[Federal Register Volume 59, Number 227 (Monday, November 28, 1994)]
[Unknown Section]
[Page ]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 94-28456]
[Federal Register: November 28, 1994]
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ENVIRONMENTAL PROTECTION AGENCY
40 CFR Parts 51 and 52
[AH-FRL-5107-1; Docket No. A-92-65]
Requirements for Preparation, Adoption, and Submittal of
Implementation Plans
AGENCY: Environmental Protection Agency (EPA).
ACTION: Notice of proposed rulemaking.
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SUMMARY: EPA is issuing this proposal to augment the final rule that
was published on July 20, 1993. Today's notice proposes to make several
additions and changes as supplement C to the ``Guideline on Air Quality
Models (Revised)''. Supplement C does the following: incorporates
improved algorithms for treatment of area sources and dry deposition in
the Industrial Source Complex (ISC2) model, adopts a solar radiation/
delta-T (SRDT) method for estimating atmospheric stability categories,
adopts a new screening approach for assessing annual NO2 impacts,
and adds SLAB and HGSYSTEM as alternative models. The Guideline sets
forth air quality models and guidance for estimating the air quality
impacts of sources and for specifying emission limits for them. The
purpose of the proposed changes is to enhance the guidance in response
to a substantial number of public comments urging the Agency to do so.
For the purposes of this document, EPA is soliciting public comments
only on the four proposed changes associated with supplement C and will
not respond to any comments that are outside the scope of this
document. This limiting of EPA's responses to comments within the scope
of this document allows the Agency to focus on the issues, data, and
information relevant to this rulemaking.
DATES: The period for comment on these proposed changes closes January
12, 1995.
ADDRESSES: Comments: Written comments should be submitted (in duplicate
if possible) to: Air Docket (6102), Room M-1500, Waterside Mall,
Attention: Docket A-92-65, U.S. Environmental Protection Agency, 401 M
Street, S.W., Washington, D.C. 20460.
Copies of supplement C (draft) to the ``Guideline on Air Quality
Models (Revised)'' may be obtained by writing or calling Joseph A.
Tikvart, Source Receptor Analysis Branch, MD-14, U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711, phone (919) 541-
5561. Supplement C (draft) is also available to registered users of the
Support Center for Regulatory Air Models Bulletin Board System (SCRAM
BBS) by downloading the appropriate file. To register or access this
electronic bulletin board, users with a personal computer should dial
(919) 541-5742.
Docket: Copies of reports referenced herein (unless otherwise
noted) and public comments made on this Notice of Proposed Rulemaking
(NPR) are maintained in Docket A-92-65. The docket is available for
public inspection and copying between 8:00 a.m. and 4:00 p.m., Monday
through Friday, at the address above.
FOR FURTHER INFORMATION CONTACT: Joseph A. Tikvart, Chief, Source
Receptor Analysis Branch, Office of Air Quality Planning and Standards,
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711;
telephone (919) 541-5561 or C. Thomas Coulter, telephone (919) 541-
0832.
SUPPLEMENTARY INFORMATION:
Background\1\
The purpose of the Guideline\2\ is to promote consistency in the
use of modeling within the air management process. The Guideline
provides model users with a common basis for estimating pollution
concentrations, assessing control strategies and specifying emission
limits; these activities are regulated at 40 CFR 51.46, 51.63, 51.112,
51.117, 51.150, 51,160, 51.166, and 51.21. The Guideline was originally
published in April 1978. It was incorporated by reference in the
regulations for the Prevention of Significant Deterioration of Air
Quality in June 1978 (43 FR 26380). The Guideline was subsequently
revised in 1986 (51 FR 32176), and later updated with the addition of
supplement A in 1987 (53 FR 393). The last such revision was supplement
B, issued on July 20, 1993 (58 FR 38816). The revisions in supplement B
included techniques and guidance for situations where specific
procedures had not previously been available, and also improved several
previously adopted techniques.
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\1\In reviewing this preamble, note the distinction between the
terms ``supplement'' and ``appendix''. Supplements A, B and C
contain the replacement pages to effect Guideline revisions;
appendix A to the Guideline is the repository for preferred models,
while appendix B is the repository for alternate models justified
for use on a case-by-case basis.
\2\``Guideline on Air Quality Models (Revised)'' (1986) [EPA-
450/2-78-027R], with supplement A (1987) and supplement B (1993),
hereinafter, the ``Guideline''. The Guideline is published as
appendix W of 40 CFR Part 51. The text of appendix W will be
appropriately modified to effect the revisions proposed for
supplement C.
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During the public comment period for supplement B, EPA received
requests to consider several additional new modeling techniques and
suggestions for enhanced technical guidance.\3\ However, because there
was not sufficient time for the public to review the new techniques and
technical guidance before promulgation of supplement B, the new models
and enhanced technical guidance could not be included in the supplement
B rulemaking. Thus, in this subsequent regulatory proposal, EPA is
proposing to revise the Guideline and is seeking public comment on the
four items described below. Once promulgated, these four items will be
included in supplement C to the Guideline. A copy of supplement C
(draft) is available for public review (Docket Item III-B-1).
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\3\The official public hearing for EPA's proposal to adopt
supplement B was the Fifth Conference on Air Quality Modeling, March
1991 (56 FR 7694). Full transcripts filed in Docket No. A-88-04; IV-
F-1 (see ADDRESSES). See also ``Summary of Public Comments and EPA
Responses on the Fifth Conference on Air Quality Modeling: March
1991'', February 1993. (Docket No. A-88-04; V-C-1)
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Proposed Action
Appendix W of 40 CFR part 51 will be appropriately amended to
effect the following revisions, proposed as supplement C to the
Guideline. EPA solicits comment on each of the following revisions.
1. Enhancements\4\ to the Industrial Source Complex Model (ISC2)
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\4\For clarification, these enhancements are discussed
separately. EPA intends to integrate these enhancements into one
model for actual use.
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A. Area Source Algorithm
Today's action proposes to replace the area source algorithm in the
Industrial Source Complex model (ISC2) with a new one based on a double
integration of the Gaussian plume kernel for area sources.
(1) Short-term algorithm: ISCST2. A previous EPA study\5\ indicated
that the currently implemented ISCST2 area source algorithm, based on a
finite line segment approximation, estimates concentration
distributions with limited accuracy, especially for receptors located
close to the area source. An independent but later evaluation confirmed
these findings.6,7 These studies suggested that the integrated
line source algorithm for modeling impacts from area sources provides a
better treatment of near-source geometry than that currently
recommended in ISCST2, and a reasonable far-field behavior. Based on
these performance evaluations and limited field data, the integrated
line source algorithm is a candidate to substitute for the current
ISCST2 area source algorithm. Responding to public comments received at
the time supplement B was proposed, steps were taken to develop and
test this algorithm. In the new algorithm,\8\ the ground-level
concentration at a receptor downwind of all or a portion of the area
source is given by a double integral in the upwind and crosswind
directions. The integral in the lateral direction is solved
analytically. The integral in the longitudinal direction (i.e., the
summation of the contributions from the line sources in the upwind
direction) is approximated with a Romberg integration technique.\9\ The
new algorithm, essentially equivalent to PAL\10\ and the convergent
mode of the FDM\11\ integrated line source algorithm, has been shown to
perform very well in terms of efficiency and of the reasonableness of
the results.\12\
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\5\Environmental Protection Agency, 1989. Review and Evaluation
of Area Source Dispersion Algorithms for Emission Sources at
Superfund Sites. EPA Publication No. EPA-450/4-89-020. U.S.
Environmental Protection Agency, Research Triangle Park, NC. (NTIS
No. PB 90-142753)
\6\American Petroleum Institute, 1992. Evaluation of Area and
Volume Source Dispersion Models for Petroleum and Chemical Industry
Facilities, Phase I (Final Report). API Publication No. 4539.
(Docket No. A-92-65; II-A-1)
\7\American Petroleum Institute, 1992. Area and Volume Source
Air Quality Model Performance Evaluation, Phase II (Final Report).
API Publication No. 4540. (Docket No. A-92-65; II-A-2)
\8\``User Instructions for a New Area Source Algorithm'' (August
1993), uploaded to the SCRAM BBS. (Docket No. A-92-65; II-A-3)
\9\W.B., B. Flannery, S. Teukolsky, and W. Vetterling, 1986.
Numerical Recipes. Cambridge University Press, New York; 797 pp.
\10\Petersen, W.B., 1978. User's Guide for PAL--A Gaussian-Plume
Algorithm for Point, Area, and Line Sources. EPA Publication No.
