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Speciation of organic fractions does matter for aerosol source apportionment. Part 2: Intensive short-term campaign in the Paris area (France)
Abstract
The present study aimed at performing PM10source apportionment, using positive matrix factorization (PMF), based on filter samples collected every 4h at a sub-urban station in the Paris region (France) during a PM pollution event in March 2015 (PM10>50μgm-3for several consecutive days). The PMF model allowed to deconvolve 11 source factors. The use of specific primary and secondary organic molecular markers favoured the determination of common sources such as biomass burning and primary traffic emissions, as well as 2 specific biogenic SOA (marine+isoprene) and 3 anthropogenic SOA (nitro-PAHs+oxy-PAHs+phenolic compounds oxidation) factors. This study is probably the first one to report the use of methylnitrocatechol isomers as well as 1-nitropyrene to apportion secondary OA linked to biomass burning emissions and primary traffic emissions, respectively. Secondary organic carbon (SOC) fractions were found to account for 47% of the total OC. The use of organic molecular markers allowed the identification of 41% of the total SOC composed of anthropogenic SOA (namely, oxy-PAHs, nitro-PAHs and phenolic compounds oxidation, representing 15%, 9%, 11% of the total OC, respectively) and biogenic SOA (marine+isoprene) (6% in total). Results obtained also showed that 35% of the total SOC originated from anthropogenic sources and especially PAH SOA (oxy-PAHs+nitro-PAHs), accounting for 24% of the total SOC, highlighting its significant contribution in urban influenced environments. Anthropogenic SOA related to nitro-PAHs and phenolic compounds exhibited a clear diurnal pattern with high concentrations during the night indicating the prominent role of night-time chemistry but with different chemical processes involved.
Supplementary resource (1)
... Although emissions play an important role for PM concentrations in the atmosphere, meteorological conditions related to large-scale circulation patterns as well as local-scale boundary layer processes and interactions with the land surface are major drivers of PM variability as well (Cermak and Knutti, 2009;Bressi et al., 2013;Megaritis et al., 2014;Dupont et al., 2016;Petäjä et al., 2016;Yang et al., 2016;Li et al., 2017). Wind speed and direction generally have a strong influence on air quality as they determine the advection of pollutants (Petetin et al., 2014;Petit et al., 2015;Srivastava et al., 2018). Limiting the vertical exchange of air masses, the mixed layer height (MLH) governs the volume of air in which particles are typically dispersed. ...
... The metropolitan area of Paris is one of the most densely populated and industrialized areas in Europe. Thus, air quality is a recurring issue and has been at the focus of many studies in recent years Petetin et al., 2014;Petit et al., 2015Petit et al., , 2017Dupont et al., 2016;Srivastava et al., 2018). Results indicate that the Paris metropolitan region is often affected by mid-range to long-range transport of pollutants, as due to the city's flat orography, an efficient horizontal exchange of air masses is frequent (Bressi et al., 2013;Petit et al., 2015). ...
... Often, these episodes are characterized by stagnant atmospheric conditions and a combination of local contributions, e.g. traffic emissions, residential emissions, or regionally transported particles, such as ammonium nitrates from manure spreading or sulfates from point sources (Petetin et al., 2014;Petit et al., 2014Petit et al., , 2015Srivastava et al., 2018). High-pressure conditions with air masses originating from continental Europe (Belgium, Netherlands, western Germany) are generally associated with an increase in particle concentrations, especially of secondary inorganic aerosols (SIAs, Bressi et al., 2013;Srivastava et al., 2018). ...
... SOA results from the condensation and coagulation of (photo-)oxidized volatile and/or semi-44 volatile organic compounds (VOCs and SVOCs) Hallquist et al., 2009;45 Kroll and Seinfeld, 2008; and accounts for a major fraction of 46 OA (up to 90%) (Srivastava et al., 2018b; making its 47 characterization and apportionment essential in terms of air quality or climate impacts. 48 ...
... Different methodologies have been developed and reported to investigate OA sources 51 (Srivastava et al., 2018b). A detailed chemical characterization of OA at a molecular level can 52 provide insights into the OA sources as several organic compounds have been identified and 53 recognized as tracers (or markers) of specific sources or chemical (trans-)formation processes 54 (Srivastava et al., , 2018a(Srivastava et al., , 2018b(Srivastava et al., , 2018c. ...
... Different methodologies have been developed and reported to investigate OA sources 51 (Srivastava et al., 2018b). A detailed chemical characterization of OA at a molecular level can 52 provide insights into the OA sources as several organic compounds have been identified and 53 recognized as tracers (or markers) of specific sources or chemical (trans-)formation processes 54 (Srivastava et al., , 2018a(Srivastava et al., , 2018b(Srivastava et al., , 2018c. For instance, for 55 primary sources, levoglucosan is commonly used to trace biomass burning emissions, polyols 56 ...
Organic aerosols (OA) account for a large fraction of ambient air particulate matter and have strong impacts on air quality and climate. As their sources and atmospheric formation processes, notably for secondary OA (SOA), are still not fully understood, their concentrations are often underestimated by air quality models. This work aimed at improving OA modelling by implementing specific organic molecular marker emissions and formation processes into the chemistry-transport model CHIMERE. It was based on the comparison of model outputs with measurements from field studies performed in the Paris region (suburban site of SIRTA, 25 km SW of Paris) over 2015 and 10 French urban locations in winter 2014-2015. 25 biogenic and anthropogenic SOA markers have been quantified in both, particulate and gas phases and the formation pathways of 10 have been developed and simulated using CHIMERE. The evolution of levoglucosan concentrations (biomass burning marker) has been also modeled. The results obtained showed that sources and precursor emissions (missing or underestimated), radical concentrations (NO, HO2 and RO2) and the lack of formation pathways, are key parameters for the simulation of SOA markers. Gas/particle partitioning seemed poorly linked to the T°C while the inclusion of hydrophilic non-ideal partitioning, usually neglected, seemed essential. Levoglucosan was well simulated, even if some underestimations existed in some regions. A significant theoretical gaseous fraction was also highlighted. The model/measurements comparison of molecular markers is a powerful tool to evaluate precursor emissions, physicochemical processes and in the end, to estimate OA sources.
... Although emissions play an important role for PM concentrations in the atmosphere, meteorological conditions related to large-scale circulation patterns as well as local-scale boundary layer processes and interactions with the land surface are major drivers of PM variability as well (Cermak and Knutti, 2009;Bressi et al., 2013;Megaritis et al., 2014;Dupont et al., 2016;Petäjä et al., 2016;Yang et al., 2016;Li et al., 2017). Wind speed and direction generally have a strong influence on air quality as they determine the advection of pollutants (Petetin et al., 2014;Petit et al., 2015;Srivastava et al., 2018). Limiting the vertical exchange of air masses, the mixed layer height (MLH) governs the volume of air in which particles are typically dispersed. ...
... The metropolitan area of Paris is one of the most densely populated and industrialized areas in Europe. Thus, air quality is a recurring issue and has been at the focus of many studies in recent years Petetin et al., 2014;Petit et al., 2015Petit et al., , 2017Dupont et al., 2016;Srivastava et al., 2018). Results indicate that the Paris metropolitan region is often affected by mid-range to long-range transport of pollutants, as due to the city's flat orography, an efficient horizontal exchange of air masses is frequent (Bressi et al., 2013;Petit et al., 2015). ...
... Often, these episodes are characterized by stagnant atmospheric conditions and a combination of local contributions, e.g. traffic emissions, residential emissions, or regionally transported particles, such as ammonium nitrates from manure spreading or sulfates from point sources (Petetin et al., 2014;Petit et al., 2014Petit et al., , 2015Srivastava et al., 2018). High-pressure conditions with air masses originating from continental Europe (Belgium, Netherlands, western Germany) are generally associated with an increase in particle concentrations, especially of secondary inorganic aerosols (SIAs, Bressi et al., 2013;Srivastava et al., 2018). ...
Air pollution, in particular high concentrations of particulate matter smaller than 1 µm in diameter (PM1), continues to be a major health problem, and meteorology is known to substantially influence atmospheric PM concentrations. However, the scientific understanding of the ways in which complex interactions of meteorological factors lead to high-pollution episodes is inconclusive. In this study, a novel, data-driven approach based on empirical relationships is used to characterize and better understand the meteorology-driven component of PM1 variability. A tree-based machine learning model is set up to reproduce concentrations of speciated PM1 at a suburban site southwest of Paris, France, using meteorological variables as input features. The model is able to capture the majority of occurring variance of mean afternoon total PM1 concentrations (coefficient of determination (R2) of 0.58), with model performance depending on the individual PM1 species predicted. Based on the models, an isolation and quantification of individual, season-specific meteorological influences for process understanding at the measurement site is achieved using SHapley Additive exPlanation (SHAP) regression values. Model results suggest that winter pollution episodes are often driven by a combination of shallow mixed layer heights (MLHs), low temperatures, low wind speeds, or inflow from northeastern wind directions. Contributions of MLHs to the winter pollution episodes are quantified to be on average ∼5 µg/m3 for MLHs below
... For source apportionment purposes, the elemental composition (starting from sodium atomic mass) is additionally measured by inductively coupled plasma mass-or atomic emissionspectrometry (ICP-MS or ICP-AES) following sample preparation and analytical procedures defined by the EN 14902 European standard. Finally, various other analytical techniques, including liquid or gas chromatography, coupled with mass spectrometry (LC or GC-MS), have also been used for a better apportionment of the organic aerosol fractions (e.g., [18,[20][21][22][23]). ...
... 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 selfamplification cycle of SOA formation during wintertime PM pollution episodes [18]. ...
... 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]. ...
The CARA program has been running since 2008 by the French reference laboratory for air quality monitoring (LCSQA) and the regional monitoring networks, to gain better knowledge—at a national level—on particulate matter (PM) chemistry and its diverse origins in urban environments. It results in strong collaborations with international-level academic partners for 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 throughout 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.
... Several previous studies have shown that a detailed chemical characterization of OA at a molecular level can provide insights into the OA sources as several organic compounds have been identified and recognized as tracers (or markers) of specific sources or chemical (trans-) formation processes (Srivastava et al., 2018a(Srivastava et al., , 2018b(Srivastava et al., , 2018c, 2019 and references therein). For instance, for primary sources, levoglucosan is commonly used to trace biomass burning emissions, polyols for biogenic emissions (fungal spores), hopanes for vehicular emissions, etc. (Cass, 1998;Samaké et al., 2019aSamaké et al., , 2019bSchauer et al., 1996;Simoneit et al., 1999). ...
... Finally, SOA markers have been commonly used for source apportionment, in the USA and in Asia but are still poorly documented in Europe (Srivastava et al., 2018a). The SOA formation conditions are expected to be quite different in Europe compared to USA and/or Asia due to the differences in the predominant SOA precursor and emission sources. ...
... As described below, a single extraction for PUF samples was performed for the analysis of SOA markers, PAHs and PAH derivatives. For both phases, 22 PAHs, 27 oxy-and 31 nitro-PAHs were quantified by UPLC/ Fluorescence (ultra-performance LC/Fluorescence detection) and GC/ NICI-MS (gas chromatography/negative ion chemical ionization MS), respectively (Albinet et al., , 2013(Albinet et al., , 2014Srivastava et al., 2018a;Tomaz et al., 2016). PAH analyses have been performed following the recommendations of European standard procedures EN 15549 and TS 16645 (CEN, 2008(CEN, , 2014 including the control of extraction efficiency using the NIST SRM 1649b (urban dust). ...
Twenty-five biogenic and anthropogenic secondary organic aerosol (SOA) markers have been measured over a one-year period in both gaseous and PM10 phases in the Paris region (France). Seasonal and chemical patterns were similar to those previously observed in Europe, but significantly different from the ones observed in America and Asia due to dissimilarities in source precursor emissions. Nitroaromatic compounds showed higher concentrations in winter due to larger emissions of their precursors originating from biomass combustion used for residential heating purposes. Among the biogenic markers, only isoprene SOA marker concentrations increased in summer while pinene SOA markers did not display any clear seasonal trend. The measured SOA markers, usually considered as semi-volatiles, were mainly associated to the particulate phase, except for the nitrophenols and nitroguaiacols, and their gas/particle partitioning (GPP) showed a low temperature and OM concentrations dependency. An evaluation of their GPP with thermodynamic model predictions suggested that apart from equilibrium partitioning between organic phase and air, the GPP of the markers is affected by processes suppressing volatility from a mixed organic and inorganic phase, such as enhanced dissolution in aerosol aqueous phase and non-equilibrium conditions. SOA marker concentrations were used to apportion secondary organic carbon (SOC) sources applying both, an improved version of the SOA-tracer method and positive matrix factorization (PMF) Total SOC estimations agreed very well between both models, except in summer and during a highly processed Springtime PM pollution event in which systematic underestimation by the SOA tracer method was evidenced. As a first approach, the SOA-tracer method could provide a reliable estimation of the average SOC concentrations, but it is limited due to the lack of markers for aged SOA together with missing SOA/SOC conversion fractions for several sources.
... Emissions from domestic heating, road transport and manure spreading along with anticyclonic atmospheric conditions result in the transport and/or accumulation of pollutants, as well as photochemical processes, within the boundary layer during such events (Waked et al., 2014;Petit et al., 2017;Dupont et al., 2016). Thus, such episodes are often dominated by a high proportion of secondary pollutants (especially ammonium nitrate and SOA) (Petit et al., 2017;Beekmann et al., 2015;Srivastava et al., 2018a;Srivastava et al., 2018c;Waked et al., 2014;Weber et al., 2019;Putaud et al., 2004;Putaud et al., 2010). Similar events have been observed in China in recent years; reduction in SO 2 emissions results in the shift of sulfate to nitrate dominated haze pollution events (Xie et al., 2020;Xu et al., 2019;Tian et al., 2019;Wang et al., 2020). ...
... Similar events have been observed in China in recent years; reduction in SO 2 emissions results in the shift of sulfate to nitrate dominated haze pollution events (Xie et al., 2020;Xu et al., 2019;Tian et al., 2019;Wang et al., 2020). During such events, organic matter (OM) is the second contributor to the PM mass concentrations observed (Putaud et al., 2004) and, as meteorological and photooxidant conditions promote chemical processes, a significant fraction of OA is probably of secondary origin Huang et al., 2014;Petit et al., 2017;Srivastava et al., 2018a;Srivastava et al., 2019;Srivastava et al., 2018c;Tomaz et al., 2017). However, OA sources during these highly processed PM pollution episodes are still poorly addressed while it is critical in terms of air quality policy management. ...
... Details about the monitoring site, online measurements, sample collection, chemical speciation analytical procedures as well as backward trajectory analyses have already been reported in two previous articles Srivastava et al., 2018a) and in the supporting material of the present one (SM). Only the essential information is presented in this section. ...
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 combination of different methodologies to apportion the POC/SOC concentrations/contributions to get the highest level of confidence in the estimates obtained.
... To examine the validity of this method, we applied it to 2 independent datasets for which AE33 and levoglucosan data as well as PMF outputs were already available elsewhere. These datasets are corresponding to i) an intensive field campaign with 4 h-filter samplings during Spring 2015 at SIRTA (Srivastava et al., 2018) and ii) daily filter-based measurements in Metz . As shown in Fig. S3, a good correlation (r 2 = 0.83, slope = 1.11 ± 0.03, N = 227) was obtained between PMF wood burning factor and PM 10,wood burning , supporting the good performance of the BrC-levoglucosan-tracer method to quantify biomass burning source emissions. ...
... As shown in Fig. 7c, HOA presents a highly similar PSCF pattern as the two BBOA factors, which is characterized by high values associated with both the local scale and the region located to the south and southeast of the sampling site. This is mainly due to that the HOA factor here is a mixed OA factor emitted from fossil fuel and biomass combustion, which has been demonstrated by some previous studies performed at SIRTA Srivastava et al., 2018;Zhang et al., 2019). Interestingly, as shown in Fig. 7d, OOA also presents a very similar PSCF pattern as the two BBOA factors. ...
... The calculated HOA MAE at 370 nm is of 1.06 ± 0.23 m 2 g −1 , which is higher than the value observed for HOA in tunnel environment in Zurich (below 0.4 m 2 g −1 ) (Moschos et al., 2018). This can be partly explained by the fact the HOA factor at SIRTA is not made of trafficemitted organic aerosols only during cold months and can be mixed with biomass burning organic aerosols Srivastava et al., 2018;Zhang et al., 2019). ...
Brown carbon (BrC) is known to absorb light at subvisible wavelengths but its optical properties and sources are still poorly documented, leading to large uncertainties in climate studies. Here, we show its major wintertime contribution to total aerosol absorption at 370 nm (18–42%) at 9 different French sites. Moreover, an excellent correlation with levoglucosan (r² = 0.9 and slope = 22.2 at 370 nm), suggesting important contribution of wood burning emissions to ambient BrC aerosols in France. At all sites, BrC peaks were mainly observed during late evening, linking to local intense residential wood burning during this time period. Furthermore, the geographic origin analysis also highlighted the high potential contribution of local and/or small-regional emissions to BrC. Focusing on the Paris region, twice higher BrC mass absorption efficiency value was obtained for less oxidized biomass burning organic aerosols (BBOA) compared to more oxidized BBOA (e.g., about 4.9 ± 0.2 vs. 2.0 ± 0.1 m² g⁻¹, respectively, at 370 nm). Finally, the BBOA direct radiative forcing effect was found to be 40% higher when these two fractions are treated as light-absorbing species, compared to the non-absorbing BBOA scenario.
... Several studies have identified key characteristic molecular compounds of the formation of SOA from specific precursors or sources and commonly defined as molecular SOA markers (or tracers if assuming that they are chemically stable) [7,8] (Table 1). These compounds are used to apportion SOA in the so-called SOA tracer method [7,9] or in source-receptor models, such as chemical mass balance (CMB) or positive matrix factorization (PMF) [7,[10][11][12][13]. The quantification of these SOA markers is critical because inaccurate values could lead to significant bias in the results obtained [7]. ...
... Our objectives also included the comparison of the extraction efficiencies, for the analysis of molecular SOA markers in PM, of two different extraction procedures, namely, sonication and QuEChERSlike (Quick Easy Cheap Effective Rugged and Safe). Sonication is commonly used for the analysis of SOA marker compounds in aerosol samples [7-9, 16, 27, 33-40] while QuEChERS-like procedure has been developed and successfully applied for the molecular chemical characterization of OA including polycyclic aromatic compounds (PAHs), nitro-PAHs, oxy-PAHs [31,[41][42][43], and also SOA markers [10,11,13,44]. In addition, this latter technique should minimize the degradation of some fragile SOA marker and preserve the integrity of the sample as it is done at room temperature [31,44]. ...
... Note that β-caryophyllinic acid has been reported by NIST as below LOQ (ESM Table S2). This SOA marker is usually observed at low concentration levels in urban atmosphere [7,10,11,36,45]. Second, these results also showed that the extraction efficiencies of sonication and QuEChERS-like were similar demonstrating the validity of the QuEChERS-like extraction procedure for the analysis of SOA markers in PM. ...
Secondary organic aerosol (SOA) accounts for a significant fraction of particulate matter (PM) in the atmosphere. Source identification, including the SOA fraction, is critical for the effective management of air pollution. Molecular SOA markers (tracers) are key compounds allowing the source apportionment of SOA using different methodologies. Therefore, accurate SOA marker measurements in ambient air PM are important. This study determined the concentrations of 12 key SOA markers (biogenic and anthropogenic) in the urban dust standard reference material available from the National Institute of Standards and Technology (NIST) (SRM 1649b). Two extraction procedures, sonication and QuEChERS-like (quick easy cheap effective rugged and safe), have been compared. Three research laboratories/institutes using two analytical techniques (gas chromatography/mass spectrometry (GC/MS) and ultra-high-pressure liquid chromatography/tandem mass spectrometry (HPLC/MS-MS)) carried out the analyses. The results obtained were all in good agreement, except for 2-methylerythritol. The analysis of this compound still seems to be challenging by both GC/MS (large injection repeatability) and HPLC/MS-MS (separation issues of both 2-methyltetrols: 2-methylthreitol and 2-methylerythritol). Possible inhomogeneity in the SRM for this compound could also explain the large discrepancies observed. Sonication and QuEChERS-like procedures gave comparable results for the extraction of the SOA markers showing that QuEChERS-like extraction is suitable for the analysis of SOA markers in ambient air PM. As this study provides, for the first time, indicative values in a reference material for typical SOA markers, the analysis of SRM 1649b (urban dust) could be used for quality control/assurance purposes.
