EPA’S NINTH CONFERENCE ONAIR QUALITY MODELINGComments on behalf of theAmerican Petroleum InstituteSteven R. Hanna, Ph.D., CCMHanna ConsultantsBruce A. Egan, Sc.D., CCMEgan Environmental Inc.Elizabeth M. Hendrick, CCMEpsilon Associates Inc.October 10, 20081Introduction2Promulgation of more stringent ambient air standardshas resulted in more non-attainment areas and theneed for more complex and more regional modeling.These comments cover many issues relating to aspectsof the EPA’s Guideline on Air Quality Models.Highlights are listed here and our written commentswill contain details and references.Need for Complete Documentation andGuidance3All codes should be in public domain.All documentation (especially CALPUFF) needs to bebrought up-to-date and made publicly available.There is a general need for more EPA guidance,workshops and training for the modeling community.Distance limits on model applications4Better guidance on distance limits for models isneeded (esp. AERMOD and CALPUFF).What is the minimum domain size and grid size wheregrid models such as CMAQ or CAMx can be used,and what is the recommendation for Plume in Grid(PinG) modeling?Distance limits should not be arbitrary, but shoulddepend upon scientific issues, including topography,wind persistence data and land use variations.Meteorological inputs to models5There has been an increase in the use of meteorological drivers(e.g., diagnostic models such as CALMET and prognostic fullphysics models such as MM5) for both steady state and timevarying dispersion models (e.g., AERMOD, CALPUFF, CMAQ).Prognostic meteorological models such as MM5 and WRF(often called ‘Met models’) have been improving with advancesin science and resolution.Other agencies (DTRA and NOAA) now have linked Metmodel(MM5 or WRF) to Puff AQ models or grid AQ model systemsthat are operational.Meteorological inputs to models (continued)6Research effort needed to optimize use of Met modeland CALMET model predictions with observations.Specific issues:Clarify differences between full-physics Met model(e.g.,MM5) and CALMETAssess effects of grid size and vertical grid spacing on biasand accuracyDevelop recommendations for optimal grid sizes fordifferent topographic and meteorological settings;minimumgrid size (Penn State MM5 developers recommend 4 kmassafe general rule, although 1 km can be used in specialcases; this is due to physics assumptions in model)Meteorological inputs to models (Specificissues continued)7Determine overall model performance of Met modelscoupled with dispersion models vs. field study datasets;possible new field experimentsDetermine how met observations can best be used andassimilated in Met models? (note differences between NCARand Penn State MM5 Met model data assimilation methods)Assess if CALMET (or any diagnostic model) is trulyneededas an intermediate step between the Met model and theAQM.Work with other agencies (DTRA, NOAA) who haveoperational Met model-AQM systems operating and makeuse of their technology where appropriate.Regional Models(CMAQ, CAMx, and others)8New mechanisms in CMAQ (and CAMx and other models) need to becomprehensively tested and subjected to review by external expert panels.We recommend that EPA devote more resources to subgrid scale modelingin CMAQ, including consideration of the use of the SCICHEM PinG model,and set up a decision process for which point sources should be modeledwith PinG.EPA should have comprehensive scientifically basedmodelevaluations/comparisons performed for CMAQ vs. CAMx (and any othercredible regional grid model).Databases are being developed in Wyoming and the Four Corners regionthat will provide monitoring data and emission inventories.EPA needs to set a de minimis significance level for project ozoneconcentration impacts for regional modeling efforts.CALMET/CALPUFF9Need overall model evaluations of CALPUFF using fullchemistry as very limited evaluations of the modelinthe mode that it is being used have been conducted.Evaluation should include other models such asSCIPUFF.Ability to handle complex terrain, short term puffdispersion, chemical reactions, and other incorporatedcapabilities (e.g., FOG) needs to be evaluated.Modify chemistry based on API/AER recommendedrevisions.CALMET/CALPUFF (Continued)Documentation is incomplete, and lack of detailcauses many users to rely heavily on default values.Need to resolve met input questions (CALMET or Metmodel such as MM5 – see previous slides on Metinputs)Need to test the use of CALPUFF for regional AQRVanalyses (NEPA studies are currently using thisapproach in the West).Operational use should be based on peer and stakeholder review using best science approach asopposed to IWAQM mandates.Proposed Collaborative Field Experiment for LinkedMet Model - AQM Evaluation11Purpose: to test and improve the