Assessment of source apportionment by Positive Matrix Factorization analysis on fine and coarse urban aerosol size fractions

This study was conducted in order to investigate the differences observed in source profiles in the urban environment, when chemical composition parameters from different aerosol size fractions are subjected to factor analysis. Source apportionment was performed in an urban area where representative types of emission sources are present. PM₁₀ and PM₂ samples were collected within the Athens Metropolitan area and analysed for trace elements, inorganic ions and black carbon. Analysis by two-way and three-way Positive Matrix Factorization was performed, in order to resolve sources from data obtained for the fine and coarse aerosol fractions. A difference was observed: seven factors describe the best solution in PMF3 while six factors in PMF2. Six factors derived from PMF3 analysis correspond to those described by the PMF2 solution for the fine and coarse particles separately. These sources were attributed to road dust, marine aerosol, soil, motor vehicles, biomass burning, and oil combustion. The additional source resolved by PMF3 was attributed to a different type of road dust. Combustion sources (oil combustion and biomass burning) were correctly attributed by PMF3 solely to the fine fraction and the soil source to the coarse fraction. However, a motor vehicle's contribution to the coarse fraction was found only by three-way PMF. When PMF2 was employed in PM₁₀ concentrations the optimum solution included six factors. Four source profiles corresponded to the previously identified as vehicles, road dust, biomass burning and marine aerosol, while two could not be clearly identified. Source apportionment by PMF2 analysis based solely on PM₁₀ aerosol composition data, yielded unclear results, compared to results from PMF2 and PMF3 analyses on fine and coarse aerosol composition data.     

Chemical characterization and source identification/apportionment of fine and coarse air particles in Thessaloniki,Greece

The distribution of air particulate mass and selected particle components (trace elements and polycyclic aromatic hydrocarbons (PAHs)) in the fine and the coarse size fractions was investigated at a traffic-impacted urban site in Thessaloniki, Greece. 76±6% on average of the total ambient aerosol mass was distributed in the fine size fraction. Fine-sized trace elemental fractions ranged between 51% for Fe and 95% for Zn, while those of PAHs were between 95% and 99%. A significant seasonal effect was observed for the size distribution of aerosol mass, with a shift to larger fine fractions in winter. Similar seasonal trend was exhibited by PAHs, whereas larger fine fractions in summer were shown by trace elements. The compositional signatures of fine and coarse particle fractions were compared to that of local paved-road dust. A strong correlation was found between coarse particles and road dust suggesting strong contribution of resuspended road dust to the coarse particles. A multivariate receptor model (multiple regression on absolute principal component scores) was applied on separate fine and coarse aerosol data for source identification and apportionment. Results demonstrated that the largest contribution to fine-sized aerosol is traffic (38%) followed by road dust (28%), while road dust clearly dominated the coarse size fraction (57%).     

Source apportionment of particulate matter at urban mixed site in Indonesia using PMF

A receptor model of positive matrix factorization (PMF) was used to identify the emission sources of fine and coarse particulates in Bandung, a city located at about 150 km south-east of Jakarta. Total of 367 samples were collected at urban mixed site, Tegalega area, in Bandung City during wet and dry season in the period of 2001–2007. The samples of fine and coarse particulate matter were collected simultaneously using dichotomous samplers and mini-volume samplers. The Samples from dichotomous Samplers were analyzed for black carbon and elements while samples from mini-volume samplers were analyzed for ions. The species analyzed in this study were Na, Mg, Al, Si, K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Pb, Cl^?, NO₃^?, SO₄^2?, and NH₄⁺. The data were then analyzed using PMF to determine the source factors. Different numbers of source factors were found during dry and wet season. During dry season, the main source factors for fine particles were secondary aerosol (NH₄)₂SO₄, electroplating industry, vehicle emission, and biomass burning, while for coarse particles, the dominant source factors were electroplating industry, followed by aged sea salt, volcanic dust, soil dust, and lime dust. During the wet season, the main source factors for fine particulate matter were vehicle emission and secondary aerosol. Other sources detected were biomass burning, lime dust, soil and volcanic dust. While for coarse particulate matter, the main source factors were sulphate-rich industry, followed by lime dust, soil dust, industrial emission and construction dust.     