... Positive matrix factorization (PMF), a bilinear factor analytic model that constrains the factors to be non-negative (Paatero et al., 2002;Paatero and Tapper, 1994), has been widely used with traditional speciation data (i.e., organic carbon (OC), elemental carbon (EC), major ions and elements) for source apportionment. The use of molecular markers within PMF has opened new perspectives for filter-based source apportionment studies (Heo et al., 2013;Hu et al., 2010;Shrivastava et al., 2007;Srivastava et al., 2018a;Srivastava et al., 2018c;Wang et al., 2012;Zhang et al., 2009). Nevertheless, short-time resolution of filter measurements is not able to reveal the rapid atmospheric processes (Srivastava et al., 2018a). ...
... The use of molecular markers within PMF has opened new perspectives for filter-based source apportionment studies (Heo et al., 2013;Hu et al., 2010;Shrivastava et al., 2007;Srivastava et al., 2018a;Srivastava et al., 2018c;Wang et al., 2012;Zhang et al., 2009). Nevertheless, short-time resolution of filter measurements is not able to reveal the rapid atmospheric processes (Srivastava et al., 2018a). Development of online instrumentation (e.g. ...
... Measurements were conducted at the SIRTA atmospheric supersite (Site Instrumental de Recherche par Télédétection Atmosphérique, 2.15°E; 48.71°N; 150 m above sea level; http://sirta.ipsl.fr). This site provides long-term, in-situ observations of the chemical, optical, and physical properties of the atmospheric aerosol and illustrates the background air quality of the Paris region (France) and belongs to the European Research Infrastructure for the observation of Aerosol, Clouds and Trace Gases, ACTRIS (Crippa et al., 2013a;Haeffelin et al., 2005;Petit et al., 2017a;Petit et al., 2014;Petit et al., 2015;Sciare et al., 2011;Srivastava et al., 2018a). An intensive campaign was performed from 6th-21st, March 2015 during a severe PM pollution event (PM 10 N 50 μg m −3 for at least 3 consecutive days). ...
The present study proposes an advanced methodology to refine the source apportionment of organic aerosol (OA). This methodology is based on the combination of offline and online datasets in a single Positive Matrix Factorization (PMF) analysis using the multilinear engine (ME-2) algorithm and a customized time synchronization procedure. It has been applied to data from measurements conducted in the Paris region (France) during a PM pollution event in March 2015. Measurements included OA ACSM (Aerosol Chemical Speciation Monitor) mass spectra and specific primary and secondary organic molecular markers from PM10 filters on their original time resolution (30 min for ACSM and 4 h for PM10 filters). Comparison with the conventional PMF analysis of the ACSM OA dataset (PMF-ACSM) showed very good agreement for the discrimination between primary and secondary OA fractions with about 75% of the OA mass of secondary origin. Furthermore, the use of the combined datasets allowed the deconvolution of 3 primary OA (POA) factors and 7 secondary OA (SOA) factors. A clear identification of the source/origin of 54% of the total SOA mass could be achieved thanks to specific molecular markers. Specifically, 28% of that fraction was linked to combustion sources (biomass burning and traffic emissions). A clear identification of primary traffic OA was also obtained using the PMF-combined analysis while PMF-ACSM only gave a proxy for this OA source in the form of total hydrocarbon-like OA (HOA) mass concentrations. In addition, the primary biomass burning-related OA source was explained by two OA factors, BBOA and OPOA-like BBOA. This new approach has showed undeniable advantages over the conventional approaches by providing valuable insights into the processes involved in SOA formation and their sources. However, the origins of highly oxidized SOA could not be fully identified due to the lack of specific molecular markers for such aged SOA.
... However, the synthesis remains a quite expensive and/or time-consuming task. Only very recently, a few papers have reported the use of authentic standards that are commercially available or synthesized on purpose by worldwide suppliers [73,273]. ...
... However, the synthesis remains a quite expensive and/or timeconsuming task. Only very recently, a few papers have reported the use of authentic standards that are commercially available or synthesized on purpose by worldwide suppliers [73,273]. ...
... By comparison, molecular organic markers (tracers) are mostly source-class specific and may provide a more definitive link between factors and source classes. Molecular markers for SOA and POA can be directly included in the PMF model providing an insight into the primary-secondary split of OA sources [14,40,73,214,273,[304][305][306]. The effectiveness of the method depends on the molecular markers used. ...
Secondary organic aerosol (SOA) is known to account for a major fraction of airborne particulate matter, with significant impacts on air quality and climate at the global scale. Despite the substantial amount of research studies achieved during these last decades, the source apportionment of the SOA fraction remains difficult due to the complexity of the physicochemical processes involved. The selection and use of appropriate approaches are a major challenge for the atmospheric science community. Several methodologies are nowadays available to perform quantitative and/or predictive assessments of the SOA amount and composition. This review summarizes the current knowledge on the most commonly used approaches to evaluate secondary organic carbon (SOC) contents: elemental carbon (EC) tracer method, chemical mass balance (CMB), SOA tracer method, radiocarbon (14 C) measurement and positive matrix factorization (PMF). The principles, limitations, challenges and good practices of each of these methodologies are discussed in the present article. Based on a comprehensive-although not exhaustive-review of research papers published during the last decade (2006-2016), SOC estimates obtained using these methodologies are also summarized for different regions across the world. Conclusions of some studies which are directly comparing the performances of different methodologies are then specifically discussed. An overall picture of SOC contributions and concentrations obtained worldwide for urban sites under similar conditions (i.e., geographical and seasonal ones) is also proposed here. Finally, further needs to improve SOC apportionment methodologies are also identified and discussed.
... In Athens NO 3 − concentrations are comparable with Moscow while other SIA are higher (Eleftheriadis et al., 2014). The average PM 10 in Paris suburbs is almost twice higher while the concentrations of SIA are 3-12 times higher (Srivastava et al., 2018). Continental Toronto downtown, that is found at a similar latitude than Moscow but is influenced by the Great Lakes, shows SIA (Jeong et al., 2020) comparable to those observed in Moscow. ...
... Under ordinary circulation conditions, sea salt cannot exceed a few kilometers from the coast-line inward. In Toronto (Srivastava et al., 2018), Na + and Cl − are significantly less, revealing the absence either sea-salt or road management impact on the ion composition. The similar trend of strongly higher Mg 2+ concentrations are found for coastal cities, probably the indication of the impact of sea salt aerosols on water-soluble species as well. ...
In-depth study of aerosol and precipitation ion chemistry was carried out in order to cover an existing data gap in the seasonal-dependent ionic data in Moscow urban background atmosphere. Literature about atmospheric pollution in this megacity is, indeed, still poor, despite its peculiar climatological characteristics that make it a very interesting site for atmospheric research. Particulate matter (PM) and precipitation were collected at Moscow urban background during spring of 2018, summer, and autumn of 2019. Aerosol inorganic ions are characterized for the whole period, carboxylic acids and sugars for summer. Inorganic ions constitute a major PM10 fraction of 27% in autumn, it drops down to 16.5% in summer. Dominance of secondary inorganic aerosol (SIA) over all the other inorganic ion species is determined. Na⁺ and Ca²⁺ shows the largest variability between seasons, with maximum in summer and spring, respectively. Excess of anions in autumn is indicated by ion balance while adding carbonates, spring and summer aerosol is found electroneutral. Chloride depletion phenomenon follows the snow melt and remobilization of salt applied to roads for deicing, demonstrating the biggest impact in summer. Degree of neutralization of ammonia as sulfate and nitrate is found by the correlation between the concentration of NH4⁺ and calculated from SO4²⁻ and NO3⁻. Inorganic fraction in PM10 is higher (16.5%) than total carboxylic acids (3.5%), and total sugars and anhydrosugars (0.8%). Concentration polar plots show ion variation jointly with wind speed and wind direction and the source origin. Highest SIA concentrations relate a cluster of the prevalent air mass transportation and indicate the source in the northwestern direction in spring and summer. K⁺ acts as a marker of fires in spring and summer as well as of the domestic biomass burning in the region around a megacity in autumn. Source apportionment of inorganic ion and BC by Varimax analysis reveals major sources namely SIA, soil resuspension, biomass burning, deicing salt, and fossil fuel combustion. In summer, organic ions, anhydrosugars, and sugars shows additional impact of photochemistry and biological activities. Rainfall is heavier in summer than in autumn, with pH of acid rain during spring and summer. The highest concentrations for almost all ions were observed in spring, except HCO3⁻. Precipitation composition is described with aerosol wet removal by seasonal variability of SIA scavenging factors, decreasing in summer and increasing in autumn and spring.
... The next step in the verification of the results was the assessment of the normality of the distribution of the 24-h data sets. It was related to the possibility of using the parametric Student's t-test, which is much more powerful compared to typical non-parametric tests such as the U-Mann Whitney test [62][63][64]. First, the frequency distributions of the daily averaged mass concentrations of the analyzed pollutants were prepared, both for the data from the entire measurement period as well as by the heating and non-heating season ( Figure 2). ...
... . The average annual eBC concentration was 3.22 ± 2.80 µg·m −3 , similar to the value obtained for the urban background station in Barcelona, Spain (3 µg·m −3 ) [72] and urban station in Ostrava, Czech Republic (3.48 µg·m −3 ) [73]. Lower concentrations of eBC were reported in some European locations-e.g., Istanbul, Turkey (2.76 µg m −3 ; 1 May 2019-1 February 2020) [74] and three urban stations in the UK (2015): Birmingham (1.1 µg·m −3 ), Glasgow (0.9 µg·m −3 ), and North Kensington (1.0 µg·m −3 )[63]. Higher than the values obtained in Zabrze, concentrations of eBC are recorded at many measurement sites in Asia, e.g., at the urban background station in Pulchowk Campus, Nepal (8.60 µg·m −3 , May 2009-April 2010)[75] and in Xi'an, China (above 10 µg·m −3 , 2006-2015)[65]. ...
This study assesses the air quality in Zabrze (southern Poland) based on the ambient concentrations of equivalent black carbon (eBC). eBC measurement campaigns were carried out from April 2019 to March 2020 using a modern AE33 Aethalometer, accompanied by parallel measurements of gaseous pollutants, PM10 and meteorological parameters. The use of the two-component AE33 model allows for the determination of the eBC from fossil fuel combustion (eBCff) and biomass burning (eBCbb). The obtained results showed a clear seasonal variability of eBC concentrations, with higher average levels in the heating season (4.70 µg·m−3) compared to the non-heating one (1.79 µg·m−3). In both seasons, the eBCff component had a dominant share in total eBC, which indicates significant emissions from the combustion of fossil fuels for heating purposes and from local traffic sources. The obtained results showed high correlation coefficients with gaseous and particulate pollutants, with the strongest relationship for eBC and carbon monoxide (CO). During the non-heating and heating period, both anticyclone and cyclone systems played an important role in shaping eBC, eBCff and eBCbb concentrations. High concentrations of all components occurred with a significant decrease in air temperature and solar radiation in winter.
... 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 Preprints (www.preprints.org) ...
... 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]. Regarding biogenic SOA, and besides the MSA-rich factor, one additional fraction could be attributed to the oxidation of alkenes (i.e., isoprene and terpenes) emitted by terrestrial vegetation at both sites, more importantly at summertime. ...
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.
... It has been shown that concentrations of ambient particle-bound PAHs when collected over long sampling times are subject to higher uncertainties related to sampling artefacts deriving from meteorological effects and oxidant concentrations such as ozone (Goriaux et al., 2006;Stephanou, 2003, 2007;Ringuet et al., 2012a;Keyte et al., 2013). Using shorter time periods for ambient particle sampling (e.g. 3 and 4 h) has been suggested as offering a more accurate diagnosis of emission sources (Tian et al., 2017;Srivastava et al., 2018); shorter time sampling is still scarce and limited to studies outside China and India (Reisen and Arey, 2004;Srivastava et al., 2018). Considering the above and that particles collected during 24 h sampling time integrate both daytime and night-time chemistry together, we collected highfrequency ambient air particle samples (PM 2.5 ) in urban Beijing (China) and Delhi (India) to determine the temporal diurnal and nocturnal variation of PAHs. ...
... It has been shown that concentrations of ambient particle-bound PAHs when collected over long sampling times are subject to higher uncertainties related to sampling artefacts deriving from meteorological effects and oxidant concentrations such as ozone (Goriaux et al., 2006;Stephanou, 2003, 2007;Ringuet et al., 2012a;Keyte et al., 2013). Using shorter time periods for ambient particle sampling (e.g. 3 and 4 h) has been suggested as offering a more accurate diagnosis of emission sources (Tian et al., 2017;Srivastava et al., 2018); shorter time sampling is still scarce and limited to studies outside China and India (Reisen and Arey, 2004;Srivastava et al., 2018). Considering the above and that particles collected during 24 h sampling time integrate both daytime and night-time chemistry together, we collected highfrequency ambient air particle samples (PM 2.5 ) in urban Beijing (China) and Delhi (India) to determine the temporal diurnal and nocturnal variation of PAHs. ...
Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants in air, soil, and water and are known to have harmful effects on human health and the environment. The diurnal and nocturnal variations of 17 PAHs in ambient particle-bound PAHs were measured in urban Beijing (China) and Delhi (India) during the summer season using gas-chromatography–quadrupole time-of-flight mass spectrometry (GC-Q-TOF-MS). The mean concentration of particles less than 2.5 µm (PM2.5) observed in Delhi was 3.6 times higher than in Beijing during the measurement period in both the daytime and night-time. In Beijing, the mean concentration of the sum of the 17 PAHs (P17 PAHs) was 8.2 ± 5.1 ng m−3 in daytime, with the highest contribution from indeno[1,2,3-cd]pyrene (12 %), while at nighttime the total PAHs was 7.2 ± 2.0 ng m−3, with the largest contribution from benzo[b]fluoranthene (14 %). In Delhi, the mean P17 PAHs was 13.6 ± 5.9 ng m−3 in daytime and 22.7 ± 9.4 ng m−3 at night-time, with the largest contribution from indeno[1,2,3-cd]pyrene in both the day (17 %) and night (20 %). Elevated mean concentrations of total PAHs in Delhi observed at night were attributed to emissions from vehicles and biomass burning and to meteorological conditions leading to their accumulation from a stable and low atmospheric boundary layer. Local emission sources were typically identified as the major contributors to total measured PAHs in both cities. Major emission sources were characterized based on the contribution from each class of PAHs, with the four-, five- and six-ring PAHs accounting ∼ 95 % of the total PM2.5-bound PAHs mass in both locations. The high contribution of five-ring PAHs to total PAH concentration in summer Beijing and Delhi suggests a high contribution from petroleum combustion. In Delhi, a high contribution from six-ring PAHs was observed at night, suggesting a potential emission source from the combustion of fuel and oil in power generators, widely used in Delhi. The lifetime excess lung cancer risk (LECR) was calculated for Beijing and Delhi, with the highest estimated risk attributed to Delhi (LECR = 155 per million people), which is 2.2 times higher than the Beijing risk assessment value (LECR = 70 per million people). Finally, we have assessed the emission control policies in each city and identified those major sectors that could be subject to mitigation measures.
... It has been shown that concentrations of ambient particle-bound PAHs when collected over long sampling times are subject to higher uncertainties related to sampling artefacts deriving from meteorological effects and oxidant concentrations such as ozone (Goriaux et al., 2006;Stephanou, 2003, 2007;Ringuet et al., 2012a;Keyte et al., 2013). Using shorter time periods for ambient particle sampling (e.g. 3 and 4 h) has been suggested as offering a more accurate diagnosis of emission sources (Tian et al., 2017;Srivastava et al., 2018); shorter time sampling is still scarce and limited to studies outside China and India (Reisen and Arey, 2004;Srivastava et al., 2018). Considering the above and that particles collected during 24 h sampling time integrate both daytime and night-time chemistry together, we collected highfrequency ambient air particle samples (PM 2.5 ) in urban Beijing (China) and Delhi (India) to determine the temporal diurnal and nocturnal variation of PAHs. ...
... It has been shown that concentrations of ambient particle-bound PAHs when collected over long sampling times are subject to higher uncertainties related to sampling artefacts deriving from meteorological effects and oxidant concentrations such as ozone (Goriaux et al., 2006;Stephanou, 2003, 2007;Ringuet et al., 2012a;Keyte et al., 2013). Using shorter time periods for ambient particle sampling (e.g. 3 and 4 h) has been suggested as offering a more accurate diagnosis of emission sources (Tian et al., 2017;Srivastava et al., 2018); shorter time sampling is still scarce and limited to studies outside China and India (Reisen and Arey, 2004;Srivastava et al., 2018). Considering the above and that particles collected during 24 h sampling time integrate both daytime and night-time chemistry together, we collected highfrequency ambient air particle samples (PM 2.5 ) in urban Beijing (China) and Delhi (India) to determine the temporal diurnal and nocturnal variation of PAHs. ...
Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants in air,
soil, and water and are known to have harmful effects on human health and the
environment. The diurnal and nocturnal variations of 17 PAHs in ambient
particle-bound PAHs were measured in urban Beijing (China) and Delhi (India)
during the summer season using gas-chromatography–quadrupole time-of-flight mass
spectrometry (GC-Q-TOF-MS). The mean concentration of
particles less than 2.5 µm (PM2.5) observed in Delhi was 3.6 times
higher than in Beijing during the measurement period in both the daytime and
night-time. In Beijing, the mean concentration of the sum of the 17 PAHs
(∑17 PAHs) was 8.2 ± 5.1 ng m−3 in daytime, with the
highest contribution from indeno[1,2,3-cd]pyrene (12 %), while at
night-time the total PAHs was 7.2 ± 2.0 ng m−3, with the largest
contribution from benzo[b]fluoranthene (14 %). In Delhi, the mean ∑17 PAHs was 13.6 ± 5.9 ng m−3 in daytime and 22.7 ± 9.4 ng m−3 at night-time, with the largest contribution from
indeno[1,2,3-cd]pyrene in both the day (17 %) and night (20 %).
Elevated mean concentrations of total PAHs in Delhi observed at night were
attributed to emissions from vehicles and biomass burning and to
meteorological conditions leading to their accumulation from a stable and
low atmospheric boundary layer. Local emission sources were typically
identified as the major contributors to total measured PAHs in both cities.
Major emission sources were characterized based on the contribution from
each class of PAHs, with the four-, five- and six-ring PAHs accounting
∼ 95 % of the total PM2.5-bound PAHs mass in both
locations. The high contribution of five-ring PAHs to total PAH concentration
in summer Beijing and Delhi suggests a high contribution from petroleum
combustion. In Delhi, a high contribution from six-ring PAHs was observed at
night, suggesting a potential emission source from the combustion of fuel
and oil in power generators, widely used in Delhi. The lifetime excess lung
cancer risk (LECR) was calculated for Beijing and Delhi, with the highest
estimated risk attributed to Delhi (LECR = 155 per million people), which is 2.2
times higher than the Beijing risk assessment value (LECR = 70 per million
people). Finally, we have assessed the emission control policies in each
city and identified those major sectors that could be subject to mitigation
measures.
... However, a long averaging period creates some limitations such as sampling artefacts, notably where changing atmospheric photolysis conditions (air humidity, temperature, wind direction, ozone or other oxidant concentrations) may have a significant influence on PAH concentrations and oxidation rates (Albinet et al., 2007b(Albinet et al., , 2009Goriaux et al., 2006;Stephanou, 2003, 2007;Ringuet et al., 2012b). More intensive and higher frequency measurements in field campaigns have been suggested as a means to improve the positive matrix factorization model performance (Tian et al., 2017;Srivastava et al., 2018). A few studies have used twice daily (12 h) sampling (Albinet et al., 2008;Zhang et al., 2018;Farren et al., 2015;Ringuet et al., 2012b), obtaining limited information on variability in concentrations during the daytime and night-time (Tsapakis and Stephanou, 2007). ...
... A few studies have used twice daily (12 h) sampling (Albinet et al., 2008;Zhang et al., 2018;Farren et al., 2015;Ringuet et al., 2012b), obtaining limited information on variability in concentrations during the daytime and night-time (Tsapakis and Stephanou, 2007). Shorter time periods for sampling (3 and 4 h) are still very limited (Reisen and Arey, 2004;Srivastava et al., 2018). Considering the above, this paper determines the temporal diurnal and nocturnal variation of the PM 2.5 -bound concentrations of PAHs, OPAHs and NPAHs from the air of Beijing in China, it shows the role of photochemistry in the formation of OPAHs and NPAHs, and it associates the fate and evolution of PAHs, OPAHs and NPAHs with the gas-phase concentrations of other pollutants (O 3 , CO, NO, NO 2 , SO 2 , HONO). ...
