Wednesday, November 9, 2005

Part III

Environmental Protection Agency 40 CFR Part 51 Revision to the Guideline on Air Quality Models: Adoption of a Preferred General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions; Final Rule

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ENVIRONMENTAL PROTECTION telephone (919) 541–5562. SCRAM) at: www.epa.gov/scram001. AGENCY ([email protected]). You may find codes and documentation SUPPLEMENTARY INFORMATION: for models referenced in today’s action 40 CFR Part 51 on the SCRAM Web site. We have also Outline uploaded various support documents [AH–FRL–7990–9] I. General Information (e.g., evaluation reports). II. Background RIN 2060–AK60 III. Public Hearing on the April 2000 II. Background proposal The Guideline is used by EPA, States, Revision to the Guideline on Air IV. Discussion of Public Comments and Quality Models: Adoption of a and industry to prepare and review new Issues from our April 21, 2000 Proposal source permits and State Preferred General Purpose (Flat and A. AERMOD and PRIME Complex Terrain) Dispersion Model B. Appropriate for Proposed Use Implementation Plan revisions. The and Other Revisions C. Implementation Issues/Additional Guideline is intended to ensure Guidance consistent air quality analyses for AGENCY: Environmental Protection D. AERMOD revision and reanalyses in activities regulated at 40 CFR 51.112, Agency (EPA). 2003 51.117, 51.150, 51.160, 51.166, and ACTION: Final rule. 1. Performance analysis for AERMOD 52.21. We originally published the (02222) Guideline in April 1978 and it was SUMMARY: EPA’s Guideline on Air a. Non-downwash cases: AERMOD (99351) incorporated by reference in the Quality Models (‘‘Guideline’’) addresses vs. AERMOD (02222) b. Downwash cases regulations for the Prevention of the regulatory application of air quality 2. Analysis of regulatory design Significant Deterioration (PSD) of Air models for assessing criteria pollutants concentrations for AERMOD (02222) Quality in June 1978. We revised the under the Clean Air Act. In today’s a. Non-downwash cases Guideline in 1986, and updated it with action we promulgate several additions b. Downwash cases supplement A in 1987, supplement B in and changes to the Guideline. We c. Complex terrain July 1993, and supplement C in August recommend a new dispersion model— E. Emission and Dispersion Modeling 1995. We published the Guideline as AERMOD—for adoption in appendix A System (EDMS) appendix W to 40 CFR part 51 when we of the Guideline. AERMOD replaces the V. Discussion of Public Comments and Issues issued supplement B. We republished from our September 8, 2003 Notice of Industrial Source Complex (ISC3) Data Availability the Guideline in August 1996 (61 FR model, applies to complex terrain, and VI. Final action 41838) to adopt the CFR system for incorporates a new downwash VII. Final editorial changes to appendix W labeling paragraphs. On April 21, 2000 algorithm—PRIME. We remove an VIII. Statutory and Executive Order Reviews we issued a Notice of Proposed existing model—the Emissions Rulemaking (NPR) in the Federal I. General Information Dispersion Modeling System (EDMS)— Register (65 FR 21506), which was the from appendix A. We also make various A. How Can I Get Copies of Related original proposal for today’s editorial changes to update and Information? promulgation. reorganize information. EPA established an official public III. Public Hearing on the April 2000 DATES: This rule is effective December 9, docket for this action under Docket No. Proposal 2005. As proposed, beginning November A–99–05. The official public docket is We held the 7th Conference on Air 9, 2006, the new model—AERMOD— the collection of materials that is Quality Modeling (7th conference) in should be used for appropriate available for public viewing at the Air Washington, DC on June 28–29, 2000. application as replacement for ISC3. Docket in the EPA Docket Center, (EPA/ As required by Section 320 of the Clean During the one-year period following DC) EPA West (MC 6102T), 1301 Air Act, these conferences take place this promulgation, protocols for Constitution Ave., NW., Washington, approximately every three years to modeling analyses based on ISC3 which DC 20004. The EPA Docket Center standardize modeling procedures, with are submitted in a timely manner may Public Reading Room (B102) is open special attention given to appropriate be approved at the discretion of the from 8:30 a.m. to 4:30 p.m., Monday modeling practices for carrying out appropriate Reviewing Authority. through Friday, excluding legal programs PSD (42 U.S.C. 7620). This Applicants are therefore encouraged to holidays. The telephone number for the conference served as the forum for consult with the Reviewing Authority as Reading Room is (202) 566–1744, and receiving public comments on the soon as possible to assure acceptance the telephone number for the Air Docket Guideline revisions proposed in April during this period. is (202) 566–1742. An electronic image 2000. The 7th conference featured ADDRESSES: All documents relevant to of this docket may be accessed via presentations in several key modeling this rule have been placed in Docket No. Internet at www.epa.gov/eDocket, where areas that support the revisions A–99–05 at the following address: Air Docket No. A–99–05 is indexed as promulgated today. A presentation by Docket in the EPA Docket Center, (EPA/ OAR–2003–0201. Materials related to the American Meteorological Society DC) EPA West (MC 6102T), 1301 our Notice of Data Availability (AMS)/EPA Regulatory Model Constitution Ave., NW., Washington, (published September 8, 2003) and Improvement Committee (AERMIC) DC 20004. This docket is available for public comments received pursuant to covered the enhanced Gaussian public inspection and copying between the notice were placed in eDocket OAR– dispersion model with boundary layer 1 8 a.m. and 5:30 p.m., Monday through 2003–0201. parameterization: AERMOD.2 Also at Friday, at the address above. Our Air Quality Modeling Group the 7th conference, the Electric Power FOR FURTHER INFORMATION CONTACT: maintain an Internet website (Support Research Institute (EPRI) presented Tyler J. Fox, Air Quality Modeling Center for Regulatory Air Models— evaluation results from the recent Group (MD–D243–01), Office of Air research efforts to better define and 1 http://cascade.epa.gov/RightSite/ Quality Planning and Standards, U.S. dk_public_collection_detail.htm? characterize dispersion around Environmental Protection Agency, ObjectType=dk_docket_collection&cid=OAR-2003- Research Triangle Park, NC 27711; 0201&ShowList=items&Action=view. 2 AMS/EPA Regulatory MODel.

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buildings (downwash effects). These to public concerns, we believed that the considered and discussed all significant efforts were part of a program called the revised AERMOD merited another comments. Whenever the comments Plume RIse Model Enhancements public examination of performance revealed any new information or (PRIME). At the time, PRIME was results. Also, since the April 2000 NPR, suggested any alternative solutions, we integrated within ISC3ST (ISC–PRIME) the Federal Aviation Administration considered this prior to taking final and the results presented were within (FAA) decided to configure EDMS 3.1 to action. the ISC3 context. As discussed in incorporate the AERMOD dispersion The remainder of this preamble today’s rule, the PRIME algorithm has model. FAA presented this strategy at section discusses the primary issues now been fully integrated into the 7th conference and performance encountered by the Agency during the AERMOD. evaluations at two airports were to be public comment period associated with We proposed an update to the available before final promulgation. the April 2000 proposal. This overview Emissions and Dispersion Modeling This was in response to public concern also serves in part to explain the System (EDMS 3.1), which is used for over lack of EDMS evaluation. changes to the Guideline in today’s assessing air quality impacts from On April 15, 2003 we published a action, and the main technical and airports. A representative of the Federal Notice of Final Rulemaking (NFR; 68 FR policy concerns addressed by the Aviation Administration (FAA) 18440) that adopted CALPUFF in Agency. presented a further upgrade to EDMS appendix A of the Guideline. We also A. AERMOD and PRIME 4.0 that would include AERMOD and made various editorial changes to forthcoming performance evaluations update and reorganize information, and AERMOD is a best state-of-the- for two airports. removed obsolete models. We practice Gaussian plume dispersion The presentations were followed by a announced that action on AERMOD and model whose formulation is based on critical review/discussion of AERMOD the Emissions and Dispersion Model planetary boundary layer principles. and available performance evaluations, (EDMS) for assessing airport impacts AERMOD provides better facilitated jointly by the Air & Waste was being deferred, and would be characterization of plume dispersion Management Association’s AB–3 reconsidered in a separate action when than does ISC3. At the 7th conference, Committee and the American new information became available for AERMIC members presented Meteorological Society’s Committee of these models. developmental and evaluation results of Meteorological Aspects of Air Pollution. This deferred action took the form of AERMOD. Comprehensive comments For the new models and modeling a Notice of Data Availability (NDA), were submitted on the AERMOD code techniques proposed in April 2000, we which was published on September 8, and formulation document and on the asked the public to address the 2003 (68 FR 52934). In this notice, we AERMET draft User’s Guide (AERMET following questions: made clear that the purpose of the NDA is the meteorological preprocessor for • Has the scientific merit of the was to furnish pertinent technical AERMOD). models presented been established? details related to model changes since As identified in the April 2000 • Are the models’ accuracy the April 2000 NPR. New performance Federal Register proposal, applications for which AERMOD was suited include sufficiently documented? data and evaluation of design • assessment of plume impacts from Are the proposed regulatory uses of concentration using the revised stationary sources in simple, individual models for specific AERMOD are contained in reports cited intermediate, and complex terrain, for applications appropriate and later in this preamble (see section V). In other than downwash and deposition reasonable? our April 2003 NFR, we stated that • applications. We invited comments on Do significant implementation results of EDMS 4.0 performance (with whether technical concerns had been issues remain or is additional guidance AERMOD) had recently become reasonably addressed and whether needed? available. In the NDA we clarified that • AERMOD is appropriate for its intended Are there serious resource these results would not be provided constraints imposed by modeling applications. Since AERMOD lacks a because of FAA’s decision to withdraw general (all-terrain) screening tool, we systems presented? EDMS from the Guideline’s appendix A, • What additional analyses or invited comment on the practicality of and we affirmed our support for this information are needed? using SCREEN3 as an interim tool for removal. We solicited public comments We placed a transcript of the 7th AERMOD. We also sought comments on on the new data and information related conference proceedings and a copy of minor changes to the list of acceptable to AERMOD. all written comments, many of which screening techniques for complex address the above questions, in Docket IV. Discussion of Public Comments and terrain. No. A–99–05. The comments on Issues From Our April 21, 2000 PRIME was designed to incorporate AERMOD were reviewed and nearly Proposal the latest scientific algorithms for evaluating building downwash. At the every commenter urged us to integrate All comments submitted to Docket time of the proposal, the PRIME aerodynamic downwash into AERMOD No. A–99–05 are filed in Category IV– algorithm for simulating aerodynamic (i.e., not to require two models for some D.3 We summarized these comments, downwash was not incorporated into analyses). The only comments calling developed detailed responses, and AERMOD. For testing purposes, PRIME for further actions were associated with documented conclusions on appropriate was implemented within ISC3ST (short- the need for documentation, evaluation actions in a Response-to-Comments term average version of the Industrial and review of the suggested downwash document.4 In this document, we enhancement to AERMOD. Source Complex), which AERMOD was proposed to replace. This special model, As a result of American 3 Additional comments received since we Meteorological Society (AMS)/EPA published the final rule on April 15, 2003 called ISC–PRIME, was proposed for Regulatory Model Improvement (discussed in the previous section) are filed in Committee’s (AERMIC) efforts to revise category IV–E. This category includes comments Quality Modeling; Washington, DC, June 28–29, received pursuant to the Notice of Data Availability 2000 AND Notice of Data Availability—September AERMOD, incorporating the PRIME we published in September 2003. 8, 2003 (Air Docket A–99–05, Item V–C–2). This algorithm and making certain other 4 Summary of Public Comments and EPA document may also be examined from EPA’s incidental modifications and to respond Responses: AERMOD; 7th Conference on Air SCRAM Web site at www.epa.gov/scram001.

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aerodynamic downwash and dry and the reasoning and references for the simultaneous use of two models (ISC– deposition. We sought comment on the model assumptions.9 PRIME and AERMOD) for those sources technical viability of AERMOD and Although some comments asked for with potential downwash concerns. ISC–PRIME for its intended more detailed documentation and Commenters urged the Agency to applications. review, there were no comments which eliminate the need to use two models questioned the technical credibility of Scientific merit and accuracy. for evaluating the same source. In the PRIME model. In fact, almost every Regarding the scientific merits of response to this request, AERMIC commenter asked for PRIME to be developed a version of AERMOD that AERMOD, substantial support was incorporated into AERMOD. As incorporates PRIME: AERMOD (02222) expressed in public comments that summarized above, we believe that the and initiated an analysis to insure that AERMOD represents sound and scientific merit of PRIME has been concentration estimates by AERMOD significant advances over ISC3ST. The established via (1) model evaluation and (02222) are equivalent to ISC–PRIME scientific merits of this approach have documentation, (2) peer review within predictions in areas affected by been documented both through the submittal process to a technical downwash before it replaces ISC– scientific peer review and performance journal, and (3) via the public review PRIME. Careful thought was given to the evaluations. The formulation of process. way that PRIME was incorporated into AERMOD has been subjected to an Based on the external peer review of AERMOD, with the goal of making the 5 extensive, independent peer review. the evaluation report and the public merge seamless. While discontinuities Findings of the peer review panel review comments, we have concluded from the concatenation of these two sets suggest that AERMOD’s scientific basis that: (1) AERMOD’s accuracy is of algorithms were of concern, we is ‘‘state-of-the-science.’’ Additionally, adequately documented; (2) AERMOD’s mitigated this situation wherever the model formulations used in accuracy is an improvement over possible (see part D of this preamble, AERMOD and the performance ISC3ST’s ability to predict measured and the Response to Comments evaluations have been accepted for concentrations; and (3) AERMOD is an document 4). With regard to testing the publication in two refereed journals.67 acceptable regulatory air dispersion performance of AERMOD (02222), we Finally, the adequacy of AERMOD’s model replacement for ISC3ST. have carefully confirmed that the complex terrain approach for regulatory Some commenters have identified AERMOD (02222)’s air quality applications is seen most directly in its what they perceived to be weaknesses in concentration predictions in the wake performance. AERMOD’s complex the evaluation and performance of ISC– region reasonably compare to those terrain component has been evaluated PRIME,10 and some concerns were predictions from ISC–PRIME. In fact, extensively by comparing model- raised about the scope of the PRIME the results indicate that AERMOD estimated regulatory design values and evaluation. However, as shown by the (02222)’s performance matches the concentration frequency distributions overwhelming number of requests for performance of ISC–PRIME, and are with observations. These comparisons the incorporation of PRIME into presented in an updated evaluation have demonstrated AERMOD’s AERMOD, commenters were convinced report 11 and analysis of regulatory superiority to ISC3ST and CTDMPLUS that the accuracy of PRIME, as design concentrations.12 We discuss (Complex Terrain Dispersion Model implemented within the ISC3ST AERMOD (02222) performance in detail PLUS unstable algorithms) in estimating framework, was reasonably documented in part D. those flat and complex terrain impacts and found acceptable for regulatory Because the technical basis for the of greatest regulatory importance.8 For applications. Although some PRIME algorithms and the AERMOD incidental and unique situations commenters requested more formulations have been independently involving a well-defined hill or ridge evaluations, practical limitations on the peer-reviewed, we believe that further and where a detailed dispersion number of valid, available data sets peer review of the new model analysis of the spatial pattern of plume prevented the inclusion of every source (AERMOD 02222) is not necessary. The impacts is of interest, CTDMPLUS in the type and setting in the evaluation. All scientific formulation of the PRIME Guideline’s appendix A remains the data bases that were reasonably algorithms has not been changed. available. available were used in the development However, the coding for the interface and evaluation of the model, and those Public comments also supported our between PRIME and the accompanying data bases were sufficient to establish conclusion about the scientific merits of dispersion model had to be modified the basis for the evaluation. Based on PRIME. A detailed article in a peer- somewhat to accommodate the different our review of the documentation and reviewed journal has been published ways that ISC3ST and AERMOD the public comments, we conclude that which contains all the basic equations simulate the atmosphere. The main the accuracy of PRIME is sufficiently with clear definitions of the variables, public concern was the interaction documented and find it acceptable for between the two models and whether use in a dispersion model recommended 5 U.S. Environmental Protection Agency, 2002. the behavior would be appropriate for Compendium of Reports from the Peer Review in the Guideline. all reasonable source settings. This Process for AERMOD. February 2002. Available at B. Appropriate for Proposed Use concern was addressed through the www.epa.gov/scram001/. extensive testing conducted within the 6 Cimorelli, A. et al., 2005. AERMOD: A Responding to a question posed in our performance evaluation 11 and analysis Dispersion Model for Industrial Source April 2000 proposal, the majority of of design concentrations.12 Both sets of Applications. Part I: General Model Formulation commenters questioned the and Boundary Layer Characterization. Journal of Applied Meteorology, 44(5): 682–693. reasonableness of requiring 11 Environmental Protection Agency, 2003. 7 Perry, S. et al., 2005. AERMOD: A Dispersion AERMOD: Latest Features and Evaluation Results. Model for Industrial Source Applications. Part II: 9 Schulman, L.L. et al., 2000. Development and Publication No. EPA–454/R–03–003. Available at Model Performance against 17 Field Study Evaluation of the PRIME Plum Rise and Building www.epa.gov/scram001/. Databases. Journal of Applied Meteorology, 44(5): Downwash Model. JAWMA 50: 378–390. 12 Environmental Protection Agency, 2003. 694–708. 10 Electric Power Research Institute, 1997. Results Comparison of Regulatory Design Concentrations: 8 Paine R. J. et al., 1998. Evaluation Results for of the Independent Evaluation of ISCST3 and ISC– AERMOD versus ISC3ST, CTDMPLUS, and ISC– AERMOD, Draft Report. Docket No. A–99–05; II–A– PRIME. Final Report, TR–2460026, November 1997. PRIME. Final Report. Publication No. EPA–454/R– 05. Available at www.epa.gov./scram001/. Available at www.epa.gov/scram001/. 03–002. Available at www.epa.gov/scram001/.

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analyses indicate that the new model is the rural unstable dispersion settings Survey (USGS), (3) appropriately use performing acceptably well and the (only the rural, stable dispersion setting Digital Elevation Model (DEM) data results are similar to those obtained considered meander in AERMOD with 2 different datums (NAD27 and from the earlier performance (99351)—this change created a NAD83); (4) accept all 7 digits of the evaluation 810 and analysis of regulatory consistent treatment of air dispersion in North UTM coordinate, and (5) do more design concentrations (i.e., for AERMOD all dispersion settings); error-checking in the raw data (mostly (99351)).13 • Making some changes to the basic checking for missing values, but not for While dry deposition is treated in meander algorithms (improved harsh terrain changes in adjacent ISC3ST, time and resources did not scientific formulation); and points). All of these recommendations • allow its incorporation in AERMOD Repairing miscellaneous coding have been implemented. (99351). Since no recommendation for errors. In response to comments about the deposition is made for regulatory As we mentioned earlier, the version selection of the domain affecting the applications, we did not consider that of AERMOD that is being promulgated results of the maximum concentrations the absence of this capability today—AERMOD (02222)—has been in complex terrain and the way compromises the suitability of subjected to further performance AERMAP estimates the effective hill evaluation 11 and analysis of design AERMOD for its intended purposes. height scale (hC), the algorithms within 12 Nevertheless, a number of commenters concentrations. AERMAP and AERMOD have been requested that deposition algorithms be C. Implementation Issues/Additional adjusted so that the hill height is less added to AERMOD, and we developed Guidance sensitive to the arbitrary selection of the an update to AERMOD (02222) that domain. This adjustment has been Other than miscellaneous suggestions offers dry and wet deposition for both evaluated against the entire set of for certain enhancements for AERMOD gases and particles as an option. evaluation data. The correction was The version of AERMOD under (99351) such as a Fortran90 compilation of the source code, creation of found to substantially reduce the effect review at the 7th Conference was of the domain size upon the AERMOD (99351) and, as mentioned allocatable arrays, and development of a Windows graphical user interface, no computation of controlling hill heights above, AERMIC has made a number of for each receptor. Application of this changes to AERMOD (99351) following significant implementation obstacles were identified in public comments. change to the evaluation databases did this conference. These changes were not materially affect the evaluation initiated in response to public For AERMET (meteorological preprocessor for AERMOD), we have results. comments and, after the release of a new In general, public comments that draft version of the model, in response implemented some enhancements that commenters suggested. For site-specific requested additional guidance were to the recommendations from the beta either obviated by revisions to AERMOD testers. Changes made to AERMOD applications, several commenters cited AERMOD’s requirements for NWS cloud (99351) and its related preprocessors or include the following: deemed unnecessary. In the latter case, • Adding the PRIME algorithms to the cover data. In response, we revised the AERMET to incorporate the bulk the reasons were explained in the model (response to public comments); 4 • Modifying the complex terrain Richardson number methodology. This Response-to-Comments document. Some public comments suggested algorithms to make AERMOD less approach uses temperature differences additional testing of AERMOD (99351). sensitive to the selection of the domain near the surface of the earth, which can In fact, after the model revisions that of the study area (response to public be routinely monitored, and eliminates comments); the need for the cloud cover data at were described earlier were completed, • Modifying the urban dispersion for AERMOD (02222) was subjected to night. We made a number of other 11 12 low-level emission sources, such as area revisions in response to public additional testing. These new sources, to produce a more realistic comments, enabling AERMET to: (1) analyses will be discussed in part D. urban dispersion and, as a part of this Use the old and the new Forecasting With respect to a screening version of change, changing the minimum layer Systems Laboratory formats, (2) use the AERMOD, a tool called AERSCREEN is depth used to calculate the effective Hourly U.S. Weather Observations/ being developed with a beta version dispersion parameters for all dispersion Automated Surface Observing Stations expected to be publicly available in Fall settings (scientific formulation (HUSWO/ASOS) data, (3) use site- 2005. SCREEN3 is the current screening correction which was requested by beta specific solar radiation and temperature model in the Guideline, and since testers); and gradient data to eliminate the need for SCREEN3 has been successfully applied • Upgrading AERMOD to include all cloud cover data, (4) appropriately for a number of years, we believe that the newest features that exist in the handle meteorological data from above SCREEN3 produces an acceptable latest version of ISC3ST such as the arctic circle, and (5) accept a wider degree of conservatism for regulatory Fortran90 compliance and allocatable range of reasonable friction velocities applications and may be used until arrays, EVENTS processing and the and reduce the number of warning AERSCREEN or a similar technique TOXICS option (response to public messages. As mentioned earlier, we becomes available and tested for general comments). added a meander component to the application. In the follow-up quality control treatment of stable and unstable urban D. AERMOD Revision and Reanalyses checking of the model and the source conditions to consistently treat meander Published In 2003 code, additional changes were identified phenomena for all cases. as necessary and the following revisions AERMAP (the terrain preprocessor for 1. Performance Analysis for AERMOD were made: (02222) • AERMOD) has been upgraded in Adding meander treatment to: (1) response to public comments calling for We have tested the performance of Stable and unstable urban cases, and (2) it to: (1) Treat complex terrain receptors AERMOD (02222) by applying all of the without a dependance on the selected original data sets used to support the 13 Peters, W.D. et al., 1999. Comparison of Regulatory Design Concentrations: AERMOD vs. domain, (2) accommodate the Spatial version proposed in April, 2000: 8 10 ISCST3 and CTDMPLUS, Draft Report. Docket No. Data Transfer Standard (SDTS) data AERMOD (99351) and ISC–PRIME. A–99–05; II–A–15. available from the U.S. Geological These data sets include: 5 complex

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terrain data sets, 7 building downwash Evaluation of AERMOD (02222) pollutants, stack heights and averaging data sets, and 5 simple terrain data sets With the changes to AERMOD (99351) times where the proposed (ISC–PRIME) (see appendix A of the Response-to- model performance could be compared 4 as outlined above, how has the Comments document ). This performance of the AERMOD been to the performance of AERMOD (02222) performance analysis, which is a check affected? The performance of the current with PRIME incorporated. There was an of the model’s maximum concentration version of AERMOD is about the same equal number of non-downwash cases predictions against observed data, or slightly better than the April 2000 where AERMOD performed better than includes a comparison of the current version when a comparison is made ISC–PRIME and where ISC–PRIME performed better than AERMOD. There version of the new model (AERMOD over all the available data sets. There 02222) with ISC3ST or ISC–PRIME for was only one case where there was a were examples of AERMOD (02222) downwash conditions. The results and significant difference between the two showing better and poorer performance conclusions of the performance analyses models’ performance, and AERMOD when compared to the performance are presented in 2 sections: Non- clearly performed better than ISC– results of AERMOD (99351). However, downwash and downwash source PRIME in this case. In all other cases, for those cases where AERMOD scenarios. the difference in the performance, (02222)’s performance was degraded, whether an improvement or a a. Non-Downwash Cases the degradation was small. On the other degradation, was small. This side, there were more examples where For the user community to obtain a comparison indicated that AERMOD full understanding of the impacts of AERMOD (02222) more closely (02222) performs very similarly, if not today’s proposal for the non-downwash predicted measured concentrations. The somewhat better, when compared to source scenarios (flat and complex performance improvements were also ISC–PRIME for downwash cases. terrain), our performance evaluation of rather small but, in general, were AERMOD (02222) must be discussed somewhat larger than the size of the 2. Analysis of Regulatory Design with respect to the old model, ISC3ST, performance degradations. There also Concentrations for AERMOD (02222) and with respect to AERMOD (99351). were a number of cases where the Although not a performance tool, the Based on the evaluation, we have performance remained unchanged analysis of design concentrations concluded that AERMOD (02222) between the 2 models. Thus, overall, (‘‘consequence’’ analysis) is designed to significantly outperforms ISC3ST and there was a slight improvement in test model stability and continuity, and that AERMOD (02222)’s performance is AERMOD’s performance and, to help the user community understand even better than that of AERMOD consequently, we believe that AERMOD the differences to be expected between (99351). (02222) significantly outperforms air dispersion models. The ISC3ST for non-downwash source consequences, or changes in the Evaluation of AERMOD (99351) scenarios. regulatory concentrations predicted Comparative performance statistics For AERMOD (02222) with the 5 data when using the new model (AERMOD were calculated for both ISC3ST and bases examined for simple terrain, the 02222) versus ISC3ST, cover 96 source AERMOD (99351) using data sets in ratios of modeled/observed Robust High scenarios and at least 3 averaging non-downwash conditions. This Concentration ranged from 0.77 to 1.11 periods per source scenario, and are analysis looked at combinations of test (1-hr average), 0.98 to 1.24 (3-hr evaluated and summarized here. The sites (flat and complex terrain), average), 0.94 to 0.97 (24-hr average) purpose is to provide the user pollutants, and concentration averaging and 0.30 to 0.97 (annual average). These community with a sense of potential times. Comparisons indicated very ratios reflect better performance than changes in their air dispersion analyses significant improvements in ISC3ST for all cases. when applying the new model over a performance when applying AERMOD For AERMOD (02222) with the 5 data broad range of source types and settings. (99351). In all but 1 of the total of 20 bases examined for complex terrain, The consequence analysis, in which cases in which AERMOD (99351) could these ratios ranged from 1.03 to 1.12 (3- AERMOD was run for hundreds of be compared to ISC3ST, AERMOD hr average), 0.67 to 1.78 (24-hr average) source scenarios, also provides a check performed as well as (but generally and 0.54 to 1.59 (annual average). At for model stability (abnormal halting of better than) ISC3ST, that is, AERMOD Tracy—the only site for which there are model executions when using valid predicted maximum concentrations that 1-hr data—AERMOD performed control files and input data) and for were closer to the measured maximum considerably better (ratio = 1.04) than spurious results (unusually high or low concentrations. In the most dramatic either ISC3ST or CTDMPLUS. At three concentration predictions which are case (i.e., Lovett; 24-hr) in which of the other four sites, AERMOD unexplained). The results are placed AERMOD performed better than generally performed much better than into 3 categories: non-downwash source ISC3ST, AERMOD’s maximum either ISC3ST or (where applicable) scenarios in flat, simple terrain; concentration predictions were about alternative models for the 3-hr and 24- downwash source scenarios in flat the same as the measured hr averaging times; results were terrain; and, complex terrain source concentrations while the ISC3ST’s comparable for Clifty Creek (for the 3- settings. The focus of this discussion is predicted maximum concentrations hr averaging times, AERMOD (02222) on how design concentrations change were about 9 times higher than the predictions were only about 5% higher from those predicted by ISC3ST when measured concentrations. In the one than ISC3ST’s—down from 25% for applying the latest version of AERMOD case (i.e., Clifty Creek; 3-hr) where AERMOD (99351) as described earlier). versus applying the earlier version of ISC3ST performed better than AERMOD At the two sites where annual peak AERMOD (99351). (99351), ISC3ST’s concentration comparisons are available, AERMOD predictions matched the observed data performed much better than either a. Non-Downwash Cases and the AERMOD concentration ISC3ST or alternative models. For the non-downwash situations, predictions were about 25% higher than there were 48 cases covering a variety of the observed data. These results were b. Downwash Cases source types (point, area, and volume reported in the supporting For the downwash data sets, there sources), stack heights, terrain types documentation for AERMOD (99351). were combinations of test sites, (flat and simple), and dispersion

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settings (urban and rural). For each case from 2.24 for ISC–PRIME/ISC3ST to were almost unchanged. There were no in the consequence analysis, we 1.87 for AERMOD (02222)/ISC3ST and cases in either consequence analysis calculated the ratio between AERMOD’s the minimum value of the concentration where AERMOD (02222 & 99351) regulatory concentration predictions ratios range from 0.34 for ISC–PRIME/ predicted higher concentrations than and ISC3ST’s regulatory concentration ISC3ST to 0.38 for AERMOD (02222)/ those predicted by ISC3ST. Thus, in predictions. The average ratio of ISC3ST. These results show relatively general, the consequences of moving AERMOD to ISC3ST-predicted close agreement between the two PRIME from ISC3ST to AERMOD (02222) rather concentrations changed from 1.14 when models. (See Table 4–6 in reference 12.) than to AERMOD (99351) in complex applying AERMOD (99351) to 0.96 ISC3ST does not predict cavity terrain were essentially the same. (See when applying AERMOD (02222).14 concentrations but comparisons can be Table 4–9 in reference 12.) Thus, in general, AERMOD (02222) made between AERMOD and ISC– E. Emission and Dispersion Modeling tends to predict concentrations closer to PRIME. The average AERMOD (02222) System (EDMS) ISC3ST than does version 99351 predicted 1-hour cavity concentration is proposed in April 2000. Also, the about the same (112%) as the average The Emissions and Dispersion variation of the differences between ISC–PRIME 1-hour cavity concentration. Modeling System (EDMS) was ISC3ST and AERMOD has decreased In the extremes, the AERMOD (02222)- developed jointly by the Federal with AERMOD (02222). Comparing the predicted cavity concentrations ranged Aviation Administration (FAA) and the earlier consequence analysis to the from about 40% higher to 15% lower U.S. Air Force in the late 1970s and first latest study with AERMOD (02222), we than the corresponding ISC–PRIME released in 1985 to assess the air quality saw a 25% reduction in the number of cavity concentration predictions. Thus, of proposed airport development cases where the AERMOD-predicted in general, where downwash is a projects. EDMS has an emissions concentrations differed by over a factor significant factor, AERMOD (02222) and preprocessor and its dispersion module of two from ISC3ST’s predictions. ISC–PRIME predict similar maximum estimates concentrations for various concentrations. (See Table 4–8 in averaging times for the following b. Downwash Cases reference 12.) pollutants: CO, HC, NOX, SOX, and For the downwash analysis, there Although the same downwash suspended particles (e.g., PM–10). The were 20 cases covering a range of stack algorithms are used in both models, first published application of EDMS was heights, locations of stacks relative to there are differences in the melding of in December 1986 for Stapleton the building, dispersion settings, and PRIME with the core model, and International Airport (FAA–EE–11–A/ building shapes. As before, we differences in the way that these models REV2). calculated the ratio regulatory simulate the atmosphere.15 The In 1988, version 4a4 revised the concentration predictions from downwash algorithm implementation dispersion module to include an AERMOD (02222 with PRIME) and therefore could not be exactly the same. integral dispersion submodel: GIMM compared them as ratios to those from (Graphical Input Microcomputer ISC3ST for each case. For additional c. Complex Terrain Model). This version was proposed for information, we also included ratios During the testing of AERMOD after adoption in the Guideline’s appendix A with ISC–PRIME that was also proposed modifications were made to the in February 1991 (56 FR 5900). This in April 2000. complex terrain algorithm (see version was included in appendix A in July 1993 (58 FR 38816) and Calculated over all the 20 cases, and discussion of hill height scale (hC) in B. for all averaging times considered, the Appropriate for Proposed Use in this recommended for limited applications average ISC–PRIME to ISC3ST preamble), a small error was found in for assessments of localized airport concentration ratio is about 0.86, the original complex terrain code while impacts on air quality. FAA later whereas for AERMOD (PRIME) to conducting the consequence analysis. updated EDMS to Version 3.0. ISC3ST, it is 0.82. The maximum value This error was subsequently repaired. In response to the growing needs of of the concentration ratios range from Final testing indicated that the revised air quality analysts and changes in 2.24 for ISC–PRIME/ISC3ST to 3.67 for complex terrain code produced regulations (e.g., conformity AERMOD (PRIME)/ISC3ST. Similarly, reasonable results for the consequence requirements from the Clean Air Act the minimum value of the concentration analysis, as described below. Amendment of 1990), FAA updated ratio range from 0.04 for ISC–PRIME/ The analysis of predicted design EDMS to version 3.1, which is based on 16 ISC3ST to 0.08 for AERMOD (PRIME)/ concentrations included a suite of the CALINE3 and PAL2 dispersion ISC3ST. (See Table 4–5 in reference 12.) complex terrain settings. There were 28 kernels. In our April 2000 NPR we Although results above for the two cases covering a variety of stack heights, proposed to adopt the version 3.1 models that use PRIME—AERMOD stack gas buoyancy values, types of update to EDMS. However, this update (02222) and ISC–PRIME—show hills, and distances between source and had not been subjected to performance differences, we find that building terrain. The ratios between the evaluation and no studies of EDMS’ downwash is not a significant factor in AERMOD (02222 & 99351)—predicted performance have been cited in determining the maximum maximum concentrations and the appendix A of the Guideline. Comment concentrations in some of the cases, i.e., ISC3ST maximum concentrations were was invited on whether this the PRIME algorithms do not predict a calculated for all cases for a series of compromises the viability of EDMS 3.1 building cavity concentration. Of those averaging times. When comparing as a recommended or preferred model cases where downwash was important, AERMOD (99351) to ISC3ST and then and how this deficiency can be the average concentration ratios of ISC– AERMOD (02222) to ISC3ST, the corrected. PRIME/ISC3ST and AERMOD (02222)/ average maximum concentration ratio, Several commenters expressed ISC3ST are about 1. The maximum the highest ratios and the lowest ratios concern about EDMS 3.1 as a value of the concentration ratios range recommended model in appendix A. 15 AERMOD uses more complex techniques to Indeed, there were concerns that EDMS 14 A ratio of 1.00 indicates that the two models estimate temperature profiles which, in turn, affect are predicting the same concentrations. See Table the calculation of the plume rise. Plume rise may 16 Currently listed in appendix A of the 4.1 in reference 12. affect the cavity and downwash concentrations. Guideline.

