Exhibit 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 SO2 NAAQS SIP Submissions 

Thank you for the opportunity to comment on USEPA’s guidance for one-hour SO2 NAAQS SIP 

submissions. In the 9/22/2011 public draft of their 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 SO2 NAAQS implementation program elements. 

These elements include: (1) establishing that compliance with the 1-hour SO2

NAAQS is appropriately based on the results of both air quality modeling and 

monitoring; (2) establishing the modeling requirements necessary to determine 

compliance with the 1-hour SO2 NAAQS; (3) establishing the minimum scope of 

analysis required to demonstrate attainment and maintenance of the 1-hour SO2

NAAQS to comply with the SIP requirements in CAA section 110(a)(1); (4) 

establishing a reasonable time period for sources to comply with any new 

emissions limitations states need to establish in the 110(a)(1) SIPs to demonstrate 

attainment and maintenance of the 1-hour SO2 NAAQS; (5) to set an attainment 

date for areas designated as unclassifiable; and (6) establishing the criteria for 

redesignating areas from “unclassifiable” 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 order to ensure compliance with the 1-

hour SO2 NAAQS in a timely manner.2

In summary, I believe that air dispersion modeling should be the preferred method for 

determining one-hour SO2 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 SO2 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. 
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essence, USEPA’s proposed hybrid modeling and monitoring implementation approach should 

be heavily weighted towards modeling. 

Air dispersion modeling has been used for decades to assess ambient air impacts from proposed 

and existing sources, and for SO2 NAAQS SIP purposes, monitoring alone (or a program based 

predominantly on monitoring) is not a viable alternative. I recently submitted a subset of these 

comments to USEPA’s 10th Conference on Air Quality Modeling docket. 

I specialize in atmospheric dispersion 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 air 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 curriculum vitae is attached. 

My comments on this docket concentrate on the issue of modeling vs. monitoring for verifying 

compliance with the one-hour SO2 NAAQS (attainment determinations). My comments are in 

response to USEPA’s “key questions” presented in their Implementation of the 2010 Primary 1-

Hour SO2 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 described above sufficient to determine whether 

ambient SO2 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 collection 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 feasible for monitoring alone to verify compliance with the one-hour 

SO2 NAAQS. A suitable monitoring program would require many monitors and data would 

need to be collected for at least several years. The number of required monitors would be 

prohibitively expensive and the duration of the monitoring program, while compounding the 

expense, also delays the implementation needed to protect public health from any unhealthy SO2

exposures. 
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The question of modeling or monitoring was discussed in a California Proposition 65 

enforcement declaration by John Vimont, when he was USEPA’s Region IX Regional 

Meteorologist: 

Monitoring data suffers from a number 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 maximum concentration and to adequately 

characterize the concentration field would be very expensive. A number of years 

of data would be necessary to collect enough samples to cover all possible 

meteorological situations in combination 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 ambient measurements for information on 

background concentrations, provided 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 standards. This sentiment is also expressed 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 provides excellent characterization of its 

concentrations, it is time consuming, costly, and typically limited to a few 

receptor locations and snapshots in time. 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-John-Declaration.pdf) 4

 Id. 
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and cumulative source contributions, and characterization of concentration over 

greater spatial extents.5

In addition, it is not always possible to place monitors where maximum project or cumulative 

impacts may be occurring. I have first-hand experience 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 District, I sited over 30 pre- and post-construction 

air quality PSD monitoring systems. These monitors were required by permit conditions for 

various oil and gas processing facilities, and several monitors were to be sited for each project. 

Using air dispersion modeling, we determined where the peak project impacts were likely to 

occur and then attempted to place the air quality monitoring systems at those locations. In 

virtually every case, it was not possible to place the 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, denial 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 SO2

NAAQS attainment determinations. There are not nearly enough SO2 monitors in place to 

determine attainment status of the existing major SO2 emission sources. Moreover, very few, if 

any, of these monitors are “well-placed” for measuring the maximum ambient air impacts from 

these existing SO2 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 SO2 ambient air concentrations and resulting attainment status. 

The lack of existing major source-specific SO2 monitoring is partly due to a failure of State air 

agencies requiring pre-and post-construction air quality monitoring. In the past few years I have 

reviewed and commented on major SO2 emission source PSD permit applications in Texas, 

Louisiana, Oklahoma, Nevada, Kentucky, North Carolina, South Carolina, Missouri, Kansas, 

South Dakota, Illinois, and Arkansas. With the exception of Nevada, the State air agencies have 

not required pre- or post-construction air quality monitoring, even though the PSD significant 

monitoring concentrations were exceeded. This is the norm for these 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 surrounding these facilities. It is self-serving if a 

facility that could (should) have been collecting ambient air quality data now argues that SO2

NAAQS attainment determinations must be based on monitoring, not modeling. 