Wintertime and summertime São Paulo aerosol source apportionment study

A detailed aerosol source apportionment study was performed with two sampling campaigns, during wintertime and summertime in the heavily polluted metropolitan area of São Paulo, Brazil. In addition to 12 h fine and coarse mode filter sampling, several real time aerosol and trace gas monitors were used. PM₁₀ was sampled using stacked filter units that collects fine (d<2.5 μm) and coarse (2.5<d<10 μm) particulate matter, providing mass, black carbon (BC) and elemental concentration for each aerosol mode. The concentration of about 20 elements was determined using the particle induce X-ray emission technique. Real time aerosol monitors provided PM₁₀ aerosol mass (TEOM), organic and elemental carbon (Carbon Monitor 5400, R&P) and BC concentration (Aethalometer). A complex system of sources and meteorological conditions modulates the heavy air pollution of the urban area of São Paulo. The boundary layer height and the primary emissions by motor vehicles controls the strong pattern of diurnal cycles obtained for PM₁₀, BC, CO, NO_x, and SO₂. Absolute principal factor analysis results showed a very similar source pattern between winter and summer field campaigns, despite the different locations of the sampling sites of both campaigns, pointing that there are no significant change in the main air pollution sources. The source identified as motor vehicle represented 28% and 24% of the PM_2.5 for winter and summer, respectively. Resuspended soil dust accounted for 25% and 30%. The oil combustion source represented 18% and 21%. Sulfates accounts for 23% and 17% and finally industrial emissions contributed with 5% and 6% of PM_2.5, for winter and summer, respectively. The resuspended soil dust accounted for a large fraction (75–78%) of the coarse mode aerosol mass. Certainly automobile traffic and soil dust are the main air pollution sources in São Paulo. The sampling and analytical procedures applied in this study showed that it is possible to perform a quantitative aerosol source apportionment in a complex urban area such as São Paulo.     

A new methodological approach: The combined use of two-stage streaker samplers and optical particle counters for the characterization of airborne particulate matter

We describe a new experimental methodology based on the contemporary use of two-stage continuous streaker samplers and optical particle counters. This is a complementary approach to size-segregated particulate matter (PM) sampling, and it is able to give information on the elemental size distribution and to assess the contribution of major PM source to size bins. PM samples in the fine and coarse fraction of PM10 have been collected by a two-stage streaker sampler and analyzed by particle-induced X-ray emission (PIXE) to obtain elemental concentration time series with hourly resolution. PM sources and profiles were singled out by positive matrix factorization (PMF). A multi-linear regression of size-segregated number of particles versus the sources, resolved by PMF, made possible the apportionment of size-segregated particles number in a fast and direct way. Results obtained in three sampling sites, located in different urban districts are discussed.     

Identification of PM sources by principal component analysis (PCA) coupled with wind direction data

The effectiveness of combining principal component analysis (PCA) with multi-linear regression (MLRA) and wind direction data was demonstrated in this study. PM data from three grain-size fractions from a highly industrialised area in Northern Spain were analysed. Seven independent PM sources were identified by PCA: steel (Pb, Zn, Cd, Mn) and pigment (Cr, Mo, Ni) manufacture, road dust (Fe, Ba, Cd), traffic exhaust (P, OC + EC), regional-scale transport (, , V), crustal contributions (Al2O3, Sr, K) and sea spray (Na, Cl). The spatial distribution of the sources was obtained by coupling PCA with wind direction data, which helped identify regional drainage flows as the main source of crustal material. The same analysis showed that the contribution of motorway traffic to PM10 levels is 4-5 microg m-3 higher than that of local traffic. The coupling of PCA-MLRA with wind direction data proved thus to be useful in extracting further information on source contributions and locations. Correct identification and characterisation of PM sources is essential for the design and application of effective abatement strategies.     

