[Federal Register: November 9, 2005 (Volume 70, Number 216)]
[Rules and Regulations]
[Page 68217-68261]
From the Federal Register Online via GPO Access [wais.access.gpo.gov]
[DOCID:fr09no05-20]
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Part III
Environmental Protection Agency
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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
[[Page 68218]]
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ENVIRONMENTAL PROTECTION AGENCY
40 CFR Part 51
[AH-FRL-7990-9]
RIN 2060-AK60
Revision to the Guideline on Air Quality Models: Adoption of a
Preferred General Purpose (Flat and Complex Terrain) Dispersion Model
and Other Revisions
AGENCY: Environmental Protection Agency (EPA).
ACTION: Final rule.
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SUMMARY: EPA's Guideline on Air Quality Models (``Guideline'')
addresses the regulatory application of air quality models for
assessing criteria pollutants under the Clean Air Act. In today's
action we promulgate several additions and changes to the Guideline. We
recommend a new dispersion model--AERMOD--for adoption in appendix A of
the Guideline. AERMOD replaces the Industrial Source Complex (ISC3)
model, applies to complex terrain, and incorporates a new downwash
algorithm--PRIME. We remove an existing model--the Emissions Dispersion
Modeling System (EDMS)--from appendix A. We also make various editorial
changes to update and reorganize information.
DATES: This rule is effective December 9, 2005. As proposed, beginning
November 9, 2006, the new model--AERMOD--should be used for appropriate
application as replacement for ISC3. During the one-year period
following this promulgation, protocols for modeling analyses based on
ISC3 which are submitted in a timely manner may be approved at the
discretion of the appropriate Reviewing Authority. Applicants are
therefore encouraged to consult with the Reviewing Authority as soon as
possible to assure acceptance during this period.
ADDRESSES: All documents relevant to this rule have been placed in
Docket No. A-99-05 at the following address: Air Docket in the EPA
Docket Center, (EPA/DC) EPA West (MC 6102T), 1301 Constitution Ave.,
NW., Washington, DC 20004. This docket is available for public
inspection and copying between 8 a.m. and 5:30 p.m., Monday through
Friday, at the address above.
FOR FURTHER INFORMATION CONTACT: Tyler J. Fox, Air Quality Modeling
Group (MD-D243-01), Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency, Research Triangle Park, NC 27711;
telephone (919) 541-5562. (Fox.Tyler@epa.gov).
SUPPLEMENTARY INFORMATION:
Outline
I. General Information
II. Background
III. Public Hearing on the April 2000 proposal
IV. Discussion of Public Comments and Issues from our April 21, 2000
Proposal
A. AERMOD and PRIME
B. Appropriate for Proposed Use
C. Implementation Issues/Additional Guidance
D. AERMOD revision and reanalyses in 2003
1. Performance analysis for AERMOD (02222)
a. Non-downwash cases: AERMOD (99351) vs. AERMOD (02222)
b. Downwash cases
2. Analysis of regulatory design concentrations for AERMOD
(02222)
a. Non-downwash cases
b. Downwash cases
c. Complex terrain
E. Emission and Dispersion Modeling System (EDMS)
V. Discussion of Public Comments and Issues from our September 8,
2003 Notice of Data Availability
VI. Final action
VII. Final editorial changes to appendix W
VIII. Statutory and Executive Order Reviews
I. General Information
A. How Can I Get Copies of Related Information?
EPA established an official public docket for this action under
Docket No. A-99-05. The official public docket is the collection of
materials that is available for public viewing at the Air Docket in the
EPA Docket Center, (EPA/DC) EPA West (MC 6102T), 1301 Constitution
Ave., NW., Washington, DC 20004. The EPA Docket Center Public Reading
Room (B102) is open from 8:30 a.m. to 4:30 p.m., Monday through Friday,
excluding legal holidays. The telephone number for the Reading Room is
(202) 566-1744, and the telephone number for the Air Docket is (202)
566-1742. An electronic image of this docket may be accessed via
Internet at http://www.epa.gov/eDocket, where Docket No. A-99-05 is indexed as
OAR-2003-0201. Materials related to our Notice of Data Availability
(published September 8, 2003) and public comments received pursuant to
the notice were placed in eDocket OAR-2003-0201.\1\
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\1\ http://cascade.epa.gov/RightSite/ dk--public--collection--
detail.htm? ObjectType=dk--docket--collection&cid=OAR-2003-
0201&ShowList=items&Action=view.
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Our Air Quality Modeling Group maintain an Internet website
(Support Center for Regulatory Air Models--SCRAM) at: http://www.epa.gov/scram001.
You may find codes and documentation for models referenced in
today's action on the SCRAM Web site. We have also uploaded various
support documents (e.g., evaluation reports).
II. Background
The Guideline is used by EPA, States, and industry to prepare and
review new source permits and State Implementation Plan revisions. The
Guideline is intended to ensure consistent air quality analyses for
activities regulated at 40 CFR 51.112, 51.117, 51.150, 51.160, 51.166,
and 52.21. We originally published the Guideline in April 1978 and it
was incorporated by reference in the regulations for the Prevention of
Significant Deterioration (PSD) of Air Quality in June 1978. We revised
the Guideline in 1986, and updated it with supplement A in 1987,
supplement B in July 1993, and supplement C in August 1995. We
published the Guideline as appendix W to 40 CFR part 51 when we issued
supplement B. We republished the Guideline in August 1996 (61 FR 41838)
to adopt the CFR system for labeling paragraphs. On April 21, 2000 we
issued a Notice of Proposed Rulemaking (NPR) in the Federal Register
(65 FR 21506), which was the original proposal for today's
promulgation.
III. Public Hearing on the April 2000 Proposal
We held the 7th Conference on Air Quality Modeling (7th conference)
in Washington, DC on June 28-29, 2000. As required by Section 320 of
the Clean Air Act, these conferences take place approximately every
three years to standardize modeling procedures, with special attention
given to appropriate modeling practices for carrying out programs PSD
(42 U.S.C. 7620). This conference served as the forum for receiving
public comments on the Guideline revisions proposed in April 2000. The
7th conference featured presentations in several key modeling areas
that support the revisions promulgated today. A presentation by the
American Meteorological Society (AMS)/EPA Regulatory Model Improvement
Committee (AERMIC) covered the enhanced Gaussian dispersion model with
boundary layer parameterization: AERMOD.\2\ Also at the 7th conference,
the Electric Power Research Institute (EPRI) presented evaluation
results from the recent research efforts to better define and
characterize dispersion around
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buildings (downwash effects). These efforts were part of a program
called the Plume RIse Model Enhancements (PRIME). At the time, PRIME
was integrated within ISC3ST (ISC-PRIME) and the results presented were
within the ISC3 context. As discussed in today's rule, the PRIME
algorithm has now been fully integrated into AERMOD.
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\2\ AMS/EPA Regulatory MODel.
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We proposed an update to the Emissions and Dispersion Modeling
System (EDMS 3.1), which is used for assessing air quality impacts from
airports. A representative of the Federal Aviation Administration (FAA)
presented a further upgrade to EDMS 4.0 that would include AERMOD and
forthcoming performance evaluations for two airports.
The presentations were followed by a critical review/discussion of
AERMOD and available performance evaluations, facilitated jointly by
the Air & Waste Management Association's AB-3 Committee and the
American Meteorological Society's Committee of Meteorological Aspects
of Air Pollution.
For the new models and modeling techniques proposed in April 2000,
we asked the public to address the following questions:
Has the scientific merit of the models presented been
established?
Are the models' accuracy sufficiently documented?
Are the proposed regulatory uses of individual models for
specific applications appropriate and reasonable?
Do significant implementation issues remain or is
additional guidance needed?
Are there serious resource constraints imposed by modeling
systems presented?
What additional analyses or information are needed?
We placed a transcript of the 7th conference proceedings and a copy
of all written comments, many of which address the above questions, in
Docket No. A-99-05. The comments on AERMOD were reviewed and nearly
every commenter urged us to integrate aerodynamic downwash into AERMOD
(i.e., not to require two models for some analyses). The only comments
calling for further actions were associated with the need for
documentation, evaluation and review of the suggested downwash
enhancement to AERMOD.
As a result of American Meteorological Society (AMS)/EPA Regulatory
Model Improvement Committee's (AERMIC) efforts to revise AERMOD,
incorporating the PRIME algorithm and making certain other incidental
modifications and to respond to public concerns, we believed that the
revised AERMOD merited another public examination of performance
results. Also, since the April 2000 NPR, the Federal Aviation
Administration (FAA) decided to configure EDMS 3.1 to incorporate the
AERMOD dispersion model. FAA presented this strategy at the 7th
conference and performance evaluations at two airports were to be
available before final promulgation. This was in response to public
concern over lack of EDMS evaluation.
On April 15, 2003 we published a Notice of Final Rulemaking (NFR;
68 FR 18440) that adopted CALPUFF in appendix A of the Guideline. We
also made various editorial changes to update and reorganize
information, and removed obsolete models. We announced that action on
AERMOD and the Emissions and Dispersion Model (EDMS) for assessing
airport impacts was being deferred, and would be reconsidered in a
separate action when new information became available for these models.
This deferred action took the form of a Notice of Data Availability
(NDA), which was published on September 8, 2003 (68 FR 52934). In this
notice, we made clear that the purpose of the NDA was to furnish
pertinent technical details related to model changes since the April
2000 NPR. New performance data and evaluation of design concentration
using the revised AERMOD are contained in reports cited later in this
preamble (see section V). In our April 2003 NFR, we stated that results
of EDMS 4.0 performance (with AERMOD) had recently become available. In
the NDA we clarified that these results would not be provided because
of FAA's decision to withdraw EDMS from the Guideline's appendix A, and
we affirmed our support for this removal. We solicited public comments
on the new data and information related to AERMOD.
IV. Discussion of Public Comments and Issues From Our April 21, 2000
Proposal
All comments submitted to Docket No. A-99-05 are filed in Category
IV-D.\3\ We summarized these comments, developed detailed responses,
and documented conclusions on appropriate actions in a Response-to-
Comments document.\4\ In this document, we considered and discussed all
significant comments. Whenever the comments revealed any new
information or suggested any alternative solutions, we considered this
prior to taking final action.
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\3\ Additional comments received since we published the final
rule on April 15, 2003 (discussed in the previous section) are filed
in category IV-E. This category includes comments received pursuant
to the Notice of Data Availability we published in September 2003.
\4\ Summary of Public Comments and EPA Responses: AERMOD; 7th
Conference on Air Quality Modeling; Washington, DC, June 28-29, 2000
AND Notice of Data Availability--September 8, 2003 (Air Docket A-99-
05, Item V-C-2). This document may also be examined from EPA's SCRAM
Web site at http://www.epa.gov/scram001.
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The remainder of this preamble section discusses the primary issues
encountered by the Agency during the public comment period associated
with the April 2000 proposal. This overview also serves in part to
explain the changes to the Guideline in today's action, and the main
technical and policy concerns addressed by the Agency.
A. AERMOD and PRIME
AERMOD is a best state-of-the-practice Gaussian plume dispersion
model whose formulation is based on planetary boundary layer
principles. AERMOD provides better characterization of plume dispersion
than does ISC3. At the 7th conference, AERMIC members presented
developmental and evaluation results of AERMOD. Comprehensive comments
were submitted on the AERMOD code and formulation document and on the
AERMET draft User's Guide (AERMET is the meteorological preprocessor
for AERMOD).
As identified in the April 2000 Federal Register proposal,
applications for which AERMOD was suited include assessment of plume
impacts from stationary sources in simple, intermediate, and complex
terrain, for other than downwash and deposition applications. We
invited comments on whether technical concerns had been reasonably
addressed and whether AERMOD is appropriate for its intended
applications. Since AERMOD lacks a general (all-terrain) screening
tool, we invited comment on the practicality of using SCREEN3 as an
interim tool for AERMOD. We also sought comments on minor changes to
the list of acceptable screening techniques for complex terrain.
PRIME was designed to incorporate the latest scientific algorithms
for evaluating building downwash. At the time of the proposal, the
PRIME algorithm for simulating aerodynamic downwash was not
incorporated into AERMOD. For testing purposes, PRIME was implemented
within ISC3ST (short-term average version of the Industrial Source
Complex), which AERMOD was proposed to replace. This special model,
called ISC-PRIME, was proposed for
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aerodynamic downwash and dry deposition. We sought comment on the
technical viability of AERMOD and ISC-PRIME for its intended
applications.
