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.     

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.     

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.     

Sources of fine urban particulate matter in Detroit, MI

Data from the speciation trends network (STN) was used to evaluate the amount and temporal patterns of particulate matter originating from local industrial sources and long-range transport at two sites in Detroit, MI: Allen Park, MI, southwest of both Detroit and the areas of heavy industrial activity; Dearborn, MI, located on the south side of Detroit near the most heavily industrialized region. Using positive matrix factorization (PMF) and comparing source contributions at Allen Park to those in Dearborn, contributions made by local industrial sources (power plants, coke refineries, iron smelting, waste incineration), local area sources (automobile and diesel truck) and long range sources of PM(2.5) can be distinguished in greater Detroit. Overall, the mean mass concentration measured at Dearborn was 19% higher than that measured at Allen Park. The mass at Allen Park was apportioned as: secondary sulfate 31%, secondary nitrate 28%, soil 8%, mixed aged sea and road salts 4%, gasoline 15%, diesel 4%, and biomass burning 3%. At Dearborn the mass was apportioned as: secondary sulfate 25%, secondary nitrate 20%, soil 12%, mixed aged sea and road salts 4%, gasoline 20%, diesel 8%, iron and steel, 5%, and mixed industrial 7%. The impact of the iron and steel, soil, and mixed aged sea and road salt was much higher at the Dearborn site than at the Allen Park site, suggesting that close proximity to a local industrial complex has a direct negative impact on local air quality.     

Fine particulate matter and visibility in the Lake Tahoe Basin: chemical characterization, trends, and source apportionment

Speciated PM2.5 (particulate matter with an aerodynamic diameter相似文献   

Natural background visibility and regional haze goals in the Southeastern United States

The goal of the regional haze mitigation program in the United States is to attain "natural conditions" in national parks and wilderness areas by 2064. Results of research investigations on background concentrations of sea salt and biogenic organic matter, of episodic Saharan and Asian dust, and of carbon from natural fires were reviewed to provide a basis for making site-specific estimates of what the concentrations of atmospheric fine particulate matter components might be under natural conditions in the Southeastern United States. Based on this review, rough estimates were made of potential contributions of these aerosol components to natural background visibility. Natural organic particles were the dominant influence on the rate of visibility improvement required to reach natural conditions at an inland, mountainous location, and organic particles and sea salt were the dominant influences on the rate at a coastal location. African dust also had a large episodic effect, but the current regulatory approach is not designed to address episodic background variations. Insufficient data exist to quantify the contributions of wildfires with any detail, although global air pollution modeling provides insight, and their emissions can be locally dominant. Conservative regional refinements to the default natural background estimates do not greatly alter the region-wide rates of reduction of ambient particulate matter concentrations that will be needed to accomplish the first phase of the regional haze program. However, refinements at specific Class I areas may have considerable influence on defining the nature (magnitude and spatial and temporal distribution) of local emission reduction efforts there.     

Identification of sources contributing to Mid-Atlantic regional aerosol

Source types or source regions contributing to the concentration of atmospheric fine particles measured at Brigantine National Wildlife Refuge, NJ, were identified using a factor analysis model called Positive Matrix Factorization (PMF). Cluster analysis of backward air trajectories on days of high- and low-factor concentrations was used to link factors to potential source regions. Brigantine is a Class I visibility area with few local sources in the center of the eastern urban corridor and is therefore a good location to study Mid-Atlantic regional aerosol. Sulfate (expressed as ammonium sulfate) was the most abundant species, accounting for 49% of annual average fine mass. Organic compounds (22%; expressed as 1.4 x organic carbon) and ammonium nitrate (10%) were the next abundant species. Some evidence herein suggests that secondary organic aerosol formation is an important contributor to summertime regional aerosol. Nine factors were identified that contributed to PM2.5 mass concentrations: coal combustion factors (66%, summer and winter), sea salt factors (9%, fresh and aged), motor vehicle/mixed combustion (8%), diesel/Zn-Pb (6%), incinerator/industrial (5%), oil combustion (4%), and soil (2%). The aged sea salt concentrations were highest in springtime, when the land breeze-sea breeze cycle is strongest. Comparison of backward air trajectories of high- and low-concentration days suggests that Brigantine is surrounded by sources of oil combustion, motor vehicle/mixed combustion, and waste incinerator/industrial emissions that together account for 17% of PM2.5 mass. The diesel/Zn-Pb factor was associated with sources north and west of Brigantine. Coal combustion factors were associated with coal-fired power plants west and southwest of the site. Particulate carbon was associated not only with oil combustion, motor vehicle/mixed combustion, waste incinerator/industrial, and diesel/Pb-Zn, but also with the coal combustion factors, perhaps through common transport.     

