# APPENDIX (

EVIDENCE OF PUBLIC PARTICIPATION; PUBLIC COMMENTS AND NEVADA’S RESPONSES

# (This page left intentionally blank.)NOTICE OF PUBLIC COMMENT PERIOD BEGINNING APRIL 19, 2013 AND A PUBLIC HEARING ON MAY 20, 2013, IF REQUESTED

Conducted by the Nevada Division of Environmental Protection
, Bureau of Air Quality Planning

Pursuant to the public hearing requirements in Title 40 of the Code of Federal Regulations Part 51 section 102, the Nevada Division of Environmental Protection (NDEP) is issuing the following notice to solicit comments on a proposal to certify that the existing Nevada State Implementation Plan (SIP) is adequate for implementation of the 2010 sulfur dioxide (SO 2 ) national ambient air quality standards (NAAQS) in those areas under the NDEP’s jurisdiction

.
On June 22, 2010, the United States Environmental Protection Agency (US EPA) established a new 1- hour SO 2 standard at a level of 75 parts per billion (75 FR 35520 ). Clean Air Act section 110(a)(1) requires each state to submit a plan showing it has the authority and programs needed to implement, maintain, and enforce any new or revised standard, regardless of designation status; section 110(a)(2) lists the elements that must be addressed in the plan. Because many of the section 110(a)(2) elements relate to the general information and authorities that constitute the infrastructure of a s tate’s air quality management program, the 110(a) plans are generally referred to as “infrastructure SIP s .” The NDEP’s portion of Nevada’s 2010 SO 2 NAAQS infrastructure SIP is a compilation of existing authorities and programs to demonstrate that the NDEP has a plan in place to address the 2010 SO 2 NAAQS. Nevada’s SO 2 infrastructure SIP will be submitted to US EPA in May 2013.

The NDEP is responsible for developing and implementing state plans in the 15 rural counties of Nevada. Clark County and Washoe County have their own air quality agencies, which are responsible for their respective counties. The NDEP’s portion of the Nevada SO 2 infrastructure SIP and related materials are available on the NDEP website at http://ndep.nv.gov/admin/public.htm , cl ick on “Air Quality Planning.” Access to the draft documents may also be obtained by contacting Tony Roberts at NDEP, 901 S. Stewart Street, Suite 4001, Carson City, NV 89701; (775) 687-9543; or e-mail to aroberts@ndep.nv.gov

.
Persons wishing to comment on the draft plan or to request a public hearing should submit their written comments or request either in person or by mail or fax to Tony Roberts at the above address or by fax at (775) 687-6396. A request for a hearing must be received by May 13, 2013. Written comments will be received by the NDEP until 5:00 PM PD T, May 20, 2013 and will be retained and considered.

Upon receipt of a valid written request, the NDEP will hold a public hearing in Carson City on:



### May 20, 2013 11:00 a.m. to 1:00 p.m. Great Basin Conference Room, 4 th 

### Floor 901 South Stewart Street Carson City, Nevada

An agenda will be posted on the NDEP web site at least 3 working days before the hearing. Oral comments will be received at the Hearing. If no request for a public hearing is received by May 13
, 2013, the hearing will be cancelled. Persons may check on the status of the hearing on the NDEP web site at http://ndep.nv.gov/admin/public.htm , click on “Air Quality Planning,” or you may call the NDEP Bureau of Air Quality Planning at (775) 687-9349.

This notice has been published in the Las Vegas Review-Journal and the Reno Gazette Journal newspapers. It has been posted at the NDEP offices in Carson City and Las Vegas, at the State Library in Carson City and at County libraries throughout Nevada. Members of the public who are disabled and require special accommodations or assistance at the hearing are requested to notify Tony Roberts or Cathy Douglas (775-687-9349) no later than 3 working days before the hearing. 04/17/2013

### NOTICE OF CANCELLATION OF PUBLIC HEARING ON May 20, 2013

Nevada Division of Environmental Protection Bureau of Air Quality Planning

Pursuant to the public hearing provisions in Title 40 of the Code of Federal Regulations Part 51
section 102, the Nevada Division of Environmental Protection (NDEP) is cancelling the following
public hearing because no request for a hearing was received:

May 20, 2013

11 :00 a.m. to 1:00 p.m.
Great Basin Conference Room, 4 th Floor

901 South Stewart Street
Carson City, Nevada

The NDEP’s draft Sulfur Dioxide Infrastructure State Implementation Plan (SIP) and related

materials are available on the NDEP website at http://ndep.nv.gov/admin/public.htm , click on
“Air Quality Planning.” Persons may also check on the status of Nevada’s Sulfur Dioxide
Infrastructure SIP revision by telephone at (775) 687- 9543

.

# Public Comments and Nevada’s Responses
(Only one comment was received)

## (This page left intentionally blank.)

## North Valmy Generating Station

Valmy, Nevada

Sierra Club Evaluation of Compliance with 1-hour SO 2 

## NAAQS

May 16, 2013

Conducted by:

Steven Klafka, P.E., BCEE

Wingra Engineering, S.C.

Madison, WisconsinSierra Club Evaluation of Compliance with 1-hour SO 2 NAAQS May 16, 2013 Page 2



### 1. Introduction

The Sierra Club prepared an air modeling impact analysis to help USEPA, state and local air agencies identify facilities that are likely causing violations of the 1-hour sulfur dioxide (SO 2 

### ) national ambient air quality standard (NAAQS). This document descri bes the results and procedures for an evaluation conducted for the North Valmy Generating Station loca ted in Valmy, Nevada.

The dispersion modeling analysis predicted ambient air concentrations for comparison with the one
hour SO 2 

### NAAQS. The modeling was performed usi ng the most recent version of AERMOD, AERMET, and AERMINUTE, with data provided to the Sierra Club by regulatory air agencies and through other publicly-available sources as document ed below. The analysis was conducted in adherence to all available USEPA guidance for ev aluating source impacts on attainment of the 1-
hour SO 2 

### NAAQS via aerial dispersion modeling, includ ing the AERMOD Implementation Guide; USEPA's Applicability of Appendix W Modeling Guidance for the 1-hour SO 2 

### National Ambient Air Quality Standard, August 23, 2010; modeling guidance promulgated by USEPA in Appendix W to 40 CFR Part 51; and, USEPA’s March 2011 Modeling Guidance for SO 2 

### NAAQS Designations, available at http://www.epa.gov/ttn/scram/ SO2%20Designations%20Guidance%202011.pdf.

2. Compliance with the 1-hour SO 2 

### NAAQS

2.1 1-hour SO 2 

### NAAQS

The 1-hour SO 2 

### NAAQS takes the form of a three-year average of the 99 th 

### -percentile of the annual distribution of daily maximum 1-hour c oncentrations, which cannot exceed 75 ppb. 1 

### Compliance with this standard was verified using USEPA’s AERMOD air dispersion model, which produces air concentrations in units of μg/m 3 

### . The 1-hour SO 2 

### NAAQS of 75 ppb equals 196.2 μg/m 3 

### , and this is the value used for determining whether modeled impacts exceed the NAAQS. 2 

### The 99 th 

### -percentile of the annual distribution of daily maximum 1-hour concentra tions corresponds to the fourth-highest value at each receptor for a given year.

2.2 Modeling Results

Modeling results for North Valmy Generating Stati on are summarized in Table 1. It was determined that based on either currently permitted emissions or measured actual emissions, the North Valmy Generating Station is esti mated to create downwind SO 2 

### concentrations which exceed the 1-hour NAAQS.

1 USEPA, Applicability of Appendix W Modeling Guidance for the 1-hour SO 2 National Ambient Air Quality Standard, August 23, 2010.

2 The ppb to μg/m 3 conversion is found in the source code to AERMOD v. 12325, subroutine Modules. The conversion calculation is 75/0.3823 = 196.2 μg/m 3

.Sierra Club Evaluation of Compliance with 1-hour SO 2 NAAQS May 16, 2013 Page 3



### The currently permitted emissions and measured actua l emissions used for the modeling analysis are summarized in Table 2. Based on the modeling re sults, emission reductions from current rates considered necessary to achieve compliance with the 1-hour NAAQ S were calculated and presented
in Table 3.

Predicted exceedences of the 1-hour NAAQS for SO 2 

### extend throughout the region to a maximum distance of 40 kilometers.

Figure 1 shows the extent of NAAQS violati ons throughout the entire 50 kilometer modeling
domain.

Figure 2 provides a close-up loca l view of NAAQS violations.

Air quality impacts in Nevada are base d on a background concentration of 14.4 μg/m 3 

### . This is the 2008-10 design value for Washoe Co unty, Nevada - the lowest measured background concentration
in the state. This is the most recently available design value.

2.3 Conservative Modeling Assumptions

A dispersion modeling analysis re quires the selection of numerous parameters which affect the predicted concentrations. For the enclosed analys is, several parameters were selected which underpredict facility impacts.

Assumptions used in this modeling analysis whic h likely under-estimate con centrations include the following:

 Allowable emissions are based on a limitation with an averaging period which is greater than the 1-hour average used for the SO 2 

### air quality standard. Emissions and impacts during any 1-hour period may be higher than assumed for the modeling analysis.

 No consideration of facility operation at less than 100% load. Stack parameters such as exit flow rate and temperature are typically lower at less than full load, reducing pollutant dispersion and increasing pr edicted air quality impacts.

 No consideration of building or structure downwash. These downwash effects typically increase predicted concentr ations near the facility.

 No consideration of off-site sources. These other sources of SO 2 

### will increase the predicted impacts.Sierra Club Evaluation of Compliance with 1-hour SO 2 NAAQS May 16, 2013 Page 4



### Table 1 - SO 2 

### Modeling Results for North Valmy Generating Station Modeling Analysis

Emission Rates Averaging Period 99 th Percentile 1-hour Daily Maximum (μg/m 3 ) Complies with NAAQS? Impact Background Total NAAQS

Allowable 1-hour 480.6 14.4 495.0 196.2 No

Maximum 1-hour 303.9 14.4 318.3 196.2 No



### Table 2 - Modeled SO 2 

### Emissions from North Valmy Generating Station 3
, 4



### Stack

ID Unit
ID Allowable Emissions 3-hour Average (lbs/hr) Maximum Emissions 1-hour Average (lbs/hr)

S01 Unit 1 3,072.0 1,083
S02 Unit 2 1,728.6 1,672
Stack Total All Units 4,800.6 2,755

Table 3 - Required Emission Reduct ions for Compliance with 1-hour SO 2 

### NAAQS

Acceptable Impact (NAAQS - Background) 99th Percentile 1-hour Daily Max (μg/m 3 

### ) Required Total Facility Reduction Based on Allowable Emissions (%) Required Total Facility Emission Rate (lbs/hr) Required Total Facility Emission Rate

(lbs/mmbtu)

181.8 62.2% 1,814.6 0.33

3 Nevada Department of Conservation and Natural Resources, Bureau of Air Pollution Control, Class I Air Quality Operating Permit No. AP4911-0457.01, June 23, 2009.

4 Maximum emissions are measured hourly rates reported for 2011 in USEPA, Clean Air Markets - Data and Maps.Sierra Club Evaluation of Compliance with 1-hour SO 2 NAAQS May 16, 2013 Page 5



### Figure 1 - Regional View - North Valmy Gene rating Station - Based on Allowable EmissionsSierra Club Evaluation of Compliance with 1-hour SO 2 NAAQS May 16, 2013 Page 6



### Figure 2 – Local View - North Valmy Genera ting Station - Based on Allowable EmissionsSierra Club Evaluation of Compliance with 1-hour SO 2 NAAQS May 16, 2013 Page 7



### 3. Modeling Methodology

3.1 Air Dispersion Model

The modeling analysis used USEPA’s AERMOD program, version 12345. AERMOD, as available from the Support Center for Regulatory Atmosphe ric Modeling (SCRAM) website, was used in conjunction with a third-part y modeling software program, AERMOD View , sold by Lakes
Environmental Software.

3.2 Control Options

The AERMOD model was run with the following control options:

 1-hour average air concentrations

 Regulatory defaults

 Flagpole receptors

To reflect a representative inhala tion level, a flagpole height of 1.5 meters was used for all modeled receptors. This parameter was added to the recep tor file when running AERMAP, as described in
Section 4.4.

An evaluation was conducted to determine if the m odeled facility was located in a rural or urban setting using USEPA’s methodology outlined in S ection 7.2.3 of the Guideline on Air Quality
Models. 5 

### For urban sources, the URBANOPT option is used in conjunction with the urban population from an appropriate nearby city and a default surface roughness of 1.0 meter. Methods
described in Section 4.1 to determine whether rura l or urban dispersion co efficients were used.

3.3 Output Options

The AERMOD analysis was based on five years of recent meteorological data. The modeling analyses used one run with five years of seque ntial meteorological data from 2007-2011. Consistent with USEPA’s Modeling Guidance for SO 2 

### NAAQS Designations, AERM OD provided a table of fourth-high 1-hour SO 2 

### impacts concentrations consistent with the form of the 1-hour SO 2 

### NAAQS. 6



### Please refer to Table 1 for the modeling results.

5 USEPA, Revision to the Guideline on Air Quality Models : Adoption of a Preferred General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions, Appendix W to 40 CFR Part 51, November 9, 2005.

6 USEPA, Area Designations for the 2010 Revised Primary Sulfur Dioxide National Ambient Air Quality Standards, Attachment 3, March 24, 2011, pp. 24-26.Sierra Club Evaluation of Compliance with 1-hour SO 2 NAAQS May 16, 2013 Page 8



### 4. Model Inputs

4.1 Geographical Inputs

The “ground floor” of all air disp ersion modeling analyses is estab lishing a coordinate system for identifying the geographical location of emissi on sources and receptors. These geographical
locations are used to determine lo cal characteristics (such as land use and elevation), and also to ascertain source to receptor distances and relationships.

The Universal Transverse Mercator (UTM) NAD83 c oordinate system was used for identifying the easting (x) and northing (y) coordina tes of the modeled sources and receptors. Stack locations were obtained from facility permits and prior modeling f iles provided by the state regulatory agency. The
stack locations were then veri fied using aerial photographs.

The facility was evaluated to determine if it shou ld be modeled using the rural or urban dispersion coefficient option in AERMOD. A GIS was used to determine whether rural or urban dispersion coefficients apply to a site. La nd use within a three-kilometer radi us circle surrounding the facility was considered. USEPA guidance states that urban dispersion coefficients are used if more than 50%
of the area within 3 kilometers has urban land uses. Otherwise, ru ral dispersion coefficients are appropriate. 7



### USEPA’s AERSURACE model Version 08009 was used to develop the meteor ological data for the modeling analysis. This model was also used to evaluate surrounding land use within 3 kilometers. Based on the output from the AERSURFACE, a pproximately 1.9% of surrounding land use around the airport was of urban land use types includ ing: 21 – Low Intensity Residential, 22 – High Intensity Residential, and 23 - Comm ercial/Industrial/T ransportation.

This is less than the 50% value considered appropri ate for the use of urban dispersion coefficients. Based on the AERSURFACE analysis, it was conclude d that the rural option would be used for the modeling summarized in this report. Please re fer to Section 4.5.3 fo r a discussion of the AERSURFACE analysis.

7 USEPA, Revision to the Guideline on Air Quality Models : Adoption of a Preferred General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions, Appendix W to 40 CFR Part 51, November 9, 2005, Section 7.2.3.Sierra Club Evaluation of Compliance with 1-hour SO 2 NAAQS May 16, 2013 Page 9



### 4.2 Emission Rates and Source Parameters

The modeling analyses only considered SO 2 

### emissions from the facilit y. Off-site sources were not considered. Concentrations were predicte d for two scenarios shown in Table 2:

1) approved or allowable emissions based on pe rmits issued by the regulatory agency, and

2) measured actual hourly SO 2 

### emissions obtained from USEPA’s Clean Air Markets
Database. To assure realistic emission rates were used, emissions from all units at the facility
were combined and the hour with the maximu m total facility emissions was used to
determine the actual emissions.

Stack parameters and emissions used for the modeling analysis are summarized in Table 4.

Table 4 – Facility Stack Parameters and Emissions 8



### Stack S01 S02 Description Unit 1 Unit 2 X Coord. [m] 487131.86 487214.26 Y Coord. [m] 4525611.27 4525674.1 Base Elevation [m] 1357.97 1358 Release Height [m] 153.89 137.22 Gas Exit Temperature [°K] 413.817 368.15

Gas Exit Velocity [m/s] 20.133 20.734

Inside Diameter [m] 5.621 5.182 Allowable Emission Rate [g/s] 387.1 217.8 Maximum Emission Rate [g/s] 136.5 210.7

The above stack parameters and emissions were obtained from regulatory agency documents and
databases identified in Section 2.3. The analysis was conducted ba sed on 100% operating load using
maximum exhaust flow rates and em ission rates. Operation at less th an full capacity loads was not considered. This assumption tends to under-predict im pacts since stack parameters such as exit flow rate and temperature are typically lower at less than full load, reducing pollutant dispersion and increasing predicted air quality impacts. Stack lo cation, height and diameter were verified using aerial photographs, and flue gas flow rate and temperature were veri fied using combustion
calculations.

8 Nevada Department of Conservation and Natural Resources , Bureau of Air Pollution Control, Class I Air Quality Operating Permit No. AP4911-0457.01, August 17, 2005.Sierra Club Evaluation of Compliance with 1-hour SO 2 NAAQS May 16, 2013 Page 10



### 4.3 Building Dimensions and GEP

No building dimensions or prior downwash evalua tions were available. Therefore this modeling analysis did not address the e ffects of downwash which may incr ease predicted c oncentrations.

4.4 Receptors

For North Valmy Generating Station, three receptor grids were employed:

1. A 100-meter Cartesian receptor grid centered on North Valmy Gene rating Station and extending out 5 kilometers.
2. A 500-meter Cartesian receptor grid centered on North Valmy Gene rating Station and extending out 10 kilometers.
3. A 1,000-meter Cartesian receptor grid centere d on North Valmy Generating Station and extending out 50 kilometers. 50 kilometers is the maximum distance accepted by USEPA for the use of the AERMOD dispersion model. 9



### A flagpole height of 1.5 meters wa s used for all these receptors.

Elevations from stacks and receptors were obtained from National Elevati on Dataset (NED) GeoTiff data. GeoTiff is a binary file that includes da ta descriptors and geo-referencing information necessary for extracting terrain el evations. These elevations were extracted from 1 arc-second (30 meter) resolution NED files. The USEPA software program AERMAP v. 11103 is used for these
tasks.

4.5 Meteorological Data

To improve the accuracy of the modeling analysis , recent meteorological data for the 2007 to 2011 period were prepared using the USEPA’s program AERMET which creates the model-ready surface and profile data files required by AERMOD. Required data inputs to AERMET included surface meteorological measurements, twice-daily soundings of upper air measurements, and the micrometeorological parameters surface roughness, albedo, and Bowen ratio. One-minute ASOS
data were available so USEPA methods we re used to reduce calm and missing hours. 10 

### The USEPA software program AERMINUTE v. 11325 is used for these tasks.

9 USEPA, Revision to the Guideline on Air Quality Models: Adoption of a Preferred General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions, Appendix W to 40 CFR Part 51, Section A.1.(1), November 9, 2005.

10 USEPA, Area Designations for the 2010 Revised Primar y Sulfur Dioxide National Ambient Air Quality Standards, Attachment 3, March 24, 2011, p. 19.Sierra Club Evaluation of Compliance with 1-hour SO 2 NAAQS May 16, 2013 Page 11



### This section discusses how th e meteorological data was prep ared for use in the 1-hour SO 2 

### NAAQS modeling analyses. The USEPA software program AERMET v. 11059 is used for these tasks.

4.5.1 Surface Meteorology

Surface meteorology was obtained for Winnemucca Muni cipal Airport located near the North Valmy Generating Station. Integrated Su rface Hourly (ISH) data for th e 2007 to 2011 period were obtained from the National Climatic Data Center (NCDC) . The ISH surface data was processed through AERMET Stage 1, which performs data extr action and quality c ontrol checks.

4.5.2 Upper Air Data

Upper-air data are collected by a “weather balloon ” that is released twice per day at selected
locations. As the balloon is releas ed, it rises through the atmosphere, and radios the data back to the surface. The measuring and transmitting device is known as either a radiosonde, or rawindsonde. Data collected and radioed back include: air pressure, height, temperature, dew point, wind speed, and wind direction. The upper air data were pr ocessed through AERMET Stage 1, which performs data extraction and qua lity control checks.

