March 7, 2012 

Mr. Gerardo Rios 

Chief, Permits Office 

U.S. EPA Region 9 

75 Hawthorne Street 

San Francisco, CA 94105 

Subject: Pio Pico Energy Center PSD Permit Application 

 

Dear Mr. Rios: 

As requested by EPA during the February 13, 2012 meeting between representatives of 

EPA and Pio Pico Energy Center, LLC (Applicant), we are submitting this additional 

information on behalf of Applicant. EPA also requested that the Applicant provide the 

modeling files that support the Class I Increment Analysis; those are provided on the 

enclosed CD. 

It should be noted that the Applicant submitted the proposed modeling protocol for the 

Pio Pico Energy Center (Project) to EPA on December 1, 2010, with a request for review 

and comment, consistent with EPA’s policy encouraging early consultation on modeling 

issues.1

 EPA did not respond to Applicant’s request. In the absence of any questions or 

concern expressed by EPA regarding the protocol, Applicant proceeded with modeling 

and analysis consistent with the protocol, and has expended considerable time and effort 

in reliance on EPA’s tacit approval.2

 

It should also be noted that Applicant submitted the PSD permit application on April 1, 

2011. The original PSD permit application included an air quality analysis, and the 

applicant sought guidance from EPA on selection of nearby sources to include in the 

cumulative impact modeling. The cumulative impact modeling was submitted on July 6, 

2011. 

 

1

 Appendix W, Section 10.2.1: “[e]very effort should be made by the Regional Office to meet with all 

parties involved in a SIP revision or a PSD permit application prior to the start of any work on such a 

project. During this meeting, a protocol should be established between the preparing and reviewing parties 

to define the procedures to be followed, the data to be collected, the model to be used, and the analysis of 

the source and concentration data.” 

2

 It should also be noted that during the December 9 meeting, EPA staff indicated that any additional 

concerns regarding modeling issues would be documented in a letter to Applicant on or before 

December 16, 2011; however, to date, no such letter has been received. In addition, several calls have been 

placed to EPA modeling staff to confirm that any remaining issues have been resolved, but no calls have 

been returned. Applicant has therefore proceeded on the assumption that EPA’s requests for additional 

information about modeling issues have been fully addressed. 

sierra 

research

1801 J Street 

Sacramento, CA 95811 

Tel: (916) 444-6666 

Fax: (916) 444-8373

Ann Arbor, MI 

Tel: (734) 761-6666 

Fax: (734) 761-6755 
Gerardo Rios -2- March 7, 2012 

At the February 13, 2012 meeting, EPA staff asked for more information about modeling 

parameters. Some of these parameters were first presented to EPA in the July 2011 

modeling submittal whereas other parameters were presented to EPA in April 2011as part 

of the original PSD permit submittal. 

Federal regulations require EPA staff to attempt to determine whether a PSD application 

is complete within 30 days of submittal.3 While this is not an enforceable requirement, it 

represents EPA policy at its highest and most public level. EPA’s long delays in 

responding to submittals, the incremental and shifting nature of its requests for additional 

information (this is EPA’s fourth different request for modeling information), and its 

failure to provide guidance that would allow an applicant to provide a complete and 

satisfactory response, are not consistent with the spirit represented by this regulation. 

SF6 Emissions 

Comment: Please estimate SF6 emissions from circuit breakers at the project.

Response: 

Sulfur hexafluoride (SF6) will be used as an insulating medium in three 230 kV 

switchyard breakers and in two generator circuit breakers (GCB). Estimates of the SF6 

contained in a 230 kV breaker range from 161 to 208 lbs, depending on the manufacturer. 

The GCBs will each contain 24.2 lb of SF6. The IEC standard for SF6 leakage is less 

than 0.5%; the NEMA leakage standard for new circuit breakers is 0.1%. A maximum 

leakage rate of 0.5% per year is assumed. 

