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Improving Source Profiles and Apportionment of Combustion Sources Using Thermal Carbon Fractions in Multivariate Receptor Models

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Abstract: The purpose of this study was to improve combustion source profiles and apportionment of a PM2.5 urban aerosol by using 7 individual organic and elemental carbon thermal fractions in place of total organic and elemental carbon. This study used 3 years (96-99) of speciated data from 289 sets of PM2.5 filters (Teflon, nylon and quartz) collected at the Seattle Beacon Hill monitoring site using the IMPROVE protocol. Particulate carbon was analyzed on quartz filters using the thermal optical reflectance (TOR) method that divides the organic carbon (OC) into four fractions (OC1-OC4) and three elemental carbon (EC) fractions (EC1-EC3). The relatively new multivariate receptor models used in this study were Positive Matrix Factorization (PMF) and UNMIX. These two models are used to derive source profiles from the ambient data as well as for source apportionment. The total PM2.5 measurements used in the analysis included mass, 7 carbon fractions, 20 trace elements determined by two X-ray methods, anions (sulfate, nitrate, chloride) by ion chromatography, and elemental hydrogen (H) by proton scattering. The PMF model was able to utilize all of the data (30 species) to derive 8 source profiles. The sources with the highest contribution of the most most abundant carbon fractions(OC1-OC4 and EC1), all appear to be combustion sources. We have designated those as gasoline/motor vehicles, diesel emissions, vegetative burning, and fuel oil based on the source profiles from the PMF model. The following elements are found in relatively high abundance for each of these sources: OC3, Pb, Zn, and Ti in the gasoline profile; EC1, Fe, Zn, Si, Ca, and Mn in the diesel profile; OC3, OC4, EC1, OC2, and K in the vegetative burning profile; and OC4, Ni, and V in the fuel oil profile. The other 4 profiles derived from the PMF model have been designated as follows with distinguishing elements indicated in parentheses: soil (Si, Al, Ti), marine (Na, Cl), Na rich (nitrate, Na, E2, Ca, K, E3), and sulfate source (sulfate, nitrate, E1). UNMIX was more restrictive in deriving 6 source profiles based on a statistically acceptable model solution using 15 out of the 30 available species including OC2, OC3, OC4 and EC1 but not OC1 or EC2. Both of these receptor models derived source profiles for 4 different combustion sources containing OC fractions and EC1 whose abundances differ between the sources. Both models derived a profile for soil (Si and Al) and marine/sulfate source(s) (sulfate, Ca, and K). The marine and sodium rich source(s) containing EC1/EC2 fractions may contain some marine diesel combustion emissions. Both of these multivariant models generally agree in the estimated relative source contributions of the combustion sources to the PM2.5 mass as follows: vegetative burning (28-37%), diesel (18-19%), fuel oil (10-15%), gasoline (4-9%). Previously, we reported the analysis of this data by the Chemical Mass Balance model (CMB8) using total OC and EC. The CMB8 distinguished only two major combustion sources, vegetative burning and mobile sources.

This work has been funded by the U S Environmental Protection Agency. It has been subjected to Agency review and approved for publication.
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Citation:Lewtas, J., N. Maykut, E. Kim, and T. Larson. Improving Source Profiles and Apportionment of Combustion Sources Using Thermal Carbon Fractions in Multivariate Receptor Models. Presented at American Association for Aerosol Research, Charlotte, NC, October 7-11, 2002.
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Contact: Liz Hope - (919) 541-2785 or hope.elizabeth@epa.gov
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Division: Human Exposure & Atmospheric Sciences Division
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Branch: Immediate Office
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Product Type: Abstrct/Oral
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Presented: 10/07/2002
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Related Entries:
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Bullet Item Biomarkers of PM Exposure to Combustion Source Emissions & Organic (Toxic) Components
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