Spatio-temporal variation in fine particulate matter and effect on air quality during the COVID-19 in New Delhi, India.
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ABSTRACT:
SUBMITTER: Singh BP
PROVIDER: S-EPMC8549199 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Long-term particulate matter (PM10) measurements were conducted during the period January 2016 to September 2017 at three sites in Uganda (Mbarara, Kyebando, and Rubindi) representing a wide range of urbanization. Spatial, temporal and diurnal variations are assessed in this paper. Particulate matter (PM10) samples were collected for 24-h periods on PTFE filters using a calibrated pump and analyzed gravimetrically to determine the average density. Particulate levels were monitored simultaneously using a light scattering instrument to acquire real time data from which diurnal variations were assessed. The PM10 levels averaged over the sampling period at Mbarara, Kyebando, and Rubindi were 5.8, 8.4, and 6.5 times higher than the WHO annual air quality guideline of 20 µg·m-3, and values exceeded the 24-h mean PM10 guideline of 50 µg·m-3 on 83, 100, and 86% of the sampling days. Higher concentrations were observed during dry seasons at all sites. Seasonal differences were statistically significant at Rubindi and Kyebando. Bimodal peaks were observed in the diurnal analysis with higher morning peaks at Mbarara and Kyebando, which points to the impact of traffic sources, while the higher evening peak at Rubindi points to the influence of dust suspension, roadside cooking and open-air waste burning. Long-term measurement showed unhealthy ambient air in all three locations tested in Uganda, with significant spatial and seasonal differences.
| S-EPMC6571861 | biostudies-literature
Project description:Using daily fine particulate matter (PM2.5) composition data from the 2000-2005 U.S. EPA Chemical Speciation Network (CSN) for over 200 sites, we applied multivariate methods to identify and quantify the major fine particulate matter (PM2.5) source components in the U.S. Novel aspects of this work were: (1) the application of factor analysis (FA) to multi-city daily data, drawing upon both spatial and temporal variations of chemical species; and, (2) the exclusion of secondary components (sulfates, nitrates and organic carbon) from the source identification FA to more clearly discern and apportion the PM2.5 mass to primary emission source categories. For the quantification of source-related mass, we considered two approaches based upon the FA results: 1) using single key tracers for sources identified by FA in a mass regression; and, 2) applying Absolute Principal Component Analysis (APCA). In each case, we followed a two-stage mass regression approach, in which secondary components were first apportioned among the identified sources, and then mass was apportioned to the sources and to other secondary mass not explained by the individual sources. The major U.S. PM2.5 source categories identified via FA (and their key elements) were: Metals Industry (Pb, Zn); Crustal/Soil Particles (Ca, Si); Motor Vehicle Traffic (EC, NO2); Steel Industry (Fe, Mn); Coal Combustion (As, Se); Oil Combustion (V, Ni); Salt Particles (Na, Cl) and Biomass Burning (K). Nationwide spatial plots of the source-related PM2.5 impacts were confirmatory of the factor interpretations: ubiquitous sources, such as Traffic and Soil, were found to be spread across the nation, more unique sources (such as Steel and Metals Processing) being highest in select industrialized cities, Biomass Burning was highest in the U.S. Northwest, while Residual Oil combustion was highest in cities in the Northeastern U.S. and in cities with major seaports. The sum of these source contributions and the secondary PM2.5 components agreed well with the U.S. PM2.5 observed during the study period (mean=14.3 ug/m3; R2= 0.91). Apportionment regression analyses using single-element tracers for each source category gave results consistent with the APCA estimates. Comparisons of nearby sites indicated that the PM2.5 mass and the secondary aerosols were most homogenous spatially, while traffic PM2.5 and its tracer, EC, were among the most spatially representative of the source-related components. Comparison of apportionment results to a previous analysis of the 1979-1982 IP Network revealed similar and correlated major U.S. source category factors, albeit at lower levels than in the earlier period, suggesting a consistency in the U.S. spatial patterns of these source-related exposures over time, as well. These results indicate that applying source apportionment methods to the nationwide CSN can be an informative avenue for identifying and quantifying source components for the subsequent estimation of source-specific health effects, potentially contributing to more efficient regulation of PM2.5.
