Speciation of organic fractions does matter for aerosol source apportionment. Part 3: Combining off-line and on-line measurements

Real-time chemical characterization of primary and aged biomass burning aerosols derived from sub-Saharan African biomass fuels in smoldering fires

The influence of biomass burning (BB)-derived organic aerosol (OA) emissions on solar radiation via absorption and scattering is related to their physicochemical properties and can change upon atmospheric aging. We systematically examined the compositionally-resolved mass concentration and production of primary and secondary organic aerosol (POA and SOA, respectively) in the NC A&T University smog chamber facility. Mass spectral profiles of OA measured by the Aerosol Chemical Speciation Monitor (ACSM) revealed the influence of dark- and photo-aging, fuel type, and relative humidity. Unit mass resolution (UMR) mapping, the ratio of the fraction of the OA mass spectrum signal at m/z 55 and 57 (f 55/f 57) vs. the same fraction at m/z 60 (f 60) was used to identify source-specific emission profiles. Furthermore, Positive Matrix Factorization (PMF) analysis was conducted using OA mass spectra, identifying four distinct factors: low-volatility oxygenated OA (LV-OOA), primary biomass-burning OA (BBOA), BB secondary OA (BBSOA), and semi-volatile oxygenated OA (SV-OOA). Data supports a robust four-factor solution, providing insights into the chemical transformations under different experimental conditions, including dark- and photo-aged, humidified, and dark oxidation with NO3 radicals. This work presents the first such laboratory study of African-derived BBOA particles, addressing a gap in global atmospheric chemistry research.

Improvements in source apportionment of multiple time-resolved PM2.5 inorganic and organic speciation measurements using constrained Positive Matrix Factorization

The equation of Positive Matrix Factorization (PMF) has been modified to resolve multiple time resolution inputs and applied in numerous field studies. The refined modeling results provide a solution with an increased number of factors and enriched profile features. However, the incorporation of low time-resolved data may retrieve unfavorable mixed factor profiles, introducing high uncertainties into the PMF solution computations. To address this issue, a dual-stage PMF modeling procedure with predefined constraints was proposed. Multiple time-resolved PM2.5 inorganic and organic speciation measurements were collected from autumn of 2022 to summer of 2023 in Taipei, Taiwan. Without using the proposed approach, a mixed factor of vehicle/biomass burning and an unphysically meaningful factor of sodium ion- and ammonium ion-rich were identified. After implementing the proposed approach, a refined number of eight factors with separated and reasonable profiles were retrieved. Over the sampling period, the largest contributor to PM2.5 and organic carbon was vehicle (contribution = 26% and 47%, respectively), while those for secondary inorganic aerosols of SO42-, NO3-, and NH4+ were industry (27%, 25%, and 31%, respectively), highlighting the importance of regulating these two sources. The low vehicle contribution to NO3- may be due to time-lag effects from gas-to-particle conversion, which led to different temporal patterns between NO3- and primary species. Addressing this issue is crucial in future studies for better apportionment of secondary aerosols.

Chemical characterization, source identification and potential health effects of PM2.5-bound non-polar organic compounds over a COALESCE network site - Bhopal, India

Year-long (2019) measurements of carbonaceous aerosols were performed at Bhopal, a regionally representative site as a part of the COALESCE (Carbonaceous Aerosol Emissions, Source apportionment and Climate Impacts) campaign. Aerosol-associated non-polar organic compounds (NPOCs) were analysed using thermal desorption (TD) Gas chromatography/Mass spectrometry (TD-GC/MS). The annual average of the total organic carbon (OC), elemental carbon (EC), and analysed PAHs (Polycyclic Aromatic Hydrocarbons), and n-alkanes were, 9.74 ± 9.47 μg m-3, 2.13 ± 3.12 μg m-3, 10.43 ± 5.49 ng m-3, and 114.93 ± 49.24 ng m-3, respectively. PAHs diagnostic ratios suggested emissions from petroleum, grass, wood, and coal combustion. Combustion derived PAHs (CombPAHs) accounted for 72.5 % of the total measured PAHs. During wintertime, based on Pyr/BaP ratio (∼0.6), gasoline exhaust emissions were higher compared to diesel exhaust emissions. The weak correlations between PAHs and meteorological parameters suggested that variations in PAH levels are primarily driven by alterations in emission sources. Total PAHs were correlated moderately with BrC (r2 = 0.60). The estimated lifetime lung cancer risk (LLCR) values on exposure to 16 USEPA priority PAHs (5 × 10-5) demonstrated that PAH levels in this region pose moderate health risks. Given observations from only campaign mode short-term measurements of NPOCs over India, this work provides a more comprehensive understanding of the concentrations, seasonal variations, and sources of n-alkanes and health risk associated with particle bound PAHs over the data-poor central Indian region.