Scientific merit and accuracy. Regarding the scientific merits of
AERMOD, substantial support was expressed in public comments that
AERMOD represents sound and significant advances over ISC3ST. The
scientific merits of this approach have been documented both through
scientific peer review and performance evaluations. The formulation of
AERMOD has been subjected to an extensive, independent peer review.\5\
Findings of the peer review panel suggest that AERMOD's scientific
basis is ``state-of-the-science.'' Additionally, the model formulations
used in AERMOD and the performance evaluations have been accepted for
publication in two refereed journals.\6\ \7\ Finally, the adequacy of
AERMOD's complex terrain approach for regulatory applications is seen
most directly in its performance. AERMOD's complex terrain component
has been evaluated extensively by comparing model-estimated regulatory
design values and concentration frequency distributions with
observations. These comparisons have demonstrated AERMOD's superiority
to ISC3ST and CTDMPLUS (Complex Terrain Dispersion Model PLUS unstable
algorithms) in estimating those flat and complex terrain impacts of
greatest regulatory importance.\8\ For incidental and unique situations
involving a well-defined hill or ridge and where a detailed dispersion
analysis of the spatial pattern of plume impacts is of interest,
CTDMPLUS in the Guideline's appendix A remains available.
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\5\ U.S. Environmental Protection Agency, 2002. Compendium of
Reports from the Peer Review Process for AERMOD. February 2002.
Available at http://www.epa.gov/scram001/.
\6\ Cimorelli, A. et al., 2005. AERMOD: A Dispersion Model for
Industrial Source Applications. Part I: General Model Formulation
and Boundary Layer Characterization. Journal of Applied Meteorology,
44(5): 682-693.
\7\ Perry, S. et al., 2005. AERMOD: A Dispersion Model for
Industrial Source Applications. Part II: Model Performance against
17 Field Study Databases. Journal of Applied Meteorology, 44(5):
694-708.
\8\ Paine R. J. et al., 1998. Evaluation Results for AERMOD,
Draft Report. Docket No. A-99-05; II-A-05. Available at
http://www.epa.gov./scram001/.
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Public comments also supported our conclusion about the scientific
merits of PRIME. A detailed article in a peer-reviewed journal has been
published which contains all the basic equations with clear definitions
of the variables, and the reasoning and references for the model
assumptions.\9\
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\9\ Schulman, L.L. et al., 2000. Development and Evaluation of
the PRIME Plum Rise and Building Downwash Model. JAWMA 50: 378-390.
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Although some comments asked for more detailed documentation and
review, there were no comments which questioned the technical
credibility of the PRIME model. In fact, almost every commenter asked
for PRIME to be incorporated into AERMOD. As summarized above, we
believe that the scientific merit of PRIME has been established via (1)
model evaluation and documentation, (2) peer review within the
submittal process to a technical journal, and (3) via the public review
process.
Based on the external peer review of the evaluation report and the
public review comments, we have concluded that: (1) AERMOD's accuracy
is adequately documented; (2) AERMOD's accuracy is an improvement over
ISC3ST's ability to predict measured concentrations; and (3) AERMOD is
an acceptable regulatory air dispersion model replacement for ISC3ST.
Some commenters have identified what they perceived to be
weaknesses in the evaluation and performance of ISC-PRIME,\10\ and some
concerns were raised about the scope of the PRIME evaluation. However,
as shown by the overwhelming number of requests for the incorporation
of PRIME into AERMOD, commenters were convinced that the accuracy of
PRIME, as implemented within the ISC3ST framework, was reasonably
documented and found acceptable for regulatory applications. Although
some commenters requested more evaluations, practical limitations on
the number of valid, available data sets prevented the inclusion of
every source type and setting in the evaluation. All the data bases
that were reasonably available were used in the development and
evaluation of the model, and those data bases were sufficient to
establish the basis for the evaluation. Based on our review of the
documentation and the public comments, we conclude that the accuracy of
PRIME is sufficiently documented and find it acceptable for use in a
dispersion model recommended in the Guideline.
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\10\ Electric Power Research Institute, 1997. Results of the
Independent Evaluation of ISCST3 and ISC-PRIME. Final Report, TR-
2460026, November 1997. Available at http://www.epa.gov/scram001/.
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B. Appropriate for Proposed Use
Responding to a question posed in our April 2000 proposal, the
majority of commenters questioned the reasonableness of requiring
simultaneous use of two models (ISC-PRIME and AERMOD) for those sources
with potential downwash concerns. Commenters urged the Agency to
eliminate the need to use two models for evaluating the same source. In
response to this request, AERMIC developed a version of AERMOD that
incorporates PRIME: AERMOD (02222) and initiated an analysis to insure
that concentration estimates by AERMOD (02222) are equivalent to ISC-
PRIME predictions in areas affected by downwash before it replaces ISC-
PRIME. Careful thought was given to the way that PRIME was incorporated
into AERMOD, with the goal of making the merge seamless. While
discontinuities from the concatenation of these two sets of algorithms
were of concern, we mitigated this situation wherever possible (see
part D of this preamble, and the Response to Comments document \4\).
With regard to testing the performance of AERMOD (02222), we have
carefully confirmed that the AERMOD (02222)'s air quality concentration
predictions in the wake region reasonably compare to those predictions
from ISC-PRIME. In fact, the results indicate that AERMOD (02222)'s
performance matches the performance of ISC-PRIME, and are presented in
an updated evaluation report \11\ and analysis of regulatory design
concentrations.\12\ We discuss AERMOD (02222) performance in detail in
part D.
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\11\ Environmental Protection Agency, 2003. AERMOD: Latest
Features and Evaluation Results. Publication No. EPA-454/R-03-003.
Available at http://www.epa.gov/scram001/.
\12\ Environmental Protection Agency, 2003. Comparison of
Regulatory Design Concentrations: AERMOD versus ISC3ST, CTDMPLUS,
and ISC-PRIME. Final Report. Publication No. EPA-454/R-03-002.
Available at http://www.epa.gov/scram001/.
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Because the technical basis for the PRIME algorithms and the AERMOD
formulations have been independently peer-reviewed, we believe that
further peer review of the new model (AERMOD 02222) is not necessary.
The scientific formulation of the PRIME algorithms has not been
changed. However, the coding for the interface between PRIME and the
accompanying dispersion model had to be modified somewhat to
accommodate the different ways that ISC3ST and AERMOD simulate the
atmosphere. The main public concern was the interaction between the two
models and whether the behavior would be appropriate for all reasonable
source settings. This concern was addressed through the extensive
testing conducted within the performance evaluation \11\ and analysis
of design concentrations.\12\ Both sets of
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analyses indicate that the new model is performing acceptably well and
the results are similar to those obtained from the earlier performance
evaluation \8\ \10\ and analysis of regulatory design concentrations
(i.e., for AERMOD (99351)).\13\
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\13\ Peters, W.D. et al., 1999. Comparison of Regulatory Design
Concentrations: AERMOD vs. ISCST3 and CTDMPLUS, Draft Report. Docket
No. A-99-05; II-A-15.
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While dry deposition is treated in ISC3ST, time and resources did
not allow its incorporation in AERMOD (99351). Since no recommendation
for deposition is made for regulatory applications, we did not consider
that the absence of this capability compromises the suitability of
AERMOD for its intended purposes. Nevertheless, a number of commenters
requested that deposition algorithms be added to AERMOD, and we
developed an update to AERMOD (02222) that offers dry and wet
deposition for both gases and particles as an option.
The version of AERMOD under review at the 7th Conference was AERMOD
(99351) and, as mentioned above, AERMIC has made a number of changes to
AERMOD (99351) following this conference. These changes were initiated
in response to public comments and, after the release of a new draft
version of the model, in response to the recommendations from the beta
testers. Changes made to AERMOD include the following:
Adding the PRIME algorithms to the model (response to
public comments);
Modifying the complex terrain algorithms to make AERMOD
less sensitive to the selection of the domain of the study area
(response to public comments);
Modifying the urban dispersion for low-level emission
sources, such as area sources, to produce a more realistic urban
dispersion and, as a part of this change, changing the minimum layer
depth used to calculate the effective dispersion parameters for all
dispersion settings (scientific formulation correction which was
requested by beta testers); and
Upgrading AERMOD to include all the newest features that
exist in the latest version of ISC3ST such as Fortran90 compliance and
allocatable arrays, EVENTS processing and the TOXICS option (response
to public comments).
In the follow-up quality control checking of the model and the
source code, additional changes were identified as necessary and the
following revisions were made:
Adding meander treatment to: (1) Stable and unstable urban
cases, and (2) the rural unstable dispersion settings (only the rural,
stable dispersion setting considered meander in AERMOD (99351)--this
change created a consistent treatment of air dispersion in all
dispersion settings);
Making some changes to the basic meander algorithms
(improved scientific formulation); and
Repairing miscellaneous coding errors.
As we mentioned earlier, the version of AERMOD that is being
promulgated today--AERMOD (02222)--has been subjected to further
performance evaluation \11\ and analysis of design concentrations.\12\
C. Implementation Issues/Additional Guidance
Other than miscellaneous suggestions for certain enhancements for
AERMOD (99351) such as a Fortran90 compilation of the source code,
creation of allocatable arrays, and development of a Windows[supreg]
graphical user interface, no significant implementation obstacles were
identified in public comments.
For AERMET (meteorological preprocessor for AERMOD), we have
implemented some enhancements that commenters suggested. For site-
specific applications, several commenters cited AERMOD's requirements
for NWS cloud cover data. In response, we revised the AERMET to
incorporate the bulk Richardson number methodology. This approach uses
temperature differences near the surface of the earth, which can be
routinely monitored, and eliminates the need for the cloud cover data
at night. We made a number of other revisions in response to public
comments, enabling AERMET to: (1) Use the old and the new Forecasting
Systems Laboratory formats, (2) use the Hourly U.S. Weather
Observations/Automated Surface Observing Stations (HUSWO/ASOS) data,
(3) use site-specific solar radiation and temperature gradient data to
eliminate the need for cloud cover data, (4) appropriately handle
meteorological data from above the arctic circle, and (5) accept a
wider range of reasonable friction velocities and reduce the number of
warning messages. As mentioned earlier, we added a meander component to
the treatment of stable and unstable urban conditions to consistently
treat meander phenomena for all cases.
AERMAP (the terrain preprocessor for AERMOD) has been upgraded in
response to public comments calling for it to: (1) Treat complex
terrain receptors without a dependance on the selected domain, (2)
accommodate the Spatial Data Transfer Standard (SDTS) data available
from the U.S. Geological Survey (USGS), (3) appropriately use Digital
Elevation Model (DEM) data with 2 different datums (NAD27 and NAD83);
(4) accept all 7 digits of the North UTM coordinate, and (5) do more
error-checking in the raw data (mostly checking for missing values, but
not for harsh terrain changes in adjacent points). All of these
recommendations have been implemented.
In response to comments about the selection of the domain affecting
the results of the maximum concentrations in complex terrain and the
way AERMAP estimates the effective hill height scale (hC),
the algorithms within AERMAP and AERMOD have been adjusted so that the
hill height is less sensitive to the arbitrary selection of the domain.
This adjustment has been evaluated against the entire set of evaluation
data. The correction was found to substantially reduce the effect of
the domain size upon the computation of controlling hill heights for
each receptor. Application of this change to the evaluation databases
did not materially affect the evaluation results.
In general, public comments that requested additional guidance were
either obviated by revisions to AERMOD (99351) and its related
preprocessors or deemed unnecessary. In the latter case, the reasons
were explained in the Response-to-Comments document.\4\
Some public comments suggested additional testing of AERMOD
(99351). In fact, after the model revisions that were described earlier
were completed, AERMOD (02222) was subjected to additional testing.\11\
\12\ These new analyses will be discussed in part D.
With respect to a screening version of AERMOD, a tool called
AERSCREEN is being developed with a beta version expected to be
publicly available in Fall 2005. SCREEN3 is the current screening model
in the Guideline, and since SCREEN3 has been successfully applied for a
number of years, we believe that SCREEN3 produces an acceptable degree
of conservatism for regulatory applications and may be used until
AERSCREEN or a similar technique becomes available and tested for
general application.
D. AERMOD Revision and Reanalyses Published In 2003
1. Performance Analysis for AERMOD (02222)
We have tested the performance of AERMOD (02222) by applying all of
the original data sets used to support the version proposed in April,
2000: AERMOD (99351) \8\ and ISC-PRIME.\10\ These data sets include: 5
complex
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terrain data sets, 7 building downwash data sets, and 5 simple terrain
data sets (see appendix A of the Response-to-Comments document \4\).
