Source Apportionment of PM 2.5 Mass and Carbon in Seattle using Chemical Mass Balance and Positive Matrix Factorization Naydene Maykut, Puget Sound Clean.

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Presentation transcript:

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 Extensive PM 2.5 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

Beacon Hill Site Seattle

>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) Measured Species in Seattle (IMPROVE protocol)

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

TOR Analysis Time (sec) OC1 OC2 OC3OC4EC1 EC2EC Temperature (  C) Temperature Profile Laser Signal CH 4 Calibration FID Baseline Organic Carbon Elemental Carbon Pyrolized carbon HeHe + O 2

Seattle PMF Results (288 Samples: all seasons) SourcePercentRange Vegetative Burning 33.8 (1.0)*0.0 – 80.5 Fuel Oil 1.8 (0.3)0.0 – 36.5 Diesel Vehicles 14.5 (0.6) Gasoline Vehicles 5.4 (0.3)0.0 – 71.4 Secondary (Sulfate) 19.1 (0.7)0.0 – 57.1 Marine/ Secondary/ Pulp Mill 8.9 (0.4)0.0 – 33.5 Paved Road Dust 8.7 (0.4)0.0 – 59.8 Marine 7.7 (0.8)0.0 – 61.1 *Standard Error

E3E3 ZnMnTiAsCuCrBr E2E2 HSiAlFeCaVNiKPb E3E3 ZnMnTiAsCuCrBr E2E2 HSiAlFeCaVNiKPb E3E3 ZnMnTiAsCuCrBr E2E2 HSiAlFeCaVNiKPb E3E3 ZnMnTiAsCuCrBr SO 4 NO 3 NaClO1O1 O2O2 O3O3 O4O4 E1E1 SO 4 NO 3 NaClO1O1 O2O2 O3O3 O4O4 E1E1 SO 4 NO 3 NaClO1O1 O2O2 O3O3 O4O4 E1E1 SO 4 NO 3 NaClO1O1 O2O2 O3O3 O4O4 E1E1 E2E2 HSiAlFeCaVNiKPb Road Dust Marine Marine/Secondary/Pulp Mill Secondary Source Profiles from PMF (Mass %)

SO 4 NO 3 NaClO1O1 O2O2 O3O3 O4O4 E1E E2E2 HSiAlFeCaVNiKPb E3E3 ZnMnTiAsCuCrBr E3E3 ZnMnTiAsCuCrBr E3E3 ZnMnTiAsCuCrBr E3E3 ZnMnTiAsCuCrBr SO 4 NO 3 NaClO1O1 O2O2 O3O3 O4O4 E1E1 SO 4 NO 3 NaClO1O1 O2O2 O3O3 O4O4 E1E1 SO 4 NO 3 NaClO1O1 O2O2 O3O3 O4O4 E1E1 E2E2 HSiAlFeCaVNiKPb E2E2 HSiAlFeCaVNiKPb E2E2 HSiAlFeCaVNiKPb Diesel Gasoline Vegetative Fuel Oil Source Profiles from PMF (Mass %)

Carbon Apportionment

Source Apportionment of Organic and Elemental Carbon using PMF SourceOC(%)EC(%) Vegetative Burning5747 Diesel Vehicles1936 Gasoline Vehicles 5 1 Secondary12 9 Fuel Oil 3 4 Road Dust 2 2 Marine (Sea Salt) 2 0

Seattle PMF vs. CMB

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

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

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)

SourceOC (%)EC (%) PMF Vegetative Denver RWC* PMF Gasoline 24 2 Phoenix Gasoline** PMF Diesel Phoenix Diesel** Source Composition of OC and EC (PMF vs Source Tests) * Watson, Chow and Houck, 1996 **Watson et al., 1994