Ambient particulate matter (PM) can contain a mix of different toxic species derived from a wide variety of sources. This study quantifies the diurnal variation and nocturnal abundance of 16 polycyclic aromatic hydrocarbons (PAHs), 10 oxygenated PAHs (OPAHs) and 9 nitrated PAHs (NPAHs) in ambient PM in central Beijing during winter. Target compounds were identified and quantified using gas chromatography-time-of-flight mass spectrometry (GC-Q-ToF-MS). The total concentration of PAHs varied between 18 and 297 ng m −3 over 3 h daytime filter samples and from 23 to 165 ng m −3 in 15 h night-time samples. The total concentrations of PAHs over 24 h varied between 37 and 180 ng m −3 (mean: 97 ± 43 ng m −3). The total daytime concentrations during high particulate loading conditions for PAHs, OPAHs and NPAHs were 224, 54 and 2.3 ng m −3 , respectively. The most abundant PAHs were fluoranthene (33 ng m −3), chrysene (27 ng m −3), pyrene (27 ng m −3), benzo[a]pyrene (27 ng m −3), benzo[b]fluoranthene (25 ng m −3), benzo[a]anthracene (20 ng m −3) and phenanthrene (18 ng m −3). The most abundant OPAHs were 9,10-anthraquinone (18 ng m −3), 1,8-naphthalic anhydride (14 ng m −3) and 9-fluorenone (12 ng m −3), and the three most abundant NPAHs were 9-nitroanthracene (0.84 ng m −3), 3-nitrofluoranthene (0.78 ng m −3) and 3-nitrodibenzofuran (0.45 ng m −3). PAHs and OPAHs showed a strong positive correlation with the gas-phase abundance of NO, CO, SO 2 and HONO, indicating that PAHs and OPAHs can be associated with both local and regional emissions. Diagnostic ratios suggested emissions from traffic road and coal combustion were the predominant sources of PAHs in Beijing and also revealed the main source of NPAHs to be secondary photochemical formation rather than primary emissions. PM 2.5 and NPAHs showed a strong correlation with gas-phase HONO. 9-Nitroanthracene appeared to undergo a photodegradation during the daytime and showed a strong positive correlation with ambient HONO (R = 0.90, P < 0.001). The lifetime excess lung cancer risk for those species that have available toxicological data (16 PAHs, 1 OPAH and 6 NPAHs) was calculated to be in the range 10 −5 to 10 −3 (risk per million people ranges from 26 to 2053 cases per year).
... It has already been demonstrated that OA plays a dominant role in controlling atmospheric pollution in this region (Bressi et al., 2013;Petit et al., 2015). Furthermore, time-limited (typically, 1-2 months) measurement campaigns demonstrated that primary fine aerosols are mainly influenced there by traffic emissions all over the year and residential wood burning during cold seasons, while secondary aerosols originate from both local production and regional transport (Sciare et al., 2011;Crippa et al., 2013a, b;Petit et al., 2014;Srivastava et al., 2018b). Furthermore, such a background site can be considered representative of air quality at a regional scale, including neighboring northwestern countries (Bressi et al., 2013(Bressi et al., , 2014. ...
... As shown in Fig. 10c and d, both MO-OOA and LO-OOA present high springtime PSCF values originating from the northeastern regions too, which can participate in pollution episodes frequently observed during this season Srivastava et al., 2018b). Therefore, mitigation of VOC emissions at the regional scale could help to reduce the substantial influence of OA on PM limit value exceedances during this season. ...
Organic aerosol (OA) particles are recognized as key factors influencing air
quality and climate change. However, highly time-resolved long-term
characterizations of their composition and sources in ambient air are still
very limited due to challenging continuous observations. Here, we present an
analysis of long-term variability of submicron OA using the combination of
an aerosol chemical speciation monitor (ACSM) and a multiwavelength Aethalometer
from November 2011 to March 2018 at a peri-urban background site of the
Paris region (France). Source apportionment of OA was achieved via partially
constrained positive matrix factorization (PMF) using the multilinear engine
(ME-2). Two primary OA (POA) and two oxygenated OA (OOA) factors were
identified and quantified over the entire studied period. POA factors were
designated as hydrocarbon-like OA (HOA) and biomass burning OA (BBOA). The
latter factor presented a significant seasonality with higher concentrations
in winter with significant monthly contributions to OA (18 %–33 %) due to
enhanced residential wood burning emissions. HOA mainly originated from
traffic emissions but was also influenced by biomass burning in cold
periods. OOA factors were distinguished between their less- and
more-oxidized fractions (LO-OOA and MO-OOA, respectively). These factors
presented distinct seasonal patterns, associated with different atmospheric
formation pathways. A pronounced increase in LO-OOA concentrations and
contributions (50 %–66 %) was observed in summer, which may be mainly
explained by secondary OA (SOA) formation processes involving biogenic
gaseous precursors. Conversely, high concentrations and OA contributions
(32 %–62 %) of MO-OOA during winter and spring seasons were partly
associated with anthropogenic emissions and/or long-range transport from
northeastern Europe. The contribution of the different OA factors as a
function of OA mass loading highlighted the dominant roles of POA during
pollution episodes in fall and winter and of SOA for highest springtime and
summertime OA concentrations. Finally, long-term trend analyses indicated a
decreasing feature (of about −175 ng m−3 yr−1) for MO-OOA, very
limited or insignificant decreasing trends for primary anthropogenic
carbonaceous aerosols (BBOA and HOA, along with the fossil-fuel and biomass-burning black carbon components) and no statistically significant trend for
LO-OOA over the 6-year investigated period.
... Indeed, atmospheric organic aerosols (OAs) contain specific chemical species that can be used as reliable biomarkers in tracing the sources and abundance of PBOA (Bauer et al., 2008;Gosselin et al., 2016;Holden et al., 2011;Jia et al., 2010;Li et al., 2018;Medeiros et al., 2006b;Wang et al., 2018). For instance, among sugar alcohols, arabitol and mannitol (two common storage soluble carbohydrates in fungi) have been recognized as tracers for airborne fungi, and their concentrations are widely used to estimate PBOA contributions to OA mass Bauer et al., 2008;Buiarelli et al., 2013;Golly et al., 2018;Medeiros et al., 2006b;Samaké et al., 2019;Srivastava et al., 2018;Verma et al., 2018;Weber et al., 2018Weber et al., , 2019. Similarly, glucose has also been used as a tracer for plant materials (such as pollen, leaves, and their fragments) or soil emissions within various studies around the world (Chen et al., 2013;Medeiros et al., 2006b;Pietrogrande et al., 2014;Rathnayake et al., 2017;Rogge et al., 2007;Wan et al., 2019;Xiao et al., 2018;Zhu et al., 2015). ...
... In addition, a CarboPAC MA1 column was used (4 × 250 mm, Dionex) along with an isocratic analytical run with 480 mM sodium hydroxide eluent. This analytical technique allows us to quantify arabitol, mannitol, and glucose (Srivastava et al., 2018). Examples of standard solution and sample raw HPLC-PAD chromatograms are presented in Fig. S1. ...
The primary sugar compounds (SCs, defined as glucose,
arabitol, and mannitol) are widely recognized as suitable molecular markers
to characterize and apportion primary biogenic organic aerosol emission
sources. This work improves our understanding of the spatial behavior and
distribution of these chemical species and evidences their major effective
environmental drivers. We conducted a large study focusing on the daily (24 h) PM10 SC concentrations for 16 increasing space scale sites (local to nationwide), over at least 1 complete year. These sites are distributed
in several French geographic areas of different environmental conditions.
Our analyses, mainly based on the examination of the short-term evolutions
of SC concentrations, clearly show distance-dependent correlations. SC
concentration evolutions are highly synchronous at an urban city scale and
remain well correlated throughout the same geographic regions, even if the
sites are situated in different cities. However, sampling sites located in
two distinct geographic areas are poorly correlated. Such a pattern indicates
that the processes responsible for the evolution of the atmospheric SC
concentrations present a spatial homogeneity over typical areas of at least
tens of kilometers. Local phenomena, such as the resuspension of topsoil and
associated microbiota, do no account for the major emissions processes of SC in urban areas not directly influenced by agricultural activities. The
concentrations of SC and cellulose display remarkably synchronous temporal
evolution cycles at an urban site in Grenoble, indicating a common source
ascribed to vegetation. Additionally, higher concentrations of SC at another site located in a crop field region occur during each harvest periods, indicating resuspension processes of plant materials (crop detritus, leaf debris) and associated microbiota for agricultural and nearby urbanized areas. Finally, ambient air temperature, relative humidity, and vegetation density constitute the main effective drivers of SC atmospheric concentrations.
... However, a long averaging period creates some limitations such as sampling artefacts, notably where changing atmospheric photolysis conditions (air humidity, temperature, wind direction, ozone or other oxidant concentrations) may have a significant influence on PAH concentrations and oxidation rates (Albinet et al., 2007b(Albinet et al., , 2009Goriaux et al., 2006;Stephanou, 2003, 2007;Ringuet et al., 2012b). More intensive and higher frequency measurements in field campaigns have been suggested as a means to improve the positive matrix factorization model performance (Tian et al., 2017;Srivastava et al., 2018). A few studies have used twice daily (12 h) sampling (Albinet et al., 2008;Zhang et al., 2018;Farren et al., 2015;Ringuet et al., 2012b), obtaining limited information on variability in concentrations during the daytime and night-time (Tsapakis and Stephanou, 2007). ...
... A few studies have used twice daily (12 h) sampling (Albinet et al., 2008;Zhang et al., 2018;Farren et al., 2015;Ringuet et al., 2012b), obtaining limited information on variability in concentrations during the daytime and night-time (Tsapakis and Stephanou, 2007). Shorter time periods for sampling (3 and 4 h) are still very limited (Reisen and Arey, 2004;Srivastava et al., 2018). Considering the above, this paper determines the temporal diurnal and nocturnal variation of the PM 2.5 -bound concentrations of PAHs, OPAHs and NPAHs from the air of Beijing in China, it shows the role of photochemistry in the formation of OPAHs and NPAHs, and it associates the fate and evolution of PAHs, OPAHs and NPAHs with the gas-phase concentrations of other pollutants (O 3 , CO, NO, NO 2 , SO 2 , HONO). ...
Ambient particulate matter (PM) can contain a mix of
different toxic species derived from a wide variety of sources. This study
quantifies the diurnal variation and nocturnal abundance of 16 polycyclic
aromatic hydrocarbons (PAHs), 10 oxygenated PAHs (OPAHs) and 9 nitrated PAHs
(NPAHs) in ambient PM in central Beijing during winter. Target compounds
were identified and quantified using gas chromatography–time-of-flight
mass spectrometry (GC-Q-ToF-MS). The total concentration of PAHs varied
between 18 and 297 ng m−3 over 3 h daytime filter samples and from 23
to 165 ng m−3 in 15 h night-time samples. The total concentrations of
PAHs over 24 h varied between 37 and 180 ng m−3 (mean: 97±43 ng m−3).
The total daytime concentrations during high particulate loading
conditions for PAHs, OPAHs and NPAHs were 224, 54 and 2.3 ng m−3,
respectively. The most abundant PAHs were fluoranthene (33 ng m−3),
chrysene (27 ng m−3), pyrene (27 ng m−3), benzo[a]pyrene (27 ng m−3), benzo[b]fluoranthene (25 ng m−3), benzo[a]anthracene (20 ng m−3) and phenanthrene (18 ng m−3). The most abundant OPAHs were
9,10-anthraquinone (18 ng m−3), 1,8-naphthalic anhydride (14 ng m−3) and 9-fluorenone (12 ng m−3), and the three most abundant
NPAHs were 9-nitroanthracene (0.84 ng m−3), 3-nitrofluoranthene (0.78 ng m−3) and 3-nitrodibenzofuran (0.45 ng m−3). ∑PAHs and
∑OPAHs showed a strong positive correlation with the gas-phase
abundance of NO, CO, SO2 and HONO, indicating that PAHs and OPAHs can
be associated with both local and regional emissions. Diagnostic ratios
suggested emissions from traffic road and coal combustion were the
predominant sources of PAHs in Beijing and also revealed the main source
of NPAHs to be secondary photochemical formation rather than primary
emissions. PM2.5 and NPAHs showed a strong correlation with gas-phase
HONO. 9-Nitroanthracene appeared to undergo a photodegradation during the
daytime and showed a strong positive correlation with ambient HONO
(R=0.90, P < 0.001). The lifetime excess lung cancer risk for those
species that have available toxicological data (16 PAHs, 1 OPAH and 6 NPAHs)
was calculated to be in the range 10−5 to 10−3 (risk per million
people ranges from 26 to 2053 cases per year).
... It has already been demonstrated that OA 104 plays a dominant role in controlling atmospheric pollution in this region (Bressi et al., 2013;105 Petit et al., 2015). Furthermore, time-limited (typically, 1-2 months) measurement campaigns over the year and residential wood burning during cold seasons, while secondary aerosols 108 originate from both local production and regional transports (Sciare et al., 2011;Crippa et al., 109 2013a, Crippa et al., 2013b, Petit et al., 2014Srivastava et al., 2018b). In the present study, 110 main OA factors were identified and quantified from 25 successive and seasonal PMF analyses 111 over 6 + years, with the objective of keeping consistency between these factors from one PMF 112 analysis to another. ...
... In order to minimize the effect of atmospheric dilution and regional transport, 481 the mass concentration of MO-OOA was normalized to sulfate, the latter one being considered 482 as a regional secondary production marker (Petit et al., 2015 and Figure S11). As shown in 483 Figure episodes frequently observed during this season (Petit et al., 2015;Srivastava et al., 2018b). 604 Therefore, mitigation of VOCs emissions at the regional scale could help to reduce the 605 substantial influence of OA on PM limit value exceedances during this season. ...
Organic aerosol (OA) particles are recognized as key factors influencing air quality and climate change. However, highly-time resolved year-round characterizations of their composition and sources in ambient air are still very limited due to challenging continuous observations. Here, we present an analysis of long-term variability of submicron OA using the combination of Aerosol Chemical Speciation Monitor (ACSM) and multi-wavelength aethalometer from November 2011 to March 2018 at a background site of the Paris region (France). Source apportionment of OA was achieved via partially constrained positive matrix factorization (PMF) using the multilinear engine (ME-2). Two primary OA (POA) and two oxygenated OA (OOA) factors were identified and quantified over the entire studied period. POA factors were designated as hydrocarbon-like OA (HOA) and biomass burning OA (BBOA). The latter factor presented a significant seasonality with higher concentrations in winter with significant monthly contributions to OA (18–33 %) due to enhanced residential wood burning emissions. HOA mainly originated from traffic emissions but was also influenced by biomass burning in cold periods. OOA factors were distinguished between their less- and more-oxidized fractions (LO-OOA and MO-OOA, respectively). These factors presented distinct seasonal patterns, associated with different atmospheric formation pathways. A pronounced increase of LO-OOA concentrations and contributions (50–66 %) was observed in summer, which may be mainly explained by secondary OA (SOA) formation processes involving biogenic gaseous precursors. Conversely high concentrations and OA contributions (32–62 %) of MO-OOA during winter and spring seasons were partly associated with anthropogenic emissions and/or long-range transport from northeastern Europe. The contribution of the different OA factors as a function of OA mass loading highlighted the dominant roles of POA during pollution episodes in fall and winter, and of SOA for highest springtime and summertime OA concentrations. Finally, long-term trend analyses indicated a decreasing feature (of about 200 ng m−3 yr−1) for MO-OOA, very limited or insignificant decreasing trends for primary anthropogenic carbonaceous aerosols (BBOA and HOA, along with the fossil fuel and biomass burning black carbon components), and no trend for LO-OOA over the 6⁺-year investigated period.
... For PAH-derived SOA, key tracers were 4nitrophenol, phthalic acid for naphthalene-derived SOA, and 4-methylphtalic acid for methylnaphthalene SOA. In prior MM-PMF studies in France, oxy-PAH and nitro-PAH have been useful in tracing SOA derived from larger PAHs (Srivastava et al., 2018a;Srivastava et al., 2018b). The utilized tracers should be expanded as anthropogenic SOA becomes more chemically defined. ...
... Similarly, SOA from BB was identified by way of isopthalic acid and cis-pinonic acid, consistent with aged BB emissions documented in the literature (Yan et al., 2008); however, these compounds can also have other sources, such as primary emissions and monoterpene-derived SOA, respectively. Phenolic oxidation associated with BB SOA has also been identified using methyl-nitrocatechols (Srivastava et al., 2018a(Srivastava et al., , 2018b. To better define BB and anthropogenic SOA, future efforts should be placed on identifying and quantifying molecular markers to identify the specific precursors and pathways responsible for SOA formation. ...
Online and offline measurements of ambient particulate matter (PM) near the urban and industrial Houston Ship Channel in Houston, Texas, USA, during May 2015 were utilized to characterize its chemical composition and to evaluate the relative contributions of primary, secondary, biogenic, and anthropogenic sources. Aerosol mass spectrometry (AMS) on nonrefractory PM1 (PM ≤ 1µm) indicated major contributions from sulfate (averaging 50% by mass), organic aerosol (OA, 40%), and ammonium (14%). Positive matrix factorization (PMF) of AMS data categorized OA on average as 22% hydrocarbon-like organic aerosol (HOA), 29% cooking-influenced less-oxidized oxygenated organic aerosol (CI-LO-OOA), and 48% more-oxidized oxygenated organic aerosol (MO-OOA), with the latter two sources indicative of secondary organic aerosol (SOA). Chemical analysis of PM2.5 (PM ≤ 2.5µm) filter samples agreed that organic matter (35%) and sulfate (21%) were the most abundant components. Organic speciation of PM2.5 organic carbon (OC) focused on molecular markers of primary sources and SOA tracers derived from biogenic and anthropogenic volatile organic compounds (VOCs). The sources of PM2.5 OC were estimated using molecular marker-based positive matric factorization (MM-PMF) and chemical mass balance (CMB) models. MM-PMF resolved nine factors that were identified as diesel engines (11.5%), gasoline engines (24.3%), nontailpipe vehicle emissions (11.1%), ship emissions (2.2%), cooking (1.0%), biomass burning (BB, 10.6%), isoprene SOA (11.0%), high-NOx anthropogenic SOA (6.6%), and low-NOx anthropogenic SOA (21.7%). Using available source profiles, CMB apportioned 41% of OC to primary fossil sources (gasoline engines, diesel engines, and ship emissions), 5% to BB, 15% to SOA (including 7.4% biogenic and 7.6% anthropogenic), and 39% to other sources that were not included in the model and are expected to be secondary.
This study presents the first application of in situ AMS-PMF, MM-PMF, and CMB for OC source apportionment and the integration of these methods to evaluate the relative roles of biogenic, anthropogenic, and BB-SOA. The three source apportionment models agreed that ∼ 50% of OC is associated with primary emissions from fossil fuel use, particularly motor vehicles. Differences among the models reflect their ability to resolve sources based upon the input chemical measurements, with molecular marker-based methods providing greater source specificity and resolution for minor sources. By combining results from MM-PMF and CMB, BB was estimated to contribute 11% of OC, with 5% primary emissions and 6% BB-SOA. SOA was dominantly anthropogenic (28%) rather than biogenic (11%) or BB-derived. The three-model approach demonstrates significant contributions of anthropogenic SOA to fine PM. More broadly, the findings and methodologies presented herein can be used to advance local and regional understanding of anthropogenic contributions to SOA.
... It must be acknowledged that the parameters in this study omit transport-related variables, which could introduce errors in the simulation of PNCN. Wind speed and direction, salient in pollutant advection, 35,36,85 were initially integrated but failed to enhance model performance, primarily as a result of the intricate coastal dynamics of Xiamen, such as sea−land breezes, 86,87 terrain-related air stagnation events, 88 and terrain-driven wind and precipitation patterns. 89 Therefore, in future research frameworks, the methods developed here can be applied to other flat terrain regions to eliminate the factors that could add complexity. ...
... Cl − , SO 2− 4 , NO − 3 , Ca 2+ , Mg 2+ , K + , Na + , and NH + 4 were analyzed by liquid ion chromatography following the protocol detailed in Ledoux et al. (2006) andFadel et al. (2022). Finally, the analysis of organic compounds included the characterization of anhydrosugars (levoglucosan, mannosan, and galactosan), sugar alcohols (arabitol and mannitol), and monosaccharides (glucose and mannose) by high-performance liquid chromatography (HPLC) coupled to a pulsed amperometric detector (PAD) (Srivastava et al., 2018). ...
