Unravelling Source Contributions to Pm10 Oxidative Potential Through Comparison of Modelled and Experimental Source Apportionment Approaches

Abstract

Particulate matter (PM) is a major air pollutant linked to multiple adverse health effects, usually expressed by mass concentrations. The Oxidative Potential (OP), i.e., the ability of PM to induce oxidative stress based on its chemical composition is emerging as a potentially relevant health indicator. Source-specific, mass-normalized OP values have been obtained through measurement campaigns and the use of Positive Matrix Factorization (PMF). Chemical transport models (CTMs) aim to integrate these values to simulate source-specific OP exposure maps, advancing the understanding of the effect of OP on air pollution-related health impact. However, validation of this approach is needed, whereby matching between CTM and PMF sources is a crucial first step. This study matches the CTM LOTOS-EUROS sources against PMF profiles from PM10 observations at 15 locations in France between 2013-2016. A source- and species-dependent OP map was constructed with LOTOS-EUROS, based on the intrinsic OP derived from the PMF profiles. Comparing PM10 showed a satisfactory fit between LOTOS-EUROS and observations [r2 = 0.35 – 0.66]. Results from the source matching varied between station and source, with Biomass Burning [r2 = 0.34 – 0.75], SIA-rich [r2: 0.30 – 0.71], and Sea salt [r2: 0.18 – 0.71] showing promising fits for non-alpine stations, while other sources such as road-traffic [r2 range = 0.01 – 0.40] showed to be more challenging. This work shows the feasibility and complexity of integrating CTM and PMF frameworks for source-specific OP modelling. By identifying knowledge gaps and improving source allocated PM components, this study contributes to the developing field of OP modelling.

Keywords: Particulate matter, source attribution, Positive Matrix Factorization, Chemical transport model, Oxidative potential