Atmospheric Chemistry and Physics (Jun 2018)

Comparison between five acellular oxidative potential measurement assays performed with detailed chemistry on PM<sub>10</sub> samples from the city of Chamonix (France)

  • A. Calas,
  • G. Uzu,
  • F. J. Kelly,
  • S. Houdier,
  • J. M. F. Martins,
  • F. Thomas,
  • F. Molton,
  • A. Charron,
  • A. Charron,
  • C. Dunster,
  • A. Oliete,
  • V. Jacob,
  • J.-L. Besombes,
  • F. Chevrier,
  • F. Chevrier,
  • J.-L. Jaffrezo

DOI
https://doi.org/10.5194/acp-18-7863-2018
Journal volume & issue
Vol. 18
pp. 7863 – 7875

Abstract

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Many studies have demonstrated associations between exposure to ambient particulate matter (PM) and adverse health outcomes in humans that can be explained by PM capacity to induce oxidative stress in vivo. Thus, assays have been developed to quantify the oxidative potential (OP) of PM as a more refined exposure metric than PM mass alone. Only a small number of studies have compared different acellular OP measurements for a given set of ambient PM samples. Yet, fewer studies have compared different assays over a year-long period and with detailed chemical characterization of ambient PM. In this study, we report on seasonal variations of the dithiothreitol (DTT), ascorbic acid (AA), electron spin resonance (ESR) and the respiratory tract lining fluid (RTLF, composed of the reduced glutathione (GSH) and ascorbic acid (ASC)) assays over a 1-year period in which 100 samples were analyzed. A detailed PM10 characterization allowed univariate and multivariate regression analyses in order to obtain further insight into groups of chemical species that drive OP measurements. Our results show that most of the OP assays were strongly intercorrelated over the sampling year but also these correlations differed when considering specific sampling periods (cold vs. warm). All acellular assays are correlated with a significant number of chemical species when considering univariate correlations, especially for the DTT assay. Evidence is also presented of a seasonal contrast over the sampling period with significantly higher OP values during winter for the DTT, AA, GSH and ASC assays, which were assigned to biomass burning species by the multiple linear regression models. The ESR assay clearly differs from the other tests as it did not show seasonal dynamics and presented weaker correlations with other assays and chemical species.