TSD-1a

Meteorological Modeling using Penn State/NCAR 5th Generation Mesoscale
Model (MM5)

Bureau of Air Quality Analysis and Research

Division of Air Resources

New York State Department of Environmental Conservation

Albany, NY 12233

March 19, 2006

Meteorological Modeling using Penn State/NCAR 5th Generation Mesoscale
Model (MM5)

Version 3.6 of MM5 was used to generate annual 2002 meteorology for the
OTC modeling work. Prof. Dalin Zhang of the University of Maryland
performed the MM5 simulations in consultation with NYSDEC staff. The
model was applied in Lambert conformal map projection and utilized MPP
Version developed for clusters. The two-way nested domain consisted of
coarse (36km) and fine (12km) mesh corresponding to 149x129 and 175x175
grids, respectively, in this application (see Figure 1).

 corner at (2340km, 1188km). In the vertical direction, the terrain
following σ-coordinate system was used with the pressure at each
σ-level determined from a reference state that is estimated using the
hydrostatic equation from a given sea-level pressure and temperature
with a standard lapse rate. There are 30 unevenly spaced σ levels,
giving 29 vertical layers, with higher resolution within the planetary
boundary layer (PBL).  The σ levels are:

1.0000, 0.9974, 0.9940, 0.8980, 0.9820, 0.9720, 0.9590, 0.9430, 0.9230,
0.8990,

0.8710, 0.8390, 0.8030, 0.7630, 0.7180, 0.6680, 0.6180, 0.5680, 0.5180,
0.4680,

0.3680, 0.3180, 0.2680, 0.2180, 0.1680, 0.1230, 0.0800, 0.0400, 0.0000

The surface layer was set at about 10m, the level at which surface winds
were typically observed, and the model top was set at 50hPa with a
radiative top boundary condition. The time steps for the 36km and 12km
domains were 75 and 25 seconds, respectively.

The important model physics options used for this MM5 simulation
include:

Kain-Fritsch (1993) convective scheme for both 36- and 12-km domains

Explicit moisture scheme (without the mixed phase) containing prognostic
equations for cloud water (ice) and rainwater (snow) (Dudhia 1989; Zhang
1989)

Modified version of the Blackadar planetary boundary layer (PBL) scheme
(Zhang and Anthes 1982; Zhang and Zheng 2004)

Simple radiative cooling scheme (Grell et al. 1994)

Multi-layer soil model to predict land surface temperatures using the
surface energy budget equation (Dudhia 1996)

Note that the Blackadar PBL scheme has been modified in order to correct
the phase shift of surface wind speed and temperature diurnal cycle,
following a study that compared five different PBL schemes: the
Gayno-Seaman TKE scheme (Shafran et al. 2000), Burk-Thompson (1989),
Blackadar (Zhang and Anthes 1982), MRF (Hong and Pan 1996), and
Mellor-Yamada-Jajic (Mellor and Yamada 1974; Jajic 1990, 1994). The
details of the study can be found at Zhang and Zheng (2004).

Nudging Processes

The MM5 provides options for nudging observations for each domain during
the model integration process (Stauffer and Seaman, 1990; Stauffer et
al. 1991). The Eta analyses of   upper-air winds, temperature and
water-vapor mixing ratio as well as their associated surface   fields
were used for nudging every 6 hours, and the Eta surface wind fields
blended with surface wind observations were used to nudge every 3 hours.
 While only the surface winds were nudged, their influences could extend
into the PBL as well (see Stauffer et al. 1991). Based on UMD’s prior
experience in numerical experiments, the following nudging coefficients
have been used:

Upper-air wind fields: 5. 0E-4s-1 for Domain 1 (36km), and 2. 5E-4s-1
for Domain 2 (12km);

Upper-air temperature fields: 1.0E-5s-1   for both Domains;

Surface winds: 5. 0s-1E-4s-1 for Domain 1, and 2.5E-4s-1 for Domain 2;
and

Surface temperature and moisture: not nudged due to instability
consideration.

ASSESSMENT

This assessment covers the period of May through September 2002.

National Weather Service (NWS) and CASTNet data – Surface temperature,
Wind Speed, and Humidity

NWS (TDL) and CASTNet (  HYPERLINK "http://www.epa.gov/castnet/"
www.epa.gov/castnet/ ) surface measurements of temperature, wind speed,
and humidity (note there were no humidity measurements for CASTNet) were
used to compare with the MM5 outputs. The evaluation was performed with
METSTAT program developed by Environ Corporation (  HYPERLINK
"http://www.camx.com/files/metstat.15feb05.tar.gz"
www.camx.com/files/metstat.15feb05.tar.gz )   When comparing to NWS
data, the METSTAT interpolates the first layer MM5 (at 10m height)
temperature and humidity data to a height of 2m, the level that
corresponds to the NWS measurement of these parameters. However, no such
interpolation was made for wind speed and direction. In the case of
CASTNet surface measurements, no such changes were needed as CASTNet
data were reported at a height of 10m. In this analysis, no exclusion
was made for calm conditions. The reported calm winds (zero wind speed
measured) were treated as is in this evaluation effort. The   METSTAT
calculated standard statistical measures – average, bias, error and
index of agreement between the measured and predicted parameters.

 Figure 2 displays the temperature and wind speed comparison of MM5 and
measured data from NWS and CASTNet networks for August 2002. MM5
performance for both in magnitude and diurnal timing, temperature can be
considered to be quite good for both NWS and CASTNet data, while MM5
underpredicted NWS and overpredicted CASTNet daytime wind speed,
respectively. It should be pointed out that there are differences in how
the meteorological information is collected and reported by the two
networks as well as in MM5. The CASTNet measurements are based on hourly
averaged wind speed while NWS reports 2min average at 10min before the
hour, whereas MM5 predictions are reflective of the last time-step of
the hour of computation. Interestingly, MM5 appears to track quite well
the nighttime minimum wind speed for both networks. In the case of
humidity (not shown), MM5 tracks the NWS observed humidity trend well,
but MM5 missed the observed semi-diurnal cycles.  Comparisons for the
five months including bias and root mean square error from both NWS and
CASTNet are available on request from NYSDEC.

