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Source Apportionment of Water Soluble Elements, EC/OC, and BrC by PMF

Source Apportionment of Water Soluble Elements, EC/OC, and BrC by PMF. Linghan Zeng 04/21/2016. Introduction. Why do I focus on water soluble elements ? Why do the source apportionment?. Positive Matrix Factorization (PMF). Receptor Model

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Source Apportionment of Water Soluble Elements, EC/OC, and BrC by PMF

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  1. Source Apportionment of Water Soluble Elements, EC/OC, and BrC by PMF Linghan Zeng 04/21/2016

  2. Introduction • WhydoIfocusonwatersolubleelements? • Whydothesourceapportionment?

  3. Positive Matrix Factorization (PMF) • Receptor Model • A model for pollutant source identification contributing to the observed chemical concentrations at a receptor site. • Receptor modeling utilizes composition data collected at the receptor site to determine the source attributions.

  4. PMF Equation X = GF + E Source Profiles (p×m) Residuals (n×m) Source Contributions (n×p) Samples (n×m)

  5. Sample Description • Sites • Jefferson Street (JST) • Georgia Tech (GT) • Road Side (RS)

  6. Sample Description

  7. Data used in PMF • S, K, Ca, Ti, Mn, Fe, Cu, Zn, As, Se, Br, Sr, Ba, Pb were measured by XRF • EC/OC • BrC • Missing values are replaced by species median with 400% uncertainties. • Values below limit of detection are replaced by half of LOD with 5/6 uncertainties.

  8. Data Summary

  9. Concentration Seasonal Variation

  10. Result Four factors solution is the optimal. Transportation: Cu, Fe, Ba，EC Biomass Burning: K, BrC Mineral Dust: Ca, Mn Secondary Formation: S

  11. Other Results

  12. Biomass Burning Transportation Secondary Formation Mineral Dust

  13. Factor Contribution for Mn, Fe, Cu Cu Mn Fe

  14. Limitation • Requirelargesample number • Hard to distinguish sources with similar profiles. • No physical or chemical mechanism to support the results • Factorexplanationdependsonusers

  15. FutureWork (if needed) • UncertaintyAnalysis • Oxidative potential vs redox-active elements • Compare source apportionment with other models

  16. Thank you!

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