Type of 

Breaker 

Number of 

Breakers 

lb SF6 per 

breaker 

Maximum 

Leakage 

Rate, % 

Maximum SF6

Emissions, 

lb/yr 

Switchyard 3 208 0.5% 3.12 

Generator 2 24.2 0.5% 0.24 

Total 3.36 

Based on a global warming potential of 23,9004

, the maximum SF6 emissions from 

facility circuit breakers will not exceed 40.2 tons/yr of CO2e. 

Wind Roses 

 

3

 40 CFR 124.3 (c): “The Regional Administrator shall review for completeness every application for an 

EPA-issued permit. Each application for an EPA-issued permit submitted by a new HWM facility, a 

new UIC injection well, a major PSD stationary source or major PSD modification, or an NPDES new 

source or NPDES new discharger should be reviewed for completeness by the Regional Administrator 

within 30 days of its receipt. Each application for an EPA-issued permit submitted by an existing HWM 

facility (both Parts A and B of the application), existing injection well or existing NPDES source or sludgeonly facility should be reviewed for completeness within 60 days of receipt. Upon completing the review, 

the Regional Administrator shall notify the applicant in writing whether the application is complete. If the 

application is incomplete, the Regional Administrator shall list the information necessary to make the 

application complete.” (emphasis added). 

4 40 CFR 98 Subpart A, Table A-1.
Gerardo Rios -3- March 7, 2012 

Comment: Please provide new wind rose graphics based on the definition of “calm” 

periods used in the modeling. 

Response: In order to reduce the amount of time where wind speed is treated as “calm,” 

the San Diego Air Pollution Control District (SDAPCD or District) defines wind speeds 

below 0.45 m/sec as “calm” (standard definition is 0.5 m/sec). Charts were provided in 

the PSD application that graphically summarize quarterly and annual distributions of 

wind speed and direction (“wind roses”). The wind roses that were provided in the 

application used the standard cutoff for calm periods. EPA requested that Applicant 

provide wind roses that use the same cutoff used by the Applicant, following District 

guidance, in the modeling; the requested wind roses are attached. 

Summary of 1-hour NO2 NAAQS Compliance Calculation 

Comment: Please show the calculations and relevant data used to demonstrate 

compliance with the 1-hour NO2 NAAQS. 

Response: The requested calculations are presented in Table 1. 

Table 1 

One-hr NO2 NAAQS Compliance Calculation 

(Receptor 8164a)

Year 2004 2005 2006 2007 2008 

5-year 

Average 

Date March 7 Oct. 19 Dec. 14 March 23 Oct. 14 

Hour 21 3 18 23 19 

Cumulative 

Impact (μg/m3) 175.5 170.5 193.9 172.9 184.4 179.4 

Regional 

Background 

(μg/m3) 

125.94 78.95 107.14 101.50 110.90 

Project Impact 

(μg/m3) 37.36 62.05 67.03 20.01 36.55 

a Receptor with the highest 5-year average 98th percentile of the daily maximum 1-hour cumulative impact 

(monitor data plus modeled impact from project and non-project nearby sources). 

Isopleth Maps of 5-Year Averages of 98th Percentile Concentrations 

Comment: Please provide isopleths maps showing the 5-year averages of 98th percentile 

concentrations for both PM2.5 and NO2. 

Response: The requested isopleths maps are provided as Figures 1 and 2. 
Gerardo Rios -4- 

Figure 1. Five-Year Averages of 98th Percentile Maximum Daily One-hour NO2 Concentration

(Measured Background plus Modeled Project and Nearby Sources) 
Gerardo Rios -5- 

Figure 2. Five-Year Averages of 98th Percentile Maximum 24-hour PM2.5 Concentrations 

(Measured Background plus Modeled Project and Nearby Sources) 
Gerardo Rios -6- March 7, 2012 

Justification of Use of PVMRM 

Comment: On December 1, 2011, at EPA’s request, the applicant submitted additional 

justification for the use of the PVMRM Tier 3 non-regulatory default option. EPA specifically 

requested more information on prongs 1 and 4 of the 5-prong demonstration under Appendix 

W Section 3.2.2. Now EPA requests more information on prongs 2, 3, and 5. 