For North Valmy Generating Station, the conc urrent 2007 through 2011 upper air data from twicedaily radiosonde measurements obtained at the mo st representative location were used. This location was the Elko, Nevada measurement station. These data are in Forecast Systems Laboratory (FSL) format and were downloaded in ASCII text format from NOAA’s FSL website. 11 

### All reporting levels were downloaded and processed with AERMET.

4.5.3 AERSURFACE

AERSURFACE is a non-guideline program that extracts surface roughness, albedo, and daytime
Bowen ratio for an area surroundi ng a given location. AERSURFACE uses land use and land cover (LULC) data in the U.S. Geological Survey’s 1992 National Land Cover Dataset to extract the necessary micrometeorological data. LULC data was used for processing meteorological data sets used as input to AERMOD.

AERSURFACE v. 08009 was used to develop surf ace roughness, albedo, and daytime Bowen ratio values in a region surrounding the meteorological data collection si te. AERSURFACE was used to develop surface roughness in a one kilometer radius surrounding the data collection site. Bowen ratio and albedo was developed for a 10 k ilometer by 10 kilometer area centered on the meteorological data collection site . These micrometeorological da ta were processed for seasonal

11 Available at: http://esrl.noaa.gov/raobs/Sierra Club Evaluation of Compliance with 1-hour SO 2 NAAQS May 16, 2013 Page 12



### periods using 30-degree sectors. Seasonal moisture conditions we re considered average with no
months with continuous snow cover.

4.5.4 Data Review

Missing meteorological data were not filled as th e data file met USEPA’s 90% data completeness requirement. 12 

### The AERMOD output file shows there were 4.2% missing data.

The representativeness of airport meteorological data is a potentia l concern in modeling industrial
source sites. 13 

### The surface characteristics of the airport data collection site and the modeled source location were compared. Since the Winnemucca Munici pal Airport is located close to North Valmy Generating Station, this meteorol ogical data set was considered appropriate for this modeling analysis.

5. Background SO 2 

### Concentrations

Background concentrations were determined cons istent with USEPA’s Modeling Guidance for SO 2 

### NAAQS Designations. 14 

### To preserve the form of the 1-hour SO 2 

### standard, based on the 99 th


### percentile of the annual distribution of daily maximum 1-hour concentrations averaged across the number of years modeled, the background fourth-highest daily maximum 1-hour SO 2 

### concentration was added to the modeled fourth-highest daily maximum 1-hour SO 2 

### concentration. 15



### Background concentrations were based on the 2008-10 design value measured by the ambient
monitors located in Nevada. 16



### 6. Reporting

All files from the programs used for this modelin g analysis are available to regulatory agencies. These include analyses prepared with AE RSURFACE, AERMET, AERMAP, and AERMOD.

12 USEPA, Meteorological Monitoring Guidance for Regulatory Modeling Applications, EPA-454/R-99-05, February 2000, Section 5.3.2, pp. 5-4 to 5-5.

13 USEPA, AERMOD Implementation Guide, March 19, 2009, pp. 3-4.

14 USEPA, Area Designations for the 2010 Revised Primar y Sulfur Dioxide National Ambient Air Quality Standards, Attachment 3, March 24, 2011, pp. 20-23.

15 USEPA, Applicability of Appendix W Modeling Guidance for the 1-hour SO 2 National Ambient Air Quality Standard, August 23, 2010, p. 3.

16 http://www.epa.gov/airtrends/values.html

### Case: 10

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### ORAL ARGUMENT NOT YET SCHEDULED

UNITED STATES COURT OF APPEALS FOR
THE DISTRICT OF COLUMBIA CIRCUIT

) NATIONAL ENVIRONMENTAL ) DEVELOPMENT ASSOCIATION’S ) CLEAN AIR PROJECT, ) ) Petitioner, ) )

v. ) Docket No. 10

- 1252 ) (and consolidated cases)
UNITED STATES ENVIRONMENTAL ) PROTECTION AGENCY, ) ) Respondent. ) )

RESPONDENT’S OPPOSITION TO MOTION OF THE STATE OF NORTH DAKOTA FOR A STAY OF EPA’S 1-HOUR SULFUR DIOXIDE AMBIENT STANDARD RULE

Respondent United States Environ m ental Protection Agency (“EPA”)

sub m its this Opposition to the Motion of the State of North Dakota for a Stay of

EPA’s 1- Hour Sulfur Dioxide Am bient Stand a rd Rule (“Stay Motion”). In its Stay

Motion, North Dakota seeks a stay of the rule in its entirety or, in the alternative, a

stay of the statutory directive that States sub m it any reco mme ndations for

attain me nt/nonattain me nt designations no later than June 3, 2011. The mo tion

should be denied because North Dakota has not satisfied the stringent require me nts

### Case: 10

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### 2 for obtaining a stay of agency action. The m otion fails to address any of the

elements for obtaining a stay with regard to any of the prom ulgated ele m ents of the

rule, i.e.

, the revised sulfur dioxide (“S O 2 

### ”) standard itself and the pro m ulgated

revisions to the SO 2 

### m onitoring network. Rather, the m otion is addressed solely to

an advisory discussion in the final ru le preamble regarding EPA’s anticipated

approach to implementing the revised NAAQS. Thus, the motion provides no

basis to stay the rule as a whole.

The mo tion mu st also be denied with regard to the alternative relief requested.

First, North Dakota has not de m onstrated a substantial likelihood of success on the

m erits. It challenges only advisory state m ents in the final rule prea m ble concerning

EPA’s conte m plated approach for m aking initial attain m ent designations by the

June 2012 statutory dea d line, an approach the Agency will be addressing in future

actions. As the pream ble m akes clear, EPA has taken no final action nor

prom ulgated any regulatory require me nts regarding designations, and, in particular,

has taken no final action on its approach to ma king attain me nt deter m inations. To

the contrary, the prea m ble specifically preserves EPA’s ability to ma ke those

decisions solely on the basis of m onitoring data. 75 Fed. Reg.

35,520, 35,552 n.22 (June 22, 2010). Because these prea m ble state m ents are not

final agency action, the Court lacks jur i sdiction to review the m, and North Dakota

has no substantial likelihood of prevailing on the me rits.

### Case: 10

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### 3 Moreover, even if the challenged preamb le statements could be read as final

agency action, the Agency has historic a lly relied on m odeling to ma ke designations

for sulfur dioxide. To the extent the proposal prea m ble reflected a possible change

to that practice, it clearly left open the possibility that the Agency would choose

not to adopt the proposed change. Inter e sted parties should have known that EPA

m ight retain its past practice, and had am ple opportunity to co mm ent on that

possibility. Thus, North Dakota cannot de m onstrate a likelihood of success on its

claim that it lacked an opportunity to co mm ent on the approach to initial

designations discussed in the prea m ble.

Second, North Dakota cannot de m onstra te that it will suffer irreparable harm

from the statutory directive that it sub m it designation reco mme ndations to EPA by

June 2011. North Dakota clai ms harm from an alleged bar to the use of m onitoring

data as the sole basis for its designation reco mm e ndations. But, nothing in the SO 2



### Rule prevents North Dakota from basing its reco mme ndations solely on m onitoring

data, and thus the Rule does not cause the harm North Dakota clai m s. Id.

Further more, designation reco mme ndations have no independent legal effect. An

area is not designated until EPA pro mul gates the designation, which EPA is

required to do by June 201 2 1 / 

### (a requirem ent that would not be affected by a stay of

1 / 

### The date can be extended to June 2013 if EPA lacks sufficient infor m ation to act in 2012. 42 U.S.C. § 7407(d)(1)(B)(i).

### Case: 10

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### 4 the 2011 reco mme ndation sub m ission date). Moreover, EPA is not bound by the

State’s reco mm endations and m ust prom ulgate a designation for an area even if the

State sub m its no reco mm e ndation at all.

Finally, a stay of the SO 2 

### Rule will cause harm to other parties and is

contrary to the public interest. The rule under review revises the prim ary am bient

air quality standard for sulfur dioxide based on findings by EPA that the prior

standards were not requisite to protect hu m an health with an adequate m argin of

safety. A stay of the rule’s regulatory provisions pro m ulgating the new standard

would delay im ple m entation of the m easures needed to achieve attain me nt with the

new standard, including require me nts ass o ciated with the per m itting of new and

modified major stationary sources which became effective on the effective date of

the standard. A stay of the Rule would thus prolong the ti me during which existing

air quality causes adverse im pacts to public health. A stay of the 2011 deadline for

States to sub m it reco mme ndations to EPA would not alter EPA’s obligation to

prom ulgate designations by 2012, but would increase the burden on EPA to

develop t he de signations.

BACKGROUND

The consolidated petitions in this ca se seek review of an EPA regulation

revising the pri m ary National Am bient Air Quality Standards (“NAAQS”) and

associated regulatory require me nts for oxides of sulfur as m easured by SO 2

### Case: 10

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### 5 pursuant to section 109 of the Clean Air Act, 42 U.S.C. § 7409. 75 Fed. Reg.

35,520 (June 22, 2010) (“S O 2 

### Rule”). Those regulatory require m ents took effect

on August 23, 2010, and are currently being im ple m ented. The NAAQS

provisions of the Clean Air Act establish a co mp rehensive sche me to protect public

health and welfare from ubiquitous air pollutants. 42 U.S.C. § 7409. Pri ma ry

standards mu st be set at levels that, in the judg m ent of the Ad m inistrator, are

requisite to protect public health with an adequate margin of safety. Id.

§ 7409(b)(1). The Act requires periodic review of the NAAQS. Id. § 7409(d).

See generally Am erican Lung Ass’n v. EP A

, 134 F.3d 388, 388

- 89 (D.C. Cir.

1998).

EPA first pro m ulgated a pri mary NAAQS for sulfur dioxide in 1971. 36

Fed. Reg. 8187 (April 30, 1971). In May 1996, aftera lengthy review, EPA

announced a final decision not to revise the NAAQS. 61 Fed. Reg. 25,566 (May

22, 1996). Petitions for review of that dec i sion were filed in this Court, and the

Court held that EPA had failed to adequately explain the basis for its conclusion

that short -term SO 2 

### exposures to asth ma tics do not constitute a public health

proble m. Am erican Lung Ass’n v. EP A

, 134 F.3d 388. In the rule under review

here EPA has addressed that issue by replacing the prior 24

- hour and annual

primary standards with a new 1- hour primary standard. The new standard is now

in effect, and is being im ple m ented in EP A’s prevention of significant deterioration

### Case: 10

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### 6 per m itting program for new and m odified ma jor stationary sources. See 57 Fed.

Reg. at 35,580/1.

Within one year after prom ulgation of a new or revised NAAQS (or sooner

if required by EPA) States are directed to sub m it to EPA a list of all areas that the

State reco mm ends be designated by EPA as attain m ent, nonattain m ent, or

unclassifiable for the new or revised NAAQS. 42 U.S.C. § 7407(d)(1)(A). In the

case of the revised SO 2 

### standards, such designations are due by June 3, 2011, one

year after EPA prom ulgated the revised NAAQS by signing and publicly

disse m inating the notice of final rule ma king. Within two years of pro m ulgation (or

three years if EPA lacks sufficie nt infor m ation), the Act requires EPA to

pro m ulgate designations. Id. § 7407(d)(1)(B)(i). EPA ma y m odify any sub m itted

list of designations provided by a State if it gives the State 120 days notice, and

m ust pro m ulgate designations as EPA d ee ms appropriate for any area for which no

designation reco mme ndation is provided by a State. Id. § 7407(d)(1)(B)(ii).

Thus, EPA’s statutory obligation to prom ulgate designations is independent of

whethera State submits recommendations.

The SO 2 

### Rule, like its predecessors, includes regulatory provisions that

establish the NAAQS itself, as well as regulations governing the installation and

use of m onitors utilized to m ea sure am bient concentrations of SO 2 

### . See

, e.g

. , 40

C.F.R. §§ 50.4(e); 50.14(c)(2)(vi); 50.17; part 50 Appendices A-1 and T; part 53,

### Case: 10

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### 7 and part 58. Historically, to deter m ine if an area is in attain me nt with the SO 2



### NAAQS, EPA has used a combination of re sults from regulation

- required monitors

and air quality m odeling, even though in the NAAQS regulations the m selves EPA

has not pro m ulgated require me nts that States or sources conduct m odeling.

Instead, at 40 C.F.R. part 51, Appendix W, EPA has pro m ulgated guidelines on air

quality m odels, to be used for regulatory purposes such as State Im ple m entation

Plan (“SIP”) develop m ent and new source review and

prevention

- of

- significant

- deterioration per m itting actions. See

, e.g

. , 40 C.F.R. part

51, Appendix W, § 1.0. In the current rule EPA has revised the regulatory

require me nts for the m ini mum nu m ber and place m ent of m onitors and adopted a

new reference m ethod for detecting am bient SO 2 

### , but did not pro m ulgate or revise

any require me nts regarding m odeling.

In the prea m ble to the proposed SO 2 

### Rule, EPA discussed the revisions to

the m onitoring network proposed to account for the revision of the standard, i.e

. ,

the change from the 24

- hour and annual st andards to a single one

- hour standard.

74 Fed. Reg. 64,810, 64,846

- 55 (Dec. 8, 2009). In the proposal EPA did not

discuss its historic and current uses of m odeling in im ple m enting the then

- effective

annual and 24

- hour SO 2 

### standards. In public co mme nts on the proposal, nu m erous

parties suggested that the proposed monitoring network was both inadequate in

scope and overly burdenso me to ad m inister, and so me co mme nters suggested that

### Case: 10

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### 8 m odeling should be used to relieve the adm inistrative burden that a more extensive

m onitoring regi me would otherwise im pose. 75 Fed. Reg. at 35,551/1.

In the pream ble to the final rule, EPA explained in response to co mm ents

that the Agency anticipated in subsequent actions to continue its historic practice of

relying on both m odeling and m onitoring for deter m ining whether an area is in

attain m ent with the SO 2 

### NAAQS and adopted rules for a sm aller m onitoring

network than initially proposed. 75 Fed. Reg. at 35,550

- 51. However, the

pream ble m akes clear that, except for the pro m ulgated require m ents relating to the

scope of the m onitoring network and detection me thod, the Agency is still

developing its policy for such fut ure actions as designations and SIP

approvals/disapprovals and intends to iss ue further guidance in the future through a

notice

- and

- co mm ent process. Id. The preamble also sta t es EPA’s expectation that

any decisions about whether to base an attain me nt designation or deter m ination on

m onitoring alone, without reliance on m odeling, would be m ade on a case

- by

- case

basis. Id. at 35,552 n.22.

Following pro m ulgation of the rule, nu m erous parties filed petitions for

review with this Court, and each of those parties also submitted to EPA

ad m inistrative petitions for reconsideration of the rule under section 307(d)(7)(B)

of the Act, 42 U.S.C. § 7607(d)(7)(B). The petitions for reconsideration objected

to EPA’s final rule ma king prea m ble discussion explaining EPA’s anticipated

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### 9 approaches in future designations and SIP actions. In addition, each requested that

EPA ad m inistratively stay the final rule pending such reconsideration. EPA is

currently evaluating the petitions for r econsideration and has not yet form ally

responded to the m, but, as the Agency stated in its pending m otion filed with the

Court seeking a short -term abeyance of the instant litigation, EPA intends to

provide initial responses to the petitions for reconsideration, including the requests

for a stay of the rule, by January 8, 2011.

STANDARD OF REVIEW

A stay is a disfavored rem edy. “On a m otion for stay, it is the m ovant’s

obligation to justify the court’s exercise of such an extraordinary remedy.” Cuomo

v. United States Nuclear Regulatory Comm’n

, 772 F.2d 972, 978 (D.C. Cir. 1985).

The factors for deter m ining whether a stay is warranted are: (1) whether the

m ovant has de m onstrated a substantial li k elihood that it will prevail on the me rits;

(2) the prospect of irreparable injury to the m oving party if relief is withheld; (3)

the possibility of harm to other parties if relief is granted; and (4) the public

interest. Nken v. Holde r , 129 S. Ct. 1749, 1761 (2009). These four prongs of the

stay standard are to be applied string e ntly. Aberdeen & Ro ckfish R.R. Co. v.

Students Challenging Regulatory Agency Procedures

, 409 U.S. 1207, 1218 (1972).

“A stay is not a matter of right, even if irreparable injury m ight otherwise result.”

Nke n , 129 S. Ct. at 1760 (citation om itted).

### Case: 10

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### 10 To de m onstrate a substantial likelihood of success on the m erits, a petitioner

m ust show that it is likely to persuade this Court that EPA’s action is “arbitrary,

capricious, an abuse of discretion, or ot herwise not in accordance with law.” 42

U.S.C. § 7607(d)(9)(A). This narrow, defer e ntial standard prohibits a court from

substituting its judg m ent for that of the ag ency and presu m es the validity of agency

actions. Motor Vehicle Mfrs. Ass’n v. State Farm Mut. Auto. Ins. Co.

, 463 U.S.

29, 43

- 44 (1983). Judicial deference al so typically extends to an agency’s

interpretation of a statute it ad m inis t ers, United States v. Mead Corp

. , 533 U.S.

218, 227

- 31 (2001); Chevron, U.S.A., Inc. v. Natural Res. Def. Council, Inc.

, 467

U.S. 837, 842

- 45 (1984), and of its own regulations. Auer v. Robbin s , 519 U.S.

452, 457 (1997).

To establish irreparable har m, a petitioner mu st de m onstrate an injury that is

“both certain and great; it m ust be actual and not theoretical.” Wisconsin Gas Co.

v. FERC

, 758 F.2d 669, 674 (D.C. Cir. 1985). A m ovant for injunctive relief m ust

show that “[t ] he injury co mp lained of [i s] of such i mm inence that there is a clear

and present need for equitable relief to prevent irreparable har m .” Id. (citation

om itted). The m ovant mu st “substantiate the claim that irreparable injury is ' likely'

to occur,” and “show that the alleged harm will directly result from the action which

the m ovant seeks to enjoin.” Id ; see also Nke n , 129 S. Ct. at 1761 (m ore than a

“mere possibility” of success on the me rits is required, and the standard for

### Case: 10

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### 11 irreparable harm is more than showing the “possibility” of har m); Winter v.

NRDC

, 129 S. Ct. 365, 375

- 76 (2008) (holding that in a preli m inary injunction

case, plaintiffs must demonstrate that irreparable injury is “likely,” not just

“possible”).

ARGUMENT

I. THE MOTION IS PREMATURE

Fed. R. App. Proc. 18(a) requires that a petitioner mu st ordinarily m ove first

before the agency for a stay of its ord er before seeking a stay in the Court of

Appeals, or else show that m oving before the agency would be impracticable. In

this case, although North Dakota (and other Petitioners) have sought a stay of the

SO 2 

### Rule from EPA, EPA has not yet acted on that request, and North Dakota has

not de m onstrated that it is im practicable to wait for EPA to act on those requests

before seeking a stay from this Court. As described in EPA’s Motion to Hold Case

in Abeyance, EPA intends to act on the pending ad m inistrative petitions for

reconsideration by January 8, 2011. At that ti me EPA will also act on the included

requests for a stay, as the Agency previou s ly infor m ed Petitioners. Im plicit in Rule

18's require m ents is that a petitioner m ust receive a response to its request for a

stay from the agency before seeking a judicial stay. North Dakota has neither

waited for that response, nor de m onstra t ed why doing so would be im practicable

for sub m itting a reco mme ndation that is not due until June 2011. Because North

### Case: 10

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### 12 Dakota’s request for a stay is still pending before the Agency and the Agency has

co mm itted to responding in a ti m ely fashion, North Dakota’s mo tion for stay in

this Court is prem ature and should be denied.

II. NORTH DAKOTA HAS PRESENTED NO BASIS FOR STAYING
THE ENTIRE SO 2 

### RULE

In its m otion, North Dakota asks the Court to stay the SO 2 

### Rule in its

entirety (including the standard itself and the associated m onitoring provisions) or,

in the alternative, to stay the June 3, 2011 statutory deadline by which States ma y

sub m it reco mme nded designations to EPA. North Dakota, however, identifies no

grounds for staying the entire rule. With regard to the m erits, North Dakota

advances no objection to the pro m ulgated standard or the pro m ulgated

require me nts related to m onitoring. Nor does it present any claim that it will suffer

irreparable harm from either the revis ed standard or the revised require m ents

related to m onitoring. In fact, North Dakota does not address any aspect of the

Rule except the non

- binding prea m ble discussion concerning how EPA expects to

use m odeling in future area designations and SIP actions. Thus, North Dakota has

not m et the stringent standard for obtaining a stay of the Rule as a whole, and that

request mu st be denied.