The above assessment is based on domain-wide averages to provide an
overall response of the model over the five months. Another way of
assessing the model is to examine the degree of correlation between the
measured and predicted parameters. Figures 3a and 3b displays such a
comparison for wind speed and temperature, respectively, for the NWS
hourly data covering the period of May through September 2002. For the
NWS data, the correlations are in the range from 0.7 to 0.8 for wind
speed, above 0.96 for temperature, and in the range of 0.8 to 0.9 for
humidity. CASTNet data (not shown) also exhibit similar correlation.
These correlations indicate that MM5 simulation has captured both the
diurnal and synoptic scale variations. Detailed plots of this comparison
are available on request from NYSDEC.

Vertical Profiler – Winds

The Wind-Profiler network measurements along the U. S. East Coast
(www.madis-fsl.org/cap) were used to evaluate the vertical profiles from
MM5. There are twelve wind-profiler measurement stations from which data
were available for comparison. For convenience of comparison, the
wind-profiler measurements were interpolated to the MM5 vertical levels.
The approach used was simple interpolation between two adjacent
wind-profiler layers to the MM5 vertical level, and was limited to that
reported by the profiler measurement. The focus of the comparison was to
assess if MM5 was able to capture the measured vertical structure, and
for this we used the observed Low Level Jet (LLJ) as an indicator. The
comparison was performed for June, July and August 2002. In general it
is found that MM5 captures the profiler measured vertical wind field
structure reasonably well.  Figure 4 displays an example of the MM5 and
wind profiler comparison for the August 2002 episode at Richmond, VA and
Concord, NH. MM5 predicted weaker LLJ winds compared to those based on
the wind-profiler measurements. The detailed plots of this comparison
are available on request from NYSDEC.

Cloud Cover – Satellite cloud image

Cloud information derived from satellite image data
(www.atmos.umd.edu/~srb/gcip/webgcip.htm )were used to assess the MM5
prediction of cloud cover. The 0.5o by 0.5o resolution of the satellite
data were interpolated into the 12km MM5 grid for comparison. The MM5
total cloud fraction was estimated by MCIP based on the MM5’s low
cloud, middle cloud and high cloud predictions. In general, MM5 captured
the satellite cloud pattern well but underestimates the satellite cloud
fraction (see Figure 5 as an example). Part of problem may due to the
coarse resolution of the satellite cloud data.

Precipitation comparison

The monthly total observed precipitation data were constructed from
1/8-degree daily precipitation analysis data (  HYPERLINK
"http://data.eol.ucar.edu/codiac/dss/id=21.093"
http://data.eol.ucar.edu/codiac/dss/id=21.093  produced by Climate
Prediction Center, based on 7,000-8,000 hourly/6-hourly gauge reports
and radar). The MM5 monthly total precipitation was estimated from the
MM5 predicted convective and non-convective rainfall and summed up for
each month. In general, MM5 captured the observed spatial patterns in
May and September, but no so well for June, July and August (See Figure
6), perhaps reflective of the summertime convective rain activities not
captured by MM5. Detailed plots of this comparison are available on
request from NYSDEC.

Calm Conditions

Calm conditions are defined as observed wind speed of zero knots and
wind direction as 0o.  It would be useful to assess how MM5 performs
under observed calm conditions, because of potential pollutant buildup
that could occur under such conditions. Table 1 lists the summary of the
percentage of calm condition at each hour for the August 2002 from the
NWS data within the 12km domain. It is apparent from the Table that the
calm conditions occur primarily during the night and early morning
hours, from 23Z (7 p.m. EDT) to 15Z (11 a.m. EDT) with a peak at 10Z (6
a.m. EDT). To assess MM5 performance, the observed and MM5 predicted
wind speeds were divided into calm and non-calm according to observed
wind speed. Figure 7 displays such a comparison of the MM5 predicted
wind speed to the observed wind speed under the calm and non-calm
conditions for the month of August 2002. For the “calm” group, the
average wind speed for MM5 varies from 1 m/s during the night and early
morning hours and over 1.5 m/s during the day.  MM5 is over-predicting
during observed calm wind conditions.  There are local minima every 3
hours, due to the surface observed wind speed nudging in MM5. In
contrast under the non-calm conditions, MM5 underpredicts by about 0.5
m/s for all hours with noticeable local maximum happening at the nudging
hours. The MM5 nudging process would pull predictions toward the
measured data, while the underprediction of MM5 for the non-calm
conditions may due to the adopted PBL scheme in this simulation.

Summary

In this study, we performed an assessment of the MM5 simulation to
real-world data, both at the surface level as well as in the vertical.
While there are no specific recommended procedures identified for this
assessment, similar approaches have been   used elsewhere (Dolwick 2005,
Baker 2004, and Johnson 2004). Traditionally, the NWS surface
measurements are used for such a comparison. Since NWS data had been
used through nudging processes in developing the MM5 simulation, the
comparisons should not be far removed from each other. In this study, we
extended the evaluation by using CASTNet measurements that were not used
in the MM5 simulations. Thus comparison with CASTNet data provides for
an independent assessment and should complement the comparison with NWS
data. We also compared the MM5 results with the wind profiler data and
cloud data derived from satellite images to diagnose if the MM5
simulation is yielding the right type of dynamics in the vertical. The
analyses shows that in general, the performance of the MM5 is reasonable
both at the surface and in the vertical, thereby providing confidence in
the use of these data in the CMAQ simulations.

References

Baker, K. 2004:   HYPERLINK
"http://www.ladco.org/tech/photo/photochemical.html"
www.ladco.org/tech/photo/photochemical.html

Burk, S. D. and W. T. Thompson, 1989:  A vertically nested regional
numerical weather prediction model with second-order closure physics.
Mon. Wea. Rev., 117, 2305–2324.

Dudhia, J., 1989: Numerical study of convection observed during the
winter monsoon experiments using a mesoscale two-dimensional model. J.
Atmos. Sci., 46, 3077–3107.

Dudhia, J., 1996: A multi-layer soil temperature model for MM5.
Preprints, 6th Annual MM5 Users Workshop, Boulder, CO.

Dolwick, P. 2005:   HYPERLINK
"http://cleanairinfo.com/modelingworkshop/presentations/MPE_Dolwick.pdf"
 http://cleanairinfo.com/modelingworkshop/presentations/MPE_Dolwick.pdf

Grell, G. A., J. Dudhia , and D. R. Stauffer 1994:  A description of the
fifth-generation Penn State/NCAR Mesoscale Model (MM5). NCAR Tech.Note
NCAR/TN-398 1 STR, 122 pp.