This work focuses on filling the knowledge gap associated with the contribution of natural and anthro-pogenic marine emissions to PM 10 concentrations in northern France. For this purpose, a 1-year measurement and sampling campaign for PM 10 has been conducted at a French coastal site situated at the Strait of Dover. The characterization of PM 10 samples was performed considering major and trace elements, water-soluble ions, organic carbon (OC), elemental carbon (EC), and organic markers of biomass burning and primary biogenic emissions. Furthermore, the source apportionment of PM 10 was achieved using the constrained weighted non-negative matrix factorization (CW-NMF) model. The annual average PM 10 was 24.3 µg m −3 , with six species contributing 69 % of its mass (NO − 3 , OC, SO 2− 4 , Cl − , Na + , and NH + 4). The source apportionment of PM 10 led to the identification of 9 sources. On average yearly, fresh and aged sea salts contributed 37 % of PM 10 , while secondary nitrate and sulfate contributed 42 %, biomass burning contributed 8 %, and heavy-fuel-oil (HFO) combustion from shipping emissions contributed almost 5 %. Additionally, monthly evolution of the sources' contribution evidenced different behaviors with high contributions of secondary nitrate and biomass burning during winter. In the summer season, 15-times-higher concentrations for HFO combustion (July compared to January) and the predominance of aged sea salts versus fresh sea salts were observed.The concentration-weighted trajec-tory model showed that the sources contributing more than 80 % of PM 10 at Cap Gris-Nez are of regional and/or long-range origins, with the North Sea and the English Channel as hotspots for natural and anthropogenic marine emissions and Belgium, the Netherlands, and the west of Germany as hotspots for secondary inorganic aerosols.
... Most of these studies have only focused on identifying specific class of compounds in the particle or gaseous phase and the detailed speciation was missing. Additionally, some of the oxidation products, known as tracer compounds, can be used in the source apportionment models such as positive matrix factorisation (Srivastava et al., 2018a) and the SOA tracer method (Kleindienst et al., 2007) to estimate the SOA contribution to PM 2.5 based on observational data. The SOA-tracer method was developed by Kleindienst et al. (2007) to estimate the contributions from biogenic (isoprene, α-pinene, β-caryophyllene) and anthropogenic (toluene) precursors to ambient SOA concentrations using oxidation products as specific or selective tracer compounds. ...
Aromatic volatile organic compounds (VOCs) are an important precursor of secondary organic aerosol (SOA) in the urban environment. SOA formed from the oxidation of anthropogenic VOCs can be substantially more abundant than biogenic SOA and has been shown to account for a significant fraction of fine particulate matter in urban areas. A potential aerosol mass (PAM) chamber was used to investigate the oxidised products from the photo-oxidation of m-xylene and toluene. The experiments were carried out with OH radical as oxidant in both high- and low-NOx conditions and the resultant aerosol samples were collected using quartz filters and analysed by GC × GC-TOFMS. Results show the oxidation products derived from both precursors included ring-retaining and -opening compounds (unsaturated aldehydes, unsaturated ketones and organic acids) with a high number of ring-opening compounds observed from toluene oxidation. Glyoxal and methyl glyoxal were the major ring-cleavage products from both oxidation systems, indicating that a bicyclic route plays an important role in their formation. SOA yields were higher for both precursors under high-NOx (toluene: 0.111; m-xylene: 0.124) than at low-NOx (toluene: 0.089; m-xylene: 0.052), likely linked to higher OH concentrations during low-NOx experiments which may lead to higher degree of fragmentation. DHOPA (2,3-dihydroxy-4-oxo-pentanoic acid), a known tracer of toluene oxidation, was observed in both oxidation systems. The mass fraction of DHOPA in SOA from toluene oxidation was about double the value reported previously, but it should not be regarded as a tracer solely for oxidation of toluene as m-xylene oxidation gave a similar relative yield.
... Cl -, SO4 2-, NO3 -, Ca 2+ , Mg 2+ , K + , Na + , and 115 NH4 + were analyzed by liquid ion chromatography following the protocol detailed in Ledoux et al. (2006) andFadel et al. (2022). Finally, the analysis of organic compounds included the characterization of anhydrosugars (levoglucosan, mannosan, and galactosan), sugar alcohols (arabitol and mannitol), and monosaccharides (glucose and mannose) by High Performance Liquid Chromatography (HPLC) coupled to a Pulsed Amperometric Detector (PAD) (Srivastava et al., 2018). Kfoury, 2013;Limem et al., 2014). ...
This work is focused on filling the lack of knowledge associated with natural and anthropogenic marine emissions on PM10 concentrations in Northern France. For this purpose, a one-year measurement and sampling campaign for PM10 has been performed at a French coastal site situated in front of the Straits of Dover. The characterization of PM10 samples was performed considering major and trace elements, water-soluble ions, organic carbon (OC), elemental carbon (EC), and organic markers of biomass burning and primary biogenic emissions. Furthermore, the source apportionment of PM10 was achieved using the constrained weighted-non-negative matrix factorization (CW-NMF) model. The annual average PM10 was 24.3 µg/m3 with six species contributing to 69 % of its mass (NO3-, OC, SO42-, Cl-, Na+, and NH4+). The source apportionment of PM10 led to the identification of 10 sources. Fresh and aged sea-salts contributed to 37 % of PM10, while secondary nitrate and sulfate contributed 41 %, biomass burning 10 %, and Heavy Fuel Oil (HFO) combustion from shipping emissions contributed 5 %, on yearly averages. Additionally, monthly evolution of the sources’ contribution evidenced different behaviors with high contributions of secondary nitrate and biomass burning during winter. In the summer season, 10 times higher concentrations for HFO combustion (July compared to January) and the predominance of aged sea-salts versus fresh sea-salts were observed. Constant weighted trajectories showed that the sources contributing to more than 80 % of PM10 at Cape Gris-Nez are of regional and/or long-range origins with the North Sea and the English Channel as hotspots for natural and anthropogenic marine emissions and Belgium, the Netherlands, and the West of Germany as hotspots for secondary inorganic aerosols.
... Thus, although the concentrations of NPAHs and OPAHs are generally lower than those of their parent PAHs in the atmosphere, increasing attention has been paid to these PAH derivatives. Furthermore, their monitoring in the atmosphere, as well as that of PAHs, is becoming more important in order to determine whether their formation is due to primary emissions or secondary sources [11][12][13][14][15]. However, quantitative data of PAH derivatives in aerosol samples are much fewer than those for parent PAHs because it is difficult to quantify them using the universal method applied to parent PAHs. ...
The concentration of polycyclic aromatic hydrocarbons (PAHs) in the atmosphere has been continually monitored since their toxicity became known, whereas nitro-PAHs (NPAHs) and oxy-PAHs (OPAHs), which are derivatives of PAHs by primary emissions or secondary formations in the atmosphere, have gained attention more recently. In this study, a method for the quantification of 18 NPAH and OPAH congeners in the atmosphere based on combined applications of gas chromatography coupled with chemical ionization mass spectrometry is presented. A high sensitivity and selectivity for the quantification of individual NPAH and OPAH congeners without sample preparations from the extract of aerosol samples were achieved using negative chemical ionization (NCI/MS) or positive chemical ionization tandem mass spectrometry (PCI-MS/MS). This analytical method was validated and applied to the aerosol samples collected from three regions in Northeast Asia—namely, Noto, Seoul, and Ulaanbaatar—from 15 December 2020 to 17 January 2021. The ranges of the method detection limits (MDLs) of the NPAHs and OPAHs for the analytical method were from 0.272 to 3.494 pg/m3 and 0.977 to 13.345 pg/m3, respectively. Among the three regions, Ulaanbaatar had the highest total mean concentration of NPAHs and OPAHs at 313.803 ± 176.349 ng/m3. The contribution of individual NPAHs and OPAHs in the total concentration differed according to the regional emission characteristics. As a result of the aerosol samples when the developed method was applied, the concentrations of NPAHs and OPAHs were quantified in the ranges of 0.016~3.659 ng/m3 and 0.002~201.704 ng/m3, respectively. It was concluded that the method could be utilized for the quantification of NPAHs and OPAHs over a wide concentration range.
... By using the PMF method, the total contribution of anthropogenic primary and secondary biogenic contributions was 68-71% in the atmospheric organic carbon in Grenoble, France [61]. The PMF method found that 1-NP was a good primary organic molecular marker to trace traffic emissions, notably in diesel exhaust [62]. However, the application of the CMB to source appointment of primary emitted NPAHs is limited because of the necessity of many combustion source data sets of not only NPAHs and PAHs but also other pollutants. ...
Nitropolycyclic aromatic hydrocarbons (NPAHs) are derivatives of PAHs and contain one or more nitro functional groups (-NO2). Some NPAHs are classified as possible or probable human carcinogens and are more mutagenic than PAHs. Although the atmospheric cancer risk is estimated as 11% from PAHs but 17% from NPAHs, many of the atmospheric behaviors of NPAHs are unknown. There are two major NPAH formation processes. Primary formation of NPAHs occurs directly during the combustion of organic materials. The secondary formation of NPAHs occurs through the transformation of PAHs after they have been released into the environment. The fate, transport, and health effects of NPAHs are considerably different from their parent PAHs because of these differing formation processes. However, the amount of research conducted on NPAHs is comparatively low relative to PAHs. This is primarily due to a lack of effective analytical method for NPAHs, which generally exist in the environment at concentrations one to three orders of magnitude lower than PAHs. However, with the development of more sensitive analytical methods, the number of research papers published on NPAHs has recently increased. The Western Pacific region, one of the post polluted areas in the world, is the most frequently studied area for NPAHs. Many of them reported that atmospheric concentrations of NPAHs were much lower than parent PAHs and oxygenated derivatives (OPAHs). In this article, recent research on sample treatment and analysis, as well as the sources and environmental fate of NPAHs, are discussed with PAHs and OPAHs. A notable achievement using NPAHs is the development of a new emission source analysis method, the NP method, whose features are also discussed in this review.
... Several molecular markers from specific sources (or SOA precursors) have been reported in the literature and are used for source apportionment purposes (Hopke et al., 2020;Karagulian et al., 2015;Kleindienst et al., 2007;Lanzafame et al., 2021;Schauer et al., 1996;Srivastava et al., 2019Srivastava et al., , 2018bSrivastava et al., , 2018cSrivastava et al., , 2018aSrivastava et al., , 2021. For instance, levoglucosan is commonly used as a primary marker for biomass burning emissions (Bhattarai et al., 2019;Simoneit et al., 1999) and constant ratios between the wood burning organic matter (OM wb ) and particulate phase levoglucosan, estimated by measurement data, are often used to evaluate the contribution of wood-burning aerosol to organic aerosol (Herich et al., 2014;Puxbaum et al., 2007;Schmidl et al., 2008). ...
We developed and implemented in the 3D air quality model CHIMERE the formation of several key anthropogenic aerosol markers including one primary anthropogenic marker (levoglucosan) and 4 secondary anthropogenic markers (nitrophenols, nitroguaiacols, methylnitrocatechols and phthalic acid). Modelled concentrations have been compared to measurements performed at 12 locations in France for levoglucosan in winter 2014–15, and at a sub-urban station in the Paris region over the whole year 2015 for secondary molecular markers. While a good estimation of levoglucosan concentrations by the model has been obtained for a few sites, a strong underestimation was simulated for most of the stations especially for western locations due to a probable underestimation of residential wood burning emissions. The simulated ratio between wood burning organic matter and particulate phase levoglucosan is constant only at high OM values (>10 μg m⁻³) indicating that using marker contribution ratio may be valid only under certain conditions. Concentrations of secondary markers were well reproduced by the model for nitrophenols and nitroguaiacols but were underestimated for methylnitrocatechols and phthalic acid highlighting missing formation pathways and/or precursor emissions. By comparing modelled to measured Gas/Particle Partitioning (GPP) of markers, the simulated partitioning of Semi-Volatile Organic Compounds (SVOCs) was evaluated. Except for nitroguaiacols and nitrophenols when ideality was assumed, the GPP for all the markers was underestimated and mainly driven by the hydrophilic partitioning. SVOCs GPP, and more generally of all SVOC contributing to the formation of SOA, could therefore be significantly underestimated by air quality models, especially when only the partitioning on the organic phase is considered. Our results show that marker modelling can give insights on some processes (such as precursor emissions or missing mechanisms) involved in SOA formation and could prove especially useful to evaluate the GPP in 3D air quality models.
... A detailed description of the analytical protocols used has been published previously (Tomaz et al., 2016;Albinet et al., 2006Albinet et al., , 2013Albinet et al., , 2014Srivastava et al., 2018). Slight modifications have been applied here. ...
A total of 22 polycyclic aromatic hydrocarbons (PAHs), 29 oxy-PAHs, and 35 nitro-PAHs (polycyclic aromatic
compounds, PACs) were measured in gaseous and particulate phases in the
ambient air of Longyearbyen, the most populated settlement in Svalbard, the
European Arctic. The sampling campaign started in the polar night in November
2017 and lasted for 8 months until June 2018, when a light cycle reached a
sunlit period with no night. The transport regimes of the near-surface,
potentially polluted air masses from midlatitudes to the Arctic and the
polar boundary layer meteorology were studied. The data analysis showed the
observed winter PAC levels were mainly influenced by the lower-latitude
sources in northwestern Eurasia, while local emissions dominated in spring
and summer. The highest PAC concentrations observed in spring, with PAH
concentrations a factor of 30 higher compared to the measurements at the
closest background station in Svalbard (Zeppelin, 115 km distance from
Longyearbyen), were attributed to local snowmobile-driving emissions. The
lowest PAC concentrations were expected in summer due to enhanced
photochemical degradation under the 24 h midnight sun conditions and
inhibited long-range atmospheric transport. In contrast, the measured summer
concentrations were notably higher than those in winter due to the harbour
(ship) emissions.
... Levoglucosan is a tracer for biomass burning, while cholesterol is a good indicator of cooking, and both of them are known as primary organic tracers. Previous studies have shown that phthalic acid can be used as an aromatic SOA tracer (Al-Naiema and Stone, 2017; , while 4-methyl-5nitrocatechol can be used as a tracer for biomass burning SOA (Iinuma et al., 2010;Bertrand et al., 2018;Srivastava et al., 2018), and both of them serve as anthropogenic SOA tracers. The biogenic SOA tracers in this study included the isoprene SOA tracer 2-methylerythritol, as well as cispinonic acid and 3-hydroxyglutaric acid, which are lower and higher generation oxidative products of monoterpenes respectively (Kourtchev et al., 2009). ...
Water-soluble organic carbon (WSOC) accounts for a
large proportion of aerosols and plays a critical role in various atmospheric
chemical processes. In order to investigate the primary sources and
secondary production of WSOC in downtown Beijing, day and night
fine particulate matter (PM2.5) samples in January (winter), April (spring), July (summer) and
October (autumn) 2017 were collected and analyzed for WSOC and organic
tracers in this study. WSOC was dominated by its moderately hydrophilic
fraction and showed the highest concentration in January and comparable
levels in April, July and October 2017. Some typical organic tracers were
chosen to evaluate the emission strength and secondary formation of WSOC.
Seasonal variation of the organic tracers suggested significantly enhanced
formation of anthropogenic secondary organic aerosols (SOAs) during the
sampling period in winter and obviously elevated biogenic SOA formation
during the sampling period in summer. These organic tracers were applied
into a positive matrix factorization (PMF) model to calculate the source
contributions of WSOC as well as its moderately and strongly hydrophilic
portions. The secondary sources contributed more than 50 % to WSOC, with
higher contributions during the sampling periods in summer (75.1 %) and
winter (67.4 %), and the largest contributor was aromatic SOC. In addition,
source apportionment results under different pollution levels suggested that
controlling biomass burning and aromatic precursors would be effective to
reduce WSOC during the haze episodes in cold seasons. The impact factors for
the formation of different SOA tracers and total secondary organic carbon (SOC)
as well as moderately and strongly hydrophilic SOC were also investigated.
The acid-catalyzed heterogeneous or aqueous-phase oxidation appeared to
dominate in the SOC formation during the sampling period in winter, while
the photochemical oxidation played a more critical role during the sampling
period in summer. Moreover, photooxidation played a more critical role in
the formation of moderately hydrophilic SOC, while the heterogeneous or
aqueous-phase reactions had more vital effects on the formation of
strongly hydrophilic SOC.
... The characterization of organic aerosols is a major task in current atmospheric research, mainly due to their complex composition and the physicochemical processes involved [1,2]. In ambient particulate matter, about 20 to 50% (and up to 90% in tropical forested areas) is comprised of organic aerosols [3]. ...
Matrix-induced signal suppression or enhancements are known phenomena in electrospray ionization mass spectrometry. Very few studies report on method development for organic aerosols analyses with the evaluation of the matrix effects. The matrix effects lead to errors in the quantification of the analytes and affect the detection capability, precision, and accuracy of an analysis method. The present study reports on the matrix effects in the analysis of organic chemical compounds present in atmospheric aerosol particles collected on quartz filters. A total number of 19 analytes, including different classes of organic compounds, such as monoaromatic phenols and derivatives (e.g., catechol, 4-methylcatechol, 3-methoxycatechol, 4-nitrocatechol, 4-nitrophenol, 2,4-dinitrophenol, 2,6-dimethyl-4-nitrophenol), carboxylic acids (terebic acid, adipic acid, pimelic acid, phthalic acid, vanillic acid), and sulfonic acids (e.g., camphor-10-sulfonic acid), was investigated by high-performance liquid chromatography coupled to electrospray ionization time-of-flight mass spectrometry (HPLC/ESI-ToF-MS). The HPLC and ESI set-up parameters used in this study were previously optimized for the investigated compounds. Different volumes of a standard mixture were added to sample extracts, with final solutions concentrations in the 50–1500 μg L−1 range. For the investigated concentration range, the observed matrix effect was independent of the standard concentration level. For quartz filter extracts, the average matrix effect determined on a concentration-based method was 109.5 ± 6.1%. Both signal suppression and enhancement effects were observed for different compounds. For other analytes, the influence of the matrix effect is variable, suggesting that the use of an internal standard is not sufficient for the matrix effects correction. Competition between analyte ions and matrix components in the gas-phase ionization processes occurring in electrospray might explain signal suppression while generated coeluted isobaric compounds might induce signal enhancement.
... In the present study, Positive Matrix Factorization (PMF 5.0) was used to identify and quantify the contribution of various emission sources to PM mass concentration. PMF is widely used multivariate factor analysis model by the atmospheric scientist for source apportionment study (Murillo et al., 2012;Khan et al., 2012;Ogundele et al., 2016;Poulain et al., 2011;Singhai et al., 2017;Srivastava et al., 2018). The PMF model requires two input files (1) data matrix which includes the measured concentration of PM and associated chemical elements, and (2) uncertainty matrix which included estimated uncertainty with the measured data point. ...
The Himalayas are often considered pristine environments; however, they can be influenced by transported aerosols emitted from urbanized and industrialized areas. In the present study, atmospheric PM10 and PM2.5 were measured during 2014–15 at a semi-urban site in Dehradun, situated in the Doon valley between the Shivalik range and lesser Himalayas. Based on the information of chemical species associated with the particles, source apportionment study was performed using positive matrix factorization (PMF) model. The carcinogenic risk due to inhalation of PM was calculated through inhalation unit risk. The atmospheric PM showed a seasonal cycle with a maximum during winter (PM10: 90 ± 32 μg m−3; PM2.5: 63 ± 27 μg m−3) and minimum during summer season (PM10: 87 ± 40 μg m−3; PM2.5: 39 ± 19 μg m−3). Identified major sources of atmospheric PM are soil/road dust, vehicular activities, industrial activities, mixed aerosols, and anthropogenic burning. Seasonal variation of sources reveals that during summer, soil/road dust (56%) is the predominant source of PM10, whereas industrial activities (50%) in case of PM2.5. During winter, mixed aerosols comprising of emissions from vehicular activities, biomass and anthropogenic burning (62%) are predominant sources of PM10, whereas industrial activities (42%) in case of PM2.5. The study of aerosol vertical profile using satellite-derived CALIPSO data reveals the presence of polluted aerosol at high altitude (0.6–2.9 km) over Doon valley, suggesting the influence of neighboring polluted Indo-Gangetic Plain (IGP) region during both seasons. The carcinogenic risk assessment revealed that inhalation of PM over Dehradun can cause health risk.
... Air sampling with a shorter time duration may help to obtain significant information to characterise PAHs-derivatives; improving the understanding of secondary chemical processes, behaviour, fate, and conditions that favour the generation of highly toxic compounds, such as quinones [20,29]. Some studies have reported already variations in measurements of PAHs and derivatives (nitro-PAHs and oxy-PAHs) obtained under different time sampling schemes [20,[30][31][32][33][34]. In this context, identifying primary sources of quinones and understanding secondary transformation processes, along with their fate routes [35], are essential for reducing population exposure and the effects on public health resulting from this exposure. ...
