Comparison of PM10 Sources Profiles at 15 French Sites Using a Harmonized Constrained Positive Matrix Factorization Approach

Abstract

Receptor-oriented models, including positive matrix factorization (PMF) analyses, are now commonly used to elaborate and/or evaluate action plans to improve air quality. In this context, the SOURCES project has been set-up to gather and investigate in a harmonized way 15 datasets of chemical compounds from PM10 collected for PMF studies during a five-year period (2012–2016) in France. The present paper aims at giving an overview of the results obtained within this project, notably illustrating the behavior of key primary sources as well as focusing on their statistical robustness and representativeness. Overall, wood burning for residential heating as well as road transport were confirmed to be the two main primary sources strongly influencing PM10 loadings across the country. While wood burning profiles, as well as those dominated by secondary inorganic aerosols, present a rather good homogeneity among the sites investigated, some significant variabilities were observed for primary traffic factors, illustrating the need to better characterize the diversity of the various vehicle exhaust and non-exhaust emissions. Finally, natural sources, such as sea salts (widely observed in internal mixing with anthropogenic compounds), primary biogenic aerosols and/or terrigenous particles, were also found as non-negligible PM10 components at every investigated site.

Sources and Geographical Origins of PM10 in Metz (France) Using Oxalate as a Marker of Secondary Organic Aerosols by Positive Matrix Factorization Analysis

“…Although Mg/Na ratio of 0.11 is very close to the expected value from the composition of sea water (0.12; [37]), the observed Cl/Na ratio of 0.63 ± 0.17 contrasts with the expected value of 1.8 for fresh sea salt. This depletion of chloride, which has been clearly highlighted in Northern France by [17,38], could reflect the distance to the coast, conferring to this factor a secondary feature mainly resulting from acid-base interactions with anthropogenic pollutants, such as nitric and sulfuric acid. High SO 4 /Na and NO 3 /Na ratios respectively of 0.36 ± 0.09 (0.06 in seawater) and 0.65 ± 0.53 clearly support this assumption.…”

“…Missing concentrations were replaced with the median value, and their corresponding uncertainties calculated with the geometric mean, multiplied by 4. The authors of Reference [17] have determined optimized a j values depending on the analytical procedure for each compound, and these are summarized in Table 1. The same values were applied because the same analytical procedures were used.…”

“…were set to 1.2 and 5, respectively [17,31]. These ratios may differ, sometimes significantly, from one site to another and also depending on the type of wood burnt, but Metz is relatively close to the areas of study of References [16,30].…”

“…Although France is the second most populated country in Europe and regularly exposed to persistent pollution episodes, source apportionment studies were still scarce until recently. Nevertheless, a harmonized receptor model program conducted at the national level (so-called SOURCES project) provided a first glimpse of the spatial distribution of PM 10 sources in different French urban areas, based on 15 chemically-resolved datasets obtained in the last six years [17]. Primary anthropogenic sources such as traffic and wood-burning were commonly identified, respectively contributing to 15 and 16% of PM 10 on average, with a significant spatial variability.…”

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

“…Primary biogenic organic aerosols (PBOAs), which notably comprise bacterial and fungal cells or spores, viruses, or microbial fragments such as endotoxins and mycotoxins as well as pollens and plant debris, are ubiquitous particles released from the biosphere to the atmosphere Fang et al, 2018;Martin et al, 2010;Perrino and Marcovecchio, 2016;Wéry et al, 2017). PBOA can contribute significantly to the total coarse aerosol mass Bozzetti et al, 2016;Coz et al, 2010;Jaenicke, 2005;Manninen et al, 2014;Morris et al, 2011;Samaké et al, 2019;Vlachou et al, 2018;Yue et al, 2017).…”