EPA-600/4-78-013. U.S. Environmental Protection Agency, Research
Triangle Park, NC. (NTIS No. PB 281306)
\11\Environmental Protection Agency, 1991. User's Guide for the
Fugitive Dust Model (FDM) (Revised). EPA Publication No. EPA-910/9-
88-202R. U.S. Environmental Protection Agency, Region X. (NTIS No.
PB 90-502410)
\12\Environmental Protection Agency, 1992. Comparison of a
Revised Area Source Algorithm for the Industrial Source Complex
Short Term Model and Wind Tunnel Data. EPA Publication No. EPA-454/
R-92-014. U.S. Environmental Protection Agency, Research Triangle
Park, NC. (NTIS No. PB 93-226751)
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Existing field studies of impacts within and nearby area sources
being scarce and limited in scope, EPA compared model predictions to
measured results using a wind tunnel simulation at the Fluid Modeling
Facility, Atmospheric Research and Exposure Assessment Laboratory.\13\
Both qualitative physical and quantitative statistical analyses were
performed. The analysis results\12\ show that the new algorithm
predicts the concentration distribution with relatively good accuracy
(i.e., \10%), especially for the ground-level
receptors located near the downwind edge of the area source, a
situation of concern to regulatory modeling applications. For receptors
near ground level and within or near the area source, the
normalized modeled concentrations generally matched the wind tunnel
measured concentrations to within 20%. EPA considers this
to be an acceptable correspondence.
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\13\Snyder, W.H., 1991. DATA REPORT: Wind Tunnel Simulation of
Dispersion from Superfund Area Sources. Part: Neutral Flow. (Docket
No. A-92-65; II-a-4)
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To examine the sensitivity of the design concentrations across a
range of source characteristics, scenarios considering source size,
elevation, and downwind distance were simulated.\14\ For each scenario,
the high-second high (HSH) 1-hour, 3-hour, 24-hour averages and high
annual averages were determined using a full year of meteorological
data; both rural and urban mode dispersion options were used.
Generally, the concentration ratio\15\ averaged 1.2 (1-
hour) to 1.0 (annual). However, for receptors located
within and nearby the area source, the ratio averaged 2 (1-
hour) to 3 (annual). Thus, for receptors inside the area
source, the ratio is higher than for receptors outside the source,
where the effect is a function of averaging time and proximity to the
source in question.
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\14\Environmental Protection Agency, 1992. Sensitivity Analysis
of a Revised Area Source Algorithm for the Industrial Source Complex
Short Term Model. EPA Publication No. EPA-454/R-92-015. U.S.
Environmental Protection Agency, Research Triangle Park, NC. (NTIS
No. PB 93-226769)
\15\RATIO = XNEW/XOLD
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The proposed algorithm is equivalent to that in PAL and FDM and is
more efficient than either of these algorithms. Based on comparisons
with wind tunnel data, the proposed algorithm provides a more realistic
characterization of the magnitude of impacts at receptors located
within and nearby the area than that currently in ISC2, and gives
comparable results to the FDM convergent algorithm when modeled based
on the same assumptions for release height, mixing height, and
dispersion parameters. Furthermore, these findings confirm that the
currently used area source algorithm in ISC2 is an approximation that
routinely under-estimates (and underrepresents) the actual ambient
impact, especially for receptor locations within and near an area
source.
(2) Long-term algorithm: ISCLT2. The studies previously cited in
footnotes 5, 6, and 7 have also indicated the deficiencies of the
virtual point source algorithm used in ISCLT2. While it is
computationally efficient, the virtual point source algorithm used in
the original ISCLT2 yields estimates of limited accuracy for receptors
located near the edges and corners of the area, a problem also seen
with the original ISCST2. The algorithm cannot predict the area source
impact for receptors located inside the source itself, and does not
adequately handle effects of complex source-receptor geometry.
Thus, a new area source algorithm for the ISCLT2, based on the
numerical integration algorithm described above, was developed and
evaluated.\16\ Detailed performance tests, statistical analyses and
sensitivity analyses were completed to assure the reliability and
reasonableness of the modeling results. Using idealized meteorological
conditions, the new algorithm yields very good comparison results when
compared with the newly developed ISCST2 area source algorithm. For
realistic meteorological data, the differences between ground level
concentration values simulated with the new ISCLT2 algorithm and with
the new ISCST2 counterpart are within about 10% for a typical source.
The differences between the long-term and short-term algorithms using
actual meteorological data are because ISCLT2 uses a meteorological
frequency distribution to represent the meteorological conditions, and
does not contain precise hour-to-hour information on specific
combinations of wind speed, wind direction, stability class and mixing
height that typically control the design values for the short-term
model. Furthermore, sensitivity analyses show that the current ISCLT2
area source algorithm, based on the virtual source approach, routinely
underestimates (and underrepresents) the actual maximum concentration
impacts by a factor of 2 to 4, especially when the receptors are
located inside or near the source.
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\16\Environmental Protection Agency, 1992. Development and
Evaluation of a Revised Area Source Algorithm for the Industrial
Source Complex Long Term Model. EPA Publication No. EPA-454/R-92-
016. U.S. Environmental Protection Agency, Research Triangle Park,
NC. (NTIS No. PB 93-226777)
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B. Dry Deposition Algorithm
Deposition phenomena can be conceptualized in a two by two matrix,
with a wet/dry dichotomy on one side and a particle/gas dichotomy on
the other. Each of the four cells can then be further subdivided into
simple and complex terrain components. Today's action proposes to
replace the plume depletion and dry deposition algorithm\17\ in the
Industrial Source Complex model (ISC2) with a new algorithm that
estimates the amount of material depleted from the plume as a
combination of processes involving atmospheric turbulence and
gravitational settling. This proposal embodies the simple terrain
component of one cell in the conceptual matrix: dry deposition applied
to particles. It is proposed that the new algorithm be implemented to
treat dry deposition in rolling terrain, which is not possible in the
current versions of ISC2. Future efforts may be directed at better
characterizing gaseous and wet deposition in simple and complex.
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\17\``User Instructions for the Draft Deposition Models DEPST
and DEPLT'' (March 1994) have been uploaded to the SCRAM BBS.
(Docket No. A-92-65; II-A-5).
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The dry deposition algorithm currently used in ISC2 is applicable
to large particles (i.e., those with diameters greater than
20m) for which deposition is dominated by
gravitational settling. In 1993, EPA initiated a study to evaluate the
performance of alternative deposition algorithms. A review of the
technical literature identified four core algorithms and six variants
suitable for testing, producing a field of ten algorithm candidates.
Estimates based on these algorithms were compared with observations
from several data bases. Objective statistical procedures\18\ were used
to measure model performance. The main feature of this approach is to
compute normalized statistical measures of the fractional bias between
observed and predicted values.
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\18\Environmental Protection Agency, 1992. Protocol for
Determining the Best Performing Model. EPA Publication No. EPA-454/
R-92-025. U.S. Environmental Protection Agency, Research Triangle
Park, NC. (NTIS No. PB 93-226082)
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Based on the evaluation,\19\ the performance among the three top-
ranked dry deposition algorithms was statistically indistinguishable.
The three top-ranked models were UAM 2, CARB 3 and ADOM 1. The UAM 2
and CARB 3 algorithms represent a hybrid variant of their respective
core algorithms with an added Leaf Area Index (LAI)\20\ adjustment.
ADOM 1, currently employed in the Acid Deposition and Oxidant Model, is
a core algorithm (does not include a LAI adjustment). The results of
the evaluation suggest that the reflection coefficient method used in
ISC2 does not perform well for particle sizes less than 20m in
diameter.
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\19\Environmental Protection Agency, 1994. Development and
Testing of a Dry Deposition Algorithm (Revised). EPA Publication No.
EPA-454/R-94-015. U.S. Environmental Protection Agency, Research
Triangle Park, NC. (NTIS No. PB 94-183100)
Note: This report replaces one previously completed because an
error was discovered after the earlier report was issued. The
following memorandum details the nature of the error and documents
the validity of the newer report.
Memorandum from Jawad S. Touma et al. to Joseph A. Tikvart:
Comments on the report ``Development and Testing of a Dry Deposition
Algorithm (Revised)'', 6 May 1994 (3pp. w/5 attachments) (Dockets
No. A-92-65; II-E-1)
\20\The LAI is a ration of leaf surface area divided by ground
surface area and can be estimated from land use type and season.
