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1.
Nat Commun ; 15(1): 5263, 2024 Jun 19.
Article in English | MEDLINE | ID: mdl-38898130

ABSTRACT

Most fine ambient particulate matter (PM2.5)-based epidemiological models use globalized concentration-response (CR) functions assuming that the toxicity of PM2.5 is solely mass-dependent without considering its chemical composition. Although oxidative potential (OP) has emerged as an alternate metric of PM2.5 toxicity, the association between PM2.5 mass and OP on a large spatial extent has not been investigated. In this study, we evaluate this relationship using 385 PM2.5 samples collected from 14 different sites across 4 different continents and using 5 different OP (and cytotoxicity) endpoints. Our results show that the relationship between PM2.5 mass vs. OP (and cytotoxicity) is largely non-linear due to significant differences in the intrinsic toxicity, resulting from a spatially heterogeneous chemical composition of PM2.5. These results emphasize the need to develop localized CR functions incorporating other measures of PM2.5 properties (e.g., OP) to better predict the PM2.5-attributed health burdens.


Subject(s)
Air Pollutants , Particulate Matter , Particulate Matter/toxicity , Humans , Air Pollutants/toxicity , Oxidation-Reduction , Particle Size , Environmental Monitoring/methods , Animals , Cell Survival/drug effects
2.
Environ Sci Technol ; 56(20): 14605-14616, 2022 10 18.
Article in English | MEDLINE | ID: mdl-36153963

ABSTRACT

We investigated the influence of biomass burning (BURN), Diwali fireworks, and fog events on the ambient fine particulate matter (PM2.5) oxidative potential (OP) during the postmonsoon (PMON) and winter season in Delhi, India. The real-time hourly averaged OP (based on a dithiothreitol assay) and PM2.5 chemical composition were measured intermittently from October 2019 to January 2020. The peak extrinsic OP (OPv: normalized by the volume of air) was observed during the winter fog (WFOG) (5.23 ± 4.6 nmol·min-1·m-3), whereas the intrinsic OP (OPm; normalized by the PM2.5 mass) was the highest during the Diwali firework-influenced period (29.4 ± 18.48 pmol·min-1·µg-1). Source apportionment analysis using positive matrix factorization revealed that traffic + resuspended dust-related emissions (39%) and secondary sulfate + oxidized organic aerosols (38%) were driving the OPv during the PMON period, whereas BURN aerosols dominated (37%) the OPv during the WFOG period. Firework-related emissions became a significant contributor (∼32%) to the OPv during the Diwali period (4 day period from October 26 to 29), and its contribution peaked (72%) on the night of Diwali. Discerning the influence of seasonal and episodic sources on health-relevant properties of PM2.5, such as OP, could help better understand the causal relationships between PM2.5 and health effects in India.


Subject(s)
Air Pollutants , Humans , Aerosols/analysis , Air Pollutants/analysis , Biomass , Dithiothreitol , Dust/analysis , Environmental Monitoring , India , Oxidative Stress , Particulate Matter/analysis , Seasons , Sulfates , Vehicle Emissions/analysis
3.
J Hazard Mater ; 425: 127777, 2022 03 05.
Article in English | MEDLINE | ID: mdl-34838366

ABSTRACT

We investigated the spatiotemporal distribution and sources of cellular oxidative potential (OP) in the Midwest US. Weekly samples were collected from three urban [Chicago (IL), Indianapolis (IN), and St. Louis (MO)], one rural [Bondville (IL], and one roadside site [Champaign (IL)] for a year (May 2018 to May 2019), and analyzed for water-soluble cellular OP using a macrophage reactive oxygen species (ROS) assay. Chemical composition of the samples including several carbonaceous components, inorganic ions, and water-soluble elementals, were also analyzed. The emission sources contributing to water-soluble cellular OP and PM2.5 mass were analyzed using positive matrix factorization. The secondary organic aerosols contributed substantially (≥54%) to PM2.5 cellular OP at urban sites, while the roadside and rural OP were dominated by road dust (54%) and agricultural activities (62%), respectively. However, none of these sources contributed substantially to the PM2.5 mass (≤21%). Other sources contributing significantly to the PM2.5 mass, i.e., secondary sulfate and nitrate, biomass burning and coal combustion (14-26%) contributed minimally to the cellular OP (≤13%). Such divergent profiles of the emission sources contributing to cellular OP vs. PM2.5 mass demonstrate the need of considering more health-relevant metrics such as OP in the design of air pollution control strategies.


Subject(s)
Air Pollutants , Particulate Matter , Aerosols/analysis , Air Pollutants/analysis , Environmental Monitoring , Midwestern United States , Oxidative Stress , Particulate Matter/analysis , Seasons , Vehicle Emissions/analysis , Water
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