# 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 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 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, ) ) ) ) ) ) ) ) ) ) } ) ) 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 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 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. 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 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 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 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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