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3.1 had not been as well validated as comments, developed responses, and methodology used to evaluate AERMOD other models, nor subjected to peer documented conclusions on appropriate (one that emphasizes Robust High review, as required by the Guideline’s actions for today’s notice. Whenever the Concentration), claiming it is ill-suited subsection 3.1.1. One of these comments revealed any new to the way dispersion models estimate commenters suggested that EDMS 3.1 information or suggested any alternative ambient concentrations. We should be presented only as one of solutions, we considered them in our acknowledged that other methods are several alternative models. final action and made corrections or available that are designed to reflect the At the 7th Conference, FAA proposed enhancements where appropriate. underlying physics and formulations of for appendix A adoption an even newer, In the remainder of this preamble dispersion models, and may be more enhanced version of EDMS—version section we highlight the main issues robust in their mechanisms to account 4.0, which incorporates the AERMOD raised by the commenters who reviewed for the stochastic nature of the dispersion kernel (without alteration). the NDA, and summarize our responses. atmosphere. In fact, we cited several In this system, the latest version of These comments broadly fall into two recent cases from the literature in which AERMOD would be employed as a categories: technical/operational, and standalone component of EDMS. This administrative. such methods were applied in dispersion kernel was to replace PAL2 The technical/operational comments evaluations that included AERMOD. We and CALINE3 currently in EDMS 3.1. were varied. One commenter thought also explained that the approach taken There were no public comments specific EPA’s sensitivity studies for simulating by AERMIC was based on existing to FAA’s proposed AERMOD-based area sources were too limited, and noted guidance in section 9 of Appendix W, enhancements to EDMS announced after that AERMOD, when used to simulate and expressed a commitment to explore our April 2000 NPR. an area source adjacent to gently sloping other methods in the future, including In response to written comments on terrain, produced ground-level an update to section 9. We believe our April 2000 NPR, at the 7th concentrations not unlike those from however that the evaluation Conference (transcript) FAA promised a ISC3ST. In response we explained methodology used was reasonable for its complete evaluation process that would qualitatively how AERMOD interprets intended purpose—examining a large include sensitivity testing, intermodel this situation and cautioned that array of concentrations for a wide comparison, and analysis of EDMS reviewing authorities should be variety of source types—and confers a predictions against field observations. consulted in such scenarios for measure of consistency given its past The intermodel comparisons were guidance on switch settings. Other use. Other commenters expressed proposed for the UK’s Atmospheric commenters believed that AERMOD disappointment that AERMOD wasn’t Dispersion Modeling System (ADMS).17 exhibited unrealistic treatment of compared to state-of-the-science models As we explained in our September 8, complex terrain elements and offered as advised in its peer review report. In 2003 Notice of Data Availability, FAA supporting data. In response, AERMIC response, we cited a substantial list of has decided to withdraw EDMS from concluded that AERMOD does exhibit studies in which AERMOD has, in fact, terrain amplification factors on the the Guideline’s appendix A. We stated been compared to some of these models, windward side of isolated hills, where that no new information was therefore e.g., HPDM and ADMS (in various provided in that notice, and we affirmed impacts are expected to be greatest. Commenters also presented evidence combinations). On the whole, as we support for EDMS’ removal from noted in our response, AERMOD appendix A. This removal, which we that the PRIME algorithm in AERMOD typically performed as well as HPDM promulgate today, obviates the need for misbehaves in its treatment of building and ADMS, and all of them generally EDMS’ documentation and evaluation at wake and wind incidence. Another performed better than ISC3ST. Still this time. model was cited as having better skill in this regard. In response, we others expressed disappointment that V. Discussion of Public Comments on acknowledged this but established that the evaluation input data weren’t posted Our September 8, 2003 Notice of Data AERMOD’s capability was acceptable on our Web site until January 22, 2004— Availability for handling the majority of building three months after the close of the As mentioned in section III, after geometries encountered (see Response- comment period. We acknowledge that AERMOD was revised pursuant to to-Comments document 4 for more the input data were not posted when the comments received on the April 21, details). NDA was published. However, the 2000 proposal, a Notice of Data A number of commenters addressed actual evaluation input data for Availability (NDA) was issued on administrative or procedural matters. AERMOD had not been requested September 8, 2003 to explain the Some believed that the transition period previously, and we did not believe they modifications and to reveal AERMOD’s for implementation—one year—is too were required as a basis for reviewing new evaluation data. Public comments short. We explained in response that the reports we released. Moreover, since were solicited for 30 days and posted one year is consistent with past practice the posting, we are unaware of any electronically in eDocket OAR–2003– and is adequate for most users and belated adverse comments from anyone 0201.1 (As mentioned in section IV, reviewing authorities given our previous attempting to access and use the data. additional comments received since we experience with new models and the We believe we have carefully published the final rule on April 15, fact that AERMOD has been in the considered and responded to public 2003 are filed in Docket A–99–05; public domain for several years. Some comments and concerns regarding category IV–E.) We summarized these were disappointed that the review comments and developed detailed period (30 days) for the NDA was too AERMOD. We have also made efforts to responses; these appear as appendix C short. We believe that the period was update appendix W to better reflect to the Response-to-Comments adequate to review the two reports that current practice in model solicitation, document.4 In appendix C, we presented updated information on the evaluation and selection. We also have considered and discussed all significant performance and practical consequences made other technical revisions so the of the model as revised. Regarding the guidance conforms with the latest form 17 Cambridge Environmental Research evaluation/comparison regime used for of the PM–10 National Ambient Air Consultants; http://www.cerc.co.uk/. AERMOD, others objected to the Quality Standard.

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VI. Final Action 2004. The latest version of AERMOD Since AERMOD (02222) was released, In this section we explain the changes may now be used for deposition an updated version was posted on our to the Guideline in today’s action in analysis in special situations. Web site on March 22, 2004: AERMOD Since AERMOD treats dispersion in terms of the main technical and policy (04079). The version we are releasing complex terrain, we have merged concerns addressed by the Agency in its pursuant to today’s promulgation, sections 4 and 5 of appendix W, as response to public comments (sections however, is AERMOD (04300). This proposed in the April 2000 NPR. And IV & V). Air quality modeling involves version, consonant with AERMOD while AERMOD produces acceptable estimating ambient concentrations using (02222) in its formulations, addresses regulatory design concentrations in scientific methodologies selected from a the following minor code issues: complex terrain, it does not replace • The area source algorithm in simple range of possible methods, and should CTDMPLUS for detailed or receptor- and complex terrain required a utilize the most advanced practical oriented complex terrain analysis, as we correction to the way the dividing technology that is available at a have made clear in Guideline section streamline height is calculated. reasonable cost to users, keeping in 4.2.2. CTDMPLUS remains available for • In PRIME, incorrect turbulence mind the intended uses of the modeling use in complex terrain. parameters were being passed to one of and ensuring transparency to the public. We have implemented the majority of the numerical plume rise routines, and With these changes, we believe that the suggestions to improve the AERMET, this has been corrected. Guideline continues to reflect recent AERMAP, and AERMOD source code to • A limit has been placed on plume advances in the field and balance these reflect all the latest features that have cooling within PRIME to avoid important considerations. Today’s been available in ISC3ST and that are supercooling, which had been causing action amends Appendix W of 40 CFR available in the latest versions of runtime instability. part 51 as detailed below: Fortran compilers. Also, the latest • A correction has been made to AERMOD formats for meteorological and terrain avoid AERMOD’s termination under certain situations with capped stacks Based on the supporting information input data are now accepted by the new versions of AERMET and AERMAP. Our (i.e., where the routine was attempting contained in the docket, and reflected in to take a square root of a negative peer review and public comments, we guidance, documentation and users’ guides have been modified in response number). Our testing has demonstrated find that the AERMOD modeling system only very minor impacts from these and PRIME are based on sound to a number of detailed comments. With respect to AERMOD (02222)’s corrections on the evaluation results or scientific principles and provide performance, we have concluded that: the consequence analysis. significant improvements over the (1) AERMOD (99351), the version AERMOD (04300) has other draft current regulatory model, ISC3ST. proposed in April 2000, performs portions of code that represent options AERMOD characterizes plume significantly better than ISC3ST, and not required for regulatory applications. dispersion better than ISC3ST. The AERMOD (02222) performs slightly These include: accuracy of the AERMOD system is better than AERMOD (99351) in non- • Dry and wet deposition for both generally well-documented and superior downwash settings in both simple and gases and particles; to that of ISC3ST. We are adopting the complex terrain; • The ozone limiting method (OLM), model based on its performance and (2) The performance evaluation referenced in section 5.2.4 (Models for other factors. indicates that AERMOD (02222) Nitrogen Dioxide—Annual Average) of Public comments on the April 2000 performs slightly better than ISC–PRIME the Guideline for treating NOX proposal expressed significant concern for downwash cases. conversion; and about the need to use two models With respect to changes in AERMOD’s • The Plume Volume Molar Ratio (AERMOD and ISC–PRIME) to simulate regulatory design concentrations Method (PVMRM) for treating NOX just one source when downwash posed compared to those for ISC3ST, we have conversion. a potential impact. In response to this concluded that: • The bulk Richardson number concern we incorporated PRIME into • For non-downwash settings, approach (discussed earlier) for using AERMOD and documented satisfactory AERMOD (02222), on average, tends to near-surface temperature difference has tests of the algorithm. AERMOD, with predict concentrations closer to ISC3ST, been corrected in AERMOD (04300). the inclusion of PRIME, is now and with somewhat smaller variations, Based on the technical information appropriate and practical for regulatory than the April 2000 proposal of contained in the docket for this rule, applications. AERMOD; and with consideration of the The state-of-the-science for modeling • Where downwash is a significant performance analysis in combination atmospheric deposition continues to factor in the air dispersion analysis, with the analysis of design evolve, the best techniques are currently AERMOD (02222) predicts maximum concentrations, we believe that being assessed, and their results are concentrations that are very similar to AERMOD is appropriate for regulatory being compared with observations. ISC–PRIME’s predictions; use and we are revising the Guideline to Consequently, as we now say in • For those source scenarios where adopt it as a refined model today. Guideline paragraph 4.2.2(c), the maximum 1-hour cavity concentrations In implementing the changes to the approach taken for any regulatory are calculated, the average AERMOD Guideline, we recognize that there may purpose should be coordinated with the (02222)-predicted cavity concentration arise occasions in which the application appropriate reviewing authority. We tends to be about the same as the of a new model can result in the agreed with the public comments average ISC–PRIME cavity discovery by a permit applicant of calling for the addition of state-of-the- concentrations; and previously unknown violations of science deposition algorithms, and • In complex terrain, the NAAQS or PSD increments due to developed a modification to AERMOD consequences of using AERMOD emissions from existing nearby sources. (02222) for beta testing. This model, (02222) instead of ISC3ST remained This potential has been acknowledged AERMOD (04079) was posted on our essentially unchanged in general, previously and is addressed in existing Web site http://www.epa.gov/scram001/ although they varied based on EPA guidance (‘‘Air Quality Analysis for tt25.htm#aermoddep on March 19, individual circumstances. Prevention of Significant Deterioration

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(PSD),’’ Gerald A. Emison, July 5, 1988). the interim, as appropriate, we will Section 6 To summarize briefly, the guidance consider the use of either ISC3 or As proposed, we renumbered this to identifies three possible outcomes of AERMOD in air toxic risk assessment become section 5. In subsection 5.1, we modeling by a permit applicant and applications. reference the Plume Volume Molar details actions that should be taken in EDMS Ratio Method (PVMRM) for point response to each: sources of NO , and mention that it is 1. Where dispersion modeling shows FAA has completed development of X currently being tested to determine no violation of a NAAQS or PSD the new EDMS4.0 to incorporate suitability as a refined method. increment in the impact area of the AERMOD. The result is a conforming proposed source, a permit may be enhancement that offers a stronger Section 7 issued and no further action is required. scientific basis for air quality modeling. As proposed, we renumbered this to 2. Where dispersion modeling FAA has made this model available on become section 6. We updated the predicts a violation of a NAAQS or PSD its Web site, which we cite in an reference to the Emissions and increment within the impact area but it updated Guideline paragraph 7.2.4(c). Dispersion Modeling System (EDMS). is determined that the proposed source As described earlier in this preamble, will not have a significant impact (i.e., the summary description for EDMS will Section 8 will not be above de minimis levels) at be removed from appendix A. As proposed, we revised section 8 the point and time of the modeled (renumbered to section 7) to provide violation, then the permit may be issued VII. Final Editorial Changes to Appendix W guidance for using AERMET immediately, but the State must take (AERMOD’s meteorological appropriate actions to remedy the Today’s update of the Guideline takes preprocessor). violations within a timely manner. the form of many revisions, and some of • In subsection 7.2.4, we introduce 3. Where dispersion modeling the text is unaltered. Therefore, as a the atmospheric stability predicts a violation of a NAAQS or PSD purely practical matter, we have chosen characterization for AERMOD. increment within the impact area and it to publish the new version of the entire • In subsection 7.2.5, we describe the is determined that the proposed source text of appendix W and its appendix A. plume rise approaches used by will have a significant impact at the Guidance and editorial changes AERMOD. point and time of the modeled violation, associated with the resolution of the then the permit may not be issued until issues discussed in the previous section Section 9 the source owner or operator eliminates are adopted in the appropriate sections As proposed, we renumbered section or reduces that impact below of the Guideline, as follows: 9 to become section 8. We added significance levels through additional Preface paragraphs 8.3.1.2(e) and 8.3.1.2(f) to controls or emissions offsets. Once it clarify use of site specific does so, then the permit may be issued You will note some minor revisions of meteorological data for driving even if the violation persists after the appendix W to reflect current EPA CALMET in the separate circumstances source owner or operator eliminates its practice. of long range transport and for complex contribution, but the State must take Section 4 terrain applications. further appropriate actions at nearby sources to eliminate the violations As mentioned earlier, we revised Section 10 within a timely manner. section 4 to present AERMOD as a As proposed, we revised section 10 In previous promulgations, we have refined regulatory modeling technique (renumbered section 9) to include traditionally allowed a one-year for particular applications. AERMOD. In May 1999, the D.C. Court transition (‘‘grandfather’’) period for Section 5 of Appeals vacated the PM–10 standard new refined techniques. Accordingly, we promulgated in 1997, and this As mentioned above, we merged for appropriate applications, AERMOD standard has since been removed from pertinent guidance in section 5 may be substituted for ISC3 during the the CFR (69 FR 45592; July 30, 2004). (Modeling in Complex Terrain) with one-year period following the Paragraph 10.2.3.2(a) has been corrected that in section 4. With the anticipated promulgation of today’s notice. to be consistent with the current widespread use of AERMOD for all Beginning one year after promulgation (original) PM–10 standard, which is terrain types, there is no longer any of today’s notice, (1) applications of based on expected exceedances. ISC3 with approved protocols may be utility in the previous differentiation accepted (see DATES section) and (2) between simple and complex terrain for Section 11 AERMOD should be used for model selection. To further simplify, the As proposed, we renumbered section appropriate applications as a list of acceptable, yet equivalent, 11 to become section 10. replacement for ISC3. screening techniques for complex We separately issue guidance for use terrain was removed. CTSCREEN and Sections 12 & 13 of modeling for facility-specific and guidance for its use are retained; We renumbered section 12 to become community-scale air toxics risk CTSCREEN remains acceptable for all section 11, and section 13 (References) assessments through the Air Toxics Risk terrain above stack top. The screening to become section 12. We revised Assessment Reference Library.18 We techniques whose descriptions we renumbered section 12 by adding some recognize that the tools and approaches removed, i.e., Valley (as implemented in references, deleting obsolete/superseded recommended therein will eventually SCREEN3), COMPLEX I (as ones, and resequencing. You will note reflect the improved formulations of the implemented in ISC3ST), and RTDM that the peer scientific review for AERMOD modeling system and we remain available for use in applicable AERMOD and latest evaluation expect to appropriately incorporate cases where established/accepted references have been included. them as expeditiously as practicable. In procedures are used. Consultation with the appropriate reviewing authority is Appendix A 18 http://www.epa.gov/ttn/fera/risk still advised for application of these We added AERMOD (with the PRIME _atra_main.html. screening models. downwash algorithm integrated) to

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appendix A. We removed EDMS from needed to review instructions; develop, D. Unfunded Mandates Reform Act of appendix A. We also updated the acquire, install, and utilize technology 1995 description for CALPUFF, and made and systems for the purposes of Title II of the Unfunded Mandates minor updates to some of the other collecting, validating, and verifying Reform Act of 1995 (UMRA), Public model descriptions. information, processing and Law 104–4, establishes requirements for maintaining information, and disclosing Availability of Related Information Federal agencies to assess the effects of and providing information; adjust the their regulatory actions on State, local, Our Air Quality Modeling Group existing ways to comply with any and tribal governments and the private maintains an Internet Web site (Support previously applicable instructions and sector. Under section 202 of the UMRA, Center for Regulatory Air Models— requirements; train personnel to be able EPA generally must prepare a written SCRAM) at: http://www.epa.gov/ to respond to a collection of statement, including a cost-benefit scram001. You may find codes and information; search data sources; analysis, for proposed and final rules documentation for models referenced in complete and review the collection of with ‘‘Federal mandates’’ that may today’s action on the SCRAM Web site. information; and transmit or otherwise result in expenditures to State, local, In addition, we have uploaded various disclose the information. and tribal governments, in the aggregate, support documents (e.g., evaluation An agency may not conduct or or to the private sector, of $100 million reports). sponsor, and a person is not required to or more in any one year. Before VIII. Statutory and Executive Order respond to a collection of information promulgating an EPA rule for which a Reviews unless it displays a currently valid OMB written statement is needed, section 205 control number. The OMB control of the UMRA generally requires EPA to A. Executive Order 12866: Regulatory numbers for EPA’s regulations in 40 identify and consider a reasonable Planning and Review CFR are listed in 40 CFR part 9. number of regulatory alternatives and Under Executive Order 12866 [58 FR C. Regulatory Flexibility Act (RFA) adopt the least costly, most cost- 51735 (October 4, 1993)], the Agency effective or least burdensome alternative must determine whether the regulatory The RFA generally requires an agency that achieves the objectives of the rule. action is ‘‘significant’’ and therefore to prepare a regulatory flexibility The provisions of section 205 do not subject to review by the Office of analysis of any rule subject to notice apply when they are inconsistent with Management and Budget (OMB) and the and comment rulemaking requirements applicable law. Moreover, section 205 requirements of the Executive Order. under the Administrative Procedure Act allows EPA to adopt an alternative other The Order defines ‘‘significant or any other statute unless the agency than the least costly, most cost-effective regulatory action’’ as one that is likely certifies that the rule will not have a or least burdensome alternative if the to result in a rule that may: significant economic impact on a Administrator publishes with the final (1) Have an annual effect on the substantial number of small entities. rule an explanation why that alternative economy of $100 million or more or Small entities include small businesses, was not adopted. Before EPA establishes adversely affect in a material way the small organizations, and small any regulatory requirements that may economy, a sector of the economy, governmental jurisdictions. significantly or uniquely affect small productivity, competition, jobs, the For purposes of assessing the impact governments, including tribal environment, public health or safety, or of today’s rule on small entities, small governments, it must have developed State, local, or tribal governments or entities are defined as: (1) A small under section 203 of the UMRA a small communities; business that meets the RFA default government agency plan. (2) Create a serious inconsistency or definitions for small business (based on The plan must provide for notifying otherwise interfere with an action taken Small Business Administration size potentially affected small governments, or planned by another agency; standards), as described in 13 CFR enabling officials of affected small (3) Materially alter the budgetary 121.201; (2) a small governmental governments to have meaningful and impact of entitlements, grants, user fees, jurisdiction that is a government of a timely input in the development of EPA or loan programs of the rights and city, county, town, school district or regulatory proposals with significant obligations of recipients thereof; or special district with a population of less Federal intergovernmental mandates, (4) Raise novel legal or policy issues than 50,000; and (3) a small and informing, educating, and advising arising out of legal mandates, the organization that is any not-for-profit small governments on compliance with President’s priorities, or the principles enterprise which is independently the regulatory requirements. set forth in the Executive Order. owned and operated and is not Today’s rule recommends a new It has been determined that this rule dominant in its field. modeling system, AERMOD, to replace is not a ‘‘significant regulatory action’’ After considering the economic ISC3ST as an analytical tool for use in under the terms of Executive Order impacts of today’s final rule on small SIP revisions and for calculating PSD 12866 and is therefore not subject to EO entities, I certify that this action will not increment consumption. AERMOD has 12866 review. have a significant economic impact on been used for these purposes on a case- a substantial number of small entities. by-case basis (per Guideline subsection B. Paperwork Reduction Act As this rule merely updates existing 3.2.2) for several years. Since the two This final rule does not contain any technical requirements for air quality modeling systems are comparable in information collection requirements modeling analyses mandated by various scope and purpose, use of AERMOD subject to review by OMB under the CAA programs (e.g., prevention of itself does not involve any significant Paperwork Reduction Act, 44 U.S.C. significant deterioration, new source increase in costs. Moreover, modeling 3501 et seq. review, State Implementation Plan costs (which include those for input Burden means the total time, effort, or revisions) and imposes no new data acquisition) are typically among financial resources expended by persons regulatory burdens, there will be no the implementation costs that are to generate, maintain, retain, or disclose additional impact on small entities considered as part of the programs (i.e., or provide information to or for a regarding reporting, recordkeeping, and PSD) that establish and periodically Federal agency. This includes the time compliance requirements. revise requirements for compliance.

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Any incremental modeling costs calculating PSD increment test methods, sampling procedures, and attributable to today’s rule do not consumption, and does not impose any business practices) that are developed or approach the $100 million threshold additional requirements for the adopted by voluntary consensus prescribed by UMRA. EPA has regulated community, including Indian standards bodies. The NTTAA directs determined that this rule contains no Tribal Governments. Thus, Executive EPA to provide Congress, through OMB, regulatory requirements that might Order 13175 does not apply to this rule. explanations when the Agency decides significantly or uniquely affect small Today’s final rule does not not to use available and applicable governments. This rule therefore significantly or uniquely affect the voluntary consensus standards. contains no Federal mandates (under communities of Indian tribal the regulatory provisions of Title II of governments. Accordingly, the This action does not involve technical the UMRA) for State, local, or tribal requirements of section 3(b) of standards. Therefore, EPA did not governments or the private sector. Executive Order 13175 do not apply to consider the use of any voluntary this rule. consensus standards. E. Executive Order 13132: Federalism Executive Order 13132, entitled G. Executive Order 13045: Protection of J. Congressional Review Act of 1998 ‘‘Federalism’’ (64 FR 43255, August 10, Children From Environmental Health and Safety Risks The Congressional Review Act, 5 1999), requires EPA to develop an U.S.C. 801 et seq., as added by the Small accountable process to ensure Executive Order 13045 applies to any Business Regulatory Enforcement ‘‘meaningful and timely input by State rule that EPA determines (1) to be Fairness Act of 1996, generally provides and local officials in the development of ‘‘economically significant’’ as defined that before a rule may take effect, the regulatory policies that have federalism under Executive Order 12866, and (2) agency promulgating the rule must implications.’’ ‘‘Policies that have the environmental health or safety risk federalism implications’’ is defined in addressed by the rule has a submit a rule report, which includes a the Executive Order to include disproportionate effect on children. If copy of the rule, to each House of the regulations that have ‘‘substantial direct the regulatory action meets both the Congress and to the Comptroller General effects on the States, on the relationship criteria, the Agency must evaluate the of the United States. EPA will submit a between the national government and environmental health or safety effects of report containing this rule and other the States, or on the distribution of the planned rule on children; and required information to the U.S. Senate, power and responsibilities among the explain why the planned regulation is the U.S. House of Representatives, and various levels of government.’’ preferable to other potentially effective the Comptroller General of the United This final rule does not have and reasonably feasible alternatives States prior to publication of the rule in federalism implications. It will not have considered by the Agency. the Federal Register. A Major rule substantial direct effects on the States, This final rule is not subject to cannot take effect until 60 days after it on the relationship between the national Executive Order 13045, entitled is published in the Federal Register. government and the States, or on the ‘‘Protection of Children from This action is not a ‘‘major rule’’ as distribution of power and Environmental Health Risks and Safety defined by 5 U.S.C. 804(2), and will be responsibilities among the various Risks’’ (62 FR 19885, April 23, 1997) effective 30 days from the publication levels of government, as specified in because it does not impose an date of this notice. Executive Order 13132. This rule does economically significant regulatory not create a mandate on State, local or action as defined by Executive Order List of Subjects in 40 CFR Part 51 tribal governments. The rule does not 12866 and the action does not involve impose any enforceable duties on these decisions on environmental health or Environmental protection, entities (see D. Unfunded Mandates safety risks that may disproportionately Administrative practice and procedure, Reform Act of 1995, above). The rule affect children. Air pollution control, Carbon monoxide, would add better, more accurate Intergovernmental relations, Nitrogen techniques for air dispersion modeling H. Executive Order 13211: Actions That oxides, Ozone, Particulate Matter, analyses and does not impose any Significantly Affect Energy Supply, Reporting and recordkeeping additional requirements for any of the Distribution, or Use requirements, Sulfur oxides. affected parties covered under Executive This rule is not subject to Executive Dated: October 21, 2005. Order 13132. Thus, Executive Order Order 13211, ‘‘Actions Concerning 13132 does not apply to this rule. Regulations That Significantly Affect Stephen L. Johnson, Energy Supply, Distribution, or Use’’ (66 Administrator. F. Executive Order 13175: Consultation FR 28355 (May 22, 2001)) because it is and Coordination With Indian Tribal ■ Part 51, chapter I, title 40 of the Code not a significant regulatory action under Governments of Federal Regulations is amended as Executive Order 12866. Executive Order 13175, entitled follows: ‘‘Consultation and Coordination with I. National Technology Transfer and PART 51—REQUIREMENTS FOR Indian Tribal Governments’’ (65 FR Advancement Act of 1995 PREPARATION, ADOPTION, AND 67249, November 9, 2000), requires EPA Section 12(d) of the National to develop an accountable process to Technology Transfer and Advancement SUBMITTAL OF IMPLEMENTATION ensure ‘‘meaningful and timely input by Act of 1995 (‘‘NTTAA’’), Public Law PLANS tribal officials in the development of 104–113, section 12(d) (15 U.S.C. 272 ■ regulatory policies that have tribal note) directs EPA to use voluntary 1. The authority citation for part 51 implications.’’ This final rule does not consensus standards in its regulatory continues to read as follows: have tribal implications, as specified in activities unless to do so would be Authority: 23 U.S.C. 100; 42 U.S.C. 7401– Executive Order 13175. As stated above inconsistent with applicable law or 7671q. (see D. Unfunded Mandates Reform Act otherwise impractical. Voluntary of 1995, above), the rule does not consensus standards are technical ■ 2. Appendix W to Part 51 revised to impose any new requirements for standards (e.g., materials specifications, read as follows:

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Appendix W to Part 51—Guideline on 4.0 Stationary-Source Models 10.2.3 Emission Limits Air Quality Models 4.1 Discussion 11.0 Bibliography 4.2 Recommendations Preface 4.2.1 Screening Techniques 12.0 References a. Industry and control agencies have long 4.2.1.1 Simple Terrain Appendix A to Appendix W of 40 CFR Part expressed a need for consistency in the 4.2.1.2 Complex Terrain 51—Summaries of Preferred Air Quality application of air quality models for 4.2.2 Refined Analytical Techniques Models regulatory purposes. In the 1977 Clean Air 5.0 Models for Ozone, Particulate Matter, Act, Congress mandated such consistency LIST OF TABLES and encouraged the standardization of model Carbon Monoxide, Nitrogen Dioxide, and applications. The Guideline on Air Quality Lead Table No. Title Models (hereafter, Guideline) was first 5.1 Discussion published in April 1978 to satisfy these 5.2 Recommendations 4–1a ...... Neutral/Stable Meteorological requirements by specifying models and 5.2.1 Models for Ozone Matrix for CTSCREEN. providing guidance for their use. The 5.2.2 Models for Particulate Matter 4–1b ...... Unstable/Convective Meteoro­ Guideline provides a common basis for 5.2.2.1 PM–2.5 logical Matrix for estimating the air quality concentrations of 5.2.2.2 PM–10 CTSCREEN. criteria pollutants used in assessing control 5.2.3 Models for Carbon Monoxide strategies and developing emission limits. 5.2.4 Models for Nitrogen Dioxide 8–1 ...... Model Emission Input Data for b. The continuing development of new air (Annual Average) Point Sources. quality models in response to regulatory 5.2.5 Models for Lead 8–2 ...... Point Source Model Emission Input Data for NAAQS Com­ requirements and the expanded requirements 6.0 Other Model Requirements for models to cover even more complex pliance in PSD Demonstra­ problems have emphasized the need for 6.1 Discussion tions. periodic review and update of guidance on 6.2 Recommendations 8–3 ...... Averaging Times for Site Spe­ these techniques. Historically, three primary 6.2.1 Visibility cific Wind and Turbulence activities have provided direct input to 6.2.2 Good Engineering Practice Stack Measurements. revisions of the Guideline. The first is a series Height of annual EPA workshops conducted for the 6.2.3 Long Range Transport (LRT) (i.e., 1.0 Introduction beyond 50 km) purpose of ensuring consistency and a. The Guideline recommends air quality providing clarification in the application of 6.2.4 Modeling Guidance for Other Governmental Programs modeling techniques that should be applied models. The second activity was the to State Implementation Plan (SIP) revisions solicitation and review of new models from 7.0 General Modeling Considerations for existing sources and to new source the technical and user community. In the 7.1 Discussion reviews (NSR), including prevention of March 27, 1980 Federal Register, a procedure 7.2 Recommendations significant deterioration (PSD).123 was outlined for the submittal to EPA of 7.2.1 Design Concentrations Applicable only to criteria air pollutants, it privately developed models. After extensive 7.2.2 Critical Receptor Sites is intended for use by EPA Regional Offices evaluation and scientific review, these 7.2.3 Dispersion Coefficients in judging the adequacy of modeling analyses models, as well as those made available by 7.2.4 Stability Categories performed by EPA, State and local agencies EPA, have been considered for recognition in 7.2.5 Plume Rise and by industry. The guidance is appropriate the Guideline. The third activity is the 7.2.6 Chemical Transformation for use by other Federal agencies and by State extensive on-going research efforts by EPA 7.2.7 Gravitational Settling and agencies with air quality and land and others in air quality and meteorological Deposition management responsibilities. The Guideline modeling. 7.2.8 Complex Winds serves to identify, for all interested parties, c. Based primarily on these three activities, 7.2.9 Calibration of Models new sections and topics have been included those techniques and data bases EPA as needed. EPA does not make changes to the 8.0 Model Input Data considers acceptable. The Guideline is not guidance on a predetermined schedule, but 8.1 Source Data intended to be a compendium of modeling rather on an as-needed basis. EPA believes 8.1.1 Discussion techniques. Rather, it should serve as a that revisions of the Guideline should be 8.1.2 Recommendations common measure of acceptable technical timely and responsive to user needs and 8.2 Background Concentrations analysis when supported by sound scientific should involve public participation to the 8.2.1 Discussion judgment. greatest possible extent. All future changes to 8.2.2 Recommendations (Isolated Single b. Due to limitations in the spatial and the guidance will be proposed and finalized Source) temporal coverage of air quality in the Federal Register. Information on the 8.2.3 Recommendations (Multi-Source measurements, monitoring data normally are current status of modeling guidance can Areas) not sufficient as the sole basis for always be obtained from EPA’s Regional 8.3 Meteorological Input Data demonstrating the adequacy of emission Offices. 8.3.1 Length of Record of Meteorological limits for existing sources. Also, the impacts Data of new sources that do not yet exist can only Table of Contents 8.3.2 National Weather Service Data be determined through modeling. Thus, List of Tables 8.3.3 Site Specific Data models, while uniquely filling one program 8.3.4 Treatment of Near-calms and Calms need, have become a primary analytical tool 1.0 Introduction 9.0 Accuracy and Uncertainty of Models in most air quality assessments. Air quality 2.0 Overview of Model Use measurements can be used in a 9.1 Discussion complementary manner to dispersion 2.1 Suitability of Models 9.1.1 Overview of Model Uncertainty models, with due regard for the strengths and 2.2 Levels of Sophistication of Models 9.1.2 Studies of Model Accuracy weaknesses of both analysis techniques. 2.3 Availability of Models 9.1.3 Use of Uncertainty in Decision- Measurements are particularly useful in 3.0 Recommended Air Quality Models Making assessing the accuracy of model estimates. 9.1.4 Evaluation of Models The use of air quality measurements alone 3.1 Preferred Modeling Techniques 9.2 Recommendations 3.1.1 Discussion however could be preferable, as detailed in 3.1.2 Recommendations 10.0 Regulatory Application of Models a later section of this document, when 3.2 Use of Alternative Models 10.1 Discussion models are found to be unacceptable and 3.2.1 Discussion 10.2 Recommendations monitoring data with sufficient spatial and 3.2.2 Recommendations 10.2.1 Analysis Requirements temporal coverage are available. 3.3 Availability of Supplementary Modeling 10.2.2 Use of Measured Data in Lieu of c. It would be advantageous to categorize Guidance Model Estimates the various regulatory programs and to apply