Hong, S.-H., and H.-L. Pan, 1996: Nonlocal boundary layer vertical
diffusion in a medium-range forecast model. Mon. Wea. Rev., 124,
2322–2339.

Jajic, Z.  I., 1990: The step-mountain coordinate: Physical package.
Mon. Wea. Rev., 118, 1429-1443.

Jajic, Z. I., 1994: The step-mountain Eta coordinate model: Further
development of the convection, viscous sublayer and turbulent closure
schemes. Mon. Wea. Rev., 122, 927-945.

Johnson, M. 2004:   HYPERLINK
"http://www.ladco.org/tech/photo/photochemical.html"
www.ladco.org/tech/photo/photochemical.html

Kain, J.S., and J.M. Fritsch, 1993:  Convective parameterization for
mesoscale models: The Kain-Fritsch scheme. Cumulus Parameterization.
Meteor. Monogr., 46,  Amer.  Meteor. Soc., 165-170.

Mellor, G.  L., and T. Yamada, 1974:  A hierarchy of turbulence closure
models for planetary boundary layers. J. Atmos. Sci., 31, 1791–1806.

Shafran,  P.C.,  N.L.  Seaman, and G. A.  Gayno, 2000: Evaluation of
numerical   predictions of boundary layer structure during the Lake
Michigan ozone study.  J.  Appl.  Meteor.,  39,  412-426.

Stauffer, D. R., N. L. Seaman and F. S. Binkowski 1991:  Use of
four-dimensional data assimilation in a limited-area mesoscale model.
Part II: Effects of data assimilation within the planetary boundary
layer. Mon. Wea. Rev., 119, 734-754.

Stauffer, D.  R. and N. L. Seaman, 1990:  Use of four-dimensional data
assimilation in a limited-area mesoscale model.  Part I:  Experiments
with synoptic-scale data. Mon.  Wea.  Rev.,  118, 1250-1277.

Zhang, D.-L.,  1989:  The  effect  of  parameterized  ice  microphysics
on  the  simulation  of  vortex circulation with a mesoscale hydrostatic
model. Tellus, 41A, 132-147.

Zhang, D.-L,  and  R. A. Anthes,  1982:  A high-resolution  model  of
the  planetary  boundary  layer-sensitivity tests and comparisons with
SESAME-79 data. J. Appl. Meteor., 21, 1594–1609.

Zhang, D.-L, and W.-Z.  Zheng, 2004: Diurnal cycles of surface winds and
temperatures as simulated by five boundary-layer parameterizations. J.
Appl. Meteor., 43, 157-169.

Table 1 	Measured calm and non-calm occurrences over the modeling domain
during August 2002 based on NWS data

Hour	#Non-Calm	#Calm	#Total	% Calm

00Z	18209	3924	22133	17.7

01Z	16531	6026	22557	26.7

02Z	15604	6929	22533	30.8

03Z	14983	7245	22228	32.6

04Z	14309	7540	21849	34.5

05z	14073	7735	21808	35.5

06Z	13934	7949	21883	36.3

07Z	13792	8040	21832	36.8

08Z	13542	8273	21815	37.9

09Z	13542	8385	21927	38.2

10Z	13708	8591	22299	38.5

11Z	14139	8693	22832	38.1

12Z	15297	7690	22987	33.5

13Z	17336	5192	22528	23

14Z	18522	3439	21961	15.7

15Z	18755	2617	21372	12.2

16Z	19169	2015	21184	9.5

17Z	19555	1617	21172	7.6

18Z	19982	1430	21412	6.7

19Z	20149	1389	21538	6.4

20Z	20565	1288	21853	5.9

21Z	20518	1383	21901	6.3

22Z	20672	1556	22228	7

23Z	20231	2292	22523	10.2

Figure 1: OTC MM5 modeling domain with areal extent of 12km and 36km
grids

Figure 2:  Temperature and Wind speed comparisons for August 2002. In
each case the upper panel corresponds to comparison between MM5 and NWS
data and the lower panel between MM5 and CASTNet data.

Figure 3a:	Spatial correlation estimates between MM5 and NWS data for
wind speed

                         from May to September 2002

Figure 3b:  	Spatial distribution of correlation coefficients for
Temperature between                                        MM5 and NWS
data from May to September 2002.

Richmond, VA

Concord, NH

Figure 4: MM5 and Wind profiler comparison for August 6 to 17, 2002 at
Richmond, VA                 and Concord, NH. The upper and lower panes
at each station are for MM5 and profiler, respectively. The abcissa
represents day and the ordinate the height (m).

Figure 5: MM5 and Satellite cloud images for August 14, 2002 at 0700 EST

Figure 6: MM5 predicted and measured precipitation over the domain for
the month of August 2002

Figure 7: Comparison of averaged wind speed between MM5 and observed
under calm (C) and non-calm (NC) conditions.

 PAGE

 PAGE   16


[Federal Register Volume 77, Number 207 (Thursday, October 25, 2012)]
[Notices]
[Pages 65199-65200]
[FR Doc No: 2012-26257]

-----------------------------------------------------------------------

DEPARTMENT OF HEALTH AND HUMAN SERVICES

Food and Drug Administration

[Docket No. FDA-2012-N-0007]

Generic Drug User Fee--Backlog Fee Rate for Fiscal Year 2013

AGENCY: Food and Drug Administration, HHS.

ACTION: Notice.

-----------------------------------------------------------------------

SUMMARY: The Food and Drug Administration (FDA) is announcing the

rate for the backlog fee related to generic drug user fees for fiscal
year (FY) 2013. The Federal Food, Drug, and Cosmetic Act (the FD&C
Act), as amended by the Generic Drug User Fee Amendments of 2012
(GDUFA), authorizes FDA to assess and collect user fees for certain
applications and supplements associated with human generic drug
products, on applications in the backlog as of October 1, 2012, on
finished dosage form (FDF) and active pharmaceutical ingredient (API)
facilities, and on type II API drug master files (DMFs) to be made
available for reference. GDUFA directs FDA to establish each year the
Generic Drug User Fee rates for the upcoming year. In the first year of
GDUFA (FY 2013), some rates will be published in separate Federal
Register notices because of the timing specified in the statute. Each
year thereafter the GDUFA fee rates will be published 60 days before
the start of the FY. This document establishes the FY 2013 rate for the
backlog fee ($17,434). This fee is effective on October 1, 2012.