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### 13 III. NORTH DAKOTA CANNOT DEMONSTRATE A SUBSTANTIAL LIKELIHOOD OF SUCCESS ON THE MERITS

The sole claim on the merits present ed in the Stay Motion is that the

pream ble of the final rule allegedly requires the use of air quality m odeling for

deter m ining whether an area is in attain m ent with the revised SO 2 

### NAAQS, that

this approach differs from the approach discussed in the prea m ble to the proposal,

and that the public did not have an opportunity to co mme nt on the approach

discussed in the final rule. This claim lacks me rit for two reasons.

First, North Dakota is not challenging any provision of the pro m ulgated

regulations, but rather a discussion in the prea m ble, i.e

. , 75 Fed. Reg. at 35,550

- 54.

Although so me pream ble discussions m ay constitute final agency action, it is clear

that this particular discussion does not. Rather, the challenged discussion

regarding the potential use of m odeling is, at mo st, non

- binding guidance that the

Court lacks jurisdiction to review. The preamble specifically states:

In ma ny respects, both the overview discussion below and the subsequent more detailed discussions explain our expected and intended future action in im ple m enting the 1- hour NAAQS
– in other words, they constitute guidance, rather than final agency action

– and it is possible that our approaches m ay continue to evolve as we, States, and other stakeholders proceed with actual implementation. In other respects, such as in the final regulatory provisions regarding the

prom ulgated m onitoring network, we are explaining EPA’s final conclusions regarding what is requ i red by this rule. We expect to issue further guidance regarding im ple m entation

. . . . EPA intends to solicit public co mme nt prior to finalizing this guidance.

Id. at 35,550/3 (em phasis added).

### Case: 10

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### 14 Moreover, nowhere in the preamble (m uch less in any prom ulgated

regulation) does EPA state that m odeling m ust be used for designating areas as

attain me nt, nonattain me nt or unclassifiabl e. Thus, the alleged require m ent North

Dakota seeks to challenge does not exist. Rather, the preamble states: “We expect

that EPA’s final area designation decisions in 2012 would be based principally on

data reported from SO 2 

### monitors currently in pl ace today, and any refined

m odeling the State chooses to conduct specifically for initial designations.” Id. at

35,552/1 (em phasis added). The prea m ble then goes on to say “EPA anticipates

ma king the deter m ination of when m onitoring alone is ‘appropriate’ for a specific

area on a case

- by

- case basis, informed by the area’s factual record, as part of the

designation process.” Id. at 35,552 n.22.

In short, EPA has si m ply not taken the final agency action alleged by North

Dakota and there is no such action for the Court to review or to stay. To the

contrary, the preamble states that EPA be lieves that its historic approach to SO 2


### designations continues to appear to be appropriate, while at the sa me ti me giving

States the flexibility to reco mm end the appropriate m ix of data to rely on,

including the possibility of relying entirely on m onitoring if supportable.

Second, even if the prea m ble could be construed as final agency action,

North Dakota’s claim that the public lac k ed notice of the possibility that EPA

m ight continue to use m odeling when ma king designations is without me rit. As

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### 15 EPA has frequently explained, because of the nature of SO 2 

### pollution, EPA has

historically relied on air quality m odeling (in addition to any required m onitoring)

to determine whether an area is violating the SO 2 

### NAAQS. 75 Fed. Reg. at

35,551/2

- 3, 35,559/2

- 3; see SO 2 

### Guideline Document (available at

www.epa.gov/ttn/oarpg/t1/ mem oranda/so2_guide_092109.pdf) at 2-5 (“For SO 2



### attain me nt de m onstrations, m onitoring data alone will generally not be adequate.”)

and at 2-1 (“Attain me nt deter m inations for SO 2 

### will generally not rely on am bient

m onitoring data alone, but instead will be supported by an acceptable m odeling

analysis which quantifies that the SIP strategy is sound and that enforceable

em ission li m its are responsible for attain m ent.”) As a State responsible for

reco mm ending whether an area should be designated attain me nt or nonattain me nt,

North Dakota certainly should have been aware of the Agency’s historical

approach.

Thus, to the extent the approach to designations described in the proposal

pream ble was li m ited to m onitoring, in de-em phasizing the role m odeling has long

played in SO 2 

### im ple m entation it represented a de parture from the Agency’s prior

practice. In such circums t ances, affected parties are surely aware that not adopting

the proposed change is a possibility. Am erican Iron & Steel Inst. v. EP A

, 886 F.2d

390, 400 (D.C. Cir. 1989) (“One logical outg r owth of a proposal is surely, as EPA

says, to refrain from taking the proposed st ep.”) In fact, the Agency did receive

### Case: 10

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### 16 co mme nts urging the Agency to retain its historic approach. 75 Fed. Reg. at

35,551/1. Accordingly, there is no basis for North Dakota’s claim that it lacked

notice that the Agency m ight choose not to adopt a more m onitoring

- focused

approach as discussed in the proposal prea m ble, but instead to expect to retain its

historic approach in which m odeling is generally, though not always, utilized.

IV. NORTH DAKOTA CANNOT DEMONSTRATE AN IMMINENT THREAT OF IRREPARABLE HARM

There is no merit to North Dakota’s claim that it will suffer irreparable harm

if the SO 2 

### Rule or the statutory deadline to sub m it designation reco mme ndations is

not stayed. North Dakota first claims that it will be harmed because the SO 2 

### Rule

“casts a cloud” over its ability to use its m onitoring data and “deprive[s] the state

of its right to m anage its air resources.” Stay Motion at 17. As de m onstrated

above, there is no factual basis for this claim because neither the SO 2 

### Rule itself

nor the prea m ble discussion prohibits North Dakota from basing its reco mme nded

designations on its m onitoring data alone. 75 Fed. Reg. at 35,552 n.22. Nor does

anything in the Rule or prea m ble prohibit EPA from basing its designations for

North Dakota on m onitoring data alone if EPA deter m ines that the m onitoring data

is sufficient to deter m ine North Dakota’s attain me nt status. 2 /

2 / 

### If EPA were to deter m ine that the m onit o ring data was not sufficient to deter m ine

an area’s attainment status, and thus that the area would have to be categorized as unclassifiable until sufficient m onitoring da ta or m odeling results were available, (continued...)

### Case: 10

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### 17 Moreover, the State’s reco mm ended designations, which are due June 3,

2011, have no legal effect on sources. Not until EPA pro m ulgates the actual

designations, which the statute requires it do by June 3, 2012 (or 2013 if extended),

will there be a designation in place that has legal effect. Thus, North Dakota can

suffer no actual harm from sub m itting its reco mme nded designations.

North Dakota’s second claim of har m, that the use of m odeling will result in

more areas being designated as non a ttain me nt because m odeling is more

“conservative,” Stay Motion at 17

- 18, is purely speculative. North Dakota presents

no evidence at all to support its assertion that m odeling will necessarily result in

areas of the State being designated as nonattain me nt inappropriately, and thus there

is no basis on which the Court could find that North Dakota could suffer injury

. 3 /



### Furthermore, as the preamble states, the m odeling guidance that EPA intends to

2 / 

### (...continued) that designation would be result of the insufficiencies in the data, not of anything that EPA has done in the Rule.

3 / 

### While it m ight seem at first blush as if actual m onitoring should be inherently more

accurate than modeling, this is not nec e ssarily the case. In fact, “[i]n the past, EPA used a co mb ination of m odeling and m onitoring for SO 2 

### during per m itting, designations and re- designations in recognition of the fact that a single m onitoring site is generally not adequate to fu lly characterize ambient concentrations, including the ma xi mum ground level concentrations, which exist around stationary SO 2 

### sources.” 75 Fed. Reg. at 35,559. This is especially im portant because “[t ] he
1- hour NAAQS is intended to provide protection against short

- term (5 m inute to 24 hour) peak exposures”. Id. See Am erican Lung Ass’n v. EPA

, 134 F. 3d at 392

- 93 (re ma nding EPA’s deter m ination that such exposures do not constitute a threat to public health) and 75 Fed. Reg. at 35,536 (5

- 10 m inute SO 2 

### exposures can result in adverse health effects to asth m atics).

### Case: 10

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### 18 provide States for use in deter m ining attain me nt of the revised SO 2 

### standard is still

under develop m ent. 75 Fed. Reg. at 35

, 552

- 54. Thus, any state m ents about how

the use of m odeling affects the designation process for the revised SO 2 

### standard are

necessarily speculative.

Finally, the actual designations will be m ade by EPA, an action that EPA

expects to take by June 3, 2012. Sta t es have an opportunity under the Act to

provide input on the designations before they are m ade, and EPA’s designations

are subject to judicial review. Any cla im that m odeling is inappropriately used by

EPA for a particular designation can and should be raised in that process.

V. A STAY WOULD HARM THIRD PARTIES AND IS CONTRARY TO
THE PUBLIC INTEREST

A stay of the SO 2 

### Rule, whether in whole or in part, would cause harm to

third parties and is contrary to the public interest because it would delay

achieve m ent of the public health benefits of the revised standard, which is now in

effect and being used for the Act’s New Source Review and Prevention of

Significant Deterioration per m itting progra m s. After an exhaustive review of the

existing data, EPA deter m ined that the prior SO 2 

### standard was not adequately

protective of hu m a n he alth and required revision, a conclusion am ply supported by

the record. EPA’s statutorily m andated science review committee, the Clean Air

Scientific Advisory Co mm ittee, reco mm ended unani m ously that the current

standard be revised because the current st andards are not adequate to protect the

### Case: 10

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### 19 public health, and that EPA should adopt a one

- hour standard in their place. 75

Fed. Reg. at 35,530, 35,538. Short

- term exposure to SO 2 

### results in adverse

respiratory effects such as bronchoconst r iction (narrowing of the airways) and

increased asthma symptom s. Id. at 35,525

- 26. Studies also show an association

between short

- term SO 2 

### exposure and increased em ergency depart m ent visits and

hospital ad m issions for respiratory illness, particularly am ong children, the elderly,

and asth m atics. Id. at 35,547.

Im portantly, the data de m onstrate that these adverse health effects can occur

at concentration levels that are allowed by the prior SO 2 

### NAAQS. Id. at

35,535

- 36. Thus, im ple m entation of the rev i sed standard is necessary to reduce the

adverse health effects associated with these exposures. North Dakota’s m otion

does not address this issue at all, and t hus fails to address two of the ele m ents

needed for a stay of agency action.

A stay of the SO 2 

### Rule, either in whole or in part, is likely to delay

attain m ent of the revised standard. A delay of the SO 2 

### Rule as a whole will delay

States’ implementation of the control measures needed to achieve co mp liance with

the revised standard and the require me nt for new or m odified ma jor stationary

sources to implement necessary controls pursuant to the Clean Air Act’s New

Source Review and Prevention of Signif i cant Deterioration per m it require me nts.

### Case: 10

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### 20 A stay of the date for States to reco mm end designations for areas as

attain me nt, nonattain me nt, or unclassifiable will not delay EPA’s independent

obligation to pro m ulgate designations. However, it could complicate the process

of establishing area designations and im pose additional burdens on EPA if States

do not submit designation recommendations because EPA would not have the

States’ reco mm ended designations as a starting point. Thus, a stay of the SO 2 

### Rule

will harm third parties and be adverse to the public interest by delaying the public

health benefits of the revised standard.

CONCLUSION

For the reasons stated above, North Dakota’s m otion for a stay of the SO 2



### Rule should be denied.

Respectfully sub m itted,

IGNACIA S. MORENO Assistant Attorney General

/S/ Norman L. Rave, Jr. NORMAN L. RAVE, JR. Environ m ental Defense Section Environ m ent & Natural Resources Division United States Depart m ent of Justice P.O. Box 23986 Washington, D.C. 20026

- 3986 (202 ) 616

- 7568 Counsel for Respondent

### Case: 10

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### 21 Of Counsel:

STEVEN SILVERMAN MICHAEL THRIFT Office of General Counsel
U. S. Environ m ental Protection Agency 1200 Pennsylvania Ave., NW Washington, DC 20460

Nove m ber 8, 2010

### Case: 10

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### CERTIFICATE OF SERVICE

I hereby certify that on this 8th day of Nove mber, 2010, I caused a copy of the foregoing docu m ent to be served by the Court’s CM/ECF system on:

Andrea Bear Field Lucinda Minton Langworthy
Hunton & Willia ms LLP 1900 K Street, N.W. Washington, DC 20006

Leslie Sue Ritts Ritts Law Group, PLLC 620 Fort Willia ms Parkway Carriage House Alexandria, Virginia 22304

Donald Trahan State of Louisiana Dept. of Environ m ental Quality P.O. Box 82282 Legal Affairs Division
Baton Rouge, Louisiana 70884

- 2282

David S. Baron Seth Lee Johnson Earthjustice Legal Defense Fund 1625 Massachusetts Ave., NW Suite 702 Washington, DC 20036

- 2212

Roxanne Giedd Office of the Attorney General,

State of South Dakota 1302 East Highway 14 Suite 1 Pierre, South Dakota 57501

- 8501

Nhu Q. Nguyen Office of the Attorney General, State of Nevada 100 North Carson Street Carson, Nevada 89701

- 4717

### Case: 10

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### Sandra Patricia Franco Robert N. Steinwurtzel Bingham McCutchen LLP 2020 K Street, NW Washington, DC 20006

- 1806

Margaret I. Olson Assistant Attorney General Office of the Attorney General State of North Dakota Solicitor General 500 North 9th Street Bismark, North Dakota 58501

- 4509

Paul M. Seby Marian C. Larsen Moye White, LLP 1400 16th Street
6t h Floor Denver, Colorado 80202

- 1486

Nancy Elizabeth Olinger Assistant Attorney General Environ m ental Protection and Administrative Law Division P.O. Box 12548 (MC- 018) Austin, Texas 78711

- 2548

Benja m in Joseph Alke Goetz, Gallik& Baldwin, PC 35 North Grand P.O. Box 6580
Bozem an, Montana 59771

- 6580

/S/ Norman L. Rave, Jr.
Norman L. Rave, Jr.

2I l-45-i995 2,37at.1 FROi.1

,

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JOHN K. VAt{ DE KFr}{p, Attorney General. of the State of California ANDREA SHERIDA}I ORDTN Chief Assistant Attorney General THEODORA BERGER Assistant Attorney General CRAIG C. THOI.'PSON EDWARD G. WETL CLI FFORD RECH?SCHAFF€N Deputy Attorneys General 21ol webster Street Oakland, CA 94612 Telephone: (415) 464-0572 

# FILED

SUPERTOR

CCURT
SAfITA 8r'l"FrlilA 

## DEC 0 3 1990

xE}c{Erh A Pil ir ;, ouuf:/

ctsil'FrcoErf

PLE OF THE S?ATE I. JOHN K. VAIIT DE neral of the State

Plaintiffs,

v.

A MARIA CHILI, rNc.

Defendant1. I am currently

Environruental protection

(hereafter the "Region', COUNTY OP SHITA BARBARA

oF CALIFORNfA ex. ) No. SM 64010 KAHP, Attorney of California, ) (Case transferred to ) South County, Z/26/eol

DECI.ERATTON OF JOEN C. 

### vruo!|:l

DATE: Dec. 14, 1990 TIME: 9:oo a.m, Dept: To Be Assigned 

### ey: { yol.; (ls*

u u$*ane riootns.

oc|fu crn'Frcort

Attorneyg for the peopte of the state of carifornia

SUPERIOR COTIRT OF THE STATE OF CALTFORNIA

T, John C. Vinont, declare:

enployed by the United States

Agency (hereatter ilEpArr), Region IX

or rrRegional Officer') as the Regional
Heteorologist. I have been ernployed in this posltion since June

1987.

a. As the Regional l{eteorologist f serve as the
Regionrs expert on air guality nrodeling, neteorological

information and anbient air irnpact analyses. My position is1

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within the Air and Toxics Division of the Regional Office. f

provide support to that dlvlslon; to the other divisions witnin

the Region, such as the Haeardous waste oivision; and to state

and locar agencies vithin Region rX. one of the prinary duties

of ny position is to ensure that appropriate air quality rnodeling

techniqres are used by this and other ageneies when conducting

anrbient air quality irrpact analyses.

b. There are a variety of ,'air guality models.il

These include conceptual nrodels, qualitative descriptions of the

behavior of pollutants in tne atrnosphere; physical rnodels, scaled

nodels of pollution sources and their surroundings studied in a

conLrolled environment, Euch as a wind tunnelt statisticar

modeLs, which encompags statisticalJ.y based descriptions of

source-receptor relationships; and mathematical nodels, which are

mathehatical representations of the physical processes which lead

to transport and dispersion of pollutants in the atmosphere. The

focus of tbe remaining dlscussion is on mathematical. rrodelsi

hereafter any reference to an air guarity rrodel is inpricitly

meant to refer to a mathematical air guality nodeI.

c. f perform, review and oversee air quality nodeling

for a variety of different sources and source types. These

include stationary aources with enissions emanating fron a stack,

including st,ack sources with aerodynanlc downwash induced by

nearby buildings; stationary sources htlth emLssions emanating

f,rom a broad area, coruoonly called area sgurces; mobile sources,

emissions from autonobiles, trucks, busses, al.rcraft, etc.; and

urban and regional scale roodeling, which enconpasses modeling aI).1

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of the above processes together on the scare of an entlre urban

area or over a number of urban areas together.

d. The pollutants modeled include both inert
pollutants, those which renain cheurically stable for long periods

of tine in the atnosphere, and chemicarry reactive pollutants,

those which undergo relatively rapid chemlcal transformation and

t'hose which are not directry enitted, but rather forrn through a

series of chemical reactions withln the atnosphere.

2. Previous to rny ernployrnent at EpA, I worked from Marcir

1982 to June 1987 as an Environrnental Engineering Specialist in

the Air Quality Bureau of the State of New Mexico. My primary
responsibillties there htere very siurilar to rny current position

at EPA. f performed, anbient inrpact analyses of various air
porlution sources and conducted engineering analyses of the

sources to deternine ernission characteristics. The prinary focus

of the analyses was on inert pollutants from stationary sources.

a- prom August 1978 to March 1982 r worked for the
Atnospheric science Departnent at Colorado State University (csu)

as a Research Assistant. r vorked on a varlety of baeic

scientific researc.h projects dealing with croud physics. My
prirrary area of research dealt with the uptake of acidic
pollutants in snow,

b- Fron Novernber Lg77 to August LgTg r worked as a Physlcar science Aide for the pacj.fic Marine Environrnentar
Laboratory of the National oceanographic and Atrnospheric

Adninistration. My duties there involved writing a1

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climatological suEaar)r of h.rget Sound and analyzing the affects

of r.rlnds on o11 spill transport in hrget Sound.

3. I received a Bachelor of Science Degree ln Atnospheric

sciences fron the university of waEhington 1n 1978 and a Haster

of Science Degree in Atnospheric Science froro Colorado State

University.

4. As the Regional Meteorologiet, I routlnely evaluate the

adequacy of air cruality nodering on a technical basis and with

respect to its acceptability in the reguLatory fraroework.

Acceptable air quality rnodeling and analysis procedures are

outlined in The Guideline on Alr ouatitv Hodels (Revised) (EPA

450/2-78-027R, July 1986, supplement A, July tggz) (hereafter the 'rcuidelinen). The Guideline was first published in April 19?B to

satisfy the requirenents of g32O of the 1977 aruendrnents to the

Cl-ean Air Act. The Guideline specifies appropriate modele to use

and provides guidance on their appropriate apptication. The

Guideline provides a common basis for estinating the air quarity

concentrations used in assessing control strategies and

developing emission linits. The nodeling technigr:es ernbodied in

the Guideline are subjected to public, scientific revierr in

aeeordanee with 5320 of the CAA.

a, EPA has four prinary, on-going activities to

provide direct input for consistency in inplementation and for

revisions to the Guideline. The first is a series of annual EPA

workshops conducted for the purpose of ensuring consistency and

providing clarification in the applicatlon of nodels. The second

activity, directed toward the inprovenent of nodeling procedures,1 l-45-1995 2,39At'1 FROi'1 P 5

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27 is the cooPerative agreenent that EPA has vlth the scj.entlfic

co-'r'runity represented by the Anerican Heteorological Society.

