Measured summertime concentrations of particulate components,Hg0, and speciated polycyclic aromatic hydrocarbons at rural sites in New York State

Daily PM2.5 samples, Hg0 and speciated polycyclic aromatic hydrocarbon (PAH) were simultaneously collected at Potsdam and Stockton site in NY during the summers of 2000 and 2001. Samples for determination of the mass concentration and chemical composition of the PM2.5 were obtained with a speciation network PM2.5 sampler. Chemical composition including trace elemental composition, water-soluble ions, and elemental carbon were analyzed. Elemental mercury and PAHs were sampled separately. Daily PM2.5 concentrations ranged from 0.47 to 53.7 microg m(-3) at the Potsdam site, and from 0.82 to 47.23 microg m(-3) at the Stockton site with large daily differences between the two sites. Potsdam consistently had lower mass values than Stockton. The greatest contributors to the PM2.5 mass (generally >0.1 microg/m(3)) were sulfate, nitrate, ammonium, and BC at both sites. Seventeen PAHs were identified at each site in 2000 and the average total concentrations were 3.2 ng/m(3) and 2.9 ng/m(3) at the Potsdam and Stockton sites, respectively. The mean vapor phase mercury concentration at the Potsdam site (2.4 +/-1.2 ng m(-3), n=93) was higher than that at the Stockton site (1.2 +/- 1.0 ng m(-3), n=60) in 2000, whereas in 2001, the average concentrations were 1.1 ng m(-3) and 1.6 ng m(-3) at the Potsdam and Stockton sites, respectively. In general, vapor phase mercury concentrations increased with increasing ambient temperature at the Stockton site in 2000. These differences in values between 2000 and 2001 can be largely explained by distinct differences in the meteorological regimes that dominated in the different years.     

Identification of sources of Phoenix aerosol by positive matrix factorization

Chemical composition data for fine and coarse particles collected in Phoenix, AZ, were analyzed using positive matrix factorization (PMF). The objective was to identify the possible aerosol sources at the sampling site. PMF uses estimates of the error in the data to provide optimum data point scaling and permits a better treatment of missing and below-detection-limit values. It also applies nonnegativity constraints to the factors. Two sets of fine particle samples were collected by different samplers. Each of the resulting fine particle data sets was analyzed separately. For each fine particle data set, eight factors were obtained, identified as (1) biomass burning characterized by high concentrations of organic carbon (OC), elemental carbon (EC), and K; (2) wood burning with high concentrations of Na, K, OC, and EC; (3) motor vehicles with high concentrations of OC and EC; (4) nonferrous smelting process characterized by Cu, Zn, As, and Pb; (5) heavy-duty diesel characterized by high EC, OC, and Mn; (6) sea-salt factor dominated by Na and Cl; (7) soil with high values for Al, Si, Ca, Ti, and Fe; and (8) secondary aerosol with SO4(-2) and OC that may represent coal-fired power plant emissions. For the coarse particle samples, a five-factor model gave source profiles that are attributed to be (1) sea salt, (2) soil, (3) Fe source/motor vehicle, (4) construction (high Ca), and (5) coal-fired power plant. Regression of the PM mass against the factor scores was performed to estimate the mass contributions of the resolved sources. The major sources for the fine particles were motor vehicles, vegetation burning factors (biomass and wood burning), and coal-fired power plants. These sources contributed most of the fine aerosol mass by emitting carbonaceous particles, and they have higher contributions in winter. For the coarse particles, the major source contributions were soil and construction (high Ca). These sources also peaked in winter.     

Source apportionment with site specific source profiles

A receptor modeling study was performed to identify and apportion the sources of PM10 mass in Granite City, Illinois, an area of historic TSP nonattainment. Samples of the ambient aerosol were collected using a dichotomous sampler. Each sample was analyzed by x-ray fluorescence and instrumental neutron activation analysis. To begin the study, a factor analysis was performed. Two different chemical mass balance (CMB) analyses were then made. The first CMB analysis used only source profiles available from the literature while the second included twelve source profiles developed from dust samples collected in Granite City. Both CMB analyses used 20 of the 33 analyzed elements since many of the source profiles in the literature did not include the other thirteen elements. The results from both sets of CMB analyses were grouped by the predominate wind direction at the site during the time each sample was taken to identify the direction of each source relative to the sampler. It was found that regional sources were the primary contributors to the fine fraction while the coarse fraction was composed of material from local industries. These sources were generally the ones identified during the Regional Air Pollution Study previously conducted in the area. However, the emission profiles from these sources were observed to have changed between the studies. It was also found that the use of the locally generated profiles greatly improved the results of the CMB analysis.     

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%.     

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.     

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.     

