for five megacities suggests a statistically significant decreasing trend ranging from 1.5 to 4.19 μg/m3 (2%-8%) per year. Distinct diurnal, seasonal, and monthly variations are observed in the five cities due to the different site locations and local meteorology. All cities show the highest and lowest concentrations in the winter and monsoon months respectively except for Chennai which observed the lowest levels in April. All the cities consistently show morning peaks (~08: 00-10:00 h) and the lowest level in late afternoon hours (~15:00-16:00 h). We found that the PM2.5 levels in the cities exceed WHO standards and Indian NAAQS for 50% and 33% of days in a year except for Chennai. Delhi is found to have more than 200 days of exceedances in a year and experiences an average 15 number of episodes per year when the level exceeds the Indian NAAQS. The trends in the exceedance with a varying threshold (20-380 μg/m3) suggest that not only is the annual mean PM2.5 decreasing in Delhi but also the number of exceedances is decreasing. This decrease can be attributed to the recent policies and regulations implemented in Delhi and other cities for the abatement of air pollution. However, stricter compliance of the National Clean Air Program (NCAP) policies can further accelerate the reduction of the pollution levels.
| S-EPMC7417276 | biostudies-literature
Project description:BackgroundRecent studies have reported that air pollution exposure may have neurotoxic properties.ObjectiveTo examine longitudinal associations between prenatal particles less than 2.5 μm in diameter (PM2.5) exposure and neurodevelopment during the first two years of children's life.MethodsAnalysis was conducted in PROGRESS, a longitudinal birth cohort between 2007 and 2013 in Mexico City. We used satellite data to predict daily PM2.5 concentrations at high spatial resolution. Multivariate mixed-effect regression models were adjusted to examine cognitive, language and motor scores in children up to 24 months of age (n = 740) and each trimester-specific and whole pregnancy exposure to PM2.5.ResultsModels adjusted by child sex, gestational age, birth weight, smoking and mother's IQ, showed that each increase of 1 μg/m3 of PM2.5 was associated with a decreased language function of -0.38 points (95% CI: -0.77, -0.01). PM2.5 exposure at third trimester of pregnancy contributed most to the observed association.ConclusionOur findings suggest that language development up to 24 months of age may be particularly sensitive to PM2.5 exposure during pregnancy.
| S-EPMC8759610 | biostudies-literature
Project description:Nowadays in many countries, air pollution is one of the major issues affecting human health. Among the various air pollutants particulate matters are mainly present in ambient air pollution. The purpose of this study was to measure the concentration of particulate matter (PM) (namely PM2.5 and PM10) and to conduct zoning via GIS software in Khorramabad city (Summer - 2017). According to the findings, the average concentrations of PM2.5 in July, August and September were 100.1, 116.3, and 199.8 μg/m3, respectively. Furthermore, the average concentrations of PM10 in July, August and September were 199.8, 215.7, and 190.8 μg/m3, respectively. The findings of this study also indicated that due to continuous dust storms,particularly in recent years, the air pollution status in Khorramabad was not suitable that can adversely affect public health.