This agreement provides scientific assessDent of procedures and

proposed techniques and EPonsors workshops on key technical

iseues. The third activity is the solicitation and reviev of new

models fron the technical and user connunity. In the lilarch 27,

19Bo Feder4l..Register, a procedure was outlined for the subnittal

to EpA of privately developed models. After extensive evaluation

and scientifj.c review, these models, as well as those made

available by EPA, are considered for recognltlon ln the

Guideline. The fourth activity is the extensive, on-going

research efforts by EPA and others in air quality and

meteoroloqrical nodel lng.

b. From the aforementioned process a number of models

vere selected as being refined ruodels, suitable for regulatory

application. Each refined urodeL unde:rrent intensive evaluation.

The evaluation exercises include statistical measures of model

perfomance in conrparison with Deasured air quality data and,

where possible, peer scientific reviews.

c. After a model has been selected as a refined nodel

for a partieular €ype of apPlication, EPA considers the model

appropriate for general use for that type of application without

undergoinlt case-by-case evaluatlon, provided that the application

fol.Ior"rs the EPA reeonnendations specified in the Cuideline.

5. The fndustrial Source Conplex models (hereafter ISC) '

have been deened refined rnodels by EPA for application to

industrial complexes. The fSC nodels consist of a short tetm1

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EodeL (rscsr) and a long tern nodel (rscLT). r,ong teln rnoders,

such as rsclT, are only appropriate for sarcul.ating anblent

concentrations for averaging periods of months to a year. short

term urodels, such as rscsT, can be used for averaging tines fron

one hour up to a year. (Hereafter my connents referring to rsc apply to both fScST and fSCLT, unless othelrrise speclfied- ) I'he

rse model is appropriate for sinulating the emisslons of a variety of industriaL air enissions. These would, inctude

ernissions from rree standing stac)<s and vents; stacks and vents

which are infruenced by the aerodynarnic effects of nearby

structures; enissions fron area sourcee, such as storage piles or evaporative emissions frorn open tanlcr; line sources, such as roaduays; and volume souree,s, such as rarge openings in buildings

from which enissions emanate. The noder is approprlate for
siruulating the anbient inpacts of relativery inert pollutants,

such as ethyrene oxide, vhich do not undergo rapid chemical

transfonratlon in the atnosphere. ?he rnoder will ealcurate the

anbient concentrations at a number of user-specified rrreceptor',

locations.

a- For simulating a stack-type 6ource, rsc requires
tbe input of the location, emission rate, physical stack height,

stack gas exit verocity, stack inside diameter, and stack gas
temperature. rf the source l"s affected by the aerodynanic

effects of buildings then inputs would alao lnclude information

about the building dinensions.

b. The ISC nodel also requires meteorological data as
input- These data include the wind speed, wind direclion, P.61

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tenperatrrre, stablllty class and nixing height. The

meteorological data nust be representative of the geographic area

being modeled to be accepted for a refined regulatory

application.

c. The fSC nodel has gone through a nunber of

perfotrorance evaluation studieE, as outlined above. The following

are several references of evaluation studies invoLving fSC:

(1) Bowers, J, F., and A, J. Anderson, 1991. A n

Evaluation Study for the Industrial Source Conplex (fSC)

Disperslon ltodel, EPA PubLication No. EPA-AiO/{-81.-002. U. S.

Environmental Protection Agency, Research Triangle Park, .Nc.

(2, Bowers, J. F.; A. J. Anderson, and W. R .

Hargraves, 1982. Tests of the fndustrial Source Conplex (ISC)

Dispersion Model at the Armco Hiddle-town, Ohio Steel UiIL, EpA

Publication No, EPA-450/4-82-006. U. S. Envj.ronmental Protection

Agency, Research Triangle Park, NC.

(3) Seire, J. S., and L. L. Schulman, 1981.

Evaluation of the BLP and rsc Models with sF5 Tracer Data and soz

Measurements at Aluninum Reduction Plants. Air Pollution Control

Association Specia,Ity Conferenee on Dispersion Modeling for

Complex Sources, St. LouiE, MO.

(4) Schulman, L. L. and S. R. Hanna, 1986.

Evaluation of Downwash Modifications to the Industrial Source

CompLex Model. Journal of the Air Pollution Control Association,

36:258-264

.

d. fn uy experlence of conductlng and reviening air

quality modeling analyses, I have found that of the EPA approvedI

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models, the ISC nodel is the most widely used nodel for

determining the aubient concentrations of emissions from

industrlal sources. This is prinarily due to its abillty to

simulate alnost any t)T)e of lndustrial conflgnrratl.on and its

status aa a refined model under EPA giuidelines. EPA considers it

appropriate for use without undergoing case by case perforruance

evaluation.

6. When EPA has a refined nodeL appropriate for a specific

type of applicati,on, sueh as the ISC nodel, the nodeling results,

based on the appropriate input data, are generally preferred by

EPA over ambient rnonitoring data for detenuinl-ng emission

lirnitations for both new and existing sources. Nornrally, EPA

does not accept aonitoring data as the sole basis for deternining

an emission liroitation. When a refined nodel is available, EPA

generally considers the nodel results alone (including background

concentrations) sufficient for deteraining anbient concentrations

of enissions from industrial sources and setting appropriate

emission Lirnitations.

a. Monitoring data suffers frora a nunber of

limitations. One of the prinary linitations is that any given

nonitor can only neasure what is happening at the location where

the rnonitsor is physically located and at the tine it is

operating. In order to adequately detect the naxinun inpact of

any particular source, many nonitors would have to be run gver a

nurnber of years. A monitoring progran designed to adeguately

detect a naximum concentratlon and to adequately characterize the

concentration field would be very expensive. A nurnber of years P.a

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of data qrould be necessar-y to collect enough sanples to cover aII

possible rneteorological situations in conbination vlth the

different operating conditions of the facility. A monLtoring

progran slth only one or tso monitors or of a ve!')t short duration

would be inadequate to e,nsure that naximun anbient inpacts would

be detected.

b, The usual intent of conducting an arabient inpact

analysis of an air pollution source is to deteraine if the

emissions are likely to affect hunan health or affect the

environrnent. The arnbient coneentrations are compared against

health or environmental affects data. Rather than helping to

resolve a problem, a prolonged ambient monitoring study allons

continued air guatity degradation, which in turn affects the

health or environrnental guality which vas to be protected. For a

new source being proposed, it is inpossible to measure its

impacts, since it is not yet builtc. The rnethod of analysis preferred by EPA for

determining the ambient concentrations resultlng from emissions

into the atmosphere of industrial sources, including toxic air

emissions, is ruodeling. As discussed above, before EPA

determines a model', such as ISC, to be a refined model,

appropriate for general use. the rnodel undergoes rigorous

evaluation and is determined to yield accurate estimates of the

ambient air concentratlonE resulting fron emission sources under

a variety of eonditione. With a model, the Bource can be

simulated under the full range of its potential operating and

eruission conditions, rather than being linited to the specific P.9

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operating conditions occurring durlng the period of a linitea

nonitorlng study. Tlre uodel can also yleLd anbient concentration

data at any nunber of receptor loeationsr'rather than only at the

linited nunber of locations where a tronltor is physically

located. Also, iD air quality uodel provldes the only practical

nethod of estirnating the anbient lnpacts of a new source. A

model provides flexibility in an analysis and ean be :ltn

relatively quickly, at relativety little expense.

d. Modeling also allops source contributions to a

particular anbient concentration to be ascertained- If two

sources each eroit tbe sane pollutant, it is impossible to tell

from an anbl,ent meaEureDent of the specific pollutant, the

relative contributions to the measured arnbient concentration,

unless there is sone unigue surrogiate being ernitted fron one of

the facilities. Also, there is the uncertainty of whether a

heretofore unknown source of the pollutant of concern has

contributed to the measurernent. Hodeling, allows the impact of

each source to be calculated separately and in combination.

e. The use of rnonitoring data also Pre-suPposes that

there are acceptable and reliable nronitoring techniques available

for the pollutant^of interest. fn the past, this has generally

been the case. EPA has established acceptable and reliable

methods of rneasuring a nurnber of pollutants whtcn were regulated

under the Clean Air Act. Recently, howcver, the issue of toxic

air contarninants has arisen. Ambient heasurement techniques,

which can adeguately and accurately detect a speciflc toxic air

contarninant, are not necessarily available. The transport and11-05-1995 2 42AM FROM P. 11

1 dispersion of buoyant or neutral plumes of gaseous pollutants,

2 which are relatively inert in the atmosphere, is the same,

3 regardless of the specific chemical constituents of the gas.

4 Therefore, modeling provides a useful technique for detecting

5 levels of pollutants in the air if reliable ambient measurement

6 techniques are not available.

7 f. EPA does recognize the usefulness of ambient

8 measurements for information on background concentrations,

9 provided reliable monitoring techniques are available. EPA does

10 not recommend, however, that ambient measurements be used as the

11 sole basis of setting emission limitations or determining the

12 ambient concentrations resulting from emissions from an

13 industrial source. These should be based on an appropriate

14 modeling analysis.

15 I declare under penalty of perjury that the foregoing is

16 true and correct.

17 DATED: 

# #o**V~mbfr-** ..JO 

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### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 1



### ORAL ARGUMENT NOT YET SCHEDULED

UNITED STATES COURT OF APPEALS

FOR THE DISTRICT OF COLUMBIA CIRCUIT

NATIONAL ENVIRONMENTAL

DEVELOPMENT ASSOCIATION'S

CLEAN AIR PROJECT,



### Petitioner,



### v.

UNITED STATES ENVIRONMENTAL

PROTECT ION AGENCY,



### Respondent. 

### )

Docket No. 10-1252

(and consolidated cases)

DECLARATION OF ROGER W

. BRODE

1. My name is Roger W

. Brode. I hold B.S. and M

. S. degrees in Atmospheric Sciences and I

am currently assigned as a physical scientist in the Air Quality Modeling Group within the

Air Quality Assessment Division of the Office of Air and Radiation ' s Office of Air Quality

Planning and Standards at th e U .S. Environmen tal Protection Agency ("EPA"), where my

1

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 2

responsibilities include t he development

, evaluation and applicatio n of air quali t y dispersion

models and the development of gu id ance associated wi t h application of such models in

support of EPA regulations governing the Prevention o f Significan t Deteriora t i on

("PSD")_permit t ing program. I ha v e bee n involved in the dev e lopment

, evaluation

, testing,

and documentation o f the American Me t eorological Society EPA Regu l atory Model

("AERMOD " ) throughout its history. I currently serve as co-chair of the AMS / EP A

Regulatory Model Improvement Committee (AERM I C) consisting of atmospheric scienti s ts

and dispersion model experts overseeing the further t echn i cal development of the model

, and

as co-chair of the AERMOD Implementation Workgroup consisting of EPA Reg i onal Office

and State dispers i on mode l ers whose charge has bee n to indentify and as s ess potential i s sues

with implementation of the A E RMOD model as EPA ' s preferred model under Appendix W

of Part 51 of the Code ofF ederal Regulat i ons.

2. The revised primary nat i onal ambient air quality standard for oxides of sulfur ( " S02

NAAQS " ) requires that the three year ave r age ofthe annual 99 111 percentile of the daily

maximum 1-hour average concentrations ofS02 be less than or equal to 75 parts per billion.

I n add i t i on, owners and operators of a new major stationary source or a major source

undergoing a major modification l ocated in areas not designated " nonattainment " for the S02

NAAQS must obtain a PSD permit

, and to do so must demonstrate (among other things) that

the emissions increases f rom the new or modified source will not cause or contribute to a

violation ofthe revi s ed S02 NAAQS. E xisting a i r quality models

, including AERMOD

, are

readily capab l e of accurately predicting whether the r e vised primary S02 N AAQS is a t tained

and whether individual s ources cause or contribu t e t o a violation of the S02 NAAQS.

Specifically

, dispersion models that are used to demonstrate compliance with the S02 (and

2

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 3

other) NAAQS, including under PSD permitting programs, use sequentia l hourly

meteorological data as the basis for estimating ambient concentration levels. These data are

combined with other inputs (chiefly source emission information, background emissions, and

receptor information) to predict transport and dispersion of emitted pollutant plumes. Since

the key varying inputs to these models are input on an hourly basis

, all applications of these

models under the guidance in Appendix W (40 CFR Part 51) are predicated upon the models '

ability to predict hourly amb i ent concentrations. These models thus generate one-hour air

quality distributions from which the three year average of the annual 99th percentile of daily

maximum 1-hour average concentration of S02 can be readily calculated or otherwise

reasonably approximated

.

3

. As part ofthe basis for EPA adopting the AERMOD model as the preferred model for nearfield applications in the Guideline on Air Quality Models, Appendix W to 40 CFR Part 51,

the performance ofthe AERMOD model was extensive l y evaluated based on a total of 17

fie ld study data bases (AERMOD: Latest Features and Evaluation Results. EPA

- 454 / R-03-

003. U.S. Environmental Protection Agency, Research Triangle Park (2003), portions of

which are attached to this affidavit) ("EPA 2003")

. The scope of the model evaluations

conducted for AERMOD far exceeds the scope of evaluations conducted on any other model

that has been adopted in Appendix W to Part 51. These evaluations demonstrate the overall

good performance of the AERMOD model based on techn i ca ll y sound model evaluation

procedures, and also illustrate the significant advancement in the science of dispersion

modeling represented by the AERMOD model as compared to other models that have been

used in the past. In particular, adoption of the AERMOD model has significantly reduced the

3

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 4

potential for overestimation of ambient impacts from elevated sources in complex terrain

compared to other-models.

4. Some of the field studies used to evaluate AERMOD model performance involved ambient

sampling of S02 for a period of one year or more at several (typically about 1 0) monitors

sited around operating power plants. Other field s tudies involved sampling of controlled

releases of non-reactive tracers, typically SF6, generally over a shorter duration than the

operational studies, but with more robust sam pling to facilitate more detailed diagnosis of

model performance. Al t hough the long-term field studies associated with operating power

plants included assessments of 3-hour, 24-hour and even annual average impacts from the

model, evaluation re sults for 1-hour averages were routinely included for all of the field

studies. As shown in Tables 2 and 3 of EPA 2003

, modeling and monitored results for 1-

hour averages are in exce ll en t correlation in t he se studies, with the ratio of predicted to

observed performance approaching 1: 1 in most instances. Thus, in my opinion

, the

per forma nce of the AERMOD model for estima ting 1-hour ambient concentrations is welldocumented and the form of the new 1-hour S02 standard raises no questions or concerns

regarding the appropriateness of AERMOD.

5. The S02 NAAQS Coalition states that the revised S02 NAAQS is a "p robabilistic " s tandard

and asserts that this makes modeling more problematic, especially as compared to the

previous " determinis tic" standard. (C oalition p. 5.) The terms "probabilistic" and

"deter minis t ic" do no t have an ordinarily understood meaning in this context, but it appears

that the assertion is t hat predictive models like AERMOD are not suitable for a standard

which includes a percentile-based form (where the relevant comparison is to a percentile of

air quality from an air quality distribution), a s opposed to an expected exceedance form

4

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 5

(whereby a standard may exceeded on a given number of days and compliance is assessed

based on air quality on the designated day once the allowed exceedance days are removed

from the distribution )

. I know of no reason that AERMOD and other similar types of models

is suitable for one type of form and not the other. As just state d in paragraph 2, the models

readily generate air quality distribu t ions from which either percentiles (for th e revised S02

NAAQS, the 99 1 h percentile) or exceeding days can be determined. In fact, the percentile

form of th e 1 -hour S02 NAAQS is a more "s tab le" metric than a sta nd ard based on the 1 51

-

highest or 2"d

- high est concentrations

, since the potential impact of "outliers" in the

distribution is mitigated, especially when the multi-year average aspect of the S02 NAAQS

is accounted for.

6. Both the S02 NAAQS Coalition and their affiant Mr. Paine raise a number of points

r egarding the issue of whether allowable or actual source emissions should be modeled,

stating that use of allowable emissions overstates sources' impacts. See, e.g. Paine Decl. at 1[**~** 11-14. This issue is independent of th e predictive accuracy of AERMOD or other models.

7. EPA's rules and guidance provide significant flexibility in th e choice of which models to use

in determining if sources cause of contribute to NAAQS violations for purposes ofPSD

permitting. EPA's rules specify that "where an air quality model s pec ified in Appendix W of

th i s part

.. . is inappropriate, the model may be modified or another model substituted" with

written approval from EPA

. 40 C

. F .R. §51. 166 (1)(2). The rules t herefore allow flexibility

,
subject to appropriate requirements, for alternative modeling techniques to be applied on a

case-by-case basis subject to appro v al by appropriate reviewing authority.

8. The declaration of Michael E. Long voices concerns regarding the use of the AERMOD

dispersion model to support implementation of the 1-hour S02 standard

, and asserts that

5

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 6

"AERMOD significantly over predic ts the ac tual one -hou r ambien t concentrations in our

a r ea when the available information is used in the model as directed by EPA." Long Decl. at**~** 8. This assertion is based on a comparison bf model -pre dicted ambient concentrations to

amb i ent 

### 802 concentrations reported for 2008 at local EPA monitoring stations in the

vicinity of the ArcelorMitta l facilities b ei ng mode le d. Mr. Long reports that the "AERMOD

model predicted one -ho u r concentrations that were higher than the monitored va l ues 90% of

th e time and the predicted values were as much as 373,131 t i mes higher than the actual

monitored values." I d. Lackin g any additional details re ga rdin g the model-to

- monitor

comparisons cited by Mr. Long, t he response here is necessarily limited to a genera l

d iscuss ion of issues involved in such comparisons. A number of factors can affect the

comparison of a modeled concentration with a monitored concentration, including th e

accuracy of the emission rate and other source characteristics in put to the model, the

representativeness of the meteorological data inpu t to the model, and th e influence of lo cal

geographical features and land us e characteristics on the tr anspo rt and dispersion of the

plume. Another key factor that affects comparisons of modeled vs. monito red

concentrations, paired in time and space, i s the potential error or uncertainty in the wind

direction input to the model for that hour since the wind direction w ill determ i ne the

transpo rt direction of the plume

. Slight errors in the trans port wind direction may account for

significant dif ferences in modeled vs. monitored concentrations for a sp ecific hour,

especially for elevated plumes under stable atmospheric conditions where the latera l spread

of the plume can be very limi ted for relatively long transport di s tanc es, and errors of a few

degrees in wind direction can be the difference in the plume directly impacting the moni to r

for a particular hour or the plume missing the moni to r completely. In such cases, a factor of

6

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 7

3 73,131 differe n ce between modeled and monitored concen t rations could easily be

attributable to error or uncertainty in the wind direction

. Note that wind d i rections reported

from routine meteorological monitor i ng stat i ons l ocated at airports, the most common source

of meteoro l ogical data used in air qua li ty modeling applications, are reported to the nearest

1 0 degrees. In addition, the comparison may reflect issues related to use of a ll owab l e versus

actual em i ssions, which is irrelevant for purposes of determining whether the AERMOD

mode l itself is biased.

9

. The declaration of Robert J

. Paine addresses practical issues in applying the AERMOD

model that allegedly arise due to the form of the 1 -hour S02 standard, as well as concerns

regarding the conservatism of the assumptions on source emissions based on Appendix W

guidance in relation to the 1- hou r S02 standard. Responses to these issues are summar i zed

below, numbered according to Mr. Paine's declarat i on, with some responses applying to

multip l e comments:

(a)

Paine Decl.**~** 9. : The AERMOD model "does not yet provide results that allow permit

applicants to follow EPA ' s guidance for determining whether they comply with the 1 -hour S02

NAAQS because of the un i que statistica l form of that NAAQS

. "

Paine Dec l. 

### 11 10.: "The form ofthe 1-hour S02 NAAQS requires the applicable guideline

dispersion model to compute the highest 1-hour concentration for each day at each modeled

receptor point, and to keep track of this dai l y 1-hour maximum concentration s t atistic for each of

the 365 days for each year modeled independently at each location modeled

.

7

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 8

Paine De cl.**~** 1 1. : " In the case for which a cumulative modeling analysis is required, this same

procedure must be applied to the combined contributions of th e in d ividua l source being

permitted, nearby sources and reg ion a l background."