Road traffic impact on urban atmospheric aerosol loading at Oporto,Portugal

At urban areas in south Europe atmospheric aerosol levels are frequently above legislation limits as a result of road traffic and favourable climatic conditions for photochemical formation and dust suspension. Strategies for urban particulate pollution control have to take into account specific regional characteristics and need correct information concerning the sources of the aerosol.With these objectives, the ionic and elemental composition of the fine (PM_2.5) and coarse (PM_2.5–10) aerosol was measured at two contrasting sites in the centre of the city of Oporto, roadside (R) and urban background (UB), during two campaigns, in winter and summer.Application of Spatial Variability Factors, in association with Principal Component/Multilinear Regression/Inter-site Mass Balance Analysis, to aerosol data permitted to identify and quantify 5 main groups of sources, namely direct car emissions, industry, photochemical production, dust suspension and sea salt transport. Traffic strongly influenced PM mass and composition. Direct car emissions and road dust resuspension contributed with 44–66% to the fine aerosol and with 12 to 55% to the coarse particles mass at both sites, showing typically highest loads at roadside. In fine particles secondary origin was also quite important in aerosol loading, principally during summer, with 28–48% mass contribution, at R and UB sites respectively. Sea spray has an important contribution of 18–28% to coarse aerosol mass in the studied area, with a highest relative contribution at UB site.Application of Spatial Variability/Mass Balance Analysis permitted the estimation of traffic contribution to soil dust in both size ranges, across sites and seasons, demonstrating that as much as 80% of present dust can result from road traffic resuspension.     

Investigation of sources of atmospheric aerosol at a hot spot area in Dhaka, Bangladesh

Samples of fine and coarse fractions of airborne particulate matter were collected at the Farm Gate area in Dhaka from July 2001 to March 2002. Dhaka is a hot spot area with very high pollutant concentrations because of the proximity of major roadways. The samples were collected using a "Gent" stacked filter unit in two fractions of 0- to 2.2-microm and 2.2- to 10-microm sizes. The samples were analyzed for elemental concentrations by particle-induced X-ray excitation (PIXE) and for black carbon by reflectivity methods, respectively. The data were analyzed by positive matrix factorization (PMF) to identify the possible sources of atmospheric aerosols in this area. Six sources were found for both the coarse and fine PM fractions. The data sets were also analyzed by an expanded model to explore additional sources. Seven and six factors were obtained for coarse and fine PM fractions, respectively, in these analyses. The identified sources are motor vehicle, soil dust, emissions from construction activities, sea salt, biomass burning/brick kiln, resuspended/fugitive Pb, and two-stroke engines. From the expanded modeling, approximately 50% of the total PM2.2 mass can be attributed to motor vehicles, including two-stroke engine vehicle in this hot spot in Dhaka, whereas the PMF modeling indicates that 45% of the total PM2.2 mass is from motor vehicles. The PMF2 and expanded models could resolve approximately 4% and 3% of the total PM2.2 mass as resuspended/fugitive Pb, respectively. Although, Pb has been eliminated from gasoline in Bangladesh since July 1999, there still may be substantial amounts of accumulated lead in the dust near roadways as well as fugitive Pb emissions from battery reclaimation and other industries. Soil dust is the largest component of the coarse particle fraction (PM2.2-10) accounting for approximately 71% of the total PM2.2-10 mass in the expanded model, whereas from the PMF modeling, the dust (undifferentiated) contribution is approximately 49%.     

Use of a gas chromatography–mass spectrometry organic aerosol monitor for in-field detection of fine particulate organic compounds in source apportionment

A study was conducted on the Brigham Young University campus during January and February 2015 to identify winter-time sources of fine particulate material in Utah Valley, Utah. Fine particulate mass and components and related gas-phase species were all measured on an hourly averaged basis. Light scattering was also measured during the study. Included in the sampling was the first-time source apportionment application of a new monitoring instrument for the measurement of fine particulate organic marker compounds on an hourly averaged basis. Organic marker compounds measured included levoglucosan, dehydroabietic acid, stearic acid, pyrene, and anthracene. A total of 248 hourly averaged data sets were available for a positive matrix factorization (PMF) analysis of sources of both primary and secondary fine particulate material. A total of nine factors were identified. The presence of wood smoke emissions was associated with levoglucosan, dehydroabietic acid, and pyrene markers. Fine particulate secondary nitrate, secondary organic material, and wood smoke accounted for 90% of the fine particulate material. Fine particle light scattering was dominated by sources associated with wood smoke and secondary ammonium nitrate with associated modeled fine particulate water.