This performance analysis, which is a check of the model's maximum
concentration predictions against observed data, includes a comparison
of the current version of the new model (AERMOD 02222) with ISC3ST or
ISC-PRIME for downwash conditions. The results and conclusions of the
performance analyses are presented in 2 sections: Non-downwash and
downwash source scenarios.
a. Non-Downwash Cases
For the user community to obtain a full understanding of the
impacts of today's proposal for the non-downwash source scenarios (flat
and complex terrain), our performance evaluation of AERMOD (02222) must
be discussed with respect to the old model, ISC3ST, and with respect to
AERMOD (99351). Based on the evaluation, we have concluded that AERMOD
(02222) significantly outperforms ISC3ST and that AERMOD (02222)'s
performance is even better than that of AERMOD (99351).
Evaluation of AERMOD (99351)
Comparative performance statistics were calculated for both ISC3ST
and AERMOD (99351) using data sets in non-downwash conditions. This
analysis looked at combinations of test sites (flat and complex
terrain), pollutants, and concentration averaging times. Comparisons
indicated very significant improvements in performance when applying
AERMOD (99351). In all but 1 of the total of 20 cases in which AERMOD
(99351) could be compared to ISC3ST, AERMOD performed as well as (but
generally better than) ISC3ST, that is, AERMOD predicted maximum
concentrations that were closer to the measured maximum concentrations.
In the most dramatic case (i.e., Lovett; 24-hr) in which AERMOD
performed better than ISC3ST, AERMOD's maximum concentration
predictions were about the same as the measured concentrations while
the ISC3ST's predicted maximum concentrations were about 9 times higher
than the measured concentrations. In the one case (i.e., Clifty Creek;
3-hr) where ISC3ST performed better than AERMOD (99351), ISC3ST's
concentration predictions matched the observed data and the AERMOD
concentration predictions were about 25% higher than the observed data.
These results were reported in the supporting documentation for AERMOD
(99351).
Evaluation of AERMOD (02222)
With the changes to AERMOD (99351) as outlined above, how has the
performance of the AERMOD been affected? The performance of the current
version of AERMOD is about the same or slightly better than the April
2000 version when a comparison is made over all the available data
sets. There were examples of AERMOD (02222) showing better and poorer
performance when compared to the performance results of AERMOD (99351).
However, for those cases where AERMOD (02222)'s performance was
degraded, the degradation was small. On the other side, there were more
examples where AERMOD (02222) more closely predicted measured
concentrations. The performance improvements were also rather small
but, in general, were somewhat larger than the size of the performance
degradations. There also were a number of cases where the performance
remained unchanged between the 2 models. Thus, overall, there was a
slight improvement in AERMOD's performance and, consequently, we
believe that AERMOD (02222) significantly outperforms ISC3ST for non-
downwash source scenarios.
For AERMOD (02222) with the 5 data bases examined for simple
terrain, the ratios of modeled/observed Robust High Concentration
ranged from 0.77 to 1.11 (1-hr average), 0.98 to 1.24 (3-hr average),
0.94 to 0.97 (24-hr average) and 0.30 to 0.97 (annual average). These
ratios reflect better performance than ISC3ST for all cases.
For AERMOD (02222) with the 5 data bases examined for complex
terrain, these ratios ranged from 1.03 to 1.12 (3-hr average), 0.67 to
1.78 (24-hr average) and 0.54 to 1.59 (annual average). At Tracy--the
only site for which there are 1-hr data--AERMOD performed considerably
better (ratio = 1.04) than either ISC3ST or CTDMPLUS. At three of the
other four sites, AERMOD generally performed much better than either
ISC3ST or (where applicable) alternative models for the 3-hr and 24-hr
averaging times; results were comparable for Clifty Creek (for the 3-hr
averaging times, AERMOD (02222) predictions were only about 5% higher
than ISC3ST's--down from 25% for AERMOD (99351) as described earlier).
At the two sites where annual peak comparisons are available, AERMOD
performed much better than either ISC3ST or alternative models.
b. Downwash Cases
For the downwash data sets, there were combinations of test sites,
pollutants, stack heights and averaging times where the proposed (ISC-
PRIME) model performance could be compared to the performance of AERMOD
(02222) with PRIME incorporated. There was an equal number of non-
downwash cases where AERMOD performed better than ISC-PRIME and where
ISC-PRIME performed better than AERMOD. There was only one case where
there was a significant difference between the two models' performance,
and AERMOD clearly performed better than ISC-PRIME in this case. In all
other cases, the difference in the performance, whether an improvement
or a degradation, was small. This comparison indicated that AERMOD
(02222) performs very similarly, if not somewhat better, when compared
to ISC-PRIME for downwash cases.
2. Analysis of Regulatory Design Concentrations for AERMOD (02222)
Although not a performance tool, the analysis of design
concentrations (``consequence'' analysis) is designed to test model
stability and continuity, and to help the user community understand the
differences to be expected between air dispersion models. The
consequences, or changes in the regulatory concentrations predicted
when using the new model (AERMOD 02222) versus ISC3ST, cover 96 source
scenarios and at least 3 averaging periods per source scenario, and are
evaluated and summarized here. The purpose is to provide the user
community with a sense of potential changes in their air dispersion
analyses when applying the new model over a broad range of source types
and settings. The consequence analysis, in which AERMOD was run for
hundreds of source scenarios, also provides a check for model stability
(abnormal halting of model executions when using valid control files
and input data) and for spurious results (unusually high or low
concentration predictions which are unexplained). The results are
placed into 3 categories: non-downwash source scenarios in flat, simple
terrain; downwash source scenarios in flat terrain; and, complex
terrain source settings. The focus of this discussion is on how design
concentrations change from those predicted by ISC3ST when applying the
latest version of AERMOD versus applying the earlier version of AERMOD
(99351).
a. Non-Downwash Cases
For the non-downwash situations, there were 48 cases covering a
variety of source types (point, area, and volume sources), stack
heights, terrain types (flat and simple), and dispersion
[[Page 68223]]
settings (urban and rural). For each case in the consequence analysis,
we calculated the ratio between AERMOD's regulatory concentration
predictions and ISC3ST's regulatory concentration predictions. The
average ratio of AERMOD to ISC3ST-predicted concentrations changed from
1.14 when applying AERMOD (99351) to 0.96 when applying AERMOD
(02222).\14\ Thus, in general, AERMOD (02222) tends to predict
concentrations closer to ISC3ST than does version 99351 proposed in
April 2000. Also, the variation of the differences between ISC3ST and
AERMOD has decreased with AERMOD (02222). Comparing the earlier
consequence analysis to the latest study with AERMOD (02222), we saw a
25% reduction in the number of cases where the AERMOD-predicted
concentrations differed by over a factor of two from ISC3ST's
predictions.
---------------------------------------------------------------------------
\14\ A ratio of 1.00 indicates that the two models are
predicting the same concentrations. See Table 4.1 in reference 12.
---------------------------------------------------------------------------
b. Downwash Cases
For the downwash analysis, there were 20 cases covering a range of
stack heights, locations of stacks relative to the building, dispersion
settings, and building shapes. As before, we calculated the ratio
regulatory concentration predictions from AERMOD (02222 with PRIME) and
compared them as ratios to those from ISC3ST for each case. For
additional information, we also included ratios with ISC-PRIME that was
also proposed in April 2000.
Calculated over all the 20 cases, and for all averaging times
considered, the average ISC-PRIME to ISC3ST concentration ratio is
about 0.86, whereas for AERMOD (PRIME) to ISC3ST, it is 0.82. The
maximum value of the concentration ratios range from 2.24 for ISC-
PRIME/ISC3ST to 3.67 for AERMOD (PRIME)/ISC3ST. Similarly, the minimum
value of the concentration ratio range from 0.04 for ISC-PRIME/ISC3ST
to 0.08 for AERMOD (PRIME)/ISC3ST. (See Table 4-5 in reference 12.)
Although results above for the two models that use PRIME--AERMOD
(02222) and ISC-PRIME--show differences, we find that building downwash
is not a significant factor in determining the maximum concentrations
in some of the cases, i.e., the PRIME algorithms do not predict a
building cavity concentration. Of those cases where downwash was
important, the average concentration ratios of ISC-PRIME/ISC3ST and
AERMOD (02222)/ISC3ST are about 1. The maximum value of the
concentration ratios range from 2.24 for ISC-PRIME/ISC3ST to 1.87 for
AERMOD (02222)/ISC3ST and the minimum value of the concentration ratios
range from 0.34 for ISC-PRIME/ISC3ST to 0.38 for AERMOD (02222)/ISC3ST.
These results show relatively close agreement between the two PRIME
models. (See Table 4-6 in reference 12.)
ISC3ST does not predict cavity concentrations but comparisons can
be made between AERMOD and ISC-PRIME. The average AERMOD (02222)
predicted 1-hour cavity concentration is about the same (112%) as the
average ISC-PRIME 1-hour cavity concentration. In the extremes, the
AERMOD (02222)-predicted cavity concentrations ranged from about 40%
higher to 15% lower than the corresponding ISC-PRIME cavity
concentration predictions. Thus, in general, where downwash is a
significant factor, AERMOD (02222) and ISC-PRIME predict similar
maximum concentrations. (See Table 4-8 in reference 12.)
Although the same downwash algorithms are used in both models,
there are differences in the melding of PRIME with the core model, and
differences in the way that these models simulate the atmosphere.\15\
The downwash algorithm implementation therefore could not be exactly
the same.
---------------------------------------------------------------------------
\15\ AERMOD uses more complex techniques to estimate temperature
profiles which, in turn, affect the calculation of the plume rise.
Plume rise may affect the cavity and downwash concentrations.
---------------------------------------------------------------------------
c. Complex Terrain
During the testing of AERMOD after modifications were made to the
complex terrain algorithm (see discussion of hill height scale
(hC) in B. Appropriate for Proposed Use in this preamble), a
small error was found in the original complex terrain code while
conducting the consequence analysis. This error was subsequently
repaired. Final testing indicated that the revised complex terrain code
produced reasonable results for the consequence analysis, as described
below.
The analysis of predicted design concentrations included a suite of
complex terrain settings. There were 28 cases covering a variety of
stack heights, stack gas buoyancy values, types of hills, and distances
between source and terrain. The ratios between the AERMOD (02222 &
99351)--predicted maximum concentrations and the ISC3ST maximum
concentrations were calculated for all cases for a series of averaging
times. When comparing AERMOD (99351) to ISC3ST and then AERMOD (02222)
to ISC3ST, the average maximum concentration ratio, the highest ratios
and the lowest ratios were almost unchanged. There were no cases in
either consequence analysis where AERMOD (02222 & 99351) predicted
higher concentrations than those predicted by ISC3ST. Thus, in general,
the consequences of moving from ISC3ST to AERMOD (02222) rather than to
AERMOD (99351) in complex terrain were essentially the same. (See Table
4-9 in reference 12.)
E. Emission and Dispersion Modeling System (EDMS)
The Emissions and Dispersion Modeling System (EDMS) was developed
jointly by the Federal Aviation Administration (FAA) and the U.S. Air
Force in the late 1970s and first released in 1985 to assess the air
quality of proposed airport development projects. EDMS has an emissions
preprocessor and its dispersion module estimates concentrations for
various averaging times for the following pollutants: CO, HC,
NOX, SOX, and suspended particles (e.g., PM-10).
The first published application of EDMS was in December 1986 for
Stapleton International Airport (FAA-EE-11-A/REV2).
In 1988, version 4a4 revised the dispersion module to include an
integral dispersion submodel: GIMM (Graphical Input Microcomputer
Model). This version was proposed for adoption in the Guideline's
appendix A in February 1991 (56 FR 5900). This version was included in
appendix A in July 1993 (58 FR 38816) and recommended for limited
applications for assessments of localized airport impacts on air
quality. FAA later updated EDMS to Version 3.0.
In response to the growing needs of air quality analysts and
changes in regulations (e.g., conformity requirements from the Clean
Air Act Amendment of 1990), FAA updated EDMS to version 3.1, which is
based on the CALINE3 \16\ and PAL2 dispersion kernels. In our April
2000 NPR we proposed to adopt the version 3.1 update to EDMS. However,
this update had not been subjected to performance evaluation and no
studies of EDMS' performance have been cited in appendix A of the
Guideline. Comment was invited on whether this compromises the
viability of EDMS 3.1 as a recommended or preferred model and how this
deficiency can be corrected.