Effect of industrialization on the differences in sources and composition of ambient PM2.5 in two Southern Ontario locations

PM2.5 was sampled over a seven-year period (2013-2019) at two locations ∼50 km apart in Southern Ontario (concurrently for five years: 2015-2019). One is a heavily industrialized site (Hamilton), while the other was a rural site (Simcoe). To assess the impact of industrialization on the composition and sources of PM affecting air quality in these two locations, positive matrix factorization coupled with dispersion normalization (DN-PMF) was used to identify six and eight factors at Simcoe and Hamilton, respectively. The Simcoe factors in order of diminishing PM mass contribution were: particulate sulphate (pSO4), secondary organic aerosol (SOA), crustal matter, particulate nitrate (pNO3), biomass burning, and vehicular emissions. At Hamilton, the effects of industrialization were observed by the ∼36% higher average ambient PM2.5 concentration for the study period as well as the presence of factors unique to metallurgy, i.e., coking and steelmaking, compared to Simcoe. The coking and steelmaking factors contributed ∼15% to the PM mass at Hamilton. Seasonal variants of appropriate nonparametric trend tests with the associated slopes (Sen's) were used to assess statistically significant changes in the factor contributions to PM2.5 over time. Specifically at Hamilton, a significant decline in PM contributions was noted for coking (-0.03 μg/m³/yr or -4.1%/yr) while steelmaking showed no statistically significant decline over the study period. Other factors at Hamilton that showed statistically significant declines over the study period were: pSO4 (-0.27 μg/m³/yr or -12.6%/yr), biomass burning (-0.05 μg/m³/yr or -9.02%/yr), crustal matter (-0.03 μg/m³/yr or -5.28%/yr). These factors mainly accounted for the significant decline in PM2.5 over the study period (-0.35 μg/m³/yr or -4.24%/yr). This work shows the importance of long-term monitoring in assessing the unique contributions and temporal changes of industrialization on air quality in Ontario and similarly affected locations.

Insights on the combination of off-line and on-line measurement approaches for source apportionment studies

This paper presents a source apportionment study performed on a dataset collected at a trafficked site in Coimbra (Portugal) during the period December 2018-June 2019. The novelty of this work consists in the methodological approach used and the sensitivity study carried out to give hints to potential future applications. Indeed, a multi-time resolution and multi-parameter study was performed joining together aerosol data from 24-h chemically characterized samples and high-time resolution multi-wavelength absorption coefficients retrieved by an Aethalometer. A detailed sensitivity study on the most suitable combination of time resolution and uncertainties was carried out to obtain reliable physical and stable solutions over all analyses. In parallel, a regular EPA-PMF source apportionment study using chemical and optical variables averaged on 24 h is presented and discussed in comparison to the more complex multi-time and multi-parameter approach. Apart from results pertaining to the identification and relevance of different sources in Coimbra, the methodological results shown here can give guidance for readers who want to implement optical variables jointly with chemical ones in the same model run.

