Proof-of-Concept Evaluation of Use ofPhotochemical Grid Model SourceApportionment Techniques for Preventionof Significant Deterioration of Air QualityAnalysis RequirementsBret Anderson, Kirk Baker, RalphMorris, Chris Emery, AndyHawkins, Erik SnyderAcknowledgements toContributors• Kirk Baker, USEPA OAQPS• Ralph Morris and Chris Emery, ENVIRON• Andy Hawkins, State of Kansas•Erik Snyder, USEPA Region 6Outline• Introduction to the air quality analysisrequirements under the federal major sourcepermitting program• Discuss current methods for conducting Class Iair analyses• Compare current methods to possible futuremethods (Dispersion models v. Photochemicalmodels)• Discuss computational and regulatory barriers toimplementationWhat is PSD?• The Prevention of Significant Deteriorationof Air Quality (PSD) program is the federalmajor source permitting program.–National Ambient Air Quality Standards– Maximum Allowable Increases (“Increments”)– Air Quality Related Values (AQRV’s) inFederally Protected Class I aresPSD & Class I Analyses• PSD rules require that a new major source orsignificant modification to an existing major stationarysource must undergo an analysis to determine if thesource or modification would have an adverseimpact(s) on air quality related values (AQRV’s)determined critical by the Federal Land Managers.• The Federal Land Manager (Federal official chargedwith direct responsibility for management of suchlands) has an affirmative responsibility to protect theAQRV’s (typically visibility and acid deposition) of suchlands and to consider, in consultation with the EPAAdministrator, whether a proposed source ormodification will have an adverse impact on suchvalues.Federal Class I AreasHow Do We Conduct a Class IAir Quality Analysis• Guidance for Class I analyses– Interagency Workgroup on Air Quality Modeling Phase 2Recommendations (1998)– Federal Land Managers’ Air Quality Related ValuesWorkgroupPhase 1 Report (2000/2010)–40 CFR Part 51, Appendix W (“Guideline on Air Quality Models”)• CALPUFF modeling system used as primary modeling platform forvisibility and acid deposition analyses required under PSD• Diagnostic meteorological CALMET used to provide 3Dmeteorological fields to dispersion model• HNO3/NO3 repartitioning using POSTUTIL• Visibility post-processing using CALPOSTThe World According to theGuideline on Air Quality Models• PSD Regulations require adherence to theGuideline on Air Quality Models(“GAQM”)• GAQM requires use of CALPUFF for airquality assessments for source-receptordistances > 50-km• GAQM - 5 years of meteorological data fornear-field (e.g. < 50-km) or 3 years ofprognostic data for Class I impact analysis(typically distances > 50-km)Lessons Learned from theRegional Haze Process• Over the past several years, numerous technical issueshave been raised concerning the capability of theCALPUFF/CALMET modeling system to properlyestimate Prevention of Significant Deterioration (PSD)increments.– Numerous issues with adequacy of CALMET meteorologicalfields have been documented by the EPA since 2007.– Secondary particulate matter (PM; i.e., sulfate and nitrate) is themost important component of air quality related values (AQRVs),and CALPUFF uses a simplified chemical transformationalgorithm that was developed over two decades ago.– Concern exists about the over prediction of impacts, which hasled to proposed changes in visibility post-processing tocompensate.Issues with CALMETMeteorologyCollapsing CBL’sObjective Analysis ErrorsIssues with CALPUFFChemistryNeed for a New ModelingParadigm?• The current modeling paradigm for both Class I increment analyses andAQRV analyses remains largely consistent with the original IWAQM Phase2 recommendations dating to the mid 1990’s. The Phase2recommendations are summarized as follows:– Use of the CALPUFF modeling system– Use of fully developed time and space varying characterization of the meteorology using CALMET– 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 moredirectly correspond to the standards,increments, and thresholds of concern.• IWAQM (1992) envisioned a third phase to add more advanced modelingtechniques representing the likely emergence of photochemical grid models(PGM’s) for routine. However, additional resources werenot forthcomingand the Phase 3 recommendations were ultimately never pursued.• IWAQM reactivated in 2009 to examine current modelingparadigm anddetermine if Phase 3 goals of use of PGM’s were achievable within the PSDregulatory framework.Common Concerns Regarding Use ofPGM’s for Single Source Analyses• PGM’s can only resolve the dynamics and chemistry of apoint source plume to the grid resolution specified anduse of a high resolution grid (e.g., 100 m to 1 km) toresolve a plume would require extensive model inputsand model run times.• To assess the impacts of a source two runs have to beperformed, a base case with the source and a zerooutcase where the emissions of the source are eliminated.– As PGM runs are already more costly than a source-orientedplume model like CALPUFF, the need to do multiple zero-outruns to assess the individual impacts of multiple sources is quitecostly.Advances in SourceApportionment• PM Source Apportionment Technology (PSAT) thatallows the separate tracking of individual source PMimpacts so that the individual impacts from manydifferent sources can be obtained cost-effectively in onerun; ozone can also be tracked for single sources bydumping reactive tracers for ozone.• Threading of the PSAT PM source apportionmentthrough the full-chemistry PiG module so that the earlyplume chemistry and plume dynamics can be tracked bythe subgrid-scale PiG module until the plume size iscommensurate with the grid resolution when the plumecan be adequately simulated by the grid model.• In FY 2008, the USEPA initiated a program to reevaluateCALPUFF due to the technical concerns that had come tolight during the BART process.• In FY 2009, the USEPA/ENVIRON developed softwareplatform to couple CALPUFF directly to MM5/WRF,eliminating need for CALMET.EPA/FLM Long Range TransportModeling Project• In FY 2010, the USEPA initiated a second programwith theUNC/ENVIRON team to demonstrate the use of a PGM withsource apportionment techniques for estimating theozoneand AQRV impacts due to a single source or group ofsourcesand compare the results with CALPUFF for existing andhypothetical test sources using procedures like those thatwould be used in a far-field analysis for PSD.Example Visibility Analysis• CALPUFF Version 5.754– MESOPUFF II Chemistry• CALMET Version 5.53a– CALMET configured tobest preserve originalprognostic met• CAMx Version 4.41– CENRAP Base02fInventory– CENRAP 36-km MM5Meteorology–Probing Tool: Particulateprognostic met• Initialized with CENRAP 200236-km MM5• Prognostic upper air(NOOBS=1)• Prognostic precipitation(NPSTA=-1)–Probing Tool: ParticulateSource Apportionment(PSAT)– Plume-in-Grid: GREASDPiG– Flexinest: Optional 12 kmimposed on modeling gridto limit initial dispersion ofPiG puffsModeling DomainsCALPUFF Domain:243 x 195 x 10 (6-km)CAMx Domain:148 x 112 x 19 (36-km)CALPUFF Visibility Impacts12141618