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a designated model to each proposed source promote the use of more accurate air quality inventory, meteorological data, and air needing analysis under a given program. models and data bases. The workshops serve quality data. Appropriate data should be However, the diversity of the nation’s to provide further explanations of Guideline available before any attempt is made to apply topography and climate, and variations in requirements to the Regional Offices and a model. A model that requires detailed, source configurations and operating workshop reports are issued with this precise, input data should not be used when characteristics dictate against a strict clarifying information. In addition, findings such data are unavailable. However, modeling ‘‘cookbook’’. There is no one model from ongoing research programs, new model assuming the data are adequate, the greater capable of properly addressing all development, or results from model the detail with which a model considers the conceivable situations even within a broad evaluations and applications are spatial and temporal variations in emissions category such as point sources. continuously evaluated. Based on this and meteorological conditions, the greater Meteorological phenomena associated with information changes in the guidance may be the ability to evaluate the source impact and threats to air quality standards are rarely indicated. to distinguish the effects of various control amenable to a single mathematical treatment; g. All changes to the Guideline must follow strategies. thus, case-by-case analysis and judgment are rulemaking requirements since the Guideline b. Air quality models have been applied frequently required. As modeling efforts is codified in Appendix W of Part 51. EPA with the most accuracy, or the least degree become more complex, it is increasingly will promulgate proposed and final rules in of uncertainty, to simulations of long term important that they be directed by highly the Federal Register to amend this averages in areas with relatively simple competent individuals with a broad range of Appendix. Ample opportunity for public topography. Areas subject to major experience and knowledge in air quality comment will be provided for each proposed topographic influences experience meteorology. Further, they should be change and public hearings scheduled if meteorological complexities that are coordinated closely with specialists in requested. extremely difficult to simulate. Although emissions characteristics, air monitoring and h. A wide range of topics on modeling and models are available for such circumstances, data processing. The judgment of data bases are discussed in the Guideline. they are frequently site specific and resource experienced meteorologists and analysts is Section 2 gives an overview of models and intensive. In the absence of a model capable essential. their appropriate use. Section 3 provides of simulating such complexities, only a d. The model that most accurately specific guidance on the use of ‘‘preferred’’ preliminary approximation may be feasible estimates concentrations in the area of air quality models and on the selection of until such time as better models and data interest is always sought. However, it is clear alternative techniques. Sections 4 through 7 bases become available. from the needs expressed by the States and provide recommendations on modeling c. Models are highly specialized tools. EPA Regional Offices, by many industries techniques for application to simple-terrain Competent and experienced personnel are an and trade associations, and also by the stationary source problems, complex terrain essential prerequisite to the successful deliberations of Congress, that consistency in problems, and mobile source problems. application of simulation models. The need the selection and application of models and Specific modeling requirements for selected for specialists is critical when the more data bases should also be sought, even in regulatory issues are also addressed. Section sophisticated models are used or the area case-by-case analyses. Consistency ensures 8 discusses issues common to many being investigated has complicated that air quality control agencies and the modeling analyses, including acceptable meteorological or topographic features. A general public have a common basis for model components. Section 9 makes model applied improperly, or with estimating pollutant concentrations, recommendations for data inputs to models inappropriate data, can lead to serious assessing control strategies and specifying including source, meteorological and misjudgements regarding the source impact emission limits. Such consistency is not, background air quality data. Section 10 or the effectiveness of a control strategy. however, promoted at the expense of model covers the uncertainty in model estimates d. The resource demands generated by use and data base accuracy. The Guideline and how that information can be useful to the of air quality models vary widely depending provides a consistent basis for selection of regulatory decision-maker. The last chapter on the specific application. The resources the most accurate models and data bases for summarizes how estimates and required depend on the nature of the model use in air quality assessments. measurements of air quality are used in and its complexity, the detail of the data e. Recommendations are made in the assessing source impact and in evaluating base, the difficulty of the application, and the Guideline concerning air quality models, data control strategies. amount and level of expertise required. The bases, requirements for concentration i. Appendix W to 40 CFR Part 51 itself costs of manpower and computational estimates, the use of measured data in lieu contains an appendix: Appendix A. Thus, facilities may also be important factors in the of model estimates, and model evaluation when reference is made to ‘‘Appendix A’’ in selection and use of a model for a specific procedures. Models are identified for some this document, it refers to Appendix A to analysis. However, it should be recognized specific applications. The guidance provided Appendix W to 40 CFR Part 51. Appendix A that under some sets of physical here should be followed in air quality contains summaries of refined air quality circumstances and accuracy requirements, no analyses relative to State Implementation models that are ‘‘preferred’’ for specific present model may be appropriate. Thus, Plans and in supporting analyses required by applications; both EPA models and models consideration of these factors should lead to EPA, State and local agency air programs. developed by others are included. selection of an appropriate model. EPA may approve the use of another technique that can be demonstrated to be 2.0 Overview of Model Use 2.2 Levels of Sophistication of Models more appropriate than those recommended a. Before attempting to implement the a. There are two levels of sophistication of in this guide. This is discussed at greater guidance contained in this document, the models. The first level consists of relatively length in Section 3. In all cases, the model reader should be aware of certain general simple estimation techniques that generally applied to a given situation should be the one information concerning air quality models use preset, worst-case meteorological that provides the most accurate and their use. Such information is provided conditions to provide conservative estimates representation of atmospheric transport, in this section. of the air quality impact of a specific source, dispersion, and chemical transformations in or source category. These are called screening the area of interest. However, to ensure 2.1 Suitability of Models techniques or screening models. The purpose consistency, deviations from this guide a. The extent to which a specific air quality of such techniques is to eliminate the need should be carefully documented and fully model is suitable for the evaluation of source of more detailed modeling for those sources supported. impact depends upon several factors. These that clearly will not cause or contribute to f. From time to time situations arise include: (1) The meteorological and ambient concentrations in excess of either requiring clarification of the intent of the topographic complexities of the area; (2) the the National Ambient Air Quality Standards guidance on a specific topic. Periodic level of detail and accuracy needed for the (NAAQS) 4 or the allowable prevention of workshops are held with the headquarters, analysis; (3) the technical competence of significant deterioration (PSD) concentration Regional Office, State, and local agency those undertaking such simulation modeling; increments.23 If a screening technique modeling representatives to ensure (4) the resources available; and (5) the detail indicates that the concentration contributed consistency in modeling guidance and to and accuracy of the data base, i.e., emissions by the source exceeds the PSD increment or

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the increment remaining to just meet the appropriate reviewing authority, you should i. The model must be written in a common NAAQS, then the second level of more contact the Regional modeling contact programming language, and the executable(s) sophisticated models should be applied. (http://www.epa.gov/scram001/ must run on a common computer platform. b. The second level consists of those tt28.htm#regionalmodelingcontacts) in the ii. The model must be documented in a analytical techniques that provide more appropriate EPA Regional Office, whose user’s guide which identifies the detailed treatment of physical and chemical jurisdiction generally includes the physical mathematics of the model, data requirements atmospheric processes, require more detailed location of the source in question and its and program operating characteristics at a and precise input data, and provide more expected impacts. level of detail comparable to that available specialized concentration estimates. As a c. In all regulatory analyses, especially if for other recommended models in Appendix result they provide a more refined and, at other-than-preferred models are selected for A. least theoretically, a more accurate estimate use, early discussions among Regional Office iii. The model must be accompanied by a of source impact and the effectiveness of staff, State and local control agencies, complete test data set including input control strategies. These are referred to as industry representatives, and where parameters and output results. The test data refined models. appropriate, the Federal Land Manager, are must be packaged with the model in c. The use of screening techniques invaluable and are encouraged. Agreement computer-readable form. followed, as appropriate, by a more refined on the data base(s) to be used, modeling iv. The model must be useful to typical analysis is always desirable. However there techniques to be applied and the overall users, e.g., State air pollution control are situations where the screening techniques technical approach, prior to the actual agencies, for specific air quality control are practically and technically the only analyses, helps avoid misunderstandings problems. Such users should be able to viable option for estimating source impact. In concerning the final results and may reduce operate the computer program(s) from such cases, an attempt should be made to the later need for additional analyses. The available documentation. acquire or improve the necessary data bases use of an air quality analysis checklist, such v. The model documentation must include and to develop appropriate analytical as is posted on EPA’s Internet SCRAM Web a comparison with air quality data (and/or techniques. site (subsection 2.3), and the preparation of tracer measurements) or with other well- a written protocol help to keep established analytical techniques. 2.3 Availability of Models misunderstandings at a minimum. vi. The developer must be willing to make a. For most of the screening and refined d. It should not be construed that the the model and source code available to users models discussed in the Guideline, codes, preferred models identified here are to be at reasonable cost or make them available for associated documentation and other useful permanently used to the exclusion of all public access through the Internet or information are available for download from others or that they are the only models National Technical Information Service: The EPA’s Support Center for Regulatory Air available for relating emissions to air quality. model and its code cannot be proprietary. Modeling (SCRAM) Internet Web site at The model that most accurately estimates c. The evaluation process includes a http://www.epa.gov/scram001. A list of concentrations in the area of interest is determination of technical merit, in alternate models that can be used with case- always sought. However, designation of accordance with the above six items by-case justification (subsection 3.2) and an specific models is needed to promote including the practicality of the model for example air quality analysis checklist are consistency in model selection and use in ongoing regulatory programs. Each also posted on this Web site. This is a site application. model will also be subjected to a with which modelers should become e. The 1980 solicitation of new or different performance evaluation for an appropriate 6 familiar. models from the technical community and data base and to a peer scientific review. the program whereby these models were Models for wide use (not just an isolated 3.0 Recommended Air Quality Models evaluated, established a means by which new case) that are found to perform better will be a. This section recommends the approach models are identified, reviewed and made proposed for inclusion as preferred models in to be taken in determining refined modeling available in the Guideline. There is a pressing future Guideline revisions. techniques for use in regulatory air quality need for the development of models for a d. No further evaluation of a preferred programs. The status of models developed by wide range of regulatory applications. model is required for a particular application EPA, as well as those submitted to EPA for Refined models that more realistically if the EPA recommendations for regulatory review and possible inclusion in this simulate the physical and chemical process use specified for the model in the Guideline guidance, is discussed. The section also in the atmosphere and that more reliably are followed. Alternative models to those addresses the selection of models for estimate pollutant concentrations are needed. listed in Appendix A should generally be compared with measured air quality data individual cases and provides 3.1 Preferred Modeling Techniques recommendations for situations where the when they are used for regulatory preferred models are not applicable. Two 3.1.1 Discussion applications consistent with additional sources of modeling guidance are a. EPA has developed models suitable for recommendations in subsection 3.2. the Model Clearinghouse 5 and periodic regulatory application. Other models have 3.1.2 Recommendations Regional/State/Local Modelers workshops. been submitted by private developers for a. Appendix A identifies refined models b. In this guidance, when approval is possible inclusion in the Guideline. Refined that are preferred for use in regulatory required for a particular modeling technique models which are preferred and applications. If a model is required for a or analytical procedure, we often refer to the recommended by EPA have undergone particular application, the user should select ‘‘appropriate reviewing authority’’. In some evaluation exercises 78910 that include a model from that appendix. These models EPA regions, authority for NSR and PSD statistical measures of model performance in may be used without a formal demonstration permitting and related activities has been comparison with measured air quality data as of applicability as long as they are used as delegated to State and even local agencies. In suggested by the American Meteorological indicated in each model summary of these cases, such agencies are Society 11 and, where possible, peer scientific Appendix A. Further recommendations for ‘‘representatives’’ of the respective regions. reviews.12 13 14 the application of these models to specific Even in these circumstances, the Regional b. When a single model is found to perform source problems are found in subsequent Office retains the ultimate authority in better than others, it is recommended for sections of the Guideline. decisions and approvals. Therefore, as application as a preferred model and listed b. If changes are made to a preferred model discussed above and depending on the in Appendix A. If no one model is found to without affecting the concentration estimates, circumstances, the appropriate reviewing clearly perform better through the evaluation the preferred status of the model is authority may be the Regional Office, Federal exercise, then the preferred model listed in unchanged. Examples of modifications that Land Manager(s), State agency(ies), or Appendix A may be selected on the basis of do not affect concentrations are those made perhaps local agency(ies). In cases where other factors such as past use, public to enable use of a different computer review and approval comes solely from the familiarity, cost or resource requirements, platform or those that affect only the format Regional Office (sometimes stated as and availability. Accordingly, dispersion or averaging time of the model results. ‘‘Regional Administrator’’), this will be models listed in Appendix A meet these However, when any changes are made, the stipulated. If there is any question as to the conditions: Regional Administrator should require a test

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case example to demonstrate that the better for the given application than a workshops with headquarters, Regional concentration estimates are not affected. comparable model in Appendix A; or (3) if Office, State, and local agency modeling c. A preferred model should be operated the preferred model is less appropriate for representatives. with the options listed in Appendix A as the specific application, or there is no b. The Regional Office should always be ‘‘Recommendations for Regulatory Use.’’ If preferred model. Any one of these three consulted for information and guidance other options are exercised, the model is no separate conditions may make use of an concerning modeling methods and longer ‘‘preferred.’’ Any other modification to alternative model acceptable. Some known interpretations of modeling guidance, and to a preferred model that would result in a alternative models that are applicable for ensure that the air quality model user has change in the concentration estimates selected situations are listed on EPA’s available the latest most up-to-date policy likewise alters its status as a preferred model. SCRAM Internet Web site (subsection 2.3). and procedures. As appropriate, the Regional Use of the model must then be justified on However, inclusion there does not confer any Office may request assistance from the Model a case-by-case basis. unique status relative to other alternative Clearinghouse after an initial evaluation and models that are being or will be developed decision has been reached concerning the 3.2 Use of Alternative Models in the future. application of a model, analytical technique 3.2.1 Discussion c. Equivalency, condition (1) in paragraph or data base in a particular regulatory action. (b) of this subsection, is established by a. Selection of the best techniques for each 4.0 Traditional Stationary Source Models individual air quality analysis is always demonstrating that the maximum or highest, encouraged, but the selection should be done second highest concentrations are within 2 4.1 Discussion in a consistent manner. A simple listing of percent of the estimates obtained from the a. Guidance in this section applies to models in this Guideline cannot alone preferred model. The option to show modeling analyses for which the achieve that consistency nor can it equivalency is intended as a simple predominant meteorological conditions that necessarily provide the best model for all demonstration of acceptability for an control the design concentration are steady possible situations. An EPA reference 15 alternative model that is so nearly identical state and for which the transport distances provides a statistical technique for evaluating (or contains options that can make it are nominally 50km or less. The models model performance for predicting peak identical) to a preferred model that it can be recommended in this section are generally concentration values, as might be observed at treated for practical purposes as the preferred used in the air quality impact analysis of individual monitoring locations. This model. Two percent was selected as the basis stationary sources for most criteria protocol is available to assist in developing for equivalency since it is a rough pollutants. The averaging time of the a consistent approach when justifying the use approximation of the fraction that PSD Class concentration estimates produced by these of other-than-preferred modeling techniques I increments are of the NAAQS for SO2, i.e., models ranges from 1 hour to an annual recommended in the Guideline. The the difference in concentrations that is average. procedures in this protocol provide a general judged to be significant. However, b. Simple terrain, as used here, is framework for objective decision-making on notwithstanding this demonstration, models considered to be an area where terrain the acceptability of an alternative model for that are not equivalent may be used when features are all lower in elevation than the a given regulatory application. These one of the two other conditions described in top of the stack of the source(s) in question. objective procedures may be used for paragraphs (d) and (e) of this subsection are Complex terrain is defined as terrain conducting both the technical evaluation of satisfied. exceeding the height of the stack being the model and the field test or performance d. For condition (2) in paragraph (b) of this modeled. evaluation. An ASTM reference 16 provides a subsection, established procedures and c. In the early 1980s, model evaluation general philosophy for developing and techniques 15 16 for determining the exercises were conducted to determine the implementing advanced statistical acceptability of a model for an individual ‘‘best, most appropriate point source model’’ evaluations of atmospheric dispersion case based on superior performance should for use in simple terrain.12 No one model was models, and provides an example statistical be followed, as appropriate. Preparation and found to be clearly superior and, based on technique to illustrate the application of this implementation of an evaluation protocol past use, public familiarity, and availability, philosophy. which is acceptable to both control agencies ISC (predecessor to ISC3 17) became the b. This section discusses the use of and regulated industry is an important recommended model for a wide range of alternate modeling techniques and defines element in such an evaluation. regulatory applications. Other refined models three situations when alternative models may e. Finally, for condition (3) in paragraph (b) which also employed the same basic be used. of this subsection, an alternative refined Gaussian kernel as in ISC, i.e., BLP, CALINE3 model may be used provided that: and OCD, were developed for specialized 3.2.2 Recommendations i. The model has received a scientific peer applications (Appendix A). Performance a. Determination of acceptability of a review; evaluations were also made for these models, model is a Regional Office responsibility. ii. The model can be demonstrated to be which are identified below. Where the Regional Administrator finds that applicable to the problem on a theoretical d. Encouraged by the development of an alternative model is more appropriate basis; pragmatic methods for better characterization than a preferred model, that model may be iii. The data bases which are necessary to of plume dispersion 18 19 20 21 the AMS/EPA used subject to the recommendations of this perform the analysis are available and Regulatory Model Improvement Committee subsection. This finding will normally result adequate; (AERMIC) developed AERMOD.22 AERMOD from a determination that (1) a preferred air iv. Appropriate performance evaluations of employs best state-of-practice quality model is not appropriate for the the model have shown that the model is not parameterizations for characterizing the particular application; or (2) a more biased toward underestimates; and meteorological influences and dispersion. appropriate model or analytical procedure is v. A protocol on methods and procedures The model utilizes a probability density available and applicable. to be followed has been established. function (pdf) and the superposition of b. An alternative model should be several Gaussian plumes to characterize the evaluated from both a theoretical and a 3.3 Availability of Supplementary Modeling distinctly non-Gaussian nature of the vertical performance perspective before it is selected Guidance pollutant distribution for elevated plumes for use. There are three separate conditions a. The Regional Administrator has the during convective conditions; otherwise the under which such a model may normally be authority to select models that are distribution is Gaussian. Also, nighttime approved for use: (1) If a demonstration can appropriate for use in a given situation. urban boundary layers (and plumes within be made that the model produces However, there is a need for assistance and them) have the turbulence enhanced by concentration estimates equivalent to the guidance in the selection process so that AERMOD to simulate the influence of the estimates obtained using a preferred model; fairness and consistency in modeling urban heat island. AERMOD has been (2) if a statistical performance evaluation has decisions is fostered among the various evaluated using a variety of data sets and has been conducted using measured air quality Regional Offices and the States. To satisfy been found to perform better than ISC3 for data and the results of that evaluation that need, EPA established the Model many applications, and as well or better than indicate the alternative model performs Clearinghouse 5 and also holds periodic CTDMPLUS for several complex terrain data

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sets (Section A.1; subsection n). The current height, and wind directions for both neutral/ the terrain both as a single feature and as version of AERMOD has been modified to stable conditions and unstable convective multiple hills to determine design include an algorithm for dry and wet conditions. Table 4–1 contains the matrix of concentrations. deposition for both gases and particles. Note meteorological variables that is used for each d. Other screening techniques 17 25 29 may that when deposition is invoked, mass in the CTSCREEN analysis. There are 96 be acceptable for complex terrain cases plume is depleted. Availability of this combinations, including exceptions, for each where established procedures are used. The version is described in Section A.1, and is wind direction for the neutral/stable case, user is encouraged to confer with the subject to applicable guidance published in and 108 combinations for the unstable case. appropriate reviewing authority if any the Guideline. The specification of wind direction, however, unresolvable problems are encountered, e.g., 23 e. A new building downwash algorithm is handled internally, based on the source applicability, meteorological data, receptor was developed and tested within AERMOD. and terrain geometry. Although CTSCREEN siting, or terrain contour processing issues. The PRIME algorithm has been evaluated is designed to address a single source using a variety of data sets and has been scenario, there are a number of options that 4.2.2 Refined Analytical Techniques found to perform better than the downwash can be selected on a case-by-case basis to a. A brief description of each preferred algorithm that is in ISC3, and has been address multi-source situations. However, model for refined applications is found in shown to perform acceptably in tests within the appropriate reviewing authority should Appendix A. Also listed in that appendix are AERMOD (Section A.1; subsection n). be consulted, and concurrence obtained, on availability, the model input requirements, the protocol for modeling multiple sources 4.2 Recommendations the standard options that should be selected with CTSCREEN to ensure that the worst case when running the program, and output 4.2.1 Screening Techniques is identified and assessed. The maximum options. 4.2.1.1 Simple Terrain concentration output from CTSCREEN b. For a wide range of regulatory represents a worst-case 1-hour concentration. a. Where a preliminary or conservative applications in all types of terrain, the Time-scaling factors of 0.7 for 3-hour, 0.15 recommended model is AERMOD. This estimate is desired, point source screening for 24-hour and 0.03 for annual concentration techniques are an acceptable approach to air recommendation is based on extensive averages are applied internally by developmental and performance evaluation quality analyses. EPA has published CTSCREEN to the highest 1-hour 24 25 (Section A.1; subsection n). Differentiation of guidance for screening procedures. concentration calculated by the model. simple versus complex terrain is unnecessary b. All screening procedures should be b. Placement of receptors requires very with AERMOD. In complex terrain, AERMOD adjusted to the site and problem at hand. careful attention when modeling in complex Close attention should be paid to whether the terrain. Often the highest concentrations are employs the well-known dividing-streamline area should be classified urban or rural in predicted to occur under very stable concept in a simplified simulation of the accordance with Section 7.2.3. The conditions, when the plume is near, or effects of plume-terrain interactions. climatology of the area should be studied to impinges on, the terrain. The plume under c. If aerodynamic building downwash is help define the worst-case meteorological such conditions may be quite narrow in the important for the modeling analysis, e.g., conditions. Agreement should be reached vertical, so that even relatively small changes paragraph 6.2.2(b), then the recommended between the model user and the appropriate in a receptor’s location may substantially model is AERMOD. The state-of-the-science reviewing authority on the choice of the affect the predicted concentration. Receptors for modeling atmospheric deposition is screening model for each analysis, and on the within about a kilometer of the source may evolving and the best techniques are input data as well as the ultimate use of the be even more sensitive to location. Thus, a currently being assessed and their results are results. dense array of receptors may be required in being compared with observations. 4.2.1.2 Complex Terrain some cases. In order to avoid excessively Consequently, while deposition treatment is available in AERMOD, the approach taken for a. CTSCREEN 26 can be used to obtain large computer runs due to such a large array conservative, yet realistic, worst-case of receptors, it is often desirable to model the any purpose should be coordinated with the estimates for receptors located on terrain area twice. The first model run would use a appropriate reviewing authority. Line sources above stack height. CTSCREEN accounts for moderate number of receptors carefully can be simulated with AERMOD if point or the three-dimensional nature of plume and located over the area of interest. The second volume sources are appropriately combined. terrain interaction and requires detailed model run would use a more dense array of If buoyant plume rise from line sources is terrain data representative of the modeling receptors in areas showing potential for high important for the modeling analysis, the domain. The model description and user’s concentrations, as indicated by the results of recommended model is BLP. For other instructions are contained in the user’s the first model run. special modeling applications, CALINE3 (or guide.26 The terrain data must be digitized in c. As mentioned above, digitized contour CAL3QHCR on a case-by-case basis), OCD, the same manner as for CTDMPLUS and a data must be preprocessed 27 to provide hill and EDMS are available as described in terrain processor is available.27 A discussion shape parameters in suitable input format. Sections 5 and 6. of the model’s performance characteristics is The user then supplies receptors either d. If the modeling application involves a provided in a technical paper.28 CTSCREEN through an interactive program that is part of well defined hill or ridge and a detailed is designed to execute a fixed matrix of the model or directly, by using a text editor; dispersion analysis of the spatial pattern of meteorological values for wind speed (u), using both methods to select receptors will plume impacts is of interest, CTDMPLUS, standard deviation of horizontal and vertical generally be necessary to assure that the listed in Appendix A, is available. wind speeds (sv, sw), vertical potential maximum concentrations are estimated by CDTMPLUS provides greater resolution of temperature gradient (dq/dz), friction either model. In cases where a terrain feature concentrations about the contour of the hill velocity (u*), Monin-Obukhov length (L), may ‘‘appear to the plume’’ as smaller, feature than does AERMOD through a mixing height (zi) as a function of terrain multiple hills, it may be necessary to model different plume-terrain interaction algorithm.

TABLE 4–1A.—NEUTRAL/STABLE METEOROLOGICAL MATRIX FOR CTSCREEN

Variable Specific values

U (m/s) ...... 1 .0 2 .0 3 .0 4 .0 5.0 sv (m/s) ...... 0 .3 0 .75 sw (m/s) ...... 0.08 0.15 0 .30 0.75 Dq/Dz (K/m) ...... 0.01 0.02 0 .035 WD ...... (Wind direction is optimized internally for each meteorological combination.)

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Exceptions: (2) If sw = 0.75 m/s and U ≥ 3.0 m/s, then (4) sw ≤ sv ≤ (1) If U ≤ 2 m/s and sv ≤ 0.3 m/s, then include Dq/Dz is limited to 0.01 K/m. sw = 0.04 m/s. (3) If U ≥ 4 m/s, then sw ≥ 0.15 m/s.

TABLE 4–1B.—UNSTABLE/CONVECTIVE METEOROLOGICAL MATRIX FOR CTSCREEN

Variable Specific values

U (m/s) ...... 1 .0 2 .0 3 .0 4.0 5.0 U* (m/s) ...... 0.1 0.3 0.5 L (m) ...... ¥10 ¥50 ¥90 Dq/Dz (K/m) ...... 0.030 (potential temperature gradient above Zi) Zi (m) ...... 0 .5h 1.0h 1.5h (h = terrain height)

5.0 Models for Ozone, Particulate Matter, transport and dispersion of ozone and its geographical coverage for a modeling Carbon Monoxide, Nitrogen Dioxide, and precursors. Other approaches, such as application.33 Lead Lagrangian or observational models may be g. The NAAQS for PM–10 was used to guide choice of appropriate strategies promulgated in July 1987 (40 CFR 50.6). A 5.1 Discussion to consider with a photochemical grid model. SIP development guide 34 is available to a. This section identifies modeling These other approaches may be sufficient to assist in PM–10 analyses and control strategy approaches or models appropriate for address ozone in an area where observed development. EPA promulgated regulations a addressing ozone (O3) , carbon monoxide concentrations are near the NAAQS or only for PSD increments measured as PM–10 in a (CO), nitrogen dioxide (NO2), particulates slightly above it. Such a decision needs to be notice published on June 3, 1993 (40 CFR (PM–2.5 a and PM–10), and lead. These made on a case-by-case basis in concert with 51.166(c)). As an aid to assessing the impact pollutants are often associated with the Regional Office. on ambient air quality of particulate matter emissions from numerous sources. Generally, d. A control agency with jurisdiction over generated from prescribed burning activities, mobile sources contribute significantly to one or more areas with significant ozone a reference 35 is available. emissions of these pollutants or their problems should review available ambient air h. Models for assessing the impacts of precursors. For cases where it is of interest quality data to assess whether the problem is particulate matter may involve dispersion to estimate concentrations of CO or NO2 near likely to be significantly impacted by models or receptor models, or a combination a single or small group of stationary sources, regional transport.32 Choice of a modeling (depending on the circumstances). Receptor refer to Section 4. (Modeling approaches for approach depends on the outcome of this models focus on the behavior of the ambient SO2 are discussed in Section 4.) review. In cases where transport is environment at the point of impact as b. Several of the pollutants mentioned in considered significant, use of a nested opposed to source-oriented dispersion the preceding paragraph are closely related to regional model may be the preferred models, which focus on the transport, each other in that they share common approach. If the observed problem is believed diffusion, and transformation that begin at sources of emissions and/or are subject to to be primarily of local origin, use of a model the source and continue to the receptor site. chemical transformations of similar with a single horizontal grid resolution and Receptor models attempt to identify and precursors.30 31 For example, strategies geographical coverage that is less than that of apportion sources by relating known sample designed to reduce ozone could have an a regional model may suffice. compositions at receptors to measured or effect on the secondary component of PM–2.5 e. The fine particulate matter NAAQS, inferred compositions of source emissions. and vice versa. Thus, it makes sense to use promulgated on July 18, 1997, includes When complete and accurate emission models which take into account the chemical particles with an aerodynamic diameter inventories or meteorological coupling between O3 and PM–2.5, when nominally less than or equal to 2.5 characterization are unavailable, or unknown feasible. This should promote consistency micrometers (PM–2.5). Models for PM–2.5 pollutant sources exist, receptor modeling among methods used to evaluate strategies are needed to assess adequacy of a proposed may be necessary. for reducing different pollutants as well as strategy for meeting annual and/or 24-hour i. Models for assessing the impact of CO consistency among the strategies themselves. NAAQS for PM–2.5. PM–2.5 is a mixture emissions are needed for a number of Regulatory requirements for the different consisting of several diverse components. different purposes. Examples include pollutants are likely to be due at different Because chemical/physical properties and evaluating effects of point sources, congested times. Thus, the following paragraphs origins of each component differ, it may be intersections and highways, as well as the identify appropriate modeling approaches for appropriate to use either a single model cumulative effect of numerous sources of CO pollutants individually. capable of addressing several of the in an urban area. c. The NAAQS for ozone was revised on important components or to model primary j. Models for assessing the impact of July 18, 1997 and is now based on an 8-hour and secondary components using different sources on ambient NO2 concentrations are averaging period. Models for ozone are models. Effects of a control strategy on PM– primarily needed to meet new source review needed primarily to guide choice of strategies 2.5 is estimated from the sum of the effects requirements, such as addressing the effect of to correct an observed ozone problem in an on the components composing PM–2.5. a proposed source on PSD increments for area not attaining the NAAQS for ozone. Use Model users may refer to guidance 33 for annual concentrations of NO . Impact of an of photochemical grid models is the 2 further details concerning appropriate individual source on ambient NO2 depends, recommended means for identifying modeling approaches. in part, on the chemical environment into strategies needed to correct high ozone f. A control agency with jurisdiction over which the source’s plume is to be emitted. concentrations in such areas. Such models one or more areas with PM–2.5 problems There are several approaches for estimating need to consider emissions of volatile organic should review available ambient air quality effects of an individual source on ambient compounds (VOC), nitrogen oxides (NO ) X data to assess which components of PM–2.5 NO . One approach is through use of a and carbon monoxide (CO), as well as means 2 are likely to be major contributors to the plume-in-grid algorithm imbedded within a for generating meteorological data governing problem. If it is determined that regional photochemical grid model. However, because transport of secondary particulates, such as of the rigor and complexity involved, and a Modeling for attainment demonstrations for O3 sulfates or nitrates, is likely to contribute because this approach may not be capable of and PM–2.5 should be conducted in time to meet significantly to the problem, use of a regional defining sub-grid concentration gradients, the required SIP submission dates as provided for in the respective implementation rules. Information on model may be the preferred approach. plume-in-grid approach may be impractical implementation of the 8-hr O3 and PM–2.5 Otherwise, coverage may be limited to a for estimating effects on an annual PSD standards is available at: http://www.epa.gov/ttn/ domain that is urban scale or less. Special increment. A second approach which does naags/. care should be taken to select appropriate not have this limitation and accommodates

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distance-dependent conversion ratios—the a highly complex and resource-intensive should be approved by the Regional Office on Plume Volume Molar Ratio Method exercise. Control agencies with jurisdiction a case-by-case basis. Analyses involving (PVMRM) 36—is currently being tested to over areas with secondary PM–2.5 problems model calculations for stagnation conditions determine suitability as a refined method. A are encouraged to use models which integrate should also be justified on a case-by-case third (screening) approach is to develop site chemical and physical processes important basis (subsection 7.2.8). specific (domain-wide) conversion factors in the formation, decay and transport of these e. Fugitive dust usually refers to dust put 38 based on measurements. If it is not possible species (e.g., Models-3/CMAQ or into the atmosphere by the wind blowing 41 to develop site specific conversion factors REMSAD ). Primary components can be over plowed fields, dirt roads or desert or and use of the plume-in-grid algorithm is also simulated using less resource-intensive sandy areas with little or no vegetation. techniques. Suitability of a modeling not feasible, other screening procedures may Reentrained dust is that which is put into the be considered. approach or mix of modeling approaches for air by reason of vehicles driving over dirt k. In January 1999 (40 CFR Part 58, a given application requires technical roads (or dirty roads) and dusty areas. Such Appendix D), EPA gave notice that concern judgement,33 as well as professional sources can be characterized as line, area or about ambient lead impacts was being shifted experience in choice of models, use of the away from roadways and toward a focus on model(s) in an attainment test, development volume sources. Emission rates may be based stationary point sources. EPA has also issued of emissions and meteorological inputs to the on site specific data or values from the guidance on siting ambient monitors in the model and selection of days to model. general literature. Fugitive emissions include vicinity of such sources.37 For lead, the SIP b. Choice of Analysis Techniques to the emissions resulting from the industrial should contain an air quality analysis to Complement Air Quality Simulation Models. process that are not captured and vented determine the maximum quarterly lead Receptor models may be used to corroborate through a stack but may be released from concentration resulting from major lead point predictions obtained with one or more air various locations within the complex. In sources, such as smelters, gasoline additive quality simulation models. They may also be some unique cases a model developed plants, etc. General guidance for lead SIP potentially useful in helping to define specifically for the situation may be needed. development is also available.38 specific source categories contributing to Due to the difficult nature of characterizing major components of PM–2.5.33 and modeling fugitive dust and fugitive 5.2 Recommendations c. Estimating the Impact of Individual emissions, it is recommended that the 5.2.1 Models for Ozone Sources. Choice of methods used to assess proposed procedure be cleared by the a. Choice of Models for Multi-source the impact of an individual source depends Regional Office for each specific situation Applications. Simulation of ozone formation on the nature of the source and its emissions. before the modeling exercise is begun. Thus, model users should consult with the and transport is a highly complex and 5.2.3 Models for Carbon Monoxide resource intensive exercise. Control agencies Regional Office to determine the most with jurisdiction over areas with ozone suitable approach on a case-by-case basis a. Guidance is available for analyzing CO 48 problems are encouraged to use (subsection 3.2.2). impacts at roadway intersections. The photochemical grid models, such as the 5.2.2.2 PM–10 recommended screening model for such analyses is CAL3QHC.49 50 This model Models-3/Community Multi-scale Air a. Screening techniques like those Quality (CMAQ) modeling system,39 to combines CALINE3 (listed in Appendix A) identified in subsection 4.2.1 are applicable with a traffic model to calculate delays and evaluate the relationship between precursor to PM–10. Conservative assumptions which queues that occur at signalized intersections. species and ozone. Judgement on the do not allow removal or transformation are The screening approach is described in suitability of a model for a given application suggested for screening. Thus, it is reference 48; a refined approach may be should consider factors that include use of recommended that subjectively determined the model in an attainment test, development considered on a case-by-case basis with values for ‘‘half-life’’ or pollutant decay not 51 of emissions and meteorological inputs to the be used as a surrogate for particle removal. CAL3QHCR. The latest version of the 32 model and choice of episodes to model. Proportional models (rollback/forward) may MOBILE (mobile source emission factor) Similar models for the 8-hour NAAQS and not be applied for screening analysis, unless model should be used for emissions input to for the 1-hour NAAQS are appropriate. such techniques are used in conjunction with intersection models. b. Choice of Models to Complement receptor modeling.34 b. For analyses of highways characterized Photochemical Grid Models. As previously b. Refined models such as those discussed by uninterrupted traffic flows, CALINE3 is noted, observational models, Lagrangian in subsection 4.2.2 are recommended for recommended, with emissions input from the models, or the refined version of the Ozone PM–10. However, where possible, particle latest version of the MOBILE model. A 40 Isopleth Plotting Program (OZIPR) may be size, gas-to-particle formation, and their scientific review article for line source used to help guide choice of strategies to effect on ambient concentrations may be models is available.52 simulate with a photochemical grid model considered. For point sources of small c. For urban area wide analyses of CO, an and to corroborate results obtained with a particles and for source-specific analyses of Eulerian grid model should be used. grid model. Receptor models have also been complicated sources, use the appropriate Information on SIP development and used to apportion sources of ozone recommended steady-state plume dispersion requirements for using such models can be precursors (e.g., VOC) in urban domains. EPA model (subsection 4.2.2). found in several references.48 53 54 55 has issued guidance 32 in selecting c. Receptor models have proven useful for d. Where point sources of CO are of appropriate techniques. helping validate emission inventories and for concern, they should be treated using the c. Estimating the Impact of Individual corroborating source-specific impacts Sources. Choice of methods used to assess screening and refined techniques described estimated by dispersion models. The in Section 4. the impact of an individual source depends Chemical Mass Balance (CMB) model is on the nature of the source and its emissions. useful for apportioning impacts from 5.2.4 Models for Nitrogen Dioxide (Annual Thus, model users should consult with the localized sources.42 43 44 Other receptor Average) Regional Office to determine the most models, e.g., the Positive Matrix a. A tiered screening approach is suitable approach on a case-by-case basis Factorization (PMF) model 45 and Unmix,46 recommended to obtain annual average (subsection 3.2.2). which don’t share some of CMB’s constraints, estimates of NO2 from point sources for New 5.2.2 Models for Particulate Matter have also been applied. In regulatory Source Review analysis, including PSD, and applications, dispersion models have been for SIP planning purposes. This multi-tiered 5.2.2.1 PM–2.5 used in conjunction with receptor models to approach is conceptually shown in Figure 5– a. Choice of Models for Multi-source attribute source (or source category) 1 and described in paragraphs b through d of Applications. Simulation of phenomena contributions. Guidance is available for PM– this subsection: resulting in high ambient PM–2.5 can be a 10 sampling and analysis applicable to multi-faceted and complex problem resulting receptor modeling.47 Figure 5–1 from PM–2.5’s existence as an aerosol d. Under certain conditions, recommended Multi-tiered screening approach for mixture. Treating secondary components of dispersion models may not be reliable. In Estimating Annual NO2 Concentrations from PM–2.5, such as sulfates and nitrates, can be such circumstances, the modeling approach Point Sources

