Characterising sources and sinks of rural VOC in eastern France

Fifty non-methane hydrocarbons (NMHC) and seventeen carbonyl compounds were measured at a French rural site from 1997 to 2001, as part of the EMEP programme. Data handling was based on an original source-receptor approach. First, the examination of the levels and trends was completed by the comparison of the seasonal distribution of rural and urban VOC/acetylene ambient ratios. This analysis has shown that most of the compounds derived from mixing and photochemical transformation of mid-range transported urban pollutants from the downwind urban area. Then, identified sources and sinks were temporally apportioned. Urban air masses mixing explains, at least, 80% of the wintertime levels of anthropogenic NMHC and isoprene. In summer, photochemistry dominates the day-to-day distribution of anthropogenic NMHC whilst summertime isoprene is also controlled by in-situ biogenic emissions. Then, the results of C(1)-C(3) carbonyls were discussed with respect to their direct biogenic and anthropogenic emissions and photochemical production through the [carbonyl/auto-exhaust tracers] emission ratio. Diluted vehicle exhaust emissions mainly contribute to the total content of lower aldehydes in winter while other processes control lower ketones. Secondary production is predominant in summer with at least a 50% high intensity. Its dependence upon temperature and radiation is also demonstrated. Finally, the importance of the primary and secondary biogenic production of acetone and formaldehyde is assessed. In particular, biogenic contribution would explain 37 +/- 25% of acetone levels in summer.     

Fine particulate source apportionment using data from the USEPA speciation trends network in Chicago,Illinois: Comparison of two source apportionment models

Data from two of the United States Environmental Protection Agency's speciation trends network fine particulate matter sites within Chicago, Illinois were analyzed using the chemical mass balance (CMB) and positive matrix factorization (PMF) models to determine source contributions to the ambient fine particulate concentrations. The results from the two models were compared to determine the similarities and differences in the source contributions. This included examining the differences in the magnitude of the individual source contributions as well as the correlation between the contribution values from the two methods. The results showed that both models predicted sulfates, nitrates and motor vehicles as the three highest fine particle contributors for the two sites accounting for approximately 80% of the total. The PMF model attributed a slightly greater amount of fine particulate to the road salt, steel and soil sources while vegetative burning contributed more in the CMB results. Correlations between the contribution results from the two models were high for sulfates, nitrates and road salt with very good correlations existing for motor vehicles and petroleum refineries. The predicted PMF profiles agreed well with measured source profiles for the major species associated with each source.     

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.     

Source apportionment of ambient non-methane hydrocarbons in Hong Kong: application of a principal component analysis/absolute principal component scores (PCA/APCS) receptor model

Receptor-oriented source apportionment models are often used to identify sources of ambient air pollutants and to estimate source contributions to air pollutant concentrations. In this study, a PCA/APCS model was applied to the data on non-methane hydrocarbons (NMHCs) measured from January to December 2001 at two sampling sites: Tsuen Wan (TW) and Central & Western (CW) Toxic Air Pollutants Monitoring Stations in Hong Kong. This multivariate method enables the identification of major air pollution sources along with the quantitative apportionment of each source to pollutant species. The PCA analysis identified four major pollution sources at TW site and five major sources at CW site. The extracted pollution sources included vehicular internal engine combustion with unburned fuel emissions, use of solvent particularly paints, liquefied petroleum gas (LPG) or natural gas leakage, and industrial, commercial and domestic sources such as solvents, decoration, fuel combustion, chemical factories and power plants. The results of APCS receptor model indicated that 39% and 48% of the total NMHCs mass concentrations measured at CW and TW were originated from vehicle emissions, respectively. 32% and 36.4% of the total NMHCs were emitted from the use of solvent and 11% and 19.4% were apportioned to the LPG or natural gas leakage, respectively. 5.2% and 9% of the total NMHCs mass concentrations were attributed to other industrial, commercial and domestic sources, respectively. It was also found that vehicle emissions and LPG or natural gas leakage were the main sources of C(3)-C(5) alkanes and C(3)-C(5) alkenes while aromatics were predominantly released from paints. Comparison of source contributions to ambient NMHCs at the two sites indicated that the contribution of LPG or natural gas at CW site was almost twice that at TW site. High correlation coefficients (R(2) > 0.8) between the measured and predicted values suggested that the PCA/APCS model was applicable for estimation of sources of NMHCs in ambient air.     