Implications: The identification of sources and secondary formation pathways leading to observed levels of PM_2.5 (particulate matter with an aerodynmaic diameter <2.5 μm) is important in making regulatory decisions on pollution control. The use of organic marker compounds in this assessment has proven useful; however, data obtained on a daily, or longer, sampling schedule limit the value of the information because diurnal changes associated with emissions and secondary aerosol formation cannot be identified. A new instrument, the gas chromtography–mass spectrometry (GC-MS) organic aerosol monitor, allows for the determination on these compounds on an hourly averaged basis. The demonstrated potential value of hourly averaged data in a source apportionment analysis indicates that significant improvement in the data used for making regulatory decisions is possible.     

São Paulo Aerosol Characterization Study

Abstract

The São Paulo Metropolitan area (SPMA) is characterized as having one of the worst air pollution problems in Brazil,with frequent violations of air quality standards for particulate matter. This paper presents the results of a eceptor model source apportionment study carried out to develop a quantitative database on which a control strategy could be developed. The study was conducted in four sites with distinct land uses. Fine, coarse (CP), and total suspended particles (TSP) samples were collected on Teflon and glass filters and analyzed by x-ray fluorescence XRF), ion chromatography, and thermal evolution. The sources were characterized by similar methodology. Chemical mass balance (CMB) receptor modeling indicated that carbonaceous material plays an important role in the aerosol composition; that the three major source categories contributing to the fine particles are vehicles, secondary carbon, and sulfates; and that the main contributors to CP and TSP are road dust and vehicles. All sampling sites presented the same general pattern in terms of source contribution, although this contribution varied from site to site.     

Improving source apportionment of fine particles in the eastern United States utilizing temperature-resolved carbon fractions

The objectives of this study were to examine the use of carbon fractions to identify particulate matter (PM) sources, especially traffic-related carbonaceous particle sources, and to estimate their contributions to the particle mass concentrations. In recent studies, positive matrix factorization (PMF) was applied to ambient fine PM (PM2.5) compositional data sets of 24-hr integrated samples including eight individual carbon fractions collected at three monitoring sites in the eastern United States: Atlanta, GA, Washington, DC, and Brigantine, NJ. Particulate carbon was analyzed using the Interagency Monitoring of Protected Visual Environments/Thermal Optical Reflectance method that divides carbon into four organic carbons (OC): pyrolized OC and three elemental carbon (EC) fractions. In contrast to earlier PMF studies that included only the total OC and EC concentrations, gasoline emissions could be distinguished from diesel emissions based on the differences in the abundances of the carbon fractions between the two sources. The compositional profiles for these two major source types show similarities among the three sites. Temperature-resolved carbon fractions also enhanced separations of carbon-rich secondary sulfate aerosols. Potential source contribution function analyses show the potential source areas and pathways of sulfate-rich secondary aerosols, especially the regional influences of the biogenic, as well as anthropogenic secondary aerosol. This study indicates that temperature-resolved carbon fractions can be used to enhance the source apportionment of ambient PM2.5.     

Analysis of atmospheric aerosol (PM2.5) in Recife city,Brazil

Several studies indicate that mortality and morbidity can be well correlated to atmospheric aerosol concentrations with aerodynamic diameter less than 2.5 µm (PM_2.5). In this work the PM_2.5 at Recife city was analyzed as part of a main research project (INAIRA) to evaluate the air pollution impact on human health in six Brazilian metropolitan areas. The average concentration, for 309 samples (24-hr), from June 2007 to July 2008, was 7.3 µg/m³, with an average of 1.1 µg/m³ of black carbon. The elemental concentrations of samples were obtained by x-ray fluorescence. The concentrations were then used for characterizing the aerosol, and also were employed for receptor modelling to identify the major local sources of PM_2.5. Positive matrix factorization analysis indicated six main factors, with four being associated to soil dust, vehicles and sea spray, metallurgical activities, and biomass burning, while for a chlorine factor, and others related to S, Ca, Br, and Na, we could make no specific source association. Principal component analysis also indicated six dominant factors, with some specific characteristics. Four factors were associated to soil dust, vehicles, biomass burning, and sea spray, while for the two others, a chlorine- and copper-related factor and a nickel-related factor, it was not possible to do a specific source association. The association of the factors to the likely sources was possible thanks to meteorological analysis and sources information. Each model, although giving similar results, showed factors’ peculiarities, especially for source apportionment. The observed PM_2.5 concentration levels were acceptable, notwithstanding the high urbanization of the metropolitan area, probably due to favorable conditions for air pollution dispersion. More than a valuable historical register, these results should be very important for the next analysis, which will correlate health data, PM_2.5 levels, and sources contributions in the context of the six studied Brazilian metropolises.

