Abstract
Abstract. Reactive oxygen species (ROS) carried or induced by particulate matter (PM) are suspected of inducing oxidative stress in vivo, leading to adverse health impacts such as respiratory or cardiovascular diseases. The oxidative potential (OP) of PM, displaying the ability of PM to oxidize the lung environment, is gaining strong interest in examining health risks associated with PM exposure. In this study, OP was measured by two different acellular assays (dithiothreitol, DTT, and ascorbic acid, AA) on PM10 filter samples from 15 yearly time series of filters collected at 14 different locations in France between 2013 and 2018, including urban, traffic and Alpine valley site typologies. A detailed chemical speciation was also performed on the same samples, allowing the source apportionment of PM using positive matrix factorization (PMF) for each series, for a total number of more than 1700 samples. This study then provides a large-scale synthesis of the source apportionment of OP using coupled PMF and multiple linear regression (MLR) models. The primary road traffic, biomass burning, dust, MSA-rich, and primary biogenic sources had distinct positive redox activity towards the OPDTT assay, whereas biomass burning and road traffic sources only display significant activity for the OPAA assay. The daily median source contribution to the total OPDTT highlighted the dominant influence of the primary road traffic source. Both the biomass burning and the road traffic sources contributed evenly to the observed OPAA. Therefore, it appears clear that residential wood burning and road traffic are the two main target sources to be prioritized in order to decrease significantly the OP in western Europe and, if the OP is a good proxy of human health impact, to lower the health risks from PM exposure.
Highlights
Air quality has become a major public health issue, being considered the fourth largest global cause of mortality, with 7 million premature deaths worldwide per year due to both indoor and outdoor exposure (World Health Organization, 2016)
Since there are more samples where positive matrix factorization (PMF) has been run compared to available oxidative potential (OP) measurements, the discussion hereafter on the source contributions to the OP takes into account the whole PMF analysis, including days when models were not trained but predicted by the above-mentioned approach
We summarize the main results acquired from the harmonized PMF approach conducted for the present paper, but we invite the reader to refer to the previous study (Weber et al, 2019) and to the website to have a more complete view of the results
Summary
Air quality has become a major public health issue, being considered the fourth largest global cause of mortality, with 7 million premature deaths worldwide per year due to both indoor and outdoor exposure (World Health Organization, 2016). Strong focus has been put worldwide on source-apportionment methods in order to better understand the processes leading to the airborne concentrations and the accumulation of PM in the atmosphere. This includes direct modeling approaches such as chemistry transport models (CTMs) using tagged species (Brandt et al, 2013; Kranenburg et al, 2013; Mircea et al, 2020; Wagstrom et al, 2008; Wang et al, 2009) or field studies coupled with receptor models (RMs) (Belis et al, 2020; Pernigotti et al, 2016; Simon et al, 2010), notably positive matrix factorization (PMF). The chemistry, size distribution or reactivity of PM widely vary from location to location and season to season, which induces large changes in the health impacts depending on all of these parameters (Kelly and Fussell, 2012)
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