FOR FURTHER INFORMATION CONTACT: David Miller, Office of Financial
Management (HFA-100), Food and Drug Administration, 1350 Piccard Dr.,
PI50, rm. 210J, Rockville, MD 20850,<PHONE_NUMBER>.

SUPPLEMENTARY INFORMATION:

I. Background

    Sections 744A and744B of the FD&C Act (21 U.S.C. 379j-41 and 379j-
42), as added by GDUFA (Title III of the Food and Drug Administration
Safety and Innovation Act (Public Law 112-144), which was signed by the
President on July 9, 2012), establish user fees associated with human
generic drug products. Fees are assessed on the following: (1)
Applications in the backlog as of October 1, 2012; (2) certain types of
applications and supplements associated with human generic drug
products; (3) certain facilities where APIs and FDFs are produced; (4)
certain type II API DMFs associated with human generic drug products.
This notice focuses solely on the backlog fee.

II. Fee Revenue Amount for FY 2013

    The total fee revenue amount for FY 2013 is $299,000,000, as set in
the statute (section 744B(b)(1)(A) of the FD&C Act). Under that
provision, FDA uses the yearly revenue amount as a starting point to
set the fees. The GDUFA statute states that the backlog fee will make
up $50,000,000 of the total revenue collected for FY 2013 (section
744B(b)(1)(A)(i) of the FD&C Act). For more information about GDUFA,
please refer to the FDA Web site (http://www.fda.gov/gdufa). The
backlog fee calculation for FY 2013 is described in this document.

III. Backlog Fee

    Under GDUFA, each person that owns an abbreviated new drug
application that is pending on October 1, 2012, and that has not
received a tentative approval prior to that date, shall be subject to a
backlog fee for each such application (section 744B(a)(1)(A) of the
FD&C Act). The backlog fee is due no later than 30 days after
publication of this notice (section 744B(a)(1)(D) of the FD&C Act). The
backlog fee is assessed one time only, for FY 2013, and no backlog fee
will be assessed in subsequent years. Once incurred, the backlog fee
obligation can only be discharged by payment in full.
    Under section 744B(a)(1)(B) of the FD&C Act, FDA calculates the
backlog fee by taking the exact number of pending abbreviated new drug
applications in the backlog that have not received tentative approval
as of October 1, 2012, and dividing $50,000,000 by that number. Since
there are 2,868 applicable applications in the backlog, the backlog fee
is calculated to be $17,434 ($50,000,000 divided by 2,868 rounded to
the nearest dollar).

IV. Fee Payment Options and Procedures

    To make a payment of the backlog fee, you must complete a generic
drug user fee cover sheet, available on the FDA Web site (http://www.fda.gov/gdufa) and generate a user fee payment identification (ID)
number. Payment must be made in U.S. currency drawn on a U.S. bank by
electronic check, check, bank draft, U.S. postal money order, or wire
transfer.
    FDA has partnered with the U.S. Department of the Treasury to
utilize Pay.gov, a Web-based payment application, for online electronic
payment. The Pay.gov feature is available on the FDA Web site after
completing the generic drug user fee cover sheet and generating the
user fee payment ID number.
    Please include the user fee payment ID number on your check, bank
draft, or postal money order and make payable to the order of the Food
and Drug Administration. Your payment can be mailed to: Food and Drug
Administration, P.O. Box 979108, St. Louis, MO 63197-9000. If checks
are to be sent by a courier that requests a street address, the courier
can deliver the checks to: U.S. Bank, Attention: Government Lockbox
979108, 1005 Convention Plaza, St. Louis, MO 63101. (Note: This U.S.
Bank address is for courier delivery only.) Please make sure that the
FDA post office box number (P.O. Box 979108) is written on the check,
bank draft, or postal money order.
    If paying by wire transfer, please reference the user fee payment
ID number when completing your transfer. The originating financial
institution may charge a wire transfer fee. Please ask your financial
institution about the wire transfer fee and include it with your
payment to ensure that your backlog fee is fully paid. The account
information is as follows: New York Federal Reserve Bank, U.S.
Department of Treasury, TREAS NYC, 33 Liberty St., New York, NY 10045,
account number: 75060099, routing number: 021030004, SWIFT: FRNYUS33,
Beneficiary: FDA, 1350 Piccard Dr., Rockville, MD, 20850. The tax
identification number of the Food and Drug Administration is 53-
0196965.

    Dated: October 16, 2012.
Leslie Kux,
Assistant Commissioner for Policy.
[FR Doc. 2012-26257 Filed 10-24-12; 8:45 am]
BILLING CODE 4160-01-P


NA
                                                                             NA

NA = Not applicable

                  HOUSEHOLD AND OTHER REFRIGERATED APPLIANCES

                             Type/Site of Release

                          Refrigerators and Freezers
                         Other Refrigerated Appliances
MANUFACTURING RELEASES - FACTORY

   No. of units manufactured per plant per year
 750,000a
 170,000b
   Release per unit manufactured (kg)
                                                                           0.04
                                                                           0.04
ON-SITE RELEASES

   No. of units per site

                                                                              1
                                                                              1
   Release per unit installed (kg)

                                                                              0
                                                                              0
   Release per unit serviced (kg)

     without recycling
                                                                           0.41
                                                                           0.50
     with recycling
                                                                           0.02
                                                                           0.03
     recycling efficiency

                                                                            95%
                                                                            95%
   Release per unit operating (kg/yr)

         0.40c
         0.50[c]
   Release per unit disposed (kg)

     without recycling
                                                                             NA
                                                                           0.50
     with recycling
                                                                             NA
                                                                           0.03
     recycling efficiency
                                                                             NA
                                                                            95%
DISPOSAL RELEASES - RECYCLING/SALVAGING CENTER

   No. of units processed per site per year
   17,000d
                                                                         2,400e
   Release per unit processed (kg)

     without recycling
                                                                           0.40
                                                                           0.41
     with recycling
                                                                           0.02
                                                                           0.02
     recycling efficiency
                                                                            95%
                                                                            95%

NA = Not applicable

                            MOBILE AIR CONDITIONERS

                             Type/Site of Release
                            Mobile Air Conditioners
MANUFACTURING RELEASES - FACTORY