---------------------------------------------------------------------------
\16\ Currently listed in appendix A of the Guideline.
---------------------------------------------------------------------------
Several commenters expressed concern about EDMS 3.1 as a
recommended model in appendix A. Indeed, there were concerns that EDMS
[[Page 68224]]
3.1 had not been as well validated as other models, nor subjected to
peer review, as required by the Guideline's subsection 3.1.1. One of
these commenters suggested that EDMS 3.1 should be presented only as
one of several alternative models.
At the 7th Conference, FAA proposed for appendix A adoption an even
newer, enhanced version of EDMS--version 4.0, which incorporates the
AERMOD dispersion kernel (without alteration). In this system, the
latest version of AERMOD would be employed as a standalone component of
EDMS. This dispersion kernel was to replace PAL2 and CALINE3 currently
in EDMS 3.1. There were no public comments specific to FAA's proposed
AERMOD-based enhancements to EDMS announced after our April 2000 NPR.
In response to written comments on our April 2000 NPR, at the 7th
Conference (transcript) FAA promised a complete evaluation process that
would include sensitivity testing, intermodel comparison, and analysis
of EDMS predictions against field observations. The intermodel
comparisons were proposed for the UK's Atmospheric Dispersion Modeling
System (ADMS).\17\
---------------------------------------------------------------------------
\17\ Cambridge Environmental Research Consultants; http://www.cerc.co.uk/
.
---------------------------------------------------------------------------
As we explained in our September 8, 2003 Notice of Data
Availability, FAA has decided to withdraw EDMS from the Guideline's
appendix A. We stated that no new information was therefore provided in
that notice, and we affirmed support for EDMS' removal from appendix A.
This removal, which we promulgate today, obviates the need for EDMS'
documentation and evaluation at this time.
V. Discussion of Public Comments on Our September 8, 2003 Notice of
Data Availability
As mentioned in section III, after AERMOD was revised pursuant to
comments received on the April 21, 2000 proposal, a Notice of Data
Availability (NDA) was issued on September 8, 2003 to explain the
modifications and to reveal AERMOD's new evaluation data. Public
comments were solicited for 30 days and posted electronically in
eDocket OAR-2003-0201.\1\ (As mentioned in section IV, additional
comments received since we published the final rule on April 15, 2003
are filed in Docket A-99-05; category IV-E.) We summarized these
comments and developed detailed responses; these appear as appendix C
to the Response-to-Comments document.\4\ In appendix C, we considered
and discussed all significant comments, developed responses, and
documented conclusions on appropriate actions for today's notice.
Whenever the comments revealed any new information or suggested any
alternative solutions, we considered them in our final action and made
corrections or enhancements where appropriate.
In the remainder of this preamble section we highlight the main
issues raised by the commenters who reviewed the NDA, and summarize our
responses. These comments broadly fall into two categories: technical/
operational, and administrative.
The technical/operational comments were varied. One commenter
thought EPA's sensitivity studies for simulating area sources were too
limited, and noted that AERMOD, when used to simulate an area source
adjacent to gently sloping terrain, produced ground-level
concentrations not unlike those from ISC3ST. In response we explained
qualitatively how AERMOD interprets this situation and cautioned that
reviewing authorities should be consulted in such scenarios for
guidance on switch settings. Other commenters believed that AERMOD
exhibited unrealistic treatment of complex terrain elements and offered
supporting data. In response, AERMIC concluded that AERMOD does exhibit
terrain amplification factors on the windward side of isolated hills,
where impacts are expected to be greatest. Commenters also presented
evidence that the PRIME algorithm in AERMOD misbehaves in its treatment
of building wake and wind incidence. Another model was cited as having
better skill in this regard. In response, we acknowledged this but
established that AERMOD's capability was acceptable for handling the
majority of building geometries encountered (see Response-to-Comments
document \4\ for more details).
A number of commenters addressed administrative or procedural
matters. Some believed that the transition period for implementation--
one year--is too short. We explained in response that one year is
consistent with past practice and is adequate for most users and
reviewing authorities given our previous experience with new models and
the fact that AERMOD has been in the public domain for several years.
Some were disappointed that the review period (30 days) for the NDA was
too short. We believe that the period was adequate to review the two
reports that presented updated information on the performance and
practical consequences of the model as revised. Regarding the
evaluation/comparison regime used for AERMOD, others objected to the
methodology used to evaluate AERMOD (one that emphasizes Robust High
Concentration), claiming it is ill-suited to the way dispersion models
estimate ambient concentrations. We acknowledged that other methods are
available that are designed to reflect the underlying physics and
formulations of dispersion models, and may be more robust in their
mechanisms to account for the stochastic nature of the atmosphere. In
fact, we cited several recent cases from the literature in which such
methods were applied in evaluations that included AERMOD. We also
explained that the approach taken by AERMIC was based on existing
guidance in section 9 of Appendix W, and expressed a commitment to
explore other methods in the future, including an update to section 9.
We believe however that the evaluation methodology used was reasonable
for its intended purpose--examining a large array of concentrations for
a wide variety of source types--and confers a measure of consistency
given its past use. Other commenters expressed disappointment that
AERMOD wasn't compared to state-of-the-science models as advised in its
peer review report. In response, we cited a substantial list of studies
in which AERMOD has, in fact, been compared to some of these models,
e.g., HPDM and ADMS (in various combinations). On the whole, as we
noted in our response, AERMOD typically performed as well as HPDM and
ADMS, and all of them generally performed better than ISC3ST. Still
others expressed disappointment that the evaluation input data weren't
posted on our Web site until January 22, 2004--three months after the
close of the comment period. We acknowledge that the input data were
not posted when the NDA was published. However, the actual evaluation
input data for AERMOD had not been requested previously, and we did not
believe they were required as a basis for reviewing the reports we
released. Moreover, since the posting, we are unaware of any belated
adverse comments from anyone attempting to access and use the data.
We believe we have carefully considered and responded to public
comments and concerns regarding AERMOD. We have also made efforts to
update appendix W to better reflect current practice in model
solicitation, evaluation and selection. We also have made other
technical revisions so the guidance conforms with the latest form of
the PM-10 National Ambient Air Quality Standard.
[[Page 68225]]
VI. Final Action
In this section we explain the changes to the Guideline in today's
action in terms of the main technical and policy concerns addressed by
the Agency in its response to public comments (sections IV & V). Air
quality modeling involves estimating ambient concentrations using
scientific methodologies selected from a range of possible methods, and
should utilize the most advanced practical technology that is available
at a reasonable cost to users, keeping in mind the intended uses of the
modeling and ensuring transparency to the public. With these changes,
we believe that the Guideline continues to reflect recent advances in
the field and balance these important considerations. Today's action
amends Appendix W of 40 CFR part 51 as detailed below:
AERMOD
Based on the supporting information contained in the docket, and
reflected in peer review and public comments, we find that the AERMOD
modeling system and PRIME are based on sound scientific principles and
provide significant improvements over the current regulatory model,
ISC3ST. AERMOD characterizes plume dispersion better than ISC3ST. The
accuracy of the AERMOD system is generally well-documented and superior
to that of ISC3ST. We are adopting the model based on its performance
and other factors.
Public comments on the April 2000 proposal expressed significant
concern about the need to use two models (AERMOD and ISC-PRIME) to
simulate just one source when downwash posed a potential impact. In
response to this concern we incorporated PRIME into AERMOD and
documented satisfactory tests of the algorithm. AERMOD, with the
inclusion of PRIME, is now appropriate and practical for regulatory
applications.
The state-of-the-science for modeling atmospheric deposition
continues to evolve, the best techniques are currently being assessed,
and their results are being compared with observations. Consequently,
as we now say in Guideline paragraph 4.2.2(c), the approach taken for
any regulatory purpose should be coordinated with the appropriate
reviewing authority. We agreed with the public comments calling for the
addition of state-of-the-science deposition algorithms, and developed a
modification to AERMOD (02222) for beta testing. This model, AERMOD
(04079) was posted on our Web site http://www.epa.gov/scram001/tt25.htm#aermoddep
on March 19, 2004. The latest version of AERMOD may
now be used for deposition analysis in special situations.
Since AERMOD treats dispersion in complex terrain, we have merged
sections 4 and 5 of appendix W, as proposed in the April 2000 NPR. And
while AERMOD produces acceptable regulatory design concentrations in
complex terrain, it does not replace CTDMPLUS for detailed or receptor-
oriented complex terrain analysis, as we have made clear in Guideline
section 4.2.2. CTDMPLUS remains available for use in complex terrain.
We have implemented the majority of suggestions to improve the
AERMET, AERMAP, and AERMOD source code to reflect all the latest
features that have been available in ISC3ST and that are available in
the latest versions of Fortran compilers. Also, the latest formats for
meteorological and terrain input data are now accepted by the new
versions of AERMET and AERMAP. Our guidance, documentation and users'
guides have been modified in response to a number of detailed comments.
With respect to AERMOD (02222)'s performance, we have concluded
that:
(1) AERMOD (99351), the version proposed in April 2000, performs
significantly better than ISC3ST, and AERMOD (02222) performs slightly
better than AERMOD (99351) in non-downwash settings in both simple and
complex terrain;
(2) The performance evaluation indicates that AERMOD (02222)
performs slightly better than ISC-PRIME for downwash cases.
With respect to changes in AERMOD's regulatory design
concentrations compared to those for ISC3ST, we have concluded that:
For non-downwash settings, AERMOD (02222), on average,
tends to predict concentrations closer to ISC3ST, and with somewhat
smaller variations, than the April 2000 proposal of AERMOD;
Where downwash is a significant factor in the air
dispersion analysis, AERMOD (02222) predicts maximum concentrations
that are very similar to ISC-PRIME's predictions;
For those source scenarios where maximum 1-hour cavity
concentrations are calculated, the average AERMOD (02222)-predicted
cavity concentration tends to be about the same as the average ISC-
PRIME cavity concentrations; and
In complex terrain, the consequences of using AERMOD
(02222) instead of ISC3ST remained essentially unchanged in general,
although they varied based on individual circumstances.
Since AERMOD (02222) was released, an updated version was posted on
our Web site on March 22, 2004: AERMOD (04079). The version we are
releasing pursuant to today's promulgation, however, is AERMOD (04300).
This version, consonant with AERMOD (02222) in its formulations,
addresses the following minor code issues:
The area source algorithm in simple and complex terrain
required a correction to the way the dividing streamline height is
calculated.
In PRIME, incorrect turbulence parameters were being
passed to one of the numerical plume rise routines, and this has been
corrected.
A limit has been placed on plume cooling within PRIME to
avoid supercooling, which had been causing runtime instability.
A correction has been made to avoid AERMOD's termination
under certain situations with capped stacks (i.e., where the routine
was attempting to take a square root of a negative number). Our testing
has demonstrated only very minor impacts from these corrections on the
evaluation results or the consequence analysis.
AERMOD (04300) has other draft portions of code that represent
options not required for regulatory applications. These include:
Dry and wet deposition for both gases and particles;
The ozone limiting method (OLM), referenced in section
5.2.4 (Models for Nitrogen Dioxide--Annual Average) of the Guideline
for treating NOX conversion; and
The Plume Volume Molar Ratio Method (PVMRM) for treating
NOX conversion.
The bulk Richardson number approach (discussed earlier)
for using near-surface temperature difference has been corrected in
AERMOD (04300).
Based on the technical information contained in the docket for this
rule, and with consideration of the performance analysis in combination
with the analysis of design concentrations, we believe that AERMOD is
appropriate for regulatory use and we are revising the Guideline to
adopt it as a refined model today.
In implementing the changes to the Guideline, we recognize that
there may arise occasions in which the application of a new model can
result in the discovery by a permit applicant of previously unknown
violations of NAAQS or PSD increments due to emissions from existing
nearby sources. This potential has been acknowledged previously and is
addressed in existing EPA guidance (``Air Quality Analysis for
Prevention of Significant Deterioration
[[Page 68226]]
(PSD),'' Gerald A. Emison, July 5, 1988). To summarize briefly, the
guidance identifies three possible outcomes of modeling by a permit
applicant and details actions that should be taken in response to each:
1. Where dispersion modeling shows no violation of a NAAQS or PSD
increment in the impact area of the proposed source, a permit may be
issued and no further action is required.
2. Where dispersion modeling predicts a violation of a NAAQS or PSD
increment within the impact area but it is determined that the proposed
source will not have a significant impact (i.e., will not be above de
minimis levels) at the point and time of the modeled violation, then
the permit may be issued immediately, but the State must take
appropriate actions to remedy the violations within a timely manner.