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b. For Tier 1 (the initial screen), use an located within the same distance of the square based on the portion of highway link appropriate model in subsection 4.2.2 to source as the source-to-monitor distance. within each grid square. If localized areas of estimate the maximum annual average e. In urban areas (subsection 7.2.3), a high concentrations are likely, then mobile concentration and assume a total conversion proportional model may be used as a sources should be modeled as line sources of NO to NO2. If the concentration exceeds preliminary assessment to evaluate control using an appropriate steady-state plume the NAAQS and/or PSD increments for NO2, strategies to meet the NAAQS for multiple dispersion model (e.g., CAL3QHCR; proceed to the 2nd level screen. minor sources, i.e., minor point, area and subsection 5.2.3). c. For Tier 2 (2nd level) screening analysis, mobile sources of NOX; concentrations g. More refined techniques to handle multiply the Tier 1 estimate(s) by an resulting from major point sources should be special circumstances may be considered on empirically derived NO2/NOX value of 0.75 estimated separately as discussed above, then a case-by-case basis and agreement with the (annual national default).56 The reviewing added to the impact of the minor sources. An appropriate reviewing authority (paragraph agency may establish an alternative default acceptable screening technique for urban 3.0(b)) should be obtained. Such techniques NO2/NOX ratio based on ambient annual complexes is to assume that all NOX is should consider individual quantities of NO average NO2 and annual average NOX data emitted in the form of NO2 and to use a and NO2 emissions, atmospheric transport representative of area wide quasi-equilibrium model from Appendix A for nonreactive and dispersion, and atmospheric conditions. Alternative default NO2/NOX pollutants to estimate NO2 concentrations. A transformation of NO to NO2. Where they are ratios should be based on data satisfying more accurate estimate can be obtained by: available, site specific data on the conversion quality assurance procedures that ensure data (1) Calculating the annual average of NO to NO2 may be used. Photochemical accuracy for both NO2 and NOX within the concentrations of NOX with an urban model, dispersion models, if used for other typical range of measured values. In areas and (2) converting these estimates to NO2 pollutants in the area, may also be applied with relatively low NOX concentrations, the concentrations using an empirically derived to the NOX problem. quality assurance procedures used to annual NO /NO ratio. A value of 0.75 is 2 X 5.2.5 Models for Lead determine compliance with the NO2 national recommended for this ratio. However, a ambient air quality standard may not be spatially averaged alternative default annual a. For major lead point sources, such as adequate. In addition, default NO2/NOX NO2/NOX ratio may be determined from an smelters, which contribute fugitive emissions ratios, including the 0.75 national default existing air quality monitoring network and and for which deposition is important, value, can underestimate long range NO2 used in lieu of the 0.75 value if it is professional judgement should be used, and impacts and should be used with caution in determined to be representative of prevailing there should be coordination with the long range transport scenarios. ratios in the urban area by the reviewing appropriate reviewing authority (paragraph d. For Tier 3 (3rd level) analysis, a detailed agency. To ensure use of appropriate locally 3.0(b)). To model an entire major urban area screening method may be selected on a case- derived annual average NO2/NOX ratios, or to model areas without significant sources by-case basis. For point source modeling, monitoring data under consideration should of lead emissions, as a minimum a detailed screening techniques such as the be limited to those collected at monitors proportional (rollback) model may be used Ozone Limiting Method 57 may also be meeting siting criteria defined in 40 CFR Part for air quality analysis. The rollback considered. Also, a site specific NO2/NOX 58, Appendix D as representative of philosophy assumes that measured pollutant ratio may be used as a detailed screening ‘‘neighborhood’’, ‘‘urban’’, or ‘‘regional’’ concentrations are proportional to emissions. method if it meets the same restrictions as scales. Furthermore, the highest annual However, urban or other dispersion models described for alternative default NO2/NOX spatially averaged NO2/NOX ratio from the are encouraged in these circumstances where ratios. Ambient NOX monitors used to most recent 3 years of complete data should the use of such models is feasible. develop a site specific ratio should be sited be used to foster conservatism in estimated b. In modeling the effect of traditional line to obtain the NO2 and NOX concentrations impacts. sources (such as a specific roadway or under quasi-equilibrium conditions. Data f. To demonstrate compliance with NO2 highway) on lead air quality, dispersion obtained from monitors sited at the PSD increments in urban areas, emissions models applied for other pollutants can be maximum NOX impact site, as may be from major and minor sources should be used. Dispersion models such as CALINE3 required in a PSD pre-construction included in the modeling analysis. Point and and CAL3QHCR have been used for modeling monitoring program, likely reflect area source emissions should be modeled as carbon monoxide emissions from highways transitional NOX conditions. Therefore, NOX discussed above. If mobile source emissions and intersections (subsection 5.2.3). Where data from maximum impact sites may not be do not contribute to localized areas of high there is a point source in the middle of a suitable for determining a site specific NO2/ ambient NO2 concentrations, they should be substantial road network, the lead NOX ratio that is applicable for the entire modeled as area sources. When modeled as concentrations that result from the road modeling analysis. A site specific ratio area sources, mobile source emissions should network should be treated as background derived from maximum impact data can only be assumed uniform over the entire highway (subsection 8.2); the point source and any be used to estimate NO2 impacts at receptors link and allocated to each area source grid nearby major roadways should be modeled

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separately using the appropriate no apparent bias toward over or under authority (paragraph 3.0(b)) and the affected recommended steady-state plume dispersion prediction, so long as the transport distance Federal Land Manager (FLM). FLMs are model (subsection 4.2.2). was limited to less than 300km.60 responsible for determining whether there is an adverse effect by a plume on a Class I area. 6.0 Other Model Requirements 6.2 Recommendations e. CALPUFF (Section A.3) may be applied 6.1 Discussion 6.2.1 Visibility when assessment is needed of reasonably attributable haze impairment or atmospheric a. This section covers those cases where a. Visibility in important natural areas (e.g., deposition due to one or a small group of specific techniques have been developed for Federal Class I areas) is protected under a sources. This situation may involve more special regulatory programs. Most of the number of provisions of the Clean Air Act, sources and larger modeling domains than programs have, or will have when fully including Sections 169A and 169B that to which VISCREEN ideally may be developed, separate guidance documents that (addressing impacts primarily from existing applied. The procedures and analyses should cover the program and a discussion of the sources) and Section 165 (new source be determined in consultation with the tools that are needed. The following review). Visibility impairment is caused by appropriate reviewing authority (paragraph paragraphs reference those guidance light scattering and light absorption 3.0(b)) and the affected FLM(s). documents, when they are available. No associated with particles and gases in the f. Regional scale models are used by EPA attempt has been made to provide a atmosphere. In most areas of the country, to develop and evaluate national policy and comprehensive discussion of each topic since light scattering by PM–2.5 is the most assist State and local control agencies. Two the reference documents were designed to do significant component of visibility such models which can be used to assess that. This section will undergo periodic impairment. The key components of PM–2.5 visibility impacts from source emissions are revision as new programs are added and new contributing to visibility impairment include Models-3/CMAQ 38 and REMSAD.41 Model techniques are developed. sulfates, nitrates, organic carbon, elemental users should consult with the appropriate b. Other Federal agencies have also carbon, and crustal material. reviewing authority (paragraph 3.0(b)), which developed specific modeling approaches for b. The visibility regulations as promulgated in this instance would include FLMs. their own regulatory or other requirements.58 in December 1980 (40 CFR 51.300–307) Although such regulatory requirements and require States to mitigate visibility 6.2.2 Good Engineering Practice Stack manuals may have come about because of impairment, in any of the 156 mandatory Height EPA rules or standards, the implementation Federal Class I areas, that is found to be a. The use of stack height credit in excess of such regulations and the use of the ‘‘reasonably attributable’’ to a single source of Good Engineering Practice (GEP) stack modeling techniques is under the jurisdiction or a small group of sources. In 1985, EPA height or credit resulting from any other of the agency issuing the manual or directive. promulgated Federal Implementation Plans dispersion technique is prohibited in the c. The need to estimate impacts at (FIPs) for several States without approved development of emission limitations by 40 distances greater than 50km (the nominal visibility provisions in their SIPs. The CFR 51.118 and 40 CFR 51.164. The distance to which EPA considers most IMPROVE (Interagency Monitoring for definitions of GEP stack height and steady-state Gaussian plume models are Protected Visual Environments) monitoring dispersion technique are contained in 40 CFR applicable) is an important one especially network, a cooperative effort between EPA, 51.100. Methods and procedures for making when considering the effects from secondary the States, and Federal land management the appropriate stack height calculations, pollutants. Unfortunately, models originally agencies, was established to implement the determining stack height credits and an available to EPA had not undergone monitoring requirements in these FIPs. Data example of applying those techniques are sufficient field evaluation to be has been collected by the IMPROVE network found in several references 64 65 66 67, which recommended for general use. Data bases since 1988. provide a great deal of additional information from field studies at mesoscale and long c. In 1999, EPA issued revisions to the for evaluating and describing building cavity range transport distances were limited in 1980 regulations to address visibility and wake effects. detail. This limitation was a result of the impairment in the form of regional haze, b. If stacks for new or existing major expense to perform the field studies required which is caused by numerous, diverse sources are found to be less than the height to verify and improve mesoscale and long sources (e.g., stationary, mobile, and area defined by EPA’s refined formula for range transport models. Meteorological data sources) located across a broad region (40 determining GEP height, then air quality adequate for generating three-dimensional CFR 51.308–309). The state of relevant impacts associated with cavity or wake wind fields were particularly sparse. scientific knowledge has expanded effects due to the nearby building structures Application of models to complicated terrain significantly since the Clean Air Act should be determined. The EPA refined compounds the difficulty of making good Amendments of 1977. A number of studies formula height is defined as H + 1.5L (see 61 62 assessments of long range transport impacts. and reports have concluded that long reference 66). Detailed downwash screening EPA completed limited evaluation of several range transport (e.g., up to hundreds of procedures 24 for both the cavity and wake long range transport (LRT) models against kilometers) of fine particulate matter plays a regions should be followed. If more refined two sets of field data and evaluated results.59 significant role in visibility impairment concentration estimates are required, the Based on the results, EPA concluded that across the country. Section 169A of the Act recommended steady-state plume dispersion long range and mesoscale transport models requires states to develop SIPs containing model in subsection 4.2.2 contains were limited for regulatory use to a case-by- long-term strategies for remedying existing algorithms for building wake calculations case basis. However a more recent series of and preventing future visibility impairment and should be used. comparisons has been completed for a new in 156 mandatory Class I federal areas. In model, CALPUFF (Section A.3). Several of order to develop long-term strategies to 6.2.3 Long Range Transport (LRT) (i.e., these field studies involved three-to-four address regional haze, many States will need Beyond 50km) hour releases of tracer gas sampled along arcs to conduct regional-scale modeling of fine a. Section 165(d) of the Clean Air Act of receptors at distances greater than 50km particulate concentrations and associated requires that suspected adverse impacts on downwind. In some cases, short-term visibility impairment (e.g., light extinction PSD Class I areas be determined. However, concentration sampling was available, such and deciview metrics). 50km is the useful distance to which most that the transport of the tracer puff as it d. To calculate the potential impact of a steady-state Gaussian plume models are passed the arc could be monitored. plume of specified emissions for specific considered accurate for setting emission Differences on the order of 10 to 20 degrees transport and dispersion conditions (‘‘plume limits. Since in many cases PSD analyses were found between the location of the blight’’), a screening model, VISCREEN, and show that Class I areas may be threatened at simulated and observed center of mass of the guidance are available.63 If a more distances greater than 50km from new tracer puff. Most of the simulated centerline comprehensive analysis is required, a refined sources, some procedure is needed to (1) concentration maxima along each arc were model should be selected . The model determine if an adverse impact will occur, within a factor of two of those observed. It selection (VISCREEN vs. PLUVUE II or some and (2) identify the model to be used in was concluded from these case studies that other refined model), procedures, and setting an emission limit if the Class I the CALPUFF dispersion model had analyses should be determined in increments are threatened. In addition to the performed in a reasonable manner, and had consultation with the appropriate reviewing situations just described, there are certain

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applications containing a mixture of both b. The Offshore and Coastal Dispersion increments. For the 24-hour PM–10 NAAQS long range and short range source-receptor (OCD) model, described in Appendix A, was (which is a probabilistic standard)—when relationships in a large modeled domain (e.g., developed by the Minerals Management multiple years are modeled, they collectively several industrialized areas located along a Service and is recommended for estimating represent a single period. Thus, if 5 years of river or valley). Historically, these air quality impact from offshore sources on NWS data are modeled, then the highest applications have presented considerable onshore, flat terrain areas. The OCD model is sixth highest concentration for the whole difficulty to an analyst if impacts from not recommended for use in air quality period becomes the design value. And in sources having transport distances greater impact assessments for onshore sources. general, when n years are modeled, the than 50km significantly contributed to the Sources located on or just inland of a (n+1)th highest concentration over the n-year design concentrations. To properly analyze shoreline where fumigation is expected period is the design value, since this applications of this type, a modeling should be treated in accordance with represents an average or expected exceedance approach is needed which has the capability subsection 7.2.8. rate of one per year. of combining, in a consistent manner, c. The latest version of the Emissions and c. When sufficient and representative data impacts involving both short and long range Dispersion Modeling System (EDMS), was exist for less than a 5-year period from a transport. The CALPUFF modeling system, developed and is supported by the Federal nearby NWS site, or when site specific data listed in Appendix A, has been designed to Aviation Administration (FAA), and is have been collected for less than a full accommodate both the Class I area LRT appropriate for air quality assessment of continuous year, or when it has been situation and the large modeling domain primary pollutant impacts at airports or air determined that the site specific data may not situation. Given the judgement and bases. EDMS has adopted AERMOD for be temporally representative (subsection refinement involved, conducting a LRT treating dispersion. Application of EDMS is 8.3.3), then the highest concentration modeling assessment will require significant intended for estimating the collective impact estimate should be considered the design consultation with the appropriate reviewing of changes in aircraft operations, point value. This is because the length of the data authority (paragraph 3.0(b)) and the affected source, and mobile source emissions on record may be too short to assure that the FLM(s). The FLM has an affirmative pollutant concentrations. It is not intended conditions producing worst-case estimates responsibility to protect air quality related for PSD, SIP, or other regulatory air quality have been adequately sampled. The highest values (AQRVs) that may be affected, and to analyses of point or mobile sources at or value is then a surrogate for the provide the appropriate procedures and peripheral to airport property that are concentration that is not to be exceeded more analysis techniques. Where there is no unrelated to airport operations. If changes in than once per year (the wording of the increment violation, the ultimate decision on other than aircraft operations are associated deterministic standards). Also, the highest whether a Class I area is adversely affected with analyses, a model recommended in concentration should be used whenever is the responsibility of the appropriate Chapter 4 or 5 should be used. The latest selected worst-case conditions are input to a reviewing authority (Section 165(d)(2)(C)(ii) version of EDMS may be obtained from FAA screening technique, as described in EPA 24 of the Clean Air Act), taking into at its Web site: http://www.aee.faa.gov/ guidance. consideration any information on the impacts emissions/edms/edmshome.htm. d. If the controlling concentration is an on AQRVs provided by the FLM. According annual average value and multiple years of to Section 165(d)(2)(C)(iii) of the Clean Air 7.0 General Modeling Considerations data (site specific or NWS) are used, then the design value is the highest of the annual Act, if there is a Class I increment violation, 7.1 Discussion the source must demonstrate to the averages calculated for the individual years. a. This section contains recommendations satisfaction of the FLM that the emissions If the controlling concentration is a quarterly concerning a number of different issues not from the source will have no adverse impact average and multiple years are used, then the explicitly covered in other sections of this on the AQRVs. highest individual quarterly average should guide. The topics covered here are not b. If LRT is determined to be important, be considered the design value. specific to any one program or modeling area then refined estimates utilizing the CALPUFF e. As long a period of record as possible but are common to nearly all modeling modeling system should be obtained. A should be used in making estimates to analyses for criteria pollutants. screening approach 60 68 is also available for determine design values and PSD increments. If more than 1 year of site use on a case-by-case basis that generally 7.2 Recommendations provides concentrations that are higher than specific data is available, it should be used. 7.2.1 Design Concentrations (See Also those obtained using refined 7.2.1.2 Design Concentrations for O3 and Subsection 10.2.3.1) characterizations of the meteorological PM–2.5 conditions. The meteorological input data 7.2.1.1 Design Concentrations for SO2, PM– a. Guidance and specific instructions for requirements for developing the time and 10, CO, Pb, and NO2 the determination of the 1-hr and 8-hr design space varying three-dimensional winds and a. An air quality analysis for SO , PM–10, concentrations for ozone are provided in dispersion meteorology for refined analyses 2 CO, Pb, and NO2 is required to determine if Appendix H and I (respectively) of reference are discussed in paragraph 8.3.1.2(d). the source will (1) cause a violation of the 4. Appendix H explains how to determine Additional information on applying this NAAQS, or (2) cause or contribute to air when the expected number of days per model is contained in Appendix A. To quality deterioration greater than the calendar year with maximum hourly facilitate use of complex air quality and specified allowable PSD increment. For the concentrations above the NAAQS is equal to meteorological modeling systems, a written former, background concentration or less than 1. Appendix I explains the data protocol approved by the appropriate (subsection 8.2) should be added to the handling conventions and computations reviewing authority (paragraph 3.0(b)) and estimated impact of the source to determine necessary for determining whether the 8-hour the affected FLM(s) may be considered for the design concentration. For the latter, the primary and secondary NAAQS are met at an developing consensus in the methods and design concentration includes impact from ambient monitoring site. For PM–2.5, procedures to be followed. Appendix N of reference 4, and all increment consuming sources. supplementary guidance,69 explain the data 6.2.4 Modeling Guidance for Other b. If the air quality analyses are conducted handling conventions and computations Governmental Programs using the period of meteorological input data necessary for determining when the annual recommended in subsection 8.3.1.2 (e.g., 5 a. When using the models recommended or and 24-hour primary and secondary NAAQS discussed in the Guideline in support of years of National Weather Service (NWS) are met. For all SIP revisions the user should programmatic requirements not specifically data or at least 1 year of site specific data; check with the Regional Office to obtain the covered by EPA regulations, the model user subsection 8.3.3), then the design most recent guidance documents and policy should consult the appropriate Federal or concentration based on the highest, second- memoranda concerning the pollutant in State agency to ensure the proper application highest short term concentration over the question. There are currently no PSD and use of the models. For modeling entire receptor network for each year increments for O3 and PM–2.5. associated with PSD permit applications that modeled or the highest long term average involve a Class I area, the appropriate Federal (whichever is controlling) should be used to 7.2.2 Critical Receptor Sites Land Manager should be consulted on all determine emission limitations to assess a. Receptor sites for refined modeling modeling questions. compliance with the NAAQS and PSD should be utilized in sufficient detail to

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estimate the highest concentrations and buoyant sources, e.g., those involving fuel is the recommended technique for this possible violations of a NAAQS or a PSD combustion, are involved. situation and is used in preferred models for increment. In designing a receptor network, 7.2.4 Stability Categories point sources. the emphasis should be placed on receptor 7.2.6 Chemical Transformation resolution and location, not total number of a. The Pasquill approach to classifying receptors. The selection of receptor sites stability is commonly used in preferred a. The chemical transformation of SO2 should be a case-by-case determination models (Appendix A). The Pasquill method, emitted from point sources or single taking into consideration the topography, the as modified by Turner 75, was developed for industrial plants in rural areas is generally climatology, monitor sites, and the results of use with commonly observed meteorological assumed to be relatively unimportant to the the initial screening procedure. data from the National Weather Service and estimation of maximum concentrations when is based on cloud cover, insolation and wind travel time is limited to a few hours. 7.2.3 Dispersion Coefficients speed. However, in urban areas, where synergistic a. Steady-state Gaussian plume models b. Procedures to determine Pasquill effects among pollutants are of considerable used in most applications should employ stability categories from other than NWS data consequence, chemical transformation rates dispersion coefficients consistent with those are found in subsection 8.3. Any other may be of concern. In urban area contained in the preferred models in method to determine Pasquill stability applications, a half-life of 4 hours 75 may be Appendix A. Factors such as averaging time, categories must be justified on a case-by-case applied to the analysis of SO2 emissions. urban/rural surroundings (see paragraphs basis. Calculations of transformation coefficients (b)—(f) of this subsection), and type of source c. For a given model application where from site specific studies can be used to (point vs. line) may dictate the selection of stability categories are the basis for selecting define a ‘‘half-life’’ to be used in a steady- specific coefficients. Coefficients used in dispersion coefficients, both sy and sz should state Gaussian plume model with any travel some Appendix A models are identical to, or be determined from the same stability time, or in any application, if appropriate at least based on, Pasquill-Gifford category. ‘‘Split sigmas’’ in that instance are documentation is provided. Such conversion coefficients 70 in rural areas and McElroy- not recommended. Sector averaging, which factors for pollutant half-life should not be 71 Pooler coefficients in urban areas. A key eliminates the sy term, is commonly used with screening analyses. feature of AERMOD’s formulation is the use acceptable in complex terrain screening b. Use of models incorporating complex of directly observed variables of the methods. chemical mechanisms should be considered boundary layer to parameterize dispersion.22 d. AERMOD, also a preferred model in only on a case-by-case basis with proper b. The selection of either rural or urban Appendix A, uses a planetary boundary layer demonstration of applicability. These are dispersion coefficients in a specific scaling parameter to characterize stability.22 generally regional models not designed for application should follow one of the This approach represents a departure from the evaluation of individual sources but used procedures suggested by Irwin 72 and briefly the discrete, hourly stability categories primarily for region-wide evaluations. described in paragraphs (c)—(f) of this estimated under the Pasquill-Gifford-Turner Visibility models also incorporate chemical subsection. These include a land use scheme. transformation mechanisms which are an classification procedure or a population 7.2.5 Plume Rise integral part of the visibility model itself and based procedure to determine whether the should be used in visibility assessments. character of an area is primarily urban or a. The plume rise methods of Briggs 76 77 rural. are incorporated in many of the preferred 7.2.7 Gravitational Settling and Deposition c. Land Use Procedure: (1) Classify the models and are recommended for use in a. An ‘‘infinite half-life’’ should be used for 22 land use within the total area, Ao, many modeling applications. In AERMOD, estimates of particle concentrations when circumscribed by a 3km radius circle about for the stable boundary layer, plume rise is steady-state Gaussian plume models the source using the meteorological land use estimated using an iterative approach, similar containing only exponential decay terms for typing scheme proposed by Auer 73; (2) if to that in the CTDMPLUS model. In the treating settling and deposition are used. land use types I1, I2, C1, R2, and R3 account convective boundary layer, plume rise is b. Gravitational settling and deposition for 50 percent or more of Ao, use urban superposed on the displacements by random may be directly included in a model if either dispersion coefficients; otherwise, use convective velocities.78 In AERMOD, plume is a significant factor. When particulate appropriate rural dispersion coefficients. rise is computed using the methods of Briggs matter sources can be quantified and settling d. Population Density Procedure: (1) excepting cases involving building and dry deposition are problems, Compute the average population density, p¯ downwash, in which a numerical solution of professional judgement should be used, and per square kilometer with Ao as defined the mass, energy, and momentum there should be coordination with the conservation laws is performed.23 No explicit above; (2) If p¯ is greater than 750 people/km2, appropriate reviewing authority (paragraph use urban dispersion coefficients; otherwise provisions in these models are made for 3.0(b)). multistack plume rise enhancement or the use appropriate rural dispersion coefficients. 7.2.8 Complex Winds e. Of the two methods, the land use handling of such special plumes as flares; procedure is considered more definitive. these problems should be considered on a a. Inhomogeneous Local Winds. In many Population density should be used with case-by-case basis. parts of the United States, the ground is caution and should not be applied to highly b. Gradual plume rise is generally neither flat nor is the ground cover (or land industrialized areas where the population recommended where its use is appropriate: use) uniform. These geographical variations density may be low and thus a rural (1) In AERMOD; (2) in complex terrain can generate local winds and circulations, classification would be indicated, but the screening procedures to determine close-in and modify the prevailing ambient winds area is sufficiently built-up so that the urban impacts and (3) when calculating the effects and circulations. Geographic effects are most land use criteria would be satisfied. In this of building wakes. The building wake apparent when the ambient winds are light case, the classification should already be algorithm in AERMOD incorporates and or calm.79 In general these geographically ‘‘urban’’ and urban dispersion parameters exercises the thermodynamically based induced wind circulation effects are named should be used. gradual plume rise calculations as described after the source location of the winds, e.g., f. Sources located in an area defined as in (a) above. If the building wake is lake and sea breezes, and mountain and urban should be modeled using urban calculated to affect the plume for any hour, valley winds. In very rugged hilly or dispersion parameters. Sources located in gradual plume rise is also used in downwind mountainous terrain, along coastlines, or areas defined as rural should be modeled dispersion calculations to the distance of near large land use variations, the using the rural dispersion parameters. For final plume rise, after which final plume rise characterization of the winds is a balance of analyses of whole urban complexes, the is used. Plumes captured by the near wake various forces, such that the assumptions of entire area should be modeled as an urban are re-emitted to the far wake as a ground- steady-state straight-line transport both in region if most of the sources are located in level volume source. time and space are inappropriate. In the areas classified as urban. c. Stack tip downwash generally occurs special cases described, the CALPUFF g. Buoyancy-induced dispersion (BID), as with poorly constructed stacks and when the modeling system (described in Appendix A) identified by Pasquill 74, is included in the ratio of the stack exit velocity to wind speed may be applied on a case-by-case basis for air preferred models and should be used where is small. An algorithm developed by Briggs 77 quality estimates in such complex non-

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steady-state meteorological conditions. The 7.2.9 Calibration of Models established. As a minimum, the source purpose of choosing a modeling system like a. Calibration of models is not common should be modeled using the design capacity CALPUFF is to fully treat the time and space practice and is subject to much error and (100 percent load). If a source operates at variations of meteorology effects on transport misunderstanding. There have been attempts greater than design capacity for periods that and dispersion. The setup and application of by some to compare model estimates and could result in violations of the standards or a the model should be determined in measurements on an event-by-event basis PSD increments, this load) should be consultation with the appropriate reviewing and then to calibrate a model with results of modeled. Where the source operates at authority (paragraph 3.0(b)) consistent with that comparison. This approach is severely substantially less than design capacity, and limitations of paragraph 3.2.2(e). The limited by uncertainties in both source and the changes in the stack parameters meteorological input data requirements for meteorological data and therefore it is associated with the operating conditions developing the time and space varying three- difficult to precisely estimate the could lead to higher ground level concentrations, loads such as 50 percent and dimensional winds and dispersion concentration at an exact location for a 75 percent of capacity should also be meteorology for these situations are specific increment of time. Such modeled. A range of operating conditions discussed in paragraphs 8.3.1.2(d) and uncertainties make calibration of models of should be considered in screening analyses; 8.3.1.2(f). Examples of inhomogeneous winds questionable benefit. Therefore, model the load causing the highest concentration, in include, but aren’t limited to, situations calibration is unacceptable. addition to the design load, should be described in the following paragraphs (i)— 8.0 Model Input Data included in refined modeling. For a steam (iii): power plant, the following (b–h) is typical of i. Inversion Breakup Fumigation. Inversion a. Data bases and related procedures for estimating input parameters are an integral the kind of data on source characteristics and breakup fumigation occurs when a plume (or operating conditions that may be needed. part of the modeling procedure. The most multiple plumes) is emitted into a stable Generally, input data requirements for air appropriate data available should always be layer of air and that layer is subsequently quality models necessitate the use of metric selected for use in modeling analyses. mixed to the ground through convective units; where English units are common for Concentrations can vary widely depending transfer of heat from the surface or because engineering usage, a conversion to metric is on the source data or meteorological data of advection to less stable surroundings. required. used. Input data are a major source of Fumigation may cause excessively high b. Plant layout. The connection scheme uncertainties in any modeling analysis. This concentrations but is usually rather short- between boilers and stacks, and the distance section attempts to minimize the uncertainty lived at a given receptor. There are no and direction between stacks, building recommended refined techniques to model associated with data base selection and use parameters (length, width, height, location this phenomenon. There are, however, by identifying requirements for data used in and orientation relative to stacks) for plant screening procedures 24 that may be used to modeling. A checklist of input data structures which house boilers, control requirements for modeling analyses is posted approximate the concentrations. equipment, and surrounding buildings on EPA’s Internet SCRAM Web site Considerable care should be exercised in within a distance of approximately five stack (subsection 2.3). More specific data using the results obtained from the screening heights. requirements and the format required for the techniques. c. Stack parameters. For all stacks, the individual models are described in detail in ii. Shoreline Fumigation. Fumigation can stack height and inside diameter (meters), the users’ guide for each model. be an important phenomenon on and near and the temperature (K) and volume flow rate the shoreline of bodies of water. This can 8.1 Source Data (actual cubic meters per second) or exit gas velocity (meters per second) for operation at affect both individual plumes and area-wide 8.1.1 Discussion emissions. When fumigation conditions are 100 percent, 75 percent and 50 percent load. expected to occur from a source or sources a. Sources of pollutants can be classified as d. Boiler size. For all boilers, the associated 6 with tall stacks located on or just inland of point, line and area/volume sources. Point megawatts, 10 BTU/hr, and pounds of steam a shoreline, this should be addressed in the sources are defined in terms of size and may per hour, and the design and/or actual fuel consumption rate for 100 percent load for air quality modeling analysis. The Shoreline vary between regulatory programs. The line coal (tons/hour), oil (barrels/hour), and Dispersion Model (SDM) listed on EPA’s sources most frequently considered are natural gas (thousand cubic feet/hour). Internet SCRAM Web site (subsection 2.3) roadways and streets along which there are e. Boiler parameters. For all boilers, the may be applied on a case-by-case basis when well-defined movements of motor vehicles, but they may be lines of roof vents or stacks percent excess air used, the boiler type (e.g., air quality estimates under shoreline wet bottom, cyclone, etc.), and the type of fumigation conditions are needed.80 such as in aluminum refineries. Area and volume sources are often collections of a firing (e.g., pulverized coal, front firing, etc.). Information on the results of EPA’s f. Operating conditions. For all boilers, the evaluation of this model together with other multitude of minor sources with individually small emissions that are impractical to type, amount and pollutant contents of fuel, coastal fumigation models is available.81 consider as separate point or line sources. the total hours of boiler operation and the Selection of the appropriate model for Large area sources are typically treated as a boiler capacity factor during the year, and the applications where shoreline fumigation is of grid network of square areas, with pollutant percent load for peak conditions. concern should be determined in emissions distributed uniformly within each g. Pollution control equipment parameters. consultation with the appropriate reviewing grid square. For each boiler served and each pollutant authority (paragraph 3.0(b)). b. Emission factors are compiled in an EPA affected, the type of emission control iii. Stagnation. Stagnation conditions are publication commonly known as AP–42 82; equipment, the year of its installation, its characterized by calm or very low wind an indication of the quality and amount of design efficiency and mass emission rate, the speeds, and variable wind directions. These date of the last test and the tested efficiency, data on which many of the factors are based stagnant meteorological conditions may the number of hours of operation during the is also provided. Other information latest year, and the best engineering estimate persist for several hours to several days. concerning emissions is available in EPA of its projected efficiency if used in During stagnation conditions, the dispersion publications relating to specific source of air pollutants, especially those from low- conjunction with coal combustion; data for categories. The appropriate reviewing any anticipated modifications or additions. level emissions sources, tends to be authority (paragraph 3.0(b)) should be minimized, potentially leading to relatively h. Data for new boilers or stacks. For all consulted to determine appropriate source new boilers and stacks under construction high ground-level concentrations. If point definitions and for guidance concerning the sources are of interest, users should note the determination of emissions from and guidance provided for CALPUFF in a Malfunctions which may result in excess techniques for modeling the various source emissions are not considered to be a normal paragraph (a) of this subsection. Selection of types. the appropriate model for applications where operating condition. They generally should not be 8.1.2 Recommendations considered in determining allowable emissions. stagnation is of concern should be However, if the excess emissions are the result of determined in consultation with the a. For point source applications the load or poor maintenance, careless operation, or other appropriate reviewing authority (paragraph operating condition that causes maximum preventable conditions, it may be necessary to 3.0(b)). ground-level concentrations should be consider them in determining source impact.

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and for all planned modifications to existing also be consulted for other possible emission k. The impact of growth on emissions boilers or stacks, the scheduled date of data that could be helpful. NAAQS should be considered in all modeling completion, and the data or best estimates compliance demonstrations in a PSD analysis analyses covering existing sources. Increases available for items (b) through (g) of this should follow the emission input data shown in emissions due to planned expansion or subsection following completion of in Table 8–2. For purposes of emissions planned fuel switches should be identified. construction or modification. trading, new source review and Increases in emissions at individual sources i. In stationary point source applications demonstrations, refer to current EPA policy that may be associated with a general for compliance with short term ambient and guidance to establish input data. standards, SIP control strategies should be industrial/commercial/residential expansion j. Line source modeling of streets and tested using the emission input shown on in multi-source urban areas should also be highways requires data on the width of the Table 8–1. When using a refined model, treated. For new sources the impact of roadway and the median strip, the types and sources should be modeled sequentially with growth on emissions should generally be amounts of pollutant emissions, the number these loads for every hour of the year. To considered for the period prior to the start- evaluate SIPs for compliance with quarterly of lanes, the emissions from each lane and the height of emissions. The location of the up date for the source. Such changes in and annual standards, emission input data emissions should treat increased area source shown in Table 8–1 should again be used. ends of the straight roadway segments should emissions, changes in existing point source Emissions from area sources should generally be specified by appropriate grid coordinates. be based on annual average conditions. The Detailed information and data requirements emissions which were not subject to source input information in each model for modeling mobile sources of pollution are preconstruction review, and emissions due to user’s guide should be carefully consulted provided in the user’s manuals for each of sources with permits to construct that have and the checklist (paragraph 8.0(a)) should the models applicable to mobile sources. not yet started operation.

