@article{fdi:010073089,
  title = {{C}omparison between five acellular oxidative potential measurement assays performed with detailed chemistry on {PM}10 samples from the city of {C}hamonix ({F}rance)},
  author = {{C}alas, {A}. and {U}zu, {G}a{\¨e}lle and {K}elly, {F}. {J}. and {H}oudier, {S}. and {M}artins, {J}. {M}. {F}. and {T}homas, {F}. and {M}olton, {F}. and {C}harron, {A}. and {D}unster, {C}. and {O}liete, {A}. and {J}acob, {V}. and {B}esombes, {J}. {L}. and {C}hevrier, {F}. and {J}affrezo, {J}. {L}.},
  editor = {},
  language = {{ENG}},
  abstract = {{M}any 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. {T}hus, assays have been developed to quantify the oxidative potential ({OP}) of {PM} as a more refined exposure metric than {PM} mass alone. {O}nly a small number of studies have compared different acellular {OP} measurements for a given set of ambient {PM} samples. {Y}et, fewer studies have compared different assays over a year-long period and with detailed chemical characterization of ambient {PM}. {I}n 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 {PM}10 characterization allowed univariate and multivariate regression analyses in order to obtain further insight into groups of chemical species that drive {OP} measurements. {O}ur 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). {A}ll acellular assays are correlated with a significant number of chemical species when considering univariate correlations, especially for the {DTT} assay. {E}vidence 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. {T}he {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.},
  keywords = {{FRANCE} ; {CHAMONIX} ; {ALPES} ; {ARVE} {VALLEE}},
  booktitle = {},
  journal = {{A}tmospheric {C}hemistry and {P}hysics},
  volume = {18},
  numero = {11},
  pages = {7863--7875},
  ISSN = {1680-7316},
  year = {2018},
  DOI = {10.5194/acp-18-7863-2018},
  URL = {https://www.documentation.ird.fr/hor/fdi:010073089},
}