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Naydene Maykut, Puget Sound Clean Air Agency Joellen Lewtas, U.S. EPA

Source Apportionment of PM 2.5 Mass and Carbon in Seattle using Chemical Mass Balance and Positive Matrix Factorization. Naydene Maykut, Puget Sound Clean Air Agency Joellen Lewtas, U.S. EPA Tim Larson, University of Washington. Introduction.

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Naydene Maykut, Puget Sound Clean Air Agency Joellen Lewtas, U.S. EPA

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  1. Source Apportionment of PM2.5 Mass and Carbon in Seattle using Chemical Mass Balance and Positive Matrix Factorization Naydene Maykut, Puget Sound Clean Air Agency Joellen Lewtas, U.S. EPA Tim Larson, University of Washington

  2. Introduction • Extensive PM2.5 speciation data available from an urban IMPROVE site in Seattle (284 days over three years) • Source Apportionment comparison between traditional CMB approach with newer PMF method • For PMF method: include temperature resolved carbon fractions rather than traditional OC/EC split

  3. Seattle Beacon Hill Site

  4. Measured Species in Seattle(IMPROVE protocol) • >45 species measured on Wednesdays and Saturdays 4/96 to 1/99 (289 samples) • XRF (Fe to Zr, Pb) , PIXE (Na to Mn, Mo) , IC • Carbon measurements: OC & EC temperature dependent volatilization (TOR)

  5. PMF Method Used 7 carbon fractions from TOR (O1, O2, 03, O4, E1, E2, E3) as well as usual elements and ions Input species and uncertainties Robust Mode : FPEAK = +0.2

  6. TOR Analysis 800 700 Temperature Profile 600 Laser Signal Temperature (C) 500 He He + O2 400 Pyrolized carbon 300 Elemental Carbon Organic Carbon 200 CH4 Calibration 100 FID Baseline OC2 OC1 OC3 OC4 EC1 EC2 EC3 200 400 600 800 1000 1200 2200 1400 1600 1800 2000 Time (sec)

  7. Seattle PMF Results(288 Samples: all seasons) *Standard Error

  8. SO4 SO4 SO4 SO4 NO3 NO3 NO3 NO3 Na Na Na Na Cl Cl Cl Cl O1 O1 O1 O1 O2 O2 O2 O2 O3 O3 O3 O3 O4 O4 O4 O4 E1 E1 E1 E1 E2 H Si Al Fe Ca V Ni K Pb Source Profiles from PMF (Mass %) Road Dust 40 8 0.4 30 6 0.3 20 4 0.2 10 2 0.1 0 0 0 E3 Zn Mn Ti As Cu Cr Br Marine 0.4 40 8 0.3 30 6 0.2 20 4 0.1 10 2 0 0 0 E3 Zn Mn Ti As Cu Cr Br E2 H Si Al Fe Ca V Ni K Pb Marine/Secondary/Pulp Mill 8 0.4 40 6 0.3 30 4 0.2 20 2 0.1 10 0 0 0 E2 H Si Al Fe Ca V Ni K Pb E3 Zn Mn Ti As Cu Cr Br Secondary 0.4 8 40 0.3 6 30 0.2 4 20 0.1 2 10 0 0 0 E3 Zn Mn Ti As Cu Cr Br E2 H Si Al Fe Ca V Ni K Pb

  9. 40 30 20 10 0 SO4 SO4 SO4 SO4 NO3 NO3 NO3 NO3 Na Na Na Na Cl Cl Cl Cl O1 O1 O1 O1 O2 O2 O2 O2 O3 O3 O3 O3 O4 O4 O4 O4 E1 E1 E1 E1 E2 E2 E2 E2 H H H H Si Si Si Si Al Al Al Al Fe Fe Fe Fe Ca Ca Ca Ca V V V V Ni Ni Ni Ni K K K K Pb Pb Pb Pb Source Profiles from PMF (Mass %) Diesel 0.4 8 0.3 6 0.2 4 0.1 2 0 0 E3 Zn Mn Ti As Cu Cr Br Gasoline 0.4 40 8 0.3 30 6 0.2 20 4 0.1 10 2 0 0 0 E3 Zn Mn Ti As Cu Cr Br Vegetative 0.4 40 8 0.3 30 6 0.2 20 4 0.1 10 2 0 0 0 E3 Zn Mn Ti As Cu Cr Br Fuel Oil 0.4 40 8 0.3 30 6 0.2 20 4 0.1 10 2 0 0 0 E3 Zn Mn Ti As Cu Cr Br

  10. Carbon Apportionment

  11. Source Apportionment of Organic and Elemental Carbon using PMF Source OC(%)EC(%) Vegetative Burning 57 47 Diesel Vehicles 19 36 Gasoline Vehicles 5 1 Secondary 12 9 Fuel Oil 3 4 Road Dust 2 2 Marine (Sea Salt) 2 0

  12. Seattle PMF vs. CMB

  13. Conclusions • CMB source profiles invaluable in identifying PMF “factors” • PMF “factors” may approximate local source profiles • Next step - use PMF factors as combustion-derived profiles in CMB analysis • Using both models adds insight into the understanding of the composition of the aerosol in the urban airshed • PMF – urban-specific, combustion-derived profiles • CMB – minor impacts from known point sources

  14. Why This Study was Important • Use of Carbon Fractions in PMF • contributed to a defensible split between burning, diesel and gasoline • identified that carbon fractions may prove useful in identifying sources • raised the question whether PMF factors could be improved by de-coupling carbon

  15. Diesel/Gasoline PM Ratios • Diesel tailpipe/gasoline tailpipe emission-factor ratio (PM10) • 3.0 (EPA, 1995) • Diesel/gasoline PM2.5 source-contribution derived ratio • 3.2 Pasadena and 3.0 West Los Angeles (Schauer et al., 1996 • 2.7 (Seattle 8 Factor) and 3.1 (Seattle 9 Factor) • 2.1 Spokane (Kim et al., 2001)

  16. Source Composition of OC and EC (PMF vs Source Tests) * Watson, Chow and Houck, 1996 **Watson et al., 1994

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