5

 California Office of Environmental Health Hazard Assessment, Air Toxics Hot Spots Program Risk Assessment 

Guidelines: The Air Toxics Hot Spots Program Guidance Manual for Preparation of Health Risk Assessments, 

August 2003, p. 4-1. (http://www.oehha.org/air/hot_spots/pdf/HRAguidefinal.pdf) 
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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 meteorological data rather than rely on National 

Weather Service (NWS) airport data. On every occasion, my comments were disregarded, even 

though the PSD significant monitoring concentrations were exceeded for the proposed project. 

The State’s response and comment denial followed 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 application analyses. Although it’s water under the 

bridge, site-specific data could have been collected during these application processes without 

causing time delays to permit issuance. 

USEPA asked the question “In what situations should meteorological data collection also be 

required?” I believe the time has passed when these data could or should have been collected. 

Of course it would be ideal to have additional site-specific meteorological data for modeling 

major SO2 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 least another year for developing the data collection 

protocol, review and approval of the protocol, siting of the system, installation, and afterwards 

post-processing of the data for modeling. Starting a site-specific meteorological data collection 

effort from scratch contributes to an unreasonable delay of the measures that may be needed to 

protect ambient air from any excessive SO2 exposures. 

While I feel that site-specific meteorological data are preferable to NWS airport data, USEPA’s 

AERMINUTE program allows significant improvements to the NWS data in that calms and 

variable wind hours that were previously unusable by AERMOD can now be recaptured. In lieu 

of requiring new site-specific data collection efforts, modeling of SO2 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 meteorological data already exist, then I 

believe they should be used in preference to NWS airport data. 

Based on my experience, site-specific meteorological data tends to result in higher modeled 

impacts than NWS airport data, even when the 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 Johnstown 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 sets 
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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 twice 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 resulted in significantly higher impacts 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 Modeling 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 emissions 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. This 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 SO2 modeling analyses used for nonattainment 

SIP modeling should use actual emissions, and not the 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 General 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) 
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If actual emissions are used for nonattainment SIP modeling, a condition must be added to the 

facility’s permit requiring that emissions must not be greater than the level used in the modeling 

analysis. In other words, a facility that wants to use actual emissions in their modeling analysis 

must agree to an enforceable permit condition limiting their emissions, by unit, to that quantity 

modeled. Also, actual emissions cannot be modeled using full load stack parameters. Stack gas 

exit velocity and temperature will 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 exit velocity and temperature. I suggest that 

USEPA should develop a method for calculating stack 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 latest calendar year (or perhaps the maximum for 

the past three years). Maximum actual emissions 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 HOUREMIS in AERMOD) coupled with 

contemporaneous meteorological data, this analysis does not ensure that the one-hour SO2

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 very careful in considering emission rate cut-off levels. Without 

modeling, it is very difficult to determine the combined effects that emission rate, stack height, 

source-to-receptor distance and elevation differences, 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 concentration, not simply emission rate. 

c. Are there situations where modeling is preferable to monitoring? If so, then what are these 

situations? Should EPA require modeling 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 verifying compliance with the one-hour SO2 NAAQS. I cannot envision a 

feasible air monitoring network that would verify compliance for a major SO2 emission source – 

too many monitors would be needed and the delay in attainment demonstration and resulting 

controls would be unacceptably long. 
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I think it is beneficial to consider 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 previously existed. AB 2588 also required at least 

1,000 facilities state-wide to prepare health risk assessments, which are based on ambient air 

concentrations of the air toxics in question. In all instances, these facilities used air modeling as 

the basis for determining ambient air concentrations. 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 SO2 NAAQS SIP determinations. For example, in Santa Barbara 

County, where I was the Air Toxics Program Coordinator, 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 pollutants. Plus, we calculated excess cancer risk and noncarcinogenic health effects from inhalation and all other pathways of exposure. In other words, I 

think State air agencies should be able to handle the effort required in modeling the major SO2

emission sources within their jurisdiction. 

Some stakeholders have expressed concern that AERMOD will over-predict air impacts, 

compared to monitoring results. While this may 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 conditions that cannot be handled by air monitoring. 

On the other hand, there are likely many situations where AERMOD underpredicts air 

concentrations compared to monitoring data. 