Speciation of non-methane hydrocarbons (NMHCs) from anthropogenic sources in Beirut,Lebanon

The chemical composition of emissions from the different anthropogenic sources of non-methane hydrocarbons (NMHC) is essential for modeling and source apportionment studies. The speciated profiles of major NMHC sources in Lebanon, including road transport, gasoline vapor, power generation, and solvent use were established. Field sampling have been carried out by canisters in 2012. Around 67 NMHC (C2 to C9) were identified and quantified by using a gas chromatograph equipped with a flame ionization detector. Typical features of the roadway emissions included high percentages of isopentane, butane, toluene, xylenes, ethylene, and ethyne. Gasoline evaporation profiles included high percentage of the C4–C5 saturated hydrocarbons reaching 59 %. The main compounds of the power generator emissions are related to combustion. Toluene and C8–C9 aromatics were the most abundant species in emissions from paint applications. Finally, the impact of the use of region-specific source profile is tackled regarding the implication on air quality.     

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.     

Potential sources of atmospheric total gaseous mercury in the St. Lawrence River valley

The potential source contribution function (PSCF) has been used to study the source–receptor relationships for total gaseous mercury (TGM) found in air collected at two sites along the St. Lawrence River valley, namely at St. Anicet and Mingan. TGM concentrations have been measured with high time-resolution analysers (Tekran instrument). The source–receptor analyses have been applied with regards to the seasonality of TGM. Median TGM concentrations are significantly less (χ²: α=0.01) during the summertime than other periods at both sites. A total of 12 225 trajectory end-points for St. Anicet and 4480 trajectory end points for Mingan have been used to create potential source area maps. This study identifies preferred potential sources of TGM at St. Anicet during wintertime with strongest probability stretching from the Gulf of Mexico to the southern tip of Greenland. This pattern mimics, the North American anthropogenic Hg emission inventory. Furthermore, some Eurasian mercury air mass intrusions are suggested at Mingan during wintertime. The summertime period at Mingan points out some potential sources stretching from the american mid-west to the St. Lawrence River valley as well as areas around the southern tip of the Hudson Bay.     

Source identifications of airborne fine particles using positive matrix factorization and U.S. Environmental Protection Agency positive matrix factorization

The widely used source apportionment model, positive matrix factorization (PMF2), has been applied to various air pollution data. Recently, U.S. Environmental Protection Agency (EPA) developed EPA positive matrix factorization (PMF), a version of PMF that will be freely distributed by EPA. The objectives of this study were to conduct source apportionment studies for particulate matter less than 2.5 microm in aerodynamic diameter (PM(2.5)) speciation data using PMF2 and EPA PMF (version 1.1) and to compare identified sources between the two models. In the present study, ambient PM(2.5) compositional datasets of 24-hr integrated samples collected at EPA Speciation Trends Network monitoring sites in Chicago, IL, and Portland, OR, were analyzed. Both PMF2 and EPA PMF extracted eight sources for the Chicago data and 10 sources for the Portland data. The model-resolved source profiles were similar between two models for both datasets. However, in several sources, the average contributions did not agree well and the time series contributions were not highly correlated. The differences between PMF2 and EPA PMF solutions were caused by the different least-square algorithm and the different nonnegativity constraints. Most of the average source contributions resolved by both models were within 5-95% uncertainty provided by EPA PMF, indicating that the sources resolved by both models were reproducible.     

The accuracy of two- and three-way positive matrix factorization models: Applying simulated multisite data sets

The application of three-way data sets (combined multisite data sets) for source apportionment has become common, but its influence on the performance of receptor modeling techniques has not yet been explored systematically. To study the influence of site-to-site correlations of source contributions and the spatial variability of source profiles on two- and three-way positive matrix factorization (PMF), simulated three-way data sets were constructed and modeled by different applications of PMF (PMF2 for each site individually, PMF2 for data sets combining all sites together, and PMF3 for all sites). In addition, the performance of PMF was evaluated under conditions of collinearity and different source categories at two sites. The results indicated that if the sites were contributed by sources with identical profiles, the site-to-site correlations of source contributions would not influence the PMF2, and the three-way blocks could be used by PMF2. However, the PMF2 using three-way data sets was sensitive to the spatial variability of source profiles. For the three-way model, PMF3 could perform well only when all of the sources exhibited strong site-to-site associations among all sites, and at the same time, the spatial variability of source profiles were sufficiently small. It might due to the algorithm that, for each source, PMF3 produces the same source profile and the same temporal variation in daily contributions among all sites.