The diel variation of meteorological conditions strongly influences the formation processes of secondary air pollutants. However, due to the complexity of sampling highly reactive chemical compounds, significant information about their transformation and source can be lost when sampling over long periods, affecting the representativeness of the samples. In order to determine the contribution of primary and secondary sources to ambient levels of polyaromatic hydrocarbons (PAHs) and quinones, measurements of gas and PM 1 phases were conducted at an urban site in the Guadalajara Metropolitan Area (GMA) using a 4-h sampling protocol. The relation between PAHs, quinones, criteria pollutants, and meteorology was also addressed using statistical analyses. Total PAHs (gas phase + PM 1 phase) ambient levels ranged between 184.03 ng m −3 from 19:00 to 23:00 h and 607.90 ng m −3 from 07:00 to 11:00 h. These figures both coincide with the highest vehicular activity peak in the morning and at night near the sampling site, highlighting the dominant role of vehicular emissions on PAHs levels. For the gas phase, PAHs ranged from 177.59 to 595.03 ng m −3 , while for PM 1 , they ranged between 4.81 and 17.44 ng m −3. The distribution of the different PAHs compounds between the gas and PM 1 phases was consistent with their vapour pressure (p • L) reported in the literature, the PAHs with vapour pressure ≤ 1 × 10 −3 Pa were partitioned to the PM 1 , and PAHs with vapour pressures ≥ 1 × 10 −3 Pa were partitioned to the gas phase. PAHs diagnostic ratios confirmed an anthropogenic emission source, suggesting that incomplete gasoline and diesel combustion from motor vehicles represent the major share of primary emissions. Quinones ambient levels ranged between 18.02 ng m −3 at 19:00-23:00 h and 48.78 ng m −3 at 15:00-19:00 h, with significant increases during the daytime. The distribution of quinone species with vapour pressures (p • L) below 1 × 10 −4 Pa were primarily partitioned to the PM 1 , and quinones with vapour pressures above 1 × 10 −4 Pa were mainly partitioned to the gas phase. The analysis of the distribution of phases in quinones suggested emissions from primary sources and their consequent degradation in the gas phase, while quinones in PM 1 showed mainly secondary formation modulated by UV, temperature, O 3 , and wind speed. The sampling protocol proposed in this study allowed obtaining Sustainability 2019, 11, 6345 2 of 22 detailed information on PAHs and quinone sources and their secondary processing to be compared to existing studies within the GMA.
... This makes it difficult to directly link the obtained PMF factors with different organic aerosol (OA) sources and/or (trans-)formation processes leading to secondary organic aerosol (SOA), which may represent up to 40-50% of the PM mass in some areas (e.g., Reference [10]). Recently, a growing number of studies are proposing the use of additional markers to better identify and quantify various primary OA sources, such as fungal spores or plant debris, and/or different SOA fractions [8,[11][12][13]. In the present study, we notably attempted to use oxalate as a generic marker for SOA. ...
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 toJanuary 2017 period. Nine factors were clearly identified, showing mainly contributions fromanthropogenic 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 to30% of the PM mass fraction during winter, while primary traffic concentrations remained relativelyconstant throughout the year. These two sources are also the main contributors during observed PM10pollution episodes. Furthermore, the dominance of the oxalate-rich factor among other secondaryaerosol factors underlines the role of atmospheric processing to secondary organic aerosol loadingswhich are still poorly characterized in this region. Finally, Concentration-Weighted Trajectory (CWT)analysis were performed to investigate the geographical origins of the apportioned sources, notablyillustrating a significant transport of both nitrate-rich and sulfate-rich factors from NortheasternEurope but also from the Balkan region.
... In recent years, source apportionment of PM using organic tracers has gained momentum (Pindado and Perez, 2011;Wang et al., 2012;Mukherjee et al., 2018;Gupta et al., 2018;Srivastava et al., 2018aSrivastava et al., , 2018b. Robust studies have been performed for the source apportionment of fine ambient aerosols over Delhi region (Chowdhury et al., 2007;Sharma et al., 2016Sharma et al., , 2017Jain et al., 2017aJain et al., , 2017bSingh et al., 2011;Bisht et al., 2015;Dumka et al., 2017). ...
Fine ambient aerosols (PM2.5) levels in the atmosphere are continuously worsening over Delhi and National Capital Region (NCR) of India. Complete source profiles are required to be assessed for implementation of proper mitigation measures over the NCR. In this study, emission sources of PM2.5 are reported for the NCR of India for samples collected during December 2016 to December 2017 at three sampling sites in Delhi, Uttar Pradesh and Haryana. Organic constituents (n-alkanes, isoprenoid hydrocarbons, polycyclic aromatic hydrocarbons, phthalates, levoglucosan and n-alkanoic acids) in PM2.5 were measured to apportion the sources over the study area. Source apportionment of PM2.5 was performed using organic constituents by Positive Matrix Factorization (PMF) and Principal Component Analysis (PCA). Health risk associated with organic pollutants [PAHs and carcinogen BEHP bis(2-ethylhexyl) phthalate] demonstrated the threat of PM2.5 exposure via inhalation. Transport pathways of air masses were evaluated using 3-day backward trajectories and observed that some air masses originated from local sources along with long-range transport which influenced the PAHs concentration during most of the study period over the NCR. PMF and PCA resulted in the five major emission sources [vehicular emissions (32.2%), biomass burning (30%), cooking emissions (16.8%), plastic burning (13.4%), mixed sources (7.6%) including biogenic and industrial emissions] for PM2.5 over the sampling sites. The present study reveals that transport sector is a major source to be targeted to reduce the vehicular emissions and consequent health risks associated with organic pollutants especially PAHs.
The distribution of daytime and nighttime sources of PM10 collected from January to March 2021 at an urban background site in the city of Bragança, Portugal, was performed using positive matrix factorisation (PMF). Additional data of PM2.5, NOx and meteorological variables were collected to support the interpretations. A solution with 5 factor profiles was found: traffic (33%), dust (24%), biomass burning (21%), secondary inorganic aerosol (SIA) (12%) and sea salt (10%). Mean daytime and nighttime PM10 concentrations were 43.1 μg m−3 and 46.1 μg m−3, respectively. Nighttime concentrations were dominated by residential biomass combustion. Vehicle traffic and dust factors showed significantly greater contributions during the day (+12% and +4%, respectively), suggesting that exhaust and non-exhaust emissions and long-range transport are important contributors to daytime PM10 levels. In contrast, there were no significant differences between day and night for SIA and sea salt. Exceedances of the daily limit to PM10 (50 μg m−3) and PM2.5 (15 μg m−3) were observed in 22 (33%) and 27 (40%) days of the campaign, respectively, mostly associated with biomass burning for residential heating, but also with Saharan dust outbreaks. The application of the Aliivibrio fischeri bioluminescence inhibition assay for ecotoxicity assessment allowed classifying 70% of the samples as toxic, especially those from the nocturnal period, indicating that biomass burning is one of the main sources responsible for PM10 toxicity. Both the contributions from biomass burning estimated by the PMF and multiple tracers of this source showed statistically significant correlations with the toxicity units.
Oxidative potential (OP) has been identified as an important factor underlying the health effects of airborne particulate matter (PM). OP denotes the ability of PM to deplete antioxidants and form reactive oxygen species (ROS) in the lung. OP can be quantified using a variety of chemical assays and analytical techniques. Despite the widespread use of various OP metrics, there is no consensus or comprehensive inter-laboratory assessment on how these assays compare. In this work for the first time, we compared 11 OP indicators from acellular assays using standard reference material of urban PM. The OP indicators included ascorbic acid, glutathione, glutathione disulfide, cysteine, cystine, dithiothreitol, H2O2, •OH, O2•-, and empirical and theoretical redox potential of simulated lung lining fluid (SLF). The indicators showed first-order kinetics at low PM concentration (25 μg mL⁻¹), whereas the kinetics were non-linear at higher PM concentrations. The indicators demonstrated mainly linear dose-response relationships at PM concentrations 25–100 μg mL⁻¹, following similar trends with water-soluble transition metals, but they were rarely proportional to PM concentrations, and demonstrated substantial differences in their sensitivities to PM. The results indicate the importance of using reduced reaction time for reliable OP quantification due to non-linearity in assay responses at high PM concentrations. This work shows that the choice of molecular probes and measurement techniques must be carefully considered when planning studies on OP of ambient air and should importantly include the association of OP metrics with health outcomes.
L’alimentation à travers l'ingestion de végétaux contaminés est une source potentiellement importante d'exposition humaine aux hydrocarbures aromatiques polycycliques carbonylés (CO-HAPs). Ce travail de thèse vise à vérifier la présence des CO-HAPs dans les fruits et légumes issus de l’agriculture urbaine.Une stratégie d’analyse permettant la détection de 28 CO-HAPs et la quantification de 12 d’entre-eux à l’état de traces dans les fruits et légumes a été mise au point. Cette stratégie comprend une étape optimisée d’extraction QuEchERS utilisant de l’acétate d’éthyle et un mélange de sels, puis une étape de purification par Extraction en Phase Solide (SPE) au moyen d’une phase stationnaire de type HLB. Les CO-HAPs extraits sont séparés, identifiés et quantifiés par Chromatographie en Phase Gazeuse couplée à la Spectrométrie de Masse (GC-MS). Cette méthodologie offre de bonnes linéarités pour des teneurs dans les fruits et légumes inférieures à 10 g/kg, une bonne fidélité ainsi qu’une sensibilité adaptée à une quantification à l’état de traces (limites de détection comprises entre 0,01 et 2,6 g/kg). Elle ne présente pas d’effet matrice pour une dizaine de végétaux et peut ainsi être transposable à une palette végétale très large.Cette stratégie d’analyse a été appliquée avec succès à différents végétaux issus de jardins potagers urbains localisés en Normandie. Des teneurs relativement faibles en CO-HAPs (excédant rarement 5 µg/kg) sont retrouvées. Une présence globale plus importante en CO-HAPs est observée pour les végétaux possédant les plus grandes surfaces spécifiques permettant d’envisager une contamination majoritairement aérienne. Les concentrations les plus faibles en CO-HAPs ont pu être déterminées pour les sites les plus éloignés d’activités industrielles denses ou d’infrastructures routières importantes. L’exposition de végétaux à trois sources de combustion a permis de montrer une adsorption différente des CO-HAPs selon la nature du végétal ainsi que de proposer certains CO-HAPs comme marqueurs d’exposition pour chacun des processus de combustion étudié.
Receptor models have been widely used for the source apportionment of airborne particulate matter. However, in the last 10 years, the use of factor analysis-based models, such as PMF and UNMIX, has increased significantly. The results yielded by these models must be interpreted by users who must know all variables influencing the modeling, and without this knowledge, the probability of incorrect interpretation of the source profiles may increase, especially when two or more sources have similar chemical profiles. Concerning the quality of data, this work shows that a broad characterization of PM composition, including inorganic, organic, and mineralogical species can improve this process, avoiding misinterpretation and the attribution of mixed or unidentified sources. This work aims to provide readers with some answers for a question often risen during source apportionment studies: Which source markers should be used for better separation and interpretation of source profiles? This review shows there is no right answer for this because different strategies can be used for this purpose. Therefore, this review aims to compile and highlight qualitatively the key strategies already used by several experienced receptor models users, combining the use of inorganic, organic, and mineralogical markers of PM for better separation and interpretation of the profiles yielded by receptor models. Also, this work presents a compilation in tables of the main chemical species reported in the literature as markers for interpreting the source profiles.
Particulate matter is a component of ambient air pollution that has been linked to millions of annual premature deaths globally1–3. Assessments of the chronic and acute effects of particulate matter on human health tend to be based on mass concentration, with particle size and composition also thought to play a part⁴. Oxidative potential has been suggested to be one of the many possible drivers of the acute health effects of particulate matter, but the link remains uncertain5–8. Studies investigating the particulate-matter components that manifest an oxidative activity have yielded conflicting results⁷. In consequence, there is still much to be learned about the sources of particulate matter that may control the oxidative potential concentration⁷. Here we use field observations and air-quality modelling to quantify the major primary and secondary sources of particulate matter and of oxidative potential in Europe. We find that secondary inorganic components, crustal material and secondary biogenic organic aerosols control the mass concentration of particulate matter. By contrast, oxidative potential concentration is associated mostly with anthropogenic sources, in particular with fine-mode secondary organic aerosols largely from residential biomass burning and coarse-mode metals from vehicular non-exhaust emissions. Our results suggest that mitigation strategies aimed at reducing the mass concentrations of particulate matter alone may not reduce the oxidative potential concentration. If the oxidative potential can be linked to major health impacts, it may be more effective to control specific sources of particulate matter rather than overall particulate mass.
Air pollution, in particular high concentrations of particulate matter smaller than 1 µm in diameter (PM1), continues to be a major health problem, and meteorology is known to substantially contribute to atmospheric PM concentrations. However, the scientific understanding of the complex mechanisms leading to high pollution episodes is inconclusive, as the effects of meteorological variables are not easy to separate and quantify. In this study, a novel, data-driven approach based on empirical relationships is used to characterise the role of meteorology on atmospheric concentrations of PM1. A tree-based machine learning model is set up to reproduce concentrations of speciated PM1 at a suburban site southwest of Paris, France, using meteorological variables as input features. The contributions of each meteorological feature to modeled PM1 concentrations are quantified using SHapley Additive exPlanation (SHAP) regression values. Meteorological contributions to PM1 concentrations are analysed in selected high-resolution case studies, contrasting season-specific processes. Model results suggest that winter pollution episodes are often driven by a combination of shallow mixed layer heights (MLH), low temperatures, low wind speeds or inflow from northeastern wind directions. Contributions of MLHs to the winter pollution episodes are quantified to be on average ~ 5 µg/m³ for MLHs below 500 m agl. Temperatures below freezing initiate formation processes and increase local emissions related to residential heating, amounting to a contribution of as much as ~ 9 µg/m³. Northeasterly winds are found to contribute ~ 5 µg/m³ to total PM1 concentrations (combined effects of u- and v-wind components), by advecting particles from source regions, e.g. central Europe or the Paris region. However, in calm conditions (i.e. wind speeds
By understanding the sources and temporal variations of nitrated mono- and di-aromatic hydrocarbons (nitroaromatic hydrocarbons, NAHCs)in ambient particles, we can evaluate their impact on the climate, environment, and human health. This work quantifies (for the first time)a series of NAHCs (3,5-dinitrosalicylic acid, 2,4-dinitro-1-naphthol, 4-nitrophthalic acid, and 2-hydroxy-5-nitrobenzyl alcohol)in ambient particles collected from an urban site in Nagoya, Japan. The data were collected throughout the day/night cycles during the summer and fall of 2013. To evaluate the possible sources of the NAHCs, the observed NAHC concentrations were compared with organic tracers of anthropogenic secondary organic aerosols (ASOAs)and biomass burning. Nitrocatechols were mainly influenced by emissions from biomass burning during the fall, and by secondary formation from anthropogenic volatile organic compounds (AVOCs)during the summer. In both seasons, AVOC oxidation mainly produced nitrosalicylic acids, 4-nitro-1-naphthol, and 4-nitrophthalic acid, whereas biomass burning in the fall produced a significant amount of 4-nitro-1-naphthol. The concentrations of 3,5-dinitrosalicylic acid and 4-nitrophthalic acid were highly correlated with those of other ASOA tracers, and were strongly related to wind direction, oxidant concentration, and solar radiation. Therefore, these NAHCs are suggested as new tracers of ASOA. Meanwhile, although 2-hydroxy-5-nitrobenzyl alcohol was generated by AVOCs photo-oxidation during the day, its concentration remained high at night, indicating additional nighttime sources such as nitrate radical reactions. Our results suggest that different NAHCs could have different sources, large seasonal and day-to-night variations in their major ones.
La pollution due aux particules (aérosols, PM) présentes dans l’air ambiant est une problématique sanitaire primordiale. La connaissance et l’évaluation de leurs sources sont un enjeu majeur en termes de politiques de gestion de la qualité de l’air. Les travaux menés par l’Ineris, cofinancés par le LCSQA, ont permis de montrer qu’à travers une spéciation fine de la fraction organique de l’aérosol (aérosol organique, AO), et par la mesure de composés clés dits « marqueurs », une évaluation approfondie des sources des particules, incluant des sources primaires ou secondaires généralement non résolues, est réalisable.
PM10 source apportionment was performed by positive matrix factorization (PMF) using specific primary and secondary organic molecular markers on samples collected over a one year period (2013) at an urban station in Grenoble (France). The results provided a 9-factor optimum solution, including sources rarely apportioned in the literature, such as two types of primary biogenic organic aerosols (fungal spores and plant debris), as well as specific biogenic and anthropogenic secondary organic aerosols (SOA). These sources were identified thanks to the use of key organic markers, namely, polyols, odd number higher alkanes, and several SOA markers related to the oxidation of isoprene, α-pinene, toluene and polycyclic aromatic hydrocarbons (PAHs). Primary and secondary biogenic contributions together accounted for at least 68% of the total organic carbon (OC) in the summer, while anthropogenic primary and secondary sources represented at least 71% of OC during wintertime. A very significant contribution of anthropogenic SOA was estimated in the winter during an intense PM pollution event (PM10>50μgm-3 for several days; 18% of PM10 and 42% of OC). Specific meteorological conditions with a stagnation of pollutants over 10days and possibly Fenton-like chemistry and self-amplification cycle of SOA formation could explain such high anthropogenic SOA concentrations during this period. Finally, PMF outputs were also used to investigate the origins of humic-like substances (HuLiS), which represented 16% of OC on an annual average basis. The results indicated that HuLiS were mainly associated with biomass burning (22%), secondary inorganic (22%), mineral dust (15%) and biogenic SOA (14%) factors. This study is probably the first to state that HuLiS are significantly associated with mineral dust.
Positive Matrix Factorization (PMF), Secondary PAH factor
The present study aims at identifying and apportioning fine aerosols to their major sources in Paris (France) – the second most populated "larger urban zone" in Europe – and determining their geographical origins. It is based on the daily chemical composition of PM2.5 examined over 1 year at an urban background site of Paris (Bressi et al., 2013). Positive matrix factorization (EPA PMF3.0) was used to identify and apportion fine aerosols to their sources; bootstrapping was performed to determine the adequate number of PMF factors, and statistics (root mean square error, coefficient of determination, etc.) were examined to better model PM2.5 mass and chemical components. Potential source contribution function (PSCF) and conditional probability function (CPF) allowed the geographical origins of the sources to be assessed; special attention was paid to implement suitable weighting functions. Seven factors, namely ammonium sulfate (A.S.)-rich factor, ammonium nitrate (A.N.)-rich factor, heavy oil combustion, road traffic, biomass burning, marine aerosols and metal industry, were identified; a detailed discussion of their chemical characteristics is reported. They contribute 27, 24, 17, 14, 12, 6 and 1% of PM2.5 mass (14.7 μg m−3) respectively on the annual average; their seasonal variability is discussed. The A.S.- and A.N.-rich factors have undergone mid- or long-range transport from continental Europe; heavy oil combustion mainly stems from northern France and the English Channel, whereas road traffic and biomass burning are primarily locally emitted. Therefore, on average more than half of PM2.5 mass measured in the city of Paris is due to mid- or long-range transport of secondary aerosols stemming from continental Europe, whereas local sources only contribute a quarter of the annual averaged mass. These results imply that fine-aerosol abatement policies conducted at the local scale may not be sufficient to notably reduce PM2.5 levels at urban background sites in Paris, suggesting instead more coordinated strategies amongst neighbouring countries. Similar conclusions might be drawn in other continental urban background sites given the transboundary nature of PM2.5 pollution.
Various receptor methodologies have been developed in the last decades to investigate the geographical origins of atmospheric pollution, based either on wind data or on backtrajectory analyses. To date, only few software packages exist to make use of one or the other approach. We present here ZeFir, an Igor-based package specifically designed to achieve a comprehensive geographical origin analysis using a single statistical tool. ZeFir puts the emphasis on a user-friendly experience in order to facilitate and speed up working time. Key parameters can be easily controlled, and unique innovative features bring geographical origins work to another level.