USEPA should rely on the detailed AERMOD evaluations that were performed during the model 

development phase. I agree with Roger Brode’s 10th Modeling Conference presentation, where 

he concluded: “AERMOD model performance has been extensively evaluated and shown to 

provide generally unbiased estimates of 1-hr SO2 concentrations across a wide range of 

scenarios.”8

8

 Roger Brode, USEPA/OAQPS, AERMOD Evaluations Under the 1-hour NO2 and SO2 NAAQS, 10th 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) 
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I believe that the concerns about AERMOD over-predicting air concentrations are, on the whole, 

without merit. At the 2012 RSL Modelers’ Workshop, George Bridgers and Roger Brode 

presented a summary of AERMOD’s performance 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 across 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 SO2 emission sources have tall stacks, which were 

rigorously evaluated during AERMOD’s development process. From USEPA’s Compendium of 

Reports from the Peer review Process for AERMOD: 

Concerning the model evaluation, we reiterate 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 replacing 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 developing 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-downwashed, highly buoyant power 

plant stacks (the shortest stack in the group was 84 meters in Indianapolis).11

AERMOD’s evaluation process ultimately comprised 17 separate data sets. I believe that any 

concerns from stakeholders that AERMOD over-predicts power plant impacts, 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 NO2 & SO2 and PM2.5, 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. 
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I would also add that AERMOD’s evaluation analyses included a number 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 speeds as low as 0.31 m/s; the Kincaid SO2 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 regarding AERMOD’s ability to model low wind 

speed conditions seem to neglect the data 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 hillsides. This concern has already been addressed by 

USEPA in their response to the New Jersey Department of Environmental Protection (NJDEP) 

section 126 petition for SO2 emissions from the Portland Generating 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 complex wind fields surrounding the Portland facility.13 

USEPA also recognizes that “the performance of the AERMOD model for estimating impacts 

associated with tall stacks in complex terrain settings has been extensively evaluated and 

documented in peer-review journals... and has consistently been shown to perform better than 

competing models.”14

Air monitoring of SO2 is not a feasible alternative to modeling for steep hillsides and other 

complex terrain conditions. Proper air quality monitor 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 meteorological monitors to provide the needed 

data to develop the CALMET wind fields. For facilities 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 associated 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. 
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d. Are there situations where monitoring is preferable to modeling? If so, then what are these 

situations? Should EPA require monitoring 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 SO2 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 NO2, PM2.5, and SO2 NAAQS and PSD increment 

permit application analyses are performed with 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 determined, both existing sources and newly permitted 

sources should be assessed using the same methods. From the Guideline on Air Quality Models: 

The Guideline is used by EPA, States, and industry to prepare and review new 

source permits and State Implementation Plan revisions. The Guideline is 

intended to ensure consistent air quality analyses for activities regulated at 40 

CFR 51.112, 51.117, 51.150, 51.160, 51.166, and 52.21.15

Allowing existing sources to use monitoring (assuming adequate monitoring 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 SO2 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. USEPA must not exchange their existing guideline model for an 

ambient air monitoring program which will never be able to verify compliance with the one-hour 

SO2 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 SO2

NAAQS. I suggest that USEPA’s proposed hybrid 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) 
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approach for one-hour S02 NAAQS SIP submissions should be heavily weighted towards

modeling.

Thank you for the opportunity to submit these comments on USEPA 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: camille.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 part of a team of experts.

Education

 M.S., Atmospheric Science, University of California, Davis, 1980.

 B.S., Atmospheric Science, University 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 

modeling analyses requiring the use of on-site or site-specific meteorological data. 

These runs were made with the USEPA ISC, OCD, MESOPUFF, INPUFF, CALPUFF, 

ISC-PRIME, AERMOD, COMPLEX-I, MPTER, and other air dispersion models.

 I prepared 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, including 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 ponds;

Volume sources, including fugitive emissions 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, 

degreasing 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 oil and gas exploration, storage, processing, and transport facilities;

Fugitive dust emissions from roads, wind erosion, and farming activities;

Radionuclide emissions from actual and potential releases.

 I have extensive experience in modeling 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 extensive 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 

SBAPCD protocol on air quality modeling for OCD, OCDCPM, MPTER, COMPLEX-I/II 

and ISC.

 I provided detailed review and comments on the development of the Minerals 

Management Service OCD model. I developed the technical requirements for and 
Camille Marie Sears, Page - 2

supervised the development of the OCDCPM model, a hybrid of the OCD, COMPLEX-I 

and MPTER models.

