daven k. henze with amir hakami and john h. seinfeld caltech, chemical engineering support from:...
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![Page 1: Daven K. Henze with Amir Hakami and John H. Seinfeld Caltech, Chemical Engineering Support from: NSF, EPA, TeraGrid and JPL Supercomp., W. & S. Davidow](https://reader034.vdocument.in/reader034/viewer/2022051516/56649d815503460f94a65b38/html5/thumbnails/1.jpg)
Daven K. Henzewith Amir Hakami and John H. Seinfeld
Caltech, Chemical Engineering
Support from:
NSF, EPA, TeraGrid and JPL Supercomp., W. & S. Davidow Fellowship
Source evaluation of aerosol precursors with the adjoint of GEOS-Chem
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Forward sensitivity
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Adjoint sensitivity
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Adjoint method
Depending on “model response,” can be used for:
Sensitivity analysis: quantifying influence of uncertain model parameters (emissions, reaction rates, …)
Attainment studies: assessing the effectiveness of emissions abatement
Inverse modeling: using large data sets, optimizing parameters on resolution commensurate with forward model.
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Model Description, v6-02-05 (Bey et al., 2001; Park et al., 2004)• GEOS-3 Assimilated meteorology
• 4°x5°(Global) resolution, 30 vertical levels• HOx - NOx - HC full gas-phase chemistry• Aerosols
- Secondary inorganic- Carbonaceous (primary) aerosol- Sea salt- Dust
Forward Model: GEOS-CHEM
Gas-phase emissions
SO2, NOx, NH3
Aerosol SO4
2-, NO3-, NH4
+
Gas-phase chemistryCloud processingAerosol thermo
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Discrete (adjoint of algorithm)KPP (Damian et al., 2002; Sandu et al., 2003; Daescu et al., 2003)
- chemistryTAMC (Giering & Kaminski, 1998) and manual
- aerosol thermo- cloud processing- convection
Manual- turbulent mixing- deposition- heterogeneous chemistry
The adjoint of GEOS-Chem: hybrid
Continuous (adjoint of equation) - advection (Vukicevic et al., 2001; Thuburn and Haine, 2001; Liu and Sandu, 2006; Hakami et al., 2006; Singh et al., 2006)
Henze et. al, 2007
Resources- CPU: tadj ~ 1.5 tfwd As || as the fwd model- HD: 45 GB for 1 month (4x5)
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Testing the Adjoint Model: Gradient Check
Check gradient using finite difference calculation
Component-wise analysis affords domain wide points-of-comparison
cost function
control parameter
adjoint sensitivity
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Testing the Adjoint: single processes, 1 week
(thermo only)
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Testing the Adjoint: single processes, 1 week
(thermo only)
(chem only)
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GEOS-Chem Adjoint: full chemistry
Initial Conditions (all species and tracers)
Emissions sectors- NOx (lightning, anthro)- SOx (anthro, bioburn, biofuel, ships)- NH3 (anthro, bioburn, biofuel, natural)- OC/BC (anthro, bioburn, biofuel)- others are easy to add
Reaction rate constants- All reactions- gas-phase emissions (NO, ISOP, ACET, etc.)- dry deposition
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Pollution
= non-attainment of NAAQS for PM2.5 of 15 µg/m3 (annual ave)
www.epa.gov
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Adjoint method
Depending on “model response,” can be used for:
Sensitivity analysis: quantifying influence of uncertain model parameters (emissions, reaction rates, …)
Attainment studies: assessing the effectiveness of emissions abatement
Inverse modeling: using large data sets, optimizing parameters on resolution commensurate with forward model.
![Page 13: Daven K. Henze with Amir Hakami and John H. Seinfeld Caltech, Chemical Engineering Support from: NSF, EPA, TeraGrid and JPL Supercomp., W. & S. Davidow](https://reader034.vdocument.in/reader034/viewer/2022051516/56649d815503460f94a65b38/html5/thumbnails/13.jpg)
Attainment -- Aerosols
Define cost function ~ non-attainment for PM2.5
July 2001
NH4+ non-attainment
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Attainment -- Aerosols
Define cost function ~ non-attainment for PM2.5
NH4+ non-attainment
Emissions (normalized) Sensitivities (normalized)
anth NH3
Responsibility Effectiveness
Benefit(Hakami et al., 2006)
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Attainment -- Aerosols
Seasonal variability
July
Emissions Sensitivitiesanth NH3 stack SOx
April
NH3 controls effective in spring, SO2 in summer. Also consider $$ (Pinder et. al, 2007)
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Attainment -- Aerosols
Long range transport
Emissions Sensitivities w.r.t. surface SOx
Influences concentrations, not AQ attainmentFuture emissions scenarios? Climate change? Cost?
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Adjoint method
Depending on “model response,” can be used for:
Sensitivity analysis: quantifying influence of uncertain model parameters (emissions, reaction rates, …)
Attainment studies: assessing the effectiveness of emissions abatement
Inverse modeling (Data Assimilation): using large data sets, optimizing parameters on resolution commensurate with forward model.
![Page 18: Daven K. Henze with Amir Hakami and John H. Seinfeld Caltech, Chemical Engineering Support from: NSF, EPA, TeraGrid and JPL Supercomp., W. & S. Davidow](https://reader034.vdocument.in/reader034/viewer/2022051516/56649d815503460f94a65b38/html5/thumbnails/18.jpg)
Observed Aerosol (IMPROVE): January 2002
Observed:
NIT SO4
Model:
Diff:MOD - OBS
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Inverse Model
Parameter Estimate
PredictionsAdjoint Forcing
Gradients(sensitivities)
Optimization
Forward Model Adjoint Model
Observations
Improved Estimate
-
t0 tf tf t0
Inverse Modeling using Adjoint Model
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Emissions Scaling Factors
1
10
. . .
DIFF(GC-IMPRV)
NIT
Domain wide NH3 adjustmentssimilar to inverse modelingstudy by Gilliland et al.,2006.
Optimized Anth NH3
1
10
[kg/box/s]. . .
scaling f = ln( e10/e1)
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y = 1.33x + 0.08
R2 = 0.77
y = 1.09x + 0.14
R2 = 0.780
1
2
3
0 1 2 3
Emissions Scaling Factors
NH4+
CASTNet
Optimized Anth NH3
1
10
[kg/box/s]. . .
scaling f = ln( e10/e1)
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The End
Thanks!