3. Where dispersion modeling predicts a violation of a NAAQS or PSD
increment within the impact area and it is determined that the proposed
source will have a significant impact at the point and time of the
modeled violation, then the permit may not be issued until the source
owner or operator eliminates or reduces that impact below significance
levels through additional controls or emissions offsets. Once it does
so, then the permit may be issued even if the violation persists after
the source owner or operator eliminates its contribution, but the State
must take further appropriate actions at nearby sources to eliminate
the violations within a timely manner.
In previous promulgations, we have traditionally allowed a one-year
transition (``grandfather'') period for new refined techniques.
Accordingly, for appropriate applications, AERMOD may be substituted
for ISC3 during the one-year period following the promulgation of
today's notice. Beginning one year after promulgation of today's
notice, (1) applications of ISC3 with approved protocols may be
accepted (see DATES section) and (2) AERMOD should be used for
appropriate applications as a replacement for ISC3.
We separately issue guidance for use of modeling for facility-
specific and community-scale air toxics risk assessments through the
Air Toxics Risk Assessment Reference Library.\18\ We recognize that the
tools and approaches recommended therein will eventually reflect the
improved formulations of the AERMOD modeling system and we expect to
appropriately incorporate them as expeditiously as practicable. In the
interim, as appropriate, we will consider the use of either ISC3 or
AERMOD in air toxic risk assessment applications.
---------------------------------------------------------------------------
\18\ http://www.epa.gov/ttn/fera/risk --atra--main.html.
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EDMS
FAA has completed development of the new EDMS4.0 to incorporate
AERMOD. The result is a conforming enhancement that offers a stronger
scientific basis for air quality modeling. FAA has made this model
available on its Web site, which we cite in an updated Guideline
paragraph 7.2.4(c). As described earlier in this preamble, the summary
description for EDMS will be removed from appendix A.
VII. Final Editorial Changes to Appendix W
Today's update of the Guideline takes the form of many revisions,
and some of the text is unaltered. Therefore, as a purely practical
matter, we have chosen to publish the new version of the entire text of
appendix W and its appendix A. Guidance and editorial changes
associated with the resolution of the issues discussed in the previous
section are adopted in the appropriate sections of the Guideline, as
follows:
Preface
You will note some minor revisions of appendix W to reflect current
EPA practice.
Section 4
As mentioned earlier, we revised section 4 to present AERMOD as a
refined regulatory modeling technique for particular applications.
Section 5
As mentioned above, we merged pertinent guidance in section 5
(Modeling in Complex Terrain) with that in section 4. With the
anticipated widespread use of AERMOD for all terrain types, there is no
longer any utility in the previous differentiation between simple and
complex terrain for model selection. To further simplify, the list of
acceptable, yet equivalent, screening techniques for complex terrain
was removed. CTSCREEN and guidance for its use are retained; CTSCREEN
remains acceptable for all terrain above stack top. The screening
techniques whose descriptions we removed, i.e., Valley (as implemented
in SCREEN3), COMPLEX I (as implemented in ISC3ST), and RTDM remain
available for use in applicable cases where established/accepted
procedures are used. Consultation with the appropriate reviewing
authority is still advised for application of these screening models.
Section 6
As proposed, we renumbered this to become section 5. In subsection
5.1, we reference the Plume Volume Molar Ratio Method (PVMRM) for point
sources of NOX, and mention that it is currently being
tested to determine suitability as a refined method.
Section 7
As proposed, we renumbered this to become section 6. We updated the
reference to the Emissions and Dispersion Modeling System (EDMS).
Section 8
As proposed, we revised section 8 (renumbered to section 7) to
provide guidance for using AERMET (AERMOD's meteorological
preprocessor).
In subsection 7.2.4, we introduce the atmospheric
stability characterization for AERMOD.
In subsection 7.2.5, we describe the plume rise approaches
used by AERMOD.
Section 9
As proposed, we renumbered section 9 to become section 8. We added
paragraphs 8.3.1.2(e) and 8.3.1.2(f) to clarify use of site specific
meteorological data for driving CALMET in the separate circumstances of
long range transport and for complex terrain applications.
Section 10
As proposed, we revised section 10 (renumbered section 9) to
include AERMOD. In May 1999, the D.C. Court of Appeals vacated the PM-
10 standard we promulgated in 1997, and this standard has since been
removed from the CFR (69 FR 45592; July 30, 2004). Paragraph
10.2.3.2(a) has been corrected to be consistent with the current
(original) PM-10 standard, which is based on expected exceedances.
Section 11
As proposed, we renumbered section 11 to become section 10.
Sections 12 & 13
We renumbered section 12 to become section 11, and section 13
(References) to become section 12. We revised renumbered section 12 by
adding some references, deleting obsolete/superseded ones, and
resequencing. You will note that the peer scientific review for AERMOD
and latest evaluation references have been included.
Appendix A
We added AERMOD (with the PRIME downwash algorithm integrated) to
[[Page 68227]]
appendix A. We removed EDMS from appendix A. We also updated the
description for CALPUFF, and made minor updates to some of the other
model descriptions.
Availability of Related Information
Our Air Quality Modeling Group maintains an Internet Web site
(Support Center for Regulatory Air Models--SCRAM) at: http://www.epa.gov/scram001.
You may find codes and documentation for models
referenced in today's action on the SCRAM Web site. In addition, we
have uploaded various support documents (e.g., evaluation reports).
VIII. Statutory and Executive Order Reviews
A. Executive Order 12866: Regulatory Planning and Review
Under Executive Order 12866 [58 FR 51735 (October 4, 1993)], the
Agency must determine whether the regulatory action is ``significant''
and therefore subject to review by the Office of Management and Budget
(OMB) and the requirements of the Executive Order. The Order defines
``significant regulatory action'' as one that is likely to result in a
rule that may:
(1) Have an annual effect on the economy of $100 million or more or
adversely affect in a material way the economy, a sector of the
economy, productivity, competition, jobs, the environment, public
health or safety, or State, local, or tribal governments or
communities;
(2) Create a serious inconsistency or otherwise interfere with an
action taken or planned by another agency;
(3) Materially alter the budgetary impact of entitlements, grants,
user fees, or loan programs of the rights and obligations of recipients
thereof; or
(4) Raise novel legal or policy issues arising out of legal
mandates, the President's priorities, or the principles set forth in
the Executive Order.
It has been determined that this rule is not a ``significant
regulatory action'' under the terms of Executive Order 12866 and is
therefore not subject to EO 12866 review.
B. Paperwork Reduction Act
This final rule does not contain any information collection
requirements subject to review by OMB under the Paperwork Reduction
Act, 44 U.S.C. 3501 et seq.
Burden means the total time, effort, or financial resources
expended by persons to generate, maintain, retain, or disclose or
provide information to or for a Federal agency. This includes the time
needed to review instructions; develop, acquire, install, and utilize
technology and systems for the purposes of collecting, validating, and
verifying information, processing and maintaining information, and
disclosing and providing information; adjust the existing ways to
comply with any previously applicable instructions and requirements;
train personnel to be able to respond to a collection of information;
search data sources; complete and review the collection of information;
and transmit or otherwise disclose the information.
An agency may not conduct or sponsor, and a person is not required
to respond to a collection of information unless it displays a
currently valid OMB control number. The OMB control numbers for EPA's
regulations in 40 CFR are listed in 40 CFR part 9.
C. Regulatory Flexibility Act (RFA)
The RFA generally requires an agency to prepare a regulatory
flexibility analysis of any rule subject to notice and comment
rulemaking requirements under the Administrative Procedure Act or any
other statute unless the agency certifies that the rule will not have a
significant economic impact on a substantial number of small entities.
Small entities include small businesses, small organizations, and small
governmental jurisdictions.
For purposes of assessing the impact of today's rule on small
entities, small entities are defined as: (1) A small business that
meets the RFA default definitions for small business (based on Small
Business Administration size standards), as described in 13 CFR
121.201; (2) a small governmental jurisdiction that is a government of
a city, county, town, school district or special district with a
population of less than 50,000; and (3) a small organization that is
any not-for-profit enterprise which is independently owned and operated
and is not dominant in its field.
After considering the economic impacts of today's final rule on
small entities, I certify that this action will not have a significant
economic impact on a substantial number of small entities. As this rule
merely updates existing technical requirements for air quality modeling
analyses mandated by various CAA programs (e.g., prevention of
significant deterioration, new source review, State Implementation Plan
revisions) and imposes no new regulatory burdens, there will be no
additional impact on small entities regarding reporting, recordkeeping,
and compliance requirements.
D. Unfunded Mandates Reform Act of 1995
Title II of the Unfunded Mandates Reform Act of 1995 (UMRA), Public
Law 104-4, establishes requirements for Federal agencies to assess the
effects of their regulatory actions on State, local, and tribal
governments and the private sector. Under section 202 of the UMRA, EPA
generally must prepare a written statement, including a cost-benefit
analysis, for proposed and final rules with ``Federal mandates'' that
may result in expenditures to State, local, and tribal governments, in
the aggregate, or to the private sector, of $100 million or more in any
one year. Before promulgating an EPA rule for which a written statement
is needed, section 205 of the UMRA generally requires EPA to identify
and consider a reasonable number of regulatory alternatives and adopt
the least costly, most cost-effective or least burdensome alternative
that achieves the objectives of the rule. The provisions of section 205
do not apply when they are inconsistent with applicable law. Moreover,
section 205 allows EPA to adopt an alternative other than the least
costly, most cost-effective or least burdensome alternative if the
Administrator publishes with the final rule an explanation why that
alternative was not adopted. Before EPA establishes any regulatory
requirements that may significantly or uniquely affect small
governments, including tribal governments, it must have developed under
section 203 of the UMRA a small government agency plan.
The plan must provide for notifying potentially affected small
governments, enabling officials of affected small governments to have
meaningful and timely input in the development of EPA regulatory
proposals with significant Federal intergovernmental mandates, and
informing, educating, and advising small governments on compliance with
the regulatory requirements.
Today's rule recommends a new modeling system, AERMOD, to replace
ISC3ST as an analytical tool for use in SIP revisions and for
calculating PSD increment consumption. AERMOD has been used for these
purposes on a case-by-case basis (per Guideline subsection 3.2.2) for
several years. Since the two modeling systems are comparable in scope
and purpose, use of AERMOD itself does not involve any significant
increase in costs. Moreover, modeling costs (which include those for
input data acquisition) are typically among the implementation costs
that are considered as part of the programs (i.e., PSD) that establish
and periodically revise requirements for compliance.
[[Page 68228]]
Any incremental modeling costs attributable to today's rule do not
approach the $100 million threshold prescribed by UMRA. EPA has
determined that this rule contains no regulatory requirements that
might significantly or uniquely affect small governments. This rule
therefore contains no Federal mandates (under the regulatory provisions
of Title II of the UMRA) for State, local, or tribal governments or the
private sector.
E. Executive Order 13132: Federalism
Executive Order 13132, entitled ``Federalism'' (64 FR 43255, August
10, 1999), requires EPA to develop an accountable process to ensure
``meaningful and timely input by State and local officials in the
development of regulatory policies that have federalism implications.''
``Policies that have federalism implications'' is defined in the
Executive Order to include regulations that have ``substantial direct
effects on the States, on the relationship between the national
government and the States, or on the distribution of power and
responsibilities among the various levels of government.''
This final rule does not have federalism implications. It will not
have substantial direct effects on the States, on the relationship
between the national government and the States, or on the distribution
of power and responsibilities among the various levels of government,
as specified in Executive Order 13132. This rule does not create a
mandate on State, local or tribal governments. The rule does not impose
any enforceable duties on these entities (see D. Unfunded Mandates
Reform Act of 1995, above). The rule would add better, more accurate
techniques for air dispersion modeling analyses and does not impose any
additional requirements for any of the affected parties covered under
Executive Order 13132. Thus, Executive Order 13132 does not apply to
this rule.
F. Executive Order 13175: Consultation and Coordination With Indian
Tribal Governments
Executive Order 13175, entitled ``Consultation and Coordination
with Indian Tribal Governments'' (65 FR 67249, November 9, 2000),
requires EPA to develop an accountable process to ensure ``meaningful
and timely input by tribal officials in the development of regulatory
policies that have tribal implications.'' This final rule does not have
tribal implications, as specified in Executive Order 13175. As stated
above (see D. Unfunded Mandates Reform Act of 1995, above), the rule
does not impose any new requirements for calculating PSD increment
consumption, and does not impose any additional requirements for the
regulated community, including Indian Tribal Governments. Thus,
Executive Order 13175 does not apply to this rule.
