Identification of marine and continental aerosol sources in Paris using high resolution aerosol mass spectrometry

Crippa, Monica; Haddad, Imad El; Slowik, Jay G.; DeCarlo, P. F.; Mohr, Claudia; Heringa, M. F.; Chirico, R.; Marchand, Nicolas; Sciare, Jean; Baltensperger, Urs; Prévôt, Andrê S. H.

doi:10.1002/jgrd.50151

Cited by 178 publications

(210 citation statements)

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“…Hourly PILS-IC mass concentrations of MSA (average of 21 ng m −3 ; lower than those measured in Paris; average of 122 ng m −3 ; Crippa et al, 2013) compared to Mace Head, Ireland and Erdemli, Turkey (shown in Fig. 12) did not correlate with any ATOFMS particle numbers or mass concentrations or with any other measurements over the whole sampling period.…”

Section: Msamentioning

confidence: 72%

Sources and mixing state of summertime background aerosol in the north-western Mediterranean basin

et al. 2017

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Abstract. An aerosol time-of-flight mass spectrometer (ATOFMS) was employed to provide real-time single particle mixing state and thereby source information for aerosols impacting the western Mediterranean basin during the ChArMEx-ADRIMED and SAF-MED campaigns in summer 2013. The ATOFMS measurements were made at a ground-based remote site on the northern tip of Corsica.Twenty-seven distinct ATOFMS particle classes were identified and subsequently grouped into eight general categories: EC-rich (elemental carbon), K-rich, Na-rich, amines, OC-rich (organic carbon), V-rich, Fe-rich and Carich particles. Mass concentrations were reconstructed for the ATOFMS particle classes and found to be in good agreement with other co-located quantitative measurements (PM 1 , black carbon (BC), organic carbon, sulfate mass and ammonium mass). Total ATOFMS reconstructed mass (PM 2.5 ) accounted for 70-90 % of measured PM 10 mass and was comprised of regionally transported fossil fuel (EC-rich) and biomass burning (K-rich) particles. The accumulation of these transported particles was favoured by repeated and extended periods of air mass stagnation over the western Mediterranean during the sampling campaigns. The single particle mass spectra proved to be valuable source markers, allowing the identification of fossil fuel and biomass burning combustion sources, and was therefore highly complementary to quantitative measurements made by Particle into Liquid Sampler ion chromatography (PILS-IC) and an aerosol chemical speciation monitor (ACSM), which have demonstrated that PM 1 and PM 10 were comprised predominantly of sulfate, ammonium and OC. Good temporal agreement was observed between ATOFMS EC-rich and K-rich particle mass concentrations and combined mass concentrations of BC, sulfate, ammonium and low volatility oxygenated organic aerosol (LV-OOA). This combined information suggests that combustion of fossil fuels and biomass produced primary EC-and OC-containing particles, which then accumulated ammonium, sulfate and alkylamines during regional transport.Three other sources were also identified: local biomass burning, marine and shipping. Local combustion particlesPublished by Copernicus Publications on behalf of the European Geosciences Union. (emitted in Corsica) contributed little to PM 2.5 particle number and mass concentrations but were easily distinguished from regional combustion particles. Marine emissions comprised fresh and aged sea salt: the former was detected mostly during a 5-day event during which it accounted for 50-80 % of sea salt aerosol mass, while the latter was detected throughout the sampling period. Dust was not efficiently detected by the ATOFMS, and support measurements showed that it was mainly in the PM 2.5-10 fraction. Shipping particles, identified using markers for heavy fuel oil combustion, were associated with regional emissions and represented only a small fraction of PM 2.5 particle number and mass concentration at the site.

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Section: Msamentioning

confidence: 72%

Sources and mixing state of summertime background aerosol in the north-western Mediterranean basin

et al. 2017

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“…In all PMF runs (unless mentioned otherwise), we used the high-resolution mass spectra for HOA and COA (cooking OA) from Crippa et al (2013b) as constraints, i.e. two rows of f k,j were set equal to the mass spectra of HOA and COA.…”

Section: General Principlementioning

confidence: 99%

“….04 in HOA and COA factor profiles (HOA based on Aiken et al, 2009;Mohr et al, 2012;Crippa et al, 2013bCrippa et al, , 2014, and COA based on Crippa et al, 2013bCrippa et al, , 2013cMohr et al, 2012); 2. f C 2 H 4 O + 2 <0.004 and 0.01 in HOA and COA, respectively (HOA based on Aiken et al, 2009;Mohr et al, 2012;Crippa et al, 2013bCrippa et al, , 2014, and COA based on Crippa et al, 2013bCrippa et al, , 2013cMohr et al, 2012) The first two criteria (1-2) ensure an appropriate separation of HOA and COA from OOA and BBOA, respectively. Criteria 3-5 relate to the evaluation of the correlation between factor and marker time series.…”

