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Source Apportionment of Water-Soluble Elements Using PMF

Explore source apportionment of water-soluble elements using Positive Matrix Factorization (PMF). Receptor modeling identifies pollutant sources contributing to chemical concentrations at receptor sites. Data from sites like Jefferson Street, Georgia Tech, Road Side are utilized. Key elements measured include S, K, Ca, Ti, Mn, and more. Factors like Transportation, Biomass Burning, Mineral Dust, and Secondary Formation are analyzed. Limitations and future work are discussed for improved understanding.

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Source Apportionment of Water-Soluble Elements Using 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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