Estimation of source apportionment and potential source locations of PM2.5 at a west coastal IMPROVE site

Particle composition data for PM_2.5 samples collected at Kalmiopsis Interagency Monitoring of Protected Visual Environments (IMPROVE) site in southwestern Oregon from March 2000 to May 2004 were analyzed to provide source identification and apportionment. A total of 493 samples were collected and 32 species were analyzed by particle induced X-ray emission, proton elastic scattering analysis, photon-induced X-ray fluorescence, ion chromatography, and thermal optical reflectance methods. Positive matrix factorization (PMF) was used to estimate the source profiles and their mass contributions. The PMF modeling identified nine sources. In the Kalmiopsis site, the average mass was apportioned to wood/field burning (38.4%), secondary sulfate (26.9%), airborne soil including Asian dust (8.6 %), secondary nitrate (7.6%), fresh sea salt (5.8%), OP-rich sulfate (4.9%), aged sea salt (4.5 %), gasoline vehicle (1.9%), and diesel emission (1.4%). The potential source contribution function (PSCF) was then used to help identify likely locations of the regional sources of pollution. The PSCF map for wood/field burning indicates there is a major potential source area in the Siskiyou County and eastern Oregon. The potential source locations for secondary sulfate are found in western Washington, northwestern Oregon, and the near shore Pacific Ocean where there are extensive shipping lanes. It was not possible to extract a profile directly attributable to ship emissions, but indications of their influence are seen in the secondary sulfate and aged sea salt compositions.     

Source apportionment of PM2.5 and PM10 aerosols in Brisbane (Australia) by receptor modelling

Aerosol samples for PM_2.5 and PM₁₀ (particulate matter with aerodynamic diameters less than 2.5 and 10 μm, respectively) were collected from 1993 to 1995 at five sites in Brisbane, a subtropical coastal city in Australia. This paper investigates the contributions of emission sources to PM_2.5 and PM₁₀ aerosol mass in Brisbane. Source apportionment results derived from the chemical mass balance (CMB), target transformation factor analysis (TTFA) and multiple linear regression (MLR) methods agree well with each other. The contributions from emission sources exhibit large variations in particle size with temporal and spatial differences. On average, the major contributors of PM₁₀ aerosol mass in Brisbane include: soil/road side dusts (25% by mass), motor vehicle exhausts (13%, not including the secondary products), sea salt (12%), Ca-rich and Ti-rich compounds (11%, from cement works and mineral processing industries), biomass burning (7%), and elemental carbon and secondary products contribute to around 15% of the aerosol mass on average. The major sources of PM_2.5 aerosols at the Griffith University (GU) site (a suburban site surrounded by forest area) are: elemental carbon (24% by mass), secondary organics (21%), biomass burning (15%) and secondary sulphate (14%). Most of the secondary products are related to motor vehicle exhausts, so, although motor vehicle exhausts contribute directly to only 6% of the PM_2.5 aerosol mass, their total contribution (including their secondary products) could be substantial. This pattern of source contribution is similar to the results for Rozelle (Sydney) among the major Australian studies, and is less in contributions from industrial and motor vehicular exhausts than the other cities. An attempt was made to estimate the contribution of rural dust and road side dust. The results show that road side dusts could contribute more than half of the crustal matter. More than 80% of the contribution of vehicle exhausts arises from diesel-fuelled trucks/buses. Biomass burning, large contributions of crustal matter, and/or local contributing sources under calm weather conditions, are often the cause of the high PM₁₀ episodes at the GU site in Brisbane.     