Implications: The analysis of fine particulate matter (PM_2.5) in Recife city, Brazil, gave a significant picture of the local concentration and composition of this pollutant, which exhibits robust associations to adverse human health effects. Data from 1 year of sampling evaluated the seasonal variability and its connections with weather patterns. Source apportionment in this metropolitan area was obtained based in a combination of receptor models: principal component analysis (PCA)/chemical mass balance (CMB) and positive matrix factorization (PMF). These results give guidelines for local air pollution control actions, providing significant information for a health study in the context of establishing a new national air pollution protocol based on Brazilian cities data.     

Sources of fine particulate species in ambient air over lake Champlain Basin, VT

This study is a part of an ongoing investigation of the types and locations of emission sources that contribute fine particulate air contaminants to Underhill, VT. The air quality monitoring data used for this study are from the Interagency Monitoring of Protected Visual Environments network for the period of 2001-2003 for the Underhill site. The main source-receptor modeling techniques used are the positive matrix factorization (PMF) and potential source contribution function (PSCF). This new study is intended as a comparison to a previous study of the 1988-1995 Underhill data that successfully revealed a total of 11 types of emission sources with significant contributions to this rural site. This new study has identified a total of nine sources: nitrate-rich secondary aerosol, wood smoke, East Coast oil combustion, automobile emission, metal working, soil/dust, sulfur-rich aerosol type I, sulfur-rich aerosol type II, and sea salt/road salt. Furthermore, the mass contributions from the PMF identified sources that correspond with sampling days with either good or poor visibility were analyzed to seek possible correlations. It has been shown that sulfur-rich aerosol type I, nitrate aerosol, and automobile emission are the most important contributors to visibility degradation. Soil/dust and sea salt/road salt also have an added effect.     

Sources of Fine Particulate Species in Ambient Air over Lake Champlain Basin,VT

Abstract

This study is a part of an ongoing investigation of the types and locations of emission sources that contribute fine particulate air contaminants to Underhill, VT. The air quality monitoring data used for this study are from the Interagency Monitoring of Protected Visual Environments network for the period of 2001–2003 for the Underhill site. The main source-receptor modeling techniques used are the positive matrix factorization (PMF) and potential source contribution function (PSCF). This new study is intended as a comparison to a previous study of the 1988–1995 Underhill data that successfully revealed a total of 11 types of emission sources with significant contributions to this rural site. This new study has identified a total of nine sources: nitrate-rich secondary aerosol, wood smoke, East Coast oil combustion, automobile emission, metal working, soil/dust, sulfur-rich aerosol type I, sulfur-rich aerosol type II, and sea salt/road salt. Furthermore, the mass contributions from the PMF identified sources that correspond with sampling days with either good or poor visibility were analyzed to seek possible correlations. It has been shown that sulfur-rich aerosol type I, nitrate aerosol, and automobile emission are the most important contributors to visibility degradation. Soil/dust and sea salt/road salt also have an added effect.     

Particulate matter source apportionment in a village situated in industrial region of Central Europe

The bilinear receptor model positive matrix factorization (PMF) was used to apportion particulate matter with an aerodynamic diameter of 1–10 μm (PM_1–10) sources in a village, B?ezno, situated in an industrial region of northern Bohemia in Central Europe. The receptor model analyzed the data sets of 90- and 60-min integrations of PM_1–10 mass concentrations and elemental composition for 27 elements. The 14-day sampling campaigns were conducted in the village in summer 2008 and winter 2010. Also, to ensure seasonal and regional representativeness of the data sets recorded in the village, the spatial-temporal variability of the 24-hr PM₁₀ and PM_1–10 within 2008–2010 in winter and summer across the multiple sites was evaluated. There were statistically significant interseasonal differences of the 24-hr PM data, but not intrasummer or intrawinter differences of the 24-hr PM_1–10 data across the multiple sites. PMF resolved seven sources of PM_1–10. They were high-temperature coal combustion; combustion in local heating boilers; marine aerosol; mineral dust; primary biological/wood burning; road dust, car brakes; and gypsum. The main summer factors were assigned to mineral dust (38.2%) and primary biological/wood burning (33.1%). In winter, combustion factors dominated (80%) contribution to PM_1–10. The conditional probability function (CPF) helped to identified local sources of PM_1–10. The source of marine aerosol from the North Sea and English Channel was indicated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT).