   No. of units manufactured per plant per year
              325,000a
   Release per unit manufactured (kg)
                                                                           0.11
INSTALLATION RELEASES - SERVICE STATION

   No. of units per site
                     63b
   Release per unit installed (kg)
                                                                           0.11
SERVICING RELEASES - SERVICE STATION

   No. of units serviced per site per year
                   165c
   Release per unit serviced (kg)

     without recycling
                                                                            1.2
     with recycling
                                                                           0.06
     recycling efficiency
                                                                            95%
DISPOSAL RELEASES - RECYCLING/SALVAGING CENTER

   No. of units processed per site per year
                 4,250d
   Release per unit processed (kg)

     without recycling
                                                                            1.2
     with recycling
                                                                           0.06
     recycling efficiency
                                                                            95%

                                ATTACHMENT 7-C

METHODOLOGY FOR ESTIMATING GENERAL POPULATION EXPOSURES TO AMBIENT AIR RELEASES OF SUBSTITUTES FOR CLASS I SUBSTANCES
                             FOR SNAP RISK SCREENS

   The approach used to estimate general population exposures to ambient air releases of substitutes for Class I ozone-depleting substances (ODSs) for the SNAP risk screens is patterned after the approach EPA used previously (EPA 1990a) for the interim report on HFCs and HCFCs (EPA 1990b).  The sections below summarize EPA's earlier approach and discuss how it was applied to the SNAP risk screens.

SUMMARY OF EPA'S EARLIER APPROACH FOR ESTIMATING GENERAL POPULATION EXPOSURES

   EPA's approach for estimating general population exposures for the interim report on HFCs and HCFCs is summarized in the two documents referred to above.  EPA used information developed by PEI (EPA 1990c), combined with engineering judgment, to develop estimates of ambient air releases from each of the activities shown in Exhibit 7-C-1.  EPA then used the Industrial Source Complex Long Term (ISCLT) Dispersion Model to estimate ambient air concentrations at an assumed exposure point.

   The ISCLT model is a steady-state Gaussian plume model which can be used to assess pollutant concentrations from a wide variety of sources associated with an industrial source complex.  Additional information on the model can be found in EPA's Industrial Source Complex (ISC) Dispersion Model User's Guide (EPA 1986) and addendum (EPA 1987).  The model has not been through Science Advisory Board or formal external peer review, but it has been reviewed and recommended for general use by EPA's Office of Air Quality Planning and Standards for applications similar to this.

   To run the ISCLT model, it was necessary for EPA to develop inputs for source characteristics and meteorological factors.

   	EPA used engineering judgment to develop assumptions about the characteristics of the facilities (e.g., stack height, surface area) from which the ODSs are released.

   	EPA used meteorological conditions for a "generic" site, which was selected based on an analysis of maximum exposed individual concentrations calculated for an identical release from each of 392 sites across the U.S.  The meteorological conditions at this generic site were known to cause conservative estimates of exposure point concentrations.

EPA then used the ISCLT model outputs to estimate concentrations at the fenceline of the release site.  Distances to the fenceline varied depending on the type of release site, and were based on professional judgment.  EPA points out that for some types of release sites, the model was unable to predict concentrations as close as the assumed fenceline distance.  In these cases, the exposure estimates were based on the highest concentrations predicted by the model.

   EPA documents several areas of uncertainty associated with the release, concentration, and exposure estimates; these are not repeated here.

APPLYING EPA'S EARLIER APPROACH TO THE SNAP RISK SCREENS

   For the SNAP risk screens, general population exposures to ambient air releases of Class I substances were estimated using three basic steps:

   (1)	The first step was to update the ambient air release information presented in the EPA report (EPA 1990c) using more recent data.  Conservative estimates were made of annual ambient air releases of ODS substitutes from different types of facilities (e.g., chemical manufacturing plants, factories that produce equipment containing the substitutes, sites at which the substitutes are used, service stations, centralized recycling or disposal facilities);

   (2)	Each type of release site was "matched up" with one that was modeled earlier by EPA; and

   (3)	The results of the previous ISCLT runs were used to determine the relationship between the release rate and exposure point concentration for each type of release site; that factor was then applied to the revised release estimates to derive a new fenceline concentration.

Steps (1) and (3) were straightforward.  The approach used to calculate releases from different types of facilities (Step 1) is described in the section documenting the general population exposure analysis for each use sector.  To determine the relationship between releases and fenceline concentrations (Step 3), EPA's contractor for the earlier analysis (Versar) provided a table identifying the "normalized maximum concentration at the fenceline, g/m[3]" for each of the runs conducted for the interim report.  These normalized maximum concentrations, shown in Exhibit 7-C-1, are the maximum fenceline concentrations that result from the release of one gram per second (g/sec) of ODS from a source.  Using them is simply a matter of converting estimated annual releases to g/sec and multiplying them by the normalized concentration, yielding maximum fenceline concentrations in g/m[3].

   Some difficulties were encountered in the second step, however, which add to the uncertainties associated with the ambient air modeling.  These difficulties arise from two factors, discussed below.

   	First, it was sometimes difficult to identify the type of facility associated with each normalized concentration listed in Exhibit 7-C-1.  This is because the normalized concentrations are presented by type of activity (e.g., manufacturing, servicing) rather than type of source (e.g., factory, operating site, service station).  To cross-walk the normalized concentrations provided in Exhibit 7-C-1 with different types of release sites for the SNAP risk screens, EPA examined the model input parameters and patterns among the normalized concentrations themselves.  EPA believes that the types of release sites associated with each normalized concentration were identified accurately using this approach.

   	Second, and more importantly, the SNAP risk screens cover certain end uses that were not covered in the general population exposure portion of the interim analysis because the end uses were believed to consume relatively small amounts of ODSs.  Because the SNAP risk screens attempt to cover all end uses, normalized concentrations were needed for source types not previously modeled.  Professional judgment was used to select which normalized concentrations (among those listed in Exhibit 7-C-1) to use for source types that were not modeled earlier.

   Exhibit 7-C-2 lists the normalized concentrations that EPA used for each source type in the SNAP analyses of general population exposure to ambient air releases.