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The technical applicability of a LAI adjustment, as implemented for
particle deposition velocity, has not been extensively studied. Thus,
the robustness of using a LAI in routine model applications is
uncertain. Excluding algorithms with LAI adjustments, the ADOM 1 scheme
produces the best composite fractional bias measure (CPM) and was
significantly better than other models tested at the 95% confidence
level. ADOM 1 slightly underestimates observed deposition velocities, a
trait that is shared by all the algorithm candidates. Considering all
of these factors, ADOM 1 is recommended for estimating dry deposition
velocity in the ISC2 model.
The ADOM 1 dry deposition algorithm has been tested within the
framework of the ISC2 model and comparisons of deposition estimates
using the old and new deposition algorithms have been made for a range
of source types and particulate emission scenarios. Similar comparisons
have been made of particulate concentration estimates as affected by
the old and new deposition algorithms. A report\21\ documenting these
analyses and assessing the potential consequences of replacing the
current deposition algorithm in ISC2 with the proposed algorithm has
been prepared.
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\21\Environmental Protection Agency, 1994. Comparison of ISC2
Deposition Estimates Based on Current and Proposed Deposition
Algorithms. EPA Publication No. EPA-454/R-94-018. U.S. Environmental
Protection Agency, Research Triangle Park, NC.
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The results of the comparative analyses of the proposed dry
deposition algorithm vary with release type, particle size, and
averaging period. Consequently, care should be exercised in
interpreting the generalizations that follow regarding deposition and
concentration estimates.
The effects on the actual deposition predicted by ADOM 1 were
examined. For surface releases, the new algorithm gives higher annual
and 24-hour deposition estimates for all particle sizes. For 1-hour and
3-hour estimates for surface releases the results were mixed. For
elevated releases, deposition estimates given by the new algorithm are
higher for 0.1m and 1m particles, lower for 10 and
20m particles, and higher for 80m and 100m
particles. The results for elevated releases of 50m particles
depend on release height.
The effects on ambient concentrations predicted by ISC2 were also
examined. For both surface and elevated releases of small and
intermediate particle sizes (i.e., 0.1, 1.0, 10 and 20m), the
differences in concentration estimates between the old and new
algorithms are less than 10 percent. These differences are considered
insignificant. Results for the large particle sizes (i.e., 50, 80, and
100m) depend on release height. For surface releases, the
concentration estimates using the new algorithm are diminished. For
elevated releases, concentration estimates using the new algorithm are
increased.
EPA is also soliciting public comment on whether it would be
appropriate to require the proposed dry deposition algorithm to be used
for all ISC2 analyses involving particulate matter in any of the
programs for which Guideline usage is required under 40 CFR parts 51
and 52 (see Summary). Heretofore, use of the deposition algorithm has
been optional, depending on the relevance of particle deposition to a
particular application. However, with the more accurate deposition
algorithm proposed herein, its use may result in the systematic
prediction of more accurate ambient concentrations. Therefore, EPA is
soliciting comment on whether it would be appropriate to revise
Guideline section 8.2.7 (Gravitational Settling and Deposition) to
require use of the deposition algorithm, and if so, whether the
implementation guidance provided in the User's Instructions\17\ is
sufficient.
2. Enhancements to On-site Stability Classification
EPA is proposing to revise the on-site stability classification
with the adoption of a new technique, adapted from Bowen et al.\22\ and
herein referred to as the solar radiation/delta-T (SRDT) method. This
method uses total solar radiation during daytime and temperature
difference, delta-T (T), at night and is a replacement for the
one originally proposed (56 FR 5900). As proposed in supplement C, the
hierarchy of stability classification schemes in the Guideline will be
changed to reflect a preference for SRDT-derived stability categories.
Operation of the method is fully described in section 6.4.4.2 of ``On-
Site Meteorological Program Guidance for Regulatory Modeling
Applications'' (EPA-450/4-87-013), hereafter, ``on-site guidance''.
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\22\Bowen, B.M., J.M. Dewart, and A. I. Chen, 1983. Stability
Class Determination: A Comparison for One Site. Proceedings, Sixth
Symposium on Turbulence and Diffusion, American Meteorological
Society, Boston, MA; pp. 211-214. (Docket No. A-92-65; II-A-6)
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The new method has been completely reconfigured in terms of its
classification criteria, in response to the public comments provided at
the Fifth Conference on Air Quality Modeling (March 1991) regarding the
original proposal. The comments (Docket A-88-04, Category IV-D; see
footnote #4) were generally favorable to the concept of a SRDT method
for determining stability category. However, there were some
substantial criticisms of specific SRDT components. Most significant
were comments on:
(1) Accuracy of measurements associated with a 2-10m T;
(2) Limitations on temperature measurements made at 2m;
(3) Use of a 10-60m T in lieu of one measured from 2-10m;
(4) Lack of evaluation data bases;
(5) Use of net radiation measurements in lieu of solar radiation;
and
(6) Merits of measurements for stability determination.
Regarding the use of net radiation, it is not apparent that there
is sufficient experience with routine use of such measurements to
justify requiring their use, whereas there has been extensive
experience with T systems. Regarding the use of
measurements, experience has been that, unless such systems are tuned
for site-specific regimes, the -based methods do not represent
Pasquill-Gifford (P-G) stability classification well. Evaluation
results,\23\ based on on-site measurements from three widely separated
locations, indicate that the SRDT method seems to be less sensitive to
local measurement configurations and is expected to be geographically
robust. Furthermore, the new SRDT method has been configured so that
the system accuracy will not be limiting. Thus, the method will be less
sensitive to random temperature differences. The claim (commenter IV-D-
27 in Docket Item V-C-1; see footnote #3) that accurate measurement of
the 2m temperature may be adversely affected by surface conditions
under the tower has merit in certain circumstances. The new SRDT method
does not mandate that the location of the lower temperature sensor be
at 2m. EPA believes that proper siting of temperature probes in
accordance with Chapter 3 of the on-site guidance, coupled with sound
judgment, should obviate any such problem. Use of a 10-60m T,
an interval specified in the meteorological monitoring protocol used by
the Nuclear Regulatory Commission, is accommodated by the new SRDT
method. Finally, substantial effort was made in acquiring suitable on-
site data bases with which to evaluate the new SRDT method; the new
SRDT method has been more extensively evaluated.
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\23\Environmental Protection Agency, 1993. An Evaluation of a
Solar Radiation/Delta-T (SRDT) Method for Estimating Pasquill-
Gifford (P-G) Stability Categories. EPA Publication No. EPA-454/R-
93-055. U.S. Environmental Protection Agency, Research Triangle
Park, NC. (NTIS No. PB 94-113958)
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To make the stability classification comparisons for the SRDT
evaluation, a surrogate for the preferred Turner classification
scheme\24\ was devised. This surrogate method utilized ``off-site''
National Weather Service (NWS) observations in lieu of those otherwise
made ``on-site''. To ensure the integrity of this surrogate method, it
was necessary that candidate sites be sufficiently near a
representative NWS station from which cloud cover and ceiling height
observations could be obtained. Of ten on-site data bases considered
for supporting the evaluation, three were ultimately selected because
they had the requisite attributes. The data bases thus selected were:
Kincaid, IL (21 weeks in 1980), Longview, WA (CY 1991), and a site near
Bloomington, IN (7/91-7/92). Proximity of these sites to NWS stations
ranged from 17 to 45 miles.
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\24\This method requires on-site measurements of wind speed
coupled with observations of cloud cover and ceiling height. Turner,
D.B., 1964. A Diffusion Model for an Urban Area. Journal of Applied
Meteorology, 3(1): 83-91.
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For theoretical reasons, as well as for consistency with the
approach originally proposed, the SRDT method was initially evaluated
using T data from 2-10m; such data were available for all
three sites. At two of the sites, T data from 10-50m were also
available. These data were of interest in trying to accommodate
T measurements from alternative height intervals.
As substantial site-to-site variability was seen in initial
analyses using the 2-10m T data, it was decided to pool the
data from all three sites and then determine optimum SRDT ``cutpoints''
(i.e., meteorological criteria for discriminating stability category).
Thus, optimum cutpoints were derived in an empirical, iterative fashion
from a data base of 19,540 valid hours. Use of these optimum cutpoints
resulted in a SRDT system that estimated the same P-G stability as the
preferred Turner scheme for 62% of the hours; the categories were
within one class for 89% of the hours. A randomization procedure in
which the composite data were split into two complementary sets was
done to ascertain robustness (insensitivity to random variations in the
data) of the method. The optimum cutpoints from the composite data were
then applied to the three sites individually to document site-specific
residuals.
