Proof-of-Concept Evaluation of Use 

Photochemical Grid Model Sourc

Apportionment Techniques for Preve

of Significant Deterioration of Air Qu

Analysis Requirements

Bret Anderson, Kirk Baker, Ralp

Morris, Chris Emery, Andy 

Hawkins, Erik Snyder
Acknowledgements to 

Contributors

• Kirk Baker, USEPA OAQPS• Ralph Morris and Chris Emery, ENV• Andy Hawkins, State of Kansas

• Erik Snyder, USEPA Region 6
Outline

• Introduction to the air quality analysis 

requirements under the federal major soupermitting program

• Discuss current methods for conducting C

air analyses

• Compare current methods to possible fut

methods (Dispersion models v. Photochemodels)

• Discuss computational and regulatory ba

implementation
What is PSD?

• The Prevention of Significant Deterio

of Air Quality (PSD) program is the fmajor source permitting program.

– National Ambient Air Quality Standards– Maximum Allowable Increases (“Increm– Air Quality Related Values (AQRV’s) in 

Federally Protected Class I ares
PSD & Class I Analyses

• PSD rules require that a new major source or 

significant modification to an existing major stasource must undergo an analysis to determine source or modification would have an adverse impact(s) on air quality related values (AQRV’

determined critical by the Federal Land Manag

• The Federal Land Manager (Federal official ch

with direct responsibility for management of sulands) has an affirmative responsibility to proteAQRV’s (typically visibility and acid depositionlands and to consider, in consultation with the Administrator, whether a proposed source or modification will have an adverse impact on suvalues.
Federal Class I Areas
How Do We Conduct a Cla

Air Quality Analysis

• Guidance for Class I analyses 

– Interagency Workgroup on Air Quality Modeling Phase 

Recommendations (1998)

– Federal Land Managers’ Air Quality Related Values W

Phase 1 Report (2000/2010)

– 40 CFR Part 51, Appendix W (“Guideline on Air Qualit

• CALPUFF modeling system used as primary modeling pla

visibility and acid deposition analyses required under PSD

• Diagnostic meteorological CALMET used to provide 3D 

meteorological fields to dispersion model

• HNO3/NO3 repartitioning using POSTUTIL• Visibility post-processing using CALPOST
The World According to th

Guideline on Air Quality Mod

• PSD Regulations require adherence 

Guideline on Air Quality Models (“GA

• GAQM requires use of CALPUFF fo

quality assessments for source

-rece

distances > 50-km

• GAQM - 5 years of meteorological d

near-field (e.g. < 50-km) or 3 years oprognostic data for Class I impact an(typically distances > 50-km) 
Lessons Learned from the 

Regional Haze Process

• Over the past several years, numerous technica

have been raised concerning the capability of thCALPUFF/CALMET modeling system to properlestimate Prevention of Significant Deterioration 

increments. 

– Numerous issues with adequacy of CALMET meteoro

fields have been documented by the EPA since 2007.

– Secondary particulate matter (PM; i.e., sulfate and nitr

most important component of air quality related values and CALPUFF uses a simplified chemical transformatalgorithm that was developed over two decades ago. 

– Concern exists about the over prediction of impacts, w

led to proposed changes in visibility post-processing to compensate. 
Issues with CALMET 

Meteorology

Collapsing CBL’s Objective Analysis 
Issues with CALPUFF 

Chemistry
Need for a New Modelin

Paradigm?

• The current modeling paradigm for both Class I increment analy

AQRV analyses remains largely consistent with the original IWA2 recommendations dating to the mid 1990’s. The Phase 2 recommendations are summarized as follows:

– Use of the CALPUFF modeling system– Use of fully developed time and space varying characterization of the meteorology using C– Placement of receptors within Class I areas of concern– Background concentrations of ozone and ammonia are allowed to vary in time and space– The concentration and AQRV impacts are computed to more directly correspond to the sta

increments, and thresholds of concern.

• IWAQM (1992) envisioned a third phase to add more advanced 

techniques representing the likely emergence of photochemical (PGM’s) for routine. However, additional resources were not forand the Phase 3 recommendations were ultimately never pursue

• IWAQM reactivated in 2009 to examine current modeling paradi

determine if Phase 3 goals of use of PGM’s were achievable witregulatory framework. 
Common Concerns Regarding U

PGM’s for Single Source Analy

• PGM’s can only resolve the dynamics and chem

point source plume to the grid resolution specifieuse of a high resolution grid (e.g., 100 m to 1 km

resolve a plume would require extensive model 

and model run times.

• To assess the impacts of a source two runs hav

performed, a base case with the source and a zcase where the emissions of the source are elim

– As PGM runs are already more costly than a source-o

plume model like CALPUFF, the need to do multiple zruns to assess the individual impacts of multiple sourccostly.
Advances in Source 

Apportionment

• PM Source Apportionment Technology (PSAT) t

allows the separate tracking of individual source impacts so that the individual impacts from mandifferent sources can be obtained cost-effectivelrun; ozone can also be tracked for single sourcedumping reactive tracers for ozone.