Implications: This is the first application of PMF to highly time/size resolved PM data in Czech Republic. The coarse aerosol fraction, PM_1–10, was chosen with regard to industrial character of the region, sampling site near the coal strip mine and coal power stations. Contrary to expectation, source apportionment did not show dominance of emissions from the coal strip mine. The results will enable local authorities and state bodies responsible for air quality assessment to focus on sources most responsible for air pollution in this industrial region.

Supplemental Materials:?Supplemental materials are available for this paper. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for (1) details of measurement campaigns; (2) CPF for each of the sources contributing to PM_1–10; (3) factors contribution to PM_1–10 resolved by PMF; (4) diurnal pattern of road dust, car brake factor in summer and winter; (5) trajectories during the marine aerosol episode in winter 2010; and (6) temporal temperature, concentration, and wind speed relationships during the summer 2008 campaign and winter 2010 campaign.     

Source Apportionment of Particulate Matter (PM10) and Indoor Dust in a University Building

A study on source apportionment of indoor dust and particulate matter (PM₁₀) composition was conducted in a university building by using chemometrics. The objective of this study was to investigate the potential sources of selected heavy metals and ionic species in PM₁₀ and indoor dust. PM₁₀ samples were collected using a low-volume sampler (LVS) and indoor dust was collected using a soft brush. Inductively coupled plasma spectrometry (ICP-MS) was used to determine the concentration of heavy metals, while the concentration of cations and anions was determined by atomic absorption spectrometer (AAS) and ion chromatography (IC), respectively. The concentration of PM₁₀ recorded in the building throughout the sampling period ranged from 20 ± 10 μgm^?3 to 80 ± 33 μgm^?3. The composition of heavy metals in PM₁₀ and indoor dust were dominated by zinc (Zn), followed by lead (Pb), copper (Cu), and cadmium (Cd). Principle component analysis (PCA) and multiple linear regression (MLR) showed that the main sources of pollutants in PM₁₀ came from indoor renovations (73.83%), vehicle emissions (16.38%), earth crust sources (9.68%), and other outdoor sources (0.11%). For indoor dust, the pollutant source was mainly earth crust. This study suggests that chemometrics can be used for forensic investigation to determine the possible sources of indoor contaminants within a public building.     

Trace elements in size-segregated urban aerosol in relation to the anthropogenic emission sources and the resuspension

Size segregated particulate samples of atmospheric aerosols in urban site of continental part of Balkans were collected during 6 months in 2008. Six stages impactor in the size ranges: Dp?≤?0.49 μm, 0.49?2?≈?30 %) followed by traffic (PC2, σ²?≈?20 %) that are together contributing around 50 % of elements in the investigated urban aerosol. The EF model shows that major origin of Cd, K, V, Ni, Cu, Pb, Zn, and As in the fine mode is from the anthropogenic sources while increase of their contents in the coarse particles indicates their deposition from the atmosphere and soil contamination. This approach is useful for the assessment of the local resuspension influence on element’s contents in the aerosol and also for the evaluation of the historical pollution of soil caused by deposition of metals from the atmosphere.     