TABLE 8–1.—MODEL EMISSION INPUT DATA FOR POINT SOURCES 1

Operating factor Averaging time Emission limit × Operating level × (#/MMBtu) 2 (MMBtu/hr) 2 (e.g., hr/yr, hr/day)

Stationary Point Source(s) Subject to SIP Emission Limit(s) Evaluation for Compliance with Ambient Standards (Including Areawide Demonstrations)

Annual & quarterly ...... Maximum allowable emission Actual or design capacity Actual operating factor aver­ limit or federally enforceable (whichever is greater), or fed­ aged over most recent 2 permit limit. erally enforceable permit con­ years.3 dition. Short term ...... Maximum allowable emission Actual or design capacity Continuous operation, i.e., all limit or federally enforceable (whichever is greater), or fed­ hours of each time period permit limit. erally enforceable permit con- under consideration (for all dition.4 hours of the meteorological data base).5

Nearby Source(s) 67 Same input requirements as for stationary point source(s) above.

Other Source(s) 7 If modeled (subsection 8.2.3), input data requirements are defined below.

Annual & quarterly ...... Maximum allowable emission Annual level when actually op­ Actual operating factor aver­ limit or federally enforceable erating, averaged over the aged over the most recent 2 permit limit.6 most recent 2 years.3 years.3 Short term ...... Maximum allowable emission Annual level when actually op­ Continuous operation, i.e., all limit or federally enforceable erating, averaged over the hours of each time period permit limit.6 most recent 2 years.3 under consideration (for all hours of the meteorological data base).5 1 The model input data requirements shown on this table apply to stationary source control strategies for STATE IMPLEMENTATION PLANS. For purposes of emissions trading, new source review, or prevention of significant deterioration, other model input criteria may apply. Refer to the policy and guidance for these programs to establish the input data. 2 Terminology applicable to fuel burning sources; analogous terminology (e.g., #/throughput) may be used for other types of sources. 3 Unless it is determined that this period is not representative. 4 Operating levels such as 50 percent and 75 percent of capacity should also be modeled to determine the load causing the highest concentra­ tion. 5 If operation does not occur for all hours of the time period of consideration (e.g., 3 or 24 hours) and the source operation is constrained by a federally enforceable permit condition, an appropriate adjustment to the modeled emission rate may be made (e.g., if operation is only 8 a.m. to 4 p.m. each day, only these hours will be modeled with emissions from the source. Modeled emissions should not be averaged across non-oper- ating time periods.) 6 See paragraph 8.2.3(c). 7 See paragraph 8.2.3(d).

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TABLE 8–2.—POINT SOURCE MODEL EMISSION INPUT DATA FOR NAAQS COMPLIANCE IN PSD DEMONSTRATIONS

Averaging time Emission limit × Operating level × Operating factor (#/MMBtu) 1 (MMBtu/hr) 1 (e.g., hr/yr, hr/day)

Proposed Major New or Modified Source

Annual & quarterly ...... Maximum allowable emission Design capacity or federally en- Continuous operation (i.e., 8760 limit or federally enforceable forceable permit condition. hours).2 permit limit. Short term (≤ 24 hours) ...... Maximum allowable emission Design capacity or federally en- Continuous operation, i.e., all limit or federally enforceable forceable permit condition.3 hours of each time period permit limit. under consideration (for all hours of the meteorological data base).2

Nearby Source(s) 46

Annual & quarterly ...... Maximum allowable emission Actual or design capacity Actual operating factor aver- limit or federally enforceable (whichever is greater), or fed- aged over the most recent 2 permit limit.5 erally enforceable permit con- years.78 dition. Short term (≤ 24 hours) ...... Maximum allowable emission Actual or design capacity Continuous operation, i.e., all limit or federally enforceable (whichever is greater), or fed- hours of each time period permit limit.5 erally enforceable permit con- under consideration (for all dition.3 hours of the meteorological data base).2

Other Source(s) 69

Annual & quarterly ...... Maximum allowable emission Annual level when actually op- Actual operating factor aver- limit or federally enforceable erating, averaged over the aged over the most recent 2 permit limit.5 most recent 2 years.7 years.78 Short term (≤ 24 hours) ...... Maximum allowable emission Annual level when actually op- Continuous operation, i.e., all limit or federally enforceable erating, averaged over the hours of each time period permit limit.5 most recent 2 years.7 under consideration (for all hours of the meteorological data base).2 1 Terminology applicable to fuel burning sources; analogous terminology (e.g., #/throughput) may be used for other types of sources. 2 If operation does not occur for all hours of the time period of consideration (e.g., 3 or 24 hours) and the source operation is constrained by a federally enforceable permit condition, an appropriate adjustment to the modeled emission rate may be made (e.g., if operation is only 8 a.m. to 4 p.m. each day, only these hours will be modeled with emissions from the source. Modeled emissions should not be averaged across non-oper- ating time periods. 3 Operating levels such as 50 percent and 75 percent of capacity should also be modeled to determine the load causing the highest concentra­ tion. 4 Includes existing facility to which modification is proposed if the emissions from the existing facility will not be affected by the modification. Otherwise use the same parameters as for major modification. 5 See paragraph 8.2.3(c). 6 See paragraph 8.2.3(d). 7 Unless it is determined that this period is not representative. 8 For those permitted sources not in operation or that have not established an appropriate factor, continuous operation (i.e., 8760) should be used. 9 Generally, the ambient impacts from non-nearby (background) sources can be represented by air quality data unless adequate data do not exist.

8.2 Background Concentrations c. If the source is not isolated, it may be background concentration for the averaging 8.2.1 Discussion necessary to use a multi-source model to times of concern. Determine the mean establish the impact of nearby sources. Since background concentration at each monitor by a. Background concentrations are an sources don’t typically operate at their excluding values when the source in essential part of the total air quality maximum allowable capacity (which may question is impacting the monitor. The mean concentration to be considered in include the use of ‘‘dirtier’’ fuels), modeling annual background is the average of the determining source impacts. Background air is necessary to express the potential annual concentrations so determined at each quality includes pollutant concentrations due contribution of background sources, and this to: (1) Natural sources; (2) nearby sources monitor. For shorter averaging periods, the impact would not be captured via meteorological conditions accompanying the other than the one(s) currently under monitoring. Background concentrations consideration; and (3) unidentified sources. concentrations of concern should be should be determined for each critical identified. Concentrations for meteorological b. Typically, air quality data should be (concentration) averaging time. used to establish background concentrations conditions of concern, at monitors not in the vicinity of the source(s) under 8.2.2 Recommendations (Isolated Single impacted by the source in question, should consideration. The monitoring network used Source) be averaged for each separate averaging time for background determinations should a. Two options (paragraph (b) or (c) of this to determine the average background value. conform to the same quality assurance and section) are available to determine the Monitoring sites inside a 90° sector other requirements as those networks background concentration near isolated downwind of the source may be used to established for PSD purposes.83 An sources. determine the area of impact. One hour appropriate data validation procedure should b. Use air quality data collected in the concentrations may be added and averaged to be applied to the data prior to use. vicinity of the source to determine the determine longer averaging periods.

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c. If there are no monitors located in the with the sources that they back up would not assessing representativeness should be given vicinity of the source, a ‘‘regional site’’ may be modeled as nearby sources. To reiterate, to adequate characterization of transport and be used to determine background. A in these examples and other appropriate dispersion between the source(s) of concern ‘‘regional site’’ is one that is located away cases, the burden is on the primary source and areas where maximum design from the area of interest but is impacted by being modeled to make the appropriate concentrations are anticipated to occur. The similar natural and distant man-made demonstration to the satisfaction of the representativeness of data that were collected sources. appropriate reviewing authority. off-site should be judged, in part, by 8.2.3 Recommendations (Multi-Source e. The impact of the nearby sources should comparing the surface characteristics in the Areas) be examined at locations where interactions vicinity of the meteorological monitoring site between the plume of the point source under with the surface characteristics that generally a. In multi-source areas, two components consideration and those of nearby sources describe the analysis domain. The surface of background should be determined: (plus natural background) can occur. characteristics input to AERMET should be contributions from nearby sources and Significant locations include: (1) the area of based on the topographic conditions in the contributions from other sources. maximum impact of the point source; (2) the vicinity of the meteorological tower. b. Nearby Sources: All sources expected to area of maximum impact of nearby sources; Furthermore, since the spatial scope of each cause a significant concentration gradient in and (3) the area where all sources combine variable could be different, the vicinity of the source or sources under to cause maximum impact. These locations representativeness should be judged for each consideration for emission limit(s) should be may be identified through trial and error variable separately. For example, for a explicitly modeled. The number of such analyses. variable such as wind direction, the data may sources is expected to be small except in f. Other Sources: That portion of the need to be collected very near plume height unusual situations. Owing to both the background attributable to all other sources to be adequately representative, whereas, for uniqueness of each modeling situation and (e.g., natural sources, minor sources and a variable such as temperature, data from a the large number of variables involved in distant major sources) should be determined station several kilometers away from the identifying nearby sources, no attempt is by the procedures found in subsection 89.2.2 source may in some cases be considered to made here to comprehensively define this or by application of a model using Table 8– be adequately representative. term. Rather, identification of nearby sources 1 or 8–2. d. For long range transport modeling calls for the exercise of professional assessments (subsection 6.2.3) or for judgement by the appropriate reviewing 8.3 Meteorological Input Data assessments where the transport winds are authority (paragraph 3.0(b)). This guidance is a. The meteorological data used as input to complex and the application involves a non- not intended to alter the exercise of that a dispersion model should be selected on the steady-state dispersion model (subsection judgement or to comprehensively define basis of spatial and climatological (temporal) 7.2.8), use of output from prognostic which sources are nearby sources. representativeness as well as the ability of mesoscale meteorological models is c. For compliance with the short-term and the individual parameters selected to encouraged.84 85 86 Some diagnostic annual ambient standards, the nearby sources characterize the transport and dispersion meteorological processors are designed to as well as the primary source(s) should be conditions in the area of concern. The appropriately blend available NWS evaluated using an appropriate Appendix A representativeness of the data is dependent comparable meteorological observations, model with the emission input data shown local site specific meteorological in Table 8–1 or 8–2. When modeling a nearby on: (1) The proximity of the meteorological monitoring site to the area under observations, and prognostic mesoscale source that does not have a permit and the meteorological data, using empirical emission limit contained in the SIP for a consideration; (2) the complexity of the terrain; (3) the exposure of the meteorological relationships, to diagnostically adjust the particular source category is greater than the wind field for mesoscale and local-scale emissions possible given the source’s monitoring site; and (4) the period of time during which data are collected. The spatial effects. These diagnostic adjustments can maximum physical capacity to emit, the sometimes be improved through the use of ‘‘maximum allowable emission limit’’ for representativeness of the data can be adversely affected by large distances between strategically placed site specific such a nearby source may be calculated as meteorological observations. The placement the emission rate representative of the nearby the source and receptors of interest and the complex topographic characteristics of the of these special meteorological observations source’s maximum physical capacity to emit, (often more than one location is needed) considering its design specifications and area. Temporal representativeness is a involves expert judgement, and is specific to allowable fuels and process materials. function of the year-to-year variations in the terrain and land use of the modeling However, the burden is on the permit weather conditions. Where appropriate, data domain. Acceptance for use of output from applicant to sufficiently document what the representativeness should be viewed in terms prognostic mesoscale meteorological models maximum physical capacity to emit is for of the appropriateness of the data for is contingent on concurrence by the such a nearby source. constructing realistic boundary layer profiles appropriate reviewing authorities (paragraph d. It is appropriate to model nearby sources and three dimensional meteorological fields, 3.0(b)) that the data are of acceptable quality, only during those times when they, by their as described in paragraphs (c) and (d) below. which can be demonstrated through nature, operate at the same time as the b. Model input data are normally obtained statistical comparisons with observations of primary source(s) being modeled. Where a either from the National Weather Service or primary source believes that a nearby source as part of a site specific measurement winds aloft and at the surface at several does not, by its nature, operate at the same program. Local universities, Federal Aviation appropriate locations. time as the primary source being modeled, Administration (FAA), military stations, 8.3.1 Length of Record of Meteorological the burden is on the primary source to industry and pollution control agencies may Data demonstrate to the satisfaction of the also be sources of such data. Some 8.3.1.1 Discussion appropriate reviewing authority (paragraph recommendations for the use of each type of 3.0(b)) that this is, in fact, the case. Whether data are included in this subsection. a. The model user should acquire enough or not the primary source has adequately c. Regulatory application of AERMOD meteorological data to ensure that worst-case demonstrated that fact is a matter of requires careful consideration of minimum meteorological conditions are adequately professional judgement left to the discretion data for input to AERMET. Data represented in the model results. The trend of the appropriate reviewing authority. The representativeness, in the case of AERMOD, toward statistically based standards suggests following examples illustrate two cases in means utilizing data of an appropriate type a need for all meteorological conditions to be which a nearby source may be shown not to for constructing realistic boundary layer adequately represented in the data set operate at the same time as the primary profiles. Of paramount importance is the selected for model input. The number of source(s) being modeled. Some sources are requirement that all meteorological data used years of record needed to obtain a stable only used during certain seasons of the year. as input to AERMOD must be both laterally distribution of conditions depends on the Those sources would not be modeled as and vertically representative of the transport variable being measured and has been nearby sources during times in which they and dispersion within the analysis domain. estimated by Landsberg and Jacobs 87 for do not operate. Similarly, emergency backup Where surface conditions vary significantly various parameters. Although that study generators that never operate simultaneously over the analysis domain, the emphasis in indicates in excess of 10 years may be

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required to achieve stability in the frequency data are being relied upon as the basis for data in close proximity to the actual site of distributions of some meteorological characterizing the meteorological conditions, the source(s). Site specific measured data are variables, such long periods are not a data base of at least 1 full-year of therefore preferred as model input, provided reasonable for model input data. This is due meteorological data is required. If more data that appropriate instrumentation and quality in part to the fact that hourly data in model are available, they should be used. Site assurance procedures are followed and that input format are frequently not available for specific meteorological data may have to be the data collected are adequately such periods and that hourly calculations of collected at multiple locations. Such data representative (free from inappropriate local concentration for long periods may be should have been subjected to quality or microscale influences) and compatible prohibitively expensive. Another study 88 assurance procedures as described in with the input requirements of the model to compared various periods from a 17-year paragraph 8.3.3.2(a), and should be reviewed be used. It should be noted that, while site data set to determine the minimum number for spatial and temporal representativeness. specific measurements are frequently made of years of data needed to approximate the 8.3.2 National Weather Service Data ‘‘on-property’’ (i.e., on the source’s premises), concentrations modeled with a 17-year acquisition of adequately representative site period of meteorological data from one 8.3.2.1 Discussion specific data does not preclude collection of station. This study indicated that the a. The NWS meteorological data are data from a location off property. Conversely, variability of model estimates due to the routinely available and familiar to most collection of meteorological data on a meteorological data input was adequately model users. Although the NWS does not source’s property does not of itself guarantee reduced if a 5-year period of record of provide direct measurements of all the adequate representativeness. For help in meteorological input was used. needed dispersion model input variables, determining representativeness of site 8.3.1.2 Recommendations methods have been developed and specific measurements, technical guidance 92 a. Five years of representative successfully used to translate the basic NWS is available. Site specific data should always meteorological data should be used when data to the needed model input. Site specific be reviewed for representativeness and estimating concentrations with an air quality measurements of model input parameters consistency by a qualified meteorologist. have been made for many modeling studies, model. Consecutive years from the most 8.3.3.2 Recommendations recent, readily available 5-year period are and those methods and techniques are becoming more widely applied, especially in a. EPA guidance 92 provides preferred. The meteorological data should be recommendations on the collection and use adequately representative, and may be site situations such as complex terrain of site specific meteorological data. specific or from a nearby NWS station. Where applications, where available NWS data are Recommendations on characteristics, siting, professional judgment indicates NWS- not adequately representative. However, and exposure of meteorological instruments collected ASOS (automated surface observing there are many model applications where and on data recording, processing, stations) data are inadequate {for cloud cover NWS data are adequately representative, and completeness requirements, reporting, and observations}, the most recent 5 years of the applications still rely heavily on the NWS archiving are also included. This publication NWS data that are observer-based may be data. should be used as a supplement to other considered for use. b. Many models use the standard hourly limited guidance on these subjects.83 93 94 b. The use of 5 years of NWS weather observations available from the National Climatic Data Center (NCDC). These Detailed information on quality assurance is meteorological data or at least l year of site 95 specific data is required. If one year or more observations are then preprocessed before also available. As a minimum, site specific (including partial years), up to five years, of they can be used in the models. measurements of ambient air temperature, transport wind speed and direction, and the site specific data is available, these data are 8.3.2.2 Recommendations preferred for use in air quality analyses. Such variables necessary to estimate atmospheric a. The preferred models listed in Appendix dispersion should be available in data should have been subjected to quality A all accept as input the NWS meteorological assurance procedures as described in meteorological data sets to be used in data preprocessed into model compatible modeling. Care should be taken to ensure subsection 8.3.3.2. form. If NWS data are judged to be c. For permitted sources whose emission that meteorological instruments are located adequately representative for a particular to provide representative characterization of limitations are based on a specific year of modeling application, they may be used. meteorological data, that year should be pollutant transport between sources and NCDC makes available surface 89 90 and upper added to any longer period being used (e.g., receptors of interest. The appropriate air 91 meteorological data in CD–ROM format. 5 years of NWS data) when modeling the reviewing authority (paragraph 3.0(b)) is b. Although most NWS measurements are facility at a later time. available to help determine the made at a standard height of 10 meters, the d. For LRT situations (subsection 6.2.3) appropriateness of the measurement actual anemometer height should be used as and for complex wind situations (paragraph locations. input to the preferred model. Note that 7.2.8(a)), if only NWS or comparable b. All site specific data should be reduced AERMOD at a minimum requires wind standard meteorological observations are to hourly averages. Table 8–3 lists the wind observations at a height above ground employed, five years of meteorological data related parameters and the averaging time between seven times the local surface (within and near the modeling domain) requirements. roughness height and 100 meters. should be used. Consecutive years from the c. Missing Data Substitution. After valid most recent, readily available 5-year period c. Wind directions observed by the data retrieval requirements have been met 92, are preferred. Less than five, but at least National Weather Service are reported to the hours in the record having missing data three, years of meteorological data (need not nearest 10 degrees. A specific set of randomly should be treated according to an established be consecutive) may be used if mesoscale generated numbers has been developed for data substitution protocol provided that data meteorological fields are available, as use with the preferred EPA models and from an adequately representative alternative discussed in paragraph 8.3(d). These should be used with NWS data to ensure a site are available. Such protocols are usually mesoscale meteorological fields should be lack of bias in wind direction assignments part of the approved monitoring program used in conjunction with available standard within the models. plan. Data substitution guidance is provided NWS or comparable meteorological d. Data from universities, FAA, military in Section 5.3 of reference 92. If no observations within and near the modeling stations, industry and pollution control representative alternative data are available domain. agencies may be used if such data are for substitution, the absent data should be e. For solely LRT applications (subsection equivalent in accuracy and detail to the NWS coded as missing using missing data codes 6.2.3), if site specific meteorological data are data, and they are judged to be adequately appropriate to the applicable meteorological available, these data may be helpful when representative for the particular application. pre-processor. Appropriate model options for used in conjunction with available standard 8.3.3 Site Specific Data treating missing data, if available in the NWS or comparable observations and model, should be employed. mesoscale meteorological fields as described 8.3.3.1 Discussion d. Solar Radiation Measurements. Total in paragraph 8.3.1.2(d). a. Spatial or geographical solar radiation or net radiation should be f. For complex wind situations (paragraph representativeness is best achieved by measured with a reliable pyranometer or net 7.2.8(a)) where site specific meteorological collection of all of the needed model input radiometer, sited and operated in accordance

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with established site specific meteorological categories, as originally defined, couple near- TABLE 8–3.—AVERAGING TIMES FOR 92 95 guidance. surface measurements of wind speed with SITE SPECIFIC WIND AND TURBU­ e. Temperature Measurements. subjectively determined insolation Temperature measurements should be made assessments based on hourly cloud cover and LENCE MEASUREMENTS—Continued at standard shelter height (2m) in accordance ceiling height observations. The wind speed with established site specific meteorological measurements are made at or near 10m. The Averaging guidance.92 Parameter time insolation rate is typically assessed using (hour) f. Temperature Difference Measurements. observations of cloud cover and ceiling Temperature difference (DT) measurements 70 height based on criteria outlined by Turner. Turbulence measurements (s should be obtained using matched E It is recommended that the P–G stability and s ) for use in stability thermometers or a reliable thermocouple A category be estimated using the Turner determinations ...... 11 system to achieve adequate accuracy. Siting, method with site specific wind speed Turbulence measurements for probe placement, and operation of DT measured at or near 10m and representative direct input to dispersion systems should be based on guidance found cloud cover and ceiling height. models ...... 1 in Chapter 3 of reference 92, and such Implementation of the Turner method, as guidance should be followed when obtaining 1 well as considerations in determining To minimize meander effects in sA when vertical temperature gradient data. AERMET representativeness of cloud cover and ceiling wind conditions are light and/or variable, de­ employs the Bulk Richardson scheme which height in cases for which site specific cloud termine the hourly average s value from four requires measurements of temperature sequential 15-minute s’s according to the fol­ observations are unavailable, may be found lowing formula: difference. To ensure correct application and in Section 6 of reference 92. In the absence acceptance, AERMOD users should consult of requisite data to implement the Turner with the appropriate Reviewing Authority method, the SRDT method or wind σ 2+ σ 2+ σ 2 + σ 2 before using the Bulk Richardson scheme for 15 15 15 15 fluctuation statistics (i.e., the sE and sA σ = their analysis. 1−hr methods) may be used. 4 g. Winds Aloft. For simulation of plume j. The SRDT method, described in Section rise and dispersion of a plume emitted from 6.4.4.2 of reference 92, is modified slightly 8.3.4 Treatment of Near-Calms and Calms a stack, characterization of the wind profile from that published from earlier work 96 and up through the layer in which the plume 8.3.4.1 Discussion has been evaluated with three site specific disperses is required. This is especially a. Treatment of calm or light and variable data bases.97 The two methods of stability important in complex terrain and/or complex wind poses a special problem in model classification which use wind fluctuation wind situations where wind measurements at applications since steady-state Gaussian statistics, the s and s methods, are also heights up to hundreds of meters above stack E A plume models assume that concentration is described in detail in Section 6.4.4 of base may be required in some circumstances. inversely proportional to wind speed. reference 92 (note applicable tables in For tall stacks when site specific data are Furthermore, concentrations may become Section 6). For additional information on the needed, these winds have been obtained unrealistically large when wind speeds less wind fluctuation methods, several references traditionally using meteorological sensors than 1 m/s are input to the model. are available.98 99 100 101 mounted on tall towers. A feasible alternative Procedures have been developed to prevent k. Meteorological Data Preprocessors. The to tall towers is the use of meteorological the occurrence of overly conservative following meteorological preprocessors are remote sensing instruments (e.g., acoustic concentration estimates during periods of recommended by EPA: AERMET,102 sounders or radar wind profilers) to provide calms. These procedures acknowledge that a PCRAMMET,103 MPRM,104 METPRO,105 and winds aloft, coupled with 10-meter towers to steady-state Gaussian plume model does not CALMET 106 AERMET, which is patterned provide the near-surface winds. (For specific apply during calm conditions, and that our after MPRM, should be used to preprocess all requirements for AERMOD and CTDMPLUS, knowledge of wind patterns and plume data for use with AERMOD. Except for see Appendix A.) Specifications for wind behavior during these conditions does not, at applications that employ AERMOD, measuring instruments and systems are present, permit the development of a better PCRAMMET is the recommended contained in reference 92. technique. Therefore, the procedures meteorological preprocessor for use in h. Turbulence. There are several dispersion disregard hours which are identified as calm. applications employing hourly NWS data. models that are capable of using direct The hour is treated as missing and a MPRM is a general purpose meteorological measurements of turbulence (wind convention for handling missing hours is data preprocessor which supports regulatory fluctuations) in the characterization of the recommended. models requiring PCRAMMET formatted vertical and lateral dispersion (e.g., b. AERMOD, while fundamentally a (NWS) data. MPRM is available for use in CTDMPLUS, AERMOD, and CALPUFF). For steady-state Gaussian plume model, contains applications employing site specific specific requirements for CTDMPLUS, algorithms for dealing with low wind speed meteorological data. The latest version AERMOD, and CALPUFF, see Appendix A. (near calm) conditions. As a result, AERMOD (MPRM 1.3) has been configured to For technical guidance on measurement and can produce model estimates for conditions implement the SRDT method for estimating processing of turbulence parameters, see when the wind speed may be less than 1 m/ P–G stability categories. METPRO is the reference 92. When turbulence data are used s, but still greater than the instrument required meteorological data preprocessor for in this manner to directly characterize the threshold. Required input to AERMET, the use with CTDMPLUS. CALMET is available vertical and lateral dispersion, the averaging meteorological processor for AERMOD, for use with applications of CALPUFF. All of time for the turbulence measurements should includes a threshold wind speed and a the above mentioned data preprocessors are be one hour (Table 8–3). There are other reference wind speed. The threshold wind available for downloading from EPA’s dispersion models (e.g., BLP, and CALINE3) speed is typically the threshold of the Internet SCRAM Web site (subsection 2.3). that employ P–G stability categories for the instrument used to collect the wind speed characterization of the vertical and lateral data. The reference wind speed is selected by dispersion. Methods for using site specific TABLE 8–3.—AVERAGING TIMES FOR the model as the lowest level of non-missing turbulence data for the characterization of P– SITE SPECIFIC WIND AND TURBU­ wind speed and direction data where the G stability categories are discussed in LENCE MEASUREMENTS speed is greater than the wind speed reference 92. When turbulence data are used threshold, and the height of the measurement in this manner to determine the P–G stability Averaging is between seven times the local surface category, the averaging time for the Parameter time roughness and 100 meters. If the only valid turbulence measurements should be 15 (hour) observation of the reference wind speed minutes. between these heights is less than the i. Stability Categories. For dispersion Surface wind speed (for use in threshold, the hour is considered calm, and models that employ P–G stability categories stability determinations) ...... 1 no concentration is calculated. None of the for the characterization of the vertical and Transport direction ...... 1 observed wind speeds in a measured wind lateral dispersion, the P–G stability Dilution wind speed ...... 1 profile that are less than the threshold speed

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are used in construction of the modeled wind uncertainty in the regulatory process. The comparison of model concentration estimates speed profile in AERMOD. Second (EPA) Conference on Air Quality with measured air quality data.118 The 110 8.3.4.2 Recommendations Modeling, August 1982 , was devoted to statement of accuracy is based on statistical that subject. tests or performance measures such as bias, a. Hourly concentrations calculated with b. To better deduce the statistical noise, correlation, etc.11 However, steady-state Gaussian plume models using significance of differences seen in model information that allows a distinction between calms should not be considered valid; the performance in the face of unaccounted for contributions of the various elements of wind and concentration estimates for these uncertainties and variations, investigators inherent and reducible uncertainty is only hours should be disregarded and considered have more recently explored the use of now beginning to emerge.16 As a result most to be missing. Critical concentrations for bootstrap techniques.111 112 Work is discussions of the accuracy of models make 3-, 8-, and 24-hour averages should be underway to develop a new generation of no quantitative distinction between (1) calculated by dividing the sum of the hourly evaluation metrics 16 that takes into account limitations of the model versus (2) concentrations for the period by the number the statistical differences (in error limitations of the data base and of knowledge of valid or non-missing hours. If the total distributions) between model predictions and concerning atmospheric variability. The number of valid hours is less than 18 for 24- observations.113 Even though the procedures reader should be aware that statements on hour averages, less than 6 for 8-hour averages and measures are still evolving to describe model accuracy and uncertainty may imply or less than 3 for 3-hour averages, the total performance of models that characterize the need for improvements in model concentration should be divided by 18 for the atmospheric fate, transport and performance that even the ‘‘perfect’’ model 24-hour average, 6 for the 8-hour average and diffusion 114 115 116, there has been general could not satisfy. 3 for the 3-hour average. For annual averages, acceptance of a need to address the 9.1.2 Studies of Model Accuracy the sum of all valid hourly concentrations is uncertainties inherent in atmospheric divided by the number of non-calm hours processes. a. A number of studies 119 120 have been during the year. AERMOD has been coded to conducted to examine model accuracy, implement these instructions. For models 9.1.1 Overview of Model Uncertainty particularly with respect to the reliability of listed in Appendix A, a post-processor a. Dispersion models generally attempt to short-term concentrations required for computer program, CALMPRO 107 has been estimate concentrations at specific sites that ambient standard and increment evaluations. prepared, is available on the SCRAM Internet really represent an ensemble average of The results of these studies are not Web site (subsection 2.3), and should be numerous repetitions of the same event.16 surprising. Basically, they confirm what used. The event is characterized by measured or expert atmospheric scientists have said for b. Stagnant conditions that include ‘‘known’’ conditions that are input to the some time: (1) Models are more reliable for extended periods of calms often produce models, e.g., wind speed, mixed layer height, estimating longer time-averaged high concentrations over wide areas for surface heat flux, emission characteristics, concentrations than for estimating short-term relatively long averaging periods. The etc. However, in addition to the known concentrations at specific locations; and (2) standard steady-state Gaussian plume models conditions, there are unmeasured or the models are reasonably reliable in are often not applicable to such situations. unknown variations in the conditions of this estimating the magnitude of highest When stagnation conditions are of concern, event, e.g., unresolved details of the concentrations occurring sometime, other modeling techniques should be atmospheric flow such as the turbulent somewhere within an area. For example, considered on a case-by-case basis (see also velocity field. These unknown conditions, errors in highest estimated concentrations of subsection 7.2.8). may vary among repetitions of the event. As ± 10 to 40 percent are found to be c. When used in steady-state Gaussian a result, deviations in observed typical 121 122, i.e., certainly well within the plume models, measured site specific wind concentrations from their ensemble average, often quoted factor-of-two accuracy that has speeds of less than 1 m/s but higher than the and from the concentrations estimated by the long been recognized for these models. response threshold of the instrument should model, are likely to occur even though the However, estimates of concentrations that be input as 1 m/s; the corresponding wind known conditions are fixed. Even with a occur at a specific time and site, are poorly direction should also be input. Wind perfect model that predicts the correct correlated with actually observed observations below the response threshold of ensemble average, there are likely to be concentrations and are much less reliable. the instrument should be set to zero, with the deviations from the observed concentrations b. As noted above, poor correlations input file in ASCII format. For input to in individual repetitions of the event, due to between paired concentrations at fixed AERMOD, no adjustment should be made to variations in the unknown conditions. The stations may be due to ‘‘reducible’’ the site specific wind data. In all cases statistics of these concentration residuals are uncertainties in knowledge of the precise involving steady-state Gaussian plume termed ‘‘inherent’’ uncertainty. Available plume location and to unquantified inherent models, calm hours should be treated as evidence suggests that this source of uncertainties. For example, Pasquill 123 missing, and concentrations should be uncertainty alone may be responsible for a estimates that, apart from data input errors, calculated as in paragraph (a) of this typical range of variation in concentrations of maximum ground-level concentrations at a ± 117 subsection. as much as 50 percent. given hour for a point source in flat terrain b. Moreover, there is ‘‘reducible’’ could be in error by 50 percent due to these 9.0 Accuracy and Uncertainty of Models uncertainty 108 associated with the model and uncertainties. Uncertainty of five to 10 its input conditions; neither models nor data 9.1 Discussion degrees in the measured wind direction, bases are perfect. Reducible uncertainties are which transports the plume, can result in a. Increasing reliance has been placed on caused by: (1) Uncertainties in the input concentration errors of 20 to 70 percent for concentration estimates from models as the values of the known conditions (i.e., a particular time and location, depending on primary basis for regulatory decisions emission characteristics and meteorological stability and station location. Such concerning source permits and emission data); (2) errors in the measured uncertainties do not indicate that an control requirements. In many situations, concentrations which are used to compute estimated concentration does not occur, only such as review of a proposed source, no the concentration residuals; and (3) that the precise time and locations are in practical alternative exists. Therefore, there is inadequate model physics and formulation. doubt. an obvious need to know how accurate The ‘‘reducible’’ uncertainties can be models really are and how any uncertainty in minimized through better (more accurate and 9.1.3 Use of Uncertainty in Decision- the estimates affects regulatory decisions. more representative) measurements and Making During the 1980’s, attempts were made to better model physics. a. The accuracy of model estimates varies encourage development of standardized c. To use the terminology correctly, with the model used, the type of application, evaluation methods.11 108 EPA recognized the reference to model accuracy should be and site specific characteristics. Thus, it is need for incorporating such information and limited to that portion of reducible desirable to quantify the accuracy or has sponsored workshops 109 on model uncertainty which deals with the physics and uncertainty associated with concentration accuracy, the possible ways to quantify the formulation of the model. The accuracy estimates used in decision-making. accuracy, and on considerations in the of the model is normally determined by an Communications between modelers and incorporation of model accuracy and evaluation procedure which involves the decision-makers must be fostered and further