Section 3.2.2.e of Subpart 51, Appendix W states: 

e. Finally, for condition (3) in paragraph (b) of this subsection, an alternative refined 

model may be used provided that: 

i. The model has received a scientific peer review; 

ii. The model can be demonstrated to be applicable to the problem on a 

theoretical basis; 

iii. The data bases which are necessary to perform the analysis are available 

and adequate; 

iv. Appropriate performance evaluations of the model have shown that the 

model is not biased toward underestimates; and 

v. A protocol on methods and procedures to be followed has been established. 

Applicant provided information supporting the use of PVMRM in its initial PSD application 

submitted in April 2011. At EPA’s request, Applicant provided supplemental information on 

Prongs 1 and 4 in its December 1, 2011 submittal. Additional information is provided below 

with regard to the other three prongs. 

Prong 2. The model can be demonstrated to be applicable to the problem on a theoretical 

basis.

AERMOD without PVMRM (or OLM) is a dispersion model. It predicts ground-level 

concentrations based on distribution of emissions from the sources being modeled. However, 

the NOx emitted at the stack is a mixture of (primarily) NO and NO2. If conversion of stack 

NO to NO2 in the atmosphere is not taken into account, the model will significantly 

underpredict NO2 impacts. Conversely, if the unrealistic assumption is made that 100% of 

stack NO is converted to ground-level NO2 at all receptors, regardless of transport time, 

transport distance, or ambient ozone concentrations, the dispersion model will significantly 

overpredict NO2 impacts. Conservative assumptions are initially used in compliance 

screening methodologies in order to assure compliance. As the compliance evaluation 

methodology becomes more sophisticated, the greater accuracy continues to assure 

compliance while allowing more realistic (less conservative) assumptions. EPA addresses 

this process, in the context of the 1-hour NO2 standard, through increasingly sophisticated 

(and less conservative) tiers of analysis. 
Gerardo Rios -7- March 7, 2012 

The regulatory default modeling methodologies for the 1-hour NO2 standard are 

screening methodologies.5

 

Tier 1: Assume full conversion of NO to NO2 based on application of an 

appropriate refined modeling technique under Section 4.2.2 of Appendix W to 

estimate ambient NOx concentrations. 

Tier 2: Multiply Tier 1 result by empirically derived NO2/NOx ratio, with 0.75 as 

the annual national default ratio. 

Tier 3: Detailed screening methods may be considered on a case-by-case basis, 

with the Ozone Limiting Method (OLM) identified as a detailed screening 

technique for point sources. PVMRM is also considered by EPA to be in this 

category at this time.6

Under EPA’s interim guidance for evaluating compliance with the 1-hour NO2 NAAQS, the 

Significant Impact Level (SIL)-equivalent is so low that almost any moderate-to-large 

combustion source will have difficulty passing a screening assessment. It is therefore 

necessary to use more sophisticated analytical tools, as provided for in EPA guidance. One 

such tool identified by EPA, and selected for use with the Project, is the PVMRM option 

within AERMOD. 

AERMOD-PVMRM has been tested specifically for its ability to compute unbiased 

results. One of the key studies was conducted by a senior modeler currently in OAQPS 

at EPA, and conducted on large natural gas-fired power plants.7 The study concluded 

the following: “Based on all of the data available, the AERMOD-PVMRM algorithm is 

judged to provide unbiased estimates of the NO2 /NOx ratio based on criteria that are 

comparable to, or more rigorous than, evaluations performed for other dispersion models 

that are judged to be refined.” 