Source identification of atlanta aerosol by positive matrix factorization

Data characterizing daily integrated particulate matter (PM) samples collected at the Jefferson Street monitoring site in Atlanta, GA, were analyzed through the application of a bilinear positive matrix factorization (PMF) model. A total of 662 samples and 26 variables were used for fine particle (particles < or = 2.5 microm in aerodynamic diameter) samples (PM2.5), and 685 samples and 15 variables were used for coarse particle (particles between 2.5 and 10 microm in aerodynamic diameter) samples (PM10-2.5). Measured PM mass concentrations and compositional data were used as independent variables. To obtain the quantitative contributions for each source, the factors were normalized using PMF-apportioned mass concentrations. For fine particle data, eight sources were identified: SO4(2-) -rich secondary aerosol (56%), motor vehicle (22%), wood smoke (11%), NO(3-) -rich secondary aerosol (7%), mixed source of cement kiln and organic carbon (OC) (2%), airborne soil (1%), metal recycling facility (0.5%), and mixed source of bus station and metal processing (0.3%). The SO4(2-) -rich and NO(3-) -rich secondary aerosols were associated with NH(4+). The SO4(2-) -rich secondary aerosols also included OC. For the coarse particle data, five sources contributed to the observed mass: airborne soil (60%), NO(3-)-rich secondary aerosol (16%), SO4(2-) -rich secondary aerosol (12%), cement kiln (11%), and metal recycling facility (1%). Conditional probability functions were computed using surface wind data and identified mass contributions from each source. The results of this analysis agreed well with the locations of known local point sources.     

Improving Source Apportionment of Fine Particles in the Eastern United States Utilizing Temperature-Resolved Carbon Fractions

Abstract

The objectives of this study were to examine the use of carbon fractions to identify particulate matter (PM) sources, especially traffic‐related carbonaceous particle sources, and to estimate their contributions to the particle mass concentrations. In recent studies, positive matrix factorization (PMF) was applied to ambient fine PM (PM_2.5) compositional data sets of 24‐hr integrated samples including eight individual carbon fractions collected at three monitoring sites in the eastern United States: Atlanta, GA, Washington, DC, and Brigantine, NJ. Particulate carbon was analyzed using the Interagency Monitoring of Protected Visual Environments/Thermal Optical Reflectance method that divides carbon into four organic carbons (OC): pyrolized OC and three elemental carbon (EC) fractions. In contrast to earlier PMF studies that included only the total OC and EC concentrations, gasoline emissions could be distinguished from diesel emissions based on the differences in the abundances of the carbon fractions between the two sources. The compositional profiles for these two major source types show similarities among the three sites. Temperature‐resolved carbon fractions also enhanced separations of carbon‐rich secondary sulfate aerosols. Potential source contribution function analyses show the potential source areas and pathways of sulfate‐rich secondary aerosols, especially the regional influences of the biogenic, as well as anthropogenic secondary aerosol. This study indicates that temperature‐resolved carbon fractions can be used to enhance the source apportionment of ambient PM_2.5.     

Coarse and fine aerosol source apportionment in Rio de Janeiro,Brazil

The metropolitan area of Rio de Janeiro is one of the twenty biggest urban agglomerations in the world, with 11 million inhabitants in the metropolitan area, and has a high population density, with 1700 hab. km^?2. For this aerosol source apportionment study, the atmospheric aerosol sampling was performed at ten sites distributed in different locations of the metropolitan area from September/2003 to December/2005, with sampling during 24 h on a weekly basis. Stacked filter units (SFU) were used to collect fine and coarse aerosol particles with a flow rate of 17 L min^?1. In both size fractions trace elements were analyzed by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) as well as water-soluble species by Ion-Chromatography (IC). Also gravimetric analysis and reflectance measurements provided aerosol mass and black carbon concentrations. Very good detection limits for up to 42 species were obtained. Mean annual PM₁₀ mass concentration ranged from 20 to 37 μg m^?3, values that are within the Brazilian air quality standards. Receptor models such as principal factor analysis, cluster analysis and absolute principal factor analysis were applied in order to identify and quantify the aerosol sources. For fine and coarse modes, circa of 100% of the measured mass was quantitatively apportioned to relatively few identified aerosol sources. A very similar and consistent source apportionment was obtained for both fine and coarse modes for all 10 sampling sites. Soil dust is an important component, accounting for 22–72% and for 25–48% of the coarse and fine mass respectively. On the other hand, anthropogenic sources as vehicle traffic and oil combustion represent a relatively high contribution (52–75%) of the fine aerosol mass. The joint use of ICP-MS and IC analysis of species in aerosols has proven to be reliable and feasible for the analysis of large amount of samples, and the coupling with receptor models provided an excellent method for quantitative aerosol source apportionment in large urban areas.