Characterization and comparison of PM<sub>2.5</sub> oxidative potential assessed by two acellular assays
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Published:2020-05-04
Issue:9
Volume:20
Page:5197-5210
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ISSN:1680-7324
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Container-title:Atmospheric Chemistry and Physics
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language:en
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Short-container-title:Atmos. Chem. Phys.
Author:
Gao Dong, Godri Pollitt Krystal J., Mulholland James A., Russell Armistead G.ORCID, Weber Rodney J.ORCID
Abstract
Abstract. The capability of ambient particles to generate in vivo reactive
oxygen species (ROS), called oxidative potential (OP), is a potential metric
for evaluating the health effects of particulate matter (PM) and is
supported by several recent epidemiological investigations. Studies using
various types of OP assays differ in their sensitivities to varying PM
chemical components. In this study, we systematically compared two
health-relevant acellular OP assays that track the depletion of antioxidants
or reductant surrogates: (i) the synthetic respiratory-tract lining fluid (RTLF)
assay that tracks the depletion of ascorbic acid (AA) and glutathione (GSH)
and (ii) the dithiothreitol (DTT) assay that tracks the depletion of DTT.
Yearlong daily samples were collected at an urban site in Atlanta, GA
(Jefferson Street), during 2017, and both DTT and RTLF assays were performed
to measure the OP of water-soluble PM2.5 components. PM2.5 mass
and major chemical components, including metals, ions, and organic and
elemental carbon were also analyzed. Correlation analysis found that OP as
measured by the DTT and AA depletion (OPDTT and OPAA,
respectively) were correlated with both organics and some water-soluble
metal species, whereas that from the GSH depletion (OPGSH) was
exclusively sensitive to water-soluble Cu. These OP assays were moderately
correlated with each other due to the common contribution from metal ions.
OPDTT and OPAA were moderately correlated with PM2.5 mass
with Pearson's r=0.55 and 0.56, respectively, whereas OPGSH
exhibited a lower correlation (r=0.24). There was little seasonal
variation in the OP levels for all assays due to the weak seasonality of
OP-associated species. Multivariate linear regression models were developed
to predict OP measures from the particle composition data. Variability in
OPDTT and OPAA were not only attributed to the concentrations of
metal ions (mainly Fe and Cu) and organic compounds but also to antagonistic
metal–organic and metal–metal interactions. OPGSH was sensitive to
the change in water-soluble Cu and brown carbon (BrC), a proxy for ambient
humic-like substances.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
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