Thermal-optical analysis is a conventional method for determining the
carbonaceous aerosol fraction and for classifying it into organic carbon,
OC, and elemental carbon, EC. Unfortunately, the different thermal evolution
protocols in use can result in a wide elemental carbon-to-total carbon
variation by up to a factor of five. In Europe, there is currently no
standard procedure for determining the carbonaceous aerosol fraction which
implies that data from different laboratories at various sites are of
unknown accuracy and cannot be considered comparable. In the framework of
the EU-project EUSAAR (European Supersites for Atmospheric Aerosol
Research), a comprehensive study has been carried out to identify the causes
of differences in the EC measured using different thermal evolution
protocols; thereby the major positive and negative biases affecting
thermal-optical analysis have been isolated and minimised to define an
optimised protocol suitable for European aerosols. Our approach to improve
the accuracy of the discrimination between OC and EC was essentially based
on four goals. Firstly, charring corrections rely on faulty assumptions –
e.g. pyrolytic carbon is considered to evolve completely before native EC
throughout the analysis –, thus we have reduced pyrolysis to a minimum by
favoring volatilisation of OC. Secondly, we have minimised the potential
negative bias in EC determination due to early evolution of light absorbing
carbon species at higher temperatures in the He-mode, including both native
EC and combinations of native EC and pyrolytic carbon potentially with
different specific attenuation cross section values. Thirdly, we have
minimised the potential positive bias in EC determination resulting from the
incomplete evolution of OC during the He-mode which then evolves during the
He/O2-mode, potentially after the split point. Finally, we have
minimised the uncertainty due to the position of the OC/EC split point on
the FID response profile by introducing multiple desorption steps in the
He/O2-mode. Based on different types of carbonaceous PM encountered
across Europe, we have defined an optimised thermal evolution protocol, the
EUSAAR_2 protocol, as follows: step 1 in He, 200 °C for 120 s; step 2
in He 300 °C for 150 s; step 3 in He 450 °C for 180 s; step 4 in He
650 °C for 180 s. For steps 1–4 in He/O2, the conditions are
500 °C for 120 s, 550 °C for 120 s, 700 ° C for 70 s,
and 850 °C for 80 s, respectively.
Aerosol Mass Spectrometer (AMS) measurements have been successfully used
towards a better understanding of non-refractory submicron (PM1)
aerosol chemical properties based on short-term campaign. The recently
developed Aerosol Chemical Speciation Monitor (ACSM) has been designed to
deliver quite similar artefact-free chemical information but for low-cost,
and to perform robust monitoring over long-term period. When deployed in
parallel with real-time Black Carbon (BC) measurements, the combined dataset
allows for a quasi-comprehensive description of the whole PM1
fraction in near real-time. Here we present a 2 year long ACSM and BC
datasets, between mid-2011 and mid-2013, obtained at the French atmospheric
SIRTA supersite being representative of background PM levels of the region of
Paris. This large dataset shows intense and time limited (few hours)
pollution events observed during wintertime in the region of Paris pointing
to local carbonaceous emissions (mainly combustion sources). A non-parametric
wind regression analysis was performed on this 2 year dataset for the major
PM1 constituents (organic matter, nitrate, sulphate and source
apportioned BC) and ammonia in order to better refine their geographical
origins and assess local/regional/advected contributions which information
are mandatory for efficient mitigation strategies. While ammonium sulphate
typically shows a clear advected pattern, ammonium nitrate partially displays
a similar feature, but less expected, it also exhibits a significant
contribution of regional and local emissions. Contribution of regional
background OA is significant in spring and summer while a more pronounced
local origin is evidenced during wintertime which pattern is also observed
for BC originating from domestic wood burning. Using time-resolved ACSM and
BC information, seasonally differentiated weekly diurnal profiles of these
constituents were investigated and helped to identify the main parameters
controlling their temporal variations (sources, meteorological parameters).
Finally, a careful investigation of all the major pollution episodes observed
over the region of Paris between 2011 and 2013 was performed and classified
in terms of chemical composition and BC-to-sulphate ratio used here as
a proxy of the local/regional vs. advected contribution of PM. In conclusion,
these first 2 year quality-controlled measurements of ACSM clearly
demonstrate their great potential to monitor on a long term basis aerosol
sources and their geographical origin and provide strategic information in
near real-time during pollution episodes. They also support the capacity of
the ACSM to be proposed as a robust and credible alternative to filter-based
sampling techniques for long term monitoring strategies.
The monosaccharide anhydrides (MAs) levoglucosan, galactosan and mannosan are products of
incomplete combustion and pyrolysis of cellulose and hemicelluloses, and are found to be major
constituents of biomass burning aerosol particles. Hence, ambient aerosol particle concentrations
of levoglucosan are commonly used to study the influence of residential wood burning, agricultural
waste burning and wild fire emissions on ambient air quality. A European-wide intercomparison on
the analysis of the three monosaccharide anhydrides was conducted based on ambient aerosol quartz
fiber filter samples collected at a Norwegian urban background site during winter. Thus, the
samples' content of MAs is representative for biomass burning particles originating from
residential wood burning. The purpose of the intercomparison was to examine the comparability of
the great diversity of analytical methods used for analysis of levoglucosan, mannosan and
galactosan in ambient aerosol filter samples. Thirteen laboratories participated, of which three
applied High-Performance Anion-Exchange Chromatography (HPAEC), four used High-Performance Liquid
Chromatography (HPLC) or Ultra-Performance Liquid Chromatography (UPLC), and six resorted to Gas
Chromatography (GC). The analytical methods used were of such diversity that they should be
considered as thirteen different analytical methods. All of the thirteen laboratories reported
levels of levoglucosan, whereas nine reported data for mannosan and/or galactosan. Eight of the
thirteen laboratories reported levels for all three isomers.
The accuracy for levoglucosan, presented as the mean percentage error (PE) for each participating
laboratory, varied from −63 to 23%; however, for 62% of the laboratories the
mean PE was within ±10%, and for 85% the mean PE was within ±20%. For
mannosan, the corresponding range was −60 to 69%, but as for levoglucosan, the range
was substantially smaller for a subselection of the laboratories; i.e., for 33% of the
laboratories the mean PE was within ±10%. For galactosan, the mean PE for the
participating laboratories ranged from −84 to 593%, and as for mannosan 33% of
the laboratories reported a mean PE within ±10%.
The variability of the various analytical methods, as defined by their minimum and maximum PE
value, was typically better for levoglucosan than for mannosan and galactosan, ranging from 3.2 to
41% for levoglucosan, from 10 to 67% for mannosan, and from 6 to 364% for
galactosan. For the levoglucosan to mannosan ratio, which may be used to assess the relative
importance of softwood vs. hardwood burning, the variability only ranged from 3.5 to
24%.
To our knowledge, this is the first major intercomparison on analytical methods used to quantify
monosaccharide anhydrides in ambient aerosol filter samples conducted and reported in the
scientific literature. The results show that for levoglucosan the accuracy is only slightly lower
than that reported for analysis of SO42− on filter samples, a constituent that has been
analyzed by numerous laboratories for several decades, typically by ion chromatography, and which
is considered a fairly easy constituent to measure. Hence, the results obtained for levoglucosan
with respect to accuracy are encouraging and suggest that levels of levoglucosan, and to a lesser
extent mannosan and galactosan, obtained by most of the analytical methods currently used to
quantify monosaccharide anhydrides in ambient aerosol filter samples, are comparable.
Finally, the various analytical methods used in the current study should be tested for other
aerosol matrices and concentrations as well, the most obvious being summertime aerosol samples
affected by wild fires and/or agricultural fires.
Secondary organic aerosol (SOA), a predominant fraction of particulate organic mass (OA), remains poorly constrained. Its formation involves several unknown precursors, formation and evolution pathways and multiple natural and anthropogenic sources. Here a combined gas-particle phase source apportionment is applied to wintertime and summertime data collected in the megacity of Paris in order to investigate SOA origin during both seasons. This was possible by combining the information provided by an aerosol mass spectrometer (AMS) and a proton transfer reaction mass spectrometer (PTR-MS). A better constrained apportionment of primary OA (POA) sources is also achieved using this methodology, making use of gas-phase tracers. These tracers allowed distinguishing between biogenic and continental/anthropogenic sources of SOA. We found that continental SOA was dominant during both seasons (24–50% of total OA), while contributions from photochemistry-driven SOA (9% of total OA) and marine emissions (13% of total OA) were also observed during summertime. A semi-volatile nighttime component was also identified (up to 18% of total OA during wintertime). This approach was successfully applied here and implemented in a new source apportionment toolkit.
Vehicular emissions are a key source of polycyclic aromatic compounds (PACs), including polycyclic aromatic hydrocarbons (PAHs) and their oxygenated (OPAH) and nitrated (NPAH) derivatives, in the urban environment. Road tunnels are a useful environment for the characterisation of on-road vehicular emissions, providing a realistic traffic fleet and a lack of direct sunlight, chemical reactivity and non-traffic sources. In the present investigation the concentrations of selected PAHs, OPAHs and NPAHs have been measured in the Parc des Princes Tunnel in Paris (PdPT, France), and at the Queensway Road Tunnel and an urban background site in Birmingham (QT, U.K). A higher proportion of semi-volatile (3-4 ring) PAH, OPAH and NPAH compounds are associated with the particulate phase compared with samples from the ambient environment. A large (~85%) decline in total PAH concentrations is observed between 1992 and 2012 measurements in QT. This is attributed primarily to the introduction of catalytic converters in the U.K as well as increasingly stringent EU vehicle emissions legislation. In contrast, NPAH concentrations measured in 2012 are similar to those measured in 1996. This observation, in addition to an increased proportion of (Phe+Flt+Pyr) in the observed PAH burden in the tunnel, is attributed to the increased number of diesel passenger vehicles in the U.K during this period. Except for OPAHs, comparable PAH and NPAH concentrations are observed in both investigated tunnels (QT and PdP). Significant differences are shown for specific substances between PAC chemical profiles in relation with the national traffic fleet differences (33% diesel passenger cars in U.K. vs 69% in France and up to 80% taking into account all vehicle categories). The dominating and sole contribution of 1-Nitropyrene observed in the PdPT NPAH profile strengthens the promising use of this compound as a diesel exhaust marker for PM source apportionment studies.
Organic gases undergoing conversion to form secondary organic aerosol (SOA) during atmospheric aging are largely unidentified, particularly in regions influenced by anthropogenic emissions. SOA dominates the atmospheric organic aerosol burden and this knowledge gap contributes to uncertainties in aerosol effects on climate and human health. Here we characterize primary and aged emissions from residential wood combustion using high resolution mass spectrometry to identify SOA precursors. We determine that SOA precursors traditionally included in models account for only ~3–27% of the observed SOA, whereas for the first time we explain ~84–116% of the SOA by inclusion of non-traditional precursors. Although hundreds of organic gases are emitted during wood combustion, SOA is dominated by the aging products of only 22 compounds. In some cases, oxidation products of phenol, naphthalene and benzene alone comprise up to ~80% of the observed SOA. Identifying the main precursors responsible for SOA formation enables improved model parameterizations and SOA mitigation strategies in regions impacted by residential wood combustion, more productive targets for ambient monitoring programs and future laboratories studies, and links between direct emissions and SOA impacts on climate and health in these regions.
The AIRUSE-LIFE+ project aims at characterizing similarities and
heterogeneities in particulate matter (PM) sources and contributions in urban
areas from southern Europe. Once the main PMx sources are identified, AIRUSE
aims at developing and testing the efficiency of specific and non-specific
measures to improve urban air quality. This article reports the results of
the source apportionment of PM10 and PM2.5 conducted at three urban
background sites (Barcelona, Florence and Milan, BCN-UB, FI-UB and MLN-UB),
one suburban background site (Athens, ATH-SUB) and one traffic site (Porto,
POR-TR). After collecting 1047 PM10 and 1116 PM2.5 24 h samples
during 12 months (from January 2013 on) simultaneously at the five cities,
these were analysed for the contents of OC, EC, anions, cations, major and
trace elements and levoglucosan. The USEPA PMF5 receptor model was applied to
these data sets in a harmonized way for each city.
The sum of vehicle exhaust (VEX) and non-exhaust (NEX) contributes between
3.9 and 10.8 µg m−3 (16–32 %) to PM10 and 2.3 and
9.4 µg m−3 (15–36 %) to PM2.5, although a fraction of
secondary nitrate is also traffic-related but could not be estimated.
Important contributions arise from secondary particles (nitrate, sulfate and
organics) in PM2.5 (37–82 %) but also in PM10 (40–71 %),
mostly at background sites, revealing the importance of abating gaseous
precursors in designing air quality plans.
Biomass burning (BB) contributions vary widely, from 14–24 % of PM10
in POR-TR, MLN-UB and FI-UB, 7 % in ATH-SUB, to < 2 % in BCN-UB. In
PM2.5, BB is the second most important source in MLN-UB (21 %) and in
POR-TR (18 %), the third one in FI-UB (21 %) and ATH-SUB (11 %), but is
again negligible (< 2 %) in BCN-UB. This large variability among cities
is mostly due to the degree of penetration of biomass for residential
heating. In Barcelona natural gas is very well supplied across the city and
is used as fuel in 96 % of homes, while in other cities, PM levels increase
on an annual basis by 1–9 µg m−3 due to biomass burning
influence. Other significant sources are the following.
– Local dust, 7–12 % of PM10 at SUB and UB sites and 19 % at the TR
site, revealing a contribution from road dust resuspension. In PM2.5
percentages decrease to 2–7 % at SUB-UB sites and 15 % at the TR site.
– Industry, mainly metallurgy, contributing 4–11 % of PM10 (5–12 % in
PM2.5), but only at BCN-UB, POR-TR and MLN-UB. No clear impact of industrial
emissions was found in FI-UB and ATH-SUB.
– Natural contributions from sea salt (13 % of PM10 in POR-TR, but only
2–7 % in the other cities) and Saharan dust (14 % in ATH-SUB, but less
than 4 % in the other cities).
During high pollution days, the largest sources (i.e. excluding secondary
aerosol factors) of PM10 and PM2.5 are VEX + NEX in
BCN-UB (27–22 %) and POR-TR (31–33 %), BB in FI-UB (30–33 %) and
MLN-UB (35–26 %) and Saharan dust in ATH-SUB (52–45 %). During those
days, there are also quite important industrial contributions in
BCN-UB (17–18 %) and local dust in POR-TR (28–20 %).
Air quality monitoring for Kanpur in North India, an industrial city ranked among the top ten most polluted cities worldwide, was conducted in summer 2011. Airborne particulate matter (PM) sample from six locations were analyzed for metals. Source identification conducted using metals as source markers reveals probable sources of airborne particles being vehicular emissions, industrial, and railway activity. Findings were substantiated by investigating morphological characteristics and elemental composition of PM using SEM-EDX analysis at three major sites. In addition to confirmation of results by metal marker method, SEM-EDX analysis revealed presence of sulphur (S) which highlights influence of Panki Thermal Power Plant on air quality. The study shows that high levels of metals observed in airborne particles at major intersections may pose a significant cancer risk by exposure to toxics such as Cr, Pb and Ni.
The performance and the uncertainty of receptor models (RMs) were assessed in intercomparison exercises employing real-world and synthetic input datasets. To that end, the results obtained by different practitioners using ten different RMs were compared with a reference. In order to explain the differences in the performances and uncertainties of the different approaches, the apportioned mass, the number of sources, the chemical profiles, the contribution-to-species and the time trends of the sources were all evaluated using the methodology described in Belis et al. (2015).
A PM10 sampling campaign was carried out on board the cruise ship Costa Concordia during three weeks in summer 2011. The ship route was Civitavecchia-Savona-Barcelona-Palma de Mallorca-Malta (Valletta)-Palermo-Civitavecchia. The PM10 composition was measured and utilized to identify and characterize the main PM10 sources along the ship route through receptor modelling, making use of the Positive Matrix Factorization (PMF) algorithm. A particular attention was given to the emissions related to heavy fuel oil combustion by ships, which is known to be also an important source of secondary sulphate aerosol. Five aerosol sources were resolved by the PMF analysis. The primary contribution of ship emissions to PM10 turned out to be (12 ± 4)%, while secondary ammonium sulphate contributed by (35 ± 5)%. Approximately, 60% of the total sulphate was identified as secondary aerosol while about 20% was attributed to heavy oil combustion in ship engines. The measured concentrations of methanesulphonic acid (MSA) indicated a relevant contribution to the observed sulphate loading by biogenic sulphate, formed by the atmospheric oxidation of dimethyl sulphide (DMS) emitted by marine phytoplankton.
Chemically resolved atmospheric aerosol data sets from the largest intercomparison of the Aerodyne aerosol chemical speciation monitors (ACSMs) performed to date were collected at the French atmospheric supersite SIRTA. In total 13 quadrupole ACSMs (Q-ACSM) from the European ACTRIS ACSM network, one time-of-flight ACSM (ToF-ACSM), and one high-resolution ToF aerosol mass spectrometer (AMS) were operated in parallel for about 3 weeks in November and December~2013. Part 1 of this study reports on the accuracy and precision of the instruments for all the measured species. In this work we report on the intercomparison of organic components and the results from factor analysis source apportionment by positive matrix factorisation (PMF) utilising the multilinear engine 2 (ME-2). Except for the organic contribution of mass-to-charge ratio m/z 44 to the total organics (f44), which varied by factors between 0.6 and 1.3 compared to the mean, the peaks in the organic mass spectra were similar among instruments. The m/z 44 differences in the spectra resulted in a variable f44 in the source profiles extracted by ME-2, but had only a minor influence on the extracted mass contributions of the sources. The presented source apportionment yielded four factors for all 15 instruments: hydrocarbon-like organic aerosol (HOA), cooking-related organic aerosol (COA), biomass burning-related organic aerosol (BBOA) and secondary oxygenated organic aerosol (OOA). ME-2 boundary conditions (profile constraints) were optimised individually by means of correlation to external data in order to achieve equivalent / comparable solutions for all ACSM instruments and the results are discussed together with the investigation of the influence of alternative anchors (reference profiles). A comparison of the ME-2 source apportionment output of all 15 instruments resulted in relative standard deviations (SD) from the mean between 13.7 and 22.7 % of the source's average mass contribution depending on the factors (HOA: 14.3 ± 2.2 %, COA: 15.0 ± 3.4 %, OOA: 41.5 ± 5.7 %, BBOA: 29.3 ± 5.0 %). Factors which tend to be subject to minor factor mixing (in this case COA) have higher relative uncertainties than factors which are recognised more readily like the OOA. Averaged over all factors and instruments the relative first SD from the mean of a source extracted with ME-2 was 17.2 %.
Forty seven years of weekly total suspended particle filters collected at Kevo, Finland from October 1964 through 2010 by the Finnish Meteorological Institute were analyzed for near-total trace elements, soluble trace elements, black carbon, major ions and methane sulfonic acid (MSA). The chemical composition dataset was analyzed by Positive Matrix Factorization using EPA PMF5. The entire dataset (1964–2010) was modeled as well as three separate time periods, 1964–1978, 1979–1990, and 1991–2010. The dataset was split in 1979 due to a change from Whatman 42 cellulose filters to a glass fiber filters, and in 1990 due to drops in concentrations related to the economic collapse of the Soviet Union. Two factors representing non-ferrous metal smelters were found for all time periods. One factor was dominated by Cu and the other by Ni and Co. Each of the time periods contained a factor describing stationary fuel combustion with high percentages of V, BC, and nss-SO4=; a ferrous metal factor dominated by Fe and some Mn; a biogenic sulfate factor; a factor containing the majority of Mo and W; and a factor dominated by Sn. The 1979–1990, 1991–2010, and 1964–2010 results contained a factor for As and Re, and a factor with the majority of Mn and Cd, which were not observed in 1964–1978. The 1964–1978 time period results contain three unique factors, a factor dominated by Ag, a factor dominated by Au, and a sea salt factor characterized by a high percentage of Na and Mg. The 1964–2010 period contains an Ag and Au factor as well. Ag and Au both have high concentrations in the late 1960s that decrease dramatically starting in the early 1970s. The increased uncertainty due to the high blanks in the glass fiber filters may account for the inability to determine a sea salt factor in the later time periods.
Aerosol black carbon is a unique primary tracer for
emissions. It affects the optical properties of the
atmosphere and is recognized as the second most important
anthropogenic forcing agent for climate change. It is the primary
tracer for adverse health effects caused by air pollution.
For the accurate determination of mass equivalent black carbon
concentrations in the air and for source apportionment of
the concentrations, optical measurements by filter-based absorption
photometers must take into account the “filter loading
effect”. We present a new real-time loading effect compensation
algorithm based on a two parallel spot measurement
of optical absorption. This algorithm has been incorporated
into the new Aethalometer model AE33. Intercomparison
studies show excellent reproducibility of the AE33 measurements
and very good agreement with post-processed data
obtained using earlier Aethalometer models and other filterbased
absorption photometers. The real-time loading effect
compensation algorithm provides the high-quality data necessary
for real-time source apportionment and for determination
of the temporal variation of the compensation parameter k.
A review of the techniques concerning the Molecular Identification of Organic Compounds in the Atmosphere is presented. An organic compound is fully identified only if its molecular structure is entirely known, including its isomeric and spatial (stereo) configuration. The first type of problem is when organic compounds need to be inventoried for the purpose of establishing a budget. Generally, such budgets are required to gain insights into specific properties of the compounds, such as their optical properties for the global energy budget or their volatility for SOA precursors. In such cases, the organic compounds do not need to be individually identified, but only quantified on the basis of this common property.