Response: As stated in paragraph 2 above

, all of these metrics are readily obtainable from model

outputs

. A l though th e existing version of AERMOD does not contain an algorithm f rom which

the se metrics emerge au to matically as model outputs

, this does not change the result that all of

these metrics are obtainable. In fact, we are aware that Mr

. Paine, along with other priv a te sector

parties, developed po st -processing tools to compute the 1

- hour S02 design va l ue based on the

fo rm of th e revised S02 NAAQS utiliz ing model output options available at the time.

(b)

Paine Decl. 

### 'II 11. : "Furtherm ore , E PA in most cases requires a conservatively high regional

background concentration to be added for all hours modeled, rather than the actual va l ues

measured during each hour of the modeling simulation

. "

Response: EPA issued guidance on a range of issues re l ated to the new 1-hour S02 standard on

August 23,2010, including a recommendation that the overall hi g hes t 1 -ho ur monitored S02

concentration from a representative monitor could be u sed to account for the monitored

background component i n a cumulative impact assessment "without further j us tification. " We

recognize that use of the overall highest 1-hour monitored value may entail a degree of

conservatism tha t could prevent a source from demonstrat i ng comp li ance with NAAQS;

however

, tha t conservatism forms the basis for allowing the approach to be used without further

justification. The Augus t 23 memorandum further stated that " Additional refinements to this

'first t i er ' approach based on some level of t emporal pairing of modeled and monitored values

8

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 9

may be considered on a case-by-case basis, subject to approval by the r eviewing authority, with

adequate justificat i on and documentation." However, we also note that Appendix W explicitly

makes "no attempt" to "comprehensively define" the criteria involved in determining which

nearby sources to include in an analysis "owing to both the uniqueness of each modeling

situation and the large number of variables involved i n identifying nea r by sources." See

Appendix W section 8.2.3.b.

(c)

Paine Decl. 1! 12.: "Following EPA's regulatory requirements for PSD modeling, the modeled

predictions of hourly concentrations of a probabilistic standard such as the 99th percentile daily

maximum hourly S02 concentrations produced by a single source for which a permit is sought

can be much higher than concentrations that a ctually occur in the ambient air."

Response: As noted in paragraph 6 above, the issue of allowable versus actual emissions is

independent to the question of the accuracy of AERMOD or other models. Also

, as stated in

paragraph 5 abo Y e, there is no reason that AERMOD (or other similar models) is not equally

accurate in predicting percentile air quality distributions or expected exceedances on a given day

.

The underlying data which are input to the model generate air quality d i str i butions which are

equally suitable for either type of form.

(d)

Paine Decl.**~** 12. : " Modeling of peak S02 emissions as if they occur continuously is a

distortion of reality and will overestimate the ambient air concentrations. This is especially true

for 1-hour averages, since the variation of emissions for such a short averaging period is

9

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 10

potentially much higher than that for th e other S02 NAAQS averaging periods. This makes th e

assumption of constant peak emissions a critical issue for this new standard."

Response: The purpo se of dispers i on modeling in the context of th e PSD permitting program is

to demonstrate t hat the p r oposed new or modified emissions will not cause or contribute to

vio la t ions of t he standard if the permit i s granted. This is inh erently a predictive exercise since it

entails an assessment of proposed future emissions. EPA's guidance for conducting s uch

analyses is dictated by and consistent with that purpose. Mr. Paine's stateme n t that 1 -hour

averages are more var ia b l e than longer averaging periods again does not relate to potential model

bias a nd in any case makes a sweeping generalization for situations that differ case-by-case. The

statement that peak S02 emissions should not be modeled is a restatement 

### of the dispute as to

use of allowable or actual emissions, and does not relate to the issue of model bias.

(e)

Paine Decl.

, 13. : "The model overprediction t endency is even more likely to be a prob lem in a

cumulative impact analysis because numerous sources (i.e.

, the source being permitted and

potentially thousands of other nearby sou rces) are all modeled at peak em is sions at all t imes and

added to a regional background l eve l of S02

... leading to unrealistic predictions that the 1-hour

S02 NAAQS will be exceeded."

Response: As no te d, the issue of allowable versus actual emissions is independent ofthe issue of

models' predictive accuracy. However, EPA's August 23,2010 clarification memo regarding

the applicability of A ppe ndix W guidance for the 1-hour S02 NAAQS cautioned "against the

literal and uncritical app lication of very prescriptive procedures for identifying which

background sources should be included in the mode led emission inventory for NAAQS

10

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 11

compliance demonstrations, including those described in Chapter C

, Section IV. C.l of the draft

New Source Review Wo r kshop Manual (EPA

, 1990)

, noting [again] that Appendix W

emphasizes the importan ce of professional judgment in this process." One motivation for that

caution was a concern that application of such procedures could lead to an overly conservative

result by including too many background sources in th e cumulative impact assessment. As noted

elsewhere, Section 8.2.3.b of Appendix W suggests that "the number of such sources is expected

to be small excep t in unusual situations. "

(f)

Paine Decl.**~** 13. : "Moreover, since th e nearby so urc es will be modeled individually (but their

emissions are already accounted for in t he regional monitoring), there will inevitably be doublecounting of the background impacts between the component s of the "nearby sources " and the

"regiona l background", especially for the common situation of the s tate requiring a single peak

regional b ackground value to be used for all modeled hours. "

Response: As noted in several responses above, there are many a pplication-specific factors that

need to be considered in determining how to conduct an adequate assessment of cumulative

impacts

, accounting for contributions from nearb y backgroun-d sources explicitly in the mode l as

well as a monitored contribution

, while avoiding or minimizing the potential for double-counting

of modeled and monitored impacts.

(g)

Paine Decl.**~** 14. : "T he distribution of total peak daily emissions over the three-yea r period of

2000-2002 [from major S02 sources in central North Dako ta ] was found to overpredict the

second-highest monitored 24-hour concentrations by roughly a factor of2 because the emissions

11

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 12

on average are l ower than peak va l ues assumed in the modeling

. For t h e probabilistic 1

- hour

standard

. . . and for closer receptors

, the overprediction ratio would likely be even higher than

for a 24

- hour average, caus i ng extens i ve areas of fictitious mode l ed NAAQS v i olations

. "

Response: The first statement in this comment merely confirms what was i ndicated in an earlier

response, namely that modeled impacts based on maximum allowable emissions should not be

expected to accurately predict ambient monitored concentrations in most cases, since monitored

concentrations can only reflect i mpacts from actual emissions. Overprediction by a factor of 2

does not suggest a significant degree of conservatism given that modeled emissions reflected

peak emissions. No rationale is offered to support the assertion that the overprediction ratio

would likely be even higher for the 1 -h our sta n dard, and we see no reason to expect that

necessarily to be t he case.

(h)

Paine Decl., 1 4. : "Based on my experience with modeling t he 1-hou r NAAQS for nitrogen

d i oxide

- a NAAQS that is

. similar in form to the 1-hour S02 NAAQS

- this overprediction rat i o

could approach a factor of 10 in areas with numerous sources mode l ed together."

Response: Although the form of the 1-hour N02 standard is very similar to the form of t he 1-

hour S02 standard, the ro l e ofNOx chemis t ry in modeling ambient N02 impacts associated with

NOx emissions makes 

### it difficult to draw comparisons between the two standards in terms of the

potentia l for the model to overestimate ambient impacts as compared to mon i tored

concentrations. The comment does no t indicate what assumptions were made in the N02

modeling analyses regarding the conversion ofNO emissions to ambient N02. An overly

conservative assump t ion in relation to that conversion could introduce a significant bias i n the

12

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 13

modeled concentrations relative to monitored concentrations ofN02 that would have no

relevance to modeling 1-hour 802 impac ts.

(i)

Paine Decl.**~** 15. : "If a cumulative modeling assessment shows violations of the NAAQS, then

the PSD permit applicant can still obtain a permit for its source by s howing that the proposed

source does not contribute significantly to the modeled viol ation

. EPA, however, has not yet

defined a procedure for determining whether a proposed source that conducts a cumulative

modeling analysis and finds modeled violations due to other sou rces is by itself causing or

contributing to these predic ted (and possibly false) 1-hour 802 NAAQS violations. This "sa fety

valve" thus does not yet exist for applicants tryi ng to demonstrate that their proposed 802-

emitting sources will n ot cause or contribute to any modeled violations of the

. l -hour 802

NAAQS."

Response: Recognizing the importance of the significant contribution t est within the PSD

permitting program , EPA recommended an interim Significant Impact Level (SIL) in its August

23 guidance memorandum regarding the 1-hour 802 NAAQS. This interim SIL provides the

"s afety valve" that may allow a permit applicant to obtain a permit in cases where the cumulative

impact assessment shows modeled vio lations of the 1-hour 802 NAAQ8

, if it can be

demonstrated that the proposed em is sion increa ses do not contribute sig nificantly to those

modeled violations, paired in time and space. Although the form of the 1-hour 802 standard

may complicate the "bookkeeping " needed to make such a demonstrat ion, the principle of the

significant contribution tes t based on the SIL has not changed under the 1-hour 802 NAAQS.

13

### Case: 10-1252 Document: 1288492 Filed: 01/18/2011 Page: 14

Pursuant to 28 U.S.C. § 1746, and under penalty of perjury, I declare the foregoing is

true and correct to the best of my knowledge.

Date Roger W. Brode

14

### Camille Sears 502 W. Lomita Ave., Ojai, CA 93023

Tel: (805) 646-2588 e-mail: camille.marie@sbcglobal.net



### ambient air locations, should n June 28, 2012

EPA Docket Center 1301 Constitution Ave., NW., Room 3334 Washington DC 20004

Re: Docket#: EPA-HQ-OAR-2010-1059
Comments on USEPA’s Guidance for One-Hour SO 2 

### NAAQS SIP Submissions

Thank you for the opportunity to comment on USEPA’s guidance for one-hour SO 2 

### NAAQS SIP submissions. In the 9/22/2011 public draft of th eir guidance, USEPA summarizes their planned program elements as follows:

In addition to this guidance document, EPA is also planning a rulemaking to address some of the 1-hour SO 2 

### NAAQS implementation program elements. These elements include: (1) establishi ng that compliance with the 1-hour SO 2 

### NAAQS is appropriately based on the re sults of both air quality modeling and monitoring; (2) establishing the modeling requirements necessary to determine compliance with the 1-hour SO 2 

### NAAQS; (3) establishing the minimum scope of analysis required to demonstrate atta inment and maintenance of the 1-hour SO 2 

### NAAQS to comply with th e SIP requirements in C AA section 110(a)(1); (4) establishing a reasonable time period fo r sources to comply with any new emissions limitations states need to esta blish in the 110(a)(1) SIPs to demonstrate attainment and maintenance of the 1-hour SO 2 

### NAAQS; (5) to set an attainment date for areas designated as unclassifiable ; and (6) establishing the criteria for redesignating areas from “unc lassifiable” to “attainment.” 1



### This document goes on to say:

EPA will also propose a rulemaking that would codify the hybrid modeling and monitoring implementation approach in or der to ensure compliance with the 1- hour SO 2 

### NAAQS in a timely manner. 2



### In summary, I believe that air dispersion modeling should be the preferred method for determining one-hour SO 2 

### impacts from existing sources. Monitoring should be used only in specific cases to supplement modeled impacts, and the monitored data, which cannot cover all ot be given more weight than the modeled concentrations. In

1 USEPA, Guidance for One-Hour SO 2 NAAQS SIP Submissions, Public Review Draft, September 22, 2011, pp. iiiiv. ( http://www.epa.gov/airquality/sulfurdioxide/pdfs/DraftSO2Guidance_9-22-11.pdf )

2 Id., p. iv.Docket#: EPA-HQ-OAR-2010-1059 June 28, 2012 Page - 2



### essence, USEPA’s proposed hybrid modeling and monitoring implementation approach should be heavily weighted towards modeling.

Air dispersion modeling has been used for decad es to assess ambient air impacts from proposed and existing sources, and for SO 2 

### NAAQS SIP purposes, monitori ng alone (or a program based predominantly on monitoring) is not a viable alternative. I recen tly submitted a subset of these
comments to USEPA’s 10 th 

### Conference on Air Quality Modeling docket.

I specialize in atmospheric di spersion modeling, which uses regulatory-approved computer programs to estimate chemical concentrations in the air and deposition fluxes to the ground. In the past 30 years I have prepared over 1,000 ai r dispersion modeling analyses. I hold B.S. (1978) and M.S. (1980) degrees in Atmospheric Science from the University of California at Davis. A copy of my curri culum vitae is attached.

My comments on this docket concentrate on the issue of modeling vs. monitoring for verifying compliance with the one-hour SO 2 

### NAAQS (attainment determinati ons). My comments are in response to USEPA’s “key que stions” presented in their Implementation of the 2010 Primary 1-

Hour SO 2 

### NAAQS: Draft White Paper for Discussion . I address key questions a. and b. on monitoring and key questions a., b., c., and d. on modeling.

Monitoring key questions:

a. Are the conceptual monitoring networks de scribed above sufficient to determine whether ambient SO 2 

### levels meet the NAAQS and are protective of public health without the need for additional modeling? If not, then what enhancements should be made to them? In what situations should meteorological data co llection also be required?

b. What is an appropriate number of monitors to site around a source to assess air quality?

I am providing a combined response to the above questions.

I do not believe that it is feasib le for monitoring alone to veri fy compliance with the one-hour
SO 2 

### NAAQS. A suitable monitoring program w ould require many monitors and data would need to be collected for at least several year s. The number of required monitors would be prohibitively expensive and th e duration of the monitoring program, while compounding the expense, also delays the implementation needed to protect public health from any unhealthy SO 2


### exposures.Docket#: EPA-HQ-OAR-2010-1059 June 28, 2012 Page - 3



### The question of modeling or monitoring was discussed in a California Proposition 65 enforcement declaration by John Vimont, wh en he was USEPA’s Region IX Regional Meteorologist:

Monitoring data suffers from a numb er of limitations. One of the primary limitations is that any given monitor can only measure what is happening at the location where the monitor is physically located and at the time it is operating. In order to adequately detect the maximum impact of any particular source, many monitors would have to be run over a number of years. A monitoring program designed to adequately detect a maxi mum concentration and to adequately characterize the concentration field would be very expensive. A number of years of data would be necessa ry to collect enough samp les to cover all possible meteorological situations in combinati on with the different operating conditions of the facility. A monitoring program with only one or two monitors or of a very short duration would be inadequate to ensure that maximum ambient impacts would be detected. 3



### Mr. Vimont also declared:

EPA does recognize the usefulness of am bient measurements for information on background concentrations, pr ovided reliable monitoring techniques are available. EPA does not recommend, however, that ambient measurements be used as the sole basis of setting emission limitations or determining the ambient concentrations resulting from emissions from an industrial source. These should be based on an appropriate modeling analysis. 4



### I agree with Mr. Vimont on the disadvantages of relying on air monitoring to verify compliance with ambient air quality st andards. This sentiment is also e xpressed by the State of California, in their Air Toxics Hot Spots Health Risk Assessment (HRA) guidelines:

Pollutant concentrations are required in HRA calculations to estimate the potential cancer risk or hazard indices associated with the emissions of any given facility. Although monitoring of a pollutant provide s excellent characterization of its concentrations, it is ti me consuming, costly, and typically limited to a few receptor locations and snapshots in tim e. Air dispersion modeling has the advantage of being relatively inexpensive and is less time consuming, provided that all the model inputs are available. In addition, air dispersion modeling provides greater flexibility for placement of receptors, assessment of individual

3 Vimont, John, People of the State of California v. Santa Maria Chili, Declaration, November 30, 1990. (see attached file: Vimont-J ohn-Declaration.pdf)

4 Id.Docket#: EPA-HQ-OAR-2010-1059 June 28, 2012 Page - 4



### and cumulative source contributions, and characterization of concentration over greater spatial extents. 5



### In addition, it is not always po ssible to place monitors where maximum project or cumulative impacts may be occurring. I have first-hand expe rience with the problem of siting monitors to ensure that maximum project impacts are being measured. While I was an employee with the Santa Barbara County Air Pollution Control Distri ct, I sited over 30 pre- and post-construction air quality PSD monitoring syst ems. These monitors were required by permit conditions for various oil and gas processing facilities, and severa l monitors were to be sited for each project. Using air dispersion modeling, we determined wh ere the peak project impacts were likely to occur and then attempted to place the air qual ity monitoring systems at those locations. In virtually every case, it was not possible to place th e air quality monitor in the desired location. Impediments to siting the monitors where we wanted to place them included: power or communication constraints, lack of security, deni al of landowner permission, lack of access, and terrain and vegetation restrictions. In other words, it’s one thing to have an adequate number of monitors; it’s quite another thing to place them where they are needed.

Part of the problem is that there are relatively few existing monitors that can be used for SO 2 

### NAAQS attainment determinations. There are not nearly enough SO 2 

### monitors in place to determine attainment status of the existing major SO 2 

### emission sources. Moreover, very few, if any, of these monitors are “well-placed” for m easuring the maximum ambient air impacts from these existing SO 2 

### sources. This situation dictates that in virtually every instance, a monitoring program needs to be started from scratch, or air dispersion modeling must be used as the method for determining SO 2 

### ambient air concentrations a nd resulting attainment status.

The lack of existing major source-specific SO 2 

### monitoring is partly due to a failure of State air agencies requiring pre-and post-c onstruction air quality monitoring. In the past few years I have reviewed and commented on major SO 2 

### emission source PSD permit applications in Texas, Louisiana, Oklahoma, Nevada, Kentucky, North Carolina, South Carolina, Missouri, Kansas, South Dakota, Illinois, and Arkans as. With the exception of Nevada, the State air agencies have not required pre- or post-cons truction air quality monitoring, even though the PSD significant monitoring concentrations were exc eeded. This is the norm for th ese major sources, and it is one of the key reasons that there is a paucity of ambient air quality monitoring data that could be used to help determine attainment status surround ing these facilities. It is self-serving if a facility that could (should) ha ve been collecting am bient air quality data now argues that SO 2 

### NAAQS attainment determinations must be based on monitoring, not modeling.

5 California Office of Environmental H ealth Hazard Assessment, Air Toxics Hot Spots Program Risk Assessment Guidelines: The Air Toxics Hot Spot s Program Guidance Manual for Preparation of Health Risk Assessments, August 2003, p. 4-1. ( http://www.oehha.org/air/hot_spots/pdf/HRAguidefinal.pdf )Docket#: EPA-HQ-OAR-2010-1059 June 28, 2012 Page - 5



### This same issue applies to pre-construction monitoring for meteorological data. On many
occasions I have commented that States should require major source facilities, as part of their PSD permit analysis, to collect site-specific me teorological data rather than rely on National Weather Service (NWS) airport da ta. On every occasion, my comments were disregarded, even though the PSD significant monitoring concentrati ons were exceeded for the proposed project. The State’s response and comment denial followe d a common theme, summarized as follows: site-specific meteorological data monitoring is unnecessary for modeling purposes and that NWS airport data are appropriate for permit applic ation analyses. Alt hough it’s water under the bridge, site-specific data could have been collected during thes e application processes without causing time delays to permit issuance.

USEPA asked the question “ In what situations should meteor ological data collection also be required?” I believe the time has passed when these da ta could or should have been collected. Of course it would be ideal to have additional site-specific meteorological data for modeling major SO 2 

### emissions sources. But such a monitoring system will take at least two years to implement, and then the modeling will still have to be performed. The data collection itself will take a minimum of one year. It will take at le ast another year for developing the data collection protocol, review and approval of the protocol, siting of the syst em, installation, and afterwards post-processing of the data for modeling. Starting a site-specific meteor ological data collection
effort from scratch contributes to an unreasonabl e delay of the measures that may be needed to protect ambient air from any excessive SO 2 

### exposures.

While I feel that site-specific meteorological data are preferable to NWS airport data, USEPA’s AERMINUTE program allows significant improve ments to the NWS data in that calms and variable wind hours that were previously unusab le by AERMOD can now be recaptured. In lieu of requiring new site-specific data collection efforts, modeling of SO 2 

### emissions for NAAQS SIP submissions should be performed using NWS data prepared with AERMET, in conjunction with
AERMINUTE. The use of one-minute ASOS data should be a requirement, not a recommendation. If available high -quality site-specific meteorologi cal data already exist, then I believe they should be used in preference to NWS airport data.

