Applicability of CMAQ-DDM to source apportionment and control strategy development

1. Applicability of CMAQ-DDM to source apportionment and control strategy development Daniel Cohan Georgia Institute of Technology 2004 Models-3 Users’ Workshop October 19, 2004

2. Policy Applications of AQ Models • Source apportionment • How much of ambient pollutant concentrations can be attributed to each emission source? • Control strategy assessment • How would concentrations change under a control measure? • Forward projections • How will concentrations change under future trends (regulation, technology, growth)?

3. Emissions, Initial Conditions, Boundary Conditions, etc. ∆ (e.g., Atlanta Emissions) Air Quality Model Air Quality Model Concentrations Sensitivities ∆ Check scientific understanding Extend beyond observations Forecasting and prediction Atmospheric response Control strategies Source apportionment

4. Complication: Nonlinearity ENOx • Often, only a handful of sensitivities are modeled (e.g., 30% NOx reduction, 30% VOC reduction) • Linear scaling and additivity assumption may be inaccurate • But it may be impractical to model all combinations of emission sources or control measures High O3 Low O3 EVOC

5. Brute ForceandHDDM-3D Ozone A + CA ∆C a1 B + CB EVOC -DeEA EB EA

6. Applications of HDDM-3D Incremental sensitivity Control strategy Source apportionment Taylor expansion(=-1) S.C. ≈S(1) - 0.5∙S(2) First-order sensitivity S(1) = ∂C/∂ Taylor expansion(<0) C ≈C0+ S(1) + 0.52S(2)

7. Consistency of local sensitivities Brute Force HDDM-3D R2 > 0.99 Low bias & error

8. HDDM performance & nonlinearity 1st+2nd order: Well captures response DDM – Brute Force 1st order only: Extent of nonlinearity % emission reduction For 8-hr ozone, averaged over 12-km domain, Aug. 13-19, 2000 (2007 emissions)

9. Interactions of emission impacts Impact of single perturbation: E(x,t)=E0(x,t)+εjpj(x,t) 1st-order 2nd-order Impact of dual perturbation: E(x,t)=E0(x,t)+εjpj(x,t)+εkpk(x,t) 1st-order 2nd-order Cross term

10. Isopleths of atmospheric response Atlanta Macon Ozone (ppmV) August 17, 2000 peak-hour ozone (from the method of Hakami et al., 2004)

11. Atlanta apportionment by NOx category Cross-sens. Contribution to Atlanta ozone (ppm) Sum of parts Atlanta NOx: Aggregate Atlanta NOx: By Category Atlanta MSA, 8-hour ozone, Aug. 13-19, 2000 (Year 2007 emissions)

12. Macon apportionment by NOx source region A B S M Macon MSA, Aug. 13-19, 2000 (2007 emissions)

13. Recommendations • HDDM-3D is a powerful scoping tool for examining numerous source contributions or control measures, and the interactions among pairs • Caution: Only 1st order DDM-3D is being implemented for PM • Due to nonlinearity and non-additivity, an aggregate brute force assessment should be used to evaluate the cumulative effect of the entire strategy • Iterative DDM-3D / brute force approach may be considered • Important to match modeling methods to objectives in source apportionment and strategy assessment • Contribution of aggregate emissions may differ from sum of parts

14. Acknowledgments • Funding: Fall-Line Air Quality Study (Georgia Environmental Protection Division and the Fall-Line cities) • Amir Hakami, Yongtao Hu, Ted Russell