In its March 1, 2011 guidance, EPA states: 

“We believe that these additional model evaluation results lend further credence to the 

use of these Tier 3 options in AERMOD for estimating hourly NO2 concentrations, 

and we recommend that their use should be generally accepted provided some 

reasonable demonstration can be made of the appropriateness of the key inputs for 

these options, the in-stack NO2/NOx ratio and the background ozone concentrations.”8

 

For these reasons, use of the AERMOD-PVMRM algorithm is applicable to a refined analysis 

of compliance with the 1-hour average NO2 impacts from the Project on a theoretical basis. 

 

5

 EPA, Appendix W Section 5.2.4. See also Memorandum from Wood to Regional Air Division Directors, 

General Guidance for Implementing the 1-hour NO2 Standard in Prevention of Significant Deterioration 

Permits, June 28, 2010, p.14. 6

 Memorandum from Wood to Regional Air Division Directors, Applicability of Appendix W Modeling Guidance 

for the 1-hour NO2 NAAQS, June 28, 2010, p.2. 7

 Brode, Roger W. Final Report, Evaluation of Bias in AERMOD-PVMRM, MACTEC report on Alaska 

Department of Environmental Conservation Contract No. 18-9010-12, June 2005.

8 Memorandum from Fox to Regional Air Division Directors, Additional Clarification Regarding Application of 

Appendix W Modeling Guidance for the 1-hour NO2 NAAQS, March 1, 2011, p. 6. 
Gerardo Rios -8- March 7, 2012 

Prong 3. The data bases which are necessary to perform the analysis are available and 

adequate.

The additional data needed to perform the PVMRM analysis (i.e., ambient ozone data) were 

collected from the Chula Vista monitoring station, which is the same station that provided the 

ambient NO2 data. 

The justification for use of background air quality data from the Chula Vista monitoring 

station was presented in the November 2010 modeling protocol at pp. 6-7. As discussed in 

the monitoring protocol, the Chula Vista monitoring station was selected by the San Diego 

APCD as the monitoring location most representative of the project site. 

The ozone data used in the PVMRM analysis were provided by the District. The hourly 

ozone data was 6.33% incomplete before data substitution.9 The data substitution procedure 

described in the December 1, 2011 submittal was used to fill any gaps. 

In-stack NO2/NOx ratios for the project turbines are based on source test data from similar 

units, provided by the District (and described in the January 5, 2012 submittal). In-stack 

NO2/NOx ratios for nearby sources were based on District source test data, provided by the 

District (and also described in the January 5, 2012 submittal). 

Prong 5. A protocol on methods and procedures to be followed has been established.

Applicant submitted the proposed modeling protocol for the Pio Pico Energy Center (Project) 

to EPA on December 1, 2010, with a request for review and comment, consistent with EPA’s 

policy encouraging early consultation on modeling issues. EPA did not respond to 

Applicant’s request. In the absence of any questions or concern expressed by EPA regarding 

the protocol, Applicant proceeded with modeling and analysis consistent with the protocol, 

and has expended considerable time and effort in reliance on EPA’s tacit approval. 

In March 2011, EPA published additional modeling guidance for 1-hour NO2 compliance 

demonstrations.10 The modeling protocol submitted in December 2010 is consistent with that 

guidance. The AQIA submitted as part of the PSD application is also consistent with that 

guidance. 

EPA did provide some guidance in May 2011 regarding selection of nearby sources for 

cumulative impact analysis for this project. EPA did not at that time express any concern 

regarding use of PVMRM for this Project or seek additional justification for such use. 

Conclusion 

 

9 2004, 529 missing hours out of all 8784 hours / 6.02%; 

2005, 549 missing hours out of all 8760 hours / 6.27%; 

2006, 483 missing hours out of all 8760 hours / 5.51%; 

2007, 634 missing hours out of all 8760 hours / 7.34%; 

2008, 571 missing hours out of all 8784 hours / 6.50%; 

10 Memorandum from Fox to Regional Air Division Directors, Additional Clarification Regarding Application of 

Appendix W Modeling Guidance for the 1-hour NO2 NAAQS, March 1, 2011. 
Gerardo Rios -9- March 7, 2012 

Based upon the information provided above and in previous submittals to EPA, Applicant 

believes that the use of PVMRM for the demonstration of compliance with the 1-hour NOx

NAAQS meets the criteria specified in Section 3.2.2.e of Subpart 51, Appendix W. 