| S-EPMC3951912 | biostudies-literature
Project description:Although cohort studies of the health effects of PM2.5 have developed exposure prediction models to represent spatial variability across participant residences, few models exist for PM2.5 components. We aimed to develop a city-specific spatio-temporal prediction approach to estimate long-term average concentrations of four PM2.5 components including sulfur, silicon, and elemental and organic carbon for the Multi-Ethnic Study of Atherosclerosis cohort, and to compare predictions to those from a national spatial model. Using 2-week average measurements from a cohort-focused monitoring campaign, the spatio-temporal model employed selected geographic covariates in a universal kriging framework with the data-driven temporal trend. Relying on long-term means of daily measurements from regulatory monitoring networks, the national spatial model employed dimension-reduced predictors using universal kriging. For the spatio-temporal model, the cross-validated and temporally-adjusted R(2) was relatively higher for EC and OC, and in the Los Angeles and Baltimore areas. The cross-validated R(2)s for both models across the six areas were reasonably high for all components except silicon. Predicted long-term concentrations at participant homes from the two models were generally highly correlated across cities but poorly correlated within cities. The spatio-temporal model may be preferred for city-specific health analyses, whereas both models could be used for multi-city studies.
| S-EPMC5104659 | biostudies-literature
Project description:The Kathmandu Valley in Nepal experiences poor air quality, especially in the dry winter season. In this study, we investigated the concentration, chemical composition, and sources of fine and coarse particulate matter (PM2.5, PM10, and PM10-2.5) at three sites within or near the Kathmandu Valley during the winter of 2018 as part of the second Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE 2). Daily PM2.5 concentrations were very high throughout the study period, ranging 72-149 μg m-3 at the urban Ratnapark site in Kathmandu, 88-161 μg m-3 at the suburban Lalitpur site, and 40-74 μg m-3 at rural Dhulikhel on the eastern rim of the Kathmandu Valley. Meanwhile, PM10 ranged 194-309, 174-377, and 64-131 μg m-3, respectively. At the Ratnapark site, crustal materials from resuspended soil contributed an average of 11% of PM2.5 and 34% of PM10. PM2.5 was largely comprised of organic carbon (OC, 28-30% by mass) and elemental carbon (EC, 10-14% by mass). As determined by chemical mass balance source apportionment modeling, major PM2.5 OC sources were garbage burning (15-21%), biomass burning (10-17%), and fossil fuel (14-26%). Secondary organic aerosol (SOA) contributions from aromatic volatile organic compounds (13-23% OC) were larger than those from isoprene (0.3-0.5%), monoterpenes (0.9-1.4%), and sesquiterpenes (3.6-4.4%). Nitro-monoaromatic compounds-of interest due to their light-absorbing properties and toxicity-indicate the presence of biomass burning-derived SOA. Knowledge of primary and secondary PM sources can facilitate air quality management in this region.
| S-EPMC9761783 | biostudies-literature
Project description:Diwali has become an occasion of air and noise pollution, and the release of particulate matter and toxic gases has chronic and acute effects on people and their environment. Thus, an air quality assessment study was done by CSIR-CSMCRI covering the pre-to-post Diwali 2021 period (5 days) in the three locations (traffic, residential, and control) of Bhavnagar. The average 24-h concentration of PM10 (380 µg/m3), PM2.5 (182.2 µg/m3), and SPM (403 µg/m3) was significantly higher during Diwali, exceeding the National Ambient Air Quality Standards (NAAQS). The concentrations of SO2 and NO2 were 121.8 µg/m3 and 102.1 µg/m3. Metals like Zn, Al, Pb, and Mn were found in higher concentrations during the study. The air quality index (AQI) was maximum on Diwali, resembling very poor air quality. More elements and oxides were detected in PM2.5 (S, Al, Mg, Ba, and Zn and their oxides) than in PM10 (Fe and S) through WDXRF. Water-soluble anions like SO42-, Cl-, and NO3- were observed during the study, with a higher SO42- (64%) on Diwali. The PM10 morphology and mapping of elements were done using SEM-EDX. Emerging contaminants, specifically phthalate groups, were detected through GCMS. The enrichment factor (EF) showed Zn and Pb originating from anthropogenic activities. The air quality data was validated using a variance test, least significance difference (LSD), correlation, and principal component analysis (PCA). This paper is the first to highlight the air quality assessment during Diwali for a western coastal place in India. It is time to implement regulations on burning firecrackers for pollution reduction, aiming to achieve a sustainable atmosphere.