Identification of Sources Contributing to Mid-Atlantic Regional Aerosol

Abstract

Source types or source regions contributing to the concentration of atmospheric fine particles measured at Brigantine National Wildlife Refuge, NJ, were identified using a factor analysis model called Positive Matrix Factorization (PMF). Cluster analysis of backward air trajectories on days of high- and low-factor concentrations was used to link factors to potential source regions. Brigantine is a Class I visibility area with few local sources in the center of the eastern urban corridor and is therefore a good location to study Mid-Atlantic regional aerosol. Sulfate (expressed as ammonium sulfate) was the most abundant species, accounting for 49% of annual average fine mass. Organic compounds (22%; expressed as 1.4 × organic carbon) and ammonium nitrate (10%) were the next abundant species. Some evidence herein suggests that secondary organic aerosol formation is an important contributor to summertime regional aerosol.

Nine factors were identified that contributed to PM_2.5 mass concentrations: coal combustion factors (66%, summer and winter), sea salt factors (9%, fresh and aged), motor vehicle/mixed combustion (8%), diesel/Zn-Pb (6%), incinerator/industrial (5%), oil combustion (4%), and soil (2%). The aged sea salt concentrations were highest in springtime, when the land breeze-sea breeze cycle is strongest. Comparison of backward air trajectories of high- and low-concentration days suggests that Brigantine is surrounded by sources of oil combustion, motor vehicle/mixed combustion, and waste incinerator/industrial emissions that together account for 17% of PM_2.5 mass. The diesel/Zn-Pb factor was associated with sources north and west of Brigantine. Coal combustion factors were associated with coal-fired power plants west and southwest of the site. Particulate carbon was associated not only with oil combustion, motor vehicle/mixed combustion, waste incinerator/industrial, and diesel/Pb-Zn, but also with the coal combustion factors, perhaps through common transport.     

Quantifying road dust resuspension in urban environment by Multilinear Engine: A comparison with PMF2

Atmospheric PM pollution from traffic comprises not only direct emissions but also non-exhaust emissions because resuspension of road dust that can produce high human exposure to heavy metals, metalloids, and mineral matter. A key task for establishing mitigation or preventive measures is estimating the contribution of road dust resuspension to the atmospheric PM mixture. Several source apportionment studies, applying receptor modeling at urban background sites, have shown the difficulty in identifying a road dust source separately from other mineral sources or vehicular exhausts. The Multilinear Engine (ME-2) is a computer program that can solve the Positive Matrix Factorization (PMF) problem. ME-2 uses a programming language permitting the solution to be guided toward some possible targets that can be derived from a priori knowledge of sources (chemical profile, ratios, etc.). This feature makes it especially suitable for source apportionment studies where partial knowledge of the sources is available.In the present study ME-2 was applied to data from an urban background site of Barcelona (Spain) to quantify the contribution of road dust resuspension to PM₁₀ and PM_2.5 concentrations. Given that recently the emission profile of local resuspended road dust was obtained (Amato, F., Pandolfi, M., Viana, M., Querol, X., Alastuey, A., Moreno, T., 2009. Spatial and chemical patterns of PM₁₀ in road dust deposited in urban environment. Atmospheric Environment 43 (9), 1650–1659), such a priori information was introduced in the model as auxiliary terms of the object function to be minimized by the implementation of the so-called “pulling equations”.ME-2 permitted to enhance the basic PMF solution (obtained by PMF2) identifying, beside the seven sources of PMF2, the road dust source which accounted for 6.9 μg m^?3 (17%) in PM₁₀, 2.2 μg m^?3 (8%) of PM_2.5 and 0.3 μg m^?3 (2%) of PM₁. This reveals that resuspension was responsible of the 37%, 15% and 3% of total traffic emissions respectively in PM₁₀, PM_2.5 and PM₁. Therefore the overall traffic contribution resulted in 18 μg m^?3 (46%) in PM₁₀, 14 μg m^?3 (51%) in PM_2.5 and 8 μg m^?3 (48%) in PM₁. In PMF2 this mass explained by road dust resuspension was redistributed among the rest of sources, increasing mostly the mineral, secondary nitrate and aged sea salt contributions.     

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.     