 I prepared the "Modeling Exposures of Hazardous Materials Released During 

Transportation Incidents" report for the California 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 chemicals 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 am 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 Risk Assessment

 I have prepared more than 300 health risk assessments 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 were prepared for 

Proposition 65 compliance verification in a litigation support setting.

 I reviewed approximately 300 other health risk assessments of toxic air pollution 

sources in California. The regulatory programs in this review include AB 2588, 

Proposition 65, the California Environmental Quality Act, and other exposure analysis 

activities. My clients include the California Attorney General's Office, the Los Angeles 

County District Attorney's Office, the SBAPCD, the South Coast Air Quality 

Management District, numerous environmental and community groups, and several 

plaintiff law firms.

 I am experienced in assessing public health risk from continuous, intermittent, and 

accidental releases of toxic emissions. I am experienced in generating graphical 

presentations of risk results, and characterizing risks from carcinogenic and acute and 

chronic noncarcinogenic pollutants.

 I am experienced in communicating adverse health risks discovered through the 

Proposition 65 and AB 2588 processes. I have presented risk assessment results in 

many public settings -- to industry, media, and the affected public.

 For four years, I was the Air Toxics Program Coordinator for the SBAPCD. My duties 

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; management 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 pollutants. A few 

examples include: diesel PM10 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 clothes.

Litigation Support

 I have prepared numerous analyses in support of litigation, both in Federal and State 

Courts. I am experienced in preparing F.R.C.P. Rule 26(a)(2) expert reports and 

providing deposition and trial testimony (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 experienced in preparing declarations (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, questions for depositions, deposition reviews, various briefs 

and motions, and general consulting.

 Recent examples of my work include:

DTSC v. Interstate Non-Ferrous; United States District Court, Eastern District of 

California (2002).

In this case I performed 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 quantify 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 chemicals: 

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 Division (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. Defendants 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 for 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 Regulations 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 reviewed scores of other assessments for verifying compliance with 

Proposition 65. My proposition 65 litigation clients include the California 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 Fund, 

Environmental Law Foundation, and People United for a Better Oakland. 

Geographic Information Systems

 ArcGIS: I am experienced in preparing presentation and testimony maps using 

ArcView versions 3 through 9.3. I developed methods 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 regions. This provides a 

detailed view (down to the house level) of where air concentrations and health 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 prepared numerous presentation maps including exposure 

isopleths, streets and highways, and sensitive receptors, labels. I developed 

procedures for importing Surfer isopleths in AutoCAD DXF format as a layer into 

MapInfo.

 Atlas GIS: I am experienced in preparing presentation maps with both the Windows 

and DOS versions of Atlas GIS. In addition to preparing maps, I use Atlas GIS to 

aggregate census data (at the block group level) within exposure isopleths to 

determine the number of individuals living and working within exposure zones. I am 

also experienced in geocoding large numbers of addresses and performing statistical 

analyses 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 litigation support.

 I developed a Fortran program to modify AutoCAD DXF files, including batch-mode 

coordinate shifting for aligning overlays to different base maps.

Ozone and Long-Range Transport

 I developed emission reduction strategies and identified appropriate offset sources to 

mitigate project emissions liability. For VOC offsets, I developed 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/nonalkane reactive organic compound method.

 I provided technical support to the Joint Interagency Modeling Study and South Central 

Coast Cooperative Aerometric Monitoring Program. With the SBAPCD, I provided 

technical comments on analyses performed with the EKMA, AIRSHED, and PARIS 

models. I was responsible for developing emissions inventory for input into regional air 

quality planning models.

 I was the project manager for the Santa Barbara County Air Quality Attainment Plan 

Environmental Impact Report (EIR). My duties 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 Fortran 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 in 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 from various emission sources, 

including power plants.

Emission Rate Calculations

 I developed methods to estimate and verify source emission rates using air pollution

measurements collected downwind of the emitting facility, 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 experienced in developing emission inventories of hundreds of criteria and toxic 

air pollutant sources. I developed procedures and programs for quantifying emissions 

from many air emission sources, including: landfills, diesel exhaust sources, 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 hundreds 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 

results, mass-balance equations, and other emission estimating techniques.

Software Development

 I am skilled in computer operation and programming, with an emphasis on Fortran 95.

 I am experienced with numerous 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-Extended; Lahey F77L-EM32 DOSExtended; Microsoft PowerStation 32-bit DOS-Extended; and Microsoft 16-bit.