| S-EPMC6139470 | biostudies-literature
Project description:BackgroundSatellite-based PM2.5 predictions are being used to advance exposure science and air-pollution epidemiology in developed countries; including emerging evidence about the impacts of PM2.5 on acute health outcomes beyond the cardiovascular and respiratory systems, and the potential modifying effects from individual-level factors in these associations. Research on these topics is lacking in low and middle income countries. We aimed to explore the association between short-term exposure to PM2.5 with broad-category and cause-specific mortality outcomes in the Mexico City Metropolitan Area (MCMA), and potential effect modification by age, sex, and SES characteristics in such associations.MethodsWe used a time-stratified case-crossover study design with 1,479,950 non-accidental deaths from the MCMA for the period of 2004-2019. Daily 1 × 1 km PM2.5 (median = 23.4 μg/m3; IQR = 13.6 μg/m3) estimates from our satellite-based regional model were employed for exposure assessment at the sub-municipality level. Associations between PM2.5 with broad-category (organ-system) and cause-specific mortality outcomes were estimated with distributed lag conditional logistic models. We also fit models stratifying by potential individual-level effect modifiers including; age, sex, and individual SES-related characteristics namely: education, health insurance coverage, and job categories. Odds ratios were converted into percent increase for ease of interpretation.ResultsPM2.5 exposure was associated with broad-category mortality outcomes, including all non-accidental, cardiovascular, cerebrovascular, respiratory, and digestive mortality. A 10-μg/m3 PM2.5 higher cumulative exposure over one week (lag06) was associated with higher cause-specific mortality outcomes including hypertensive disease [2.28% (95%CI: 0.26%-4.33%)], acute ischemic heart disease [1.61% (95%CI: 0.59%-2.64%)], other forms of heart disease [2.39% (95%CI: -0.35%-5.20%)], hemorrhagic stroke [3.63% (95%CI: 0.79%-6.55%)], influenza and pneumonia [4.91% (95%CI: 2.84%-7.02%)], chronic respiratory disease [2.49% (95%CI: 0.71%-4.31%)], diseases of the liver [1.85% (95%CI: 0.31%-3.41%)], and renal failure [3.48% (95%CI: 0.79%-6.24%)]. No differences in effect size of associations were observed between age, sex and SES strata.ConclusionsExposure to PM2.5 was associated with non-accidental, broad-category and cause-specific mortality outcomes beyond the cardiovascular and respiratory systems, including specific death-causes from the digestive and genitourinary systems, with no indication of effect modification by individual-level characteristics.
| S-EPMC10580614 | biostudies-literature
Project description:Fine particulate matter is considered to be the most significant ambient air pollutant in terms of potential health impacts. Therefore, it is important that regulators are able to accurately assess the exposure of populations to PM10 and PM2.5 across municipal areas. We report on the practicalities of using a laser light scattering portable particulate monitor (Turnkey Instruments DustMate), in combination with a GPS, to map PM10 and PM2.5 concentrations on city-wide scales in Newcastle upon Tyne/Gateshead (UK), during a series of walking surveys. A heated inlet is necessary to remove moisture droplets from the sampled air prior to analysis by the instrument, though this also results in the loss of volatile particulate components, particularly from the PM2.5 fraction. A co-location calibration study was carried out with a reference urban background Tapered Element Oscillating Micro-Balance/Filter Dynamics Measuring System (TEOM-FDMS) system in Newcastle that is part of the UK's Automatic Urban and Rural Network (AURN) of air quality monitoring stations. For PM10, orthogonal regression of the DustMate against TEOM-FDMS data gave a slope and intercept of 1.02 ± 0.06 and -3.7 ± 1.2, respectively (R2 = 0.73), whereas for PM2.5, the respective values were 0.78 ± 0.06 and -0.63 ± 0.55 (R2 = 0.79). These parameters are comparable to literature calibration studies using this technology. There was good agreement between simultaneous samples taken using two DustMate instruments: for PM10, a slope and intercept of 1.05 ± 0.03 and 0.36 ± 0.5, respectively (R2 = 0.73), were obtained, whereas for the PM2.5, the respective values were 0.79 ± 0.01 and 0.19 ± 0.06 (R2 = 0.86). Correction factors based on the slope and intercepts obtained from the calibration exercise were applied to raw data collected from the DustMate. An annually-normalised correction procedure was then used to account for different background particulate concentrations on different sampling days. These corrected PM10 and PM2.5 concentrations and corresponding GPS coordinates were displayed on a base map using Google Fusion Tables and Google Earth Professional. Almost all areas surveyed in Newcastle/Gateshead were well below the EU Air Quality Standards for PM10 and PM2.5.
