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    Glojek, K.; Dinh Ngoc Thuy, V.; Weber, S.; Uzu, G.; Manousakas, M.; Elazzouzi, R.; Džepina, K.; Darfeuil, S.; Ginot, P.; Jaffrezo, J.L.; Žabkar, R.; Turšič, J.; Podkoritnik, A.; Močnik, G.

    Environment international, July 2024, 2024-07-00, 20240701, 2024-07-01, Volume: 189
    Journal Article

    Average daily contributions (90% CI black bar) to PM10 in relative (%, left pie charts), OPAA and OPDTT per source’s mass in absolute (OPm in nmol/min m−3, middle bar plot) and OPAA and OPDTT per volume in relative (OPv in %, right bar plot) values grouped according to sources common activities. Arrows indicate (additional) associations between the sources. Display omitted •Concentrations of PM10 at the site are comparable to other Alpine valleys, however, OP levels are higher compared to European sites.•Extensive tests with PMF were performed including organic tracers.•The most important sources of PM10, OP per µg of source as well as OP per m3 at the site are biomass burning and activities related to cement production.•Sources with important contributions to PM10 do not necessarily have high OP.•An unusual chloride-rich source was identified with high OP per µg of source. Toxicity of particulate matter (PM) depends on its sources, size and composition. We identified PM10 sources and determined their contribution to oxidative potential (OP) as a health proxy for PM exposure in an Alpine valley influenced by cement industry. PM10 filter sample chemical analysis and equivalent black carbon (eBC) were measured at an urban background site from November 2020 to November 2021. Using an optimized Positive Matrix Factorization (PMF) model, the source chemical fingerprints and contributions to PM10 were determined. The OP assessed through two assays, ascorbic acid (AA) and dithiothreitol (DTT), was attributed to the PM sources from the PMF model with a multiple linear regression (MLR) model. Ten factors were found at the site, including biomass burning (34, 40 and 38% contribution to annual PM10, OPAA and OPDDT, respectively), traffic (14, 19 and 7%), nitrate- and sulphate-rich (together: 16, 5 and 8%), aged sea salt (2, 2 and 0%) and mineral dust (10, 12 and 17%). The introduction of innovative organic tracers allowed the quantification of the PM primary and secondary biogenic fractions (together: 13, 8 and 21%). In addition, two unusual factors due to local features, a chloride-rich factor and a second mineral dust-rich factor (named the cement dust factor) were found, contributing together 10, 14 and 8%. We associate these two factors to different processes in the cement plant. Despite their rather low contribution to PM10 mass, these sources have one of the highest OPs per µg of source. The results of the study provide vital information about the influence of particular sources on PM10 and OP in complex environments and are thus useful for PM control strategies and actions.