Light Extinction (Mm -1)Predicted CALPUFF Impact at Badlands (2002)0246810 1 9 17 25 33 41 49 57 65 73 81 89 97 105 113 121 129 137 145 153 161 169 177 185 193 201 209 217 225 233 241 249 257 265 273 281 289 297 305 313 321 329 337 345 353 361

Light Extinction (MmbFMbCMbECbOCbNO3bSO4CAMx Visibility Impacts12141618

Light Extinction (Mm -1)Predicted CAMx Impact for Badlands (2002)0246810 1 9 17 25 33 41 49 57 65 73 81 89 97 105 113 121 129 137 145 153 161 169 177 185 193 201 209 217 225 233 241 249 257 265 273 281 289 297 305 313 321 329 337 345 353 361

Light Extinction (MmbFMbCMbECbOCbNO3bSO4CALPUFF v. CAMx5678Predicted Visibility Impairment in Badlands National Park(2002)012345 1 10 19 28 37 46 55 64 73 82 91 100 109 118 127 136 145 154 163 172 181 190 199 208 217 226 235 244 253 262 271 280 289 298 307 316 325 334 343 352 361

Visibility [d-dv]CALPUFFCAMxComputational Comparison(2007)• Annual CALPUFF run with nospinup• Each annual run on singlecompute node– 2 x 2.8 GHz XEON CPUs, 2 GB RAM• Single source, entire annualsimulation can be completed in• Annual CAMx run with 15 days ofspinup per calendar quarter.• Each calendar quarter run on aseparate compute node (105days).– 2 x 2.8 GHz XEON CPUs, 2 GB RAM•With 7 source regions (singlesimulation can be completed inless than 6-8 hourssources) and 2 source groups(point and area), average of 3hours per simulation day or 8simulation days per CPU day.• 105/8 = 13.125 days for calendarquarter to complete.• Run sequentially, it would require47.5 days to complete.Barriers to Implementation -Computational• The modeling platforms for the permit modelingcommunity are largely Microsoft Windows basedand are engineered for serial applications ofmodels.• The meteorological and photochemical modelingcommunity is largely Unix/Linux based.• Time necessary for annual PGM simulationscompared to simplified CALPUFF chemistry.Computational Considerations• Adaptation of the PGM platforms to operate in aWindows based environment?– The permit modeling community typically does not have thesame level of fluency in either the Unix/Linux operating systemor Fortran based programming skills that are essential skillrequisites– IT authorities within State and Local permitting agencies oftenlack the familiarity and/or resources to dedicate to systemsadministration and security for Unix/Linux based systems, andthus actively prevent the acquisition of such equipment or, ifsuch hardware is acquired, prevent the presence ofsuchequipment on the State’s internal network.Barriers to Implementation -Regulatory• The operational construct for the permit modelingcommunity is highly rigid– Based upon a series of regulations and guidelineswhichrestrict operational flexibility in order to promote moregeneral consistency in the application of models.• The operational construct of the meteorological andphotochemical modeling communities is vastlydifferent,– Based upon a more loosely binding set of EPArecommendations which typically encourage adaptingbothscience and modeling techniques to produce the mostscientifically feasible answer given the constraints of thestate-of-the-science.Regulatory Considerations• The differences in the operational paradigms between the twocommunities will require both the EPA and the FLM’stodevelop a more rigid set of operational proceduressimilar tothe current permit modeling paradigm in order to insure both ascientifically sound and consistent set of procedures toprevent an ‘anything goes’ process as would likelydevelopwithout such procedures.• Length of meteorological record for PGM’s will likely have tobe expanded to be consistent with requirements of GAQM(e.g. 3 years of prognostic data).• Development of significance thresholds for singlesource(cause or contribute test) required for NAAQSdemonstrations.Conclusion• PGM’s capable of assessing single source impacts forboth AQRV and ozone requirements under PSD.• Source apportionment eliminates need for multiple “zeroout” runs•Significant barriers remain to implementation of PGM’s– Increased computational requirements– Increased training requirements for permit modelingstaff– Creation of a hybrid regulatory and guidanceframework for implementation of PGM’s within aregulatory permit modeling paradigm which is highlyrigid and prescriptive