Towards a better understanding of fine PM sources: Online and offline datasets combination in a single PMF

Source apportionment (SA) techniques allocate the measured ambient pollutants with their potential source origin; thus, they are a powerful tool for designing air pollution mitigation strategies. Positive Matrix Factorization (PMF) is one of the most widely used SA approaches, and its multi-time resolution (MTR) methodology, which enables mixing different instrument data in their original time resolution, was the focus of this study. One year of co-located measurements in Barcelona, Spain, of non-refractory submicronic particulate matter (NR-PM₁), black carbon (BC) and metals were obtained by a Q-ACSM (Aerodyne Research Inc.), an aethalometer (Aerosol d.o.o.) and fine offline quartz-fibre filters, respectively. These data were combined in a MTR PMF analysis preserving the high time resolution (30 min for the NR-PM₁ and BC, and 24 h every 4th day for the offline samples). The MTR-PMF outcomes were assessed varying the time resolution of the high-resolution data subset and exploring the error weightings of both subsets. The time resolution assessment revealed that averaging the high-resolution data was disadvantageous in terms of model residuals and environmental interpretability. The MTR-PMF resolved eight PM₁ sources: ammonium sulphate + heavy oil combustion (25%), ammonium nitrate + ammonium chloride (17%), aged secondary organic aerosol (SOA) (16%), traffic (14%), biomass burning (9%), fresh SOA (8%), cooking-like organic aerosol (5%), and industry (4%). The MTR-PMF technique identified two more sources relative to the 24 h base case data subset using the same species and four more with respect to the pseudo-conventional approach mimicking offline PMF, indicating that the combination of both high and low TR data is significantly beneficial for SA. Besides the higher number of sources, the MTR-PMF technique has enabled some sources disentanglement compared to the pseudo-conventional and base case PMF as well as the characterisation of their intra-day patterns.

Offline analysis of secondary formation markers in ambient organic aerosols by liquid chromatography coupled with time-of-flight mass spectrometry

The present study provides a comprehensive assessment of the quantitative analysis by high-performance liquid chromatography coupled with dual orthogonal electrospray ionization time-of-flight mass spectrometry (HPLC-ESI-TOF-MS) of pinene markers, biomass-burning related phenols, and other relevant carboxylic acids in atmospheric aerosol samples. Significant insights into the quantitative determination are offered on the basis of systematic experiments targeting the optimization of chromatographic separation, ionization source, and mass spectrometer performance. After testing three analytical columns, the best separation of the compounds of interest was achieved on a Poroshell 120 ECC18 column (4.6 × 50 mm, 2.7 µm) thermostated at 35 °C, operating in gradient elution mode with 0.1% acetic acid in water and acetonitrile at a 0.8 mL min^-1 flow rate. Optimal operational conditions for the ESI-TOF-MS instrument were identified as a 350 °C drying gas temperature, 13 L min^-1 drying gas flow rate, 60 psig nebulizer pressure, 3000 V for the ion transfer capillary, 60 V for the skimmer, and 150 V for the fragmentor. Additionally, the matrix effect on the ESI efficiency and the spike recovery factors of the compounds were tested. Method quantification limits can go as low as in the 0.88-48.0 μg L ^- 1 (3.67-200 pg m ^- 3_, at 120 m³ of sampled air) range. The developed method was shown to be reliable for the quantification of the targeted compounds in real atmospheric aerosol samples. The accuracy in the molecular mass determination of less than 5 ppm and the acquisition in the full scan mode were shown to bring additional insights into the organic constituents in atmospheric aerosols.

Source apportionment of ambient PM2.5 in an industrialized city using dispersion-normalized, multi-time resolution factor analyses

Ambient fine particulate matter (PM_2.5) data were collected in the lower City of Hamilton, Ontario to apportion the sources of this pollutant over an 18-month period. Hamilton has complex topographical features that may result in worsened air pollution within the lower city, thus, dispersion-normalized, multi-time resolution factor analysis (DN-MT-FA) was used to identify and quantify contributions of factors in a manner that reduced the influence of local meteorology. These factors were secondary organic aerosols type 1 (SOA_1), particulate nitrate (pNO3), particulate sulphate (pSO4), primary traffic organic matter (PTOM), Steel/metal processing and vehicular road dust emissions (Steel & Mobile) and, secondary organic aerosols type 2 (SOA_2) with origins ranging from mainly regional to mainly local. Factors that were mainly local (PTOM, Steel & Mobile, SOA_2) contributed up to 17% of the average PM_2.5 mass while mixed local/regional factors (pNO3, pSO4) made up 43% on average, indicating the potential for further reduction of harmful PM concentrations locally. Of particular interest from a health protection perspective, was the composition of PM_2.5 on days when an exceedance of the 24-hr WHO air quality guideline for this pollutant was observed. In general, SOA_1 was found to drive summer exceedances while pNO3 dominated in the winter. During the summer period, SOA_1 was attributable to wildfires in the northern parts of Canada while local traffic sources in winter contributed to the high levels of pNO3. While local, industrial factors only had minor relative mass contributions during exceedances, they are high in highly oxidized organic species (SOA_2) and toxic metals (Steel & Mobile). Thus, they are likely to have more impacts on human health. The methods and results described in this work will be useful in understanding prevalent sources of particulate matter pollution in the ambient air in the presence of complex topography and meteorological effects.