Based on my experience, site-specific meteorologi cal data tends to resu lt in higher modeled impacts than NWS airport data, even when th e NWS data is processed with AERMINUTE and one-minute ASOS data. For example, I modeled the Homer City, PA power station with three different meteorological data sets: One year of site-specific data from the Manor monitoring station; 2006 through 2010 NWS data from J ohnstown PA, including one-minute ASOS data processed with AERMINUTE (KJST); and 2006 through 2010 NWS data from Pittsburgh PA, including one-minute ASOS data processed with AERMINUTE (KAGC). All three data setsDocket#: EPA-HQ-OAR-2010-1059 June 28, 2012 Page - 6



### conditions are included in the used Pittsburgh upper air soundings. The peak receptor grid ambient air impacts from AERMOD modeling using Manor site -specific data were about tw ice as high as the KJST or KAGC results. And even at specific receptor locations, such as Homer City High School, the Manor site-specific data resu lted in significantly higher im pacts than the NWS/AERMINUTE
data sets.

In other words, using available NWS airport data, processed with AERMINUTE, will not likely over-predict modeled impacts, as suggested by some stakeholders. Moreover, these data have the advantage of being readily available on NCDC data DVDs for years 2007 through 2011, thus meeting The Guideline on Air Quality Modeli ng requirements of at least five years of consecutive data from the most recent, readily available five-year period. 6



### Modeling key questions:

a. Should some criteria (e.g., the PWEI concept) be used to identify priority sources to be modeled in an area where there is no nearby monitor?

I do not believe that a population weighted emi ssions index (PWEI) should be used to identify priority sources. The NAAQS, by definition, apply to ambient air, or "... that portion of the atmosphere, external to buildings, to which the general public has access." 7 

### Ambient air is the defining criteria, and it is not based on the number of people who are exposed, but whether anyone could have access to given locations. Th is includes waterways and unpopulated areas of all sorts, so long as someone in the public has access.

b. How should the modeling be performed – i.e., what changes to the March 24, 2011 guidance should be made, such as the use of size cut-offs and use of actual emissions?

Some stakeholders have suggested that one-hour SO 2 

### modeling analyses used for nonattainment SIP modeling should use actual emissions, and not th e potential to emit. I understand that using allowable emissions may result in higher impacts than the facility’s actual emissions. I have modeled many coal-fired EGUs where I analyzed both allowable and actual emissions obtained from USEPA’s Clean Air Markets Database (CAMD). The facility permitted emissions are often, though not always, greater than the reported actual emissions. This is because the permitted allowable emissions are often based on 30-day averaging periods and peak hourly emission limits were not set by the State agency in question. Also, startup, shutdown, and upset CAMD that may represent quite high actual emission rates.

6 USEPA, Revision to the Guideline on Air Quality Models: Adoption of a Preferred Ge neral Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions , Appendix W to 40 CFR Part 51, November 9, 2005. ( http://www.epa.gov/ttn/scram/guidance/guide/appw_05.pdf )

7 40 CFR Part 50.1 (e) ( http://ecfr.gpoaccess.gov/cgi/t/text/textidx?c=ecfr&rgn=div5&view=text&node=40:2.0.1.1.1&idno=40#40:2.0.1.1.1.0.1.1 )Docket#: EPA-HQ-OAR-2010-1059 June 28, 2012 Page - 7



### If actual emissions are used for nonattainment SIP modeling, a condition mu st be added to the facility’s permit requiring that emissions must not be greater than the le vel used in the modeling analysis. In other words, a fac ility that wants to use actual emissions in their modeling analysis must agree to an enforceable permit condition li miting their emissions, by unit, to that quantity modeled. Also, actual emissions cannot be modele d using full load stack parameters. Stack gas exit velocity and temperature wi ll be reduced under less than full load conditions, affecting plume rise and resulting modeled impacts. Any AERMOD modeling using actual emission levels must use corresponding actual stack gas ex it velocity and temperature. I suggest that USEPA should develop a method for calculating st ack gas exit velocity and temperature as a function of load, for use in cases where these data are not directly measured and reported.

I believe that any emission limits based on actual operating conditions must be rather straightforward and enforceable. For example, the actual emission rates could be based on the maximum hourly emissions, by stack, for the late st calendar year (or perhaps the maximum for the past three years). Maximum actual emission s could also be for shorter time periods (by season, for example), but emission limits by portion of the year may be more difficult to enforce, or the facility may not wish to be restricted by this condition. And while it is possible to model hour-by-hour actual emissions (using HOU REMIS in AERMOD) coupled with contemporaneous meteorological data, this an alysis does not ensure that the one-hour SO 2 

### NAAQS will be protected in the future. This is because combinations of meteorology and facility emissions that result in peak impacts are virtually unenforceable.

I believe that USEPA should be ve ry careful in considering emissi on rate cut-off levels. Without modeling, it is very difficult to determine the comb ined effects that emission rate, stack height, source-to-receptor distance and elevation di fferences, building downwash, background air quality, and plume rise will have on ambient air concentrations and NAAQS compliance. Obviously not every source will require modeling, but any cut-off criteria should consider all parameters that affect air concen tration, not simply emission rate.

c. Are there situations where m odeling is preferable to monitoring? If so, then what are these situations? Should EPA require modeli ng in certain situations, or is monitoring alone always a sufficient option for areas of concern?

As discussed above, modeling is preferable to monitoring for determining ambient air concentrations and for verifyi ng compliance with the one-hour SO 2 

### NAAQS. I cannot envision a feasible air monitoring network that would verify compliance for a major SO 2 

### emission source – too many monitors would be needed and the de lay in attainment demonstration and resulting
controls would be unacceptably long.Docket#: EPA-HQ-OAR-2010-1059 June 28, 2012 Page - 8



### I think it is beneficial to cons ider how California’s Air Toxics Hot Spots program, also known as AB 2588, determined ambient air concentrations of air toxics. This program required thousands
of facilities in California to quantify emissions of scores of hazardous air pollutants, when virtually no inventory of these pollutants previo usly existed. AB 2588 also required at least 1,000 facilities state-wide to pr epare health risk assessments, which are based on ambient air
concentrations of the air toxics in question. In all in stances, these facilities used air modeling as the basis for determining ambient air concentrat ions. This is based not only on State of California guidance (see the Air Toxics Hot Spots program citation in the air monitoring comments above), but on the practicality of actually quantifying air concentrations in a
reasonable fashion.

I believe that the AB 2588 program required as much or more modeling work than will be
needed for the one-hour SO 2 

### NAAQS SIP determinations. For example, in Santa Barbara County, where I was the Air Toxics Program Coor dinator, we prepared air dispersion modeling analyses for up to 50 facilities per year. Many of these facilities were very complicated and involved numerous toxic air po llutants. Plus, we calculate d excess cancer risk and noncarcinogenic health effects from i nhalation and all other pathways of exposure. In other words, I think State air agencies should be able to handl e the effort required in modeling the major SO 2 

### emission sources within their jurisdiction.

Some stakeholders have expressed concern that AERMOD will over-predict air impacts, compared to monitoring results. While this ma y be true in some circumstances, e.g., at one location at a given time, the true value in modeling is the ability to calculate air concentrations at many more places and under many physical conditi ons that cannot be hand led by air monitoring. On the other hand, there are likely many s ituations where AERMOD underpredicts air concentrations compared to monitoring data.

USEPA should rely on the detailed AERMOD eval uations that were performed during the model development phase. I agr ee with Roger Brode’s 10 th 

### Modeling Conference presentation, where he concluded: “AERMOD model performance ha s been extensively evaluated and shown to provide generally unbiased estimates of 1-hr SO 2 

### concentrations across a wide range of
scenarios.” 8

8 Roger Brode, USEPA/OAQPS, AERMOD Evaluations Under the 1-hour NO 2 and SO 2 NAAQS, 10 th Conference on Air Quality Modeling. ( http://www.epa.gov/ttn/scram/10thmodconf/presentations/2-8- Brode_10thMC_AERMOD_Evals_1hr-NO2-SO2_NAAQS_Final_3-25.pdf )Docket#: EPA-HQ-OAR-2010-1059 June 28, 2012 Page - 9



### I believe that the concerns about AERMOD over-pre dicting air concentrati ons are, on the whole,
without merit. At the 2012 RSL Modelers’ Workshop, George Bridgers and Roger Brode presented a summary of AERMOD’s performanc e evaluation results. They document that AERMOD provided better model predictions than ISCST3, ISC-Prime, and CTDMPLUS. In addition, they point out that the average ratio of predicted to observed one-hour and three-hour robust highest concentration values acro ss all field studies for AERMOD was 0.995. 9 

### This is clearly an unbiased estimate of AERMOD’s predictive performance.

It is also evident that most of the large SO 2 

### emission sources have tall stacks, which were rigorously evaluated during AERMOD’s developmen t process. From USEPA’s Compendium of Reports from the Peer review Process for AERMOD:

Concerning the model evaluation, we reiter ate that AERMOD has been evaluated against 10 substantial data bases, including: 1) four data sets for tall stack buoyant plumes in flat terrain (Kincaid SO2, Kincaid SF6, Baldwin, and Clifty Creek), 2) four data sets for tall stacks in complex terrain or near elevated terrain (Lovett, Martins Creek, Tracy, and Westvaco), 3) a buoyant elevated release in an urban environment (Indianapolis), and 4) a nonbuoyant surface release (Prairie Grass). We agree that more evaluation would be desirable (as always) especially for downwash conditions, urban sources, and surface releases. However, there is a key question to the AERMOD development process: Has there been enough evaluation already to justify replaci ng ISC3 by AERMOD? AERMIC believes that there has been. 10



### Thus, any argument that AERMOD is not applicable to tall stack emission sources should be
dismissed based on the studies used for deve loping AERMOD. In particular, AERMOD has been extensively evaluated for power plant emissions:

It is worth noting in this regard that all of the AERMOD evaluation data bases (except for Prairie Grass) involved tall, non-downwa shed, highly buoyant power plant stacks (the shortest stack in th e group was 84 meters in Indianapolis). 11



### AERMOD’s evaluation process ultim ately comprised 17 separate data sets. I believe that any concerns from stakeholders that AERMOD over-pre dicts power plant impact s, or over-predicts impacts from other source types represented in the evaluation databases, should be dismissed.

9 George Bridgers and Roger Brode, USEPA/OAQPS, Challenges in Modeling Compliance for New NAAQS: 1- hour NO 2 & SO 2 and PM 2.5 , 2012 RSL Modelers’ Workshop. ( http://www.cleanairinfo.com/regionalstatelocalmodelingworkshop/archive/2012/presentations/Tues/3- 1_2012RSL_ModelingChallenges_Bridges.pdf )

10 USEPA OAQPS, Compendium of Reports from the Peer review Process for AERMOD, February 2002, pdf page 38/69. ( http://www.epa.gov/scram001/7thconf/aermod/dockrpt.pdf )

11 Id., pdf page 49/69.Docket#: EPA-HQ-OAR-2010-1059 June 28, 2012 Page - 10



### I would also add that AERMOD’s evaluation an alyses included a num ber of site-specific meteorological data sets that incorporate low wind speed conditions. For example, the Tracy evaluation included meteorological data with wind speeds as low as 0.39 meter/second (m/s); the Westvaco evaluation included wind speed s as low as 0.31 m/s; the Kincaid SO 2 

### evaluation included wind speeds as low as 0.37 m/s; and the Lovett evaluation included wind speeds as low
as 0.30 m/s. 12 

### Concerns raised by stakeholders rega rding AERMOD’s ability to model low wind speed conditions seem to neglect the da ta used in actual AERMOD evaluations.

Some stakeholders are concerned that AERMOD is inaccurate in areas with extreme topography, such as complex river valleys and steep hillside s. This concern has already been addressed by USEPA in their response to the New Jersey De partment of Environmen tal Protection (NJDEP) section 126 petition for SO 2 

### emissions from the Portland Genera ting Station. In their review of NJDEP’s petition, USEPA found that AERMOD is the most appropriate model for determining air impacts in the complex terrain and comple x wind fields surrounding the Portland facility. 13


### USEPA also recognizes that “the performan ce of the AERMOD model for estimating impacts associated with tall stacks in complex terrain settings has been exte nsively evaluated and documented in peer-review journals... and has cons istently been shown to perform better than competing models.” 14



### Air monitoring of SO 2 

### is not a feasible alternative to modeling for steep hillsides and other complex terrain conditions. Proper air quality m onitor siting is extremely difficult in these settings, and any siting would depend on prior air dispersion modeling in the first place.

While I have used CALPUFF to model emissions in complex river valleys, I was able to do so only because there were multiple site-specific me teorological monitors to provide the needed data to develop the CALMET wind fields. For fa cilities where adequate meteorological data exist to run CALPUFF, I believe this is a possible alternative to running AERMOD. Otherwise, AERMOD should be used due to the problems asso ciated with siting and operating an adequate monitoring network in these complex terrain environments.

12 The AERMOD evaluations and modeled meteorological data are at: http://www.epa.gov/ttn/scram/dispersion_prefrec.htm

13 USEPA, Air Quality Modeling Technical Support Document: NJ 126 Petition of September 17, 2010, April 2011, p. 12 of 63. ( http://www.epa.gov/ttn/scram/reports /EPA-HQ-OAR-2011-0081-0026.pdf )

14 Id., p.11 of 63.Docket#: EPA-HQ-OAR-2010-1059 June 28, 2012 Page - 11



### d. Are there situations where m onitoring is preferable to modeli ng? If so, then what are these situations? Should EPA require monito ring in certain situations, or is modeling alone always a sufficient option for areas of concern?

As discussed above, I believe that modeling alone is sufficient for verifying compliance with the
one-hour SO 2 

### NAAQS. If monitoring is used, as in USEPA’s proposed hybrid modeling and monitoring approach, it should be only as a supplement to modeling and the modeling and monitoring results should be given equal weight.

I think it is important to remember that all NO 2 

### , PM 2.5 

### , and SO 2 

### NAAQS and PSD increment permit application analyses are performed w ith air dispersion modeling, such as running AERMOD in a manner consistent with the Guideline on Air Quality Models. In order to ensure consistency in how air impacts are determin ed, both existing sources and newly permitted sources should be assessed using the same meth ods. From the Guideline on Air Quality Models:

The Guideline is used by EPA, States, and indus try to prepare and review new source permits and State Implementation Plan revisions. The Guideline is intended to ensure consistent air qualit y analyses for activities regulated at 40 CFR 51.112, 51.117, 51.150, 51.160, 51.166, and 52.21. 15



### Allowing existing sources to use monitoring (assuming adequate mon itoring even exists or could exist), results in a lower standard of compliance verification than that being used for new permit applicants.

Concluding Remarks

Using AERMOD for one-hour SO 2 

### NAAQS SIP submissions is reasonable and reliable. AERMOD has undergone rigorous model evaluations, was subjected to numerous peer-reviewed studies, and has already been used in hundreds, if not thousands, of air quality impact analyses of major emission sources. USEP A must not exchange their ex isting guideline model for an ambient air monitoring program whic h will never be able to verify compliance with the one-hour
SO 2 

### NAAQS.

Based on my experience with both modeling and monitoring, I believe that air modeling, using AERMOD, is the best available method for verifying compliance with the one-hour SO 2 

### NAAQS. I suggest that USEPA’s proposed hybr id modeling and monitoring implementation

15 USEPA, Revision to the Guideline on Air Quality Models: Adoption of a Preferred General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions , Appendix W to 40 CFR Part 51, November 9, 2005, Section II. ( http://www.epa.gov/ttn/scram/guidance/guide/appw_05.pdf )Docket#: EPA-HQ-OAR-2010-1059 June 28, 2012 Page

- 12

approach for one-hour S02 NAAQS SIP submissions should be heavily weighted towards modeling.

Thank you for the opportunity to submit these comments on USEP A s guidance for one-hour

S02 NAAQS SIP submissions.

Sincerely,

Camille Sears

### Camille Marie Sears 502 W. Lomita Ave., Ojai, CA 93023

Tel: (805) 646

- 2588 e

- mail: cam ille.marie@sbcglobal.net

Summary I have over 30 years of regulatory and private

- sector experience in air quality impact analyses, health risk assessments, meteorological monitoring, and geographic information systems. I specialize in litigation support; I have successfully provided testimony in numerous cases, both as an individual consultant and as pa rt of a team of experts.

E ducation

**•** M.S., Atmospheric Science, University of California, Davis, 1980.

**•** B.S., Atmospheric Science, Uni versity of California, Davis, 1978.

Air Dispersion Modeling

**•** I am experienced in applying many different air dispersion models , including programs still in the development phase. I have prepared well over 1,000 air dispersion mod eling analyses requiring the use of on

- site or site

- specifi c meteorological data. T hese runs were made with the USEPA ISC, OCD, MESOPUFF, INPUFF, CALPUFF, ISC

- PRIME, AERMOD , COMPLEX

- I, MPTER, and other air dispersion models.

**•** I pr epared and submitted technical comments to the USEPA on beta

- testing versions of AERMOD; these comments are being addressed and will be incorporated into the model and instructions when it is ready for regulatory application.

**•** I am experienced in performing air dispersion modeling for virtually every emission source type imaginable

. I have modeled: Refineries and associated activities; Mobile sources, including cars, trains, airplanes, trucks, and ships; Power plants, incl udi ng natural gas and coal

- fired ; Smelting operations; Area sources, such as housing tracts, biocides from agricultural operations, landfills, highways, fugitive dust sources, airports, oil and gas seeps, and pond s; Volume sources, including fugitive em issions from buildings and diesel construction combustion emissions; Small sources, including dry cleaners, gas stations, surface coating operations, plating facilities, medical device manufacturers , coffee roasters, ethylene oxide sterilizers, degreasin g operations, foundries, and printing companies; Cooling towers and gas compressors ; Diatomaceous earth, rock and gravel plants, and other mining operations; Offshore oil platforms, drilling rigs, and processing activities; Onshore o il and gas expl oration, storage, proce ssing, and transpor t facilities; Fugitive dust emissions from roads, wind erosion, and farming activities; Radionuclide emissions from actual and potential releases.

**•** I have extensive experience in modeli ng plume depletion and deposition from air releases of particulate emissions.

**•** As a senior scientist , I developed the Santa Barbara County Air Pollution Control District (SBAPCD) protocol on air quality modeling. I developed exten sive modeling capabilities for the SBAPCD on VAX 8600 and Intel I

- 860 computer systems; I acted as systems analyst for the SBAPCD air quality modeling system; I served as director of air quality analyses for numerous major energy projects; I performed air quality impact analyses using inert and photochemical models, including EPA, ARB and private

- sector models; I performed technical review and evaluating air quality and wind field models; I developed software to prepare model inputs consistent with the SBAP CD protocol on air quality modeling for OCD, OCDCPM, MPTER, COMPLEX

- I/II and ISC.

**•** I p rovided detailed review and comments on the development of the Minerals Management Service OCD model. I d eveloped the technical requirements for andCamille Marie Sears, Page

- 2

supervised the development of the OCDCPM model, a hybrid of the OCD, COMPLEX

- I and MPTER models.

**•** I p repared the "Modeling Exposures of Hazardous Materials Released During Transportation Incidents" report for the Cali fornia Office of Environmental Health Hazard Assessment (OEHHA). This report examines and rates the ADAM, ALOHA, ARCHIE, CASRAM, DEGADIS, HGSYSTEM, SLAB, and TSCREEN models for transportation accident consequence analyses of a priority list of 50 chemical s chosen by OEHHA. The report includes a model selection guide for adequacy of assessing priority chemicals, averaging time capabilities, isopleth generating capabilities, model limitations and concerns, and model advantages.

**•** I a m experienced in assessing uncertainty in emission rate calculations, source release, and dispersion modeling. I have developed numerous probability distributions for input to Monte Carlo simulations, and I was a member of the External Advisory Group for the California EPA Air Toxics Hot Spots Program Risk Assessment Guidelines, Part IV, Technical Support Document for Exposure Assessment and Stochastic Analysis

.

Health Ri sk Assessment

**•** I have prepared more than 300 health risk ass essments of major air toxics sources

. These assessments were prepared for AB 2588 (the Air Toxics "Hot Spots" Information and Assessment Act of 1987), Proposition 65, and other exposure analysis activities. More than 120 of these exposure assessments wer e prepared for Propositi on 65 compliance verification in a litigation support setting.

**•** I r eviewed approximately 300 other health risk assessments of toxic air pollution sources in California . The regulatory programs in t his review include AB 2588, Proposition 65, the California Environmental Quality Act, and other exposure analysis activities. My c lients include the California Attorney General's Office, the Los Angeles County District Attorney's Office, the SBAPCD , the S outh Coast Air Quality Management District, numerous environmental and community groups, and several plaintiff law firms.

