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Source Apportionment of PM 2.5 With CMB8

Source Apportionment of PM 2.5 With CMB8. Limitations of the CMB Approach. Source Apportionment. Source apportionment is used to determine the contribution of various sources to ambient particulate matter. Important for determining how to control PM2.5 levels. Two typical approaches

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Source Apportionment of PM 2.5 With CMB8

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  1. Source Apportionment of PM2.5 With CMB8 Limitations of the CMB Approach

  2. Source Apportionment • Source apportionment is used to determine the contribution of various sources to ambient particulate matter. • Important for determining how to control PM2.5 levels. • Two typical approaches • Use source profiles to determine contributions. • Use variation in composition to find source compositions and impacts. (Factor Analysis)

  3. What is CMB? • CMB – Chemical Mass Balance • Used for source apportionment of particulate matter. • CMB8 – Latest version of EPA Software used for source apportionment.

  4. How Does CMB Work? • Least-squares approach. • Matrix-based: • Sij – Emissions of compound i from source j. • Ij – Contribution of source j. • Ci – Concentration of compound i.

  5. Limitations of CMB • Reactive compounds • Need more compounds than sources • Consequence of math – need at least as many equations as variables • Must know emission compositions (source profiles)

  6. Limitations of CMB (continued) • High sensitivity to uncertainty/error in source profiles. • Omission of a source can lead to large errors. • Similar (co-linear) sources can cause considerable error.

  7. CMB Study • Data collected at Jefferson Street site over a 11-day period (1/1/00 to 1/11/00).

  8. CMB Study

  9. CMB Results

  10. CMB Study • New Approach – Combine gasoline and diesel sources into a single source. • Eliminates issues of co-linearity by combining two highly correlated sources.

  11. CMB Study – 1/1/00

  12. CMB Study – 1/8/00

  13. Conclusions • Standard CMB can provide unrealistic results, particularly in the area of vehicular emissions. • By combining gasoline and diesel emissions, issues related to co-linearity are partially resolved, leading to more accurate results.

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