PM%202.5%20Source%20Apportionment%20and%20Control%20Strategy

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PM 2.5 Source Apportionment and Control Strategy

• Sun-Kyoung (Helena) Park
• Environmental Engineering, Georgia Institute of
  Technology

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Content

• PM 2.5 in Atlanta
• Source Apportionment Receptor Modeling
• Chemical Mass Balance (CMB)
• Principal Component Analysis (PCA)
• Control Strategy
• Conclusion

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PM 2.5 in Atlanta

• PM 2.5 Particles of size less than 2.5 mm

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Content

• PM 2.5 in Atlanta
• Source Apportionment Receptor Modeling
• Chemical Mass Balance (CMB)
• Principal Component Analysis (PCA)
• Control Strategy
• Conclusion

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Source Apportionment - Receptor Modeling
Objective
Receptor models use the chemical and physical
characteristics of gases and particles measured
and source and receptor to identify the presence
and to quantify source contributions to receptor
concentration
Methods
Chemical Mass Balance (CMB) receptor model
Each receptor chemical concentration is expressed
as a linear sum of products of source profile and
source contributions
Principal Component Analysis (PCA)
Identify principal components which maximize the
covariance matrix of pollutant dataset
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Content

• PM 2.5 in Atlanta
• Source Apportionment Receptor Modeling
• Chemical Mass Balance (CMB)
• Principal Component Analysis (PCA)
• Control Strategy
• Conclusion

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Chemical Mass Balance (CMB)
A ( x1 0.23x2 0.73x3 30.80x4 19.7x5 )
B ( 15.20 x1 0.36 x2 3.15 x3 4.09 x4
5.20 x5 ) C ( 0.26 x1 0.36 x2
0.21 x3 2.40 x4 52.93 x5 ) 3.36 x1
0.97 x2 1.2 x3 1.29 x4 2.91 x5 Number of
Unknowns 3, Number of the Independent Equations
5 ? A, B and C are fitted using the least square
fitting
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Chemical Mass Balance (CMB)
PM 2.5 in Jefferson Street
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Content

• PM 2.5 in Atlanta
• Source Apportionment Receptor Modeling
• Chemical Mass Balance (CMB)
• Principal Component Analysis (PCA)
• Control Strategy
• Conclusion

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Principal Component Analysis (PCA)
Identify principal components which maximize the
covariance matrix of pollutant dataset
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Content

• PM 2.5 in Atlanta
• Source Apportionment Receptor Modeling
• Chemical Mass Balance (CMB)
• Principal Component Analysis (PCA)
• Control Strategy
• Conclusion

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Control Strategy
Roll-Back Method
E(c) Annual Mean ConcentrationE(c)s Annual
Mean Concentration in the Futurek
growth factorcb Background Concentration
( 3 mg/m3)
  Emission source reduction required for
meeting NAAQS
Jefferson Street Fort McPherson South Dekalb Tucker
Mean PM 2.5 21.1 mg/m3 19.1 mg/m3 16.9 mg/m3 20.2 mg/m3
Based on the mean concentration 33.7 25.4 13.7 30.2
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Content

• PM 2.5 in Atlanta
• Source Apportionment Receptor Modeling
• Chemical Mass Balance (CMB)
• Principal Component Analysis (PCA)
• Control Strategy
• Conclusion

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Conclusion

• Major species of PM 2.5 in Atlanta ?
  Sulfate 24 ? Nitrate 5 ? Ammonium 8.5
  ? Elemental Carbon 7.8 ? Organic Carbon
  29.7
• The major sources of PM 2.5 in Jefferson Street
  site ? Diesel Engine ? Wood Burning ? Power
  Plant
• The emission source reductions required ? Fort
  McPherson 25.4 ? South Dekalb 13.7 ?
  Tucker 30.2 ? Jefferson Street 33.7

• The control strategy should focus on the major
  sources of PM 2.5 and consider the sensitivity
  between source and the pollutant concentration

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Questions Comments
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Appendix
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Chemical Mass Balance (CMB)
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Chemical Mass Balance (CMB)

• Chemical Mass Balance (CMB) receptor model
• Each receptor chemical concentration is expressed
  as a linear sum of products of source profile and
  source contributions
• Assumption
• Compositions of source emissions do not change.
• All potential sources are identified and
  characterized.
• The source profiles are linearly independent of
  each other
• Number of source categories is less than or
  equal to the number of species

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Principle Component Analysis (PCA)
Identify principal components which maximize the
covariance matrix of pollutant dataset
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Site Map

• Jefferson Street
• Fort McPherson Army Center
• South Dekalb
• Tucker