**•** I am e xperienced in assessing public health risk from continuous, intermittent, and accidental rele as es of toxic emissions. I am e xperienced in generating graphical presentations of risk results, and characterizing risks from carcinogenic and acute and chronic noncarcinogenic pollutants.

**•** I am e xperienced in communicating adver se health risks discovered through the Proposition 65 and AB 2588 processes. I have p resented risk assessment results in many public settings

-- to industry, media, and the affected public.

**•** For four years, I was the A ir Toxics Pr ogra m Coordinator for the SBAPCD. My d uties included: developing and managing the District air toxics program; supervising District staff assigned to the air toxics program; developing District air toxics rules, regulations, policies and procedures; mana gement of all District air toxics efforts, including AB 2588, Proposition 65, and federal activities; developing and tracking the SBAPCD air toxics budget.

**•** I have prepared numerous calculations of exposures from indoor air polluta nts. A few examples include: diesel PM 10 inside school buses, formaldehyde inside temporary school buildings, lead from disturbed paint, phenyl mercuric acetate from water

- based paints and drywall mud

, and tetrachloroethene from recently dry

- cleaned cloth es.

Litigation Support

**•** I have p repared numerous analyses in support of litigation, both in Federal and State Courts. I am e xperienced in preparing F.R.C.P. Rule 26(a)(2) expert r eports and providing deposition and trial testimon y (I have prepared eight Rule 26 reports) . Much of my work is focused on human dose and risk reconstruction resulting from multiple air emission sources (lifetime and specific events).Camille Marie Sears, Page

- 3

**•** I am e xperienced in preparing decla rations (many dozens) and providing expert testimony in depositions and trials (see my testimony history)

.

**•** I am experienced in providing support for legal staff. I have assisted in preparing numerous interrogatories, que stions for depositions, deposition reviews, various briefs and motions, and general consulting.

**•** Recent e xamples of my work include : DTSC v. Interstate Non

- Ferrous; United States District Court, Eastern Dist rict of California (2002). In this case I perfor med air dispersion modeling, downwind soil deposition calculations

, and resultant soil concentrations of dioxins (TCDD TEQ) from historical fires at a smelting facility. I prepared several Rule 26 Reports in my role of assisting the California Attorney General’s Office in trying this matter. Akee v. Dow et al.; United States District Court, District of Hawaii (2003

- 2004). In this case I performed air dispersion modeling used to qua ntify air concentrations and reconstruct intake, dose, excess cancer risk, and noncancer chronic hazard indices resulting from soil fumigation activities on the island of Oahu, Hawaii. I modeled 319 separate AREAPOLY pineapple fields for the following che micals: DBCP, EDB, 1,3

- trichloropropene, 1,2

- dichloropropane, and epichlorohydrin. I calculated chemical flux rates and modeled the emissions from these fumigants for years 1946 through 2001 (56 years) for 34 test plaintiffs and 97 distinct home, school, and work addresses. I prepared a Rule 26 Expert Report, successfully defended against Daubert challenges, and testified in trial. Lawrence O’Connor v. Boeing North America, Inc., United States District Court, Central District of California, Western Divis ion (2004

- 2005). In this case I performed air dispersion modeling, quantified air concentrations, and reconstructed individual intake, dose, and excess cancer risks resulting from approximately 150 air toxics sources in Los Angeles and Ventura Counties, California. I prepared these analyses for years 1950 through 2000 (51 years) for 173 plaintiffs and 741 distinct home, school, and work addresses. I prepared several Rule 26 Reports, and the case settled on the eve of trial in September, 2005

. Defendant s did not attempt a Daubert challenge of my work.

**•** I have prepared hundreds of individual and region

- wide health risk assessments in support of litigation. These analyses include specific sub

- tasks, including: calculating emission rates, choosing proper meteorological data inputs, performing air dispersion modeling, and quantifying intake, dose, excess cancer risk, and acute/chronic noncancer health effects.

**•** I have prepared over 120 exposure assessments fo r Proposition 65 litigation support

. In these analyses, my tasks include: reviewing AB 2588 risk assessments and other documents to assist in verifying compliance with Proposition 65; preparing exposure assessments consistent with Proposition 65 Regulati ons for carcinogens and reproductive toxicants; using a geographic information system (Atlas GIS) to prepare exposure maps that display areas of required warnings; calculating the number of residents and workers exposed to levels of risk requiring warnings (using the GIS); preparing declarations, providing staff support, and other expert services as required. I have also r eviewed scores of other assessments for verifying compliance with Proposition 65. My proposition 65 litigation c lients include the Cali fornia Attorney General's Office, the Los Angeles County District Attorney's Office, As You Sow, California Community Health Advocates, Center for Environmental Health, California Earth Corps, Communities for a Better Environment, Environmental Defense Fun d, Environmental Law Foundation, and People United for a Better Oakland.

Geographic Information Systems

**•** ArcGIS : I am e xperienced in preparing presentation and tes timony maps using ArcView versions 3 through 9.3 . I d eveloped m ethods to convert AutoCAD DXF files to ArcView polygon theme shape files for use in map overlays.Camille Marie Sears, Page

- 4

**•** I have created many presentation maps with ArcView using MrSID DOQQ and other aerial photos as a base and then overlaying exposure r egions. This provides a detailed view (down to the house level) of w here air concentrations and heal th risks are projected to occur.

**•** Using ArcView, I have created numerous presentations using USGS Topographic maps (as TIFF files) as the base on to which exposure regions are overlaid

.

**•** MapInfo for Windows: I p repared numerous presentation maps including exposure isopleths, streets and highways, and sensitive r eceptors, labels . I d eveloped procedures for importing Surfer isopleths in AutoCAD DXF format as a layer into MapInfo.

**•** Atlas GIS : I am e xperienced in preparing presentation maps with both the Windows and DOS versions of Atlas GIS. In addition to preparing maps, I use Atla s GIS to aggregate census data (at the block group level) within exposure isopleths to determine the number of individuals living and w orking within exposure zones. I am also e xperienced in geocoding large numbers of addresses and performing statistical

a nalyses of exposed populations.

**•** I am experienced in preparing large

- scale graphical displays, both in hard

- copy and for PowerPoint presentations. These displays are used in trial testimony, public meetings, and other lit igation support.

**•** I developed a Fortran program to modify AutoCAD DXF files , including batch

- mode

coo rdinate shifting for aligning overlays to different base maps

. Ozone and Long

- Range Transport

**•** I d evelop ed emission reduction strategies and identified appropriate offset sources to mitigate project emissions liability. For VOC offsets, I d eveloped and implemented procedures to account for reactivity of organic compound species for ozone impact mitigation. I wrote Fortran programs and developed a chemical database to calculate ozone formation potential using hydroxyl radical rate constants and an alkane/non

alkane reactive organic compound method

.

**•** I p rovided technical support to th e Joint Interagency Modeling Study and South Central Coast Cooperative Aerometric Monitoring Program. With the SBAPCD, I p rovided technical comments on analyses performed with the EKM A, AIRSHED, and PARIS models. I was responsible for developing emission s inventory for input into regional air quality planning models.

**•** I was the p roject manager for the Santa Barbara County Air Quality Attainment Plan Envir onmental Impact Report (EIR). My d uties included: preparing initial study; preparation and release of the EIR Notice of Preparation; conducting public scoping hearings to obtain comments on the initial study; managing contractor efforts to prepare the draft EIR.

**•** I modified, tested, and compiled the Fortr an code to the MESOPUFF model ( the precursor to CALPUFF) to incorporate critical dividing streamline height algorithms

. The model was then applied as part of a PSD analysis for a large copper

- smelting facility

.

**•** I am experienced i n developing and analyzing wind fields for use in long

- range transport and dispersion modeling.

**•** I have run CALPUFF numerous times. I use CALPUFF to assess visibility effects and both near

- field and mesoscale air concentrations fr om various emission sources, including power plants.

Emission Rate Calculation s

**•** I d eveloped methods to estimate and verify source emission rates using air pollution measurements collected downwind of the emitting facilit y, local meteorological data, and dispersion models. This technique is useful in determining whether reported source emission rates are reasonable, and based on monitored and modeled air concentrations, revised emission rates can be created

.Camille Marie Sears, Page

- 5

**•** I am e xperienced in developing emission inventories of hundreds of criteria and toxic air pollutant source s. I d eveloped procedures and programs for quantifying emissions from many air emission sources, including: landfills, diesel exhaust so urces, natural gas combustion activities , fugitive hydrocarbons from oil and gas facilities, dry cleaners, auto body shops, and ethylene oxide sterilizers

.

**•** I have calculated flux rates (and modeled air concentrations) from hundred s of biocide applications to agricultural fields

. Emission sources include aerial spraying, boom applications, and soil injection of fumigants

.

**•** I am experienced in calculating emission rates using emission factors, source

- test

re sults, mass

- balance equations, and other emission estimating techniques.

Software Development

**•** I am s killed in computer operation and programming, with an emphasis on Fortran 95.

**•** I am e xperienced with num erous USEPA dispersion models, modifying them for system

- specific input and output, and compiling the code for personal use and distribution. I own and am experienced in using the following Fortran compilers: Lahey Fortran 95, Lahey Fortran 90 DOS

- Extend ed; Lahey F77L

- EM32 DOS

Extended; M icrosoft Power Station 32

- bit DOS

- Extended; and Microsoft 16

- bit.

**•** I c onfigured and operated an Intel I

- 860 based workstation for the SBAPC D toxics program. I c reated control files and recoded pro grams to run dispersion models and risk assessments in the 64

- bit I

- 860 environment (using Portland Group Fortran).

**•** Using Microsoft Fortran PowerStation , I wrote programs to extract terrain elevations from both 10

- meter and 30

- met er USGS DEM files

. Using a file of discrete x,y coordinates, these programs extract elevations within a user

- chosen distance for each x,y pair. The code I wrote can be run in steps or batch mode, allowing numerous DEM files to be processed at once.

**•** I have written many hundreds of utilities to facilitate data processing, entry, and quality assurance. These utility programs are a “tool chest” from which I can draw upon to expedite my work.

**•** While at the SB APCD, I designed the ACE2588 model

- the first public domain multi

source, multi

- pathway, multi

- pol lutant risk assessment model. I co

- d eveloped the structure of the ACE2588 input and output files, supervised the coding of the model, tested the model for q uality assurance, and for over 10 years I provided technical support to about 200 users of the model. I was r esponsible for updating the model each year and ensuring that it is consistent with California Air Pollution Control Officer’s Association ( CAPCOA ) Risk Assessment Guidelines.

**•** I d eveloped and coded the ISC2ACE and ACE2 programs for distribut ion by CAPCOA. These programs we re widely used in California for preparing AB 2588 and other program health risk assessments. ISC2ACE and ACE2 contain "compression" algorithms to reduce the hard drive and RAM requirement s compared to ISCST2/ACE2588. I also d eveloped ISC3ACE/ACE3 to incorporate the revised ISCST3 dispersion model requirements.

**•** I develo ped and coded the "HotSpot" system

- a series of Fortran programs to expedite the review of air toxics emissions data, to prepare air quality modeling and risk assessment inputs, and to prepare graphical risk presentations.

**•** I cust omized ACE2588 and developed a mapping s ystem for the SBAPCD. I modified the ACE2588 Fortran code to run on an Intel I

- 860 RISC workstation; I updated programs that allow SBAPCD staff to continue to use the "HotSpot" system

– a series of programs that s treamline preparing AB 2588 risk assessments; I developed a risk assessment mapping syste m based on MapInfo for Windows which linked the MapInfo mapping package to the "HotSpot" system

.

**•** I d eveloped software for electronic submitt al of all AB 2588 reporting requirements for the SBAPCD . As an update to the "HotSpot" system software, I created software that allows facilities to submit all AB 2588 reporting data, including that needed for risk prioritization, exposure assessment, and presentation mapping. The data submittedCamille Marie Sears, Page

- 6

by the facility is then reformatted to both ATDIF and ATEDS formats for transmittal to the California Air Resources Board.

**•** I d eveloped and coded Fortran programs for AB 2588 risk prioriti zation; both batch and interactive versions of the program were created. These programs we re used by several air pollution control districts in California.

Air Quality and Meteorological Monitoring

**•** I was r esponsible for the desi gn, review

, and evaluation of an offshore source tracer gas study

. This project used both inert tracer gas and a visible release to track the onshore trajectory and terrain impaction of offshore

- released buoyant plumes.

**•** I d evelop ed the technical requirements for the Santa Barbara County Air Quality/Meteor ological Monitoring Protocol. I d eveloped and implemented the protocol for siting pre

- and post

- construction air quality and meteorolo gical PSD monitoring systems. I d etermined the instrumentation requirements, and designed and sited over 30 such PSD monitoring systems. Meteorological parameters measured included ambient temperature, wind speed, wind direction, sigma

- theta (standard deviation of horizontal wind direction fluctua tions), sigma

- phi (standard deviation of vertical wind direction fluctuations), sigma

- v (standard deviation of horizontal wind speed fluctuations), and sigma

- w (standar d deviation of vertical wind spe ed fluctuations). A ir pollutants measured included PM 10 , SO 2 , NO, NO x , NO 2 , CO, O 3 , and H 2 S.

**•** I was r esponsible for data acquisition and quality assurance for an offshore meteorological monitoring station. Parameters measured included ambient temperature (and delta

- T), wind speed, win d direction, and sigma

- theta.

**•** In coordination with consultants performing air monitoring for verifying compliance with Proposition 65 a nd other regulatory programs, I w rote software to convert raw meteorological data to h ourly

- averaged values formatted for dispersion modeling input.

**•** Assisting the Ventura Unified School District, I collected air, soil, and surface samples and had them analyzed for chlorpyrifos contamination ( caused by spra y drift from a nearby citrus orchard ) . I also coordinated the analysis of the samples, and presented the results in a public meeting.

**•** Using summa canisters, I collected numerous VOC samples to characterize background and initial conditions for use in Santa Barbara County ozone attainment modeling. I also collected samples of air toxics (such as xylenes downwind of a medical device manufacturer) to assist in enforcement actions.

**•** For the California Attorney General’s Office, I purchased, calibrated, and operated a carbon monoxide monitoring system

. I measured and reported CO air concentrations resulting from numerous types of candles, gas appliances, and charcoal briquettes.

Support, Tra ining
, and Instruction

**•** For 10 years, I provided ACE2588 risk assessment model support for CAPCOA. My t asks include d : updating the ACE2588 risk assessment model Fortran code to increase user efficiency and to maintain consistency with the CAPCOA Risk Assessment Guidelines; modifying th e Fortran code to the EPA ISC model to interface with ACE2588; writing utility programs to assist ACE2588 users; updating toxicity data files to maintain consistency with the CAPCOA Risk Assessment G uidelines; developing the distribution and installation package for ACE2588 and associated programs; providing technical support for all users of ACE2588

.

**•** I i nstructed approximately 20 University Professors through the National Sc ience Foundation Faculty Enhancement Program. Instruction topics included: dispersion modeling, meteorological data, environmental fate analysis, toxicology of air pollutants, and air toxics risk assessment; professors were also trained on the use of the ISC2ACE dispersion model and the ACE2 exposure assessment model.

**•** I was the in structor of the Air Pollution and Toxic Chemicals course for the University of California, Santa Barbara, Extension certificate program in Hazardous Mat erials Management. Topics covered in this course include: detailed review of criteria andCamille Marie Sears, Page

- 7

noncriteria air pollutants; air toxics legislation and regulations; quantifying toxic air contaminant emissions; criteria and noncriteria pollutant monitoring; air quality modeling; health risk assessment procedures; health risk management; control/mitigating air pollutants; characteristics and modeling of spills and other short

term releases of air pollutants; acid deposition, precipitation and fog; indoor/occupatio nal air pollution; the effect of chlorofluorocarbons on the stratospheric ozone layer. I taught this course for five years.

**•** I have trained numerous regulatory staff on the mechanics of dispersion modeling, health risk assessments , emission rate calculations, and presentation mapping

. I provided detailed training to SBAPCD staff in using the HARP program, and in comparing and contrasting ACE2588 analyses to HARP.

**•** Through UCSB Extension, I taught a three

- d ay course on dispersion modeling, preparing health risk assessments, and presentation mapping with Atlas GIS and MapInfo

.

**•** I hold a lifetime California Community College Instructor Credential (Certificate No. 14571); Subject Matter Area: Physics

.

**•** I have presented numerous guest lectures

– at universities, public libraries, farm groups, and business organizations

. Indoor Air Quality

**•** I prepared mercury exposure assessments caused by applying indoor latex paints containing phenylmercuric acetate as a biocide

.

**•** Using a carbon monoxide monitor, I examined CO concentrations inside rooms of varying sizes and with a range of ventilation rates

. Indoor sources of CO emissions included gas appliances and candles. I also examined CO concentrations within parking garages.

**•** I calculated air concentrations of tetrachloroethene inside homes and cars from offgassing dry

- cleaned clothes

.

**•** I examined air concentrations of formaldehyde inside manufactured homes and school buildings. I also calculated formaldehyde exposures from carpet emissions within homes.

**•** I assessed lead air exposures and surface d eposition from deteriorating lead

- based paint applications within apartments

. I also calculated lead air concentrations and associated exposures resulting from milling of brass pipes and fittings.

**•** While employed by the SBAPCD, I assisted with exposure assessment and awareness activities f or Santa Barbara County high

- exposure radon areas

.

**•** I calculated BTEX air concentrations and health risks inside homes from leaking underground fuel tanks and resultant co ntaminated soil plumes. I also assessed indoor VOC exposures and remediation options with the AERIS model.

**•** I have assessed indoor air concentrations from numerous volatile organic compound sources, including printing operations, microprocessor manufacturing, and solvent degreasing activities.

**•** I calculated indoor emission flux rates and air concentrations of elemental mercury for plaintiff litigation support purposes. This analysis included an exposure re construction (home, school, workplace, outside, and other locations) for 16 plaintiffs who had collected spilled mercury in their village. The study required room volume calculations, air exchange rates, exposure history reconstruction, mercury quan tity a nd droplet size estimation , elemental mercury flux rate calculations (including decay with time), and resultant air concentration calculations. I calculated both peak acute (two

- hour) and 24

- hour average concentrations.

**•** I calcula ted emission rates of lead from disturbed paint surfaces. I then calculated indoor air concentrations of lead for plaintiff litigation support purposes.Camille Marie Sears, Page

- 8

P ublications

**•** To establish a legal record and to assist in environmental review, I prepared and submitted dozens of detailed comment letters to regulatory and decision

- making bodies

.

**•** I have contributed to over 100 Environmental Impact Statements/Reports and other technical documents required for regul atory decision

- making.

**•** I p repared two software review columns for the Journal of the Air and Waste Management Association

.

**•** Correlations of total, diffuse

, and direct solar radiation with the percentage of possible sunshine for Davis, California. Solar Energy, 27(4):357

- 360 (1981).