Comparison of source apportionments of fine particulate matter at two San Jose speciation trends network sites

In this study, the chemical composition of fine particulate matter samples collected at U.S. Environmental Protection Agency Speciation Trends Network sites in San Jose, CA, from February 2000 to February 2005 were analyzed. A San Jose site was initially established at 4th Street and then subsequently moved to Jackson Street in mid-2002. These sites are approximately 1 km apart. There were no known major changes in the nature of the sources in the area over this period. The study used positive matrix factorization model to extract the source profiles and their mass contributions and to compare the results for the congruence of the source apportionments between these two nearby sites. In the case of the 4th Street site, the average mass was apportioned to wood combustion (32.1 +/- 2.5%), secondary nitrate (22.3 +/- 2%), secondary sulfate (10.7 +/- 0.6%), fresh sea salt (7.7 +/- 0.9%), gasoline vehicles (7.3 +/- 0.5%), aged sea salt (6.8 +/- 0.4%), road dust (6.7 +/- 0.7%), diesel emissions (3.9 +/- 0.3%), and a Ni-related industrial source (2.5 +/- 0.4%). At the Jackson Street site, the average mass was apportioned to wood combustion (33.6 +/- 2.6%), secondary nitrate (20.3 +/- 1.9%), secondary sulfate (13.9 +/- 0.9%), aged sea salt (12.4 +/- 0.7%), gasoline vehicle (8.3 +/- 0.6%), fresh sea salt (5.3 +/- 0.5%), diesel emission (3.2 +/- 0.3%), road dust (1.9 +/- 0.1%), and Ni-related industrial source (1.3 +/- 0.1%). Conditional probability function analysis was used to help identify local sources. These results suggested that moving the sampling site a short distance had little effect on the nature of the resolved source types although some differences in their quantitative impacts were obtained in the positive matrix factorization analyses.     

Source apportionment of particulate matter in a large city of southeastern Po Valley (Bologna, Italy)

This study reports the results of an experimental research project carried out in Bologna, a midsize town in central Po valley, with the aim at characterizing local aerosol chemistry and tracking the main source emissions of airborne particulate matter. Chemical speciation based upon ions, trace elements, and carbonaceous matter is discussed on the basis of seasonal variation and enrichment factors. For the first time, source apportionment was achieved at this location using two widely used receptor models (principal component analysis/multi-linear regression analysis (PCA/MLRA) and positive matrix factorization (PMF)). Four main aerosol sources were identified by PCA/MLRA and interpreted as: resuspended particulate and a pseudo-marine factor (winter street management), both related to the coarse fraction, plus mixed combustions and secondary aerosol largely associated to traffic and long-lived species typical of the fine fraction. The PMF model resolved six main aerosol sources, interpreted as: mineral dust, road dust, traffic, secondary aerosol, biomass burning and again a pseudo-marine factor. Source apportionment results from both models are in good agreement providing a 30 and a 33 % by weight respectively for PCA-MLRA and PMF for the coarse fraction and 70 % (PCA-MLRA) and 67 % (PMF) for the fine fraction. The episodic influence of Saharan dust transport on PM₁₀ exceedances in Bologna was identified and discussed in term of meteorological framework, composition, and quantitative contribution.     

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.     

Identification of haze-creating sources from fine particulate matter in Dhaka aerosol using carbon fractions

Fine particulate matter (PM_2.5) samples were simultaneously collected on Teflon and quartz filters between February 2010 and February 2011 at an urban monitoring site (CAMS2) in Dhaka, Bangladesh. The samples were collected using AirMetrics MiniVol samplers. The samples on Teflon filters were analyzed for their elemental composition by PIXE and PESA. Particulate carbon on quartz filters was analyzed using the IMPROVE thermal optical reflectance (TOR) method that divides carbon into four organic carbons (OC), pyrolized organic carbon (OP), and three elemental carbon (EC) fractions. The data were analyzed by positive matrix factorization using the PMF2 program. Initially, only total OC and total EC were included in the analysis and five sources, including road dust, sea salt and Zn, soil dust, motor vehicles, and brick kilns, were obtained. In the second analysis, the eight carbon fractions (OC1, OC2, OC3, OC4, OP, EC1, EC2, EC3) were included in order to ascertain whether additional source information could be extracted from the data. In this case, it is possible to identify more sources than with only total OC and EC. The motor vehicle source was separated into gasoline and diesel emissions and a fugitive Pb source was identified. Brick kilns contribute 7.9 μg/m³ and 6.0 μg/m³ of OC and EC, respectively, to the fine particulate matter based on the two results. From the estimated mass extinction coefficients and the apportioned source contributions, soil dust, brick kiln, diesel, gasoline, and the Pb sources were found to contribute most strongly to visibility degradation, particularly in the winter.

