1. Template Comparison of PM Source Apportionment and Sensitivity Analysis in CAMx Bonyoung Koo, Gary Wilson, Ralph Morris, Greg Yarwood ENVIRON Alan Dunker General Motors R&D Center 8 th Annual CMAS Conference October 19-21, 2009 Chapel Hill, North Carolina

2. 2009 CMAS Conference 2 Probing Tools in CAMx Source Apportionment –Ozone Source Apportionment Technology (OSAT) –Particulate Source Apportionment Technology (PSAT) –Reactive Tracer Source Apportionment (RTRAC) Sensitivity Analysis –Decoupled Direct Method (DDM) for gas and particulate species –Higher-order DDM (HDDM) for gas-phase species Process Analysis –Integrated Process Rate (IPR) –Integrated Reaction Rate (IRR) –Chemical Process Analysis

3. 2009 CMAS Conference 3 Probing Tools in CAMx Source Apportionment – Tagged Species –Ozone Source Apportionment Technology (OSAT) –Particulate Source Apportionment Technology (PSAT) –Reactive Tracer Source Apportionment (RTRAC) Sensitivity Analysis –Decoupled Direct Method (DDM) for gas and particulate species –Higher-order DDM (HDDM) for gas-phase species Process Analysis –Integrated Process Rate (IPR) –Integrated Reaction Rate (IRR) –Chemical Process Analysis

4. 2009 CMAS Conference 4 Probing Tools in CAMx Source Apportionment –Ozone Source Apportionment Technology (OSAT) –Particulate Source Apportionment Technology (PSAT) –Reactive Tracer Source Apportionment (RTRAC) Sensitivity Analysis –Decoupled Direct Method (DDM) for gas and particulate species –Higher-order DDM (HDDM) for gas-phase species Process Analysis –Integrated Process Rate (IPR) –Integrated Reaction Rate (IRR) –Chemical Process Analysis

5. 2009 CMAS Conference 5 Probing Tools in CAMx Source Apportionment –Ozone Source Apportionment Technology (OSAT) –Particulate Source Apportionment Technology (PSAT) –Reactive Tracer Source Apportionment (RTRAC) Sensitivity Analysis –Decoupled Direct Method (DDM) for gas and particulate species –Higher-order DDM (HDDM) for gas-phase species Process Analysis –Integrated Process Rate (IPR) –Integrated Reaction Rate (IRR) –Chemical Process Analysis

6. 2009 CMAS Conference 6 Brute-Force Method Pollutant Concentration E0E0 E1E1 Emission0 BFM  C BFM

7. 2009 CMAS Conference 7 First-Order Sensitivity Pollutant Concentration  C DDM E0E0 E1E1 Emission0 DDM BFM  C BFM

8. 2009 CMAS Conference 8 Source Apportionment Pollutant Concentration  C PSAT E0E0 E1E1 Emission0 BFM PSAT  C BFM DDM  C DDM

9. 2009 CMAS Conference 9 Zero-Out Contribution Pollutant Concentration  C PSAT =  C BFM  C DDM E0E0 Emission0 BFM PSAT DDM

10. 2009 CMAS Conference 10 PM Modeling Episode February & July from the St. Louis 36-/12-km 2002 PM 2.5 SIP modeling Urban & rural receptors: –2 PM 2.5 NAAs –6 Federal Class-I areas BFM reductions of 20% and 100% in various emission species from anthropogenic sources PSAT and DDM Chicago PM 2.5 NAA (CNAA), St. Louis PM 2.5 NAA (SNAA), Mingo wilderness area (MING), Hercules-Glades wilderness area (HEGL), Upper Buffalo wilderness area (UPBU), Caney Creek wilderness area (CACR), Mammoth Cave national park (MACA), and Sipsey wilderness area (SIPS)

11. 2009 CMAS Conference 11 Contributions of Point-Source SO 2 to PM 2.5 Sulfate February July

12. 2009 CMAS Conference 12 Contributions of Point-Source SO 2 to PM 2.5 Sulfate February July Oxidant-limiting effects

13. 2009 CMAS Conference 13 PM 2.5 Sulfate Changes due to Point SO 2 Emiss Reductions

14. 2009 CMAS Conference 14 PM 2.5 Sulfate Changes due to Point SO 2 Emiss Reductions Oxidant-limiting effect

15. 2009 CMAS Conference 15 PM 2.5 Sulfate Changes due to Point SO 2 Emiss Reductions Non-linear responses

16. 2009 CMAS Conference 16 PM 2.5 Sulfate Changes due to On-road MV Emiss Reductions

17. 2009 CMAS Conference 17 PM 2.5 Sulfate Changes due to On-road MV Emiss Reductions February: Reducing NO x emissions Lower acidity of the aqueous phase More SO 2 dissolves in the aqueous phase More sulfate produced Negative Sensitivity Indirect effect

18. 2009 CMAS Conference 18 PM 2.5 Sulfate Changes due to On-road MV Emiss Reductions July: Reducing NO x emissions Less oxidant available to oxidize SO 2 Further reduction in sulfate Positive Sensitivity Indirect effect

19. 2009 CMAS Conference 19 PM 2.5 Ammonium Changes due to Area NH 3 Emiss Reductions

20. 2009 CMAS Conference 20 PM 2.5 Nitrate Changes due to Area NO x Emiss Reductions

21. 2009 CMAS Conference 21 PM 2.5 Nitrate Changes due to On-road MV Emiss Reductions Less indirect effect because NO x dominates on-road MV emission

22. 2009 CMAS Conference 22 PM 2.5 SOA Changes due to Area VOC Emiss Reductions

23. 2009 CMAS Conference 23 Primary PM 2.5 Changes due to On-road MV Emiss Reductions

24. 2009 CMAS Conference 24 Summary 1 st -order DDM sensitivities agree well with the BFM model responses to small emission changes (20%) –With large emission changes, non-linearity comes into play –For SOA and primary PM 2.5, the DDM works relatively well even with 100% emission reductions PSAT and zero-out are nearly equivalent in cases with no indirect effect –PSAT starts to deviate from the zero-out contribution as indirect effects from limiting reactants or non-primary precursor emissions become important

25. 2009 CMAS Conference 25 Summary (cont.) Source sensitivity and source apportionment are equivalent for pollutants that are linearly related to emissions; However, when they are different: –PSAT is best at apportioning PM pollutants to sources emitting their primary precursors (e.g., sulfate to SO 2, nitrate to NOx) –DDM sensitivities are more accurate than PSAT in determining the impact of emissions that have indirect effects on secondary PM –PSAT works better at estimating the impact of zeroing- out a source while DDM does generally better when a fraction of emissions are eliminated from the source

26. 2009 CMAS Conference 26 Summary (cont.) BFM (zero-out) also has limitations: –Computationally expensive and subject to numerical noises –Sum of the BFM source contributions will not always equal the simulated concentrations in the base case

27. 2009 CMAS Conference 27 Acknowledgement Funded by the Coordinating Research Council For more details… Koo, B., G. M. Wilson, R. E. Morris, A. M. Dunker and G. Yarwood. 2009. “Comparison of Source Apportionment and Sensitivity Analysis in a Particulate Matter Air Quality Model.” Environ. Sci. Technol., 43 (17), pp 6669-6675. doi: 10.1021/es9008129