For the two sites with 10-50m T data, the SRDT system
using the optimum (for pooled data) cutpoints was applied in the same
way as with the 2-10m T data, with reasonably accurate and
consistent results. Stability categories were duplicated by the SRDT
method at least 56% of the hours, and were within one class for about
90% of the hours. Overall, the analyses show that the SRDT system works
adequately for either T interval: the system does not appear
to be unduly sensitive to the actual T height interval. Based
on these analyses, EPA does not feel it should be overly prescriptive
regarding the use of particular T intervals. Rather, in
guidance for implementation of the method, actual placement of
temperature probes is related to fundamental site-specific phenomena,
e.g., surface roughness. While the method was evaluated using only 2-
10m and 10-50m T data, it is considered to be robust enough to
accommodate other T height intervals as well, so long as
section 6.4.4.2 of the on-site guidance cited above is followed.
Finally, consequence analyses were performed using a Gaussian
dispersion model (i.e., ISC2) to document the effect of the SRDT method
on design concentration ratios.\25\ These analyses were performed for
the 2-10m T comparisons at all three sites and for the 10-50m
T comparisons at two sites. For all such analyses, scenarios
included single 35m, 100m and 200m stacks and 180 receptors configured
radially in 5 concentric rings. Averaging times included 1-hour, 3-
hour, 24-hour, and period. Modeled concentrations of interest were the
high, and high 2nd high value. Using stability categories derived from
the 2-10m T data for the three sites, the concentration ratios
averaged 1.06-1.24 across three source types, four averaging times and
two concentration types. Likewise, using those categories derived from
the 10-50m T data, the same concentration ratios also averaged
1.06-1.24.
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\25\RATIO=XSRDT/XTurner
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In the supplement B revisions to the Guideline, EPA referenced
``On-Site Meteorological Program Guidance for Regulatory Modeling
Applications'' in section 9.3.3. This document continues to serve as
the primary source of supplementary technical guidance on the
collection and use of on-site meteorological data. EPA is proposing an
addendum\26\ to accommodate the technical details of the SRDT system.
Once finalized, the hierarchy of stability classification schemes in
that document will also be changed to reflect the preference for those
derived via SRDT. The use of other techniques prior to a year following
promulgation will be exempt from this provision, after which they will
not be considered the primary method for estimating stability. Finally,
the module designed to implement the SRDT system in Version 1.3 of the
Meteorological Processor for Regulatory Models (MPRM), EPA-600/3-88-
043, will be activated and configured with the optimum cutpoints
derived in the evaluation.
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\26\ADDENDUM: On-Site Meteorological Program Guidance for
Regulatory Modeling Applications. Draft for Public Comment
(September 1993). (Docket No. A-92-65; II-A-7)
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3. Screening Approaches for Assessing Annual NO2 Impact
EPA is proposing a revision to simplify the screening approaches
for assessing annual NO2 concentration impact in Guideline section
6.2.3.
These revisions respond to public comments contending that the
initial screening level (which assumed total conversion of NO to
NO2) was overly conservative, and that the ozone limiting approach
described in the second and third screening levels was sometimes
inapplicable or impracticable. Thus, a second level screening approach
that embodies use of an empirically derived NO2/NOX ratio is
proposed. This method replaces the multi-tiered ozone limiting method
now recommended in the Guideline. As described in Chu and Meyer
(1991),\27\ the new approach reflects a review of 10 years of ambient
NO2 and NOX concentration data collected at a variety of
monitoring sites throughout the United States.
---------------------------------------------------------------------------
\27\Chu, S.-H. and E.L. Meyer, 1991. Use of Ambient Ratios to
Estimate Impact of NOX Sources on Annual NO2
Concentrations. Proceedings, 84th Annual Meeting & Exhibition of the
Air & Waste Management Association, Vancouver, B.C.; 16-21 June 1991
(16pp.). (Docket No. A-92-65; II-A-8)
---------------------------------------------------------------------------
The underlying basis for the ambient ratio method (ARM) is that,
for a well mixed plume, the photochemical conversion of NO to NO2
is essentially controlled by the characteristics of the ambient air.
This, in turn, is reflected in the annual NO2/NOX ratio
monitored downwind. Since the photochemistry involved in converting NO
to NO2 is implicitly accounted for by the annual NO2/NOX
ratio monitored downwind, no long-term complex photochemical
calculation is needed. Thus, it makes the modeling exercise much
simpler, yet still provides results consistent with available plume
observational studies.
The method is conservative since, in many cases, maximum estimated
ground level NOX concentration may occur prior to thorough mixing
of the plume. A second, less important, source of conservatism is that
the existing NO2 and NOX data may overestimate the actual
NO2 and NOX concentrations due to interference of PAN and
nitric acid in the measurement. However, since the same amount is added
to both the numerator and denominator of the NO2NOX ratio, it
only makes the conversion ratio slightly more conservative. As shown by
Chu and Meyer (1991), the ARM, while likely to be conservative, is
somewhat less so than existing screening methods (such as the total
conversion and the ozone limiting method) for estimating annual
NO2 concentrations and PSD NO2 increments for NOX
sources. Serving as a second level screening method, ARM has the
quality of simplicity, is easy to apply and is likely to be somewhat
conservative. It relies only on the standard regulatory Gaussian models
and data from nationwide NOX monitoring networks. EPA has
therefore selected this method to propose as a revision to the
Guideline in supplement C.
4. Modeling Techniques for Toxic Air Pollutants
In response to a request made by the American Petroleum Institute
(see footnote 3), two new models for treating toxic air pollutant
releases are being proposed for addition to appendix B of the
Guideline. These models, SLAB and HGSYSTEM, will then accompany
DEGADIS, another appendix B model for treating dense gas releases for
use on a case-by-case basis. (See footnote 2.)
Administrative Requirements
A. Executive Order 12866
Under Executive Order (E.O.) 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 Order.
It has been determined that this rule is not a ``significant
regulatory action'' under the terms of E.O. 12866 and is therefore not
subject to OMB 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
of 1980, 44 U.S.C. 3501 et seq.
C. Regulatory Flexibility Act
The Regulatory Flexibility Act (5 U.S.C. 601 et seq.) requires EPA
to consider potential impacts of regulations on small ``entities''. The
action here proposed is a supplement to the notice of final rulemaking
that was published on July 20, 1993 (58 FR 38816). As described earlier
in this preamble, the revisions here proposed as supplement C to the
Guideline encompass the use of new model algorithms and techniques for
using those models. This rule merely updates existing technical
requirements for air quality modeling analyses mandated by various
Clean Air Act programs (e.g., prevention of significant deterioration,
new source review, SIP revisions) and imposes no new regulatory
burdens. As such, there will be no additional impact on small entities
regarding reporting, recordkeeping, compliance requirements, as stated
in the notice of final rulemaking (op. cit.). Furthermore, this
proposed rule does not duplicate, overlap, or conflict with other
federal rules. Thus, pursuant to the provisions of 5 U.S.C. 605(b), EPA
hereby certifies that the attached proposed rule will not have a
significant impact on a substantial number of such entities.
List of Subjects
40 CFR Part 51
Administrative practice and procedure, Air pollution control,
Intergovernmental relations, Reporting and recordkeeping requirements,
Ozone, Sulfur oxides, Nitrogen dioxide, Lead, Particulate matter,
Hydrocarbons, Carbon monoxide.
40 CFR Part 52
Air pollution control, Ozone, Sulfur oxides, Nitrogen dioxide,
Lead.
Authority: This notice of proposed rulemaking is issued under
the authority granted by sections 110(a)(2), 165(e), 172(a) & (c),
173, 301(a)(1) and 320 of the 1990 Clean Air Act Amendments, 42
U.S.C. 7410(a)(2), 7475(e), 7502(a) & (c), 7503, 7601(a)(1) and
7620, respectively.
Dated: November 7, 1994.
Carol M. Browner,
Administrator.
Parts 51 and 52, Chapter I, Title 40 of the Code of Federal
Regulations are amended as follows:
PART 51--REQUIREMENTS FOR PREPARATION, ADOPTION, AND SUBMITTAL OF
IMPLEMENTATION PLANS
1. The authority citation for part 51 continues to read as follows:
Authority: 42 U.S.C. 7410(a)(2), 7475(e), 7502(a) and (b), 7503,
7601(a)(1) and 7620.
