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

Abstract

An original source apportionment study was conducted on atmospheric particles (PM10) collected in Metz, one of the largest cities of Eastern France. A Positive matrix factorization (PMF) analysis was applied to a sampling filter-based chemical dataset obtained for the April 2015 to January 2017 period. Nine factors were clearly identified, showing mainly contributions from anthropogenic sources of primary PM (19.2% and 16.1% for traffic and biomass burning, respectively) as well as secondary aerosols (12.3%, 14.5%, 21.8% for sulfate-, nitrate-, and oxalate-rich factors, respectively). Wood-burning aerosols exhibited strong temporal variations and contributed up to 30% of the PM mass fraction during winter, while primary traffic concentrations remained relatively constant throughout the year. These two sources are also the main contributors during observed PM10 pollution episodes. Furthermore, the dominance of the oxalate-rich factor among other secondary aerosol factors underlines the role of atmospheric processing to secondary organic aerosol loadings which are still poorly characterized in this region. Finally, Concentration-Weighted Trajectory (CWT) analysis were performed to investigate the geographical origins of the apportioned sources, notably illustrating a significant transport of both nitrate-rich and sulfate-rich factors from Northeastern Europe but also from the Balkan region.

Disparities in particulate matter (PM<sub>10</sub>) origins and oxidative potential at a city-scale (Grenoble, France) – Part I: Source apportionment at three neighbouring sites

“…It is, therefore, not surprising that part of the matter in the sulfate-rich source was re-assigned to different other sources upon addition of the organic tracers in the "orga" PMF run. A comparable study in Metz (France) also used another organic tracer (oxalate) to apportion a secondary organic aerosol (SOA) source from PM, ascribing it possibly to both biogenic and anthropogenic emissions (Petit et al, 2019). We also observed an increase in the contributions of the MSA-rich factor at the three sites, with an increase in contributions from specific inorganic species, such as SO4 2and NH4 + (see Figure S3.8.1 in the SI).…”

“…rpolyols=0.87 to rprimary biogenic=0.82). This may suggest a secondary process or a combination of several different primary processes in the primary biogenic factor affecting the sites at different rates (Petit et al, 2019;Samaké et al, 2019). We also clearly see a stronger similarity between the two urban sites (LF and CB) compared to the peri urban one, notably for the primary traffic, mineral dust, and, to a lower extent, the industrial factor.…”

Overview of the French Operational Network for In Situ Observation of PM Chemical Composition and Sources in Urban Environments (CARA Program)

“…where X corresponds to the input data matrix, F represents a matrix whose vectors stand for the profiles of a p number of factors (that might eventually be attributed to specific emission sources or secondary aerosol types), G corresponds to the contributions of the p sources to total PM, and E represents the residual matrix. Detailed and practical descriptions of the way PMF has been used in the frame of the CARA program, and this program participate in the development of receptor models, can be found elsewhere [18], [36], [41]- [43]. All the PMF results presented in this paper were obtained using the most recent US EPA PMF v5.0 software and following recommendations of the EU guidance document [44].…”

“…These fractions can then be used to estimate PM loadings that may be attributable to both sources (i.e., PMff and PMwb, respectively), using conversion factors such as: PMff = a x eBCff and PMwb = b x eBCwb, where a and b can be retrieved from the literature and/or further site-specific a priori knowledge. In practice, a is considered here as constant over the metropolitan territory (with a = 2, roughly corresponding to OC/EC ratio of 0.5-0.6 and hydrocarbon-like organic aerosol O-to-C ratio of 1.2-1.4 within vehicular exhaust, [52], [53]) whereas fit-for-purpose b values have been determined at each site through comparisons with independent offline filter-based source apportionment analyses [41], [54]. For stations where no independent source apportionment study allowed to determine a site-specific b value, the LCSQA currently recommends to AASQAs estimating wintertime PMwb from AE33-based brown carbon measurement and using a constant conversion factor, as explained in [55] and [56].…”

Personal Exposure Levels to O3, NOx, PM10 and the Association to Ambient Levels in two Swedish Cities

“…Particles with an aerodynamic diameter smaller than 10 µm, PM 10 , mainly deposit in central airways but a small fraction will also reach the small airways (inner diameter < 2 mm), whereas ne particles smaller than 2,5 µm (PM 2,5 ) reach further into the very peripheral airways and to a larger extent deposit in the transition zone, between conducting and acinar airways (Pinkerton KE 2000). The most prominent sources of PM 10 are local emission related to tra c (Segersson et al 2017), but PM 10 levels are also in uenced by long-range transport, which may account for up to 70% of the background levels in urban areas (Petit et al 2019;Carlsen et al 2020).…”