Today's final rule does not significantly or uniquely affect the
communities of Indian tribal governments. Accordingly, the requirements
of section 3(b) of Executive Order 13175 do not apply to this rule.
G. Executive Order 13045: Protection of Children From Environmental
Health and Safety Risks
Executive Order 13045 applies to any rule that EPA determines (1)
to be ``economically significant'' as defined under Executive Order
12866, and (2) the environmental health or safety risk addressed by the
rule has a disproportionate effect on children. If the regulatory
action meets both the criteria, the Agency must evaluate the
environmental health or safety effects of the planned rule on children;
and explain why the planned regulation is preferable to other
potentially effective and reasonably feasible alternatives considered
by the Agency.
This final rule is not subject to Executive Order 13045, entitled
``Protection of Children from Environmental Health Risks and Safety
Risks'' (62 FR 19885, April 23, 1997) because it does not impose an
economically significant regulatory action as defined by Executive
Order 12866 and the action does not involve decisions on environmental
health or safety risks that may disproportionately affect children.
H. Executive Order 13211: Actions That Significantly Affect Energy
Supply, Distribution, or Use
This rule is not subject to Executive Order 13211, ``Actions
Concerning Regulations That Significantly Affect Energy Supply,
Distribution, or Use'' (66 FR 28355 (May 22, 2001)) because it is not a
significant regulatory action under Executive Order 12866.
I. National Technology Transfer and Advancement Act of 1995
Section 12(d) of the National Technology Transfer and Advancement
Act of 1995 (``NTTAA''), Public Law 104-113, section 12(d) (15 U.S.C.
272 note) directs EPA to use voluntary consensus standards in its
regulatory activities unless to do so would be inconsistent with
applicable law or otherwise impractical. Voluntary consensus standards
are technical standards (e.g., materials specifications, test methods,
sampling procedures, and business practices) that are developed or
adopted by voluntary consensus standards bodies. The NTTAA directs EPA
to provide Congress, through OMB, explanations when the Agency decides
not to use available and applicable voluntary consensus standards.
This action does not involve technical standards. Therefore, EPA
did not consider the use of any voluntary consensus standards.
J. Congressional Review Act of 1998
The Congressional Review Act, 5 U.S.C. 801 et seq., as added by the
Small Business Regulatory Enforcement Fairness Act of 1996, generally
provides that before a rule may take effect, the agency promulgating
the rule must submit a rule report, which includes a copy of the rule,
to each House of the Congress and to the Comptroller General of the
United States. EPA will submit a report containing this rule and other
required information to the U.S. Senate, the U.S. House of
Representatives, and the Comptroller General of the United States prior
to publication of the rule in the Federal Register. A Major rule cannot
take effect until 60 days after it is published in the Federal
Register. This action is not a ``major rule'' as defined by 5 U.S.C.
804(2), and will be effective 30 days from the publication date of this
notice.
List of Subjects in 40 CFR Part 51
Environmental protection, Administrative practice and procedure,
Air pollution control, Carbon monoxide, Intergovernmental relations,
Nitrogen oxides, Ozone, Particulate Matter, Reporting and recordkeeping
requirements, Sulfur oxides.
Dated: October 21, 2005.
Stephen L. Johnson,
Administrator.
0
Part 51, chapter I, title 40 of the Code of Federal Regulations is
amended as follows:
PART 51--REQUIREMENTS FOR PREPARATION, ADOPTION, AND SUBMITTAL OF
IMPLEMENTATION PLANS
0
1. The authority citation for part 51 continues to read as follows:
Authority: 23 U.S.C. 100; 42 U.S.C. 7401-7671q.
0
2. Appendix W to Part 51 revised to read as follows:
[[Page 68229]]
Appendix W to Part 51--Guideline on Air Quality Models
Preface
a. Industry and control agencies have long expressed a need for
consistency in the application of air quality models for regulatory
purposes. In the 1977 Clean Air Act, Congress mandated such
consistency and encouraged the standardization of model
applications. The Guideline on Air Quality Models (hereafter,
Guideline) was first published in April 1978 to satisfy these
requirements by specifying models and providing guidance for their
use. The Guideline provides a common basis for estimating the air
quality concentrations of criteria pollutants used in assessing
control strategies and developing emission limits.
b. The continuing development of new air quality models in
response to regulatory requirements and the expanded requirements
for models to cover even more complex problems have emphasized the
need for periodic review and update of guidance on these techniques.
Historically, three primary activities have provided direct input to
revisions of the Guideline. The first is a series of annual EPA
workshops conducted for the purpose of ensuring consistency and
providing clarification in the application of models. The second
activity was the solicitation and review of new models from the
technical and user community. In the March 27, 1980 Federal
Register, a procedure was outlined for the submittal to EPA of
privately developed models. After extensive evaluation and
scientific review, these models, as well as those made available by
EPA, have been considered for recognition in the Guideline. The
third activity is the extensive on-going research efforts by EPA and
others in air quality and meteorological modeling.
c. Based primarily on these three activities, new sections and
topics have been included as needed. EPA does not make changes to
the guidance on a predetermined schedule, but rather on an as-needed
basis. EPA believes that revisions of the Guideline should be timely
and responsive to user needs and should involve public participation
to the greatest possible extent. All future changes to the guidance
will be proposed and finalized in the Federal Register. Information
on the current status of modeling guidance can always be obtained
from EPA's Regional Offices.
Table of Contents
List of Tables
1.0 Introduction
2.0 Overview of Model Use
2.1 Suitability of Models
2.2 Levels of Sophistication of Models
2.3 Availability of Models
3.0 Recommended Air Quality Models
3.1 Preferred Modeling Techniques
3.1.1 Discussion
3.1.2 Recommendations
3.2 Use of Alternative Models
3.2.1 Discussion
3.2.2 Recommendations
3.3 Availability of Supplementary Modeling Guidance
4.0 Stationary-Source Models
4.1 Discussion
4.2 Recommendations
4.2.1 Screening Techniques
4.2.1.1 Simple Terrain
4.2.1.2 Complex Terrain
4.2.2 Refined Analytical Techniques
5.0 Models for Ozone, Particulate Matter, Carbon Monoxide, Nitrogen
Dioxide, and Lead
5.1 Discussion
5.2 Recommendations
5.2.1 Models for Ozone
5.2.2 Models for Particulate Matter
5.2.2.1 PM-2.5
5.2.2.2 PM-10
5.2.3 Models for Carbon Monoxide
5.2.4 Models for Nitrogen Dioxide (Annual Average)
5.2.5 Models for Lead
6.0 Other Model Requirements
6.1 Discussion
6.2 Recommendations
6.2.1 Visibility
6.2.2 Good Engineering Practice Stack Height
6.2.3 Long Range Transport (LRT) (i.e., beyond 50 km)
6.2.4 Modeling Guidance for Other Governmental Programs
7.0 General Modeling Considerations
7.1 Discussion
7.2 Recommendations
7.2.1 Design Concentrations
7.2.2 Critical Receptor Sites
7.2.3 Dispersion Coefficients
7.2.4 Stability Categories
7.2.5 Plume Rise
7.2.6 Chemical Transformation
7.2.7 Gravitational Settling and Deposition
7.2.8 Complex Winds
7.2.9 Calibration of Models
8.0 Model Input Data
8.1 Source Data
8.1.1 Discussion
8.1.2 Recommendations
8.2 Background Concentrations
8.2.1 Discussion
8.2.2 Recommendations (Isolated Single Source)
8.2.3 Recommendations (Multi-Source Areas)
8.3 Meteorological Input Data
8.3.1 Length of Record of Meteorological Data
8.3.2 National Weather Service Data
8.3.3 Site Specific Data
8.3.4 Treatment of Near-calms and Calms
9.0 Accuracy and Uncertainty of Models
9.1 Discussion
9.1.1 Overview of Model Uncertainty
9.1.2 Studies of Model Accuracy
9.1.3 Use of Uncertainty in Decision-Making
9.1.4 Evaluation of Models
9.2 Recommendations
10.0 Regulatory Application of Models
10.1 Discussion
10.2 Recommendations
10.2.1 Analysis Requirements
10.2.2 Use of Measured Data in Lieu of Model Estimates
10.2.3 Emission Limits
11.0 Bibliography
12.0 References
Appendix A to Appendix W of 40 CFR Part 51--Summaries of Preferred
Air Quality Models
List of Tables
------------------------------------------------------------------------
Table No. Title
------------------------------------------------------------------------
4-1a................................ Neutral/Stable Meteorological
Matrix for CTSCREEN.
4-1b................................ Unstable/Convective Meteorological
Matrix for CTSCREEN.
8-1................................. Model Emission Input Data for
Point Sources.
8-2................................. Point Source Model Emission Input
Data for NAAQS Compliance in PSD
Demonstrations.
8-3................................. Averaging Times for Site Specific
Wind and Turbulence Measurements.
------------------------------------------------------------------------
1.0 Introduction
a. The Guideline recommends air quality modeling techniques that
should be applied to State Implementation Plan (SIP) revisions for
existing sources and to new source reviews (NSR), including
prevention of significant deterioration (PSD).1 2 3
Applicable only to criteria air pollutants, it is intended for use
by EPA Regional Offices in judging the adequacy of modeling analyses
performed by EPA, State and local agencies and by industry. The
guidance is appropriate for use by other Federal agencies and by
State agencies with air quality and land management
responsibilities. The Guideline serves to identify, for all
interested parties, those techniques and data bases EPA considers
acceptable. The Guideline is not intended to be a compendium of
modeling techniques. Rather, it should serve as a common measure of
acceptable technical analysis when supported by sound scientific
judgment.
b. Due to limitations in the spatial and temporal coverage of
air quality measurements, monitoring data normally are not
sufficient as the sole basis for demonstrating the adequacy of
emission limits for existing sources. Also, the impacts of new
sources that do not yet exist can only be determined through
modeling. Thus, models, while uniquely filling one program need,
have become a primary analytical tool in most air quality
assessments. Air quality measurements can be used in a complementary
manner to dispersion models, with due regard for the strengths and
weaknesses of both analysis techniques. Measurements are
particularly useful in assessing the accuracy of model estimates.
The use of air quality measurements alone however could be
preferable, as detailed in a later section of this document, when
models are found to be unacceptable and monitoring data with
sufficient spatial and temporal coverage are available.
c. It would be advantageous to categorize the various regulatory
programs and to apply
[[Page 68230]]
a designated model to each proposed source needing analysis under a
given program. However, the diversity of the nation's topography and
climate, and variations in source configurations and operating
characteristics dictate against a strict modeling ``cookbook''.
There is no one model capable of properly addressing all conceivable
situations even within a broad category such as point sources.
Meteorological phenomena associated with threats to air quality
standards are rarely amenable to a single mathematical treatment;
thus, case-by-case analysis and judgment are frequently required. As
modeling efforts become more complex, it is increasingly important
that they be directed by highly competent individuals with a broad
range of experience and knowledge in air quality meteorology.
Further, they should be coordinated closely with specialists in
emissions characteristics, air monitoring and data processing. The
judgment of experienced meteorologists and analysts is essential.
d. The model that most accurately estimates concentrations in
the area of interest is always sought. However, it is clear from the
needs expressed by the States and EPA Regional Offices, by many
industries and trade associations, and also by the deliberations of
Congress, that consistency in the selection and application of
models and data bases should also be sought, even in case-by-case
analyses. Consistency ensures that air quality control agencies and
the general public have a common basis for estimating pollutant
concentrations, assessing control strategies and specifying emission
limits. Such consistency is not, however, promoted at the expense of
model and data base accuracy. The Guideline provides a consistent
basis for selection of the most accurate models and data bases for
use in air quality assessments.
e. Recommendations are made in the Guideline concerning air
quality models, data bases, requirements for concentration
estimates, the use of measured data in lieu of model estimates, and
model evaluation procedures. Models are identified for some specific
applications. The guidance provided here should be followed in air
quality analyses relative to State Implementation Plans and in
supporting analyses required by EPA, State and local agency air
programs. EPA may approve the use of another technique that can be
demonstrated to be more appropriate than those recommended in this
guide. This is discussed at greater length in Section 3. In all
cases, the model applied to a given situation should be the one that
provides the most accurate representation of atmospheric transport,
dispersion, and chemical transformations in the area of interest.
