Gao, Dong: Oxidative potential and PM2.5 species data for SEARCH site Jefferson Street, 2017 [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.908043 (dataset in review),

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Supplement to: Gao, Dong; Pollitt, Krystal J; Mulholland, James A; Russell, Armistead G; Weber, Rodney J (in review): Characterization and comparison of PM2.5 oxidative potential assessed by two acellular assays. Atmospheric Chemistry and Physics Discussions, https://doi.org/10.5194/acp-2019-941

The capability of ambient particles to generate in vivo reactive oxygen species (ROS), called the oxidative potential (OP), is a potential metric for relating particulate matter (PM) to health effects and is supported by several recent epidemiological investigations. However, 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: the synthetic respiratory tract lining fluid (RTLF) assay that tracks the depletion of ascorbic acid (AA) and glutathione (GSH), and the dithiothreitol (DTT) assay that tracks the depletion of DTT. Year-long daily samples were collected at an urban site (Jefferson Street) in Atlanta during 2017 and both DTT and RTLF assays were applied 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 had a significantly 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. The models indicated that the variabilities in OPDTT and OPAA were attributed to not only the concentrations of metal ions (mainly Fe and Cu) and organic compounds, but also 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.