Implications: Fine particle concentrations in Dhaka, Bangladesh, are very high and cause significant degradation of urban visibility. This work shows that using carbon fraction data from the IMPROVE OC/EC protocol provides improved source apportionment. Soil dust, brick kiln, diesel, gasoline, and the Pb sources contribute strongly to haze, particularly in the winter.     

Temporal variations of source impacts at the receptor,as derived from air particulate monitoring data in Ho Chi Minh City,Vietnam

Varimax rotation factor analysis was applied to monthly concentrations of elements in total suspended air particulate (TSP) matter in Ho Chi Minh City collected from December 1992 to November 1996, covering four dry/rainy seasons. Six pollution source types were revealed. Resuspended soil/road dust accounts for 74% of the TSP mass loading. Motor vehicles and a source which emits particulates containing arsenic account for 10% and 9%, respectively. There are three minor sources, namely, cement dust from the nearby construction site, road dust of local traffic origin and burning emissions. The contributions from these source were estimated with high uncertainties. The interpretation of sources was corroborated by studying source profiles and temporal variations of source contributions. The monthly variations of source contributions at the receptor were modelled by using source apportionment techniques. From the variation patterns, emission scenarios for burning, construction and motor vehicle sources were reproduced. Source contributions also exhibit seasonal variability induced by changes of meteorological conditions. No seasonal change was found for the As-containing particulates, suggesting a speculation on their origin as coal fly ash emitting from any local coal burning source.     

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.     

Extensive aerosol optical properties and aerosol mass related measurements during TRAMP/TexAQS 2006 – Implications for PM compliance and planning

Extensive aerosol optical properties, particle size distributions, and Aerodyne quadrupole aerosol mass spectrometer measurements collected during TRAMP/TexAQS 2006 were examined in light of collocated meteorological and chemical measurements. Much of the evident variability in the observed aerosol-related air quality is due to changing synoptic meteorological situations that direct emissions from various sources to the TRAMP site near the center of the Houston-Galveston-Brazoria (HGB) metropolitan area. In this study, five distinct long-term periods have been identified. During each of these periods, observed aerosol properties have implications that are of interest to environmental quality management agencies. During three of the periods, long range transport (LRT), both intra-continental and intercontinental, appears to have played an important role in producing the observed aerosol. During late August 2006, southerly winds brought super-micron Saharan dust and sea salt to the HGB area, adding mass to fine particulate matter (PM_2.5) measurements, but apparently not affecting secondary particle growth or gas-phase air pollution. A second type of LRT was associated with northerly winds in early September 2006 and with increased ozone and sub-micron particulate matter in the HGB area. Later in the study, LRT of emissions from wildfires appeared to increase the abundance of absorbing aerosols (and carbon monoxide and other chemical tracers) in the HGB area. However, the greatest impacts on Houston PM_2.5 air quality are caused by periods with low-wind-speed sea breeze circulation or winds that directly transport pollutants from major industrial areas, i.e., the Houston Ship Channel, into the city center.     

Sources of PM10 and sulfate aerosol at McMurdo Station, Antarctica

Source contributions to PM10 and sulfate aerosol at McMurdo Station, Antarctica during the austral summers of 1995-1996 and 1996-1997 were estimated using Chemical Mass Balance (CMB) receptor modeling. The average PM10 (particles with aerodynamic diameters less than 10 microm) concentration at Hut Point, located less than 1 km downwind of downtown McMurdo, was 3.4 microg/m3. Emissions profiles were determined for potentially important aerosol source types in McMurdo: exposed soil, power generation, space heating, and surface vehicles. Soil dust, sea salt, combustion emissions, sulfates, marine biogenic emissions as methanesulfonate, and nitrates contributed 57%, 15%, 14%, 10%, 3%, and 1%, respectively, of average estimated PM10 at Hut Point (3.2 microg/m3). Soil dust, sea salt, and combustion sources contributed 12%, 8%, and 20%, respectively, of the average PM10 sulfate concentration of 0.46 microg/m3. Marine biogenic sources contributed 0.17 microg/m3 (37%). The remaining sulfate is thought to have come from emissions from Mt. Erebus or hemispheric pollution sources.