Single Source Modeling wit

Photochemical Models

Kirk Baker

U. S. Environmental Protection Agency,

Research Triangle Park, NC

Presented at the 2008 9th Modeling Conference
Basic Components of Air Quality Modeling 
• 1st-generation AQM (1970s - 1980s) – Dispersion Models (e.g., Gaussian Plume 

– Photochemical Box Models (e.g. OZIP/EK

• 2nd-generation AQM (1980s - 1990s) – Photochemical grid models (e.g., UAM, R• 3rd-generation AQM (1990s - 2000s) – Community-Based “One-Atmosphere” Mo

System (e.g., U.S. EPA’s Models-3/CMAQ

Evolution of Air Quality Mo
Air Toxics

PM

Acid Rain

Visibility

Ozone

One-Atmosphere Approach

Mobile Sources

Industrial Sources

Area Sources

(Cars, trucks, planes,

boats, etc.)

(Power plants, refineries/chemical plants, etc.)

(Residential, farmingcommercial, biogenic, etc.)

NOx, VOC,PM, Toxics

NOx, VOC, SOx, PM,Toxics

NOx, VOC,PM, Toxics

ChemistryMeteorology

Atmospheric 

Deposition

Climate Change
∂Ci

∂t

= −∇ • (VCi) + ∇ • (K∇Ci)+Pi − LiCi + Si 

Advection Chemistry 

Diffusion Emis

• Chemical Transformations (Gas- & Aqueou

phase and Heterogeneous Chemistry)

• Advection (Horizontal & Vertical)• Diffusion (Horizontal & Vertical)• Removal Processes (Dry & Wet Deposition)Species Mass Continuity Equation:

Major Atmospheric Processes Sim

in Air Quality Models
Gaussian Dispersion Model

ISC3, CALPUFF, AERMOD CMAQ, 

(for primary pollutant) (multi-pollutant one

First

-Generation Air Quality Mod

Photochemical G
PCM/Source Apportionment Advantag

• Full state of the science gas-phase chemistry

– Ability to estimate realistic ozone concentrations– No need for a constant ozone background value for PM

• Advanced aqueous phase chemistry provides realistic sulfat

estimates; wet and dry deposition processes include

d

• Photochemical models generally have good temporal and sp

estimates of ammonia concentrations

• Spatial/temporal representation of ammonia and nitric acid 

concentrations and state of the science inorganic chemistry (ISORROPIA) allow for realistic nitrate partitioning between gparticle phase

• Source apportionment tools allow for tracking of single emiss

sources or groups of emissions sources
PCM Source Apportionment Backgrou

• Photochemical models 

estimate [single] source contribution with source 

apportionment routines

• Source apportionment tracks 

the formation and transport of PM2.5/ozone from emissions sources and allows the calculation of contributions at receptors

• Chemically speciated PM2.5 

contribution can be converted to light extinction for visibility applications

• Precursor emissions 

chemically speciated ozone, toxics

NOX 

 NO3

- SOX 

 SO4

=

NH3 

 NH4

+

Primary OC 

 POC

Primary EC 

 PEC

Primary Other 

 POT

VOC 

 SOA

NOX 

 O3

VOC 

 O3
Particulate Source Apportionment

• Particle and Precursor Tagging Methodology (PPTM) has 

implemented in CMAQ v4.6

• Particulate Source Apportionment Technology (PSAT) ha

implemented in CAMx v4.5

• Tracks contribution to mercury and PM sulfate, nitrate, am

secondary organic aerosol, and inert species

• Estimates contributions from emissions source groups, em

source regions, and initial and boundary conditions to PMadding duplicate model species for each contributing sour

• These duplicate model species (tags) have the same prop

experience the same atmospheric processes as the bulk cspecies

• The tagged species are calculated using the regular mode

processes like dry deposition and advection as bulk speci

• Non-linear processes like gas and aqueous phase chemis

solved for bulk species and then apportioned to the tagge
Ozone Source Apportionment

• Ozone source apportionment 

has been implemented in CAMx v4.5 (OSAT & APCA) and CMAQ v4.6 (OPTM)

• Tracks ozone contribution from 

sources similarly to PM with reactive tracers

• July maximum ozone 

contribution from a source shown at right

• OSAT is simulated separately 

from particulate source apportionment
Total Light Extinction

Annual Maximum Light Extinction (1/M

Ammonium Nitrate Ammon

Other: Metals/Soil/Etc Primary Organic Carbon Eleme
Qualitative comparison to screening me

Emissions/Distance

Emissions/Distance Total Light 
Issues using PCM for Single Source 

• Photochemical models resource intensive 

(computational, disk space, staff) for multi-year applications, especially at grid resolutions <= 12