E mployment History

**•** Self

- Employed Air Quality Consultant 1992 to 20 1 2

**•** Santa Barbara County APCD , Senior Scientist 1988 to 1992

**•** URS Consultants , Senior Scientist 1987 to 1988

**•** Santa Barbara County APCD , Air Quality Engineer 1983 to 1987

**•** Dames and Moore , Meteorologist 1982 to 1983

**•** UC Davis, Research Associate 1980 to 1981

Testimony History

**•** P eople of the State of California v. McGhan Medical, Inc

. Deposi tion: Two dates: June

- July 1990

**•** People of the State of California v. San ta Maria Chili Deposi tion: Two dates: August 1990

**•** California Earth Corps v. Johnson Controls , Inc

. Deposition: October 26, 1995

**•** Larry Dale Anderson v. Pacific Gas & Electric Deposition: January 4, 1996 Arbitration: January 17, 1996

**•** Adams v. Shell Oil Company Deposition: July 3, 1996 Trial: August 21 , 1996 Trial: August 22 , 1996

**•** California Earth Corps v. Teledyne Battery Products Depositio n: January 17, 1997

**•** Marlene Hook v. Lockheed Martin Corporation Deposition: December 15, 1997

**•** Lawrence O’Connor v. Boeing North America, Inc

. Deposition: May 8, 1998

**•** Bristow v. Tri Cal Deposition: June 15, 1998

**•** Abeyta v. Pacific Refining Co

. Deposition: January 16, 1999 Arbitration: January 25, 1999

**•** Danny Aguayo v. Betz Laboratories , Inc

. Deposition: July 10, 2000 D eposition: July 11, 2000

**•** Marlene Hook v. Lockheed Martin Corporation Deposition: September 18, 2000 Deposition: September 19, 2000

**•** Tressa Haddad v. Texaco Deposition: March 9, 2001Camille Marie Sears, Page

- 9

**•** California DTSC v. Interstate Non

- Ferrous United States District Court, Eastern District of California, Case No. CV

- F

- 97 50160 OWW LJO Deposition: April 18, 2002

**•** Akee v. Dow et al. United States District Court, Distr ict of Hawaii

, Case No. CV 00 00382 BMK Deposition: April 16, 2003 Deposition: April 17, 2003 Deposition: January 7, 2004 Trial: January 17, 2004 Trial: January 20, 2004

**•** Center for Environmental Health v. Virginia Clean ers Superior Court of the State of California County of Alameda

, Case No. 2002 07 6091 Deposition: March 4, 2004

**•** Application for Certification for Small Power Plant Exemption

– Riverside Energy Resource Center. Docket No. 04

- SPPE

- 01. Evidentiary Hearing Testimony before the California Energy Resource Conservation And Development Commission : August 31 , 2004

**•** Lawrence O’Connor v. Boeing North America, Inc. United States District Court, Central Dist rict of California, Western Division. Case No. CV 97

- 1554 DT (RCx) Deposition: March 1, 2005 Deposition: March 2, 2005 Deposition: March 3, 2005 Deposition: March 15, 2005 Deposition: April 25, 2005

**•** Clemente Al varez, et al, v. Western Farm Service, Inc. Superior Court of the State of California County of Kern, Metropolitan Division. Case No. 250 621 AEW Deposition: April 11, 2005

**•** Gary June et al. v. Union Carbide Corporation & UME TCO Minerals Corporation United States District Court, District of Colorado, Case No. 04

- CV

- 00123 MSK

- MJW Deposition: January 9, 2007

**•** Alberto Achas Castillo, et al. v. Newmont Mining Corporation, et al. District Court, D enver County, Colorado, Case No. 01

- CV

- 4453 Deposition: February 19, 2007 Deposition: February 20, 2007 Arbitration : March 6, 2007 Arbitration : March 7, 2007

**•** Jacobs Farm/Del Cabo Inc. v. Western Farm S ervice, Inc. Superior Court of the State of California County of Santa Cruz, Case No. CV 157041 Deposition: May 8, 2008 Deposition: August 26, 2008 Trial: September 18, 2008 Trial: September 24, 2008Camille Marie Sears, Page

- 10

**•** Environmental Law Foundation et al. v. Laidlaw Transit Inc. et al. Superior Court of the State of California County of San Francisco, Case No. CGC

- 06

- 451832 Deposition: July 8, 2008

**•** Application of NRG Texas Power, LLC for State Air Quality Pe rmit No. 79188 and Prevention of Significant Deterioration Air Quality Permit PSD

- TX

- 1072. State Office of Administrative Hearings Docket No. 582

- 08

- 0861; TCEQ Docket No. 2007

- 1820

- AIR. Deposition: February 12, 2009 Hearing : February 24 , 2009

**•** Application of IPA Coleto Creek, LLC for State Air Quality Permit No. 83778 and Prevention of Significant Deterioration Air Quality Permit PSD

- TX

- 1118 and for Hazardous Air Pollutant Major Source [FCAA § 112(G)] P erm it HAP

- 14

. State Office of Administrative Hearings Docket No. 582

- 09

- 2045; TCEQ Docket No. 2009

- 0032

- AIR. Deposition: September 21, 2009 Hearing: October 16, 2009

**•** Application of Las Brisas Energy Center, LLC for State Air Quality Permit No. 85013 and Prevention of Significant Deterioration Air Quality Permit PSD

- TX

- 1138 and for Hazardous Air Pollutant Major Source [FCAA § 112(G)] P erm it HAP

- 48 and Plantwide Applicability Permit PAL41

. State Office of Administrativ e Hearings Docket No. 582

- 09

- 200 5; TCEQ Docket No. 2009

- 0033

- AIR. Deposition: October 9, 2009 Hearing: November 5, 2009 Hearing: November 6, 2009

**•** Abarca, Raul Valencia, et al. v. Merck & Co., Inc., et al. United States District Court, Eastern Distr ict of California, Case No. 1:07

- CV

- 00388

- OWW

- DLB Deposition: April 13, 2010 Daubert Hearing : October 7, 2010 Daubert Hearing : October 13, 2010 Daubert Hearing : October 14, 2010 Rule 706 Expert Hearing : December 2, 2010 Tria l : February 10, 201 1

**•** Commonwealth of Kentucky, Energy and Environment Cabinet, File No. DAQ

- 41109

- 048. Sierra Club, Kentucky Environmental Foundation, and Kentuckians for the Commonwealth v. Energy and Environment Cabinet, Division for Air Quality, and East Kentucky Power Cooperative, Inc. Deposition: August 31, 201011-05-1995 2 37AM FROM P 1



### ,



### DEC 03 1990 

# FILED

SUPERIOR COURT

sArnA E'.t,l""V'.RA 1 JOHN K. VAN DE KAMP, Attorney General of the state of California 2 ANDREA SHERIDAN ORDIN Chief Assistant Attorney General 3 THEODORA BERGER Assistant Attorney General 4 CRAIG C. THOMPSON
EDWARD G. WEIL 5 CLIFFORD RECHTSCHAFFEN Deputy Attorneys General
6 2101 Webster street Oakland, CA 94612

7 Telephone: (415) 464-0572

8 Attorneys for the people of the State of California

9 SUPERIOR COURT OF THE STATE OF CALIFORNIA

10 COUNTY OF SANTA BARBARA



### v.

Defendant. Plaintiffs,

ANTA MARIA CHILI, INC. Dec. 14, 1990 9:00 a.m. To Be Assigned DATE: TIME: Dept: No. SM 64010 (Case transferred to South County, 2/26/90)

DECLARATION OF JOHN C. VIMONT EOPLE OF THE STATE OF CALIFORNIA ex. el. JOHN K. VAN DE KAMP, Attorney eneral of the State of California, ) ) ) ) ) ) ) ) ) ) } ) )**If--~-~------------)** 12

16

IS 11

17 13

15 14

19 I, John C. Vimont, declare:

20 1. I am currently employed 

### by the United states

21 Environmental Protection Agency (hereafter "EPA"), Region IX

22 (hereafter the "Region" or "Regional Office!') as the Regional

23 Meteorologist. I have been employed 

### in this position since June

24 1987.

2S 

### a. As the Regional Meteorologist I serve as the

26 Region's expert on air quality**~odelin9,** meteorological

27 information and ambient air impact analyses. My position is11-05-1995 2 38AM FROM P 2

1 within the Air and Toxics Division of the Regional Office. I

2 provide support to that division; to the other divisions within

3 the Region, such as the Hazardous Waste Division; and to state

4 and local agencies vithin Region IX. One of the primary duties

5 of my position is to ensure that appropriate air quality modeling

6 techniques are used by this and other agencies when conducting

7 ambient air quality impact analyses.

8 b. There are a variety of "air quality models."

9 These include conceptual models, qualitative**dQ~criptions** of the

10 behavior of pollutants in the atmosphere; physical models, scaled

11 models of pollution sources and their surroundings studied in a

12 controlled environment, such as a wind tunnel; statistical

13 models, which encompass statistically based descriptions of

14 source-receptor relationships; and mathematical models, vhich are

15 mathematical representations of the physical processes which lead

16 to transport and dispersion of pollutants 

### in the atmosphere. The

17 focus of the remaining discussion is on mathematical models;

18 hereafter any reference to an air quality model is implicitly

19 meant to refer to a mathematical air quality model.

20 c. I perform, review and oversee air 

### quality modeling

21 for a variety of different sources and source types. These

22 include stationary sources vith emissions emanating from a stack,

23 inclUding stack sources with aerodynamic downwash induced by

24 nearby buildings; stationary sources with emissions emanating

25 from a broad area, commonly called area sources; mobile sources,

26 emissions from automobiles, trucks, busses, aircraft, etc.; and

27 urban and regional scale modeling, which encompasses modeling all11-05-19952:38AM FPOt·1 P 3

1 of the above processes together on the scale of an entire urban

2 area or over a number of urban areas together.

3 d. The pollutants modeled include both inert

4 pollutants, those which remain chemically stable for long periods

5 of time in the atmosphere, and chemically reactive pollutants,

6 those which undergo relatively rapid chemical transformation and

7 those which are not directly emitted, but rather form through a

8 series of chemical reactions within the atmosphere.

9 2. Previous to my employment at EPA, I worked from March

10 1982 to June 1987 as an Environmental Engineering Specialist in

11 the Air Quality Bureau of the State of New Mexico. My primary

12 responsibilities there were very similar to my current position

13 at EPA. I performed ambient impact analyses of various air

14 pollution sources and conducted engineering analyses of the

15 sources to determine emission characteristics. The primary focus

16 of the analyses was on inert pollutants from stationary sources.

17 a. From August 1978 to March 1982 I worked for the

18 Atmospheric Science Department at COlorado state University (CSU)

19 as a Research Assistant. I worked on a variety of basic

20 scientific research projects dealing with cloud physics. 

### My

21 primary area of research dealt with the uptake of acidic

22 pollutants in snow.

23 b. From November 1977 to August 1978 I worked as a

24 Phys'ical Science Aide for the Pacific Marine Environmental

25 Laboratory of the National oceanographic and Atmospheric

26 Administration. My duties there involved writing a

2711-05-1995 2:39AM FROM P.d

1 climatological summary of Puget Sound and analyzing the affects

2 of winds on oil spill transport in Puget sound.

J J. I received a Bachelor of Science Degree in Atmospheric

4 Sciences from the university of Washington in 1978 and a Master

5 of Science Degree in Atmospheric Science from Colorado State

6 University.

7 4. As the Regional MQteorologist, I routinely evaluate the

8 adequacy of air quality modeling on a technical basis and with

9 respect to its acceptability in the regulatory framework.

10 Acceptable air quality modeling and analysis procedures are

11 outlined in Ahe Guideline on Air Quality Models (Revised) (EPA

12 450/2-78-027R, 3uly 1986, Supplement A, JUly 1987) (hereafter the

13 "Guideline"). The Guideline was first pUblished in April 1978 to

14 satisfy the requirements of §320 of the 1977 amendments to the

15 Clean Air Act. The Guideline specifies appropriate models to use

16 and provides gUidance on their appropriate application. The

17 Guideline provides a common basis for estimating the air quality

18 concentrations used in assessing control strategies and

19 developing emission limits. The modeling techniques embodied in

20 the Guideline are subjected to public, scientific review in

21 accordance with §320 of the CAA.

22 a. EPA has four primary, on-going activities to

23 provide direct input for consistency in implementation and for

24 revisions to the Guideline. The first is a series of annual EPA

25 workshops conducted for the purpose of ensuring consistency and

26 providing clarification in the application of models. The second

27 activity, directed toward the improvement of modeling procedures,11-05-1995 239AM FROM P5

1. is the cooperative agreement that EPA has with the scientific

2 community represented by the American Meteorological Society.

3 This agreement provides scientific assessment of procedures and

4 proposed techniques and sponsors workshops on key technical

5 issues. The third activity is the solicitation and review of new

6 models from the technical and user community. In the March 27,

7 1980 Federal Register, a procedure was outlined for the submittal

8 to EPA of privately developed models. After extensive evaluation

9 and scientific review, these models, as well as those made

10 available by EPA, are considered for recognition in the

11 Guideline. The fourth activity is the extensive, on-going

12 research efforts by EPA and others in air quality and

13 meteorological modeling.

14 b. From the aforementioned process a number of models

15 were selected as being refined models, suitable for regulatory

16 application. Each refined model underwent intensive evaluation.

17 The evaluation exercises include statistical measures of model

18 performance in comparison with measured air quality data and,

19 Where possible, peer scientific reviews.

20 c. After a model has been selected as a refined model

21 for a particular type of application, EPA considers the model

22 appropriate for general use for that type of application without

23 undergoing case-by-case evaluation, provided that the application

24 follows the EPA recommendations specified in the Guideline.

25 5. The Industrial Source Complex models (hereafter ISC),

26 have been deemed refined models by EPA for application to

27 industrial complexes. The ISC models consist of a short term11-05-1995 2.d0AM P.6

1 model (ISCST) and a long term model (ISCLT). Long term models,

2 such as ISCLT, are only appropriate for calculating ambient

3 concentrations for averaging periods of months to a year. Short

4 term models, such as ISCST, can be used for averaging times frOm

5 one hour up to a year. (Hereafter my comments referring to ISC

6 apply to both ISCST and ISCLT, unless otherwise specified.) The

7 ISC model is appropriate for simUlating the emissions of a

8 variety of industrial air emissions. These would include

9 emissions from free standing stacks and vents; stacks and vents

10 which are influenced by the aerodynamic effects of nearby

11 structures; emissions from area sources, such as storage piles or

12 evaporative emissions from open tanks; line sources, such as

13 roadways; and volume sources, such as large openings in buildings

14 from which emissions emanate. The model is appropriate for

15 simulating the ambient impacts of relatively inert pollutants,

16 such as ethylene oxide, Which do not undergo rapid chemical

17 transformation in the atmosphere. The model will calculate the

18 ambient concentrations at a number of user-specified "receptor"

19 locations.

20 a. For simulating a stack-type source, ISC requires

21 the input of the location, emission rate, physical stack height,

22 stack gas exit velocity, stack inside diameter, and stack gas

23 temperature. If the source is affected by the aerodynamic

24 effects of buildings then inputs would also include information

25 about the building dimensions.

26 b. The ISC model also requires meteorological data as

27 input. These data include the wind speed, wind direction,11-05-1995 240AM FROM P. 7

1 temperature, stability class and mixing height. The

2 meteorological data must be representative of the geographic area

3 being modeled to be accepted for a refined regulatory

4 application.

5 c. The ISC model has gone through a number of

6 performance evaluation studies, as outlined above. The fOllowing

7 are several references of evaluation studies involving ISC:

8 (1) Bowers, 

### J. F., and A. 

### J. Anderson, 1981. An

9 Evaluation study for the Industrial Source Complex elSe)

10 Dispersion Model, EPA Publication No. EPA-450/4-81-002. U. S.

11 Environmental Protection Agency, Research Triangle Park, ·NC.

12 (2) Bowers, J.**F.~** A. J. Anderson, and W. R.

13 Hargraves, 1982. Tests of the Industrial Source Complex (lSC)

14 Dispersion Model at the Armco Middle-town, Ohio Steel Mill, EPA

15 Publication No. EPA-450/4-82-006. U. S. Environmental Protection

16 Agency, Research Triangle Park, NC.

17 (3) Scire, J. 5., and L. L. Schulman, 1981.

18 Evaluation or the BLP and ISC Models with SF 6 Tracer Data and S02

19 Measurements at Aluminum Reduction Plants. Air Pollution Control

20 Association Specialty Conference on Dispersion Modeling for

21 Complex Sources, St. Louis, MO.

22 (4) Schulman, L. L. and S. R. Hanna, 1986.

23 Evaluation of Downwash Modifications to the Industrial Source

24 Complex Model. Journal of the Air Pollution Control Association,

25 36:258-264.

26 d. In my experience of conducting and reviewing air

27 quality modeling analyses, I have found that of the EPA approved11-05-19952d0AM FROt1 P.8

1 models, the ISC model is the most widely used model for

2 determining the ambient concentrations of emissions from

3 industrial sources. This is primarily due to its ability to

4 simulate almost any type of industrial configuration and its

5 status as a refined model under EPA guidelines. EPA considers it

6 appropriate for use without undergoing case by case performance

7 evaluation.

S 6. When EPA has a refined model appropriate for a specific

9 type of application, such as the ISC model, the modeling results,

10 based on the appropriate input data, are generally preferred by

11 EPA over ambient monitoring data for determining emission

12 limitations for both new and existing sources. Normally, EPA

13 does not accept monitoring data as the sole basis for determining

14 an emission limitation. When a refined model is available, EPA

15 generally considers the model results alone (including background

16 concentrations) sufficient for determining ambient concentrations

17 of emissions from industrial sources and setting appropriate

18 emission limitations.

19 a. Monitoring data suffers from a number of

20 limitations. One of the primary limitations is that any given

21 monitor can only measure what is happening at the location where

22 the monitor is physically located and at the time it is

23 operating. In order to adequately detect the maximum impact of

24 any partiCUlar source, many monitors would have to be run over a

25 number of years. A monitoring program designed to adequately

26 detect a maximum concentration and to adequately characterize the

27 concentration field would be very expensive. A number of years

R.11-05-1995 2:d1AM FROt.' P.9

1 of data would be**naces~ary** to collect enough samples to cover all

2 possible meteorological situations in combination with the

3 different operating conditions of the facility. A monitoring

4 program with only one or two monitors or of a very short duration

5 would be inadequate to ensure that maximum ambient impacts would

6 be detected.

7 b. The usual intent of conducting an ambient impact

8 analysis of an air pollution source is to determine if the

9 emissions are likely to affect human health or affect the

10 environment. The ambient concentrations are compared against

11 health or environmental affects data. Rather than helping to

12 resolve a problem, a prolonged ambient monitoring study allows

13 continued air quality degradation, which in turn affects the

14 health or environmental quality which was to be protected. For a

15 new source being proposed, it is impossible to measure its

16 impacts, since it is not yet built.

17 c. The method of analysis preferred by EPA for

18 determining the ambient concentrations resulting from emissions

19 into the atmosphere of industrial sources, including toxic air

20 emissions, is modeling. As discussed above, before EPA

21 determines a model, such as ISC, to be a refined model,

22 appropriate for general use, the model undergoes rigorous

23 evaluation and is determined to yield accurate estimates of the

24 ambient air concentrations resulting from emission sources under

25 a variety of conditions. With a model, the source can be

26 simulated under the full range of its potential operating and

21 emission conditions, rather than being limited to the specific

9.11-05-1995 2:d1AM FROt,1 P.10

1 operating conditions occurring during the period of a limited

2 monitoring study. The model can also yield ambient concentration

3 data at any number of receptor locations; rather than only at the

4 limited number Of locations where a monitor is physically

5 located. Also, an air quality model provides the only practical

6 method of estimating the ambient impacts of a new source. A

7 model provides flexibility in an analysis and can be run

8 relatively quickly, at relatively little expense.

9 d. Modeling also**allo~s** source contributions to a

10 particular ambient concentration to be ascertained. If two

11 sources each emit the same pollutant, it is impossible to tell

12 from an ambient measurement of the specific pollutant, the

13 relative contributions to the measured ambient concentration,

14 unless there is some unique surrogate being emitted from one of

15 the facilities. Also, there is the uncertainty of whether a

16 heretofore unknown source of the pollutant of concern has

17 contributed to the measurement. Modeling, allows the impact of

18 each source to be calculated separately and in combination.

19 e. The use of monitoring data also pre-supposes that

20 there are acceptable and reliable monitoring techniques available

21 for the pollutant-of interest. In the past, this has generally

22 been the case. EPA has established acceptable and reliable

23 methods of measuring a number of pollutants which were regulated

24 under the Clean Air Act. Recently,**ho~ever,** the issue of toxic

25 air contaminants has arisen. Ambient**~easurement** techniques,

26 Which can adequately and accurately detect a specific toxic air

27 contaminant, are not necessarily available. The transport and11-05-1995 2 42AM FROM P.11

1 dispersion of buoyant or neutral plumes of gaseous pollutants,

2 which are relatively inert in the atmosphere, is the same,

3 regardless of the specific chemical constituents of the gas.

4 Therefore, modeling provides a useful technique for detecting

5 levels of pollutants in the air if reliable ambient measurement

6 techniques are not available.

7 f. EPA does recognize the usefulness of ambient

8 measurements for information on background concentrations,

9 provided reliable monitoring techniques are available. EPA does

10 not recommend, however, that ambient measurements be used as the

11 sole basis of setting emission limitations or determining the

12 ambient concentrations reSUlting from emissions from an

13 industrial source. These should be based on an appropriate

14 modeling analysis.

15 I declare under penalty of perjury that the foregoing is

16 true and correct.

17 DATED:;tJ6

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