A phenomenology of submicron organic aerosol components in urban France based on long-term online observations and modeling.

This study presents the first nationwide phenomenological analysis of submicron organic aerosol (OA) sources in France, based on highly time‑resolved Aerosol Chemical Speciation Monitor (ACSM) measurements collected at 12 (sub)urban sites over one to seven years. A harmonized rolling Positive Matrix Factorization (PMF) approach was applied, ensuring consistent constraints and criteria across all datasets. The methodology enabled the identification of major OA sources, including primary OA (POA) factors such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), and cooking-like OA (COA), which together accounted for approximately 33 % of the OA mass. Secondary or aged OA was represented by oxygenated OA (OOA), which dominated OA at all sites and was further separated into Less Oxidized (LO-OOA) and More Oxidized OOA (MO-OOA), except for Poitiers and Strasbourg. Additional site-specific OA factors were also resolved, including a mixed shipping/industrial OA factor in Marseille Longchamp and an amine-related OA factor in Strasbourg and Creil. Strong seasonality was observed for POA, particularly BBOA, which increased substantially during winter due to residential heating. LO-OOA correlated with BBOA in winter, highlighting the important contribution of biomass combustion to wintertime air quality degradation across France, while summer LO-OOA was mainly associated with biogenic precursors. Comparison with the CHIMERE chemical transport model revealed systematic biases in simulated OA components, underscoring the value of this unique long-term dataset for improving OA representation. These findings are highly relevant for various applications, including epidemiological studies, -in which source-specific exposure indicators can reveal stronger links to health effects-, and near-real-time source apportionment, -by using these identified profiles to constrain the factors in real-time analysis- facilitating the rapid identification of pollution episodes and enable the implementation of air quality management measures. They also offer observational insights for improving air quality, providing valuable information to policymakers for proposing effective mitigation strategies.