Sec. 51.112 [Amended]
2. In Sec. 51.112, paragraphs (a)(1) and (a)(2) are amended by
revising ``and supplement B (1993)'' to read ``, supplement B (1993)
and supplement C (1994)''.
Sec. 51.160 [Amended]
3. In Sec. 51.160, paragraphs (f)(1) and (f)(2) are amended by
revising ``and supplement B (1993)'' to read ``, supplement B (1993)
and supplement C (1994)''.
Sec. 51.166 [Amended]
4. In Sec. 51.166, paragraph (l)(1) and (l)(2) are amended by
revising ``and supplement B (1993)'' to read ``, supplement B (1993)
and supplement C (1994)''.
5. Appendix W to Part 51, section 4.2.2, is amended by revising
footnote 1 in Table 4-1 to read as follows:
Appendix W to Part 51--Guideline on Air Quality Models (Revised)
* * * * *
4.2.2 * * *
Table 4-1. * * *
------------------------------------------------------------------------
Land
Use Model\1\
------------------------------------------------------------------------
*****
\1\The models as listed in this table reflect the applications for which
they were originally intended. Several of these models have been
adapted to contain options which allow them to be interchanged. For
example, ISCST2 could be substituted for ISCLT2. Similarly, for a
point source application, ISCST2 with urban option can be substituted
for RAM. Where a substitution is convenient to the user and equivalent
estimates are assured, it may be made.
* * * * *
Appendix W [Amended]
6. Appendix W to Part 51, section 6.2.3, is revised to read as
follows:
* * * * *
6.2.3 Models for Nitrogen Dioxide (Annual Average)
a. A tiered screening approach is recommended to obtain annual
average estimates of NO2 from point sources for New Source
Review analysis, including PSD, and for SIP planning purposes. This
multi-tiered approach is conceptually shown in Figure 6-1 below:
Figure 6-1--Multi-tiered Screening Approach for Estimating Annual
NO2 Concentrations From Point Sources
BILLING CODE 6560-50-M
TP28NO94.000
BILLING CODE 6560-50-C
b. For Tier 1 (the initial screen), use an appropriate Gaussian
model from appendix A to estimate the maximum annual average
concentration and assume a total conversion of NO to NO2. If
the concentration exceeds the NAAQS and/or PSD increments for
NO2, proceed to the 2nd level screen.
c. For Tier 2 (2nd level) screening analysis, multiply the Tier
1 estimate(s) by an empirically derived NO2/NOX value of
0.75 (annual national default).\36\ An annual NO2/NOX
ratio differing from 0.75 may be used if it can be shown that such a
ratio is based on data likely to be representative of the
location(s) where maximum annual impact from the individual source
under review occurs. In the case where several sources contribute to
consumption of a PSD increment, a locally derived annual NO2/
NOX ratio should also be shown to be representative of the
location where the maximum collective impact from the new plus
existing sources occurs.
d. In urban areas, a proportional model may be used as a
preliminary assessment to evaluate control strategies to meet the
NAAQS for multiple minor sources, i.e. minor point, area and mobile
sources of NOX; concentrations resulting from major point
sources should be estimated separately as discussed above, then
added to the impact of the minor sources. An acceptable screening
technique for urban complexes is to assume that all NOX is
emitted in the form of NO2 and to use a model from appendix A
for nonreactive pollutants to estimate NO2 concentrations. A
more accurate estimate can be obtained by: (1) calculating the
annual average concentrations of NOX with an urban model, and
(2) converting these estimates to NO2 concentrations using an
empirically derived annual NO2/NOX ratio. A value of 0.75
is recommended for this ratio. However, a spatially averaged annual
NO2/NOX ratio may be determined from an existing air
quality monitoring network and used in lieu of the 0.75 value if it
is determined to be representative of prevailing ratios in the urban
area by the reviewing agency. To ensure use of appropriate locally
derived annual NO2/NOX ratios, monitoring data under
consideration should be limited to those collected at monitors
meeting siting criteria defined in 40 CFR 58, appendix D as
representative of ``neighborhood'', ``urban'', or ``regional''
scales. Furthermore, the highest annual spatially averaged NO2/
NOX ratio from the most recent 3 years of complete data should
be used to foster conservatism in estimated impacts.
e. To demonstrate compliance with NO2 PSD increments in
urban areas, emissions from major and minor sources should be
included in the modeling analysis. Point and area source emissions
should be modeled as discussed above. If mobile source emissions do
not contribute to localized areas of high ambient NO2
concentrations, they should be modeled as area sources. When modeled
as area sources, mobile source emissions should be assumed uniform
over the entire highway link and allocated to each area source grid
square based on the portion of highway link within each grid square.
If localized areas of high concentrations are likely, then mobile
sources should be modeled as line sources with the preferred model
ISCLT2.
f. More refined techniques to handle special circumstances may
be considered on a case-by-case basis and agreement with the
reviewing authority should be obtained. Such techniques should
consider individual quantities of NO and NO2 emissions,
atmospheric transport and dispersion, and atmospheric transformation
of NO to NO2. Where they are available, site-specific data on
the conversion of NO to NO2 may be used. Photochemical
dispersion models, if used for other pollutants in the area, may
also be applied to the NOX problem.
* * * * *
7. Appendix W to Part 51, section 9.3.3.2, is revised to read as
follows:
* * * * *
9.3.3.2 Recommendations--Site-specific Data Collection.
a. The document ``On-Site Meteorological Program Guidance for
Regulatory Modeling Applications''\66\ provides recommendations on
the collection and use of on-site meteorological data.
Recommendations on characteristics, siting, and exposure of
meteorological instruments and on data recording, processing,
completeness requirements, reporting, and archiving are also
included. This publication should be used as a supplement to the
limited guidance on these subjects now found in the ``Ambient
Monitoring Guidelines for Prevention of Significant
Deterioration''.\63\ Detailed information on quality assurance is
provided in the ``Quality Assurance Handbook for Air Pollution
Measurement Systems: Volume IV''.\67\ As a minimum, site-specific
measurements of ambient air temperature, transport wind speed and
direction, and the parameters to determine Pasquill-Gifford (P-G)
stability categories should be available in meteorological data sets
to be used in modeling. Care should be taken to ensure that
meteorological instruments are located to provide representative
characterization of pollutant transport between sources and
receptors of interest. The Regional Office will determine the
appropriateness of the measurement locations.
b. All site-specific data should be reduced to hourly averages.
Table 9-3 lists the wind related parameters and the averaging time
requirements.
c. Solar Radiation Measurements. Total solar radiation should be
measured with a reliable pyranometer, sited and operated in
accordance with established on-site meteorological guidance.\66\
d. Temperature Measurements. Temperature measurements should be
made at standard shelter height (2m) in accordance with established
on-site meteorological guidance.\66\
e. Temperature Difference Measurements. Temperature difference
() measurements for use in estimating P-G
stability categories using the SRDT methodology (see Stability
Categories) should be obtained using two matched thermometers or a
reliable thermocouple system to achieve adequate accuracy.
f. Siting, probe placement, and operation of T systems
should be based on guidance found in Chapter 3 of reference 66, and
such guidance should be followed when obtaining vertical temperature
gradient data for use in plume rise estimates or in determining the
critical dividing streamline height.
g. Wind Measurements. The wind speed for determining plume rise
using the methods of Briggs56,57 should be measured at stack
top. For refined modeling applications in simple terrain situations,
if a source has a stack below 100m, select the stack top height as
the wind measurement height for characterization of plume dilution
and transport. In some cases, collection of stack top wind speed may
be impractical. For sources with stacks extending above 100m, a 100m
tower is suggested unless the stack top is significantly above 100m
(i.e., 200m). In cases with stack tops 200m,
the Regional Office should determine the appropriate measurement
height on a case-by-case basis. Remote sensing may be a feasible
alternative.
h. For refined modeling applications in complex terrain,
multiple level (typically three or more) measurements of wind speed
and direction, temperature and turbulence (wind fluctuation
statistics) are required. Such measurements should be obtained up to
the representative plume height(s) of interest (i.e., the plume
height(s) under those conditions important to the determination of
the design concentration). The representative plume height(s) of
interest should be determined using an appropriate complex terrain
screening procedure (e.g., CTSCREEN) and should be documented in the
monitoring/modeling protocol. The necessary meteorological
measurements should be obtained from an appropriately sited
meteorological tower augmented by SODAR if the representative plume
height(s) of interest exceed 100m. The meteorological tower need not
exceed the lesser of the representative plume height of interest
(the highest plume height if there is more than one plume height of
interest) or 100m.