| S-EPMC9937863 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic has had a deep global impact, not only from a social and economic perspective, but also with regard to human health and the environment. To restrict transmission of the virus, the Indian government enforced a complete nationwide lockdown except for essential services and supplies in phases from 25 March to 31 May 2020. Ambient air quality in and around New Delhi, one of the most polluted cities of world, was also impacted during this period.ObjectiveThe aim of the present study was to assess and understand the impact of four different lockdown phases (LD1, LD2, LD3 and LD4) on five air pollutants (particulate matter (PM) PM2.5, PM10, nitrogen oxide (NOx), sulfur dioxide (SO2) and ozone (O3)) compared to before lockdown (BLD) at 13 air monitoring stations in and around New Delhi.MethodsSecondary data on five criteria pollutants for 13 monitoring stations in and around New Delhi for the period 1 March to 31 May 2020 was accessed from the Central Pollution Control Bard, New Delhi. Data were statistically analyzed across lockdown phases, meteorological variables, and prevailing air sources around the monitoring stations.ResultsPollutant concentrations decreased during LD1 compared to BLD except for O3 at all stations. PM2.5 and PM10 remained either close to or higher than the National Ambient Air Quality Standards (NAAQS) due to prevailing high-speed winds. During lockdown phases, NO2 decreased, whereas O3 consistently increased at all stations. This was a paradoxical situation as O3 is formed via photochemical reactions among NOx and volatile organic compounds. Principal component analysis (PCA) extracted two principal components (PC1 and PC2) which explained up to 80% of cumulative variance in data. PM2.5, PM10 and NO2 were associated with PC1, whereas PC2 had loadings of either O3 only or O3 and SO2 depending upon monitoring station.ConclusionsThe present study found that air pollutants decreased during lockdown phases, but these decreases were specific to the site(s) and pollutant(s). The decrease in pollutant concentrations during lockdown could not be attributed completely to lockdown conditions as the planetary boundary layer increased two-fold during lockdown compared to the BLD phase. Such restrictions could be applied in the future to control air pollution but should be approached with caution.Competing interestsThe authors declare no competing financial interests.
| S-EPMC8276728 | biostudies-literature
Project description:Ambient fine particulate matter (PM2.5) samples were collected from January to December 2007 to investigate the sources and chemical speciation in Palestine, Jordan, and Israel. The 24-h PM2.5 samples were collected on 6-day intervals at eleven urban and rural sites simultaneously. Major chemical components including metals, ions, and organic and elemental carbon were analyzed. The mass concentrations of PM2.5 across the 11 sites varied from 20.6 to 40.3 μg/m(3), with an average of 28.7 μg/m(3). Seasonal variation of PM2.5 concentrations was substantial, with higher average concentrations (37.3 μg/m(3)) in the summer (April-June) months compared to winter (October-December) months (26.0 μg/m(3)) due mainly to high contributions of sulfate and crustal components. PM2.5 concentrations in the spring were greatly impacted by regional dust storms. Carbonaceous mass was the most abundant component, contributing 40% to the total PM2.5 mass averaged across the eleven sites. Crustal components averaged 19.1% of the PM2.5 mass and sulfate, ammonium, and nitrate accounted for 16.2%, 6.4%, and 3.7%, respectively, of the total PM2.5 mass. The results of this study demonstrate the need to better protect the health and welfare of the residents on both sides of the Jordan River in the Middle East.
| S-EPMC4090475 | biostudies-literature
Project description:Using data from rural monitoring sites across the contiguous United States, we evaluated fine particulate matter (PM2.5) trends for 1988-2016. We calculate trends in the policy-relevant 98th quantile of PM2.5 using Quantile Regression. We use Kriging and Gaussian Geostatistical Simulations to interpolate trends between observed data points. Overall, we found positive trends in 98th quantile PM2.5 at sites within the Northwest United States (average 0.21 ± 0.12 µg·m-3·y-1; ±95% confidence interval). This was in contrast with sites throughout the rest of country, which showed a negative trend in 98th quantile PM2.5, likely due to reductions in anthropogenic emissions (average -0.66 ± 0.10 µg·m-3·y-1). The positive trend in 98th quantile PM2.5 is due to wildfire activity and was supported by positive trends in total carbon and no trend in sulfate across the Northwest. We also evaluated daily moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) for 2002-2017 throughout the United States to compare with ground-based trends. For both Interagency Monitoring of Protected Visual Environments (IMPROVE) PM2.5 and MODIS AOD datasets, we found positive 98th quantile trends in the Northwest (1.77 ± 0.68% and 2.12 ± 0.81% per year, respectively) through 2016. The trend in Northwest AOD is even greater if data for the high-fire year of 2017 are included. These results indicate a decrease in PM2.5 over most of the country but a positive trend in the 98th quantile PM2.5 across the Northwest due to wildfires.