linkage of Metmodels and air quality models in mountainous terrain,such as Wyoming where there is much currentmesoscale and regional modeling underway.EPA should lead effort with invited participation ofAPI and other industries and stakeholders.Include meteorological observations, tracer releases,and PM and visibility observations over an area ofabout 200 km by 200 km, sufficient to test the useofMet model (e.g., MM5) direct input vs CALMETdiagnostic model.Model Evaluation and Uncertainty12Recent improvements in regional dispersion modelperformance measures have been made; EPA efforts(in collaboration with members of an internationalworkgroup) are described in a recently submittedpaper by Dennis et al.Rather than having different evaluation approachesand performance measures for the different modelscales, a comprehensive set of performance measuresshould be devised for use at all model scales.Model Evaluation and Uncertainty (Cont)13The bootstrap method used in the ASTM and BOOTsoftware should be recommended to evaluatesignificant differences in model performance resultsfor all model scales.Model acceptance criteria should be set and used inmodeling protocols and decision making.Uncertainty in model predictions (also called“probabilistic forecasts”) should become availabletoand used by regulatory decision makers. EPA shouldinvestigate and possibly make use of the probabilisticAQM system (Met model –SCIPUFF) in use at DTRA.Modeling Protocols and Screening Models14Modeling Protocols should be determined up frontand dependent upon science and regulatory needs.When will the screening model AERSCREEN bereleased to the public?AERMOD15Establish a peer–review panel from all segments ofthe community to review planned improvements anddraft documents produced.Incorporate algorithms for near calm winds and testwith appropriate field data sets.Improve algorithms for use in urban areas, especiallyfor near-ground sources in built-up downtown areas.Determine science-based criteria for deciding distancelimits and whether “complex terrain” is significant.ASOS and AERSURFACE16EPA guidance limits the influence of nearby land usein parameterizing surface roughness to a 1 kmradius of ASOS anemometers generally located onairport property.For many pollutant sources this means that thedispersion modeling domain is dominated by surfaceroughness of airport property.Better guidance is needed for translating the airportwind observations to the land characteristics of thepollutant source domain.Meteorological data processing with AERMET forinput to AERMOD17AERMET Stage 3 output should summarize theprocessed met data so the user knows during theAERMET processing steps if that year of data issuitable for regulatory modeling purposes (>90%available).Currently this summary information is not provideduntil AERMOD is run.Plume Molar Volume Ratio Model (PMVRM)18EPA should further test this model and, if acceptable,recommend the use of this model for predicting NO2concentrations in the presence of ambient air ozoneconcentrations.This should be performed for both AERMOD andCALPUFF.Encourage development and use of sciencebased models19Some non-regulatory driven studies concerned, for example,with health risk assessments use AQ monitoring datacombinedwith statistical correlations as a substitute for the use ofdetailed dispersion models (AERMOD, CALPUFF, or CMAQ) forestimating air quality concentrations.EPA should promote consistent and general use of dispersionmodels that are based on physical understanding ofmeteorological principles (e.g., AERMOD, CALPUFF, CMAQ,CAMx etc.) as opposed to statistical fits to site specificconcentration data sets.The use of statistical models in place of more rigorousdispersion models should be reviewed by an expert panel thatincludes all scientific and stakeholder communities.Encourage development and use of sciencebased models (continued)20Avoid arbitrary non-scientific criteria for modelselection (such as eliminating models with a biasforover-prediction)Encourage scientific peer review of all models (i.e.,both internal EPA and outside models) and ofproposed modifications to model algorithms.Model acceptance criteria should be developedthrough discussions with the entire community of modeldevelopers and stakeholders.Summary of Key Recommendations21Need to update and improve model guidance anddocumentation.Encourage development and use of science–based modelsthrough model evaluation efforts and enhanced publicinvolvement.Test, validate, and recommend procedures for usingmeteorological models to drive dispersion models.Conduct a Mesoscale/Regional collaborative model evaluationusing the existing databases and/or conduct a fieldexperimentthat could be used to evaluate regional models in rural regionsin the intermountain west or similar location.