The monosaccharide anhydrides (MAs) levoglucosan, galactosan and mannosan are products of incomplete combustion and pyrolysis of cellulose and hemicelluloses, and are found to be major constituents of biomass burning (BB) aerosol particles. Hence, ambient aerosol particle concentrations of levoglucosan are commonly used to study the influence of residential wood burning, agricultural waste burning and wildfire emissions on ambient air quality. A European-wide intercomparison on the analysis of the three monosaccharide anhydrides was conducted based on ambient aerosol quartz fiber filter samples collected at a Norwegian urban background site during winter. Thus, the samples' content of MAs is representative for BB particles originating from residential wood burning. The purpose of the intercomparison was to examine the comparability of the great diversity of analytical methods used for analysis of levoglucosan, mannosan and galactosan in ambient aerosol filter samples. Thirteen laboratories participated, of which three applied high-performance anion-exchange chromatography (HPAEC), four used high-performance liquid chromatography (HPLC) or ultra-performance liquid chromatography (UPLC) and six resorted to gas chromatography (GC). The analytical methods used were of such diversity that they should be considered as thirteen different analytical methods. All of the thirteen laboratories reported levels of levoglucosan, whereas nine reported data for mannosan and/or galactosan. Eight of the thirteen laboratories reported levels for all three isomers.
The accuracy for levoglucosan, presented as the mean percentage error (PE) for each participating laboratory, varied from g'63 to 20%; however, for 62% of the laboratories the mean PE was within ±10%, and for 85% the mean PE was within ±20%. For mannosan, the corresponding range was g'60 to 69%, but as for levoglucosan, the range was substantially smaller for a subselection of the laboratories; i.e. for 33% of the laboratories the mean PE was within ±10%. For galactosan, the mean PE for the participating laboratories ranged from g'84 to 593%, and as for mannosan 33% of the laboratories reported a mean PE within ±10%.
The variability of the various analytical methods, as defined by their minimum and maximum PE value, was typically better for levoglucosan than for mannosan and galactosan, ranging from 3.2 to 41% for levoglucosan, from 10 to 67% for mannosan and from 6 to 364% for galactosan. For the levoglucosan to mannosan ratio, which may be used to assess the relative importance of softwood versus hardwood burning, the variability only ranged from 3.5 to 24 .
To our knowledge, this is the first major intercomparison on analytical methods used to quantify monosaccharide anhydrides in ambient aerosol filter samples conducted and reported in the scientific literature. The results show that for levoglucosan the accuracy is only slightly lower than that reported for analysis of SO42-(sulfate) on filter samples, a constituent that has been analysed by numerous laboratories for several decades, typically by ion chromatography and which is considered a fairly easy constituent to measure. Hence, the results obtained for levoglucosan with respect to accuracy are encouraging and suggest that levels of levoglucosan, and to a lesser extent mannosan and galactosan, obtained by most of the analytical methods currently used to quantify monosaccharide anhydrides in ambient aerosol filter samples, are comparable.
Finally, the various analytical methods used in the current study should be tested for other aerosol matrices and concentrations as well, the most obvious being summertime aerosol samples affected by wildfires and/or agricultural fires.
Online non-refractory submicron aerosol mass spectrometer (AMS) measurements
in urban areas have successfully allowed the apportionment of specific
sources and/or physical and chemical properties of the organic fraction.
However, in order to be fully representative of PM pollution, a
comprehensive source apportionment analysis is needed by taking into account
all major components of submicron aerosols, creating strengthened bonds
between the organic components and pollution sources. We present here a
novel two-step methodology to perform such an analysis, by taking advantage
of high time resolution of monitoring instruments: the aerosol chemical
speciation monitor (ACSM) and the multi-wavelength absorption measurements
(Aethalometer AE31) in Paris, France. As a first step, organic aerosols (OA)
were deconvolved to hydrocarbon-like OA (HOA), biomass burning OA (BBOA)
and oxygenated OA (OOA) with positive matrix factorization (PMF), and black carbon
was deconvolved into its wood burning and fossil fuel combustion fractions.
A second PMF analysis was then carried out with organic factors, BC
fractions and inorganic species (nitrate, sulfate, ammonium, chloride),
leading to a four-factor solution allowing highly time-resolved
characterization of the major sources of PM1. Outputs of this
PMF2 include two dominant combustion sources (wood burning
and traffic) as well as semi-volatile and low-volatile secondary aerosols.
While HOA is found to be emitted by both wood burning and traffic, the
latter sources occurred to significantly contribute also to OOA.
The present study aims at identifying and apportioning fine aerosols to their major sources in Paris (France) – the second most populated "larger urban zone" in Europe – and determining their geographical origins. It is based on the daily chemical composition of PM2.5 examined over 1 year at an urban background site of Paris (Bressi et al., 2013). Positive matrix factorization (EPA PMF3.0) was used to identify and apportion fine aerosols to their sources; bootstrapping was performed to determine the adequate number of PMF factors, and statistics (root mean square error, coefficient of determination, etc.) were examined to better model PM2.5 mass and chemical components. Potential source contribution function (PSCF) and conditional probability function (CPF) allowed the geographical origins of the sources to be assessed; special attention was paid to implement suitable weighting functions. Seven factors, namely ammonium sulfate (A.S.)-rich factor, ammonium nitrate (A.N.)-rich factor, heavy oil combustion, road traffic, biomass burning, marine aerosols and metal industry, were identified; a detailed discussion of their chemical characteristics is reported. They contribute 27, 24, 17, 14, 12, 6 and 1% of PM2.5 mass (14.7 μg m−3) respectively on the annual average; their seasonal variability is discussed. The A.S.- and A.N.-rich factors have undergone mid- or long-range transport from continental Europe; heavy oil combustion mainly stems from northern France and the English Channel, whereas road traffic and biomass burning are primarily locally emitted. Therefore, on average more than half of PM2.5 mass measured in the city of Paris is due to mid- or long-range transport of secondary aerosols stemming from continental Europe, whereas local sources only contribute a quarter of the annual averaged mass. These results imply that fine-aerosol abatement policies conducted at the local scale may not be sufficient to notably reduce PM2.5 levels at urban background sites in Paris, suggesting instead more coordinated strategies amongst neighbouring countries. Similar conclusions might be drawn in other continental urban background sites given the transboundary nature of PM2.5 pollution.
Aerosol black carbon is a unique primary tracer for combustion emissions. It affects the optical properties of the atmosphere and is recognized as the second most important anthropogenic forcing agent for climate change. It is the primary tracer for adverse health effects caused by air pollution. For the accurate determination of mass equivalent black carbon concentrations in the air and for source apportionment of the concentrations, optical measurements by filter-based absorption photometers must take into account the "filter loading effect". We present a new real-time loading effect compensation algorithm based on a two parallel spot measurement of optical absorption. This algorithm has been incorporated into the new Aethalometer model AE33. Intercomparison studies show excellent reproducibility of the AE33 measurements and very good agreement with post-processed data obtained using earlier Aethalometer models, and other filter-based absorption photometers. The real-time loading effect compensation algorithm provides the high-quality data necessary for real-time source apportionment, and for determination of the temporal variation of the compensation parameter k.
Aerosol mass spectrometer (AMS) measurements have been successfully used towards a better
understanding of non-refractory submicron (PM1) aerosol chemical
properties based on short-term campaigns. The recently developed Aerosol
Chemical Speciation Monitor (ACSM) has been designed to deliver quite similar
artifact-free chemical information but for low cost, and to perform robust
monitoring over long-term periods. When deployed in parallel with real-time
black carbon (BC) measurements, the combined data set allows for a
quasi-comprehensive description of the whole PM1 fraction in near real
time. Here we present 2-year long ACSM and BC data sets, between mid-2011 and
mid-2013, obtained at the French atmospheric SIRTA supersite that is
representative of background PM levels of the region of Paris. This large
data set shows intense and time-limited (a few hours) pollution events
observed during wintertime in the region of Paris, pointing to local
carbonaceous emissions (mainly combustion sources). A non-parametric wind
regression analysis was performed on this 2-year data set for the major
PM1 constituents (organic matter, nitrate, sulfate and source apportioned BC) and ammonia in order to better
refine their geographical origins and assess local/regional/advected
contributions whose information is mandatory for efficient mitigation strategies. While ammonium
sulfate typically shows a clear advected pattern, ammonium nitrate partially
displays a similar feature, but, less expectedly, it also exhibits a
significant contribution of regional and local emissions. The contribution of
regional background organic aerosols (OA) is
significant in spring and summer, while a more pronounced local origin is
evidenced during wintertime, whose pattern is also observed for BC
originating from domestic wood burning. Using time-resolved ACSM and BC
information, seasonally differentiated weekly diurnal profiles of these
constituents were investigated and helped to identify the main parameters
controlling their temporal variations (sources, meteorological parameters).
Finally, a careful investigation of all the major pollution episodes observed
over the region of Paris between 2011 and 2013 was performed and classified
in terms of chemical composition and the BC-to-sulfate ratio used here as a
proxy of the local/regional/advected contribution of PM. In conclusion, these
first 2-year quality-controlled measurements of ACSM clearly demonstrate
their great potential to monitor on a long-term basis aerosol sources and
their geographical origin and provide strategic information in near real time
during pollution episodes. They also support the capacity of the ACSM to be
proposed as a robust and credible alternative to filter-based sampling
techniques for long-term monitoring strategies.
Two intensive PM10 sampling campaigns were performed in the summers of 2009 and 2010 on the ship Costa Pacifica during cruises in the Western Mediterranean. Samples, mainly collected on an hourly basis, were analysed with different techniques (Particle Induced X-Ray Emission, PIXE; Energy Dispersive - X Ray Fluorescence, ED-XRF; Ion Chromatography, IC; Thermo-optical analysis) to retrieve the PM10 composition and its time pattern. The data were used for obtaining information about the sources of aerosol, with a focus on ship emissions, through apportionment using chemical marker compounds, correlation analysis and Positive Matrix Factorization (PMF) receptor modelling. For the campaign in 2010, 66% of the aerosol sulphate was found to be anthropogenic, only minor contributions of dust and sea salt sulphate were observed while the biogenic contribution, estimated based on the measurements of MSA, was found to be more important (26%), but influenced by large uncertainties. V and Ni were found to be suitable tracers of ship emissions during the campaigns. Four sources of aerosol were resolved by the PMF analysis; the source having the largest impact on PM10, BC and sulphate was identified as a mixed source, comprising emissions from ships. The correlations between sulphate and V and Ni showed the influence of ship emissions on sulphate in marine air masses. For the leg Palma–Tunis crossing a main ship route, the correlations between aerosol sulphate and V and Ni were particularly strong (r2 = 0.9 for both elements).
The formation of ozone and secondary organic aerosol (SOA) from benzene–NO x and ethylbenzene–NOx irradiations was investigated under different levels of relative humidity (RH) in a smog chamber. In benzene and ethylbenzene irradiations, the intensity of the bands of O‐H, CO, C‐O, and C‐OH from SOA samples all greatly increased with increasing RH. The major substances in SOA were determined to be carboxylic acids and glyoxal hydrates. It was also found that SOA contained aromatic products, and NO2- and ONO2-containing products. The results show that the increase in RH can greatly reduce the maximum O3 by the transfer of NO2- and ONO2-containing products into the particle phase. During the process of evaporation, the lost substances from the collected SOA have similar structures for both benzene and ethylbenzene. This demonstrates that ethyl-containing substances are very stable and difficult to evaporate. For benzene, some of glyoxal hydrates were left to form C‐O‐C- and CO-containing species like hemiacetal and acetal after evaporation, whereas for ethylbenzene, glyoxal favored cross reactions with ethylglyoxal during evaporation. Only a few species in SOA were released into the gas phase during evaporation while a large part of SOA remained, which is mainly composed of carboxylic acid. It is concluded that the aqueous radical reactions and the hydration from glyoxal can be enhanced under high RH conditions, which can irreversibly enhance the formation of SOA from both benzene and ethylbenzene.Copyright 2014 American Association for Aerosol Research
In this work, the source of ambient particulate matter (PM10)
collected over a one year period at an urban background site in Lens
(France) were determined and investigated using a~Positive Matrix
Factorization receptor model (US EPA PMF v3.0). In addition, a Potential
Source Contribution Function (PSCF) was performed by means of the
Hysplit v4.9 model to assess prevailing geographical origins of the
identified sources. A selective iteration process was followed for the
qualification of the more robust and meaningful PMF solution. Components
measured and used in the PMF include inorganic and organic species:
soluble ionic species, trace elements, elemental carbon (EC), sugars
alcohols, sugar anhydride, and organic carbon (OC). The mean
PM10 concentration measured from March 2011 to March 2012 was
about 21 μg m-3 with typically OM, nitrate and sulfate
contributing to most of the mass and accounting respectively for 5.8,
4.5 and 2.3 μg m-3 on a yearly basis. Accordingly, PMF
outputs showed that the main emission sources were (in a decreasing
order of contribution): secondary inorganic aerosols (28% of the total
PM10 mass), aged marine emissions (19%), with probably
predominant contribution of shipping activities, biomass burning (13%),
mineral dust (13%), primary biogenic emissions (9%), fresh sea salts
(8%), primary traffic emissions (6%) and heavy oil combustion (4%).
Significant temporal variations were observed for most of the identified
sources. In particular, biomass burning emissions were negligible in
summer but responsible for about 25% of total PM10 and 50% of
total OC at wintertime. Conversely, primary biogenic emissions were
found to be negligible in winter but to represent about 20% of total
PM10 and 40% of total OC in summer. The latter result calls
for more investigations of primary biogenic aerosols using source
apportionment studies, which quite usually disregards this type of
sources. This study furthermore underlines the major influence of
secondary processes during daily threshold exceedances. Finally,
apparent discrepancies that could be generally observed between
filter-based studies (such as the present one) and Aerosol Mass
Spectrometer-based PMF analyses (organic fractions) are also discussed
here.
Studies describing the chemical composition of fine aerosol
(PM2.5) in urban areas are often conducted during few weeks
only, and at one sole site, giving thus a narrow view of their temporal
and spatial characteristics. This paper presents a one-year (11
September 2009-10 September 2010) survey of the daily chemical
composition of PM2.5 in the region of Paris, which is the
second most populated "Larger Urban Zone" in Europe. Five sampling sites
representative of suburban (SUB), urban (URB), northeast (NER),
northwest (NWR) and south (SOR) rural backgrounds were implemented. The
major chemical components of PM2.5 were determined including
elemental carbon (EC), organic carbon (OC), and the major ions. OC was
converted to organic matter (OM) using the chemical mass closure
methodology, which leads to conversion factors of 1.95 for the SUB and
URB sites, and 2.05 for the three rural ones. On average,
gravimetrically determined PM2.5 annual mass concentrations
are 15.2, 14.8, 12.6, 11.7 and 10.8 μg m-3 for SUB, URB,
NER, NWR and SOR sites, respectively. The chemical composition of fine
aerosol is very homogeneous at the five sites and is composed of OM
(38-47%), nitrate (17-22%), non-sea-salt sulfate (13-16%), ammonium
(10-12%), EC (4-10%), mineral dust (2-5%) and sea salt (3-4%). This
chemical composition is in agreement with those reported in the
literature for most European environments. On the annual scale, Paris
(URB and SUB sites) exhibits its highest PM2.5 concentrations
during late autumn, winter and early spring (higher than 15 μg
m-3 on average, from December to April), intermediates during
late spring and early autumn (between 10 and 15 μg m-3
during May, June, September, October, and November) and the lowest
during summer (below 10 μg m-3 during July and August). PM
levels are mostly homogeneous at the regional scale, on the whole
duration of the project (e.g. for URB plotted against NER sites: slope =
1.06, r2 = 0.84, n = 330), suggesting the importance of mid-
or long-range transport, and regional instead of local scale phenomena.
During this one-year project, two third of the days exceeding the
PM2.5 2015 EU annual limit value of 25 μg m-3
were due to continental import from countries located northeast, east of
France. This result questions the efficiency of local, regional and even
national abatement strategies during pollution episodes, pointing the
need for a wider collaborative work with the neighbourhood countries on
these topics. Nevertheless, emissions of local anthropogenic sources
lead to higher levels at the URB and SUB sites compared to the others
(e.g. 26% higher on average at the URB than at the NWR site for
PM2.5, during the whole campaign), which can even be
emphasised by specific meteorological conditions such as low boundary
layer heights. OM and secondary inorganic species (nitrate, non-sea-salt
sulfate and ammonium, noted SIA) are mainly imported by mid- or
long-range transport (e.g. for NWR plotted against URB sites: slope =
0.79, r2 = 0.72, n = 335 for OM, and slope = 0.91,
r2 = 0.89, n = 335 for SIA) whereas EC is primarily locally
emitted (e.g. for SOR plotted against URB sites: slope = 0.27;
r2 = 0.03; n = 335). This database will serve deepest
investigations of carbonaceous aerosols, metals as well as the main
sources and geographical origins of PM in the region of Paris.
Secondary organic aerosol (SOA), a predominant fraction of particulate
organic mass (OA), remains poorly constrained. Its formation involves
several unknown precursors, formation and evolution pathways and
multiple natural and anthropogenic sources. Here a combined gas-particle
phase source apportionment is applied to wintertime and summertime data
collected in the megacity of Paris in order to investigate SOA origin
during both seasons. This was possible by combining the information
provided by an aerosol mass spectrometer (AMS) and a proton transfer
reaction mass spectrometer (PTR-MS). A better constrained apportionment
of primary OA (POA) sources is also achieved using this methodology,
making use of gas-phase tracers. These tracers allowed distinguishing
between biogenic and continental/anthropogenic sources of SOA. We found
that continental SOA was dominant during both seasons (24-50% of total
OA), while contributions from photochemistry-driven SOA (9% of total OA)
and marine emissions (13% of total OA) were also observed during
summertime. A semi-volatile nighttime component was also identified (up
to 18% of total OA during wintertime). This approach was successfully
applied here and implemented in a new source apportionment toolkit.
[1] Major summertime aerosol emission sources in Paris were assessed using a high resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). The application of positive matrix factorization (PMF) to the highly mass and time resolved AMS measurements allowed the identification of primary and secondary sources of organic (OA) and sulfate aerosols. Primary anthropogenic emissions contributed on average ~27% (14.7% cooking, 12% traffic) to the total organic mass, while the major contribution to the organic fraction was associated with secondary formation products. Low-volatility oxygenated OA (LV-OOA, 25.2%) and semi-volatile oxygenated OA (SV-OOA, 32.4%) factors were classified as SOA. An additional component with high S:C and O:C ratios was identified and attributed to marine emissions (marine organic aerosol, MOA), owing to its high correlation with methanesulfonic acid (R2 = 0.84) and contributing on average 15.7% to the total OA mass, even in the continental megacity of Paris. Non-sea salt sulfate was apportioned by including both organic and sulfate ions in the PMF data matrix. This allowed apportionment of submicron sulfate to continental vs. marine sources. A detailed source apportionment of PM1 combining AMS, aethalometer and filter data is presented.
PM10 source apportionment was performed by positive matrix factorization (PMF) using specific primary and secondary organic molecular markers on samples collected over a one year period (2013) at an urban station in Grenoble (France). The results provided a 9-factor optimum solution, including sources rarely apportioned in the literature, such as two types of primary biogenic organic aerosols (fungal spores and plant debris), as well as specific biogenic and anthropogenic secondary organic aerosols (SOA). These sources were identified thanks to the use of key organic markers, namely, polyols, odd number higher alkanes, and several SOA markers related to the oxidation of isoprene, α-pinene, toluene and polycyclic aromatic hydrocarbons (PAHs). Primary and secondary biogenic contributions together accounted for at least 68% of the total organic carbon (OC) in the summer, while anthropogenic primary and secondary sources represented at least 71% of OC during wintertime. A very significant contribution of anthropogenic SOA was estimated in the winter during an intense PM pollution event (PM10>50μgm-3 for several days; 18% of PM10 and 42% of OC). Specific meteorological conditions with a stagnation of pollutants over 10days and possibly Fenton-like chemistry and self-amplification cycle of SOA formation could explain such high anthropogenic SOA concentrations during this period. Finally, PMF outputs were also used to investigate the origins of humic-like substances (HuLiS), which represented 16% of OC on an annual average basis. The results indicated that HuLiS were mainly associated with biomass burning (22%), secondary inorganic (22%), mineral dust (15%) and biogenic SOA (14%) factors. This study is probably the first to state that HuLiS are significantly associated with mineral dust.
