One-year measurements of secondary organic aerosol (SOA) markers in the Paris region (France): Concentrations, gas/particle partitioning and SOA source apportionment

Lanzafame, Grazia Maria; Srivastava, Deepchandra; Favez, Olivier; Bandowe, Benjamin A. Musa; Shahpoury, Pourya; Lammel, Gerhard; Bonnaire, Nicolas; Alleman, L.; Couvidat, Florian; Bessagnet, Bertrand; Albinet, Alexandre

doi:10.1016/j.scitotenv.2020.143921

Cited by 25 publications

(45 citation statements)

References 149 publications

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“…chemical mass balance (CMB) and positive matrix factorization (PMF)) (Watson et al, 1990;Paatero, 1997;Paatero and Tapper, 1994), SOA-tracer method (Kleindienst et al, 2007) and radiocarbon ( 14 C) measurements (Szidat et al, 2009;Gelencsér et al, 2007). These methodologies have been successfully applied worldwide and, in general, good agreements have been reported when compared by twos directly (Song et al, 2006;Kim et al, 2004;Kleindienst et al, 2010;Pachon et al, 2010;Heo et al, 2013;Al-Naiema et al, 2018;Srivastava et al, 2018b;Bove et al, 2018;Bae et al, 2019;Antony Chen and Cao, 2018;Hettiyadura et al, 2018;Jiang et al, 2018;Keerthi et al, 2018;Matawle et al, 2018;Shi et al, 2018;Shirmohammadi et al, 2016;Lanzafame et al, 2020). However, large discrepancies have been also observed when apportioning the SOA fraction, depending on the methods compared, the period of the year considered or atmospheric conditions observed (Srivastava et al, 2018b).…”

Section: Introductionmentioning

confidence: 99%

Comparison of five methodologies to apportion organic aerosol sources during a PM pollution event

Srivastava

Daellenbach

Zhang

et al. 2021

Science of The Total Environment

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This study presents a comparison of five methodologies to apportion primary (POA) and secondary organic aerosol (SOA) sources from measurements performed in the Paris region (France) during a highly processed PM pollution event. POA fractions, estimated from EC-tracer method and positive matrix factorization (PMF) analyses, conducted on measurements from PM10 filters, aerosol chemical speciation monitor (ACSM) and offline aerosol mass spectrometry (AMS), were all comparable (2.2 -3.7 µg m -3 as primary organic carbon (POC)). Associated relative uncertainties (measurement + model) on POC estimations ranged from 8 to 50%. The best apportionment of primary traffic OA was achieved using key markers (EC and 1-nitropyrene) in the chemical speciation-based PMF showing more pronounced rush-hour peaks and greater correlation with NOx than other traffic related POC factors. All biomass burning-related factors were in good agreement, with a typical diel profile and a night-time increase linked to residential heating. If PMF applied to ACSM data showed good agreement with other PMF outputs corrected from dust-related factors (coarse PM), discrepancies were observed between individual POA factors (traffic, biomass burning) and directly comparable SOA factors and highly oxidized OA.Similar secondary organic carbon (SOC) concentrations (3.3 ± 0.1 µg m -3 ) were obtained from all approaches, except the SOA-tracer method (1.8 µg m -3 ). Associated uncertainties ranged from 14 to 52% with larger uncertainties obtained for PMF-chemical data, EC-and SOA-tracer methods. This latter significantly underestimated total SOA loadings, even including biomass burning SOA, due to missing SOA classes and precursors. None of the approaches was able to identify the formation mechanisms and/or precursors responsible for the highly oxidized SOA fraction associated with nitrate-and/or sulfate-rich aerosols (35% of OA). We recommend the use of a 3 combination of different methodologies to apportion the POC/SOC concentrations/contributions to get the highest level of confidence in the estimates obtained.

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Section: Introductionmentioning

confidence: 99%

Comparison of five methodologies to apportion organic aerosol sources during a PM pollution event

Srivastava

Daellenbach

Zhang

et al. 2021

Science of The Total Environment

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“…Further, the chemical profile is also quite variable. Indeed, this PMF factor is not well described in the literature, and few studies reported it so far (Srivastava et al, 2019;Lanzafame et al, 2020;Borlaza et al, 2020). As a result, we do not know for instance the loading of HULIS, quinone or isoprene-derived-compounds contained in this factor, nor the amount of ageing it presents at each site.…”

Section: Secondary Organics Aerosolsmentioning

confidence: 92%

Source apportionment of atmospheric PM<sub>10</sub> Oxidative Potential: synthesis of 15 year-round urban datasets in France