	EXHIBIT 7-C-1
	NORMALIZED FENCELINE CONCENTRATIONS (EPA/VERSAR)
	SECTOR
	ACTIVITY
                                TYPE OF RELEASE
                   NORMALIZED MAX. FENCELINE CONC. (g/m[3])
                            CHEMICAL MANUFACTURING
Manufacture of CFCs
Stack
     8.9

Manufacture of CFCs
Area
    60.4
                                 REFRIGERATION
Retail Food: Manuf./Install.
Volume
   166.3

Retail Food: Servicing
Volume
   864.8

CSW: Manuf./Install.
Volume
   102.5

CSW: Servicing
Volume
   102.5

Chillers: Manuf./Install.
Volume
   166.3

Chillers: Servicing
Volume
    40.7

Ice Makers: Manuf.
Volume
   166.3

Ice Makers: Servicing
Volume
   864.8

Ice Skate Rinks: Manuf.
Volume
   254.8

Ice Skate Rinks: Servicing
Volume
   254.8

MACs: Manuf.
Volume
    58.8

MACs: Servicing
Volume
   864.8

Chem. Proc. & Refineries: Manuf.
Area
    56.7

Chem. Proc. & Refin.: Servicing
Area
    56.7
FOAM BLOWING
Foam Blowing: Rigid & Flexible
Stack
     6.2

Foam Blowing: Rigid & Flexible
Volume
    62.4
SOLVENTS
PC Board Cleaning
Stack
     9.6[a]

PC Board Cleaning
Volume
   166.3

Other Electronics Cleaning
Stack
     9.6[a]

Other Electronics Cleaning
Volume
   472.7

Metal Cleaning
Stack
     9.6[a]

Metal Cleaning
Volume
   166.3
STERILIZATION
Sterilization
Volume
    40.7

[a] Normalized maximum concentrations for stack releases for the solvents sector were not provided by Versar.  These values were back-calculated based on the releases and fenceline concentrations provided in the earlier EPA reports.

                                 EXHIBIT 7-C-2
NORMALIZED MAXIMUM CONCENTRATIONS (g/m[3]) APPLIED TO DIFFERENT TYPES OF RELEASE SITES FOR SNAP RISK SCREENS
	SECTOR
	END USE
                               FACTORY RELEASES
                                OPERATING SITE
                                   RELEASES
                           SERVICE STATION RELEASES
                           DISPOSAL SITE RELEASES[b]
CHEMICAL
MANUFACTURE
Manufacture of CFCs
Stack: 8.9
Area: 60.4
   NA
   NA
   NA
REFRIGERATION
Retail Food
 166.3
 864.8
   NA
   NA

CSW
 166.3
 102.5
   NA
   NA

Chillers
 166.3
  40.7
   NA
   NA

Ice Makers
 166.3
 864.8
   NA
   NA

Ice Rinks
 166.3
 254.8
   NA
   NA

MACs
  58.8
   NA
  864.8
  56.7

ChProc & Ref
 166.3
  56.7
   NA
   NA

Transport Ref
 166.3
 864.8
   NA
   NA

Home
Appliances
 166.3
 864.8
   NA
 254.8

Commercial A/C
 166.3
 254.8
   NA
   NA
FOAM BLOWING
Flexible Foam
   6.2
   NA
   NA
   NA

Other End Uses
  62
   NA
   NA
   NA
SOLVENT
CLEANING
Cleaner
Formulation
Stack: 8.9
Area: 60.4
   NA
   NA
   NA

PC Board Cleaning
  NA
Stack: 9.6
Volume: 166.3
   NA
   NA

Other Electron. Cleaning
  NA
Stack: 9.6
Volume: 472.7
   NA
   NA

Metal
Cleaning
  NA
Stack: 9.6
Volume: 166.3
   NA
   NA
STERILIZATION
Sterilization
  NA
  40.7
   NA
   NA
AEROSOLS
Propellants
 166.3
   NA
   NA
   NA

Solvents
 166.3
  472.7
   NA
   NA
HALONS
Processing and Equipment
 173
   NA
   NA
   NA
ADHESIVES, COATINGS, AND INKS
All End Uses
 166.3
  166.3
   NA
   NA

[a]	Entries in bold were developed for the SNAP risk screens based on a review of EPA and Versar documents; those not in bold were taken directly from Versar (see Exhibit 7-C-1).
[b]	Applies to cases in which equipment is transported to a centralized location (e.g., recycling center or salvaging yard) before the ODS substitute is removed.

	REFERENCES FOR ATTACHMENT 7-C

U.S. EPA.  1990a.  Potential Ambient Inhalation Exposures for Chlorofluorocarbon Substitutes.  Office of Toxic Substances, Exposure Evaluation Division, Exposure Assessment Branch.  November 7, 1990.

U.S. EPA.  1990b.  External Review Draft, Hydrofluorocarbons and Hydrochlorofluorocarbons, Interim Report.  Office of Toxic Substances.  November, 1990.

U.S. EPA.  1990c.  Revised Draft: Occupational Exposure and Environmental Release Data for 	Chlorofluorocarbons (CFCs) and Their Substitutes.  Office of Toxic Substances.

U.S. EPA.  1986.  Industrial Source Complex (ISC) Dispersion Model User's Guide, Second Edition, 	Volumes 1 and 2.  Publication Nos. EPA-450/4-86-005a, and -005b.  U.S. Environmental Protection Agency, Research Triangle Park, NC. (NTIS PB86 234259 and PB86 234267).

U.S. EPA.  1987.  Industrial Source Complex (ISC) Dispersion Model.  Addendum to the User's Guide.  	U.S. Environmental Protection Agency, Research Triangle Park, NC.

	ATTACHMENT 7-D
	NOTE

   The disposal scenario for household and other refrigerated appliances included emissions from the refrigerators and freezers, dehumidifiers (part of the "other refrigerated appliances" category), and window air conditioners sectors.  Since all three kinds of equipment could conceivably be disposed of at the same salvage location, for the purposes of maintaining the conservative nature of this analysis, ratios should be summed for any substitutes that are common across these sectors.  The resulting ratios are:

Substitute		Ratio w/Recycling		Ratio w/o Recycling		Cancer Risk

HCFC-22		    9.7E-05			      N/A			  3.8E-08
HCFC-124		    2.2E-06			      N/A			    N/A
HFC-134a		    4.9E-04			     4.4E-02			    N/A
HFC-152a		    1.2E-04			     1.1E-02			    N/A

None of the resulting summed ratios are high enough to be considered of concern.