Section: Solution Selectionmentioning

confidence: 99%

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Long-term chemical analysis and organic aerosol source apportionment at nine sites in central Europe: source identification and uncertainty assessment

et al. 2017

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Abstract. Long-term monitoring of organic aerosol is important for epidemiological studies, validation of atmospheric models, and air quality management. In this study, we apply a recently developed filter-based offline methodology using an aerosol mass spectrometer (AMS) to investigate the regional and seasonal differences of contributing organic aerosol sources. We present offline AMS measurements for particulate matter smaller than 10 µm at nine stations in central Europe with different exposure characteristics for the entire year of 2013 (819 samples). The focus of this study is a detailed source apportionment analysis (using positive matrix factorization, PMF) including in-depth assessment of the related uncertainties. Primary organic aerosol (POA) is separated in three components: hydrocarbon-like OA related to traffic emissions (HOA), cooking OA (COA), and biomass burning OA (BBOA). We observe enhanced production of secondary organic aerosol (SOA) in summer, following the increase in biogenic emissions with temperature (summer oxygenated OA, SOOA). In addition, a SOA component was extracted that correlated with an anthropogenic secondary inorganic species that is dominant in winter (winter oxygenated OA, WOOA). A factor (sulfur-containing organic, SC-OA) explaining sulfur-containing fragments (CH 3 SO + 2 ), which has an event-driven temporal behaviour, was also identified. The relative yearly average factor contributions range from 4 to 14 % for HOA, from 3 to 11 % for COA, from 11 to 59 % for BBOA, from 5 to 23 % for SC-OA, from 14 to 27 % for WOOA, and from 15 to 38 % for SOOA. The uncertainty of the relative average factor contribution lies between 2 and 12 % of OA. At the sites north of the alpine crest, the sum of HOA, COA, and BBOA (POA) contributes less to OA (POA / OA = 0.3) than at the southern alpine valley sites (0.6). BBOA is the main contributor to POA with 87 % in alpine valleys and 42 % north of the alpine crest. Furthermore, the influence of primary biological particles (PBOAs), not resolved by PMF, is estimated and could contribute significantly to OA in PM 10 .

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“…Over the past years, source apportionment using high time resolution OA mass spectra measured by an aerosol mass spectrometer (AMS) or an aerosol chemical speciation monitor (ACSM) has been a useful approach to reduce the dimensionality of complex organic 15 fractions into more easily interpretable OA factors (e.g. Ulbrich et al, 2009;He et al, 2010;Ng et al, 2011;Crippa et al, 2013;Bougiatioti et al, 2014;Lee et al, 2015). Three primary factors: hydrocarbon-like organic aerosol (HOA), cooking organic aerosol (COA), and biomass burning organic aerosol (BBOA), are commonly identified in many locations.…”

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confidence: 99%

Source Apportionment of Urban Particulate Matter using Hourly Resolved Trace Metals, Organics, and Inorganic Aerosol Components

Jeong

Wang

Evans

2016

Preprint

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Abstract. Source apportionment analysis of hourly resolved particulate matter (PM) speciation data was performed using positive matrix factorization (PMF). The data were measured at an urban site in downtown Toronto, Canada during two campaign periods (April-July, 2013;November, 2013-February, 2014, and included trace metals, black carbon, and mass 10 spectra for organic and inorganic species (PMFFull). The chemical composition was measured by collocated high time resolution instrumentation, including an Aerosol Chemical Speciation Monitor, an Xact metals monitor, and a seven-wavelength Aethalometer. Separate PMF analyses were conducted using the trace metal only data (PMFmetal) and organic mass spectra only (PMForg), and compared with the PMFFull results. Comparison of these three PMF analyses demonstrated that the full analysis offered many advantages in the apportionment of local and regional sources compared to using the organic or metals data 15 individually. In combining the high time resolution data, this analysis enabled i) the quantification of metal-rich sources of PM2.5 (PM < 2.5 μm), ii) the resolution of more robust factor profiles and contributions, and iii) the identification of additional organic aerosol sources.Nine factors were identified through the PMFFull analysis: five local factors (i.e. Road Dust, Primary Vehicle Emissions, Tire Wear, Cooking, and Industrial Sector) and four regional factors (i.e. Biomass Burning, Oxidised Organics, Sulphate and 20Oxidised Organics, and Nitrate and Oxidised Organics). The majority of the metal emissions (83%) and almost half of the black carbon (49%) were associated with the three traffic-related factors which, on average, contributed a minority (17%) of the overall PM2.5 mass. Strong seasonal patterns were observed for the traffic-related emissions: higher contributions of resuspended road dust in spring vs. a winter high for tire wear related emissions. Biomass Burning contributed the majority of the PM2.5 mass (52%) in June and July due to a major forest fire event. Much of this mass was due to photochemical aging of the biomass 25 burning aerosol. On average, industrially related factors contributed almost half (49%) of the PM2.5; most of this mass was secondary aerosol species. Nitrate coupled with highly oxidised organics was the largest contributor, accounting for 30% of PM2.5 on average, with higher levels in winter and at night. Including the temporal variabilities of inorganic ions and trace metals in the PMFFull analysis provided additional structure to subdivide the low volatility oxidised organic aerosol into three sources.Resuspended road dust was identified as a potential source of aged organic aerosol. 30The novelty of this study is the application of PMF receptor modeling to hourly resolved trace metals in conjunction with organic mass spectra, inorganic species, and black carbon for different seasons, and the comparison of separate PMF analyses applied to metals or organics alone. The inclusion of these different types of hourly data all...

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Identification of marine and continental aerosol sources in Paris using high resolution aerosol mass spectrometry

Cited by 178 publications

References 90 publications

Sources and mixing state of summertime background aerosol in the north-western Mediterranean basin

Sources and mixing state of summertime background aerosol in the north-western Mediterranean basin

Long-term chemical analysis and organic aerosol source apportionment at nine sites in central Europe: source identification and uncertainty assessment

Source Apportionment of Urban Particulate Matter using Hourly Resolved Trace Metals, Organics, and Inorganic Aerosol Components

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