Estimating uncertainties and uncertainty contributors of CMB PM2.5 source apportionment results |
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| Authors: | Sangil Lee Armistead G Russell |
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| Institution: | aSchool of Civil and Environmental Engineering, Georgia Institute of Technology, 311 Ferst Drive, Atlanta, GA 30332-0512, USA;bSchool of Earth and Atmospheric Sciences, Georgia Institute of Technology, 311 Ferst Drive, Atlanta, GA 30332-0340, USA |
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| Abstract: | The chemical mass balance (CMB) model was applied for source apportionment of PM2.5 in Atlanta in order to explore levels and causes of uncertainties in source contributions. Monte Carlo analysis with Latin hypercube sampling (MC-LHS) was performed to evaluate the source impact uncertainties and quantify how uncertainties in ambient measurement and source profile data affect results. In general, uncertainties in the source profile data contribute more to the final uncertainties in source apportionment results than do those in ambient measurement data. Uncertainty contribution estimates suggest that non-linear interactions among source profiles also affect the final uncertainties although their influence is typically less than uncertainties in source profile data. |
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| Keywords: | CMB PM2 5 Uncertainty Monte Carlo analysis |
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