i. Specifications for wind measuring instruments and systems are
contained in the ``On-Site Meteorological Program Guidance for
Regulatory Modeling Applications''.\66\
j. Stability Categories. The (P-G) stability categories, as
originally defined, couple near-surface measurements of wind speed
with subjectively determined insolation assessments based on hourly
cloud cover and ceiling height observations. The wind speed
measurements are made at or near 10m. The insolation rate is
typically assessed using observations of cloud cover and ceiling
height based on criteria outlined by Turner.\50\ In the absence of
site specific observations of cloud cover and ceiling height, it is
recommended that the P-G stability category be estimated using the
solar radiation/delta-T (SRDT) method described in section 6.4.4.2
of reference 66. This method requires measurements of total solar
radiation during the daytime and temperature difference ()
at night (see Temperature Difference Measurements), coupled with
average wind speed at 10m above ground level. This technique is
modified slightly from that published by Bowen et al. (1983),\136\
has been evaluated with three on-site data bases,\137\ and allows
practical and reasonable implementation of the preferred Turner
method.\55\
k. Two methods of stability classification which use wind
fluctuation statistics, the and
methods, are also described in detail in
reference 66 (note applicable tables in Chapter 6). As a primary
method, these two techniques may only be used for processing data
collected within 1 year following the promulgation date of
Supplement C, and then only when data are unavailable to implement
either the preferred Turner method\55\ or the SRDT method. After
promulgation of Supplement C, these turbulence methods should only
be used to provide back-up stability category estimates for missing
hours in the record according to an established data substitution
protocolg and after valid data retrieval requirements have been
met.
---------------------------------------------------------------------------
\2\Such protocols are usually part of the approved monitoring
program plan. Data substitution guidance is provided in section 5.3
of reference 66.
---------------------------------------------------------------------------
l. In the case of the method it should be
noted that wind meander may occasionally bias the determination of
and thus lead to an erroneous determination of
the P-G stability category. To minimize wind direction meander
contributions, may be determined for each of four
15-minute periods in an hour. However, 360 samples are needed during
each 15-minute period. If the method is being
used for stability determinations in these situations, take the
square root of one-quarter of the sum of the squares of the four 15
minute 's, as illustrated in the footnote to Table
9-3. While this approach is an acceptable alternative for
determining stability, as qualified above, 's
calculated in this manner are not likely to be suitable for input to
models that are designed to accept on-site hourly 's based
on 60-minute periods, e.g., CTDMPLUS. For additional information on
stability classification using wind fluctuation statistics, see
references 68-72.
m. In summary, when on-site data are being used, P-G stability
categories should be determined by (1) Turner's method\55\ using
site specific data which include cloud cover, ceiling height and
surface (10m) wind speeds, or (2) the radiation-based
technique (SRDT) described in reference 66.
n. The following techniques may only be applied to on-site data
bases collected within 1 year following the promulgation date of
Supplement C, and then only when data are unavailable to implement
the preferred Turner\55\ or SRDT method; or to provide back-up
stability category estimates for missing hours in the record
according to an established data substitution protocolg and
after valid data retrieval requirements have been met (choice is
based on data availability and site suitability):
(1) from site-specific measurements in accordance
with guidance;\66\
(2) from site-specific measurements in accordance
with guidance;\66\
(3) Turner's method\55\ using site-specific wind speed with cloud
cover and ceiling height from a nearby NWS site.
o. Meteorological Data Processors. The following meteorological
preprocessors are recommended by EPA: RAMMET, PCRAMMET, STAR,
PCSTAR, MPRM,\135\ and METPRO.\24\ RAMMET is the recommended
meteorological preprocessor for use in applications employing hourly
NWS data. The RAMMET format is the standard data input format used
in sequential Gaussian models recommended by EPA. PCRAMMET\138\ is
the PC equivalent of the mainframe version (RAMMET). STAR is the
recommended preprocessor for use in applications employing joint
frequency distributions (wind direction and wind speed by stability
class) based on NWS data. PCSTAR is the PC equivalent of the
mainframe version (STAR). MPRM is the recommended preprocessor for
use in applications employing on-site meteorological data. The
latest version (MPRM 1.3) has been configured to implement the SRDT
method for estimating P-G stability categories. MPRM is a general
purpose meteorological data preprocessor which supports regulatory
models requiring RAMMET formatted data and STAR formatted data. In
addition to on-site data, MPRM provides equivalent processing of NWS
data. METPRO is the required meteorological data preprocessor for
use with CTDMPLUS. All of the above mentioned data preprocessors are
available for downloading from the SCRAM BBS.\19\
* * * * *
8. Appendix W to Part 51, section 12.0, is amended by:
a. Redesignating footnote g and h as footnotes h and i;
b. Revising references 36 and 90; and
c. Adding references 136 through 138.
The revisions and additions read as follows:
* * * * *
12.0 * * *
* * * * *
36. Chu, S.-H. and E. L.Meyer, 1991. Use of Ambient Ratios to
Estimate Impact of NOx Sources on Annual NO2
Concentrations. Proceedings, 84th Annual Meeting & Exhibition of the
Air & Waste Management Association, Vancouver, B.C.; 16-21 June
1991. (16pp.) (Docket No. A-92-65, II-A-7)
* * * * *
90. Environmental Research and Technology, 1987. User's Guide to the
Rough Terrain Diffusion Model (RTDM), Rev. 3.20. ERT document No.
PD535-585. Environmental Research and Technology, Inc., Concord, MA.
(NTIS No. PB 88-171467)
* * * * *
136. Bowen, B.M., J.M. Dewart and A.I. Chen, 1983. Stability Class
Determination: A Comparison for One Site. Proceedings, Sixth
Symposium on Turbulence and Diffusion. American Meteorological
Society, Boston, MA; pp. 211-214. (Docket No. A-92-65, II-A-5)
137. Environmental Protection Agency, 1993. An Evaluation of a Solar
Radiation/Delta-T (SRDT) Method for Estimating Pasquill-Gifford (P-
G) Stability Categories. EPA Publication No. EPA-454/R-93-055. U.S.
Environmental Protection Agency, Research Triangle Park, NC. (NTIS
No. PB 94-113958)
138. Environmental Protection Agency, 1993. PCRAMMET User's Guide.
EPA Publication No. EPA-454/B-93-009. U.S. Environmental Protection
Agency, Research Triangle Park, NC.
* * * * *
Appendix W [Amended]
9. Appendix W to Part 51, section 13.0, is amended by redesignating
footnote i as footnote j.
Appendix W [Amended]
10. Appendix W to Part 51, Appendix A, is amended by:
a. Revising section A.5.d;
b. Revising section A.5.m;
c. Adding four references in alphabetical order in section A.5.n;
and
d. Adding a reference at the end of section A.REF.
The revisions and additions read as follows:
Appendix A to Appendix W of Part 51--Summaries of Alternative Air
Quality Models
* * * * *
A. 5 * * *
d. Type of Model
ISC2 is a Gaussian plume model. It has been revised to perform a
double integration of the Gaussian plume kernel for area sources.
* * * * *
m. Physical Removal
Dry deposition effects for particles are treated using a
resistance formulation in which the deposition velocity is the sum
of the resistances to pollutant transfer within the surface layer of
the atmosphere, plus a gravitational settling term (EPA, 1994),
based on the modified surface depletion scheme of Horst (1983).
n. Evaluation Studies
* * * * *
Environmental Protection Agency, 1992. Comparison of a Revised
Area Source Algorithm for the Industrial Source Complex Short Term
Model and Wind Tunnel Data. EPA Publication No. EPA-454/R-92-014.
U.S. Environmental Protection Agency, Research Triangle Park, NC.
(NTIS No. PB 93-226751)
Environmental Protection Agency, 1992. Sensitivity Analysis of a
Revised Area Source Algorithm for the Industrial Source Complex
Short Term Model. EPA Publication No. EPA-454/R-92-015. U.S.
Environmental Protection Agency, Research Triangle Park, NC. (NTIS
No. PB 93-226769)
Environmental Protection Agency, 1992. Development and
Evaluation of a Revised Area Source Algorithm for the Industrial
Source Complex Long Term Model. EPA Publication No. EPA-454/R-92-
016. U.S. Environmental Protection Agency, Research Triangle Park,
NC. (NTIS No. PB 93-226777)
Environmental Protection Agency, 1994. Development and Testing
of a Dry Deposition Algorithm (Revised). EPA Publication No. EPA-
454/R-94-015. U.S. Environmental Protection Agency, Research
Triangle Park, NC.