• Threading of the PSAT PM source apportionme

through the full-chemistry PiG module so that thplume chemistry and plume dynamics can be trathe subgrid-scale PiG module until the plume sizcommensurate with the grid resolution when the can be adequately simulated by the grid model.
• In FY 2008, the USEPA initiated a program to reeva

CALPUFF due to the technical concerns that had colight during the BART process.

• In FY 2009, the USEPA/ENVIRON developed softwa

platform to couple CALPUFF directly to MM5/WRF, 

eliminating need for CALMET.

EPA/FLM Long Range Trans

Modeling Project

• In FY 2010, the USEPA initiated a second program 

UNC/ENVIRON team to demonstrate the use of a PG

source apportionment techniques for estimating the 

and AQRV impacts due to a single source or group o

and compare the results with CALPUFF for existing hypothetical test sources using procedures like those would be used in a far-field analysis for PSD.
Example Visibility Analys

• CALPUFF Version 5.754

– MESOPUFF II Chemistry 

• CALMET Version 5.53a 

– CALMET configured to 

best preserve original prognostic met 

• CAMx Version 4.41

– CENRAP Base0

Inventory

– CENRAP 36-km 

Meteorology

– Probing Tool: Pa

prognostic met 

• Initialized with CENRAP 2002 

36-km MM5

• Prognostic upper air 

(NOOBS=1)

• Prognostic precipitation 

(NPSTA=-1)

– Probing Tool: Pa

Source Apportio(PSAT)

– Plume-in-Grid: G

PiG

– Flexinest: Option

imposed on modto limit initial dispPiG puffs
Modeling Domains

CALPUFF Domain: 243 x 195 x 10 (6-km)

CAMx Domain: 148 x 112 x 19 (36-
CALPUFF Visibility Impac

12141618

Light Extinction (Mm-1)

Predicted CALPUFF Impact at Badlands (2002)

02468

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1

9

17

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49

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Light Extinction (Mm
CAMx Visibility Impacts 

12141618

Light Extinction (Mm-1)

Predicted CAMx Impact for Badlands (2002)

02468

10

1

9

17

25

33

41

49

57

65

73

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105

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Light Extinction (Mm
CALPUFF v. CAMx

5678

Predicted Visibility Impairment in Badlands National 

(2002)

012345

1

10

19

28

37

46

55

64

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82

91

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Visibility [d-dv] 
Computational Comparis

(2007)

• Annual CALPUFF run with no 

spinup

• Each annual run on single 

compute node

– 2 x 2.8 GHz XEON CPUs, 2 GB RAM

• Single source, entire annual 

simulation can be completed in 

• Annual CAMx run with 

spinup per calendar qu

• Each calendar quarter 

separate compute noddays).

– 2 x 2.8 GHz XEON CPU

simulation can be completed in • With 7 source regions less than 6-8 hours sources) and 2 source 

(point and area), averahours per simulation dsimulation days per CP

• 105/8 = 13.125 days fo

quarter to complete.

• Run sequentially, it wo

47.5 days to complete
Barriers to Implementatio

Computational

• The modeling platforms for the permit mo

community are largely Microsoft Windows and are engineered for serial applications models. 

• The meteorological and photochemical m

community is largely Unix/Linux based.

• Time necessary for annual PGM simulati

compared to simplified CALPUFF chemis
Computational Considerat

• Adaptation of the PGM platforms to operate in a 

Windows based environment?

– The permit modeling community typically does not hav

same level of fluency in either the Unix/Linux operating or Fortran based programming skills that are essentiarequisites

– IT authorities within State and Local permitting agenci

lack the familiarity and/or resources to dedicate to sysadministration and security for Unix/Linux based systethus actively prevent the acquisition of such equipmensuch hardware is acquired, prevent the presence of sequipment on the State’s internal network. 
Barriers to Implementatio

Regulatory

• The operational construct for the permit mode

community is highly rigid

– Based upon a series of regulations and guideline

restrict operational flexibility in order to promote mgeneral consistency in the application of models. 

• The operational construct of the meteorologica

photochemical modeling communities is vastly different, 

– Based upon a more loosely binding set of EPA 

recommendations which typically encourage adascience and modeling techniques to produce the scientifically feasible answer given the constraintstate-of-the-science.
Regulatory Consideration

• The differences in the operational paradigms betwee

communities will require both the EPA and the FLM’develop a more rigid set of operational procedures sthe current permit modeling paradigm in order to insscientifically sound and consistent set of procedures 

prevent an ‘anything goes’ process as would likely dwithout such procedures.

• Length of meteorological record for PGM’s will likely 

be expanded to be consistent with requirements of G(e.g. 3 years of prognostic data).

• Development of significance thresholds for single so

(cause or contribute test) required for NAAQS demonstrations.
Conclusion

• PGM’s capable of assessing single source impa

both AQRV and ozone requirements under PSD

• Source apportionment eliminates need for multip

out” runs

• Significant barriers remain to implementation of 

– Increased computational requirements– Increased training requirements for permit mo

staff 

– Creation of a hybrid regulatory and guidance 

framework for implementation of PGM’s withiregulatory permit modeling paradigm which is rigid and prescriptive