• Additional level of staff expertise• Existing community emissions inputs (from State

RPOs, etc) for photochemical models are actuaemissions and may need to be modified if more conservative emissions estimates are necessary

• Useful for near-field applications?
Near Field & Long Range Transp

• Further research is necessary to 

determine how useful PCMs are for near-field modeling (<50 km)

• Currently, some photochemical 

models support full science subgrid plume treatment, sub-cell receptor locations, and 2-way nesting capability

• Review existing near-field 

applications using PCMs, evaluate tracer studies
Other Work

• Midwest RPO did some preliminary testin

an evaluation of CAMx PSAT or CALPUFsingle source modeling with CAMx PSAT compare with CALPUFF visibility estimate

• Several States did single source visibility 

modeling for sources less than 50 km froI areas; used sub-grid plume treatment
MRPO: CALPUFF (left) and CAMx PSAT 

• Annual 2002 Simulations using latest 

version of CALPUFF (incl. POSTUTIL and 

CALPOST)

• Meteorological input data is hourly and 

from an annual 2002 MM5 simulation

• Grid is consistent with photochemical 

model grid: 97 X 90 x 16 (36km grid cells) over Eastern U.S.

• Results show the number of times

each grid cell exceeds the 24hr average .5 DV degradation over “background” visibility

• Results are the combined visibility 

degradation from sulfate and nitrate

• These runs were facility total actual 

emissions

• Applied CAMx4 PSAT su

Sept 2002

• These results do not show 

from nitrate; Assume that degradation is dominated sulfate

• Results for each facility a

similar to CALPUFF resu> .5 DV change over natubackground conditions

• fRH values derived using 

average relative humidity cell as predicted by MM5 calculated using the exacup table that is used in Cmaximum daily average R
Total 24hr avg .5 DV Exceedances

CALPUFF (top) CAMx4 PSAT (bottom)

*CALPUFF includes sulfate+nitrate and CAMx4 includes s
*CALPUFF includes sulfate+nitrate and CAMx4 includes s

Total 24hr avg .5 DV Exceedances

CALPUFF (top) CAMx4 PSAT (bottom)
MRPO Conclusions

• CAMx4 PSAT results do not show visibilit

degradation as far downwind as CALPUF

• Need to consider nitrate PSAT runs for b

comparison although visibility degradatioexpected to be dominated by summer su

• The tools agree qualitatively for certain fa

but not all of them
Final Remarks

• Photochemical grid models provide an 

opportunity for credible single source mowith source apportionment methodology

• These models have the advantage of sta

the science chemistry, but that comes witincreased resource burden

• These models are routinely used for othe

regulatory purposes like O3/PM2.5/RegioHaze State Implementation Plans
END OF PRESENTATIO
Post-Processing

• Estimate .5 DV changes over natural backgroun

conditions

• Methodology equivalent to CALPOST visibility p

processing

• A natural background value of 18 1/Mm is used 

Eastern U.S. (see CALPUFF manual)

• A count of > .5 DV change over natural backgro

kept for each grid cell and compared to Class I a

• Bext Total = Bext Modeled + Bext Background• Delta DV = 10*ln(Bext Total/10) – 10*ln(Bext

Background/10)
Daily avg RH

PSAT Results:

fRH calc from 24-hr RH v monthly gridded fRH val

Monthly avg fRH

Monthly avg fRH

Daily avg RH
Soil EC

Primary OC

Anthropogenic Bi

VOC

S

OC

 PM2.5 Chemical Composition

Sulfate

SO2

OH, H2O2, O3

VOC, NOx

O2, Fe, Mn

Oxidizing Agent

H2SO4

NOx O3 and OH

HNO3

VOC, NOx

NH3

Nitrate 

•PM2.5 Nitrate formation depends on temperature, humidity

concentration of other nearby species•PM2.5 Nitrate formation is favored by lower temperatures a

humidity (winter and night-time)•PM2.5 Sulfate and Organic Carbon is higher during the sum

there is higher availability of by-products of photochemical 
Regional Photochemical Models: TOPTool for O3, PM2.5 (and Haze)

~ 9 miles
CALPUFF Sensitivity

• Sensitivity simulation for visibility 

calculation parameter BCKNH3

• Background ammonia concentration

(same value for entire domain for enyear)

• Important parameter in CALPUFF 

estimation of PM2.5 nitrate
CALPUFF Sensitivity:BCKNH3 = 1.0 (basecase/default)BCKNH3 = 0.5 and 1.5

Difference Plot SENS-BASE Difference Plot SENS-BASE