* * * * *
A. Ref Rerences
* * * * *
Horst, T. W., 1983. A Correction to the Gaussian Source-
depletion Model. In Precipitation Scavenging, Dry Deposition and
Resuspension. H. R. Pruppacher, R. G. Semonin, and W. G. N. Slinn,
eds., Elseview, NY.
11. Appendix W to Part 51, Appendix B, is amended by:
a. Adding two entries to the Table of Contents in numerical order;
and
b. Adding sections B.32 and B.33 immediately following section
B.31.
The additions read as follows:
Appendix B to Appendix W of Part 51--Summaries of Alternative Air
Quality Models
Table of Contents
* * * * *
B.32 HGSYSTEM
B.33 SLAB
* * * * *
B.32 HGSYSTEM: Dispersion Models for Ideal Gases and Hydrogen Fluoride
References
Witlox, H.W.M., 1991. HGSYSTEM: dispersion models for ideal
gases and hydrogen fluoride, tutorial and quick-reference guide.
Report TNER.91.007. Thornton Research Centre, Shell Research,
Chester, England. [EGG 1067-1150] (NTIS No. DE 93-000952)
Availability
The PC-DOS version of the HGSYSTEM software (HGSYSTEM: Version
NOV90, Programs for modeling the dispersion of ideal gas and
hydrogen fluoride releases. [EGG 1067-1153]), executable programs
and source code, can be installed from ten 5\1/4\'' diskettes. These
diskettes and all documentation are available as a package from
Energy, Science & Technology Center: (615) 576-1301.
Technical Contacts
Doug N. Blewitt, Amoco Corporation, Environmental Affairs & Safety
Department, Mail Code 4901, 200 East Randolph Drive, Chicago, IL
60601, (312) 856-4099
Howard J. Feldman, American Petroleum Institute, 1220 L Street,
Northwest, Washington, D.C. 20005, (202) 682-8340
Abstract
HGSYSTEM is a software package consisting of mathematical models
for simulating one or more of the consecutive phases between
spillage and far-field dispersion of a non-reactive ideal gas or
hydrogen fluoride (HF). The individual models can be described as
follows: (1) HFSPILL calculates the time-dependent spill rate of HF
liquid or HF vapor from a pressurized vessel; (2) EVAP calculates
the spreading and evaporation of a boiling liquid pool on water or
non-boiling liquid pool on land; (3) HFPLUME calculates the
depressurization to ambient pressure, the jet release and the near-
field dispersion from a pressurized release of HF; (4) PLUME
calculates the depressurization to ambient pressure, the jet release
and the near-field dispersion from a pressurized release of non-
reactive, ideal gases; (5) HEGADAS calculates the steady-state or
time-dependent ground-level heavy-gas dispersion resulting from
either a ground-level pool or a source in a vertical plane; and (6)
PGPLUME simulates passive-gas dispersion downwind of a transition
point based on a simple Pasquill/Gifford similarity model. The
models assume flat, unobstructed terrain. HGSYSTEM can be used to
model steady-state, finite-duration and time-dependent releases. The
models can be run in either the interactive or batch mode.
a. Recommendations for Regulatory Use
HGSYSTEM can be used as a refined model to estimate short-term
ambient concentrations. For toxic chemical releases (non-reactive
chemicals or hydrogen fluoride; 1-hour or less averaging times) the
expected area of exposure to concentrations above specified
threshold values can be determined. For flammable non-reactive gases
it can be used to determine the area in which the cloud may ignite.
b. Input Requirements
1. HFSPILL input data: reservoir data (temperature, pressure,
volume, HF mass, mass-fraction water), pipe-exit diameter and
ambient pressure.
2. EVAP input data: spill rate, liquid properties, and
evaporation rate (boiling pool) or ambient data (non-boiling pool).
3. HFPLUME and PLUME input data: reservoir characteristics,
pollutant parameters, pipe/release data, ambient conditions, surface
roughness and stability class.
4. HEGADAS input data: ambient conditions, pollutant parameters,
pool data or data at transition point, surface roughness, stability
class and averaging time.
5. PGPLUME input data: link data provided by HFPLUME and the
averaging time.
c. Output
1. The HGSYSTEM models contain three post-processor programs
which can be used to extract modeling results for graphical display
by external software packages. GET2COL can be used to extract data
from the model output files. HSPOST can be used to develop
isopleths, extract any 2 parameters for plotting and correct for
finite release duration. HTPOST can be used to produce time history
plots.
2. HFSPILL output data: reservoir mass, spill rate, and other
reservoir variables as a function of time. For HF liquid, HFSPILL
generates link data to HFPLUME for the initial phase of choked
liquid flow (flashing jet), and link data to EVAP for the subsequent
phase of unchoked liquid flow (evaporating liquid pool).
3. EVAP output data: pool dimensions, pool evaporation rate,
pool mass and other pool variables for steady state conditions or as
a function of time. EVAP generates link data to the dispersion model
HEGADAS (pool dimensions and pool evaporation rate).
4. HFPLUME and PLUME output data: plume variables
(concentration, width, centroid height, temperature, velocity, etc.)
as a function of downwind distance.
5. HEGADAS output data: concentration variables and temperature
as a function of downwind distance and (for transient case) time.
6. PGPLUME output data: concentration as a function of downwind
distance, cross-wind distance and height.
d. Type of Model
HGSYSTEM is made up of four types of dispersion models. HFPLUME
and PLUME simulate the near-field dispersion and PGPLUME simulates
the passive-gas dispersion downwind of a transition point. HEGADAS
simulates the ground-level heavy-gas dispersion.
e. Pollutant Types
HGSYSTEM may be used to model non-reactive chemicals or hydrogen
fluoride.
f. Source-Receptor Relationships
HGSYSTEM estimates the expected area of exposure to
concentrations above user-specified threshold values. By imposing
conservation of mass, momentum and energy the concentration,
density, speed and temperature are evaluated as a function of
downwind distance.
g. Plume Behavior
1. HFPLUME and PLUME: (1) are steady-state models assuming a
top-hat profile with cross-section averaged plume variables; and (2)
the momentum equation is taken into account for horizontal ambient
shear, gravity, ground collision, gravity-slumping pressure forces
and ground-surface drag.
2. HEGADAS: assumes the heavy cloud to move with the ambient
wind speed, and adopts a power-law fit of the ambient wind speed for
the velocity profile.
3. PGPLUME: simulates the passive-gas dispersion downwind of a
transition point from HFPLUME or PLUME for steady-state and finite
duration releases.
h. Horizontal Winds
A power law fit of the ambient wind speed is used.
i. Vertical Wind Speed
Not treated.
j. Horizontal Dispersion
1. HFPLUME and PLUME: Plume dilution is caused by air
entrainment resulting from high plume speeds, trailing vortices in
wake of falling plume (before touchdown), ambient turbulence and
density stratification. Plume dispersion is assumed to be steady and
momentum-dominated, and effects of downwind diffusion and wind
meander (averaging time) are not taken into account.
2. HEGADAS: This model adopts a concentration similarity profile
expressed in terms of an unknown center-line ground-level
concentration and unknown vertical/cross-wind dispersion parameters.
These quantities are determined from a number of basic equations
describing gas-mass conservation, air entrainment (empirical law
describing vertical top-entrainment in terms of global Richardson
number), cross-wind gravity spreading (initial gravity spreading
followed by gravity-current collapse) and cross-wind diffusion
(Briggs formula).
3. PGPLUME: It assumes a Gaussian concentration profile in which
the cross-wind and vertical dispersion coefficients are determined
by empirical expressions. All unknown parameters in this profile are
determined by imposing appropriate matching criteria at the
transition point.
k. Vertical Dispersion
See description above.
l. Chemical Transformation
Not treated.
m. Physical Removal
Not treated.
n. Evaluation Studies
1. PLUME has been validated against field data for releases of
liquified propane, and wind tunnel data for buoyant and vertically-
released dense plumes. HFPLUME and PLUME have been validated against
field data for releases of HF (Goldfish experiments) and propane
releases. In addition, the plume rise algorithms have been tested
against Hoot, Meroney, and Peterka, Ooms and Petersen databases.
HEGADAS has been validated against steady and transient releases of
liquid propane and LNG over water (Maplin Sands field data), steady
and finite-duration pressurized releases of HF (Goldfish
experiments; linked with HFPLUME), instantaneous release of Freon
(Thorney Island field data; linked with the box model HEGABOX) and
wind tunnel data for steady, isothermal dispersion.