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developed. Communications concerning performance measures, including measures they can provide additional information on concentration estimates currently exist in of difference (or residuals) such as bias, the effect of inaccuracies in the data bases most cases, but the communications dealing variance of difference and gross variability of and on the uncertainty in model estimates. with the accuracy of models and its meaning the difference, and measures of correlation Sensitivity analyses can aid in determining to the decision-maker are limited by the lack such as time, space, and time and space the effect of inaccuracies of variations or of a technical basis for quantifying and combined as recommended by the AMS uncertainties in the data bases on the range directly including uncertainty in decisions. Woods Hole Workshop 11, were generally of likely concentrations. Uncertainty analyses Procedures for quantifying and interpreting followed. Third, more specific information can aid in determining the range of likely uncertainty in the practical application of has been provided for justifying the site concentration values, resulting from such concepts are only beginning to evolve; specific use of alternative models in uncertainties in the model inputs, the model much study is still required.108 109 110 124 125 previously cited EPA guidance 15, and new formulations, and parameterizations. Such b. In all applications of models an effort is models are under consideration and information may be used to determine source encouraged to identify the reliability of the review.16 Together these documents provide impact and to evaluate control strategies. model estimates for that particular area and methods that allow a judgement to be made Where possible, information from such to determine the magnitude and sources of as to what models are most appropriate for sensitivity analyses should be made available error associated with the use of the model. a specific application. For the present, to the decision-maker with an appropriate The analyst is responsible for recognizing performance and the theoretical evaluation of interpretation of the effect on the critical and quantifying limitations in the accuracy, models are being used as an indirect means concentrations. precision and sensitivity of the procedure. to quantify one element of uncertainty in air Information that might be useful to the pollution regulatory decisions. 9.2 Recommendations decision-maker in recognizing the b. EPA has participated in a series of a. No specific guidance on the seriousness of potential air quality violations conferences entitled, ‘‘Harmonisation within quantification of model uncertainty for use in includes such model accuracy estimates as Atmospheric Dispersion Modelling for decision-making is being given at this time. accuracy of peak predictions, bias, noise, Regulatory Purposes.’’ 128 for the purpose of As procedures for considering uncertainty correlation, frequency distribution, spatial promoting the development of improved develop and become implementable, this extent of high concentration, etc. Both space/ methods for the characterization of model guidance will be changed and expanded. For time pairing of estimates and measurements performance. There is a consensus the present, continued use of the ‘‘best and unpaired comparisons are developing on what should be considered in estimate’’ is acceptable; however, in specific recommended. Emphasis should be on the the evaluation of air quality models 129, circumstances for O3, PM–2.5 and regional highest concentrations and the averaging namely quality assurance planning, haze, additional information and/or times of the standards or increments of documentation and scrutiny should be procedures may be appropriate.32 33 concern. Where possible, confidence consistent with the intended use, and should 10.0 Regulatory Application of Models intervals about the statistical values should include: be provided. However, while such • Scientific peer review; 10.1 Discussion • information can be provided by the modeler Supportive analyses (diagnostic a. Procedures with respect to the review to the decision-maker, it is unclear how this evaluations, code verification, sensitivity and and analysis of air quality modeling and data information should be used to make an air uncertainty analyses); • analyses in support of SIP revisions, PSD pollution control decision. Given a range of Diagnostic and performance evaluations permitting or other regulatory requirements possible outcomes, it is easiest and tends to with data obtained in trial locations, and • need a certain amount of standardization to ensure consistency if the decision-maker Statistical performance evaluations in ensure consistency in the depth and confines his judgement to use of the ‘‘best the circumstances of the intended comprehensiveness of both the review and estimate’’ provided by the modeler (i.e., the applications. the analysis itself. This section recommends design concentration estimated by a model Performance evaluations and diagnostic procedures that permit some degree of recommended in the Guideline or an evaluations assess different qualities of how standardization while at the same time alternate model of known accuracy). This is well a model is performing, and both are allowing the flexibility needed to assure the an indication of the practical limitations needed to establish credibility within the technically best analysis for each regulatory imposed by current abilities of the technical client and scientific community. Performance application. community. evaluations allow us to decide how well the b. Dispersion model estimates, especially c. To improve the basis for decision- model simulates the average temporal and with the support of measured air quality making, EPA has developed and is spatial patterns seen in the observations, and data, are the preferred basis for air quality continuing to study procedures for employ large spatial/temporal scale data sets demonstrations. Nevertheless, there are determining the accuracy of models, (e.g., national data sets). Performance instances where the performance of quantifying the uncertainty, and expressing evaluations also allow determination of recommended dispersion modeling confidence levels in decisions that are made 126 127 relative performance of a model in techniques, by comparison with observed air concerning emissions controls. comparison with alternative modeling quality data, may be shown to be less than However, work in this area involves systems. Diagnostic evaluations allow acceptable. Also, there may be no ‘‘breaking new ground’’ with slow and determination of a model capability to recommended modeling procedure suitable sporadic progress likely. As a result, it may simulate individual processes that affect the for the situation. In these instances, emission be necessary to continue using the ‘‘best results, and usually employ smaller spatial/ limitations may be established solely on the estimate’’ until sufficient technical progress temporal scale date sets (e.g., field studies). basis of observed air quality data as would has been made to meaningfully implement Diagnostic evaluations allow us to decide if be applied to a modeling analysis. The same such concepts dealing with uncertainty. we get the right answer for the right reason. care should be given to the analyses of the 9.1.4 Evaluation of Models The objective comparison of modeled air quality data as would be applied to a a. A number of actions have been taken to concentrations with observed field data modeling analysis. ensure that the best model is used correctly provides only a partial means for assessing c. The current NAAQS for SO2 and CO are for each regulatory application and that a model performance. Due to the limited both stated in terms of a concentration not to model is not arbitrarily imposed. First, the supply of evaluation data sets, there are be exceeded more than once a year. There is Guideline clearly recommends the most severe practical limits in assessing model only an annual standard for NO2 and a appropriate model be used in each case. performance. For this reason, the conclusions quarterly standard for Pb. Standards for fine Preferred models, based on a number of reached in the science peer reviews and the particulate matter (PM–2.5) are expressed in factors, are identified for many uses. General supportive analyses have particular relevance terms of both long-term (annual) and short- guidance on using alternatives to the in deciding whether a model will be useful term (daily) averages. The long-term standard preferred models is also provided. Second, for its intended purposes. is calculated using the three year average of the models have been subjected to a c. To extend information from diagnostic the annual averages while the short-term systematic performance evaluation and a and performance evaluations, sensitivity and standard is calculated using the three year peer scientific review. Statistical uncertainty analyses are encouraged since average of the 98th percentile of the daily

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average concentration. For PM–10, the d. Regional Offices should require permit highly desirable. The design of the network, convention is to compare the arithmetic applicants to incorporate the pollutant the number, type and location of the mean, averaged over 3 consecutive years, contributions of all sources into their monitors, the sampling period, averaging with the concentration specified in the analysis. Where necessary this may include time as well as the need for meteorological NAAQS (50 µg/m3). The 24-hour NAAQS emissions associated with growth in the area monitoring or the use of mobile sampling or (150 µg/m3) is met if, over a 3-year period, of impact of the new or modified source. PSD plume tracking techniques, should all be there is (on average) no more than one air quality assessments should consider the specified in the protocol and agreed upon exceedance per year. As noted in subsection amount of the allowable air quality prior to start-up of the network. 7.2.1.1, the modeled compliance for this increment that has already been consumed 10.2.3 Emission Limits NAAQS is based on the highest 6th highest by other sources. Therefore, the most recent concentration over 5 years. For ozone the source applicant should model the existing 10.2.3.1 Design Concentrations short term 1-hour standard is expressed in or permitted sources in addition to the one a. Emission limits should be based on terms of an expected exceedance limit while currently under consideration. This would concentration estimates for the averaging the short term 8-hour standard is expressed permit the use of newly acquired data or time that results in the most stringent control in terms of a three year average of the annual improved modeling techniques if such have requirements. The concentration used in fourth highest daily maximum 8-hour value. become available since the last source was specifying emission limits is called the The NAAQS are subjected to extensive permitted. When remodeling, the worst case design value or design concentration and is review and possible revision every 5 years. used in the previous modeling analysis a sum of the concentration contributed by the d. This section discusses general should be one set of conditions modeled in primary source, other applicable sources, requirements for concentration estimates and the new analysis. All sources should be identifies the relationship to emission limits. and—for NAAQS assessments—the modeled for each set of meteorological background concentration. The following recommendations apply to: (1) conditions selected. Revisions of State Implementation Plans and b. To determine the averaging time for the 10.2.2 Use of Measured Data in Lieu of (2) the review of new sources and the design value, the most restrictive NAAQS or Model Estimates prevention of significant deterioration (PSD). PSD increment, as applicable, should be a. Modeling is the preferred method for identified. For a NAAQS assessment, the 10.2 Recommendations determining emission limitations for both averaging time for the design value is 10.2.1 Analysis Requirements new and existing sources. When a preferred determined by calculating, for each averaging time, the ratio of the difference between the a. Every effort should be made by the model is available, model results alone applicable NAAQS (S) and the background Regional Office to meet with all parties (including background) are sufficient. concentration (B) to the (model) predicted involved in either a SIP revision or a PSD Monitoring will normally not be accepted as permit application prior to the start of any the sole basis for emission limitation. In concentration (P) (i.e., (S–B)/P). For a PSD work on such a project. During this meeting, some instances when the modeling technique increment assessment, the averaging time for a protocol should be established between the available is only a screening technique, the the design value is determined by preparing and reviewing parties to define the addition of air quality data to the analysis calculating, for each averaging time, the ratio procedures to be followed, the data to be may lend credence to model results. of the applicable PSD increment (I) and the collected, the model to be used, and the b. There are circumstances where there is model-predicted concentration (P) (i.e., I/P). analysis of the source and concentration data. no applicable model, and measured data may The averaging time with the lowest ratio An example of requirements for such an need to be used. However, only in the case identifies the most restrictive standard or effort is contained in the Air Quality of a NAAQS assessment for an existing increment. If the annual average is the most Analysis Checklist posted on EPA’s Internet source should monitoring data alone be a restrictive, the highest estimated annual SCRAM Web site (subsection 2.3). This basis for emission limits. In addition, the average concentration from one or a number checklist suggests the level of detail required following items (i–vi) should be considered of years of data is the design value. When to assess the air quality resulting from the prior to the acceptance of the measured data: short term standards are most restrictive, it proposed action. Special cases may require i. Does a monitoring network exist for the may be necessary to consider a broader range additional data collection or analysis and this pollutants and averaging times of concern? of concentrations than the highest value. For should be determined and agreed upon at ii. Has the monitoring network been example, for pollutants such as SO2, the this preapplication meeting. The protocol designed to locate points of maximum highest, second-highest concentration is the should be written and agreed upon by the concentration? design value. For pollutants with statistically parties concerned, although a formal legal iii. Do the monitoring network and the data based NAAQS, the design value is found by document is not intended. Changes in such reduction and storage procedures meet EPA determining the more restrictive of: (1) The a protocol are often required as the data monitoring and quality assurance short-term concentration over the period collection and analysis progresses. However, requirements? specified in the standard, or (2) the long-term the protocol establishes a common iv. Do the data set and the analysis allow concentration that is not expected to exceed understanding of the requirements. impact of the most important individual the long-term NAAQS. Determination of b. An air quality analysis should begin sources to be identified if more than one design values for PM–10 is presented in more with a screening model to determine the source or emission point is involved? detail in EPA guidance.34 potential of the proposed source or control v. Is at least one full year of valid ambient 10.2.3.2 NAAQS Analyses for New or strategy to violate the PSD increment or data available? Modified Sources NAAQS. For traditional stationary sources, vi. Can it be demonstrated through the EPA guidance 24 should be followed. comparison of monitored data with model a. For new or modified sources predicted Guidance is also available for mobile results that available models are not to have a significant ambient impact 83 and to sources.48 applicable? be located in areas designated attainment or c. If the concentration estimates from c. The number of monitors required is a unclassifiable for the SO2, Pb, NO2, or CO screening techniques indicate a significant function of the problem being considered. NAAQS, the demonstration as to whether the impact or that the PSD increment or NAAQS The source configuration, terrain source will cause or contribute to an air may be approached or exceeded, then a more configuration, and meteorological variations quality violation should be based on: (1) The refined modeling analysis is appropriate and all have an impact on number and placement highest estimated annual average the model user should select a model of monitors. Decisions can only be made on concentration determined from annual according to recommendations in Sections 4– a case-by-case basis. Guidance is available for averages of individual years; or (2) the 8. In some instances, no refined technique establishing criteria for demonstrating that a highest, second-highest estimated may be specified in this guide for the model is not applicable? concentration for averaging times of 24-hours situation. The model user is then encouraged d. Sources should obtain approval from the or less; and (3) the significance of the spatial to submit a model developed specifically for appropriate reviewing authority (paragraph and temporal contribution to any modeled the case at hand. If that is not possible, a 3.0(b)) for the monitoring network prior to violation. For Pb, the highest estimated screening technique may supply the needed the start of monitoring. A monitoring concentration based on an individual results. protocol agreed to by all concerned parties is calendar quarter averaging period should be

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used. Background concentrations should be 11.0 Bibliography a 1980, Raleigh, NC. Bulletin of the American added to the estimated impact of the source. American Meteorological Society. Meteorological Society, 62(2): 255–261. The most restrictive standard should be used Symposia on Turbulence, Diffusion, and Air Hunt, J.C.R., R.G. Holroyd, D.J. Carruthers, in all cases to assess the threat of an air Pollution (1st–10th); 1971–1992. Symposia A.G. Robins, D.D. Apsley, F.B. Smith and D.J. quality violation. For new or modified on Boundary Layers & Turb. 11th–12th; Thompson, 1990. Developments in Modeling sources predicted to have a significant 1995–1997. Boston, MA. Air Pollution for Regulatory Uses. In ambient impact 83 in areas designated American Meteorological Society, 1977– Proceedings of the 18th NATO/CCMS attainment or unclassifiable for the PM–10 1998. 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Ellis once per year, on average; (2) the expected Horwood Limited, Chichester, West Sussex, (i.e., average) annual mean concentration will 1025–1026. American Meteorological Society, 1981. England, 438pp. exceed the annual NAAQS; and (3) the Randerson, D., Ed., 1984. Atmospheric source contributes significantly, in a Air Quality Modeling and the Clean Air Act: Recommendations to EPA on Dispersion Science and Power Production. DOE/TIC temporal and spatial sense, to any modeled Modeling for Regulatory Applications. 2760l. Office of Scientific and Technical violation. Boston, MA. Information, U.S. Department of Energy, Oak 10.2.3.3 PSD Air Quality Increments and Briggs, G.A., 1969. Plume Rise. U.S. Ridge, TN. Impacts Atomic Energy Commission Critical Review Scire, J.S. and L.L. Schulman, 1980: Modeling plume rise from low-level buoyant a. The allowable PSD increments for Series, Oak Ridge National Laboratory, Oak line and point sources. AMS/APCA Second criteria pollutants are established by Ridge, TN. Joint Conference on Applications of Air regulation and cited in 40 CFR 51.166. These Drake, R.L. and S.M. Barrager, 1979. Pollution Meteorology, March 24–27, New maximum allowable increases in pollutant Mathematical Models for Atmospheric Pollutants. EPRI EA–1131. Electric Power Orleans, LA. concentrations may be exceeded once per Research Institute, Palo Alto, CA. Smith, M.E., Ed., 1973. Recommended year at each site, except for the annual Environmental Protection Agency, 1978. Guide for the Prediction of the Dispersion of increment that may not be exceeded. The Workbook for Comparison of Air Quality Airborne Effluents. The American Society of highest, second-highest increase in estimated Models. Publication No. EPA–450/2–78–028a Mechanical Engineers, New York, NY. concentrations for the short term averages as and b. Office of Air Quality Planning & Stern, A.C., Ed., 1976. Air Pollution, Third determined by a model should be less than Standards, Research Triangle Park, NC. Edition, Volume I: Air Pollutants, Their or equal to the permitted increment. The Erisman J.W., Van Pul A. and Wyers P. Transformation and Transport. Academic modeled annual averages should not exceed (1994) Parameterization of surface resistance Press, New York, NY. the increment. for the quantification of atmospheric Turner, D.B., 1979. Atmospheric b. Screening techniques defined in deposition of acidifying pollutants and Dispersion Modeling: A Critical Review. subsection 4.2.1 can sometimes be used to ozone. Atmos. Environ., 28: 2595–2607. Journal of the Air Pollution Control estimate short term incremental Fox, D.G., and J.E. Fairobent, 1981. NCAQ Association, 29(5): 502–519. concentrations for the first new source that Panel Examines Uses and Limitations of Air Venkatram, A. and J.C. Wyngaard, Editors, triggers the baseline in a given area. Quality Models. Bulletin of the American 1988. Lectures on Air Pollution Modeling. However, when multiple increment- Meteorological Society, 62(2): 218–221. American Meteorological Society, Boston, consuming sources are involved in the Gifford, F.A., 1976. Turbulent Diffusion MA. 390pp. calculation, the use of a refined model with Typing Schemes: A Review. Nuclear Safety, 12.0 References at least 1 year of site specific or 5 years of 17(1): 68–86. (off-site) NWS data is normally required Gudiksen, P.H., and M.H. Dickerson, Eds., 1. Code of Federal Regulations; Title 40 (subsection 8.3.1.2). In such cases, sequential Executive Summary: Atmospheric Studies in (Protection of Environment). Sections 51.112, modeling must demonstrate that the Complex Terrain Technical Progress Report 51.117, 51.150, 51.160. allowable increments are not exceeded FY–1979 Through FY–1983. Lawrence 2. Environmental Protection Agency, 1990. temporally and spatially, i.e., for all receptors Livermore National Laboratory, Livermore, New Source Review Workshop Manual: for each time period throughout the year(s) CA. (Docket Reference No. II–I–103). Prevention of Significant Deterioration and (time period means the appropriate PSD Hanna, S.R., G.A. Briggs, J. Deardorff, B.A. Nonattainment Area Permitting (Draft). Office averaging time, e.g., 3-hour, 24-hour, etc.). Egan, G.A. Gifford and F. Pasquill, 1977. of Air Quality Planning & Standards, c. The PSD regulations require an AMS Workshop on Stability Classification Research Triangle Park, NC. (Available at: Schemes And Sigma Curves—Summary of http://www.epa.gov/ttn/nsr/) estimation of the SO2, particulate matter Recommendations. Bulletin of the American 3. Code of Federal Regulations; Title 40 (PM–10), and NO2 impact on any Class I area. Normally, steady-state Gaussian plume Meteorological Society, 58(12): 1305–1309. (Protection of Environment). Sections 51.166 models should not be applied at distances Hanna, S.R., G.A. Briggs and R.P. Hosker, and 52.21. greater than can be accommodated by the Jr., 1982. Handbook on Atmospheric 4. Code of Federal Regulations (Title 40, Part 50): Protection of the Environment; steady state assumptions inherent in such Diffusion. Technical Information Center, U.S. National Primary and Secondary Ambient models. The maximum distance for refined Department of Energy, Washington, D.C. Haugen, D.A., Workshop Coordinator, Air Quality Standards. steady-state Gaussian plume model 1975. Lectures on Air Pollution and 5. Environmental Protection Agency, 1988. application for regulatory purposes is Environmental Impact Analyses. Sponsored Model Clearinghouse: Operational Plan generally considered to be 50km. Beyond the by the American Meteorological Society, (Revised). Staff Report. Office of Air Quality 50km range, screening techniques may be Boston, MA. Planning & Standards, Research Triangle used to determine if more refined modeling Hoffnagle, G.F., M.E. Smith, T.V. Crawford Park, NC. (Docket No. A–88–04, II–J–1) is needed. If refined models are needed, long and T.J. Lockhart, 1981. On-site 6. Environmental Protection Agency, 1980. range transport models should be considered Meteorological Instrumentation Guidelines on Air Quality Models. Federal in accordance with subsection 6.2.3. As Requirements to Characterize Diffusion from Register, 45(61): 20157–20158. previously noted in Sections 3 and 7, the Point Sources—A Workshop, 15–17 January 7. Scire, J.S. and L.L. Schulman, 1981. need to involve the Federal Land Manager in Evaluation of the BLP and ISC Models with decisions on potential air quality impacts, a The documents listed here are major sources of SF6 Tracer Data and SO2 Measurements at particularly in relation to PSD Class I areas, supplemental information on the theory and Aluminum Reduction Plants. APCA cannot be overemphasized. application of mathematical air quality models. Specialty Conference on Dispersion

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Evaluation of the CALPUFF Formulation and Boundary Layer 1987. PM–10 SIP Development Guideline. Dispersion Model with Two Power Plant Characterization. Journal of Applied Publication No. EPA–450/2–86–001. Office of Data Sets. Tenth Joint Conference on the Meteorology, 44(5): 682–693. Air Quality Planning & Standards, Research Application of Air Pollution Meteorology, 23. L.L. Schulman, D.G. Strimaitis and J.S. Triangle Park, NC. (NTIS No. PB 87–206488) Phoenix, Arizona. American Meteorological Scire, 2002. Development and evaluation of 35. U.S. Forest Service, 1996. User Society, Boston, MA. January 11–16, 1998. the PRIME plume rise and building Assessment of Smoke-Dispersion Models for 10. Environmental Protection Agency, downwash model. Journal of the Air & Waste Wildland Biomass Burning. USDA, Pacific 2003. AERMOD: Latest Features and Management Association, 50: 378–390. Northwest Research Station, Portland, OR. Evaluation Results. Publication No. EPA– 24. Environmental Protection Agency, General Technical Report PNW–GTR–379. 454/R–03–003. U.S. Environmental 1992. Screening Procedures for Estimating 30pp. (NTIS No. PB 97–163380) Protection Agency, Research Triangle Park, the Air Quality Impact of Stationary Sources, 36. Hanrahan, P.L., 1999. The Polar NC. (Available at http://www.epa.gov/ Revised. Publication No. EPA–454/R–92– Volume Polar Ratio Method for Determining scram001/) 019. U.S. Environmental Protection Agency, NO2 / NOX Ratios in Modeling—Part I: 11. Fox, D.G., 1981. Judging Air Quality Research Triangle Park, NC. (NTIS No. PB Methodology. J. Air & Waste Manage. Assoc., Model Performance. Bulletin of the American 93–219095) 49: 1324–1331. Meteorological Society, 62(5): 599–609. 25. Environmental Protection Agency, 37. Environmental Protection Agency, 12. American Meteorological Society, 1983. 1995. SCREEN3 User’s Guide. Publication 1997. Guidance for Siting Ambient Air Synthesis of the Rural Model Reviews. No. EPA–454/B–95–004. U.S. Environmental Monitors around Stationary Lead Sources. Publication No. EPA–600/3–83–108. Office of Protection Agency, Research Triangle Park, Publication No. EPA–454/R–92–009R. Office Research & Development, Research Triangle NC. (NTIS No. PB 95–222766) of Air Quality Planning & Standards, Park, NC. (NTIS No. PB 84–121037) 26. Perry, S.G., D.J. Burns and A.J. Research Triangle Park, NC. (NTIS No. PB 13. Allwine, K.J., W.F. Dabberdt and L.L. Cimorelli, 1990. User’s Guide to CTDMPLUS: 97–208094) Simmons. 1998. Peer Review of the Volume 2. The Screening Mode (CTSCREEN). 38. Environmental Protection Agency, CALMET/CALPUFF Modeling System. Publication No. EPA–600/8–90–087. U.S. 1993. Lead Guideline Document. Publication Prepared by the KEVRIC Company, Inc. Environmental Protection Agency, Research No. EPA–452/R–93–009. Office of Air under EPA Contract No. 68–D–98–092 for Triangle Park, NC. (NTIS No. PB 91–136564) Quality Planning & Standards, Research Environmental Protection Agency, Research 27. Mills, M.T., R.J. Paine, E.A. Insley and Triangle Park, NC. (NTIS No. PB 94–111846) Triangle Park, NC. (Docket No. A–99–05, II– B.A. Egan, 1987. The Complex Terrain 39. Environmental Protection Agency, A–8) Dispersion Model Terrain Preprocessor 1998. EPA Third-Generation Air Quality 14. Hanna, S., M. Garrison and B. Turner, System—User’s Guide and Program Modeling System. Models-3, Volume 9b: 1998. AERMOD Peer Review report. Prepared Description. Publication No. EPA–600/8–88– User Manual. Publication No. EPA–600/R– by SAI, Inc. under EPA Contract No. 68–D6– 003. U.S. Environmental Protection Agency, 98/069(b). Office of Research and 0064/1–14 for Environmental Protection Research Triangle Park, NC. (NTIS No. PB Development, Washington, D.C. Agency, Research Triangle Park, NC. 12pp. & 88–162094) 40. Gery, M.W. and R.R. Crouse, 1991. appendices (Docket No. A–99–05, II–A–6) 28. Burns, D.J., S.G. Perry and A.J. User’s Guide for Executing OZIPR. 15. Environmental Protection Agency, Cimorelli, 1991. An Advanced Screening Publication No. EPA–600/8–90–069. Office of 1992. Protocol for Determining the Best Model for Complex Terrain Applications. Research & Development, Research Triangle Performing Model. Publication No. EPA–454/ Paper presented at the 7th Joint Conference Park, NC. (NTIS No. PB 91–175877) R–92–025. Office of Air Quality Planning & on Applications of Air Pollution Meteorology 41. Environmental Protection Agency, Standards, Research Triangle Park, NC. (NTIS (cosponsored by the American 2002. User’s Guide to the Regulatory No. PB 93–226082) Meteorological Society and the Air & Waste Modeling System for Aerosols and 16. ASTM D6589: Standard Guide for Management Association), January 13–18, Deposition (REMSAD) Version 7. Prepared Statistical Evaluation of Atmospheric 1991, New Orleans, LA. for Environmental Protection Agency under Dispersion Model Performance. (2000) 29. Environmental Research and Contract No. GS–10F–0124J by ICF 17. Environmental Protection Agency, Technology, 1987. User’s Guide to the Rough Consulting, July 2002. (Available at http:// 1995. User’s Guide for the Industrial Source Terrain Diffusion Model (RTDM), Rev. 3.20. www.epa.gov/scram001/) Complex (ISC3) Dispersion Models, Volumes ERT Document No. P–D535–585. 42. Environmental Protection Agency, 1 and 2. Publication Nos. EPA–454/B–95– Environmental Research and Technology, 2004. EPA–CMB8.2 Users Manual. 003a & b. U.S. Environmental Protection Inc., Concord, MA. (NTIS No. PB 88–171467) Publication No. EPA–452/R–04–011. Office Agency, Research Triangle Park, NC. (NTIS 30. Meng, Z.D. Dabdub and J.H. Seinfeld, of Air Quality Planning & Standards, Nos. PB 95–222741 and PB 95–222758, 1997. 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Meteorol., 58, 229–259. Other Analyses in Attainment 44. Environmental Protection Agency, 20. Hanna, S.R. and J.C. Chang, 1993. Demonstrations for the 8-hr Ozone NAAQS 1988. Chemical Mass Balance Model Hybrid Plume Dispersion Model (HPDM) (Draft Final). Office of Air Quality Planning Diagnostics. Publication No. EPA–450/4–88– Improvements and Testing at Three Field & Standards, Research Triangle Park, NC. 005. Office of Air Quality Planning & Sites. Atmos. Environ., 27A: 1491–1508. (Latest version available on SCRAM Web site Standards, Research Triangle Park, NC. (NTIS 21. American Meteorological Society, 1984. as draft-final-O3.pdf; see subsection 2.3) No. PB 88–208319) Workshop on Updating Applied Diffusion 33. Environmental Protection Agency, 45. Paatero, P. and U. Tapper, 1994. Models. 24–27 January 1984. Clearwater, 2005. Guidance on the Use of Models and Positive Matrix Factorization: A Non-

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negative Factor Model with Optimal Sources on Annual NO2 Concentrations. 3–85–022. Office of Research & Development, Utilization of Error Estimates of Data Values. Proceedings, 84th Annual Meeting & Research Triangle Park, NC. (NTIS No. PB Environmetrics, 5: 111–126. (Other Exhibition of the Air & Waste Management 85–203107) documents related to PMF may be accessed Association, Vancouver, B.C.; 16–21 June 68. Bennett, M.J, M.E. Yansura, I.G. via FTP at ftp://rock.helsinki.fi/pub/misc/ 1991. (16pp.) (Docket No. A–92–65, II–A–9) Hornyik, J.M. Nall, D.G. Caniparoli and C.G. pmf.) 57. Cole, H.S. and J.E. Summerhays, 1979. Ashmore, 2002. Evaluation of the CALPUFF 46. Lewis, C.W., G.A. Norris, R.C. Henry A Review of Techniques Available for Long-range Transport Screening Technique and T.L. Conner, 2003. Source Estimation of Short-Term NO2 by Comparison to Refined CALPUFF Results Apportionment of Phoenix PM–2.5 Aerosol Concentrations. Journal of the Air Pollution for Several Power Plants in Both the Eastern with the Unmix Receptor Model. Journal of Control Association, 29(8): 812–817. and Western United States. Proceedings of the Air & Waste Management Association, 58. U.S. Department of Housing and Urban the Air & Waste Management Association’s 53(3): 325–338. Development, 1980. Air Quality 95th Annual Conference, June 23–27, 2002; 47. Environmental Protection Agency, Considerations in Residential Planning. U.S. Baltimore, MD. Paper #43454. 1994. Guidelines for PM10 Sampling and Superintendent of Documents, Washington, 69. Environmental Protection Agency, Analysis Applicable to Receptor Modeling. DC. (GPO Order Nos. 023–000–00577–8, 1999. Guideline of Data Handling Publication No. EPA–452/R–94–009. Office 023–000–00576–0, 023–000–00575–1) Conventions for the PM NAAQS. Publication of Air Quality Planning & Standards, 59. Environmental Protection Agency, No. EPA–454/R–99–008. Office of Air Research Triangle Park, NC. (NTIS No. PB 1986. Evaluation of Short-Term Long-Range Quality Planning & Standards, Research 94–177441) Transport Models, Volumes I and II. Triangle Park. (NTIS PB 99–149023) 48. Environmental Protection Agency, Publication Nos. EPA–450/4–86–016a and b. 70. Turner, D.B., 1969. Workbook of 1992. Guideline for Modeling Carbon Office of Air Quality Planning & Standards, Atmospheric Dispersion Estimates. PHS Monoxide from Roadway Intersections. Research Triangle Park, NC. (NTIS Nos. PB Publication No. 999–AP–26. U.S. Department Publication No. EPA–454/R–92–005. Office 87–142337 and PB 87–142345) of Health, Education and Welfare, Public of Air Quality Planning & Standards, 60. Environmental Protection Agency, Health Service, Cincinnati, OH. (NTIS No. Research Triangle Park, NC. (NTIS No. PB 1998. Interagency Workgroup on Air Quality PB–191482) 93–210391) Modeling (IWAQM) Phase 2 Summary Report 71. McElroy, J.L. and F. Pooler, Jr., 1968. 49. Environmental Protection Agency, and Recommendations for Modeling Long- St. Louis Dispersion Study, Volume II— 1992. User’s Guide for CAL3QHC Version 2: Range Transport Impacts. Publication No. Analysis. National Air Pollution Control A Modeling Methodology for Predicting EPA–454/R–98–019. Office of Air Quality Administration Publication No. AP–53, U.S. Pollutant Concentrations near Roadway Planning & Standards, Research Triangle Department of Health, Education and Intersections. Publication No. EPA–454/R– Park, NC.(NTIS No. PB 99–121089) Welfare, Public Health Service, Arlington, 92–006. Office of Air Quality Planning & 61. National Acid Precipitation Assessment VA. (NTIS No. PB–190255) Standards, Research Triangle Park, NC. (NTIS Program (NAPAP), 1991. Acid Deposition: 72. Irwin, J.S., 1978. Proposed Criteria for No. PB 93–210250) State of Science and Technology. Volume III Selection of Urban Versus Rural Dispersion 50. Environmental Protection Agency, Terrestrial, Materials, Health and Visibility Coefficients. (Draft Staff Report). Meteorology 1992. Evaluation of CO Intersection Modeling Effects. Report 24, Visibility: Existing and and Assessment Division, U.S. techniques Using a New York City Database. Historical Conditions—Causes and Effects Environmental Protection Agency, Research Publication No. EPA–454/R–92–004. Office Edited by Patricia M. Irving. Washington, DC Triangle Park, NC. (Docket No. A–80–46, II- of Air Quality Planning & Standards, RTP, 129pp. B–8) NC 27711. (NTIS No. PB 93–105559) 62. National Research Council, 1993. 73. Auer, Jr., A.H., 1978. Correlation of 51. Environmental Protection Agency, Protecting Visibility in National Parks and Land Use and Cover with Meteorological 1995. Addendum to the User’s Guide to Wilderness Areas. National Academy Press, Anomalies. Journal of Applied Meteorology, CAL3QHC Version 2.0. Staff Report. Office of Washington, DC 446pp. 17(5): 636–643. Air Quality Planning & Standards, Research 63. Environmental Protection Agency, 74. Pasquill, F., 1976. Atmospheric Triangle Park, NC. (Available at http:// 1992. Workbook for Plume Visual Impact Dispersion Parameters in Gaussian Plume www.epa.gov/scram001/) Screening and Analysis (Revised). Modeling, Part II. Possible Requirements for 52. Shannon, J.D., 1987. Mobile Source Publication No. EPA–454/R–92–023. Office Change in the Turner Workbook Values. Modeling Review. A report prepared under a of Air Quality Planning & Standards, Publication No. EPA–600/4–76–030b. Office cooperative agreement with the Research Triangle Park, NC. (NTIS No. PB of Research & Development, Research Environmental Protection Agency. 5pp. 93–223592) Triangle Park, NC. (NTIS No. PB–258036/ (Docket No. A–88–04, II–J–2) 64. Environmental Protection Agency, 3BA) 53. Environmental Protection Agency, 1981. Guideline for Use of Fluid Modeling to 75. Turner, D.B., 1964. A Diffusion Model 1991. Emission Inventory Requirements for Determine Good Engineering Practice (GEP) for an Urban Area. Journal of Applied Carbon Monoxide State Implementation Stack Height. Publication No. EPA–450/4– Meteorology, 3(1): 83–91. Plans. Publication No. EPA–450/4–91–011. 81–003. Office of Air Quality Planning & 76. Briggs, G.A., 1975. Plume Rise Office of Air Quality Planning & Standards, Standards, Research Triangle Park, NC. (NTIS Predictions. Chapter 3 in Lectures on Air Research Triangle Park, NC. (NTIS No. PB No. PB 82–145327) Pollution and Environmental Impact 92–112150) 65. Lawson, Jr., R.E. and W.H. Snyder, Analyses. American Meteorological Society, 54. Environmental Protection Agency, 1983. Determination of Good Engineering Boston, MA; pp. 59–111. 1992. Guideline for Regulatory Application Practice Stack Height: A Demonstration 77. Hanna, S.R., G.A. Briggs and R.P. of the Urban Airshed Model for Areawide Study for a Power Plant. Publication No. Hosker, Jr., 1982. Plume Rise. Chapter 2 in Carbon Monoxide. Publication No. EPA–450/ EPA–600/3–83–024. Office of Research & Handbook on Atmospheric Diffusion. 4–92–011a and b. Office of Air Quality Development, Research Triangle Park, NC. Technical Information Center, U.S. Planning & Standards, Research Triangle (NTIS No. PB 83–207407) Department of Energy, Washington, DC; pp. Park, NC. (NTIS Nos. PB 92–213222 and PB 66. Environmental Protection Agency, 11–24. DOE/TIC–11223 (DE 82002045) 92–213230) 1985. Guideline for Determination of Good 78. Weil, J.C., L.A. Corio and R.P. Brower, 55. Environmental Protection Agency, Engineering Practice Stack Height (Technical 1997. A PDF dispersion model for buoyant 1992. Technical Support Document to Aid Support Document for the Stack Height plumes in the convective boundary layer. States with the Development of Carbon Regulations), Revised. Publication No. EPA– Journal of Applied Meteorology, 36: 982– Monoxide State Implementation Plans. 450/4–80–023R. Office of Air Quality 1003. Publication No. EPA–452/R–92–003. Office Planning & Standards, Research Triangle 79. Stull, R.B., 1988. An Introduction to of Air Quality Planning & Standards, Park, NC. (NTIS No. PB 85–225241) Boundary Layer Meteorology. Kluwer Research Triangle Park, NC. (NTIS No. PB 67. Snyder, W.H. and R.E. Lawson, Jr., Academic Publishers, Boston, MA. 666pp. 92–233055) 1985. Fluid Modeling Demonstration of Good 80. Environmental Protection Agency, 56. Chu, S.H. and E.L. Meyer, 1991. Use of Engineering-Practice Stack Height in 1988. User’s Guide to SDM—A Shoreline Ambient Ratios to Estimate Impact of NOX Complex Terrain. Publication No. EPA–600/ Dispersion Model. Publication No. EPA–450/

