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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. SIMULATION. SENSITIVITY. I.C. I.C. B.C. B.C.

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implementation of a direct sensitivity method into cmaq

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

slide2

SIMULATION

SENSITIVITY

I.C.

I.C.

B.C.

B.C.

Emissions

Emissions

( )

Δ

CMAQ

CMAQ

( )

Δ

uses of sensitivity
Uses of Sensitivity
  • Policy development:
    • Impact of emission control measures
    • Impact of new emitters
  • Uncertainty analysis:
    • Dependence of model results on assumptions
  • Inverse modeling (“Area of Influence”):
    • Which emitters affect a receptor
sensitivity methods
Sensitivity Methods
  • “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)
    • Solve for sensitivities decoupled from concentrations, using the same numerical routines in a single CMAQ run
    • Local, first-order sensitivities:
slide5

DDM andBrute Force

Conc.

(e.g., O3)

DDM

BF

∆Ci

a2

a1

Sensitivity = tan(a)

Sensitivity Parameter

(e.g., NOx Emissions)

Dpj

slide6

Direct Decoupled Method

Concentrations

(t)

Concentrations

(t+Δt)

Chemistry

Advection &

Diffusion

I.C., B.C.,

Emissions

Chemistry

Sensitivities

(t)

Sensitivities

(t+Δt)

pros cons
Pros & Cons

Brute Force:

▲Simple

▲ Captures non-linearities

▼Inefficient for large N

▼Inaccurate for small perturbations

DDM:

▲ Efficient for large N

▲ Accurate for small perturbations

▼ Does not capture non-linearities

demonstration of cmaq ddm
Demonstration of CMAQ-DDM
  • Fall-Line Air Quality Study:
  • Focus on Georgia
  • 12 km horizontal; 13 layers
  • SAPRC-99 chemistry
  • SAMI emissions inventory
  • DDM (implemented so far):
  • gas-phase
  • first-order
  • emissions, I.C., & B.C.
sensitivity to point no emissions
Sensitivity to point NO emissions

DDM to Actual NO Emissions

DDM to 1 mol/s, Layer 6 Emission

slide14

DDM

E

R

AOI

DDM

DDM

E

E

E

Area of Influence

  • DDM shows impact of one emitter on concentrations domainwide
  • To compute the receptor-based “Area of Influence”:
      • Compute DDM for unit emissions from various emitters E
      • Interpolate to obtain AOI of receptor R to every emitter E
      • Scale to amount of emissions at each E
aoi atlanta ozone to no
AOI: Atlanta Ozone to NO

Response to 1 mol/s NO source

Scaled by NO emissions

aoi macon ozone to no
AOI: Macon Ozone to NO

Response to 1 mol/s NO source

Scaled by NO emissions

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