	ATTACHMENT 7-E

	Percent of Equipment with Assumed Charge Size

	END USE
	Charge Size
	(Kgs)
	Percent of
	Total in End
	Use Category
	Comments
Retail Food - Parallel
                                      466
                                      100

Retail Food - Stand alone
                                      19
                                      50
other 50% are 10 kg
Cold Storage Warehouses
                                      250
                                      100

Reciprocating Chillers
                                      73
                                      100

Screw Chillers
                                      230
                                      100

Centrifugal Chillers - LP
                                      450
                                      100

Centrifugal Chillers - HP
                                      900
                                      70
25% are 820 kg,
5% are 540 kg
Industrial Process - LP
                                      680
                                      100

Industrial Process
High Pressure Package
                                      180
                                      89
11% are 145 kg
Industrial Process
High Pressure Built Up
                                     9100
                                       7
58% are 4550 kg
6% are 2200 kg
29% are 1800 kg
Ice Skating Rinks
                                     1360
                                      52
48% are approx. 350 kg
Medium Ice Makers
                                      2.3
                                      100

Large Ice Makers
                                     34.1
                                      100

Transport Refrigeration
                                      8.1
                                      100

Window A/C
                                      1.8
                                      100

Central A/C and Heat Pumps
                                      3.8
                                      20
75% are approx. 3 kg
5% are 0.7 kg
Commercial Direct A/C
                                      33
                                      10
90% are 10.2 kg
Refrigerators and Freezers
                                      0.4
                                       8
92% are between 0.19 kg and 0.33 kg
Other Refrigerated Appliances
                                      0.5
                                      10
42% are 0.4 kg
14% are 0.2 kg
34% are 0.1 kg
Mobile Air Conditioners
                                      1.2
                                      40
60% ar 0.88 kg

	8.  VOLATILE ORGANIC COMPOUND ANALYSIS

   This chapter examines volatile organic compound (VOC) emissions from substitutes to Class I ozone-depleting substances (ODSs) that may be used for some end uses within the refrigeration and air conditioning sector. The VOCs of concern for this sector are the hydrocarbons.  VOCs are important to investigate as they can lead to the formation of ground-level ozone and, thus, degradation of ambient air quality and adverse health effects.

   This is a screening-level assessment where overly conservative, worst-case scenarios are presented.  The general approach used in this analysis was to compare total nationwide potential emissions from sources using VOC substitutes in the refrigeration and air conditioning industry with total VOCs from all other sources (e.g., other industries, mobile sources, and biogenic sources).  Next, a hypothetical sample area (the Trane facility in the city of Indianapolis) was chosen to demonstrate a worst-case air emission situation.  The estimated potential emissions from a facility that had switched to VOCs were added to a per-capita emissions amount (to account for releases from refrigeration and air conditioning units already in operation) and compared with the total VOC emissions from all other sources.

   These comparisons give an indication of the potential impact of Class I substitutes in this sector on VOC emissions and the resulting formation of ground-level ozone.

8.1	VOC EMISSIONS FROM SUBSTITUTES TO CLASS I ODSs

   To estimate VOC releases from ODS substitutes in the refrigerant and air conditioning industry, the estimated 1992 nationwide release of ODSs were examined in all refrigerant and air conditioning end uses for which hydrocarbons have been suggested as substitutes.  The year 1992 was chosen based on the assumption that the effects of the CAA phaseout mandate would not begin until after 1991 or 1992.

   The release estimates are from the Vintaging Model.w  For the purposes of this screening-level analysis, it was assumed that hydrocarbons would capture 100 percent of the market share for substitutes to Class I ODSs in 1992, and that the replacement factor for substituting a Class I substance with a VOC alternative is one.  EPA believes that these assumptions grossly overestimate the amount of VOCs that could potentially be released, which is consistent with the objective of conducting a screening-level assessment.

8.2	VOC EMISSIONS FROM ALL SOURCES

   The VOCs from both anthropogenic and biogenic sources are considered for purposes of this analysis as emissions of VOCs from all sources (i.e., background).  Attachment 8-A provides details on the calculation of total (background) VOCs from all sources.  Refer to Attachment 8-A for the breakdown of total emissions for the nation, for each of the six areas as taken from the Urban Airshed Model (UAM), and for a description of the UAM.

8.3	COMPARISON OF VOCS FROM SUBSTITUTES TO VOCS FROM ALL SOURCES

   The comparison between total nationwide VOC emissions from all sources (21,070,000 MT) and VOC emissions from ODS substitutes in the refrigeration and air conditioning industry in 1992 (67,295 MT) results in a national increase in total VOCs of no more than about 0.32 percent.

   EPA does not expect to see any significant difference between the national ratio and the regional ratios, and therefore has not estimated VOC increases in detail for each region in  Attachment 8-A (as was done for several other sectors).  However, releases from refrigerant and air conditioning use in a concentrated area were roughly evaluated by placing several of the "worst" possible hypothetical factories in that area, assessing emissions, adding this to a per-capita emissions amount (to account for releases from units in operation), and comparing the potential VOC emissions to the total VOC emissions from all sources in that area.

   In the sample region, Trane was chosen as the factory with the highest estimated potential air emissions (because of its size).  It was assumed that Trane manufactures all industrial process equipment in one factory.  (Industrial process equipment factories account for some of the highest VOC releases of any equipment-producing factories; see the general population analysis for more details.)  From the analysis on general population risk for the refrigeration and air conditioning sectors, VOC releases from three of these facilities were estimated to be 74 MT/yr.  Next, the per-capita emissions were added in to account for non-factory sources.  To do this, the 67,295 MT/yr emissions estimated from the vintaging model were used and it was assumed that there are 250 million people in the United States.  Indianapolisa has a population of 780,000 people, yielding a total annual release of 210 MT/yr for non-factory sources.  Total VOCs from hydrocarbon substitutes in the refrigerant and air conditioning sector in Indianapolis thus is estimated at 284 MT/yr.  This increase is 0.43 percent of the total VOCs from all sources in Indianapolis (66,640 tons).  Using data from Systems Applications International (SAI),b and the assumption that one month of VOC emissions (23.67 MT) occurs instantaneously and enters a 3,000 foot high column of air over Indianapolis (which has an area of approximately 10[12] m[2]), ozone levels would increase by about 12.8 ppt.  When added to Indianapolis' current ozone level of 0.121 ppm, the increase would be insignificant, especially compared to the amount needed to change Indianapolis' ozone classification to the next worse nonattainment level (i.e., moderate at 0.138 ppm ozone).