| S-EPMC5093208 | biostudies-literature
Project description:PurpuseThe COVID-19 outbreak has escalated into the worse pandemic of the present century. The fast spread of the new SARS-CoV-2 coronavirus has caused devastating health and economic crises all over the world, with Spain being one of the worst affected countries in terms of confirmed COVID-19 cases and deaths per inhabitant. In this situation, the Spanish Government declared the lockdown of the country.MethodsThe variations of air pollution in terms of fine particulate matter (PM2.5) levels in seven representative cities of Spain are analyzed here considering the effect of meteorology during the national lockdown. The possible associations of PM2.5 pollution and climate with COVID-19 accumulated cases were also analyzed.ResultsWhile the epidemic curve was flattened, the results of the analysis show that the 4-week Spanish lockdown significantly reduced the PM2.5 levels in only one city despite the drastically reduced human activity. Furthermore, no associations between either PM2.5 exposure or environmental conditions and COVID-19 transmission were found during the early spread of the pandemic.ConclusionsA longer period applying human activity restrictions is necessary in order to achieve significant reductions of PM2.5 levels in all the analyzed cities. No effect of PM2.5 pollution or weather on COVID-19 incidence was found for these pollutant levels and period of time.Graphical abstractSupplementary informationThe online version contains supplementary material available at 10.1007/s40201-022-00786-2.
| S-EPMC8734552 | biostudies-literature
Project description:It is well-documented that subway stations exhibit high fine particulate matter (PM2.5) concentrations. Little is known about the potential of river-tunnels to increase PM2.5 concentrations in subways. We hypothesized a "river-tunnel" effect exists: Stations adjacent to poorly ventilated tunnels that travel beneath rivers exhibit higher PM2.5 concentrations than more distant stations. Accordingly, the PM2.5 concentrations were monitored at stations adjacent to and two- and three-stations distant from the river-tunnel. Multivariate linear regression analysis was conducted to disentangle how proximity to a river-tunnel and other factors (e.g., depth) influence concentrations. Stations adjacent to a river-tunnel had 80-130% higher PM2.5 concentrations than more distant stations. Moreover, distance from a river-tunnel was the strongest PM2.5-influencing factor This distance effect was not observed at underground stations adjacent to a river-bridge. The "river-tunnel" effect explains some of the inter-station variability in subway PM2.5 concentrations. These results support the need for improving ventilation systems in subways.
| S-EPMC9879276 | biostudies-literature
Project description:Specification of PM 2.5 transmission characteristics is important for pollution control and policymaking. We apply higher-order organization of complex networks to identify major potential PM 2.5 contributors and PM 2.5 transport pathways of a network of 189 cities in China. The network we create in this paper consists of major cities in China and contains information on meteorological conditions of wind speed and wind direction, data on geographic distance, mountains, and PM 2.5 concentrations. We aim to reveal PM 2.5 mobility between cities in China. Two major conclusions are revealed through motif analysis of complex networks. First, major potential PM 2.5 pollution contributors are identified for each cluster by one motif, which reflects movements from source to target. Second, transport pathways of PM 2.5 are revealed by another motif, which reflects transmission routes. To our knowledge, this is the first work to apply higher-order network analysis to study PM 2.5 transport.
| S-EPMC5643331 | biostudies-literature
Project description:Ambient air pollution is a growing public health concern in major African cities, including Addis Ababa (Ethiopia), where little information is available on fine particulate matter (PM2.5, with aerodynamic diameter <2.5 µm) pollution. This paper aims to characterize annual PM2.5, including bulk composition and seasonal patterns, in Addis Ababa. We collected 24-h PM2.5 samples in the central city every 6 days from November 2015 to November 2016. The mean (±SD) daily PM2.5 concentration was 53.8 (±25.0) µg/m3, with 90% of sampled days exceeding the World Health Organization's guidelines. Principal components were organic matter (OM, 44.5%), elemental carbon (EC, 25.4%), soil dust (13.5%), and SNA (sulfate, nitrate, and ammonium ions, 8.2%). Higher PM2.5 concentrations were observed during the heavy rain season, while crustal dust concentrations ranged from 2.9 to 37.6%, with higher levels during dry months. Meteorological variables, vehicle emissions, biomass fuels, unpaved roads, and construction activity contribute to poor air quality. Compared to the Air Quality Index (AQI), 31% and 36% of observed days were unhealthy for everyone and unhealthy for sensitive groups, respectively. We recommend adopting effective prevention strategies and pursuing research on vehicle emissions, biomass burning, and dust control to curb air pollution in the city.
| S-EPMC7579520 | biostudies-literature