Source apportionment of PM2.5 using organic/inorganic markers and emission inventory evaluation in the East Mediterranean-Middle East city of Beirut

Source contributions to PM_2.5 concentrations were evaluated in Greater Beirut (Lebanon), a typical East Mediterranean-Middle East (EMME) city, using Positive Matrix Factorization with two approaches. The first approach included only inorganic species (PMF-trad) and the other approach added organic markers (PMF-org). PMF-org identified 4 additional sources, and large discrepancies in contributions were observed for some major sources found in both approaches, highlighting the importance of including organic markers. The traffic factor was underestimated in PMF-trad by 2 to 7 folds. Moreover, results showed that this city is prone to high desert dust concentrations originating from uncontrollable dust storm events, like all cities in the Middle East. A PM_2.5 mitigation plan taking into account the potency of the identified sources was developed. Sources like diesel generators or traffic presented smaller contributions in term of mass compared to desert dust, however the health impact of the latter is relatively small and actions should target sources with the highest potency. Local emission inventories in the EMME region are scarce and studies typically rely on global emission inventories for local air quality management plans, but these inventories significantly underestimate Beirut's road transport emissions by more than an order of magnitude.

Characterization of fresh PM deposits on calcareous stone surfaces: Seasonality, source apportionment and soiling potential

Particulate matter (PM) pollution is one of the major threats to cultural heritage outdoors. It has been recently implied that organic aerosols will prevail over inorganic carbon particulates in the future, changing the main mechanisms of damage caused by poor air quality to calcareous heritage in particular. We studied fresh particulate deposits on marble and limestone surfaces exposed to urban air in sheltered and unsheltered configurations. Due to different air pollution sources in different seasons, the amount and composition of surface deposits varied throughout the year. The main and most constant contributor to PM_2.5 (particles smaller than 2.5 μm) were primary traffic emissions (30 %), followed by secondary formation of acidic inorganic aerosols, such as sulphate in summer and nitrate in winter (33 % altogether), and seasonal biomass-burning emissions (14 %). Although biomass burning is the major source of primary organic aerosols including the light-absorbing fraction that prevailed over black carbon (BC) in colder months (up to 60 % carbonaceous aerosol mass), we show that surface darkening causing the soiling effect is still governed by the minor BC fraction of atmospheric aerosols, which remained below 20 % of the carbonaceous aerosol mass throughout the year. This, however, can change in remote environments affected by biomass-burning emissions, such as winter resorts, or by rigorous BC mitigation measures in the future. In the short run, sheltered positions were less affected by different removal processes, but we show that surface deposits are not simply additive when considering longer periods of time. This must be taken into account when extrapolating surface accumulation to longer time scales.

Source apportionment of ambient PM10 collected at three sites in an urban-industrial area with multi-time resolution factor analyses