Multiple-year black carbon measurements and source apportionment using delta-C in Rochester, New York

Black carbon (BC), an important component ofthe atmospheric aerosol, has climatic, environmental, and human health significance. In this study, BC was continuously measured using a two-wavelength aethalometer (370 nm and 880 nm) in Rochester; New York, from January 2007 to December 2010. The monitoring site is adjacent to two major urban highways (I-490 and I-590), where 14% to 21% of the total traffic was heavy-duty diesel vehicles. The annual average BC concentrations were 0.76 microg/m3, 0.67 microg/m3, 0.60 microg/m3, and 0.52 microg/m3 in 2007, 2008, 2009, and 2010, respectively. Positive matrix factorization (PMF) modeling was performed using PM2.5 elements, sulfate, nitrate, ammonia, elemental carbon (EC), and organic carbon (OC) data from the US. Environmental Protection Agency (EPA) speciation network and Delta-C (UVBC370nm-BC880nm) data. Delta-C has been previously shown to be a tracer of wood combustion factor It was used as an input variable in source apportionment models for the first time in this study and was found to play an important role in separating traffic (especially diesel) emissions from wood combustion emissions. The result showed the annual average PM2.5 concentrations apportioned to diesel emissions in 2007, 2008, 2009, and 2010 were 1.34 microg/m3, 1.25 microg/m3, 1.13 microg/m3, and 0.97 microg/m3, respectively. The BC conditional probability function (CPF) plots show a large contribution from the highway diesel traffic to elevated BC concentrations. The measurements and modeling results suggest an impact of the US Environmental Protection Agency (EPA) 2007 Heavy-Duty Highway Rule on the decrease ofBC and PM2.5 concentrations during the study period.     

Apportionment of ambient primary and secondary fine particulate matter at the Pittsburgh National Energy Laboratory particulate matter characterization site using positive matrix factorization and a potential source contributions function analysis

Fine particulate matter (PM2.5) concentrations associated with 202 24-hr samples collected at the National Energy Technology Laboratory (NETL) particulate matter (PM) characterization site in south Pittsburgh from October 1999 through September 2001 were used to apportion PM2.5 into primary and secondary contributions using Positive Matrix Factorization (PMF2). Input included the concentrations of PM2.5 mass determined with a Federal Reference Method (FRM) sampler, semi-volatile PM2.5 organic material, elemental carbon (EC), and trace element components of PM2.5. A total of 11 factors were identified. The results of potential source contributions function (PSCF) analysis using PMF2 factors and HYSPLIT-calculated back-trajectories were used to identify those factors associated with specific meteorological transport conditions. The 11 factors were identified as being associated with emissions from various specific regions and facilities including crustal material, gasoline combustion, diesel combustion, and three nearby sources high in trace metals. Three sources associated with transport from coal-fired power plants to the southeast, a combination of point sources to the northwest, and a steel mill and associated sources to the west were identified. In addition, two secondary-material-dominated sources were identified, one was associated with secondary products of local emissions and one was dominated by secondary ammonium sulfate transported to the NETL site from the west and southwest. Of these 11 factors, the four largest contributors to PM2.5 were the secondary transported material (dominated by ammonium sulfate) (47%), local secondary material (19%), diesel combustion emissions (10%), and gasoline combustion emissions (8%). The other seven factors accounted for the remaining 16% of the PM2.5 mass. The findings are consistent with the major source of PM2.5 in the Pittsburgh area being dominated by ammonium sulfate from distant transport and so decoupled from local activity emitting organic pollutants in the metropolitan area. In contrast, the major local secondary sources are dominated by organic material.     

Study of urban atmospheric pollution in Navarre (Northern Spain)

An ambient air quality study was undertaken in two cities (Pamplona and Alsasua) of the Province of Navarre in northern Spain from July 2001 to June 2004. The data were obtained from two urban monitoring sites. At both monitoring sites, ambient levels of ozone, NO_x, and SO₂ were measured. Simultaneously with levels of PM₁₀ measured at Alsasua (using a laser particle counter), PM₁₀ levels were also determined at Pamplona (using a beta attenuation monitor). Mean annual PM₁₀ concentrations in Pamplona and Alsasua reached 30 and 28 μg m⁻³, respectively. These concentrations are typical for urban background sites in Northern Spain. By using meteorological information and back trajectories, it was found that the number of exceedances of the daily PM₁₀ limit as well as the PM₁₀ temporal variation was highly influenced by air masses from North Africa. Although North African transport was observed on only 9% of the days, it contributed the highest observed PM₁₀ levels. Transport from the Atlantic Ocean was observed on 68% of the days; transport from Europe on 13%; low transport and local influences on 7%; and transport from the Mediterranean region on 3% of the days. The mean O₃ concentrations were 45 and 55 μg m⁻³ in Pamplona and Alsasua, respectively, which were above the values reported for the main Spanish cities. The mean NO and NO₂ levels were very similar in both sites (12 and 26 μg m⁻³, respectively). Mean SO₂ levels were 8 μg m⁻³ in Pamplona and 5 μg m⁻³ in Alsasua. Hourly levels of PM₁₀, NO and NO₂ showed similar variations with the typically two coincident maximums during traffic rush hours demonstrating a major anthropogenic origin of PM₁₀, in spite of the sporadic dust outbreaks.