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4–88–017. Office of Air Quality Planning & Can be ordered from NOAA National Data 104. Environmental Protection Agency, Standards, Research Triangle Park, NC. (NTIS Center’s Internet Web site at http:// 1996. Meteorological Processor for No. PB 89–164305) lwf.ncdc.noaa.gov/oa/ncdc.html Regulatory Models (MPRM) User’s Guide. 81. Environmental Protection Agency, 92. Environmental Protection Agency, Publication No. EPA–454/B–96–002. Office 1987. Analysis and Evaluation of Statistical 2000. Meteorological Monitoring Guidance of Air Quality Planning & Standards, Coastal Fumigation Models. Publication No. for Regulatory Modeling Applications. Research Triangle Park, NC. (NTIS No. PB EPA–450/4–87–002. Office of Air Quality Publication No. EPA–454/R–99–005. Office 96–180518) Planning & Standards, Research Triangle of Air Quality Planning & Standards, 105. Paine, R.J., 1987. User’s Guide to the Park, NC. (NTIS No. PB 87–175519) Research Triangle Park, NC. (PB 2001– CTDM Meteorological Preprocessor Program. 82. Environmental Protection Agency, 103606) (Available at http://www.epa.gov/ Publication No. EPA–600/8–88–004. Office of 1995. Compilation of Air Pollutant Emission scram001/) Research & Development, Research Triangle Factors, Volume I: Stationary Point and Area 93. ASTM D5527: Standard Practice for Park, NC. (NTIS No. PB 88–162102) Sources (Fifth Edition, AP–42: GPO Stock Measuring Surface Winds and Temperature 106. Scire, J.S., F.R. Francoise, M.E. Fernau No. 055–000–00500–1), and Supplements A– by Acoustic Means. (1994) and R.J. Yamartino, 1998. A User’s Guide for D; Volume II: Mobile Sources (Fifth Edition). 94. ASTM D5741: Standard Practice for the CALMET Meteorological Model (Version Office of Air Quality Planning & Standards, Characterizing Surface Wind Using Wind 5.0). Earth Tech, Inc., Concord, MA. (http:// Research Triangle Park, NC. Volume I can be Vane and Rotating Anemometer. (1996) www.src.com/calpuff/calpuff1.htm) downloaded from EPA’s Internet Web site at 95. Environmental Protection Agency, 107. Environmental Protection Agency, http://www.epa.gov/ttn/chief/ap42.html; 1995. Quality Assurance for Air Pollution 1984. Calms Processor (CALMPRO) User’s Volume II can be downloaded from http:// Measurement Systems, Volume IV— Guide. Publication No. EPA–901/9–84–001. www.epa.gov/omswww/ap42.htm Meteorological Measurements. Publication Office of Air Quality Planning & Standards, 83. Environmental Protection Agency, No. EPA600/R–94/038d. Office of Air Quality Region I, Boston, MA. (NTIS No. PB 84– 1987. Ambient Air Monitoring Guidelines for Planning & Standards, Research Triangle 229467) Prevention of Significant Deterioration (PSD). Park, NC. Note: for copies of this handbook, 108. Fox, D.G., 1984. Uncertainty in air Publication No. EPA–450/4–87–007. Office of you may make inquiry to ORD Publications, quality modeling. Bulletin of the American Air Quality Planning & Standards, Research 26 West Martin Luther King Dr., Cincinatti, Meteorological Society, 65(1): 27–36. Triangle Park, NC. (NTIS No. PB 90–168030) OH 45268. Phone (513) 569–7562 or (800) 109. Burton, C.S., 1981. The Role of 84. Stauffer, D.R. and Seaman, N.L., 1990. 490–9198 (automated request line) Atmospheric Models in Regulatory Decision- Use of four-dimensional data assimilation in 96. Bowen, B.M., J.M. Dewart and A.I. Making: Summary Report. Systems a limited-area mesoscale model. Part I: Chen, 1983. Stability Class Determination: A Applications, Inc., San Rafael, CA. Prepared Experiments with synoptic-scale data. Comparison for One Site. Proceedings, Sixth under contract No. 68–01–5845 for U.S. Environmental Protection Agency, Research Monthly Weather Review, 118: 1250–1277. Symposium on Turbulence and Diffusion. Triangle Park, NC. (Docket No. A–80–46, 85. Stauffer, D.R., N.L. Seaman and F.S. American Meteorological Society, Boston, II–M–6) Binkowski, 1991. Use of four-dimensional MA; pp. 211–214. (Docket No. A–92–65, 110. Environmental Protection Agency, data assimilation in a limited-area mesoscale II–A–7) 1981. Proceedings of the Second Conference model. Part II: Effect of data assimilation 97. Environmental Protection Agency, on Air Quality Modeling, Washington, DC. within the planetary boundary layer. Monthly 1993. An Evaluation of a Solar Radiation/ Office of Air Quality Planning & Standards, Weather Review, 119: 734–754. Delta-T (SRDT) Method for Estimating Research Triangle Park, NC. (Docket No. A– 86. Grell, G.A., J. Dudhia, and D.R. Pasquill-Gifford (P–G) Stability Categories. 80–46, Stauffer, 1994. A Description of the Fifth- Publication No. EPA–454/R–93–055. Office II–M–16) Generation Penn State/NCAR Mesoscale of Air Quality Planning & Standards, 111. Hanna, S.R., 1989. Confidence limits Model (MM5). NCAR Technical Note, NCAR/ Research Triangle Park, NC. (NTIS No. PB for air quality model evaluations, as TN–398+STR, National Center for 94–113958) estimated by bootstrap and jackknife Atmospheric Research, Boulder, CO; 138pp. 98. Irwin, J.S., 1980. Dispersion Estimate resampling methods. Atmospheric http://www.mmm.ucar.edu/mm5/mm5- Suggestion #8: Estimation of Pasquill Environment, 23(6): 1385–1398. home.html Stability Categories. Office of Air Quality 112. Cox, W.M. and J.A. Tikvart, 1990. A 87. Landsberg, H.E. and W.C. Jacobs, 1951. Planning & Standards, Research Triangle statistical procedure for determining the best Compendium of Meteorology. American Park, NC (Docket No. A–80–46, II–B–10) performing air quality simulation model. Meteorological Society, Boston, MA; pp. 99. Mitchell, Jr., A.E. and K.O. Timbre, Atmos. Environ., 24A(9): 2387–2395. 976–992. 1979. Atmospheric Stability Class from 113. Oreskes, N.K., K. Shrader-Frechette 88. Burton, C.S., T.E. Stoeckenius and J.P. Horizontal Wind Fluctuation. Presented at and K. Beliz, 1994. Verification, validation Nordin, 1983. The Temporal 72nd Annual Meeting of Air Pollution and confirmation of numerical models in the Representativeness of Short-Term Control Association, Cincinnati, OH; June earth sciences. Science, 263: 641–646. Meteorological Data Sets: Implications for Air 24–29, 1979. (Docket No. A–80–46, II–P–9) 114. Dekker, C.M., A. Groenendijk, C.J. Quality Impact Assessments. Systems 100. Smedman—Hogstrom, A. and V. Sliggers and G.K. Verboom, 1990. Quality Applications, Inc., San Rafael, CA. (Docket Hogstrom, 1978. A Practical Method for Criteria for Models to Calculate Air Pollution. No. A–80–46, II-G–11) Determining Wind Frequency Distributions Lucht (Air) 90, Ministry of Housing, Physical 89. Solar and Meteorological Surface for the Lowest 200m from Routine Planning and Environment, Postbus 450, Observation Network, 1961–1990; 3-volume Meteorological Data. J. of Applied 2260 MB Leidschendam, The Netherlands; CD–ROM. Version 1.0, September 1993. Meteorology, 17(7): 942–954. 52pp. Produced jointly by National Climatic Data 101. Smith, T.B. and S.M. Howard, 1972. 115. Weil, J.C., R.I. Sykes and A. Center and National Renewable Energy Methodology for Treating Diffusivity. MRI 72 Venkatram, 1992. Evaluating air-quality Laboratory. Can be ordered from NOAA FR–1030. Meteorology Research, Inc., models: review and outlook. Journal of National Data Center’s Internet Web site at Altadena, CA. (Docket No. A–80–46, II–P–8) Applied Meteorology, 31: 1121–1145. http://www.NNDC.NOAA.GOV/. 102. Environmental Protection Agency, 116. Cole, S.T. and P.J. Wicks, Editors 90. Hourly United States Weather 2004. User’s Guide for the AERMOD (1995): Model Evaluation Group: Report of Observations, 1990–1995 (CD–ROM). October Meteorological Preprocessor (AERMET). the Second Open Meeting. EUR 15990 EN, 1997. Produced jointly by National Climatic Publication No. EPA–454/B–03–002. U.S. European Commission, Directorate-General Data Center and Environmental Protection Environmental Protection Agency, Research XII, Environmental Research Programme, L– Agency. Can be ordered from NOAA National Triangle Park, NC. (Available at http:// 2920 Luxembourg; 77pp. Data Center’s Internet Web site at http:// www.epa.gov/scram001/) 117. Hanna, S.R., 1982. Natural Variability lwf.ncdc.noaa.gov/oa/ncdc.html 103. Environmental Protection Agency, of Observed Hourly SO2 and CO 91. Radiosonde Data of North America, 1993. PCRAMMET User’s Guide. Publication Concentrations in St. Louis. Atmospheric 1946–1996; 4-volume CD–ROM. August No. EPA–454/R–96–001. Office of Air Environment, 16(6): 1435–1440. 1996. Produced jointly by Forecast Systems Quality Planning & Standards, Research 118. Bowne, N.E., 1981. Validation and laboratory and National Climatic Data Center. Triangle Park, NC. (NTIS No. PB 97–147912) Performance Criteria for Air Quality Models.

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Appendix F in Air Quality Modeling and the A.2 Buoyant Line and Point Source 454/B–03–001. U.S. Environmental Clean Air Act: Recommendations to EPA on Dispersion Model (BLP) Protection Agency, Research Triangle Park, Dispersion Modeling for Regulatory A.3 CALINE3 NC 27711; September 2004. (Available at Applications. American Meteorological A.4 CALPUFF http://www.epa.gov/scram001/) Society, Boston, MA; pp. 159–171. (Docket A.5 Complex Terrain Dispersion Model Environmental Protection Agency, 2004. No. A–80–46, II–A–106) Plus Algorithms for Unstable Situations User’s Guide for the AERMOD 119. Bowne, N.E. and R.J. Londergan, 1983. (CTDMPLUS) Meteorological Preprocessor (AERMET). Overview, Results, and Conclusions for the A.6 Offshore and Coastal Dispersion Model Publication No. EPA–454/B–03–002. U.S. EPRI Plume Model Validation and (OCD) Environmental Protection Agency, Research Development Project: Plains Site. EPRI EA– A.REF References Triangle Park, NC 27711; November 2004. 3074. Electric Power Research Institute, Palo (Available at http://www.epa.gov/scram001/) A.0 Introduction and Availability Alto, CA. Environmental Protection Agency, 2004. 120. Moore, G.E., T.E. Stoeckenius and (1) This appendix summarizes key features User’s Guide for the AERMOD Terrain D.A. Stewart, 1982. A Survey of Statistical of refined air quality models preferred for Preprocessor (AERMAP). Publication No. Measures of Model Performance and specific regulatory applications. For each EPA–454/B–03–003. U.S. Environmental Accuracy for Several Air Quality Models. model, information is provided on Protection Agency, Research Triangle Park, Publication No. EPA–450/4–83–001. Office of availability, approximate cost (where NC 27711; October 2004. (Available at http:// Air Quality Planning & Standards, Research applicable), regulatory use, data input, www.epa.gov/scram001/) Triangle Park, NC. (NTIS No. PB 83–260810) output format and options, simulation of Schulman, L.L., D.G. Strimaitis and J.S. 121. Rhoads, R.G., 1981. Accuracy of Air atmospheric physics, and accuracy. These Scire, 2000. Development and evaluation of Quality Models. Staff Report. Office of Air models may be used without a formal the PRIME plume rise and building Quality Planning & Standards, Research demonstration of applicability provided they downwash model. Journal of the Air and Triangle Park, NC. (Docket No. A–80–46, satisfy the recommendations for regulatory Waste Management Association, 50: 378– II–G–6) use; not all options in the models are 390. necessarily recommended for regulatory use. 122. Hanna, S.R., 1993. Uncertainties in air Availability quality model predictions. Boundary-Layer (2) Many of these models have been Meteorology, 62: 3–20. subjected to a performance evaluation using The model codes and associated 123. Pasquill, F., 1974. Atmospheric comparisons with observed air quality data. documentation are available on EPA’s Diffusion, 2nd Edition. John Wiley and Sons, Where possible, several of the models Internet SCRAM Web site (Section A.0). contained herein have been subjected to New York, NY; 479pp. Abstract 124. Morgan, M.G. and M. Henrion, 1990. evaluation exercises, including (1) statistical AERMOD is a steady-state plume Uncertainty, A Guide to Dealing With performance tests recommended by the American Meteorological Society and (2) dispersion model for assessment of pollutant Uncertainty in Quantitative Risk and Policy peer scientific reviews. The models in this concentrations from a variety of sources. Analysis. Cambridge University Press. New appendix have been selected on the basis of AERMOD simulates transport and dispersion York, NY; 332pp. the results of the model evaluations, from multiple point, area, or volume sources 125. Irwin, J.S., K. Steinberg, C. experience with previous use, familiarity of based on an up-to-date characterization of the Hakkarinen and H. Feldman, 2001. the model to various air quality programs, atmospheric boundary layer. Sources may be Uncertainty in Air Quality Modeling for Risk and the costs and resource requirements for located in rural or urban areas, and receptors Calculations. (CD–ROM) Proceedings of use. may be located in simple or complex terrain. Guideline on Air Quality Models: A New (3) Codes and documentation for all AERMOD accounts for building wake effects Beginning. April 4–6, 2001, Newport, RI, Air models listed in this appendix are available (i.e., plume downwash) based on the PRIME & Waste Management Association. from EPA’s Support Center for Regulatory Air building downwash algorithms. The model Pittsburgh, PA; 17pp. Models (SCRAM) Web site at http:// employs hourly sequential preprocessed 126. Austin, B.S., T.E. Stoeckenius, M.C. www.epa.gov/scram001. Documentation is meteorological data to estimate Dudik and T.S. Stocking, 1988. User’s Guide also available from the National Technical concentrations for averaging times from one to the Expected Exceedances System. Information Service (NTIS), http:// hour to one year (also multiple years). Systems Applications, Inc., San Rafael, CA. www.ntis.gov or U.S. Department of AERMOD is designed to operate in concert Prepared under Contract No. 68–02–4352 Commerce, Springfield, VA 22161; phone: with two pre-processor codes: AERMET Option I for the U.S. Environmental (800) 553–6847. Where possible, accession processes meteorological data for input to Protection Agency, Research Triangle Park, numbers are provided. AERMOD, and AERMAP processes terrain NC. (Docket No. A–88–04, II–I–3) elevation data and generates receptor 127. Thrall, A.D., T.E. Stoeckenius and C.S. A.1 AMS/EPA Regulatory Model— information for input to AERMOD. Burton, 1985. A Method for Calculating AERMOD a. Recommendations for Regulatory Use Dispersion Modeling Uncertainty Applied to References the Regulation of an Emission Source. (1) AERMOD is appropriate for the Systems Applications, Inc., San Rafael, CA. Environmental Protection Agency, 2004. following applications: Prepared for the U.S. Environmental AERMOD: Description of Model • Point, volume, and area sources; Protection Agency, Research Triangle Park, Formulation. Publication No. EPA–454/R– • Surface, near-surface, and elevated NC. (Docket No. A–80–46, IV–G–1) 03–004. U.S. Environmental Protection releases; 128. ‘‘Ten years of Harmonisation Agency, Research Triangle Park, NC 27711; • Rural or urban areas; activities: Past, present and future’’ at http:// September 2004. (Available at http:// • Simple and complex terrain; www.dmu.dk/AtmosphericEnvironment/ www.epa.gov/scram001/) • Transport distances over which steady- Harmoni/Conferences/Belgirate/ Cimorelli, A. et al., 2005. AERMOD: A state assumptions are appropriate, up to BelgiratePapers.asp. Dispersion Model for Industrial Source 50km; • 129. ‘‘A platform for model evaluation’’ at Applications. Part I: General Model 1-hour to annual averaging times; and • http://www.dmu.dk/ Formulation and Boundary Layer Continuous toxic air emissions. AtmosphericEnvironment/Harmoni/ Characterization. Journal of Applied (2) For regulatory applications of Conferences/Belgirate/BelgiratePapers.asp. Meteorology, 44(5): 682–693. AERMOD, the regulatory default option Perry, S. et al., 2005. AERMOD: A should be set, i.e., the parameter DFAULT APPENDIX A TO APPENDIX W OF Dispersion Model for Industrial Source should be employed in the MODELOPT PART 51—SUMMARIES OF Applications. Part II: Model Performance record in the COntrol Pathway. The DFAULT PREFERRED AIR QUALITY MODELS against 17 Field Study Databases. Journal of option requires the use of terrain elevation Applied Meteorology, 44(5): 694–708. data, stack-tip downwash, sequential date Table of Contents Environmental Protection Agency, 2004. checking, and does not permit the use of the A.0 Introduction and Availability User’s Guide for the AMS/EPA Regulatory model in the SCREEN mode. In the A.1 Aermod Model—AERMOD. Publication No. EPA– regulatory default mode, pollutant half life or

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decay options are not employed, except in (ii) For recommendations regarding the the mixed layer, but can disperse downward the case of an urban source of sulfur dioxide length of meteorological record needed to and re-enter the mixed layer. In the CBL, where a four-hour half life is applied. Terrain perform a regulatory analysis with AERMOD, plume rise is superposed on the elevation data from the U.S. Geological see Section 8.3.1. displacements by random convective Survey 7.5-Minute Digital Elevation Model (3) Receptor data: Receptor coordinates, velocities (Weil et al., 1997). (edcwww.cr.usgs.gov/doc/edchome/ndcdb/ elevations, height above ground, and hill (2) In the stable boundary layer, plume rise ndcdb.html) or equivalent (approx. 30-meter height scales are produced by the AERMAP is estimated using an iterative approach, resolution) should be used in all terrain preprocessor for input to AERMOD. similar to that in the CTDMPLUS model (see applications. In some cases, exceptions of the Discrete receptors and/or multiple receptor A.5 in this appendix). terrain data requirement may be made in grids, Cartesian and/or polar, may be (3) Stack-tip downwash and buoyancy consultation with the permit/SIP reviewing employed in AERMOD. AERMAP requires induced dispersion effects are modeled. authority. input of Digital Elevation Model (DEM) Building wake effects are simulated for stacks b. Input Requirements terrain data produced by the U.S. Geological less than good engineering practice height Survey (USGS), or other equivalent data. using the methods contained in the PRIME (1) Source data: Required input includes AERMAP can be used optionally to estimate downwash algorithms (Schulman, et al., source type, location, emission rate, stack source elevations. 2000). For plume rise affected by the height, stack inside diameter, stack gas exit presence of a building, the PRIME downwash c. Output velocity, stack gas temperature, area and algorithm uses a numerical solution of the volume source dimensions, and source Printed output options include input mass, energy and momentum conservation elevation. Building dimensions and variable information, high concentration summary laws (Zhang and Ghoniem, 1993). Streamline emission rates are optional. tables by receptor for user-specified deflection and the position of the stack (2) Meteorological data: The AERMET averaging periods, maximum concentration relative to the building affect plume meteorological preprocessor requires input of summary tables, and concurrent values trajectory and dispersion. Enhanced surface characteristics, including surface summarized by receptor for each day dispersion is based on the approach of Weil roughness (zo), Bowen ratio, and albedo, as processed. Optional output files can be (1996). Plume mass captured by the cavity is well as, hourly observations of wind speed generated for: a listing of occurrences of well-mixed within the cavity. The captured between 7zo and 100m (reference wind speed exceedances of user-specified threshold plume mass is re-emitted to the far wake as measurement from which a vertical profile value; a listing of concurrent (raw) results at a volume source. can be developed), wind direction, cloud each receptor for each hour modeled, suitable (4) For elevated terrain, AERMOD cover, and temperature between zo and 100m for post-processing; a listing of design values incorporates the concept of the critical (reference temperature measurement from that can be imported into graphics software dividing streamline height, in which flow which a vertical profile can be developed). for plotting contours; an unformatted listing below this height remains horizontal, and Surface characteristics may be varied by of raw results above a threshold value with flow above this height tends to rise up and wind sector and by season or month. A a special structure for use with the TOXX over terrain (Snyder et al., 1985). Plume morning sounding (in National Weather model component of TOXST; a listing of concentration estimates are the weighted sum Service format) from a representative upper concentrations by rank (e.g., for use in of these two limiting plume states. However, air station, latitude, longitude, time zone, and quantile-quantile plots); and, a listing of consistent with the steady-state assumption wind speed threshold are also required in concentrations, including arc-maximum of uniform horizontal wind direction over the AERMET (instrument threshold is only normalized concentrations, suitable for modeling domain, straight-line plume required for site specific data). Additionally, model evaluation studies. trajectories are assumed, with adjustment in measured profiles of wind, temperature, d. Type of Model the plume/receptor geometry used to account vertical and lateral turbulence may be for the terrain effects. AERMOD is a steady-state plume model, required in certain applications (e.g., in h. Horizontal Winds complex terrain) to adequately represent the using Gaussian distributions in the vertical meteorology affecting plume transport and and horizontal for stable conditions, and in Vertical profiles of wind are calculated for dispersion. Optionally, measurements of the horizontal for convective conditions. The each hour based on measurements and solar, or net radiation may be input to vertical concentration distribution for surface-layer similarity (scaling) AERMET. Two files are produced by the convective conditions results from an relationships. At a given height above AERMET meteorological preprocessor for assumed bi-Gaussian probability density ground, for a given hour, winds are assumed input to the AERMOD dispersion model. The function of the vertical velocity. constant over the modeling domain. The surface file contains observed and calculated e. Pollutant Types effect of the vertical variation in horizontal wind speed on dispersion is accounted for surface variables, one record per hour. The AERMOD is applicable to primary profile file contains the observations made at through simple averaging over the plume pollutants and continuous releases of toxic depth. each level of a meteorological tower (or and hazardous waste pollutants. Chemical remote sensor), or the one-level observations transformation is treated by simple i. Vertical Wind Speed taken from other representative data (e.g., exponential decay. In convective conditions, the effects of National Weather Service surface random vertical updraft and downdraft f. Source-Receptor Relationships observations), one record per level per hour. velocities are simulated with a bi-Gaussian (i) Data used as input to AERMET should AERMOD applies user-specified locations probability density function. In both possess an adequate degree of for sources and receptors. Actual separation convective and stable conditions, the mean representativeness to insure that the wind, between each source-receptor pair is used. vertical wind speed is assumed equal to zero. temperature and turbulence profiles derived Source and receptor elevations are user input j. Horizontal Dispersion by AERMOD are both laterally and vertically or are determined by AERMAP using USGS representative of the source area. The DEM terrain data. Receptors may be located Gaussian horizontal dispersion coefficients adequacy of input data should be judged at user-specified heights above ground level. are estimated as continuous functions of the independently for each variable. The values parameterized (or measured) ambient lateral g. Plume Behavior for surface roughness, Bowen ratio, and turbulence and also account for buoyancy- albedo should reflect the surface (1) In the convective boundary layer (CBL), induced and building wake-induced characteristics in the vicinity of the the transport and dispersion of a plume is turbulence. Vertical profiles of lateral meteorological tower, and should be characterized as the superposition of three turbulence are developed from measurements adequately representative of the modeling modeled plumes: The direct plume (from the and similarity (scaling) relationships. domain. Finally, the primary atmospheric stack), the indirect plume, and the penetrated Effective turbulence values are determined input variables including wind speed and plume, where the indirect plume accounts from the portion of the vertical profile of direction, ambient temperature, cloud cover, for the lofting of a buoyant plume near the lateral turbulence between the plume height and a morning upper air sounding should top of the boundary layer, and the penetrated and the receptor height. The effective lateral also be adequately representative of the plume accounts for the portion of a plume turbulence is then used to estimate source area. that, due to its buoyancy, penetrates above horizontal dispersion.

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k. Vertical Dispersion Availability c. Output In the stable boundary layer, Gaussian The computer code is available on EPA’s (1) Printed output (from a separate post- vertical dispersion coefficients are estimated Internet SCRAM Web site and also on processor program) includes: as continuous functions of parameterized diskette (as PB 2002–500051) from the (2) Total concentration or, optionally, vertical turbulence. In the convective National Technical Information Service (see source contribution analysis; monthly and boundary layer, vertical dispersion is Section A.0). annual frequency distributions for 1-, 3-, and characterized by a bi-Gaussian probability 24-hour average concentrations; tables of Abstract density function, and is also estimated as a 1-, 3-, and 24-hour average concentrations at continuous function of parameterized BLP is a Gaussian plume dispersion model each receptor; table of the annual (or length vertical turbulence. Vertical turbulence designed to handle unique modeling of run) average concentrations at each profiles are developed from measurements problems associated with aluminum receptor; and similarity (scaling) relationships. These reduction plants, and other industrial sources (3) Five highest 1-, 3-, and 24-hour average turbulence profiles account for both where plume rise and downwash effects from concentrations at each receptor; and convective and mechanical turbulence. stationary line sources are important. (4) Fifty highest 1-, 3-, and 24-hour Effective turbulence values are determined concentrations over the receptor field. from the portion of the vertical profile of a. Recommendations for Regulatory Use vertical turbulence between the plume height (1) The BLP model is appropriate for the d. Type of Model and the receptor height. The effective vertical following applications: BLP is a gaussian plume model. turbulence is then used to estimate vertical • Aluminum reduction plants which e. Pollutant Types dispersion. contain buoyant, elevated line sources; BLP may be used to model primary l. Chemical Transformation • Rural areas; • Transport distances less than 50 pollutants. This model does not treat settling Chemical transformations are generally not and deposition. treated by AERMOD. However, AERMOD kilometers; • Simple terrain; and f. Source-Receptor Relationship does contain an option to treat chemical • transformation using simple exponential One hour to one year averaging times. (1) BLP treats up to 50 point sources, 10 decay, although this option is typically not (2) The following options should be parallel line sources, and 100 receptors used in regulatory applications, except for selected for regulatory applications: arbitrarily located. sources of sulfur dioxide in urban areas. (i) Rural (IRU=1) mixing height option; (2) User-input topographic elevation is Either a decay coefficient or a half life is (ii) Default (no selection) for plume rise applied for each stack and each receptor. wind shear (LSHEAR), transitional point input by the user. Note also that the Plume g. Plume Behavior Volume Molar Ratio Method (subsection 5.1) source plume rise (LTRANS), vertical and the Ozone Limiting Method (subsection potential temperature gradient (DTHTA), (1) BLP uses plume rise formulas of vertical wind speed power law profile Schulman and Scire (1980). 5.2.4) and for point-source NO2 analyses are available as non-regulatory options. exponents (PEXP), maximum variation in (2) Vertical potential temperature gradients number of stability classes per hour (IDELS), of 0.02 Kelvin per meter for E stability and m. Physical Removal pollutant decay (DECFAC), the constant in 0.035 Kelvin per meter are used for stable AERMOD can be used to treat dry and wet Briggs’ stable plume rise equation (CONST2), plume rise calculations. An option for user deposition for both gases and particles. constant in Briggs’ neutral plume rise input values is included. n. Evaluation Studies equation (CONST3), convergence criterion (3) Transitional rise is used for line for the line source calculations (CRIT), and sources. American Petroleum Institute, 1998. maximum iterations allowed for line source (4) Option to suppress the use of Evaluation of State of the Science of Air calculations (MAXIT); and transitional plume rise for point sources is Quality Dispersion Model, Scientific (iii) Terrain option (TERAN) set equal to included. Evaluation, prepared by Woodward-Clyde 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 (5) The building downwash algorithm of Consultants, Lexington, Massachusetts, for (3) For other applications, BLP can be used Schulman and Scire (1980) is used. American Petroleum Institute, Washington, if it can be demonstrated to give the same D.C., 20005–4070. h. Horizontal Winds estimates as a recommended model for the Brode, R.W., 2002. Implementation and same application, and will subsequently be (1) Constant, uniform (steady-state) wind is Evaluation of PRIME in AERMOD. Preprints executed in that mode. assumed for an hour. of the 12th Joint Conference on Applications (4) BLP can be used on a case-by-case basis Straight line plume transport is assumed to of Air Pollution Meteorology, May 20–24, with specific options not available in a all downwind distances. 2002; American Meteorological Society, recommended model if it can be (2) Wind speeds profile exponents of 0.10, Boston, MA. demonstrated, using the criteria in Section 0.15, 0.20, 0.25, 0.30, and 0.30 are used for Brode, R.W., 2004. Implementation and stability classes A through F, respectively. Evaluation of Bulk Richardson Number 3.2, that the model is more appropriate for a specific application. An option for user-defined values and an Scheme in AERMOD. 13th Joint Conference option to suppress the use of the wind speed on Applications of Air Pollution b. Input Requirements profile feature are included. Meteorology, August 23–26, 2004; American (1) Source data: point sources require stack i. Vertical Wind Speed Meteorological Society, Boston, MA. location, elevation of stack base, physical Environmental Protection Agency, 2003. stack height, stack inside diameter, stack gas Vertical wind speed is assumed equal to AERMOD: Latest Features and Evaluation exit velocity, stack gas exit temperature, and zero. Results. Publication No. EPA–454/R–03–003. pollutant emission rate. Line sources require j. Horizontal Dispersion U.S. Environmental Protection Agency, coordinates of the end points of the line, (1) Rural dispersion coefficients are from Research Triangle Park, NC. Available at release height, emission rate, average line http://www.epa.gov/scram001/. Turner (1969), with no adjustment made for source width, average building width, variations in surface roughness or averaging A.2 Buoyant Line and Point Source average spacing between buildings, and time. Dispersion Model (BLP) average line source buoyancy parameter. (2) Six stability classes are used. (2) Meteorological data: surface weather Reference data from a preprocessor such as k. Vertical Dispersion Schulman, Lloyd L., and Joseph S. Scire, PCRAMMET which provides hourly stability (1) Rural dispersion coefficients are from 1980. Buoyant Line and Point Source (BLP) class, wind direction, wind speed, Turner (1969), with no adjustment made for Dispersion Model User’s Guide. Document temperature, and mixing height. variations in surface roughness. P–7304B. Environmental Research and (3) Receptor data: locations and elevations (2) Six stability classes are used. Technology, Inc., Concord, MA. (NTIS No. of receptors, or location and size of receptor (3) Mixing height is accounted for with PB 81–164642; also available at http:// grid or request automatically generated multiple reflections until the vertical plume www.epa.gov/scram001/) receptor grid. standard deviation equals 1.6 times the

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mixing height; uniform mixing is assumed (2) Meteorological data: wind speed, wind EPA–450/4–86–002. Office of Air Quality beyond that point. angle (measured in degrees clockwise from Planning & Standards, Research Triangle (4) Perfect reflection at the ground is the Y axis), stability class, mixing height, Park, NC. (NTIS No. PB 86–167293) assumed. ambient (background to the highway) A.4 CALPUFF l. Chemical Transformation concentration of pollutant. (3) Receptor data: coordinates and height References Chemical transformations are treated using above ground for each receptor. linear decay. Decay rate is input by the user. Scire, J.S., D.G. Strimaitis and R.J. c. Output Yamartino, 2000. A User’s Guide for the m. Physical Removal Printed output includes concentration at CALPUFF Dispersion Model (Version 5.0). Physical removal is not explicitly treated. each receptor for the specified meteorological Earth Tech, Inc., Concord, MA. n. Evaluation Studies condition. Scire J.S., F.R. Robe, M.E. Fernau and R.J. Yamartino, 2000. A User’s Guide for the Schulman, L.L. and J.S. Scire, 1980. d. Type of Model CALMET Meteorological Model (Version Buoyant Line and Point Source (BLP) CALINE–3 is a Gaussian plume model. 5.0). Earth Tech, Inc., Concord, MA. Dispersion Model User’s Guide, P–7304B. e. Pollutant Types Environmental Research and Technology, Availability Inc., Concord, MA. CALINE–3 may be used to model primary pollutants. The model code and its documentation are Scire, J.S. and L.L. Schulman, 1981. available at no cost for download from the f. Source-Receptor Relationship Evaluation of the BLP and ISC Models with model developers’ Internet Web site: http:// SF6 Tracer Data and SO2 Measurements at (1) Up to 20 highway links are treated. www.src.com/calpuff/calpuff1.htm. You may Aluminum Reduction Plants. APCA (2) CALINE–3 applies user input location also contact Joseph Scire, Earth Tech, Inc., Specialty Conference on Dispersion and emission rate for each link. User-input 196 Baker Avenue, Concord, MA 01742; Modeling for Complex Sources, St. Louis, receptor locations are applied. Telephone: (978) 371–4270; Fax: (978) 371– MO. g. Plume Behavior 2468; e-mail: [email protected]. A.3 CALINE3 Plume rise is not treated. Abstract Reference h. Horizontal Winds CALPUFF is a multi-layer, multi-species Benson, Paul E., 1979. CALINE3—A (1) User-input hourly wind speed and non-steady-state puff dispersion modeling Versatile Dispersion Model for Predicting Air direction are applied. system that simulates the effects of time- and Pollutant Levels Near Highways and Arterial (2) Constant, uniform (steady-state) wind is space-varying meteorological conditions on Streets. Interim Report, Report Number assumed for an hour. pollutant transport, transformation, and FHWA/CA/TL–79/23. Federal Highway removal. CALPUFF is intended for use on i. Vertical Wind Speed Administration, Washington, DC (NTIS No. scales from tens of meters from a source to PB 80–220841). Vertical wind speed is assumed equal to hundreds of kilometers. It includes zero. algorithms for near-field effects such as stack Availability j. Horizontal Dispersion tip downwash, building downwash, The CALINE3 model is available on (1) Six stability classes are used. transitional buoyant and momentum plume diskette (as PB 95–502712) from NTIS. The rise, rain cap effects, partial plume source code and user’s guide are also (2) Rural dispersion coefficients from Turner (1969) are used, with adjustment for penetration, subgrid scale terrain and coastal available on EPA’s Internet SCRAM Web site interactions effects, and terrain impingement ( Section A.0). roughness length and averaging time. (3) Initial traffic-induced dispersion is as well as longer range effects such as Abstract handled implicitly by plume size parameters. pollutant removal due to wet scavenging and dry deposition, chemical transformation, CALINE3 can be used to estimate the k. Vertical Dispersion vertical wind shear effects, overwater concentrations of nonreactive pollutants from (1) Six stability classes are used. transport, plume fumigation, and visibility highway traffic. This steady-state Gaussian (2) Empirical dispersion coefficients from effects of particulate matter concentrations. model can be applied to determine air Benson (1979) are used including an a. Recommendations for Regulatory Use pollution concentrations at receptor locations adjustment for roughness length. downwind of ‘‘at-grade,’’ ‘‘fill,’’ ‘‘bridge,’’ (3) Initial traffic-induced dispersion is (1) CALPUFF is appropriate for long range and ‘‘cut section’’ highways located in handled implicitly by plume size parameters. transport (source-receptor distances of 50 to relatively uncomplicated terrain. The model (4) Adjustment for averaging time is several hundred kilometers) of emissions is applicable for any wind direction, highway included. from point, volume, area, and line sources. orientation, and receptor location. The model The meteorological input data should be has adjustments for averaging time and l. Chemical Transformation fully characterized with time-and-space- surface roughness, and can handle up to 20 Not treated. varying three dimensional wind and links and 20 receptors. It also contains an m. Physical Removal meteorological conditions using CALMET, as algorithm for deposition and settling velocity discussed in paragraphs 8.3(d) and 8.3.1.2(d) Optional deposition calculations are so that particulate concentrations can be of Appendix W. included. predicted. (2) CALPUFF may also be used on a case- a. Recommendations for Regulatory Use n. Evaluation Studies by-case basis if it can be demonstrated using the criteria in Section 3.2 that the model is CALINE–3 is appropriate for the following Bemis, G.R. et al., 1977. Air Pollution and more appropriate for the specific application. applications: Roadway Location, Design, and Operation— The purpose of choosing a modeling system • Highway (line) sources; Project Overview. FHWA–CA–TL–7080–77– like CALPUFF is to fully treat stagnation, • Urban or rural areas; 25, Federal Highway Administration, wind reversals, and time and space variations • Simple terrain; Washington, DC. • Transport distances less than 50 Cadle, S.H. et al., 1976. Results of the of meteorological conditions on transport and kilometers; and General Motors Sulfate Dispersion dispersion, as discussed in paragraph • One-hour to 24-hour averaging times. Experiment, GMR–2107. General Motors 7.2.8(a). Research Laboratories, Warren, MI. (3) For regulatory applications of CALMET b. Input Requirements Dabberdt, W.F., 1975. Studies of Air and CALPUFF, the regulatory default option (1) Source data: up to 20 highway links Quality on and Near Highways, Project 2761. should be used. Inevitably, some of the classed as ‘‘at-grade,’’ ‘‘fill,’’ ‘‘bridge,’’ or Stanford Research Institute, Menlo Park, CA. model control options will have to be set ‘‘depressed’’; coordinates of link end points; Environmental Protection Agency, 1986. specific for the application using expert traffic volume; emission factor; source height; Evaluation of Mobile Source Air Quality judgment and in consultation with the and mixing zone width. Simulation Models. EPA Publication No. appropriate reviewing authorities.

