An apportionment method for the oxidative potential of atmospheric particulate matter sources: application to a one-year study in Chamonix, France

Abstract

Abstract. Inhaled aerosolized particulate matter (PM) induces cellular oxidative stress in vivo, leading to adverse health outcomes. The oxidative potential (OP) of PM appears to be a more relevant proxy of the health impact of the aerosol rather than the total mass concentration. However, the relative contributions of the aerosol sources to the OP are still poorly known. In order to better quantify the impact of different PM sources, we sampled aerosols in a French city for one year (2014, 115 samples). A coupled analysis with detailed chemical speciation (more than 100 species, including organic and carbonaceous compounds, ions, metals and aethalometer measurements) and two OP assays (ascorbic acid, AA, and dithiothreitiol, DTT) in a simulated lung fluid (SLF) were performed in these samples. We present in this study a statistical framework using a coupled approach with positive matrix factorization (PMF) and multiple linear regression to attribute a redox-activity to PM sources. Our results highlight the importance of the biomass burning and vehicular sources to explain the observed OP for both assays. In general, we see a different contribution of the sources when considering the OP AA, OP DTT or the mass of the PM10. Moreover, significant differences are observed between the DTT and AA tests which emphasized chemical specificities of the two tests and the need of a standardized approach for the future studies on epidemiology or toxicology of the PM.

Seasonal Variations and Chemical Predictors of Oxidative Potential (OP) of Particulate Matter (PM), for Seven Urban French Sites

“…Overall, high OP v levels during cold period in European cities can be attributed to the common increase in PM concentrations due to additional emission sources and lower mixing rate in the cold period. Biomass burning contributes up to 70% of the PM mass in winter in alpine valleys [42,43,59] and is also likely to induce higher OP level through the chemical composition of the primary emissions and the biomass emissions ageing processes. Indeed, primary biomass emissions emit large quantity of PAHs that will lead to the formation of oxy-PAHs (and notably quinones) and nitro-PAHs, through homogeneous and heterogeneous oxidation reactions in the atmosphere [44,[60][61][62], which are redox active species and of importance in oxidative potential contribution [22,24,63].…”

“…This is probably one of the main limitations of this study but the analysis of all these chemical species, and especially SOA markers and PAH derivatives, would be very time consuming and expensive and cannot be achieved on a such number of samples. Alternatively, the deconvolution of OP according to PM sources is probably more promising than simply connecting OP and ambient air concentrations of few chemical species [14,17,59,88]. Finally, note that, as all OP assays were obtained from PM 10 samples, results cannot be extrapolated to other PM size fractions.…”

Arabitol, mannitol, and glucose as tracers of primary biogenic organic aerosol: the influence of environmental factors on ambient air concentrations and spatial distribution over France

“…Indeed, atmospheric organic aerosols (OAs) contain specific chemical species that can be used as reliable biomarkers in tracing the sources and abundance of PBOA (Bauer et al, 2008;Gosselin et al, 2016;Holden et al, 2011;Jia et al, 2010;Li et al, 2018;Medeiros et al, 2006b;Wang et al, 2018). For instance, among sugar alcohols, arabitol and mannitol (two common storage soluble carbohydrates in fungi) have been recognized as tracers for airborne fungi, and their concentrations are widely used to estimate PBOA contributions to OA mass Bauer et al, 2008;Buiarelli et al, 2013;Golly et al, 2018;Medeiros et al, 2006b;Samaké et al, 2019;Srivastava et al, 2018;Verma et al, 2018;Weber et al, 2018Weber et al, , 2019. Similarly, glucose has also been used as a tracer for plant materials (such as pollen, leaves, and their fragments) or soil emissions within various studies around the world (Chen et al, 2013;Medeiros et al, 2006b;Pietrogrande et al, 2014;Rathnayake et al, 2017;Rogge et al, 2007;Wan et al, 2019;Xiao et al, 2018;Zhu et al, 2015).…”

Answer to referee #1

“…3d), associated with long-range aerosol transport (Abdalmogith and Harrison, 2005;Amato et al, 2016;Coulibaly et al, 2015;Pindado and Perez, 2011;Waked et al, 2014), and levoglucosan ( Fig. 3e), associated with biomass burning (Weber et al, 2019;Xiao et al, 2018), display stronger positive correlations (R > 0.72-0.98, p < 0.01) at all pairs of sites considered in the present work. The concentrations of levoglucosan and those of SC clearly display very different annual atmospheric evolution cycles: i.e., higher concentrations of levoglucosan in France are observed in the coldest season (winter) due to the increased biomass burning, while those of SC are observed in warm seasons and coinciding with negligible ambient concentrations of levoglucosan (Fig.…”

“…Indeed, atmospheric organic aerosols (OAs) contain specific chemical species that can be used as reliable biomarkers in tracing the sources and abundance of PBOA (Bauer et al, 2008;Gosselin et al, 2016;Holden et al, 2011;Jia et al, 2010;Li et al, 2018;Medeiros et al, 2006b;Wang et al, 2018). For instance, among sugar alcohols, arabitol and mannitol (two common storage soluble carbohydrates in fungi) have been recognized as tracers for airborne fungi, and their concentrations are widely used to estimate PBOA contributions to OA mass (Amato et al, 2017;Bauer et al, 2008;Buiarelli et al, 2013;Golly et al, 2018;Medeiros et al, 2006b;Samaké et al, 2019;Srivastava et al, 2018;Verma et al, 2018;Weber et al, 2018Weber et al, , 2019. Similarly, glucose has also been used as a tracer for plant materials (such as pollen, leaves, and their fragments) or soil emissions within various studies around the world (Chen et al, 2013;Medeiros et al, 2006b;Pietrogrande et al, 2014;Rathnayake et al, 2017;Rogge et al, 2007;Wan et al, 2019;Xiao et al, 2018;Zhu et al, 2015).…”