2. The validation studies are contained in the following
references:
McFarlane, K., Prothero, A., Puttock, J.S., Roberts, P.T. and
Witlox, H.W.M., 1990. Development and validation of atmospheric
dispersion models for ideal gases and hydrogen fluoride, Part I:
Technical Reference Manual. Report TNER.90.015. Thornton Research
Centre, Shell Research, Chester, England. [EGG 1067-1151] (NTIS No.
DE 93-000953)
Witlox, H.W.M., McFarlane, K., Rees, F.J., and Puttock, J.S.,
1990. Development and validation of atmospheric dispersion models
for ideal gases and hydrogen fluoride, Part II: HGSYSTEM Program
User's Manual. Report TNER.90.016. Thornton Research Centre, Shell
Research, Chester, England. [EGG 1067-1152] (NTIS No. DE 93-000954)
B.33 SLAB
Reference
Ermak, D.L., 1990. User's Manual for SLAB: An Atmospheric
Dispersion Model for Denser-than-Air Releases (UCRL-MA-105607),
Lawrence Livermore National Laboratory.
Availability
1. The computer code is available on the Support Center for
Regulatory Air Models Bulletin Board System (Upload/Download Area;
see page B-1), and can also be obtained from:
Energy Science and Technology Center, P.O. Box 1020, Oak Ridge, TN
37830, (615) 576-2606
2. The User's Manual (NTIS No. DE 91-008443) can be obtained
from:
Computer Products, National Technical Information Service, U.S.
Department of Commerce, Springfield, VA 22161, (703) 487-4650
Abstract
The SLAB model is a computer model, PC-based, that simulates the
atmospheric dispersion of denser-than-air releases. The types of
releases treated by the model include a ground-level evaporating
pool, an elevated horizontal jet, a stack or elevated vertical jet
and an instantaneous volume source. All sources except the
evaporating pool may be characterized as aerosols. Only one type of
release can be processed in any individual simulation. Also, the
model simulates only one set of meteorological conditions; therefore
direct application of the model over time periods longer than one or
two hours is not recommended.
a. Recommendations for Use
The SLAB model should be used as a refined model to estimate
spatial and temporal distribution of short-term ambient
concentration (e.g., 1-hour or less averaging times) and the
expected area of exposure to concentrations above specified
threshold values for toxic chemical releases where the release is
suspected to be denser than the ambient air.
b. Input Requirements
1. The SLAB model is executed in the batch mode. Data are input
directly from an external input file. There are 29 input parameters
required to run each simulation. These parameters are divided into 5
categories by the user's guide: source type, source properties,
spill properties, field properties, and meteorological parameters.
The model is not designed to accept real-time meteorological data or
convert units of input values. Chemical property data are not
available within the model and must be input by the user. Some
chemical and physical property data are available in the user's
guide.
2. Source type is chosen as one of the following: evaporating
pool release, horizontal jet release, vertical jet or stack release,
or instantaneous or short duration evaporating pool release.
3. Source property data requirements are physical and chemical
properties (molecular weight, vapor heat capacity at constant
pressure; boiling point; latent heat of vaporization; liquid heat
capacity; liquid density; saturation pressure constants), and
initial liquid mass fraction in the release.
4. Spill properties include: source temperature, emission rate,
source dimensions, instantaneous source mass, release duration, and
elevation above ground level.
5. Required field properties are: desired concentration
averaging time, maximum downwind distance (to stop the calculation),
and four separate heights at which the concentration calculations
are to be made.
6. Meteorological parameter requirements are: ambient
measurement height, ambient wind speed at designated ambient
measurement height, ambient temperature, surface roughness, relative
humidity, atmospheric stability class, and inverse Monin-Obukhov
length (optional, only used as an input parameter when stability
class is unknown).
c. Output
No graphical output is generated by the current version of this
program. The output print file is automatically saved and must be
sent to the appropriate printer by the user after program execution.
Printed output includes in tabular form:
1. Listing of model input data;
2. Instantaneous spatially-averaged cloud parameters--time,
downwind distance, magnitude of peak concentration, cloud dimensions
(including length for puff-type simulations), volume (or mole) and
mass fractions, downwind velocity, vapor mass fraction, density,
temperature, cloud velocity, vapor fraction, water content, gravity
flow velocities, and entrainment velocities;
3. Time-averaged cloud parameters--parameters which may be used
externally to calculate time-averaged concentrations at any location
within the simulation domain (tabulated as functions of downwind
distance);
4. Time-averaged concentration values at plume centerline and at
five off-centerline distances (off-centerline distances are
multiples of the effective cloud half-width, which varies as a
function of downwind distance) at four user-specified heights and at
the height of the plume centerline.
d. Type of Model
As described by Ermak (1989), transport and dispersion are
calculated by solving the conservation equations for mass, species,
energy, and momentum, with the cloud being modeled as either a
steady-state plume, a transient puff, or a combination of both,
depending on the duration of the release. In the steady-state plume
mode, the crosswind-averaged conservation equations are solved and
all variables depend only on the downwind distance. In the transient
puff mode, the volume-averaged conservation equations are solved,
and all variables depend only on the downwind travel time of the
puff center of mass. Time is related to downwind distance by the
height-averaged ambient wind speed. The basic conservation equations
are solved via a numerical integration scheme in space and time.
e. Pollutant Types
Pollutants are assumed to be non-reactive and non-depositing
dense gases or liquid-vapor mixtures (aerosols). Surface heat
transfer and water vapor flux are also included in the model.
f. Source-Receptor Relationships
1. Only one source can be modeled at a time.
2. There is no limitation to the number of receptors; the
downwind receptor distances are internally calculated by the model.
The SLAB calculation is carried out up to the user-specified maximum
downwind distance.
3. The model contains submodels for the source characterization
of evaporating pools, elevated vertical or horizontal jets, and
instantaneous volume sources.
g. Plume Behavior
Plume trajectory and dispersion is based on crosswind-averaged
mass, species, energy, and momentum balance equations. Surrounding
terrain is assumed to be flat and of uniform surface roughness. No
obstacle or building effects are taken into account.
h. Horizontal Winds
A power law approximation of the logarithmic velocity profile
which accounts for stability and surface roughness is used.
i. Vertical Wind Speed
Not treated.
j. Vertical Dispersion
The crosswind dispersion parameters are calculated from formulas
reported by Morgan et al. (1983), which are based on experimental
data from several sources. The formulas account for entrainment due
to atmospheric turbulence, surface friction, thermal convection due
to ground heating, differential motion between the air and the
cloud, and damping due to stable density stratification within the
cloud.
k. Horizontal Dispersion
The horizontal dispersion parameters are calculated from
formulas similar to those described for vertical dispersion, also
from the work of Morgan, et al. (1983).
l. Chemical Transformation
The thermodynamics of the mixing of the dense gas or aerosol
with ambient air (including water vapor) are treated. The
relationship between the vapor and liquid fractions within the cloud
is treated using the local thermodynamic equilibrium approximation.
Reactions of released chemicals with water or ambient air are not
treated.
m. Physical Removal
Not treated.
n. Evaluation Studies
Blewitt, D. N., J. F. Yohn, and D. L. Ermak, 1987. An Evaluation
of SLAB and DEGADIS Heavy Gas Dispersion Models Using the HF Spill
Test Data, Proceedings, AIChE International Conference on Vapor
Cloud Modeling, Boston, MA, November, pp. 56-80.
Ermak, D. L., S.T. Chan, D. L. Morgan, and L. K. Morris, 1982. A
Comparison of Dense Gas Dispersion Model Simulations with Burro
Series LNG Spill Test Results, J. Haz. Matls., 6: 129-160.
Zapert, J. G., R. J. Londergan, and H. Thistle, 1991. Evaluation
of Dense Gas Simulation Models. EPA Publication No. EPA-450/4-90-
018. U.S. Environmental Protection Agency, Research Triangle Park,
NC.
PART 52--APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS
1. The authority citation for Part 52 continues to read as follows:
Authority: 42 U.S.C. 7401-7671q.
Sec. 52.21 [Amended]
2. In Sec. 52.21, paragraphs (l)(1) and (l)(2) are amended by
revising ``and supplement B (1993)'' to read ``, supplement B (1993)
and supplement C (1994)''.
[FR Doc. 94-28456 Filed 11-25-94; 8:45 am]
BILLING CODE 6560-50-P
