What You Should Know About Air Quality Modeling
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What You Should Know What You Should Know About Air Quality Modeling About Air Quality Modeling Tyler Cruickshank & Patrick Barickman State of Utah Department of Environmental Quality Division of Air Quality
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What You Should Know About Air Quality Modeling. Tyler Cruickshank & Patrick Barickman State of Utah Department of Environmental Quality Division of Air Quality. λ 2. ∫. ј A = σ A ( λ ,T) Ф A ( λ ,T)I( λ ) d λ. λ 1. Objective 1: . Derive each term of the first-order rate - PowerPoint PPT Presentation
Transcript of What You Should Know About Air Quality Modeling
What You Should Know What You Should Know About Air Quality ModelingAbout Air Quality Modeling
Tyler Cruickshank & Patrick BarickmanState of UtahDepartment of Environmental QualityDivision of Air Quality
јA = σA(λ,T)ФA(λ,T)I(λ) dλ∫λ1
λ2
where,
јA is the First-order rate constant for photolysis (јA )
Objective 1: Objective 1: Derive each term of the first-order rate constant for winter-time photolysis .
Modeling Atmospheric ChemistryModeling Atmospheric Chemistry
The Model - CMAQ?
What Are People Doing With CMAQ?
What You Should Know About CMAQ Results (Challenges).
CMAQ
Simulates:
Gas phase: NO2, NO, O3, OH, VOC’s, …Aerosol Phase: NH4, NO3, OC, EC, …Wet DepositionDry Deposition
CMAQ is a 3-D Grid Based Model
MM5 or WRFMM5 or WRF
Meteorology Interface Processor (MCIP)Meteorology Interface Processor (MCIP)- Interpolate met fields to CMAQ grid
CMAQCMAQInitial Chemistry ConditionsBoundary Chemistry ConditionsGas Phase ChemistryAerosol Chemistry
Emissions (SMOKE)Emissions (SMOKE)AreaPointMobileBiogenic
Too Much InterpolationNo Feedback
CMAQ Model StructureCMAQ Model Structure
A Coupler Has Been Developed (but not released)
CMAQCMAQWRFWRFCMAQ “Calls”
Chemistry Feedback
Next Generation CMAQNext Generation CMAQ
1) Pollution control strategies
2) Research
3) Operational air quality forecasting
CMAQ ApplicationsCMAQ Applications
Let’s look at some examples.Let’s look at some examples.
Annual Ozone Mortalities (cardiopulmonary)Annual Ozone Mortalities (cardiopulmonary)
Mortalities/1000km Mortalities/1,000,000 people
Casper and West. CMAS 2008
Air Pollution & Health ImpactsAir Pollution & Health Impacts
Lin 2008. CMAS 2008
Evaluation of Mercury Outflow from East Asia using CMAQ-Hg
Asian TransportAsian Transport
Lightning NOx Emissions
Kaynak 2008. CMAS 2008
Operational ForecastingOperational Forecasting
2.5 km5 km12 km
Winter PM2.5Summer O3
Secondary pollutantsSecondary pollutants
Utah’s Air Quality Modeling ApplicationsUtah’s Air Quality Modeling Applications
Not just dust and “stuff”, but complex gaseous chemistrythat creates O3 and PM2.5.
1. Chemistry based on “summer” laboratory data.
2. UV ground surface albedo & photolysis rates.
3. Poor western landuse data and biogenic emissions.
Atmospheric Chemistry Modeling ChallengesAtmospheric Chemistry Modeling Challenges
Examples:
Wont even talk about this challenge …NN
SSEE
WW
Salt Lake Valley
► Model development history
Where:California, Eastern USOzone
When:Chemical Mechanisms: 1970’s – 1980’sFirst CMAQ: June 1998
► Today’s wide ranging applications & challenges
Chemistry Based on Summer Laboratory DataChemistry Based on “Summer” Laboratory DataChemistry Based on “Summer” Laboratory DataChallenge #1Challenge #1
CONUS 365 days/year
UNKNOWN3%
AMMONIUM NITRATE
67%
AMMONIUM SULFATE
13%
CARBON16%
PM2.5: Ammonium Nitrate (NH4NO3)PM2.5: Ammonium Nitrate (NH4NO3)
Wasatch Front Inversion PM2.5 Components
Wasatch Front’s Winter-Time ChallengeWasatch Front’s Winter-Time Challenge
HNO3 + NH3
Daytime Pathway to HNO3
O3 + λ -> O2 + 2 OHNO2 + OH -> HNO3
Nighttime Pathway to HNO3
N2O5 + H2O -> HNO3
N2O5 lab data performed at 293+ K
Ultra Violet (UV) Radiation
Ammonium Nitrate (NH4NO3) Particulate Ammonium Nitrate (NH4NO3) Particulate
1)
2)
Ultraviolet Radiation ultimately creates O3 and HNO3
UV Ground Surface AlbedoUV Ground Surface AlbedoChallenge #2Challenge #2
O3
ScatteredIncid
ent
Reflection
Actinic flux = Incident + Scattered + Reflected
Estimated UV Albedo ValuesEstimated UV Albedo Values
Data from Tanskanen and Manninen (2007)
Croplands: 0.37
“Bare” Ground: 0.83
Evergreens: 0.27
Grasses: 0.72
CMAQ/JPROC Uses 0.05
Photolysis Rate Sensitivity to UV AlbedoPhotolysis Rate Sensitivity to UV Albedo
NO2 Photolysis Rates
0
0.25
0.5
0.75
1
0 0.25 0.5 0.75 1UV Albedo
July 18 January 18
NO
2 Ph
otol
ysis
Rat
e
CMAQ Results: OCMAQ Results: O3 3 @ 1400 MST - Difference Plots@ 1400 MST - Difference Plots
0.850.85
Albedo O3 HNO3 NO3(p) NH4(p) NH4NO3
0.55 +27% +14% +33% +22% +30%
0.65 +34% +17% +43% +29% +38%
0.75 +41% +21% +54% +36% +48%
0.85 +49% +26% +66% +45% +59%
Maximum Hourly Concentration Change
Poor Western Landuse Data & Biogenic EmissionsPoor Western Landuse Data & Biogenic Emissions
Challenge #3Challenge #3
Biogenics (VOC’s) play a significant role in atmospheric chemistry.
Some biogenic species are highly reactive WRT the formation of ozone.
Gamble Oak: IsopreneJuniper, Saltbush: λ-pineneRabbitbrush: LimoneneSagebrush: Other monoterpenes
Categorized as USGS Shrubland
Q: All “Shrublands” = ? A: Probably Not ….
* This is an issue in met modeling as well.
Species?Leaf Area Index?Species Emission Factors?
Landuse Data Landuse Data
& Biogenic Emissions& Biogenic Emissions
0%
10%
20%
30%
40%
0 24 48 72 96 120 144 168
Salt Lake City
0%
10%
20%
30%
40%
0 24 48 72 96 120 144 168
Logan
Biogenics Impact on Ozone (CMAQ Model – July 2005)
+
+
Biogenics and Ozone FormationBiogenics and Ozone Formation
ConclusionsConclusions
• It is the only tool that we have so …
• Utah is up a creek.
• Significant challenges exist (external/internal)
Time-Science.com
• But progress is being made.