Chemical speciation data for PM₁₀, collected for annual trend analyses of health-relevant species, at three receptor sites in a highly industrialized area (IJmond) in the Netherlands were used in a multi-time resolution receptor model (ME-2) to identify the PM₁₀ sources in this area. Despite the available data not being optimized for receptor modelling, five-factor solutions were obtained for all sites based on independent PMF analysis on PM₁₀ data from the three sites (IJM, WAZ and BEV). Four factors were common to all three sites: nitrate-sulphate (average percentage contributions to PM₁₀: IJM: 35.3 %, WAZ: 37.7 %, and BEV: 36.3 %); sea salt (20.2 %, 23.7 %, 15.2 %); industrial (8.1 %, 11.0 %, 18.1 %) and brake wear/traffic (31.4 %, 21.2 %, 20.6 %). At WAZ, a local/site-specific factor containing most of the PAH measurements was found (6.4 %) while a crustal matter factor was resolved at IJM (7.6 %) and BEV (9.8 %). Additionally, sludge-drying was a potential source of the marker species in the industrial factor at WAZ. Bootstrapping (BS) and factor displacement (DISP) were applied to the factor profiles in this work for error estimation. In general, the factor profiles at all three sites had very small intervals from both BS and DISP methods. To our knowledge, this is the first time DISP was applied in a complex model such as the multi-time resolution model. Most of the measured metal and PAH concentrations found in the IJmond area during the 2017-2019 period had local sources, with significant contributions from several processes related to the steel industry. This study shows that available detailed PM₁₀ chemical speciation data, although primarily collected for annual trend analyses of health-relevant species, could also be used in receptor modelling by applying a multi-time framework. We propose general recommendations for the optimization of the measurement strategy for source apportionment of PM in areas with similar urban-industrial land use.

Chemical composition, sources and optical properties of nitrated aromatic compounds in fine particulate matter during winter foggy days in Nanjing, China

Functionalized aromatic compounds are one of the most important light-absorbing organic chromophores - so-called brown carbon (BrC) - in fine particulate matter (PM_2.5). In this study, we conducted a wintertime field campaign to measure eight nitrated aromatic compounds (NACs) in PM_2.5 with offline analysis techniques, including liquid chromatograph mass spectrometer (LC-MS) and aerodyne high-resolution aerosol mass spectrometer (AMS) measurements, during foggy and nonfoggy days in suburban Nanjing in the Yangtze River Delta region, China. On average, 4-nitrophenol could be one of the most important light absorbing materials in the observed BrC, which accounted for over 40% of the mass concentration of identified chromophores. The mass concentration of 2-methyl-4-nitrophenol and 2,6-dimethyl-4-nitrophenol were evidently increased during foggy days, contribution of which to total NACs were increased by 10% and 5%, respectively. Positive matrix factorization analysis of combining LC-MS and AMS dataset was performed to identify the primary and secondary sources of NACs. Primary sources, e.g., traffic and solid-fuel combustion, accounted for 71% of the sum of 4-nitrophenol, 2,6-dimethyl-4-nitrophenol and 3-nitrosalicylic acid, suggesting important contribution of primary emissions to these NACs. The contribution of secondary sources, associated with two oxygenated organic aerosols, could contribute 66% to 4-nitrophenol, reflecting the link of such nitrated aromatic compounds to secondary organic aerosol source. Together with optical measurements, 4-nitrophenol presented a high contribution (>50%) to the identified BrC absorbance in the light range 250 and 550 nm was observed. This could highlight an important role of such NACs in ambient BrC light absorption, despite its mass contribution to total organic carbon was negligible. Our work could improve the understanding of the links between optical properties and chemical composition of BrC, and the difference between BrC chromophores from nonfoggy days and foggy days under the typical polluted atmospheric conditions.

Modelling aerosol molecular markers in a 3D air quality model: Focus on anthropogenic organic markers

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.

Sources, variability and parameterizations of intra-city factors obtained from dispersion-normalized multi-time resolution factor analyses of PM2.5 in an urban environment