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b. Input Requirements MM5, RUC, Eta and RAMS) can be used by and POSTUTIL allows the re-partitioning of Source Data: CALMET as well (paragraph 8.3.1.2(d)). nitric acid and nitrate to account for the 1. Point sources: Source location, stack CALMET contains an option to be run in effects of ammonia limitation (Scire et al., height, diameter, exit velocity, exit ‘‘No-observations’’ mode (Robe et al., 2002), 2001; Escoffier-Czaja and Scire, 2002). temperature, base elevation, wind direction which allows the 3–D CALMET CALPUFF contains an options to output specific building dimensions (for building meteorological fields to be based on liquid water concentrations for use in downwash calculations), and emission rates prognostic model output alone, without computing visible plume lengths and for each pollutant. Particle size distributions observations. This allows CALMET and frequency of icing and fogging from cooling may be entered for particulate matter. CALPUFF to be run in prognostic mode for towers and other water vapor sources. The Temporal emission factors (diurnal cycle, forecast applications. CALPRO Graphical User Interface (GUI) monthly cycle, hour/season, wind speed/ 2. Single station surface and upper air contains options for creating graphics such as stability class, or temperature-dependent meteorological data in CTDMPLUS data file contour plots, vector plots and other displays emission factors) may also be entered. formats (SURFACE.DAT and PROFILE.DAT when linked to graphics software. Arbitrarily-varying point source parameters files) or AERMOD data file formats. These d. Type of Model options allow a vertical variation in the may be entered from an external file. (1) CALPUFF is a non-steady-state time- 2. Area sources: Source location and shape, meteorological parameters but no horizontal spatial variability. and space-dependent Gaussian puff model. release height, base elevation, initial vertical CALPUFF treats primary pollutants and distribution (s ) and emission rates for each 3. Single station meteorological data in z ISCST3 data file format. This option does not simulates secondary pollutant formation pollutant. Particle size distributions may be using a parameterized, quasi-linear chemical entered for particulate matter. Temporal account for variability of the meteorological parameters in the horizontal or vertical, conversion mechanism. Pollutants treated emission factors (diurnal cycle, monthly = except as provided for by the use of stability- include SO2, SO4 , NOX (i.e., NO + NO2), cycle, hour/season, wind speed/stability - dependent wind shear exponents and average HNO3, NO3 , NH3, PM–10, PM–2.5, toxic class, or temperature-dependent emission pollutants and others pollutant species that factors) may also be entered. Arbitrarily- temperature lapse rates. Gridded terrain and land use data are are either inert or subject to quasi-linear varying area source parameters may be chemical reactions. The model includes a entered from an external file. Area sources required as input into CALMET when Option 1 is used. Geophysical processor programs resistance-based dry deposition model for specified in the external file are allowed to both gaseous pollutants and particulate be buoyant and their location, size, shape, are provided that interface the modeling system to standard terrain and land use data matter. Wet deposition is treated using a and other source characteristics are allowed scavenging coefficient approach. The model to change in time. bases available from various sources such as the U.S. Geological Survey (USGS) and the has detailed parameterizations of complex 3. Volume sources: Source location, release terrain effects, including terrain height, base elevation, initial horizontal and National Aeronautics and Space impingement, side-wall scrapping, and steep- vertical distributions (s , s ) and emission Administration (NASA). y z walled terrain influences on lateral plume rates for each pollutant. Particle size Receptor Data: growth. A subgrid-scale complex terrain distributions may be entered for particulate CALPUFF includes options for gridded and module based on a dividing streamline matter. Temporal emission factors (diurnal non-gridded (discrete) receptors. Special concept divides the flow into a lift cycle, monthly cycle, hour/season, wind subgrid-scale receptors are used with the component traveling over the obstacle and a speed/stability class, or temperature- subgrid-scale complex terrain option. An wrap component deflected around the dependent emission factors) may also be option is provided for discrete receptors to be obstacle. entered. Arbitrarily-varying volume source placed at ground-level or above the local parameters may be entered from an external ground level (i.e., flagpole receptors). (2) The meteorological fields used by file. Volume sources with buoyancy can be Gridded and subgrid-scale receptors are CALPUFF are produced by the CALMET simulated by treating the source as a point placed at the local ground level only. meteorological model. CALMET includes a source and entering initial plume size Other Input: diagnostic wind field model containing CALPUFF accepts hourly observations of parameterized treatments of slope flows, parameters—initial (sy, sz)—to define the initial size of the volume source. ozone concentrations for use in its chemical valley flows, terrain blocking effects, and 4. Line sources: Source location, release transformation algorithm. Monthly kinematic terrain effects, lake and sea breeze height, base elevation, average buoyancy concentrations of ammonia concentrations circulations, a divergence minimization parameter, and emission rates for each can be specified in the CALPUFF input file, procedure, and objective analysis of pollutant. Building data may be entered for although higher time-resolution ammonia observational data. An energy-balance line source emissions experiencing building variability can be computed using the scheme is used to compute sensible and downwash effects. Particle size distributions POSTUTIL program. Subgrid-scale coastlines latent heat fluxes and turbulence parameters may be entered for particulate matter. can be specified in its coastal boundary file. over land surfaces. A profile method is used Temporal emission factors (diurnal cycle, Optional, user-specified deposition velocities over water. CALMET contains interfaces to monthly cycle, hour/season, wind speed/ and chemical transformation rates can also be prognostic meteorological models such as the stability class, or temperature-dependent entered. CALPUFF accepts the CTDMPLUS Penn State/NCAR Mesoscale Model (e.g., terrain and receptor files for use in its emission factors) may also be entered. MM5; Section 12.0, ref. 86), as well as the subgrid-scale terrain algorithm. Inflow Arbitrarily-varying line source parameters RAMS, Ruc and Eta models. boundary conditions of modeled pollutants may be entered from an external file. e. Pollutant Types can be specified in a boundary condition file. Meteorological Data (different forms of Liquid water content variables including CALPUFF may be used to model gaseous meteorological input can be used by cloud water/ice and precipitation water/ice pollutants or particulate matter that are inert CALPUFF): can be used as input for visibility analyses or which undergo quasi-linear chemical 1. Time-dependent three-dimensional (3– and other CALPUFF modules. reactions, such as SO2, SO4 =, NOX (i.e., NO D) meteorological fields generated by + NO ), HNO , NO -, NH , PM–10, PM–2.5 c. Output 2 3 3 3 CALMET. This is the preferred mode for and toxic pollutants. For regional haze running CALPUFF. Data inputs used by CALPUFF produces files of hourly analyses, sulfate and nitrate particulate CALMET include surface observations of concentrations of ambient concentrations for components are explicitly treated. wind speed, wind direction, temperature, each modeled species, wet deposition fluxes, cloud cover, ceiling height, relative dry deposition fluxes, and for visibility f. Source-Receptor Relationships humidity, surface pressure, and precipitation applications, extinction coefficients. CALPUFF contains no fundamental (type and amount), and upper air sounding Postprocessing programs (PRTMET, limitations on the number of sources or data (wind speed, wind direction, CALPOST, CALSUM, APPEND, and receptors. Parameter files are provided that temperature, and height) and air-sea POSTUTIL) provide options for summing, allow the user to specify the maximum temperature differences (over water). scaling, analyzing and displaying the number of sources, receptors, puffs, species, Optional 3–D meteorological prognostic modeling results. CALPOST contains options grid cells, vertical layers, and other model model output (e.g., from models such as for computing of light extinction (visibility) parameters. Its algorithms are designed to be

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suitable for source-receptor distances from m. Physical Removal Dispersion Model Plus Algorithms for tens of meters to hundreds of kilometers. Dry deposition of gaseous pollutants and Unstable Situations (CTDMPLUS). Volume 1: g. Plume Behavior particulate matter is parameterized in terms Model Descriptions and User Instructions. of a resistance-based deposition model. EPA Publication No. EPA–600/8–89–041. Momentum and buoyant plume rise is Gravitational settling, inertial impaction, and Environmental Protection Agency, Research treated according to the plume rise equations Brownian motion effects on deposition of Triangle Park, NC. (NTIS No. PB 89–181424) of Briggs (1975) for non-downwashing point particulate matter is included. CALPUFF Perry, S.G., 1992. CTDMPLUS: A sources, Schulman and Scire (1980) for line contains an option to evaluate the effects of Dispersion Model for Sources near Complex sources and point sources subject to building plume tilt resulting from gravitational Topography. Part I: Technical Formulations. downwash effects using the Schulman-Scire settling. Wet deposition of gases and Journal of Applied Meteorology, 31(7): 633– downwash algorithm, and Zhang (1993) for particulate matter is parameterized in terms 645. buoyant area sources and point sources of a scavenging coefficient approach. Availability affected by building downwash when using n. Evaluation Studies the PRIME building downwash method. This model code is available on EPA’s Stack tip downwash effects and partial Berman, S., J.Y. Ku, J. Zhang and S.T. Rao, Internet SCRAM Web site and also on plume penetration into elevated temperature 1977. Uncertainties in estimating the mixing diskette (as PB 90–504119) from the National inversions are included. An algorithm to treat depth—Comparing three mixing depth Technical Information Service (Section A.0). models with profiler measurements, horizontally-oriented vents and stacks with Abstract rain caps is included. Atmospheric Environment, 31: 3023–3039. Chang, J.C., P. Franzese, K. Chayantrakom CTDMPLUS is a refined point source h. Horizontal Winds and S.R. Hanna, 2001. Evaluations of Gaussian air quality model for use in all A three-dimensional wind field is CALPUFF, HPAC and VLSTRACK with Two stability conditions for complex terrain computed by the CALMET meteorological Mesoscale Field Datasets. Journal of Applied applications. The model contains, in its entirety, the technology of CTDM for stable model. CALMET combines an objective Meteorology, 42(4): 453–466. and neutral conditions. However, analysis procedure using wind observations Environmental Protection Agency, 1998. CTDMPLUS can also simulate daytime, with parameterized treatments of slope flows, Interagency Workgroup on Air Quality Modeling (IWAQM) Phase 2 Summary Report unstable conditions, and has a number of valley flows, terrain kinematic effects, terrain additional capabilities for improved user blocking effects, and sea/lake breeze and Recommendations for Modeling Long- Range Transport Impacts. EPA Publication friendliness. Its use of meteorological data circulations. CALPUFF may optionally use No. EPA–454/R–98–019. Office of Air and terrain information is different from single station (horizontally-constant) wind Quality Planning & Standards, Research other EPA models; considerable detail for fields in the CTDMPLUS, AERMOD or Triangle Park, NC. both types of input data is required and is ISCST3 data formats. Irwin, J.S., 1997. A Comparison of supplied by preprocessors specifically i. Vertical Wind Speed CALPUFF Modeling Results with 1997 INEL designed for CTDMPLUS. CTDMPLUS requires the parameterization of individual Vertical wind speeds are not used Field Data Results. In Air Pollution Modeling hill shapes using the terrain preprocessor and explicitly by CALPUFF. Vertical winds are and its Application, XII. Edited by S.E. the association of each model receptor with used in the development of the horizontal Gyrning and N. Chaumerliac. Plenum Press, a particular hill. wind components by CALMET. New York, NY. Irwin, J.S., J.S. Scire and D.G. Strimaitis, a. Recommendation for Regulatory Use j. Horizontal Dispersion 1996. A Comparison of CALPUFF Modeling CTDMPLUS is appropriate for the Turbulence-based dispersion coefficients Results with CAPTEX Field Data Results. In Air Pollution Modeling and its Application, following applications: provide estimates of horizontal plume • Elevated point sources; dispersion based on measured or computed XI. Edited by S.E. Gyrning and F.A. • Schiermeier. Plenum Press, New York, NY. Terrain elevations above stack top; values of sv. The effects of building • Morrison, K, Z–X Wu, J.S. Scire, J. Chenier Rural or urban areas; downwash and buoyancy-induced dispersion • Transport distances less than 50 are included. The effects of vertical wind and T. Jeffs-Schonewille, 2003. CALPUFF- Based Predictive and Reactive Emission kilometers; and shear are included through the puff splitting • One hour to annual averaging times algorithm. Options are provided to use Control System. 96th A&WMA Annual Conference & Exhibition, 22–26 June 2003; when used with a post-processor program Pasquill-Gifford (rural) and McElroy-Pooler such as CHAVG. (urban) dispersion coefficients. Initial plume San Diego, CA. Schulman, L.L., D.G. Strimaitis and J.S. b. Input Requirements size from area or volume sources is allowed. Scire, 2000. Development and evaluation of (1) Source data: For each source, user k. Vertical Dispersion the PRIME Plume Rise and Building supplies source location, height, stack Turbulence-based dispersion coefficients Downwash Model. JAWMA, 50: 378–390. diameter, stack exit velocity, stack exit provide estimates of vertical plume Scire, J.S., Z–X Wu, D.G. Strimaitis and temperature, and emission rate; if variable dispersion based on measured or computed G.E. Moore, 2001. The Southwest Wyoming emissions are appropriate, the user supplies Regional CALPUFF Air Quality Modeling values of sw. The effects of building hourly values for emission rate, stack exit downwash and buoyancy-induced dispersion Study—Volume I. Prepared for the Wyoming velocity, and stack exit temperature. are included. Vertical dispersion during Dept. of Environmental Quality. Available (2) Meteorological data: For applications of convective conditions is simulated with a from Earth Tech at http://www.src.com. CTDMPLUS, multiple level (typically three Strimaitis, D.G., J.S. Scire and J.C. Chang, probability density function (pdf) model or more) measurements of wind speed and 1998. Evaluation of the CALPUFF Dispersion based on Weil et al. (1997). Options are direction, temperature and turbulence (wind Model with Two Power Plant Data Sets. provided to use Pasquill-Gifford (rural) and fluctuation statistics) are required to create Tenth Joint Conference on the Application of McElroy-Pooler (urban) dispersion the basic meteorological data file Air Pollution Meteorology, Phoenix, Arizona. coefficients. Initial plume size from area or (‘‘PROFILE’’). Such measurements should be American Meteorological Society, Boston, obtained up to the representative plume volume sources is allowed. MA. January 11–16, 1998. height(s) of interest (i.e., the plume height(s) l. Chemical Transformation A.5 Complex Terrain Dispersion Model under those conditions important to the Gas phase chemical transformations are Plus Algorithms for Unstable Situations determination of the design concentration). treated using parameterized models of SO2 (CTDMPLUS) The representative plume height(s) of interest conversion to SO4= and NO conversion to should be determined using an appropriate Reference NO3-, HNO3, and NO2. Organic aerosol complex terrain screening procedure (e.g., formation is treated. The POSTUTIL program Perry, S.G., D.J. Burns, L.H. Adams, R.J. CTSCREEN) and should be documented in contains an option to re-partition HNO3 and Paine, M.G. Dennis, M.T. Mills, D.G. the monitoring/modeling protocol. The NO3- in order to treat the effects of ammonia Strimaitis, R.J. Yamartino and E.M. Insley, necessary meteorological measurements limitation. 1989. User’s Guide to the Complex Terrain should be obtained from an appropriately

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sited meteorological tower augmented by e. Pollutant Types observed vertical turbulence intensity, e.g., SODAR and/or RASS if the representative CTDMPLUS may be used to model non- sw (standard deviation of the vertical velocity plume height(s) of interest is above the levels reactive, primary pollutants. fluctuation). In simulating unstable represented by the tower measurements. (convective) conditions, CTDMPLUS relies Meteorological preprocessors then create a f. Source-Receptor Relationship on a skewed, bi-Gaussian probability density SURFACE data file (hourly values of mixed Up to 40 point sources, 400 receptors and function (pdf) description of the vertical layer heights, surface friction velocity, 25 hills may be used. Receptors and sources velocities to estimate the vertical distribution Monin-Obukhov length and surface are allowed at any location. Hill slopes are of pollutant concentration. ° roughness length) and a RAWINsonde data assumed not to exceed 15 , so that the l. Chemical Transformation file (upper air measurements of pressure, linearized equation of motion for Boussinesq Chemical transformation is not treated by temperature, wind direction, and wind flow are applicable. Receptors upwind of the CTDMPLUS. speed). impingement point, or those associated with (3) Receptor data: receptor names (up to any of the hills in the modeling domain, m. Physical Removal 400) and coordinates, and hill number (each require separate treatment. Physical removal is not treated by receptor must have a hill number assigned). g. Plume Behavior CTDMPLUS (complete reflection at the (4) Terrain data: user inputs digitized (1) As in CTDM, the basic plume rise ground/hill surface is assumed). contour information to the terrain algorithms are based on Briggs’ (1975) n. Evaluation Studies preprocessor which creates the TERRAIN recommendations. data file (for up to 25 hills). Burns, D.J., L.H. Adams and S.G. Perry, (2) A central feature of CTDMPLUS for 1990. Testing and Evaluation of the c. Output neutral/stable conditions is its use of a CTDMPLUS Dispersion Model: Daytime (1) When CTDMPLUS is run, it produces critical dividing-streamline height (Hc) to Convective Conditions. Environmental a concentration file, in either binary or text separate the flow in the vicinity of a hill into Protection Agency, Research Triangle Park, two separate layers. The plume component in format (user’s choice), and a list file NC. the upper layer has sufficient kinetic energy containing a verification of model inputs, i.e., Paumier, J.O., S.G. Perry and D.J. Burns, to pass over the top of the hill while • Input meteorological data from 1990. An Analysis of CTDMPLUS Model streamlines in the lower portion are ‘‘SURFACE’’ and ‘‘PROFILE’’. Predictions with the Lovett Power Plant Data constrained to flow in a horizontal plane • Stack data for each source. Base. Environmental Protection Agency, around the hill. Two separate components of • Terrain information. Research Triangle Park, NC. CTDMPLUS compute ground-level • Receptor information. Paumier, J.O., S.G. Perry and D.J. Burns, concentrations resulting from plume material • Source-receptor location (line printer 1992. CTDMPLUS: A Dispersion Model for in each of these flows. map). Sources near Complex Topography. Part II: (3) The model calculates on an hourly (or Performance Characteristics. Journal of (2) In addition, if the case-study option is appropriate steady averaging period) basis selected, the listing includes: Applied Meteorology, 31(7): 646–660. • how the plume trajectory (and, in stable/ Meteorological variables at plume height. A.6 Offshore and Coastal Dispersion Model • neutral conditions, the shape) is deformed by Geometrical relationships between the each hill. Hourly profiles of wind and (OCD) source and the hill. temperature measurements are used by • Reference Plume characteristics at each receptor, CTDMPLUS to compute plume rise, plume i.e., penetration (a formulation is included to DiCristofaro, D.C. and S.R. Hanna, 1989. —Distance in along-flow and cross flow handle penetration into elevated stable OCD: The Offshore and Coastal Dispersion direction layers, based on Briggs (1984)), convective Model, Version 4. Volume I: User’s Guide, —Effective plume-receptor height difference scaling parameters, the value of Hc, and the and Volume II: Appendices. Sigma Research —Effective sy & sz values, both flat terrain Froude number above Hc. Corporation, Westford, MA. (NTIS Nos. PB 93–144384 and PB 93–144392; also available and hill induced (the difference shows the h. Horizontal Winds effect of the hill) at http://www.epa.gov/scram001/) —Concentration components due to WRAP, CTDMPLUS does not simulate calm Availability LIFT and FLAT. meteorological conditions. Both scalar and (3) If the user selects the TOPN option, a vector wind speed observations can be read This model code is available on EPA’s summary table of the top 4 concentrations at by the model. If vector wind speed is Internet SCRAM Web site and also on each receptor is given. If the ISOR option is unavailable, it is calculated from the scalar diskette (as PB 91–505230) from the National selected, a source contribution table for every wind speed. The assignment of wind speed Technical Information Service (see Section hour will be printed. (either vector or scalar) at plume height is A.0). Official contact at Minerals done by either: Management Service: Mr. Dirk Herkhof, (4) A separate disk file of predicted (1-hour • only) concentrations (‘‘CONC’’) is written if Interpolating between observations Parkway Atrium Building, 381 Elden Street, the user chooses this option. Three forms of above and below the plume height, or Herndon, VA 20170, Phone: (703) 787–1735. • Extrapolating (within the surface layer) output are possible: Abstract (i) A binary file of concentrations, one from the nearest measurement height to the value for each receptor in the hourly plume height. (1) OCD is a straight-line Gaussian model sequence as run; i. Vertical Wind Speed developed to determine the impact of (ii) A text file of concentrations, one value offshore emissions from point, area or line Vertical flow is treated for the plume sources on the air quality of coastal regions. for each receptor in the hourly sequence as component above the critical dividing run; or OCD incorporates overwater plume transport streamline height (Hc); see ‘‘Plume and dispersion as well as changes that occur (iii) A text file as described above, but with Behavior’’. a listing of receptor information (names, as the plume crosses the shoreline. Hourly positions, hill number) at the beginning of j. Horizontal Dispersion meteorological data are needed from both the file. Horizontal dispersion for stable/neutral offshore and onshore locations. These (3) Hourly information provided to these conditions is related to the turbulence include water surface temperature, overwater air temperature, mixing height, and relative files besides the concentrations themselves velocity scale for lateral fluctuations, sv, for includes the year, month, day, and hour which a minimum value of 0.2 m/s is used. humidity. information as well as the receptor number Convective scaling formulations are used to (2) Some of the key features include with the highest concentration. estimate horizontal dispersion for unstable platform building downwash, partial plume conditions. penetration into elevated inversions, direct d. Type of Model use of turbulence intensities for plume CTDMPLUS is a refined steady-state, point k. Vertical Dispersion dispersion, interaction with the overland source plume model for use in all stability Direct estimates of vertical dispersion for internal boundary layer, and continuous conditions for complex terrain applications. stable/neutral conditions are based on shoreline fumigation.

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a. Recommendations for Regulatory Use f. Source-Receptor Relationship theory as default in the model. For very OCD has been recommended for use by the (1) Up to 250 point sources, 5 area sources, stable conditions, vertical dispersion is also Minerals Management Service for emissions or 1 line source and 180 receptors may be a function of lapse rate. located on the Outer Continental Shelf (50 FR used. (2) Vertical dispersion may be enhanced 12248; 28 March 1985). OCD is applicable for (2) Receptors and sources are allowed at because of obstructions near the source. A overwater sources where onshore receptors any location. virtual source technique is used to simulate are below the lowest source height. Where (3) The coastal configuration is determined the initial plume dilution due to downwash. onshore receptors are above the lowest by a grid of up to 3600 rectangles. Each (3) Formulas recommended by Pasquill source height, offshore plume transport and element of the grid is designated as either (1976) are used to calculate buoyant plume dispersion may be modeled on a case-by-case land or water to identify the coastline. enhancement. (4) At the water/land interface, the change basis in consultation with the appropriate g. Plume Behavior reviewing authority (paragraph 3.0(b)). to overland dispersion rates is modeled using (1) As in ISC, the basic plume rise a virtual source. The overland dispersion b. Input Requirements algorithms are based on Briggs’ rates can be calculated from either vertical (1) Source data: Point, area or line source recommendations. turbulence intensity or the Pasquill-Gifford location, pollutant emission rate, building (2) Momentum rise includes consideration coefficients. The change is implemented height, stack height, stack gas temperature, of the stack angle from the vertical. where the plume intercepts the rising stack inside diameter, stack gas exit velocity, (3) The effect of drilling platforms, ships, internal boundary layer. stack angle from vertical, elevation of stack or any overwater obstructions near the source 1. Chemical Transformation base above water surface and gridded are used to decrease plume rise using a Chemical transformations are treated using specification of the land/water surfaces. As revised platform downwash algorithm based exponential decay. Different rates can be an option, emission rate, stack gas exit on laboratory experiments. specified by month and by day or night. velocity and temperature can be varied (4) Partial plume penetration of elevated hourly. inversions is included using the suggestions m. Physical Removal (2) Meteorological data (over water): Wind of Briggs (1975) and Weil and Brower (1984). Physical removal is also treated using direction, wind speed, mixing height, relative (5) Continuous shoreline fumigation is exponential decay. humidity, air temperature, water surface parameterized using the Turner method n. Evaluation Studies temperature, vertical wind direction shear where complete vertical mixing through the (optional), vertical temperature gradient thermal internal boundary layer (TIBL) DiCristofaro, D.C. and S.R. Hanna, 1989. (optional), turbulence intensities (optional). occurs as soon as the plume intercepts the OCD: The Offshore and Coastal Dispersion (2) Meteorological data: TIBL. Model. Volume I: User’s Guide. Sigma Over land: Surface weather data from a Research Corporation, Westford, MA. h. Horizontal Winds preprocessor such as PCRAMMET which Hanna, S.R., L.L. Schulman, R.J. Paine and provides hourly stability class, wind (1) Constant, uniform wind is assumed for J.E. Pleim, 1984. The Offshore and Coastal direction, wind speed, ambient temperature, each hour. Dispersion (OCD) Model User’s Guide, and mixing height are required. (2) Overwater wind speed can be estimated Revised. OCS Study, MMS 84–0069. Over water: Hourly values for mixing from overland wind speed using relationship Environmental Research & Technology, Inc., height, relative humidity, air temperature, of Hsu (1981). Concord, MA. (NTIS No. PB 86–159803). and water surface temperature are required; (3) Wind speed profiles are estimated using Hanna, S.R., L.L. Schulman, R.J. Paine, J.E. if wind speed/direction are missing, values similarity theory (Businger, 1973). Surface Pleim and M. Baer, 1985. Development and over land will be used (if available); vertical layer fluxes for these formulas are calculated Evaluation of the Offshore and Coastal wind direction shear, vertical temperature from bulk aerodynamic methods. Dispersion (OCD) Model. Journal of the Air gradient, and turbulence intensities are i. Vertical Wind Speed Pollution Control Association, 35: 1039– optional. 1047. Vertical wind speed is assumed equal to (3) Receptor data: Location, height above Hanna, S.R. and D.C. DiCristofaro, 1988. zero. local ground-level, ground-level elevation Development and Evaluation of the OCD/API above the water surface. j. Horizontal Dispersion Model. Final Report, API Pub. 4461, c. Output (1) Lateral turbulence intensity is American Petroleum Institute, Washington, DC. (1) All input options, specification of recommended as a direct estimate of sources, receptors and land/water map horizontal dispersion. If lateral turbulence A. REFERENCES including locations of sources and receptors. intensity is not available, it is estimated from boundary layer theory. For wind speeds less Benson, P.E., 1979. CALINE3—A Versatile (2) Summary tables of five highest Dispersion Model for Predicting Air concentrations at each receptor for each than 8 m/s, lateral turbulence intensity is assumed inversely proportional to wind Pollution Levels Near Highways and Arterial averaging period, and average concentration Streets. Interim Report, Report Number for entire run period at each receptor. speed. (2) Horizontal dispersion may be enhanced FHWA/CA/TL–79/23. Federal Highway (3) Optional case study printout with Administration, Washington, DC. hourly plume and receptor characteristics. because of obstructions near the source. A virtual source technique is used to simulate Briggs, G.A., 1975. Plume Rise Predictions. Optional table of annual impact assessment Lectures on Air Pollution and Environmental from non-permanent activities. the initial plume dilution due to downwash. (3) Formulas recommended by Pasquill Impact Analyses. American Meteorological (4) Concentration files written to disk or Society, Boston, MA, pp. 59–111. tape can be used by ANALYSIS (1976) are used to calculate buoyant plume enhancement and wind direction shear Briggs, G.A., 1984. Analytical postprocessor to produce the highest Parameterizations of Diffusion: The concentrations for each receptor, the enhancement. (4) At the water/land interface, the change Convective Boundary Layer. Journal of cumulative frequency distributions for each Climate and Applied Meteorology, 24(11): receptor, the tabulation of all concentrations to overland dispersion rates is modeled using a virtual source. The overland dispersion 1167–1186. exceeding a given threshold, and the Environmental Protection Agency, 1980. manipulation of hourly concentration files. rates can be calculated from either lateral turbulence intensity or Pasquill-Gifford Recommendations on Modeling (October d. Type of Model curves. The change is implemented where 1980 Meetings). Appendix G to: Summary of OCD is a Gaussian plume model the plume intercepts the rising internal Comments and Responses on the October constructed on the framework of the MPTER boundary layer. 1980 Proposed Revisions to the Guideline on model. Air Quality Models. Meteorology and k. Vertical Dispersion Assessment Division, Office of Research and e. Pollutant Types (1) Observed vertical turbulence intensity Development, Research Triangle Park, NC OCD may be used to model primary is not recommended as a direct estimate of 27711. pollutants. Settling and deposition are not vertical dispersion. Turbulence intensity Environmental Protection Agency, 1998. treated. should be estimated from boundary layer Interagency Workgroup on Air Quality

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Modeling (IWAQM) Phase 2 Summary Report Impact Model. Systems Applications, Inc., Modeling. Journal of the Air Pollution and Recommendations for Modeling Long- San Rafael, CA. Control Association, 23: 598–600. Range Transport Impacts. Publication No. Pasquill, F., 1976. Atmospheric Dispersion Snyder, W.H., R.S. Thompson, R.E. EPA–454/R–98–019. (NTIS No. PB 99– Parameters in Gaussian Plume Modeling Part Eskridge, R.E. Lawson, I.P. Castro, J.T. Lee, 121089). II. Possible Requirements for Change in the J.C.R. Hunt, and Y. Ogawa, 1985. The Escoffier-Czaja, C. and J.S. Scire, 2002. The Turner Workbook Values. Publication No. structure of the strongly stratified flow over Effects of Ammonia Limitation on Nitrate EPA–600/4–76–030b. Office of Air Quality hills: Dividing streamline concept. Journal of Aerosol Formation and Visibility Impacts in Planning & Standards, Research Triangle Fluid Mechanics, 152: 249–288. Class I Areas. Twelfth AMS/AWMA Park, NC 27711. Turner, D.B., 1969. Workbook of Conference on the Application of Air Petersen, W.B., 1980. User’s Guide for Atmospheric Dispersion Estimates. PHS Pollution Meteorology, 20–24 May 2002; HIWAY–2 A Highway Air Pollution Model. Publication No. 999–26. U.S. Environmental Norfolk, VA. Publication No. EPA–600/8–80–018. Office of Protection Agency, Research Triangle, Park, Gifford, F.A., Jr. 1976. Turbulent Diffusion Research & Development, Research Triangle NC 27711. Typing Schemes—A Review. Nuclear Safety, Park, NC 27711. (NTIS PB 80–227556) Weil, J.C. and R.P. Brower, 1984. An 17: 68–86. Rao, T.R. and M.T. Keenan, 1980. Updated Gaussian Plume Model for Tall Horst, T.W., 1983. A Correction to the Suggestions for Improvement of the EPA– Stacks. Journal of the Air Pollution Control Gaussian Source-depletion Model. In HIWAY Model. Journal of the Air Pollution Association, 34: 818–827. Precipitation Scavenging, Dry Deposition and Control Association, 30: 247–256 (and Weil, J.C., 1996. A new dispersion Resuspension. H. R. Pruppacher, R.G. reprinted as Appendix C in Petersen, 1980). algorithm for stack sources in building Semonin and W.G.N. Slinn, eds., Elsevier, Robe, F.R., Z–X. Wu and J.S. Scire, 2002: wakes, Paper 6.6. Ninth Joint Conference on NY. Real-time SO2 Forecasting System with Applications of Air Pollution Meteorology Hsu, S.A., 1981. Models for Estimating Combined ETA Analysis and CALPUFF with A&WMA, January 28–February 2, 1996. Offshore Winds from Onshore Meteorological Modeling. Proceedings of the 8th Atlanta, GA. Measurements. Boundary Layer Meteorology, International Conference on Harmonisation Weil, J.C., L.A. Corio, and R.P. Brower, 20: 341–352. within Atmospheric Dispersion Modelling 1997. A PDF dispersion model for buoyant Huber, A.H. and W.H. Snyder, 1976. for Regulatory Purposes, 14–17 October 2002; plumes in the convective boundary layer. Building Wake Effects on Short Stack Sofia, Bulgaria. Journal of Applied Meteorology, 36: 982– Effluents. Third Symposium on Atmospheric Schulman, L.L. and J.S. Scire, 1980: 1003. Turbulence, Diffusion and Air Quality, Buoyant Line and Point Source (BLP) Zhang, X., 1993. A computational analysis American Meteorological Society, Boston, dispersion model user’s guide. The of the rise, dispersion, and deposition of MA. Aluminum Association; Washington, DC. buoyant plumes. Ph.D. Thesis, Massachusetts Irwin, J.S., 1979. A Theoretical Variation of (See A.2 in this appendix.) Institute of Technology, Cambridge, MA. the Wind Profile Power-Law Exponent as a Schulman, L.L. and S.R. Hanna, 1986. Zhang, X. and A.F. Ghoniem, 1993. A Function of Surface Roughness and Stability. Evaluation of Downwash Modification to the computational model for the rise and Atmospheric Environment, 13: 191–194. Industrial Source Complex Model. Journal of dispersion of wind-blown, buoyancy-driven Liu, M.K. et al., 1976. The Chemistry, the Air Pollution Control Association, 36: plumes—I. Neutrally stratified atmosphere. Dispersion, and Transport of Air Pollutants 258–264. Atmospheric Environment, 15: 2295–2311. Emitted from Fossil Fuel Power Plants in Segal, H.M., 1983. Microcomputer [FR Doc. 05–21627 Filed 11–8–05; 8:45 am] California: Data Analysis and Emission Graphics in Atmospheric Dispersion BILLING CODE 6560–50–P

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