Major Source Categories for PM_2.5in Pittsburgh using PMF and UNMIX

Abstract

An objective of the Pittsburgh Air Quality Study was to determine the major sources of PM 2.5 in the Pittsburgh region. Daily 24-hour averaged filter-based data were collected for 13 months, starting in July 2001, including sulfate and nitrate data from IC analysis, trace element data from ICP-MS analysis, and organic and elemental carbon from the thermal optical transmittance (TOT) method and the NIOSH thermal evolution protocol. These data were used in two source-receptor models, Unmix and PMF. Unmix, which is limited to a maximum number of seven factors, resolved six source factors, including crustal material, a regional transport factor, secondary nitrate, an iron, zinc and manganese factor, specialty steel production and processing, and cadmium. PMF, which has no limit to the number of factors, apportioned the PM 2.5 mass into ten factors, including crustal material, secondary sulfate, primary OC and EC, secondary nitrate, an iron, zinc and manganese factor, specialty steel production and processing, cadmium, selenium, lead, and a gallium-rich factor. The Unmix and PMF common factors agree reasonably well, both in composition and contributions to PM 2.5 . To further identify and apportion the sources of PM 2.5 , specific OC compounds that are known markers of some sources were added to the PMF analysis. The results were similar to the original solution, except that the primary OC and EC factor split into two factors. One factor was associated with vehicles as identified by the hopanes, PAH's, and other OC compounds. The other factor had strong correlations with the OC and EC ambient data as well as wood smoke markers such as levoglucosan, syringols, and resin acids.

Source Apportionment: Findings from the U.S. Supersites Program

“…Pekney et al 65 enhanced their analysis by including organic markers in the PMF model. A few organic classes have been shown to be effective source indicators, including hopanes for vehicle exhaust, levoglucosan for vegetative burning, and n-alkanes for vegetative detritus (Table 2).…”

“…A few organic classes have been shown to be effective source indicators, including hopanes for vehicle exhaust, levoglucosan for vegetative burning, and n-alkanes for vegetative detritus (Table 2). Because organic markers were not measured in all samples at Pittsburgh (e.g., 24% of the sampling days), gaps were filled with the geometric mean concentration and assigned an uncertainty of four times the average precision, as suggested by Polissar et al 92,93 Although the effect of this approximation has not been systematically evaluated, Pekney et al 65 found that all of the hopanes were correlated with a primary OC/EC factor, and this was assigned to mobile source emissions. The final PMF solution contained 11 factors, with the primary OC/EC factor split into two factors: one associated with vehicle exhaust and road dust, and the other associated with vegetative burning, cooking, and vegetative detritus.…”

“…[57][58][59][60][61] For example, high-temperature EC (e.g., EC2, EC evolved at 740°C in a 98% helium [He]/2% oxygen [O 2 ] atmosphere) dominates particulate emissions from diesel engines. 54 Specific organic markers (Table 2) have also proven useful in PMF modeling studies, [63][64][65][66] but advances are needed to make them more available in source and receptor samples. 61 Modern PM source profiles that include organic compounds were obtained and applied for source apportionment at Fresno 64 and Pittsburgh.…”

“…UNMIX used fewer species (12) than PMF (22) because PMF solutions could give less weight to outliers that biased the UNMIX solution. Pekney et al 65 BAC BRES BTI CLO COP FEDL FEL FREM FRES FSF HELM LVR1 M14 MRM PIXL PLE S13 SELM SNFH SOH period (November-January). Data were collected as part of the California Regional PM 10 /PM 2.5 Air Quality Study (CRPAQS).…”

“…Intermodel Comparability PM 2.5 source apportionment was conducted for the Pittsburgh Supersite with UNMIX, 65 PMF, 65,91 and ME. 46 These solutions used different measurements as input for the July 2001 to July 2002 study period.…”