8.4	CAVEATS AND LIMITATIONS

   EPA believes that actual VOC increases due to refrigerants will be less than presented here for several reasons, including:

   	VOC emissions controls required by EPA and the states will likely be used (Attachment 8-B describes the expected impact of VOC controls);

   	Improved waste minimization and other housekeeping techniques will likely be used;

   	VOCs will not have 100 percent of the market share.

	CHAPTER 8 REFERENCES

Reid, Steven.  Systems Applications International (SAI).  1990.  May-June.  San Rafael, CA.  Personal communication.

	ATTACHMENT 8-A
	ESTIMATION OF TOTAL VOC EMISSIONS FROM ALL SOURCES IN 1995

   The estimates for total VOC emissions from all sources incorporate both anthropogenic (including mobile sources) and biogenic sources.  For Los Angeles, Philadelphia, Atlanta, and Dallas, estimates of VOC emissions for 1995 were extracted directly from the latest Urban Airshed Modela results (June 1990).  For Indianapolis and Hennepin, VOC emissions estimates for 1995 were not available (nor were estimates for any other marginal nonattainment or attainment area).  Similarly, anthropogenic and biogenic estimates were not readily available for nationwide 1995 VOC emissions.  Therefore, anthropogenic emissions for 1985 were first obtained from the National Acid Precipitation Assessment Program (NAPAP) emissions inventory.  These 1985 figures then were adjusted for 1995 using economic indicator data from the Bureau of Economic Analysis (BEA) Regional Projections Data System (June 1990).  The biogenic emissions were obtained by averaging seasonal biogenic VOC data from the Regional Biogenic Emissions Inventory System (1990)b.  These biogenic emissions were assumed to remain the same for 1995.  The figures obtained from this analysis are presented in Exhibit 8-A-1.

	EXHIBIT 8-A-1
	TOTAL VOC EMISSIONS FROM ALL SOURCES IN 1995 (TONS)

	Area
	Current
	Status
	Anthropogenic
	Emissions
	Biogenic
	Emissions
	Total VOC
	Emissions
Los Angeles, CA
Extreme
Nonattainment
                                    762,485
                                    295,285
                                   1,057,770
Philadelphia, PA
Severe
Nonattainment
                                    760,295
                                    230,315
                                    990,610
Atlanta, GA
Serious
Nonattainment
                                    244,550
                                    466,105
                                    710,655
Dallas, TX
Moderate
Nonattainment
                                    360,620
                                    253,310
                                    613,930
Indianapolis, IN
Marginal
Nonattainment
                                    71,588
                                     1,718
                                    73,306
Hennepin, MN
Attainment
                                    82,022
                                     2,078
                                    84,100
United States
	--
                                      --
                                      --
                                  23,176,700

	ATTACHMENT 8-B
	VOC CONTROLS

   Facilities in ozone nonattainment areas switching from ODSs to VOCs may be required to offset the VOC emissions from their facility so that net VOC emissions decrease within the nonattainment area.  Within nonattainment areas, major sources of emissions are subject to the provisions of the New Source Review (NSR) program.  This program requires affected sources to reduce emissions to the lowest achievable emissions rate (LAER), and to offset new VOC emissions increases with reductions obtained within the facility or at other facilities located within the nonattainment area.

   The NSR program affects "major sources" in nonattainment areas, and the  definition of major source depends primarily upon the potential of the source to emit pollutants (potential emissions).  Potential emissions are the amount of pollutant the source is capable of emitting in the absence of any federally enforceable emission limitation.  These amounts are similar to those estimated for individual facilities in the SNAP analyses.  The potential emissions necessary for a source to be defined as major is a function of the classification of the ozone nonattainment area, with the amount of emissions necessary to be defined as a major source becoming smaller as ozone nonattainment problems of the area become greater (Exhibit 8-B-1).

	EXHIBIT 8-B-1
	MAJOR SOURCE DEFINITION AND OFFSET REQUIREMENTS

                      Nonattainment Area Classification
	Major Source Definition
	(Tons per Year)
	Offset Ratios
	(VOC reduct.:VOC incr.)
	Marginal
	100 TPY
	1.1 : 1
	Moderate
	100 TPY[a]
	1.15 : 1
	Serious
	 50 TPY[a]
	1.2 : 1
	Severe
	 25 TPY[a]
	1.3 : 1
	Extreme
	 10 TPY[a]
	1.5 : 1

[a] States have the option of electing to define major source at 5 tons/yr (and accepting other conditions) as opposed to demonstrating further reasonable progress.  See text.

   It should be noted that some states may elect to opt out of the reasonable further progress (RFP) demonstration required by the CAA, which requires states with some classifications of nonattainment areas to demonstrate a 15 percent reduction in VOC emissions within the first six years of enactment (i.e., by November 1996).  States electing to opt out of the RFP demonstration must define major source at the 5 ton/yr level and accept other conditions.

   The CAA also requires that major sources in nonattainment areas any offset any new VOC emissions with reductions in VOC emissions from within their facility or from other facilities located within the nonattainment area.  This offset requirement results in a net decrease in VOC emissions for sources affected by the NSR program.  As shown in Exhibit 8-B-1, the required offsets are a function of the classification of the nonattainment area and increase with increasing ozone nonattainment status.

   Sources affected by the NSR program are also required to reduce emissions to LAER.  LAER determinations are typically based on the minimum expected performance of air pollution control devices.  The reductions achievable by control devices are well established and as shown in Exhibit 8-B-2 exceed 95 percent.

	EXHIBIT 8-B-2
	EFFECTIVENESS OF COMMON VOC CONTROL DEVICES

	Control Device
	Minimum Expected Reduction
                             Efficiency (Percent)
	Thermal Oxidizer
	98%
	Carbon Absorber
	95%
	Condenser
	95%

   Because facilities switching to VOCs would be required to install LAER, and controls are capable of reducing emissions by 95 percent, EPA would expect the projected increases in VOC from NSR affected facilities to be reduced by at least 95 percent.  These facilities must offset any residual emissions (i.e., the remaining 5 percent) by the amount specified in Exhibit 8-B-2, thus mitigating any impacts from switching from ozone depleting substances to VOCs.