Ambient fine particulate matter (PM_2.5) data of similar continuously monitored species at two air monitoring sites with different characteristics within the City of Toronto were used to gauge the intra-city variations in the PM composition over a largely concurrent period spanning two years. One location was <8 m from the side of a major highway while the other was an urban background location. For the first time, multi-time resolution factor analysis was applied to dispersion-normalized concentrations to identify and quantify source contributions while reducing the influence of local meteorology. These factors were particulate sulphate (pSO4), particulate nitrate (pNO3), secondary organic aerosols (SOA), crustal matter (CrM) that were common to both sites, a hydrocarbon-like organic matter (HOM) exclusive to the urban background site, three black carbon related factors (BC, BC-HOM at the highway site, and a brown carbon rich factor (BC-BrC) at the urban background site), biomass burning organic matter (BBOM) and brake dust (BD) factors exclusive to the highway site. The PM_2.5 composition was different between these two locations, over only a 10 km distance. The sum of SOA, pSO4 and pNO3 at the urban background site averaged 57% of the PM_2.5 mass while the same species represented 43% of the average PM_2.5 mass at the highway site. Local or site-specific factors may be of greater interest for control policy design. Thus, regression analyses with potential explanatory, site-specific variables were performed for results from the highway site. Three model approaches were explored: multiple linear regression (MLR), regression with a generalized reduced gradient (GRG) algorithm, and a generalized additive model (GAM). GAM gave the largest fraction of variance for the locally-found factors at the highway site. Heavy-duty vehicles were most important for explaining the black carbon (BC and BC-HOM) factors. Light-duty vehicles were dominant for the brake dust (BD) factor. The auxiliary modelling for the local factors showed that the traffic-related factors likely originated along the main roadways at their respective sites while the more regional factors, - pSO4, pNO3, SOA, - had sources that were both regional and local in origin and with contributions that varied seasonally. These results will be useful in understanding ambient particulate matter sources on a city scale that will support air quality management planning.

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

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.

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

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 NO_x 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.

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

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.

An evaluation of source apportionment of fine OC and PM2.5 by multiple methods: APHH-Beijing campaigns as a case study

This paper reports an evaluation of multiple source apportionment methods for OC and PM_2.5.

Global review of recent source apportionments for airborne particulate matter

Source apportionments have become increasingly performed to determine the origins of ambient particulate pollution. The results can be helpful in designing mitigation strategies to improve air quality. Source specific particulate matter (PM) concentrations are also being used in health effects studies to be able to focus attention on those sources most likely to be responsible for the observed adverse health effects. In 2015, the World Health Organization (WHO) released its initial compilation of source apportionment studies published through August 2014. This initial database was described by Karagulian et al. (Atmospheric Environment120 (2015) 475-483). In the present report, a new compilation has been prepared of those apportionments published since 2014 through December 2019. In addition, the database has been expanded to include apportionments of heavy metals, water-soluble components, and carbonaceous components in ambient PM. As a result of this work, we have developed and presented some perspectives on source apportionment going forward. We also have made a series of recommendations for source apportionment studies and reporting them. It is essential for papers to provide a minimum set of information so that the study can be adequately assessed, and the results utilized by others in making policy decisions or as part of other scientific studies.

Quantification of primary and secondary sources to PM2.5 using an improved source regional apportionment method in an industrial city, China

Identifying and quantifying the major sources of atmospheric particulate matter (PM) is essential for the development of pollution mitigation strategies to protect public health. However, urban PM is affected by local primary emissions, transport, and secondary formation; therefore, advanced methods are needed to elucidate the complex sources and transport patterns. Here, an improved source apportionment method was developed by incorporating the receptor model, Lagrangian simulation, and emissions inventories to quantify PM_2.5 sources for an industrial city in China. PM_2.5 data including ions, metals, organic carbon, and elemental carbon were obtained by analyzing 1 year of sampling results at urban and rural sites. This method identified coal combustion (30.64%), fugitive dust (13.25%), and vehicles (12.51%) as major primary sources. Secondary sources, including sulfate, nitrate, and secondary organic aerosols also contributed strongly (25.28%-30.76% in total) over urban and rural areas. Hebei Province was the major regional source contributor (43.05%-57.51%) except for fugitive dust, on which Inner Mongolia had a greater impact (43.51%). The megacities of Beijing and Tianjin exerted strong regional impacts on the secondary nitrate and secondary organic aerosols factors, contributing 11.32% and 15.65%, respectively. Pollution events were driven largely by secondary inorganic aerosols, highlighting the importance of reducing precursor emissions at the regional scale, particularly in the Beijing-Tianjin-Hebei region. Overall, our results demonstrate that this novel method offers good flexibility and efficiency for quantifying PM_2.5 sources and regional contributions, and that it can be extended to other cities.