 I configured and operated an Intel I-860 based workstation for the SBAPCD toxics 

program. I created control files and recoded programs 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-meter 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 SBAPCD, I designed the ACE2588 model - the first public domain multisource, multi-pathway, multi-pollutant risk assessment model. I co-developed the 

structure of the ACE2588 input and output files, supervised the coding of the model, 

tested the model for quality assurance, and for over 10 years I provided technical 

support to about 200 users of the model. I was responsible 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 developed and coded the ISC2ACE and ACE2 programs for distribution by CAPCOA. 

These programs were 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 requirements compared to 

ISCST2/ACE2588. I also developed ISC3ACE/ACE3 to incorporate the revised 

ISCST3 dispersion model requirements.

 I developed 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 customized ACE2588 and developed a mapping system 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 streamline preparing AB 2588 risk assessments; I developed

a risk assessment mapping system based on MapInfo for Windows which linked the 

MapInfo mapping package to the "HotSpot" system.

 I developed software for electronic submittal 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 submitted 
Camille 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 developed and coded Fortran programs for AB 2588 risk prioritization; both batch and 

interactive versions of the program were created. These programs were used by 

several air pollution control districts in California.

Air Quality and Meteorological Monitoring

 I was responsible for the design, 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 developed the technical requirements for the Santa Barbara County Air 

Quality/Meteorological Monitoring Protocol. I developed and implemented the protocol 

for siting pre- and post-construction air quality and meteorological PSD monitoring 

systems. I determined 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 fluctuations), sigma-phi (standard deviation of vertical wind 

direction fluctuations), sigma-v (standard deviation of horizontal wind speed 

fluctuations), and sigma-w (standard deviation of vertical wind speed fluctuations). Air 

pollutants measured included PM10, SO2, NO, NOx, NO2, CO, O3, and H2S.

 I was responsible for data acquisition and quality assurance for an offshore 

meteorological monitoring station. Parameters measured included ambient 

temperature (and delta-T), wind speed, wind direction, and sigma-theta.

 In coordination with consultants performing air monitoring for verifying compliance with 

Proposition 65 and other regulatory programs, I wrote software to convert raw 

meteorological data to hourly-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 spray 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, Training, and Instruction

 For 10 years, I provided ACE2588 risk assessment model support for CAPCOA. My 

tasks included: updating the ACE2588 risk assessment model Fortran code to 

increase user efficiency and to maintain consistency with the CAPCOA Risk 

Assessment Guidelines; modifying the 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 Guidelines; 

developing the distribution and installation package for ACE2588 and associated 

programs; providing technical support for all users of ACE2588.

 I instructed approximately 20 University Professors through the National Science 

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 instructor of the Air Pollution and Toxic Chemicals course for the University 

of California, Santa Barbara, Extension certificate program in Hazardous Materials 

Management. Topics covered in this course include: detailed review of criteria and 
Camille 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 shortterm releases of air pollutants; acid deposition, precipitation and fog; 

indoor/occupational 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-day 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 deposition 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 for Santa Barbara County high-exposure radon areas.

 I calculated BTEX air concentrations and health risks inside homes from leaking 

underground fuel tanks and resultant contaminated 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 reconstruction 

(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 quantity and 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 calculated 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

Publications

 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 regulatory decision-making.

 I prepared 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).

Employment History

 Self-Employed Air Quality Consultant 1992 to 2012

 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

 People of the State of California v. McGhan Medical, Inc.

Deposition: Two dates: June - July 1990

 People of the State of California v. Santa Maria Chili

Deposition: 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

Deposition: 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

Deposition: July 11, 2000

 Marlene Hook v. Lockheed Martin Corporation

Deposition: September 18, 2000

Deposition: September 19, 2000

 Tressa Haddad v. Texaco

Deposition: March 9, 2001
Camille 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, District 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 Cleaners

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 District 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 Alvarez, 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 & UMETCO 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, Denver 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 Service, 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, 2008
Camille 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 Permit 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)] Permit 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)] Permit HAP-48 and Plantwide 

Applicability Permit PAL41.

State Office of Administrative Hearings Docket No. 582-09-2005;

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 District 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

Trial: February 10, 2011

 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, 2010
11-05-1995 2 37AM FROM P 1

,

DEC 0 3 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,

)

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}

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)

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 meteorological

27 information and ambient air impact analyses. My position is
11-05-1995 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 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 all
11-05-19952:38AM 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

27
11-05-1995 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 term
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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. 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 SF6 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 approved
11-05-19952d0AM 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 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.
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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 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, the issue of toxic

25 air contaminants has arisen. Ambient techniques,

26 Which can adequately and accurately detect a specific toxic air

27 contaminant, are not necessarily available. The transport and
11-05-1995 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 30 /f90 ./

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