Implications:?The application of multisite data sets for source apportionment has become common. However, limited work investigated the accuracy of two- and three-way PMFs when using multisite data sets. If the application of PMFs using multisite data sets were not appropriate, the results would be unreasonable. The unreasonable results would supply confused information for PM control strategies. In this work, simulated multisite data sets were modeled by different applications of PMFs. The effort to assess and compare the performance of two- and three-way PMFs using multisite data sets is very limited. The findings could provide information for multisite source apportionment.     

Transport patterns and potential sources of total gaseous mercury measured in Canadian high Arctic in 1995

Trajectory cluster analysis and the potential source contribution function (PSCF) model have been used to investigate the source–receptor relationship for the total gaseous mercury (TGM) measured in the Canadian High Arctic (Alert, 82.5°N, 62.3°W) during 1995. Cluster analysis of 10-day back-trajectories in 1995 shows that the synoptic flows arriving at Alert are dominated by the air masses from the north. Long-range transport only occurs in the cold seasons while summertime flows tend to circulate in the Arctic Ocean. The potential source regions identified by the PSCF modeling include Eurasia and populated areas in the North America and Europe. Based on the modeling results, it is suggested that the elevated TGM concentrations found in the Arctic summer should be of geological origins, mainly from the evasion of volatile Hg⁰ from earth's surfaces. In the autumn and winter, mercury is transported to the receptor site from remote anthropogenic sources. The preferred sources of TGM in the spring cannot be clearly determined due to the Arctic springtime mercury depletion, which significantly reduces the number of trajectories contributing to PSCF values. Using TGM data of higher temporal resolution improves the sensitivity of the PSCF modeling results.     

The aerosol at Barrow,Alaska: long-term trends and source locations

Aerosol data consisting of condensation nuclei (CN) counts, black carbon (BC) mass, aerosol light scattering (SC), and aerosol optical depth (AOD) measured at Barrow, Alaska from 1977 to 1994 have been analyzed by three-way positive matrix factorization (PMF3) by pooling all of the different data into one large three-way array. The PMF3 analysis identified four factors that indicate four different combinations of aerosol sources active throughout the year in Alaska. Two of the factors (F1, F2) represent Arctic haze. The first Arctic haze have factor F1 is dominant in January–February while the second factor F2 is dominant in March–April. They appear to be material that is generally ascribed to long-range transported anthropogenic particles. A lower ratio of condensation nuclei to scattering coefficient loadings is obtained for F2 indicating larger particles. Factor F3 is related to condensation nuclei. It has an annual cycle with two maxima, March and July–August indicating some involvement of marine biogenic sources. The fourth factor F4 represents the contribution to the stratospheric aerosol from the eruptions of El Chichon and Mt. Pinatubo. No significant long-term trend for F1 was detected while F2 shows a negative trend over the period from 1982 to 1994 but not over the whole measurement period. A positive trend of F3 over the whole period has been observed. This trend may be related to increased biogenic sulfur production caused by reductions in the sea-ice cover in the Arctic and/or an air temperature increase in the vicinity of Barrow. Potential source contribution function (PSCF) analysis showed that in winter and spring during 1989 to 1993 regions in Eurasia and North America are the sources of particles measured at barrow. In contrast to this, large areas in the North Pacific Ocean and the Arctic Ocean was contributed to observed high concentrations of CN in the summer season. Three-way positive matrix factorization was an effective method to extract time-series information contained in the measured quantities. PSCF was useful for the identification possible source areas and the potential pathways for the Barrow aerosol. The effects of long-distance transport, photochemical aerosol production, emissions from biogenic activities in the ocean, volcanic eruptions on the aerosol measurements made at Barrow were extracted using this combined methodology.     

High occurrence of BTEX around major industrial plants in Kaohsiung,Taiwan

The Houjing River, which flows by large industrial complexes in southwestern Taiwan, has been seriously polluted with benzene, toluene, ethylbenzene, and xylene (BTEX). Using Spearman’s analysis of BTEX concentrations measured at different sites along the river, we identified the main sources of this pollution to be the Dashe and Renwu Industrial Parks. Maximum concentrations of benzene and toluene (402 and 143.19 µg/L, respectively) were considerably higher than those reported in similar studies and regulatory limits. We compared these findings with those of positive matrix factorization (PMF) modelling. PMF also identified the two industrial parks as being sources of BTEX, most likely originating from petrochemical activities that occur there. This study can serve as an important reference for future watershed management and pollution control plans for Kaohsiung, the most industrialized city in Taiwan. PMF proved to be a reliable computer modelling program for source apportionment and environmental forensic studies.     

