Source: Javier Fochesatto Regulatory Context for Modeling Robert Elleman EPA Region 10

What It Is and What It Isn’t Not Guidance –Nothing beyond Clean Air Act, EPA Rulemaking, and existing Guidance For Fairbanks, interpretation is based on our collaborative work over several years –Regional Office interpretation for this NAA only, not Agency position None of this presentation will be a surprise to this group

Why Model? A model is a representation of what we know It is our petri dish for testing our knowledge of a situation and for playing with future scenarios –This makes for more informed decisions And, it demonstrates a future emission reduction will attain the NAAQS

The Regulatory Pyramid Clean Air Act EPA Rulemaking Guidance, Common Practice, consultation with Regional Office

Origins of Modeling in the Clean Air Act Stays pretty vague: 1.State Implementation Plan must provide air quality modeling performance to predict future pollution levels, as EPA Administrator prescribes –110(a)(2)(k)(i) 2.Nonattainment plans shall provide for attainment of the standard –172(c)

PM2.5 Implementation Rule (EPA Rulemaking) Adopted in 2007 for 1997 standard –Briefly describes modeling guidance –Other rules required modeling for past standards 40 CFR : 1.State must submit attainment demonstration 2.Must include inventory data, modeling results, and emission reduction analyses 3.Demonstration will meet requirements of and Appendix W 4.Attainment demonstration should be consistent with modeling guidance

40 CFR (EPA Rulemaking) Adopted in 1986 and revised three times in 1990s 1.Adequacy of control strategy shall be demonstrated by means of air quality models, data bases, and other requirements as specified in Appendix W 2.Describes generally what to include in the attainment demonstration

Appendix W (EPA Rulemaking) Appendix W to Part 51 describes air quality modeling rules Been around for decades, has been updated for PM2.5 1.No preferred model for PM2.5 (Section ) –Areas with secondary PM2.5 issues are encouraged to use CMAQ, etc. –Primary components can be simulated using less resource- intensive techniques 2.For point sources (large permitted sources), CALPUFF can be used for multi-day stagnant conditions (section 7.2.8) –Normally, near-field modeling would be done with AERMOD

Model to Use All models for PM2.5 SIPs are alternative models (except AERMOD/CALPUFF for points sources) Alternative models conform to Appendix W Section 3.2.2(e) requirements: 1.The model has received a scientific peer review 2.The model can be demonstrated to be applicable to the problem on a theoretical basis 3.Adequate inputs 4.Not biased towards underestimates 5.A modeling protocol exists

Types of Models Regional Grid Models e.g., CMAQ Good for heterogeneous sources and chemistry Downside: resource-intensive Dispersion Models e.g., CALPUFF Good for single source Downsides: only one source at a time, difficult to analyze Box models e.g., PCA and rollback Relatively easy to implement Downsides: no chemistry, no spatial information

How We Will Use Them Use all types for their strengths to build an effective attainment strategy Probably highlight CMAQ for final demonstration with others as weight of evidence Will continue to be collaborative process with DEC and FNSB More sophisticated but less “playful” More “playful” but but less sophisticated Rollback PCA CALPUFF CMAQ

Emission Inventory Requirements Clean Air Act 172(c)(3) specifies one for non-attainment SIP –“a comprehensive, accurate, current inventory of actual emissions from all sources of the relevant pollutant or pollutants in such area” PM2.5 Implementation Rule 40 CFR –Submit inventory to EPA 3 years after designation –Direct PM2.5 and all precursors –Any additional inventory information Condensables –Consolidated Emission Reporting Rule (2002) defines primary PM2.5 as combination of filterable PM2.5 and condensable PM2.5 –PM2.5 Implementation Rule ( ) requires emission limits for RACT/RACM to account for condensables after January 1, 2011

PM2.5 Modeling Guidance Model used in a relative sense and then applied to observed data –Speciated Model Attainment Test (SMAT) Requires supplemental analyses –Supplemental analyses become weight of evidence when projected DV close to NAAQS Requires an unmonitored area analysis (Future) = (Current) * (Controls) Relative Response Factor (RRF): A ratio of future to current emissions from model Current monitor PM2.5

Base Year Design Value Procedure changed slightly since June meeting –Tyler Fox memo, “Update to the 24 Hour PM2.5 NAAQS Modeled Attainment Test”, Appendix B –Glitch in previous methodology did not affect Fairbanks

Future DV (All Data) Baseline DV (All Data) Old Way of Applying SMAT Apply RRF to Q1 and Q4 Not species specific for this analysis An RRF of 0.3 or less give Future DV of 35.5 Shown for RRF= RRF crit

1.Rank top PM2.5 for each year 2.Split into species concentrations –Split according to SMAT by quarter 3.Apply species-specific, quarter-specific RRF 4.Add species back up to total PM2.5 5.Rerank PM2.5 and find new 98th percentile New Way of Applying SMAT SO 4 2- NO3 - NH 4 + H2OH2OECOPPblankOCTotal PM 2.5 Baseline DV Example RRF Future DV

Source: Fairbanks North Star Borough The Gist Regulatory framework for modeling is a combination of Clean Air Act, EPA Regulations, EPA Guidance, and common practice Combine modeling techniques to build consistent case for attainment –Each model has unique strengths –No single model provides all capabilities and information Models are used in a relative sense for control scenarios, not absolute numbers No bright line at 35  g/m 3 –Weight of Evidence

The End Source: Fairbanks North Star Borough

Actuals vs. Allowables Appendix W, Table 8.1 requires “Maximum allowable emission limit or federally enforceable permit limit” for modeling point sources Modeling guidance recommends actual emissions for most cases Need actual emissions if modeling chemistry