At the 3 MV Tandetron accelerator of the LABEC laboratory of INFN (Florence, Italy) an external beam facility is fully dedicated to PIXE-PIGE measurements of the elemental composition of atmospheric aerosols. All the elements with Z > 10 are simultaneously detected by PIXE typically in one minute. This setup allows us an easy automatic positioning, changing and scanning of samples collected by different kinds of devices: long series of daily PM (Particulate Matter) samples can be analysed in short times, as well as size-segregated and high time-resolution aerosol samples.
Thanks to the capability of detecting all the crustal elements, PIXE-PIGE analyses are unrivalled in the study of mineral dust: consequently, they are very effective in the study of natural aerosols, like, for example, Saharan dust intrusions. Among the detectable elements there are also important markers of anthropogenic sources, which allow effective source apportionment studies in polluted urban environments using a multivariate method like Positive Matrix Factorization (PMF).
Examples regarding recent monitoring campaigns, performed in urban and remote areas, both daily and with high time resolution (hourly samples), as well as with size selection, are presented. The importance of the combined use of the Particle Induced Gamma Ray emission technique (PIGE) and of other complementary (non-nuclear) techniques is highlighted.
Total individual concentrations (in both gaseous and particulate phases) of 80 polycyclic aromatic compounds (PACs) including 32 nitro-PAHs, 27 oxy-PAHs (polycyclic aromatic hydrocarbons) and 21 parent PAHs have been investigated over a year in the ambient air of Grenoble (France) together with an extended aerosol chemical characterization. The results indicated that their concentrations were strongly affected by primary emissions in cold period, especially from residential heating (i.e. biomass burning). Besides, secondary processes occurred in summer but also in cold period under specific conditions such as during long thermal inversion layer periods and severe PM pollution events. Different secondary processes were involved during both PM pollution events observed in March–April and in December 2013. During the first one, long range transport of air masses, nitrate chemistry and secondary nitro-PAH formation seemed linked. During the second one, the accumulation of primary pollutants over several consecutive days enhanced secondary chemical processes notably highlighted by the dramatic increase of oxy-PAH concentrations. The study of the time trends of ratios of individual nitro- or oxy-PAHs to parent PAHs, in combination with key primary or secondary aerosol species and literature data, allowed the identification of potential molecular markers of PAH oxidation. Finally, 6H-dibenzo[b,d]pyran-6-one, biphenyl-2,2’-dicarboxaldehyde and 3-nitrophenanthrene have been selected to be the best candidates as markers of PAH oxidation processes in ambient air.
During March 2015, a severe and large-scale particulate matter (PM) pollution episode occurred in France. Measurements in near real-time of the major chemical composition at four different urban background sites across the country (Paris, Creil, Metz and Lyon) allowed the investigation of spatiotemporal variabilities during this episode. A climatology approach showed that all sites experienced clear unusual rain shortage, a pattern that is also found on a longer timescale, highlighting the role of synoptic conditions over Wester-Europe. This episode is characterized by a strong predominance of secondary pollution, and more particularly of ammonium nitrate, which accounted for more than 50% of submicron aerosols at all sites during the most intense period of the episode. Pollution advection is illustrated by similar variabilities in Paris and Creil (distant of around 100 km), as well as trajectory analyses applied on nitrate and sulphate. Local sources, especially wood burning, are however found to contribute to local/regional sub-episodes, notably in Metz. Finally, simulated concentrations from Chemistry-Transport model CHIMERE were compared to observed ones. Results highlighted different patterns depending on the chemical components and the measuring site, reinforcing the need of such exercises over other pollution episodes and sites.
Little is known about the impact of post-combustion processes, condensation and dilution, on the aerosol concentration and chemical composition from residential wood combustion. The evolution of aerosol emitted by two different residential log wood stoves (old and modern technologies) from emission until it is introduced into ambient air was studied under controlled "real" conditions. The first objective of this research was to evaluate the emission factors (EF) of polycyclic aromatic hydrocarbons (PAH) and their nitrated and oxygenated derivatives from wood combustion. These toxic substances are poorly documented in the literature. A second objective was to evaluate the oxidation state of the wood combustion effluent by studying these primary/secondary compounds. EFs of Sigma(37)PAHs and Sigma(27)Oxy-PAHs were in the same range and similar to those reported in literature (4-240 mg kg(-1)). Sigma(31)Nitro-PAH EFs were 2-4 orders of magnitude lower (3.10(-2)-8.10(-2) mg kg(-1)) due to the low temperature and low emission of NO2 from wood combustion processes. An increase of equivalent EF of PAH derivatives was observed suggesting that the oxidation state of the wood combustion effluent from the emission point until its introduction in ambient air changed in a few seconds. These results were confirmed by the study of both, typical compounds of SOA formation from PAH oxidation and, PAH ratio-ratio plots commonly used for source evaluation.
A chemical mass balance receptor model based on organic compounds has been developed that relates sours; contributions to airborne fine particle mass concentrations. Source contributions to the concentrations of specific organic compounds are revealed as well. The model is applied to four air quality monitoring sites in southern California using atmospheric organic compound concentration data and source test data collected specifically for the purpose of testing this model. The contributions of up to nine primary particle source types can be separately identified in ambient samples based on this method, and approximately 85% of the organic fine aerosol is assigned to primary sources on an annual average basis. The model provides information on source contributions to fine mass concentrations, fine organic aerosol concentrations and individual organic compound concentrations. The largest primary source contributors to fine particle mass concentrations in Los Angeles are found to include diesel engine exhaust, paved road dust, gasoline-powered vehicle exhaust, plus emissions from food cooking and wood smoke, with smaller contribution:; from tire dust, plant fragments, natural gas combustion aerosol, and cigarette smoke. Once these primary aerosol source contributions are added to the secondary sulfates, nitrates and organics present, virtually all of the annual average fine particle mass at Los Angeles area monitoring sites can be assigned to its source.
Field evaluations and comparisons of continuous fine particulate matter (PM2.5) mass measurement technologies at an urban and a rural site in New York state are performed. The continuous measurement technologies include the filter dynamics measurement system (FDMS) tapered element oscillating microbalance (TEOM) monitor, the stand-alone TEOM monitor (without the FDMS), and the beta attenuation monitor (BAM). These continuous measurement methods are also compared with 24-hr integrated filters collected and analyzed under the Federal Reference Method (FRM) protocol. The measurement sites are New York City (the borough of Queens) and Addison, a rural area of southwestern New York state. New York City data comparisons between the FDMS TEOM, BAM, and FRM are examined for bias and seasonality during a 2-yr period. Data comparisons for the FDMS TEOM and FRM from the Addison location are examined for the same 2-yr period. The BAM and FDMS measurements at Queens are highly correlated with each other and the FRM. The BAM and FDMS are very similar to each other in magnitude, and both are similar to 25% higher than the FRM filter measurements at this site. The FDMS at Addison measures similar to 9% more mass than the FRM. Mass reconstructions using the speciation trends network filter data are examined to provide insight as to the contribution of volatile species of PM2.5 in the FDMS mass measurement and the fraction that is likely lost in the FRM mass measurement. The reconstructed mass at Queens is systematically lower than the FDMS by similar to 10%.
Efforts have been made to relate measured concentrations of airborne constituents to their origins for more than 50 years. During this time interval, there have been developments in the measurement technology to gather highly time resolved, detail chemical compositional data. Similarly, the improvements in computers have permitted a parallel development of data analysis tools that permit the extraction of information from these data. There is now a substantial capability to provide useful insights into the sources of pollutants and their atmospheric processing that can help inform air quality management options. Efforts have been made to combine receptor and chemical transport models to provide improved apportionments. Tools are available to utilize limited numbers of known profiles with the ambient data to obtain more accurate apportionments for targeted sources. In addition, tools are in place to allow more advanced models to be fit to the data based on conceptual models of the nature of the sources and the sampling/analytical approach. Each of the approaches has its strengths and weaknesses. However, the field as a whole suffers from a lack of measurements of source emission compositions. There has not been an active effort to develop source profiles for stationary sources for a long time and with many significant sources built in developing countries, the lack of local profiles is a serious problem in effective source apportionment. The field is now relatively mature in terms of its methods and its ability to adapt to new measurement technologies so that we can be assured of a high likelihood of extracting the maximal information from the collected data. Implications Efforts have been made over the past 50 years to use air quality data to estimate the influence of air pollution sources. These methods are now relatively mature and many are readily accessible through publically available software. This review examines the development of receptor models and the current state-of-the-art in extracting source identification and apportionments from ambient air quality data.
With emerging evidence that diesel exhaust exposure poses distinct risks to human health, the need for fine-scale models of diesel exhaust pollutants is growing. We modeled the spatial distribution of several nitrated polycyclic aromatic hydrocarbons (NPAHs) to identify fine-scale gradients in diesel exhaust pollution in two Seattle, WA neighborhoods. Our modeling approach fused land-use regression, meteorological dispersion modeling and pollutant monitoring from both fixed and mobile platforms. We applied these modeling techniques to concentrations of 1-Nitropyrene (1-NP), a highly specific diesel exhaust marker, at the neighborhood scale. We developed models of two additional nitroarenes present in secondary organic aerosol: 2-Nitropyrene and 2-Nitrofluoranthene. Summer predictors of 1-NP, including distance to railroad, truck emissions and mobile black carbon measurements, showed a greater specificity to diesel sources than predictors of other NPAHs. Winter sampling results did not yield stable models, likely due to regional mixing of pollutants in turbulent weather conditions. The model of summer 1-NP had an R(2) of 0.87 and cross-validated R(2) of 0.73. The synthesis of high-density sampling and hybrid modeling was successful in predicting diesel exhaust pollution at a very fine scale and identifying clear gradients in NPAH concentrations within urban neighborhoods.
HYSPLIT, developed by NOAA’s Air Resources Laboratory, is one of the most widely used models for atmospheric trajectory and dispersion calculations. We present the model’s historical evolution over the last 30 years from simple hand drawn back trajectories to very sophisticated computations of transport, mixing, chemical transformation, and deposition of pollutants and hazardous materials. We highlight recent applications of the HYSPLIT modeling system, including the simulation of atmospheric tracer release experiments, radionuclides, smoke originated from wild fires, volcanic ash, mercury, and wind-blown dust.
In the present study, formation of aromatic organosulfates (OSs) from the photooxidation of polycyclic aromatic hydrocarbons (PAHs) was investigated. Naphthalene (NAP) and 2-methylnaphthalene (2-MeNAP), two of the most abundant gas-phase PAHs and thought to represent "missing" sources of urban SOA, were photochemically oxidized in an outdoor smog chamber facility in the presence of non-acidified and acidified sulfate seed aerosol. Effects of seed aerosol composition, acidity and relative humidity on OS formation were examined. Chemical characterization of SOA extracts by ultra performance liquid chromatography coupled to electrospray ionization high-resolution quadrupole time-of-flight mass spectrometry (UPLC/ESI-HR-QTOFMS) revealed the formation of OSs and sulfonates from photooxidation in the presence of sulfate seed aerosol. Many of the organosulfur compounds identified in the smog chamber extracts were also measured in urban fine aerosol collected at Lahore, Pakistan, and Pasadena, USA, demonstrating that PAH photooxidation in the presence of sulfate aerosol is a hitherto unrecognized source of anthropogenic secondary organosulfur compounds, and providing new PAH SOA tracers.
Secondary organic aerosol (SOA) is a major component of atmospheric fine particle mass. Intermediate-volatility organic compounds (IVOCs) have been proposed to be an important source of SOA. We present a comprehensive analysis of atmospheric IVOC concentrations and their SOA production using measurements made in Pasadena, California during the California at the Nexus of Air Quality and Climate Change (CalNex) study. The campaign-average concentration of primary IVOCs was 6.3 ± 1.9 µg m-3 (average ± standard deviation) which is comparable to the concentration of the organic aerosol but only 7.4 ± 1.2% of the concentration of speciated volatile organic compounds. Only 8.6 ± 2.2% of the mass of the primary IVOCs was speciated. Almost no weekend/weekday variation in the ambient concentration of both speciated and total primary IVOCs was observed, suggesting that petroleum-related sources other than on-road diesel vehicles contribute substantially the IVOC emissions. Primary IVOCs are estimated to produce about 30% of newly formed SOA in the afternoon during CalNex, about five times that from single-ring aromatics. The importance of IVOCs in SOA formation is expected to be similar in many urban environments.
An extraction procedure based on the Quick Easy Cheap Effective Rugged and Safe (QuEChERS) approach has been developed and used for analysis of particle-bound nitrated and oxygenated PAH derivatives (NPAH and OPAH, respectively). Several analytical conditions, for example GC injection temperature and MS detection settings, were optimized. This analytical procedure enabled simultaneous GC–NICIMS quantification of 32 NPAH and 32 OPAH (or other oxygenated compounds), including typical components of secondary organic aerosol (SOA) formed by photooxidation of PAH (e.g. 2-formyl-trans-cinnamaldehyde and 6H-dibenzo[b,d]pyran-6-one). The QuEChERS-like approach was optimized, including the nature of the extraction solvent, the sorbent used for clean-up, and extraction time. The final extraction procedure was based on brief mechanical agitation (vortex mixing for 1.5 min), with 7 mL acetonitrile as solvent. Because dispersive solid-phase extraction (d-SPE) did not provide satisfactory results, SPE using SiO2 was selected for sample purification. Identical results were obtained when the QuEChERS-like and traditional pressurised solvent extraction (PLE) procedures were compared for analysis of fortified ambient air particle samples. The procedure was validated by analysis of two aerosol standard reference materials (NIST SRM 1649b (urban dust) and SRM 2787 (fine particulate matter, <10 μm)). For numerous NPAH and OPAH, this is the first report of their quantification in both SRMs. Compared with other extraction methods, including PLE, the QuEChERS-like procedure resulted in increased productivity and reduced extraction cost. This paper shows that QuEChERS-like extraction procedures can be suitably adapted for molecular chemical characterization of aerosol samples and could be extended to other categories of compound.
Figure
ᅟ
The major source categories contributing to particulate air pollution in
urban as well as non-urban areas of Ireland were studied over an
18-month period using measurements at five sites including urban
roadside, urban centre/background, rural and coastal environments. Daily
fine and coarse aerosol samples were collected using dichotomous
Partisol samplers. The measurements included gravimetric mass (PM
10, PM 2.5 and PM 2.5-10), soluble ions
(SO 42-, NO 3-, Cl
-, CH 3SO 3-, NH
4+, Na +, K +, Mg
2+ and Ca 2+), elemental carbon (EC) and organic
carbon (OC). Mass closure procedures using reconstructed chemical
components were used to identify major source categories contributing to
the aerosol mass, namely primary marine aerosol (NaCl), secondary
inorganic materials [NH 4NO 3 + (NH 4)
2SO 4], primary anthropogenic combustion materials
(EC), primary and secondary organic materials, and re-suspended dusts.
Source component contributions differed for fine and coarse particles
and at different locations. In urban areas, the major components
contributing to fine particle mass (together accounting for 79-84% of PM
2.5 mass) were, in order, organic compounds, elemental
carbon, ammonium sulphate/ammonium nitrate, whilst in the coarse
fraction re-suspended material and sea salt were predominant (56-66%).
At the rural and coastal sites, PM 2.5 mainly consisted of
ammonium sulphate/ammonium nitrate and organic materials (65%), whilst
sea salt was the largest contributor to coarse particles (39% rural, 56%
coastal). Unexplained materials, accounting for about 7-28% of the mass,
were attributed mainly to re-suspended materials at urban sites and
organic materials at the other sites, as well as unmeasured water
content.
Near real-time measurements of carbonaceous aerosols were performed in
fine aerosols for a 10-day period during winter at a suburban site of
Paris (France). These measurements were performed using an OCEC Sunset
Field instrument for elemental carbon (EC) and organic carbon (OC); a
Particle-Into-Liquid-Sampler coupled with a Total Organic Carbon
(PILS-TOC) instrument for water-soluble OC (WSOC); and a 7-λ
aethalometer for absorption. A successful comparison was performed with
filter sampling performed in parallel for EC, OC, and WSOC, providing
further confidence on the results obtained by the online analyzers. A
modified version of the aethalometer model was used to derive hourly
concentrations of 3 organic aerosol (OA) sources: fossil fuel, wood
burning, and secondary. This source apportionment was validated for
primary OA (fossil fuel, wood burning) using time-resolved measurements
of specific tracers (including levoglucosan, water-soluble potassium and
methanol for wood burning) and showed that secondary organic aerosols
(SOA) were the most abundant OA species during our study. Water-soluble
properties of these different OA sources were investigated from the
reconstruction of experimentally determined water-soluble/insoluble OC.
About 23% of WSOC was found to be of a secondary (photochemical) origin.
A large fraction of SOA was assigned as water-insoluble and could
originate from semi-volatile primary OA from wood burning and/or
anthropogenic emissions. These results have been obtained at a typical
suburban site in France and may be then representative of a larger
European area. They bring new light on the commonly accepted idea that
SOA is mainly water-soluble.
Reactivity of polycyclic aromatic compounds (PACs) adsorbed on natural aerosol particles exposed to different atmospheric oxidants (O3, OH and NO2/O3 mixture) was studied. Decay of polycyclic aromatic hydrocarbons (PAHs) and formation/decay of oxygenated PAHs (OPAHs) and nitrated PAHs (NPAHs) were monitored. Overall, benzo[a]pyrene appeared to be the most reactive PAH (degradation of 50%). Only its nitrated derivative, 6-nitrobenzo[a]pyrene, was significantly formed explaining just 0.4% of reacted benzo[a]pyrene. No other nitrated or oxygenated benzo[a]pyrene derivatives were detected. Interestingly, B[e]P and In[1,2,3,c,d]P, which are usually considered as quite stable PAHs, also underwent decay in all experiments. In presence of O3, ketones were significantly formed but their amount was not totally explained by decay of parent PAH. These results suggest that PAH derivatives could be formed from the reaction of other compounds than their direct parent PAHs and raise the question to know if the oxidation of methyl-PAHs, identified in vehicle-exhausts, could constitute this missing source of OPAHs. NPAHs were significantly formed in presence of O3/NO2 and OH. Surprisingly, NPAH formation was clearly observed during O3 experiments. Nitrated species, already associated with aerosol particles (NO3−, NO2−) or formed by ozonation of particulate nitrogen organic matter, could react with PAHs to form NPAHs. Heterogeneous formation of 2-nitropyrene from pyrene oxidation was for the first time observed, questioning its use as an indicator of NPAH formation in gaseous phase. Equally, formation of 2-nitrofluoranthene by heterogeneous reaction of fluoranthene with O3/NO2 was clearly shown, while only its formation by homogeneous processes (gaseous phase) is reported in the literature. Finally, results obtained highlighted the dependence of heterogeneous PAH reactivity with the substrate nature and the importance to focus reactivity studies on natural particles, whatever the quality of the models previously studied.
The Chemical Mass Balance (CMB) receptor model of the US-EPA was applied to PM10 data obtained during a field study performed in the Milan urban area, including daily average concentrations, element and ion concentrations. Two chemical fingerprints were estimated to characterise total traffic emissions and diesel engine exhaust emissions. Four main source groups were identified: road traffic, with a 56% contribution, secondary particulate with 26%, soil dust (15%), and industrial emissions (3%). A more detailed treatment of the traffic source showed the important contributions of diesel exhaust and tyre and brake wear to ambient PM10 concentrations. The influence of meteorology on source apportionment was also studied by analysing the effects of rainfall of different intensities, and those of wind speed.
A laboratory study was carried out to investigate the secondary organic aerosol products from photooxidation of the aromatic hydrocarbon toluene. The laboratory experiments consisted of irradiating toluene/propylene/NOx/air mixtures in a smog chamber operated inthe dynamic mode and collecting submicron secondary organic aerosol samples through a sampling train that consisted of an XAD denuder and a ZefluorTM filter. Oxidation products in the filter extracts were treated using O-(2,3,4,5,6,-pentafluorobenzyl)-hydroxylamine (PFBHA) to derivatize carbonyl groups followed by treatment with N,O-Bis(trimethylsilyl)-acetamide (BSTFA) to derivatize OH groups. The derivatized products were detected with a positive chemical ionization (CI) gas chromatography ion trap mass spectroscopy (GC-ITMS) system. The results of the GC-ITMS analyses were consistent with the previous studies that demonstrated the formation of multi-functional oxygenates. Denuder results showed that many of these same compounds were present in the gas, as well as, the particle phase. Moreover, evidence was found for a series of multifunctional acids produced as higher order oxidation products of the toluene/NOx system. Products having nearly the same mass spectrumwere also found in the ambient environment using identical analytical techniques. These products having multiple acid and alcoholic-OH moieties have substantially lower volatility than previously reported SOA products of the toluene photooxidation and might serve as an indicator for aromatic oxidation in the ambient atmosphere.