Atmospheric mercury distribution in Northern Europe and in the Mediterranean region

Mercury species in air have been measured at five sites in Northwest Europe and at five coastal sites in the Mediterranean region during measurements at four seasons. Observed concentrations of total gaseous mercury (TGM), total particulate mercury (TPM) and reactive gaseous mercury (RGM) were generally slightly higher in the Mediterranean region than in Northwest Europe. Incoming clean Atlantic air seems to be enriched in TGM in comparison to air in Scandinavia. Trajectory analysis of events where high concentrations of TPM simultaneously were observed at sites in North Europe indicate source areas in Central Europe and provide evidence of transport of mercury on particles on a regional scale.     

Source apportionment and location by selective wind sampling and Positive Matrix Factorization

In order to determine the pollution sources in a suburban area and identify the main direction of their origin, PM_2.5 was collected with samplers coupled with a wind select sensor and then subjected to Positive Matrix Factorization (PMF) analysis. In each sample, soluble ions, organic carbon, elemental carbon, levoglucosan, metals, and Polycyclic Aromatic Hydrocarbons (PAHs) were determined. PMF results identified six main sources affecting the area: natural gas home appliances, motor vehicles, regional transport, biomass combustion, manufacturing activities, and secondary aerosol. The connection of factor temporal trends with other parameters (i.e., temperature, PM_2.5 concentration, and photochemical processes) confirms factor attributions. PMF analysis indicated that the main source of PM_2.5 in the area is secondary aerosol. This should be mainly due to regional contributions, owing to both the secondary nature of the source itself and the higher concentration registered in inland air masses. The motor vehicle emission source contribution is also important. This source likely has a prevalent local origin. The most toxic determined components, i.e., PAHs, Cd, Pb, and Ni, are mainly due to vehicular traffic. Even if this is not the main source in the study area, it is the one of greatest concern. The application of PMF analysis to PM_2.5 collected with this new sampling technique made it possible to obtain more detailed results on the sources affecting the area compared to a classical PMF analysis.     

Sources of organic aerosol: Positive matrix factorization of molecular marker data and comparison of results from different source apportionment models

This paper presents results from positive matrix factorization (PMF) of organic molecular marker data to investigate the sources of organic carbon (OC) in Pittsburgh, Pennsylvania. PMF analysis of 21 different combinations of input species found essentially the same seven factors with distinctive source-class-specific groupings of molecular markers. To link factors with source classes we directly compare PMF factor profiles with actual source profiles. Six of the PMF factors appear related to primary emissions from sources such as motor vehicles, biomass combustion, and food cooking. Each primary factor contributed between 5% and 10% of the annual-average OC with the exception of the cooking related factor which contributed 20% of the OC. However, the contribution of the cooking factor was sensitive to the specific combinations of input species. PMF could not differentiate between gasoline and diesel emissions, but the aggregate contribution of primary emissions from these two source classes is estimated to be less than 10% of the annual-average OC. One factor appears related to secondary organic aerosol based on its substantial contribution to biogenic oxidation products. This secondary factor contributed more than 50% of the summertime average OC. Reasonable agreement was observed between the PMF results and those of a previously published chemical mass balance (CMB) analysis of the same molecular marker dataset. Individual PMF factors are correlated with specific CMB sources, but systematic biases exist between the two estimates. These biases were generally within the uncertainty of the two estimates, but there is also evidence that PMF is not cleanly differentiating between source classes.     