However, to ensure consistency, deviations from this guide should be
carefully documented and fully supported.
f. From time to time situations arise requiring clarification of
the intent of the guidance on a specific topic. Periodic workshops
are held with the headquarters, Regional Office, State, and local
agency modeling representatives to ensure consistency in modeling
guidance and to promote the use of more accurate air quality models
and data bases. The workshops serve to provide further explanations
of Guideline requirements to the Regional Offices and workshop
reports are issued with this clarifying information. In addition,
findings from ongoing research programs, new model development, or
results from model evaluations and applications are continuously
evaluated. Based on this information changes in the guidance may be
indicated.
g. All changes to the Guideline must follow rulemaking
requirements since the Guideline is codified in Appendix W of Part
51. EPA will promulgate proposed and final rules in the Federal
Register to amend this Appendix. Ample opportunity for public
comment will be provided for each proposed change and public
hearings scheduled if requested.
h. A wide range of topics on modeling and data bases are
discussed in the Guideline. Section 2 gives an overview of models
and their appropriate use. Section 3 provides specific guidance on
the use of ``preferred'' air quality models and on the selection of
alternative techniques. Sections 4 through 7 provide recommendations
on modeling techniques for application to simple-terrain stationary
source problems, complex terrain problems, and mobile source
problems. Specific modeling requirements for selected regulatory
issues are also addressed. Section 8 discusses issues common to many
modeling analyses, including acceptable model components. Section 9
makes recommendations for data inputs to models including source,
meteorological and background air quality data. Section 10 covers
the uncertainty in model estimates and how that information can be
useful to the regulatory decision-maker. The last chapter summarizes
how estimates and measurements of air quality are used in assessing
source impact and in evaluating control strategies.
i. Appendix W to 40 CFR Part 51 itself contains an appendix:
Appendix A. Thus, when reference is made to ``Appendix A'' in this
document, it refers to Appendix A to Appendix W to 40 CFR Part 51.
Appendix A contains summaries of refined air quality models that are
``preferred'' for specific applications; both EPA models and models
developed by others are included.
2.0 Overview of Model Use
a. Before attempting to implement the guidance contained in this
document, the reader should be aware of certain general information
concerning air quality models and their use. Such information is
provided in this section.
2.1 Suitability of Models
a. The extent to which a specific air quality model is suitable
for the evaluation of source impact depends upon several factors.
These include: (1) The meteorological and topographic complexities
of the area; (2) the level of detail and accuracy needed for the
analysis; (3) the technical competence of those undertaking such
simulation modeling; (4) the resources available; and (5) the detail
and accuracy of the data base, i.e., emissions inventory,
meteorological data, and air quality data. Appropriate data should
be available before any attempt is made to apply a model. A model
that requires detailed, precise, input data should not be used when
such data are unavailable. However, assuming the data are adequate,
the greater the detail with which a model considers the spatial and
temporal variations in emissions and meteorological conditions, the
greater the ability to evaluate the source impact and to distinguish
the effects of various control strategies.
b. Air quality models have been applied with the most accuracy,
or the least degree of uncertainty, to simulations of long term
averages in areas with relatively simple topography. Areas subject
to major topographic influences experience meteorological
complexities that are extremely difficult to simulate. Although
models are available for such circumstances, they are frequently
site specific and resource intensive. In the absence of a model
capable of simulating such complexities, only a preliminary
approximation may be feasible until such time as better models and
data bases become available.
c. Models are highly specialized tools. Competent and
experienced personnel are an essential prerequisite to the
successful application of simulation models. The need for
specialists is critical when the more sophisticated models are used
or the area being investigated has complicated meteorological or
topographic features. A model applied improperly, or with
inappropriate data, can lead to serious misjudgements regarding the
source impact or the effectiveness of a control strategy.
d. The resource demands generated by use of air quality models
vary widely depending on the specific application. The resources
required depend on the nature of the model and its complexity, the
detail of the data base, the difficulty of the application, and the
amount and level of expertise required. The costs of manpower and
computational facilities may also be important factors in the
selection and use of a model for a specific analysis. However, it
should be recognized that under some sets of physical circumstances
and accuracy requirements, no present model may be appropriate.
Thus, consideration of these factors should lead to selection of an
appropriate model.
2.2 Levels of Sophistication of Models
a. There are two levels of sophistication of models. The first
level consists of relatively simple estimation techniques that
generally use preset, worst-case meteorological conditions to
provide conservative estimates of the air quality impact of a
specific source, or source category. These are called screening
techniques or screening models. The purpose of such techniques is to
eliminate the need of more detailed modeling for those sources that
clearly will not cause or contribute to ambient concentrations in
excess of either the National Ambient Air Quality Standards (NAAQS)
\4\ or the allowable prevention of significant deterioration (PSD)
concentration increments.2 3 If a screening technique
indicates that the concentration contributed by the source exceeds
the PSD increment or
[[Page 68231]]
the increment remaining to just meet the NAAQS, then the second
level of more sophisticated models should be applied.
b. The second level consists of those analytical techniques that
provide more detailed treatment of physical and chemical atmospheric
processes, require more detailed and precise input data, and provide
more specialized concentration estimates. As a result they provide a
more refined and, at least theoretically, a more accurate estimate
of source impact and the effectiveness of control strategies. These
are referred to as refined models.
c. The use of screening techniques followed, as appropriate, by
a more refined analysis is always desirable. However there are
situations where the screening techniques are practically and
technically the only viable option for estimating source impact. In
such cases, an attempt should be made to acquire or improve the
necessary data bases and to develop appropriate analytical
techniques.
2.3 Availability of Models
a. For most of the screening and refined models discussed in the
Guideline, codes, associated documentation and other useful
information are available for download from EPA's Support Center for
Regulatory Air Modeling (SCRAM) Internet Web site at http://www.epa.gov/scram001.
A list of alternate models that can be used
with case-by-case justification (subsection 3.2) and an example air
quality analysis checklist are also posted on this Web site. This is
a site with which modelers should become familiar.
3.0 Recommended Air Quality Models
a. This section recommends the approach to be taken in
determining refined modeling techniques for use in regulatory air
quality programs. The status of models developed by EPA, as well as
those submitted to EPA for review and possible inclusion in this
guidance, is discussed. The section also addresses the selection of
models for individual cases and provides recommendations for
situations where the preferred models are not applicable. Two
additional sources of modeling guidance are the Model Clearinghouse
5 and periodic Regional/State/Local Modelers workshops.
b. In this guidance, when approval is required for a particular
modeling technique or analytical procedure, we often refer to the
``appropriate reviewing authority''. In some EPA regions, authority
for NSR and PSD permitting and related activities has been delegated
to State and even local agencies. In these cases, such agencies are
``representatives'' of the respective regions. Even in these
circumstances, the Regional Office retains the ultimate authority in
decisions and approvals. Therefore, as discussed above and depending
on the circumstances, the appropriate reviewing authority may be the
Regional Office, Federal Land Manager(s), State agency(ies), or
perhaps local agency(ies). In cases where review and approval comes
solely from the Regional Office (sometimes stated as ``Regional
Administrator''), this will be stipulated. If there is any question
as to the appropriate reviewing authority, you should contact the
Regional modeling contact (http://www.epa.gov/scram001/tt28.htm#regionalmodelingcontacts
) in the appropriate EPA Regional
Office, whose jurisdiction generally includes the physical location
of the source in question and its expected impacts.
c. In all regulatory analyses, especially if other-than-
preferred models are selected for use, early discussions among
Regional Office staff, State and local control agencies, industry
representatives, and where appropriate, the Federal Land Manager,
are invaluable and are encouraged. Agreement on the data base(s) to
be used, modeling techniques to be applied and the overall technical
approach, prior to the actual analyses, helps avoid
misunderstandings concerning the final results and may reduce the
later need for additional analyses. The use of an air quality
analysis checklist, such as is posted on EPA's Internet SCRAM Web
site (subsection 2.3), and the preparation of a written protocol
help to keep misunderstandings at a minimum.
d. It should not be construed that the preferred models
identified here are to be permanently used to the exclusion of all
others or that they are the only models available for relating
emissions to air quality. The model that most accurately estimates
concentrations in the area of interest is always sought. However,
designation of specific models is needed to promote consistency in
model selection and application.
e. The 1980 solicitation of new or different models from the
technical community 6 and the program whereby these
models were evaluated, established a means by which new models are
identified, reviewed and made available in the Guideline. There is a
pressing need for the development of models for a wide range of
regulatory applications. Refined models that more realistically
simulate the physical and chemical process in the atmosphere and
that more reliably estimate pollutant concentrations are needed.
3.1 Preferred Modeling Techniques
3.1.1 Discussion
a. EPA has developed models suitable for regulatory application.
Other models have been submitted by private developers for possible
inclusion in the Guideline. Refined models which are preferred and
recommended by EPA have undergone evaluation exercises
7 8 9 10 that include statistical measures of model
performance in comparison with measured air quality data as
suggested by the American Meteorological Society \11\ and, where
possible, peer scientific reviews.12 13 14
b. When a single model is found to perform better than others,
it is recommended for application as a preferred model and listed in
Appendix A. If no one model is found to clearly perform better
through the evaluation exercise, then the preferred model listed in
Appendix A may be selected on the basis of other factors such as
past use, public familiarity, cost or resource requirements, and
availability. Accordingly, dispersion models listed in Appendix A
meet these conditions:
i. The model must be written in a common programming language,
and the executable(s) must run on a common computer platform.
ii. The model must be documented in a user's guide which
identifies the mathematics of the model, data requirements and
program operating characteristics at a level of detail comparable to
that available for other recommended models in Appendix A.
iii. The model must be accompanied by a complete test data set
including input parameters and output results. The test data must be
packaged with the model in computer-readable form.
iv. The model must be useful to typical users, e.g., State air
pollution control agencies, for specific air quality control
problems. Such users should be able to operate the computer
program(s) from available documentation.
v. The model documentation must include a comparison with air
quality data (and/or tracer measurements) or with other well-
established analytical techniques.
vi. The developer must be willing to make the model and source
code available to users at reasonable cost or make them available
for public access through the Internet or National Technical
Information Service: The model and its code cannot be proprietary.
c. The evaluation process includes a determination of technical
merit, in accordance with the above six items including the
practicality of the model for use in ongoing regulatory programs.
Each model will also be subjected to a performance evaluation for an
appropriate data base and to a peer scientific review. Models for
wide use (not just an isolated case) that are found to perform
better will be proposed for inclusion as preferred models in future
Guideline revisions.
d. No further evaluation of a preferred model is required for a
particular application if the EPA recommendations for regulatory use
specified for the model in the Guideline are followed. Alternative
models to those listed in Appendix A should generally be compared
with measured air quality data when they are used for regulatory
applications consistent with recommendations in subsection 3.2.
3.1.2 Recommendations
a. Appendix A identifies refined models that are preferred for
use in regulatory applications. If a model is required for a
particular application, the user should select a model from that
appendix. These models may be used without a formal demonstration of
applicability as long as they are used as indicated in each model
summary of Appendix A. Further recommendations for the application
of these models to specific source problems are found in subsequent
sections of the Guideline.
b. If changes are made to a preferred model without affecting
the concentration estimates, the preferred status of the model is
unchanged. Examples of modifications that do not affect
concentrations are those made to enable use of a different computer
platform or those that affect only the format or averaging time of
the model results. However, when any changes are made, the Regional
Administrator should require a test
[[Page 68232]]
case example to demonstrate that the concentration estimates are not
affected.
c. A preferred model should be operated with the options listed
in Appendix A as ``Recommendations for Regulatory Use.'' If other
options are exercised, the model is no longer ``preferred.'' Any
other modification to a preferred model that would result in a
change in the concentration estimates likewise alters its status as
a preferred model. Use of the model must then be justified on a
case-by-case basis.
3.2 Use of Alternative Models
3.2.1 Discussion
a. Selection of the best techniques for each individual air
quality analysis is always encouraged, but the selection should be
done in a consistent manner. A simple listing of models in this
Guideline cannot alone achieve that consistency nor can it
necessarily provide the best model for all possible situations. An
EPA reference \15\ provides a statistical technique for evaluating
model performance for predicting peak concentration values, as might
be observed at individual monitoring locations. This protocol is
available to assist in developing a consistent approach when
justifying the use of other-than-preferred modeling techniques
recommended in the Guideline. The procedures in this protocol
provide a general framework for objective decision-making on the
acceptability of an alternative model for a given regulatory
application. These objective procedures may be used for conducting
both the technical evaluation of the model and the field test or
performance evaluation. An ASTM reference \16\ provides a general
philosophy for developing and implementing advanced statistical
evaluations of atmospheric dispersion models, and provides an
example statistical technique to illustrate the application of this
philosophy.
b. This section discusses the use of alternate modeling
techniques and defines three situations when alternative models may
be used.
