Implementation of a direct sensitivity method into CMAQ Daniel S. Cohan, Yongtao Hu, Amir Hakami, M. Talat Odman, Armistead G. Russell Georgia Institute of Technology, Atlanta, GA Presentation to Models-3 Users’ Workshop October 22, 2002

( ) CMAQ CMAQ Δ ΔSIMULATIONSENSITIVITY

Uses of Sensitivity Policy development:Policy development: –Impact of emission control measures –Impact of new emitters Uncertainty analysis:Uncertainty analysis: –Dependence of model results on assumptions Inverse modeling (“Area of Influence”):Inverse modeling (“Area of Influence”): –Which emitters affect a receptor

Sensitivity Methods “Brute-Force” Method:“Brute-Force” Method: –Run CMAQ once for a “base case” –Run CMAQ again for each of N perturbations Direct Decoupled Method: (Dunker 1981, Yang et al., 1997)Direct Decoupled Method: (Dunker 1981, Yang et al., 1997) –Solve for sensitivities decoupled from concentrations, using the same numerical routines in a single CMAQ run –Local, first-order sensitivities:

Sensitivity Parameter (e.g., NO x Emissions) Conc. (e.g., O 3 )  DDM Sensitivity = tan(  ) pjpj BF  ∆Ci∆Ci DDM and Brute Force

I.C., B.C., Emissions Advection & Diffusion Chemistry Concentrations(t) Sensitivities(t) Direct Decoupled Method Concentrations (t+Δt) (t+Δt) Sensitivities (t+Δt)

Pros & Cons Brute Force: ▲ Simple ▲ Captures non-linearities ▼ Inefficient for large N ▼ Inaccurate for small perturbationsDDM: ▲ Efficient for large N ▲ Accurate for small perturbations ▼ Does not capture non-linearities

Demonstration of CMAQ-DDM Fall-Line Air Quality Study: Fall-Line Air Quality Study: Focus on Georgia Focus on Georgia 12 km horizontal; 13 layers 12 km horizontal; 13 layers SAPRC-99 chemistry SAPRC-99 chemistry SAMI emissions inventory SAMI emissions inventory DDM (implemented so far): gas-phase gas-phase first-order first-order emissions, I.C., & B.C. emissions, I.C., & B.C.

DDM: O 3 to Isoprene & NO x

Sensitivity to point NO emissions DDM to Actual NO Emissions DDM to 1 mol/s, Layer 6 Emission

DDM vs. Brute Force: Ozone Initial Conditions DDM Brute Force

DDM vs. Brute Force: Domainwide NO x Emissions DDM Brute Force

DDM vs. Brute Force: Single Point NO DDM Brute Force

Area of Influence R E E AOI E DDM E DDM shows impact of one emitter on concentrations domainwide To compute the receptor- based “Area of Influence”: 1.Compute DDM for unit emissions from various emitters E 2.Interpolate to obtain AOI of receptor R to every emitter E 3.Scale to amount of emissions at each E

AOI: Atlanta Ozone to NO Response to 1 mol/s NO source Scaled by NO emissions

AOI: Macon Ozone to NO Response to 1 mol/s NO source Scaled by NO emissions

Conclusions DDM and Area of Influence enhance the functionality of CMAQDDM and Area of Influence enhance the functionality of CMAQ Strong agreement with brute force, even for fairly large perturbationsStrong agreement with brute force, even for fairly large perturbations Future work will incorporate:Future work will incorporate: – higher-order sensitivities – aerosols – further exploration of AOI