Spatial and temporal variations in PM10 and PM2.5 source contributions and comparison to emissions during the 1995 integrated monitoring study

The ambient PM₁₀ and PM_2.5 data collected during the fall and winter portions of the 1995 Integrated Monitoring Study (IMS95) were used to conduct Chemical Mass Balance (CMB) Modeling to determine source contribution estimates. Data from the core and saturation monitoring sites provided an extensive database for evaluating the spatial and temporal variations of contributing sources. Geological sources dominated fall samples, while secondary ammonium nitrate and carbonaceous sources were the largest contributors for winter samples. Secondary ammonium nitrate concentrations were uniform across all sites during both the fall and winter. Site-to-site variability was primarily due to differences in geological contributions in the fall, and carbonaceous source contributions in the winter. During the winter, diurnal profiles of particulate matter (PM) were driven by variations in carbonaceous sources at urban sites, and by variations in secondary ammonium nitrate at rural sites. Although records of day-specific PM activities were recorded during the study, no correlation was observed between 24-h CMB results and specific activities. The ambient data collected during IMS95 was also used to evaluate the adequacy of the emissions inventory. Comparison of ambient and emissions based ratios of NMHC/NO_x, PM/NO_x, CO/NO_x, and SO_x/NO_x suggested that emissions of NMHC and CO in some locations may be underestimated, while emissions for PM and SO_x may be overestimated. Comparison of fractional primary CMB source contribution estimates to corresponding fractional emissions estimates indicated that geological sources were overemphasized in the inventory, while carbonaceous sources were underrepresented.     

Sources of fine particle composition in the northeastern US

Fine particle composition data obtained at three sampling sites in the northeastern US were studied using a relatively new type of factor analysis, positive matrix factorization (PMF). The three sites are Washington, DC, Brigantine, NJ and Underhill, VT. The PMF method uses the estimates of the error in the data to provide optimal point-by-point weighting and permits efficient treatment of missing and below detection limit values. It also imposes the non-negativity constraint on the factors. Eight, nine and 11 sources were resolved from the Washington, Brigantine and Underhill data, respectively. The factors were normalized by using aerosol fine mass concentration data through multiple linear regression so that the quantitative source contributions for each resolved factor were obtained. Among the sources resolved at the three sites, six are common. These six sources exhibit not only similar chemical compositions, but also similar seasonal variations at all three sites. They are secondary sulfate with a high concentration of S and strong seasonal variation trend peaking in summer time; coal combustion with the presence of S and Se and its seasonal variation peaking in winter time; oil combustion characterized by Ni and V; soil represented by Al, Ca, Fe, K, Si and Ti; incinerator with the presence of Pb and Zn; sea salt with the high concentrations of Na and S. Among the other sources, nitrate (dominated by NO₃⁻) and motor vehicle (with high concentrations of organic carbon (OC) and elemental carbon (EC), and with the presence of some soil dust components) were obtained for the Washington data, while the three additional sources for the Brigantine data were nitrate, motor vehicle and wood smoke (OC, EC, K). At the Underhill site, five other sources were resolved. They are wood smoke, Canadian Mn, Canadian Cu smelter, Canadian Ni smelter, and another salt source with high concentrations of Cl and Na. A nitrate source similar to that found at the other sites could not be obtained at Underhill since NO₃⁻ was not measured at this site. Generally, most of the sources at the three sites showed similar chemical composition profiles and seasonal variation patterns. The study indicated that PMF was a powerful factor analysis method to extract sources from the ambient aerosol concentration data.     

Source identification of atmospheric PCBs in Philadelphia/Camden using positive matrix factorization followed by the potential source contribution function

The concentrations of gas-phase polychlorinated biphenyls (PCBs) in the atmosphere of the Camden, NJ, USA are elevated by as much as 20 times over regional background. These high PCB levels are a concern because they lead to atmospheric deposition loadings of PCBs to the tidal Delaware River that exceed the entire total maximum daily load (TMDL). Two models were applied to the atmospheric PCB concentration data from Camden in an attempt to identify the PCB source types and regions. Positive matrix factorization (PMF) was used to identify the source types. Four factors were identified which are thought to represent sources such as volatilized Aroclors and particle-phase PCBs. The potential source contribution function (PSCF) model was then used to identify the geographic source regions by examining the origination points for air parcels that result in high PCB concentrations at the Camden receptor site. The PSCF model for ΣPCBs indicates PCB source regions throughout the Philadelphia–Camden metro area, including portions of both Pennsylvania and New Jersey. The PSCF plots for the resolved PMF factors suggest that factors 1–4 show fewer distinct source regions, indicating that their sources are diffuse and/or lie very close to the receptor site. The PSCF plots for factors 2 and 3 reveal very different source regions. Factor 2 primarily arises from the city of Philadelphia, whereas factor 3 originates in southern New Jersey and south of Philadelphia. This study demonstrates the utility of the combined PMF/PSCF approach in identifying atmospheric PCB source types and regions.     

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.     

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.