Weber¹,

Uzu²,

Favez³

et al. 2021

Preprint

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Abstract. Reactive oxygen species (ROS) carried or induced by particulate matter (PM) are suspected to induce oxidative stress in vivo, leading to adverse health impacts, such as respiratory or cardiovascular diseases. The oxidative potential (OP) of PM, displaying the ability of PM to oxidize the lung environment, is gaining a strong interest to examine health risks associated to PM exposure. In this study, OP was measured by two different acellular assays (dithiothreitol, DTT and ascorbic acid, AA) on PM10 filter samples from 15 yearly time series of filters collected at 14 different locations in France between 2013 and 2018, including urban, traffic and Alpine valley site typologies. A detailed chemical speciation was also performed on the same samples allowing the source-apportionment of PM using positive matrix factorization (PMF) for each series, for a total number of more than 1700 samples. This study provides then a large-scale synthesis on the source-apportionment of OP using coupled PMF and multiple linear regression (MLR) models. The primary road traffic, biomass burning, dust, MSA-rich, and primary biogenic sources had distinct positive redox-activity towards the OPDTT assay, whereas biomass burning and road traffic sources only display significant activity for the OPAA assay. The daily median source contribution to the total OPDTT highlighted the dominant influence of the primary road traffic source. Both the biomass burning and the road traffic sources contributed evenly to the observed OPAA. Therefore, it appears clearly that residential wood burning and road traffic are the two main target sources to prioritized in order to decrease significantly the OP in Western Europe and, would the OP being a good proxy of human health impact, to lower the health risks from PM exposure.

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“…Recently, some of these SOA markers could be monitored offline at a couple of sites within the CARA program (i.e., Grenoble and SIRTA). Their use in PMF analysis allowed the deconvolution and apportionment of different SOA sources not commonly resolved in the literature, highlighting substantial contributions of specific biogenic and anthropogenic SOA factors [18], [20], [21], [117]. More precisely, a peculiar secondary anthropogenic fraction could be evidenced in Grenoble, possibly related with Fenton-like chemistry and self-amplification cycle of SOA formation during wintertime PM pollution episodes [18].…”

Section: Secondary Organic Aerosols (Soa)mentioning

confidence: 99%

“…At SIRTA, various anthropogenic SOA fractions could be linked to different secondary oxidation processes involving the following precursors: toluene and naphthalene, phenolic compounds, and PAHs (notably leading to the formation of DHOPA and phthalic acid, methylnitrocatechols and oxy/nitro-PAHs, respectively). These precursors are assumed to be mainly emitted by biomass burning and vehicular exhaust, and the sum of corresponding SOA loadings might represent up to 40% of daily PM10 concentrations in Greater Paris during the winter season [21], [117].…”

Section: Secondary Organic Aerosols (Soa)mentioning

confidence: 99%

“…This could be done for the SIRTA dataset using another type of source apportionment method, i.e. the so-called SOA-tracer method [115], which, in return, still needs fine optimizations to better account for anthropogenic SOA [117], [118]. Further efforts are then required to refine the source apportionment of the various SOA fractions, along with other PM contributors, using receptor models.…”

Section: Secondary Organic Aerosols (Soa)mentioning

confidence: 99%

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

Favez¹,

Weber²,

Petit³

et al. 2021

Preprint

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The CARA program has been developed since 2008 by the French reference laboratory for air quality monitoring (LCSQA) and the regional monitoring networks to gain a better knowledge at the national level on the particulate matter (PM) chemistry and its diverse origins in urban environments. It results of strong collaborations with international-level academic partners, allowing to bring state-of-the-art, straightforward and robust results and methodologies within operational air quality stakeholders (and subsequently, decision makers). Here, we illustrate some of the main outputs obtained over the last decade thanks to this program, regarding methodological aspects (both in terms of measurement techniques and data treatment procedures) as well as acquired knowledge on the predominant PM sources. Offline and online methods are used following well-suited quality assurance and quality control procedures, notably including inter-laboratory comparison exercises. Source apportionment studies are conducted using various receptor modeling approaches. Overall, the results presented herewith underline the major influences of residential wood burning (during the cold period) and road transport emissions (exhaust and non-exhaust ones, all along the year), as well as substantial contributions of mineral dust and primary biogenic particles (mostly during the warm period). Long-range transport phenomena, e.g., advection of secondary inorganic aerosols from the European continental sector and of Saharan dust into the French West Indies, are also discussed in this paper. Finally, we briefly address the use of stable isotope measurements (δ15N) and of various organic molecular markers for a better understanding of the origins of ammonium and of the different organic aerosol fractions, respectively.

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One-year measurements of secondary organic aerosol (SOA) markers in the Paris region (France): Concentrations, gas/particle partitioning and SOA source apportionment

Cited by 25 publications

References 149 publications

Comparison of five methodologies to apportion organic aerosol sources during a PM pollution event

Comparison of five methodologies to apportion organic aerosol sources during a PM pollution event

Source apportionment of atmospheric PM<sub>10</sub> Oxidative Potential: synthesis of 15 year-round urban datasets in France

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

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One-year measurements of secondary organic aerosol (SOA) markers in the Paris region (France): Concentrations, gas/particle partitioning and SOA source apportionment

Cited by 25 publications

References 149 publications

Comparison of five methodologies to apportion organic aerosol sources during a PM pollution event

Comparison of five methodologies to apportion organic aerosol sources during a PM pollution event

Source apportionment of atmospheric PM&lt;sub&gt;10&lt;/sub&gt; Oxidative Potential: synthesis of 15 year-round urban datasets in France

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

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Source apportionment of atmospheric PM<sub>10</sub> Oxidative Potential: synthesis of 15 year-round urban datasets in France