| S-EPMC6077721 | biostudies-literature
Project description:BackgroundIn 1997 the U.S. Environmental Protection Agency set the first annual National Ambient Air Quality Standard (NAAQS) for fine particulate matter (PM2.5). Although the weight of scientific evidence has determined that a causal relationship exists between PM2.5 exposures and cardiovascular effects, few studies have concluded whether NAAQS-related reductions in PM2.5 led to improvements in public health.MethodsWe examined the change in cardiovascular (CV) mortality rate and the association between change in PM2.5 and change in CV-mortality rate before (2000-2004) and after implementation of the 1997 annual PM2.5 NAAQS (2005-2010) among U.S. counties. We further examined how the association varied with respect to two factors related to NAAQS compliance: attainment status and design values (DV). We used difference-in-differences and linear regression models, adjusted for sociodemographic confounders.FindingsAcross 619 counties, there were 1.10 (95% CI: 0.37, 1.82) fewer CV-deaths per year per 100,000 people for each 1µg/m3 decrease in PM2.5. Nonattainment counties had a twofold larger reduction in mean annual PM2.5, 2.1µg/m3, compared to attainment counties, 0.97µg/m3. CV-mortality rate decreased by 0.59 (95% CI: -0.54, 1.71) in nonattainment and 1.96 (95% CI: 0.77, 3.15) deaths per 100,000 people for each 1µg/m3 decrease in PM2.5 in attainment counties. When stratifying counties by DV, results were similar: counties with DV greater than 15µg/m3 experienced the greatest decrease in mean annual PM2.5 (2.29µg/m3) but the smallest decrease in CV-mortality rate per unit decrease in PM2.5, 0.73 (95% CI: -0.57, 2.02).InterpretationWe report a significant association between the change in PM2.5 and the change in CV-mortality rate before and after the implementation of NAAQS and note that the health benefits per 1µg/m3 decrease in PM2.5 persist at levels below the current national standard.FundingUS EPA intermural research.
| S-EPMC6372949 | biostudies-literature
Project description:With 2.8 billion biomass users globally, household air pollution remains a public health threat in many low- and middle-income countries. However, little evidence on pollution levels and health effects exists in low-income settings, especially slums. This study assesses the levels and sources of household air pollution in the urban slums of Nairobi. This cross-sectional study was embedded in a prospective cohort of pregnant women living in two slum areas-Korogocho and Viwandani-in Nairobi. Data on fuel and stove types and ventilation use come from 1058 households, while air quality data based on the particulate matters (PM2.5) level were collected in a sub-sample of 72 households using the DustTrak™ II Model 8532 monitor. We measured PM2.5 levels mainly during daytime and using sources of indoor air pollutions. The majority of the households used kerosene (69.7%) as a cooking fuel. In households where air quality was monitored, the mean PM2.5 levels were high and varied widely, especially during the evenings (124.6 µg/m³ SD: 372.7 in Korogocho and 82.2 µg/m³ SD: 249.9 in Viwandani), and in households using charcoal (126.5 µg/m³ SD: 434.7 in Korogocho and 75.7 µg/m³ SD: 323.0 in Viwandani). Overall, the mean PM2.5 levels measured within homes at both sites (Korogocho = 108.9 µg/m³ SD: 371.2; Viwandani = 59.3 µg/m³ SD: 234.1) were high. Residents of the two slums are exposed to high levels of PM2.5 in their homes. We recommend interventions, especially those focusing on clean cookstoves and lighting fuels to mitigate indoor levels of fine particles.
| S-EPMC5606663 | biostudies-literature