3.2.2 Recommendations
a. Determination of acceptability of a model is a Regional
Office responsibility. Where the Regional Administrator finds that
an alternative model is more appropriate than a preferred model,
that model may be used subject to the recommendations of this
subsection. This finding will normally result from a determination
that (1) a preferred air quality model is not appropriate for the
particular application; or (2) a more appropriate model or
analytical procedure is available and applicable.
b. An alternative model should be evaluated from both a
theoretical and a performance perspective before it is selected for
use. There are three separate conditions under which such a model
may normally be approved for use: (1) If a demonstration can be made
that the model produces concentration estimates equivalent to the
estimates obtained using a preferred model; (2) if a statistical
performance evaluation has been conducted using measured air quality
data and the results of that evaluation indicate the alternative
model performs better for the given application than a comparable
model in Appendix A; or (3) if the preferred model is less
appropriate for the specific application, or there is no preferred
model. Any one of these three separate conditions may make use of an
alternative model acceptable. Some known alternative models that are
applicable for selected situations are listed on EPA's SCRAM
Internet Web site (subsection 2.3). However, inclusion there does
not confer any unique status relative to other alternative models
that are being or will be developed in the future.
c. Equivalency, condition (1) in paragraph (b) of this
subsection, is established by demonstrating that the maximum or
highest, second highest concentrations are within 2 percent of the
estimates obtained from the preferred model. The option to show
equivalency is intended as a simple demonstration of acceptability
for an alternative model that is so nearly identical (or contains
options that can make it identical) to a preferred model that it can
be treated for practical purposes as the preferred model. Two
percent was selected as the basis for equivalency since it is a
rough approximation of the fraction that PSD Class I increments are
of the NAAQS for SO2, i.e., the difference in
concentrations that is judged to be significant. However,
notwithstanding this demonstration, models that are not equivalent
may be used when one of the two other conditions described in
paragraphs (d) and (e) of this subsection are satisfied.
d. For condition (2) in paragraph (b) of this subsection,
established procedures and techniques 15 16 for
determining the acceptability of a model for an individual case
based on superior performance should be followed, as appropriate.
Preparation and implementation of an evaluation protocol which is
acceptable to both control agencies and regulated industry is an
important element in such an evaluation.
e. Finally, for condition (3) in paragraph (b) of this
subsection, an alternative refined model may be used provided that:
i. The model has received a scientific peer review;
ii. The model can be demonstrated to be applicable to the
problem on a theoretical basis;
iii. The data bases which are necessary to perform the analysis
are available and adequate;
iv. Appropriate performance evaluations of the model have shown
that the model is not biased toward underestimates; and
v. A protocol on methods and procedures to be followed has been
established.
3.3 Availability of Supplementary Modeling Guidance
a. The Regional Administrator has the authority to select models
that are appropriate for use in a given situation. However, there is
a need for assistance and guidance in the selection process so that
fairness and consistency in modeling decisions is fostered among the
various Regional Offices and the States. To satisfy that need, EPA
established the Model Clearinghouse 5 and also holds
periodic workshops with headquarters, Regional Office, State, and
local agency modeling representatives.
b. The Regional Office should always be consulted for
information and guidance concerning modeling methods and
interpretations of modeling guidance, and to ensure that the air
quality model user has available the latest most up-to-date policy
and procedures. As appropriate, the Regional Office may request
assistance from the Model Clearinghouse after an initial evaluation
and decision has been reached concerning the application of a model,
analytical technique or data base in a particular regulatory action.
4.0 Traditional Stationary Source Models
4.1 Discussion
a. Guidance in this section applies to modeling analyses for
which the predominant meteorological conditions that control the
design concentration are steady state and for which the transport
distances are nominally 50km or less. The models recommended in this
section are generally used in the air quality impact analysis of
stationary sources for most criteria pollutants. The averaging time
of the concentration estimates produced by these models ranges from
1 hour to an annual average.
b. Simple terrain, as used here, is considered to be an area
where terrain features are all lower in elevation than the top of
the stack of the source(s) in question. Complex terrain is defined
as terrain exceeding the height of the stack being modeled.
c. In the early 1980s, model evaluation exercises were conducted
to determine the ``best, most appropriate point source model'' for
use in simple terrain.\12\ No one model was found to be clearly
superior and, based on past use, public familiarity, and
availability, ISC (predecessor to ISC3 \17\) became the recommended
model for a wide range of regulatory applications. Other refined
models which also employed the same basic Gaussian kernel as in ISC,
i.e., BLP, CALINE3 and OCD, were developed for specialized
applications (Appendix A). Performance evaluations were also made
for these models, which are identified below.
d. Encouraged by the development of pragmatic methods for better
characterization of plume dispersion 18 19 20 21 the AMS/
EPA Regulatory Model Improvement Committee (AERMIC) developed
AERMOD.\22\ AERMOD employs best state-of-practice parameterizations
for characterizing the meteorological influences and dispersion. The
model utilizes a probability density function (pdf) and the
superposition of several Gaussian plumes to characterize the
distinctly non-Gaussian nature of the vertical pollutant
distribution for elevated plumes during convective conditions;
otherwise the distribution is Gaussian. Also, nighttime urban
boundary layers (and plumes within them) have the turbulence
enhanced by AERMOD to simulate the influence of the urban heat
island. AERMOD has been evaluated using a variety of data sets and
has been found to perform better than ISC3 for many applications,
and as well or better than CTDMPLUS for several complex terrain data
[[Page 68233]]
sets (Section A.1; subsection n). The current version of AERMOD has
been modified to include an algorithm for dry and wet deposition for
both gases and particles. Note that when deposition is invoked, mass
in the plume is depleted. Availability of this version is described
in Section A.1, and is subject to applicable guidance published in
the Guideline.
e. A new building downwash algorithm \23\ was developed and
tested within AERMOD. The PRIME algorithm has been evaluated using a
variety of data sets and has been found to perform better than the
downwash algorithm that is in ISC3, and has been shown to perform
acceptably in tests within AERMOD (Section A.1; subsection n).
4.2 Recommendations
4.2.1 Screening Techniques
4.2.1.1 Simple Terrain
a. Where a preliminary or conservative estimate is desired,
point source screening techniques are an acceptable approach to air
quality analyses. EPA has published guidance for screening
procedures.24 25
b. All screening procedures should be adjusted to the site and
problem at hand. Close attention should be paid to whether the area
should be classified urban or rural in accordance with Section
7.2.3. The climatology of the area should be studied to help define
the worst-case meteorological conditions. Agreement should be
reached between the model user and the appropriate reviewing
authority on the choice of the screening model for each analysis,
and on the input data as well as the ultimate use of the results.
4.2.1.2 Complex Terrain
a. CTSCREEN \26\ can be used to obtain conservative, yet
realistic, worst-case estimates for receptors located on terrain
above stack height. CTSCREEN accounts for the three-dimensional
nature of plume and terrain interaction and requires detailed
terrain data representative of the modeling domain. The model
description and user's instructions are contained in the user's
guide.\26\ The terrain data must be digitized in the same manner as
for CTDMPLUS and a terrain processor is available.\27\ A discussion
of the model's performance characteristics is provided in a
technical paper.\28\ CTSCREEN is designed to execute a fixed matrix
of meteorological values for wind speed (u), standard deviation of
horizontal and vertical wind speeds ([sigma]v,
[sigma]w), vertical potential temperature gradient
(d[thetas]/dz), friction velocity (u*), Monin-Obukhov
length (L), mixing height (zi) as a function of terrain
height, and wind directions for both neutral/stable conditions and
unstable convective conditions. Table 4-1 contains the matrix of
meteorological variables that is used for each CTSCREEN analysis.
There are 96 combinations, including exceptions, for each wind
direction for the neutral/stable case, and 108 combinations for the
unstable case. The specification of wind direction, however, is
handled internally, based on the source and terrain geometry.
Although CTSCREEN is designed to address a single source scenario,
there are a number of options that can be selected on a case-by-case
basis to address multi-source situations. However, the appropriate
reviewing authority should be consulted, and concurrence obtained,
on the protocol for modeling multiple sources with CTSCREEN to
ensure that the worst case is identified and assessed. The maximum
concentration output from CTSCREEN represents a worst-case 1-hour
concentration. Time-scaling factors of 0.7 for 3-hour, 0.15 for 24-
hour and 0.03 for annual concentration averages are applied
internally by CTSCREEN to the highest 1-hour concentration
calculated by the model.
b. Placement of receptors requires very careful attention when
modeling in complex terrain. Often the highest concentrations are
predicted to occur under very stable conditions, when the plume is
near, or impinges on, the terrain. The plume under such conditions
may be quite narrow in the vertical, so that even relatively small
changes in a receptor's location may substantially affect the
predicted concentration. Receptors within about a kilometer of the
source may be even more sensitive to location. Thus, a dense array
of receptors may be required in some cases. In order to avoid
excessively large computer runs due to such a large array of
receptors, it is often desirable to model the area twice. The first
model run would use a moderate number of receptors carefully located
over the area of interest. The second model run would use a more
dense array of receptors in areas showing potential for high
concentrations, as indicated by the results of the first model run.
c. As mentioned above, digitized contour data must be
preprocessed \27\ to provide hill shape parameters in suitable input
format. The user then supplies receptors either through an
interactive program that is part of the model or directly, by using
a text editor; using both methods to select receptors will generally
be necessary to assure that the maximum concentrations are estimated
by either model. In cases where a terrain feature may ``appear to
the plume'' as smaller, multiple hills, it may be necessary to model
the terrain both as a single feature and as multiple hills to
determine design concentrations.
d. Other screening techniques 17 25 29 may be
acceptable for complex terrain cases where established procedures
are used. The user is encouraged to confer with the appropriate
reviewing authority if any unresolvable problems are encountered,
e.g., applicability, meteorological data, receptor siting, or
terrain contour processing issues.
4.2.2 Refined Analytical Techniques
a. A brief description of each preferred model for refined
applications is found in Appendix A. Also listed in that appendix
are availability, the model input requirements, the standard options
that should be selected when running the program, and output
options.
b. For a wide range of regulatory applications in all types of
terrain, the recommended model is AERMOD. This recommendation is
based on extensive developmental and performance evaluation (Section
A.1; subsection n). Differentiation of simple versus complex terrain
is unnecessary with AERMOD. In complex terrain, AERMOD employs the
well-known dividing-streamline concept in a simplified simulation of
the effects of plume-terrain interactions.
c. If aerodynamic building downwash is important for the
modeling analysis, e.g., paragraph 6.2.2(b), then the recommended
model is AERMOD. The state-of-the-science for modeling atmospheric
deposition is evolving and the best techniques are currently being
assessed and their results are being compared with observations.
Consequently, while deposition treatment is available in AERMOD, the
approach taken for any purpose should be coordinated with the
appropriate reviewing authority. Line sources can be simulated with
AERMOD if point or volume sources are appropriately combined. If
buoyant plume rise from line sources is important for the modeling
analysis, the recommended model is BLP. For other special modeling
applications, CALINE3 (or CAL3QHCR on a case-by-case basis), OCD,
and EDMS are available as described in Sections 5 and 6.
d. If the modeling application involves a well defined hill or
ridge and a detailed dispersion analysis of the spatial pattern of
plume impacts is of interest, CTDMPLUS, listed in Appendix A, is
available. CDTMPLUS provides greater resolution of concentrations
about the contour of the hill feature than does AERMOD through a
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
[sigma]v (m/s)............................. 0.3 0.75
[sigma]w (m/s)............................. 0.08 0.15 0.30 0.75
[Delta][thetas]/[Delta]z (K/m)............. 0.01 0.02 0.035
WD......................................... (Wind direction is optimized internally for each meteorological
combination.)
----------------------------------------------------------------------------------------------------------------
[[Page 68234]]
Exceptions:
(1) If U <= 2 m/s and [sigma]v <= 0.3 m/s, then include
[sigma]w = 0.04 m/s.
(2) If [sigma]w = 0.75 m/s and U >= 3.0 m/s, then
[Delta][thetas]/[Delta]z is limited to < = 0.01 K/m.
(3) If U >= 4 m/s, then [sigma]w >= 0.15 m/s.
(4) [sigma]w <= [sigma]v
Table 4-1b.--Unstable/Convective Meteorological Matrix for CTSCREEN
--------------------------------------------------------------------------------