Surface Roughness 

Please provide a more detailed (by sector) comparison of the surface roughness at the project 

site with the surface roughness at the site providing the meteorological data.

Otay Mesa Meteorological Station 

Response: The surface roughness values used in the PPEC PSD permit application were 

developed by the SDAPCD, and represent the surface roughness surrounding the site where 

meteorological data were collected. The District followed EPA’s “AERMOD Implementation 

Guide” (2008 version) in using EPA’s AERSURFACE processor with the National Land 

Cover Data 1992 archive to determine surface characteristics for AERMET (Class II 

Modeling Protocol pp.2-9 to 2-14). 

AERSURFACE uses a Land Use data base from 1992, and does not take buildings into 

account. The District reviewed aerial photos for the area, which show that the vicinity of the 

Otay Mesa meteorological tower is surrounded by a light industrial and residential area that 

includes northern Mexico and the U.S border area. Using this information, the District 

adjusted the surface roughness factor from the value of approximately 0.2 meters calculated 

by AERSURFACE to 0.7 meters to more accurately represent the current terrain and 

structures surrounding the Otay Mesa meteorological monitoring station location (see Figure 

3). The District’s adjustment is supported by AERSURFACE guidance11 and the scientific 

literature.12 EPA’s AERSURFACE guidance assigns an even higher surface roughness of 0.8 

m to commercial/industrial/transportation areas (Class 23) not located at an airport. Stull’s 

scientific textbook on boundary layer meteorology, which is a scientific reference for Table 

A-3 in EPA’s AERSURFACE User’s Guide, gives a surface roughness range of 

approximately 0.7 m to 1.3 m for “Centers of large towns and cities.” 

SDAPCD performed a qualitative review of the surface roughness values used by the 

Applicant (per instructions by the District) to ensure that they were reasonably representative 

of the project site. It did this by examining the 10 km by 10 km domain centered on the 

project site, and determined that the data in the two tables are reasonably representative of the 

domain as a whole. This conclusion is not surprising, because both locations are located 

within that 10 km by 10 km domain. 

 

11 EPA. AERSURFACE User’s Guide, Table A-3 – Seasonal Values of Surface Roughness (m) for the NLCD92 

21-Land Cover Classification System, page A-5, January 2008. 

12 Stull, R.B., An Introduction to Boundary Layer Meteorology, Figure 9.6 -Aerodynamic roughness lengths for 

typical terrain types, page 380, 1988.
Gerardo Rios -10- March 7, 2012 

Figure 3. Otay Mesa Meteorological Station and Surrounding Area 

EPA has requested additional detail characterizing the surface roughness surrounding the 

project site by sector. Applicant has characterized the surface roughness as follows: 

 Twelve 30-degree land use sectors 

 Annual results by sector 

 1 kilometer radius 

 Seasons defined as follows 

o October-February: Late autumn after frost and harvest 

o March-April: Transitional spring (partial green coverage, short annuals) 

o May-September: Midsummer with lush vegetation 
Gerardo Rios -11- March 7, 2012 

The results for the PPEC project site from AERSURFACE, along with the District’s revised 

values for the location of the meteorological monitoring station, are shown in Table 2. 

Table 2 

Comparison of Surface Roughness at PPEC Stack Location 

with Otay Mesa Meteorological Station (meters) 

Sector PPEC 

Otay Mesa Met Station 

(adjusted by SDAPCD) 

1 0.2 0.7 

2 0.2 0.7 

3 0.2 0.7 

4 0.2 0.7 

5 0.2 0.7 

6 0.2 0.7 

7 0.1 0.7 

8 0.2 0.7 

9 0.2 0.7 

10 0.1 0.7 

11 0.2 0.7 

12 0.2 0.7 

In contrast to the area surrounding the Otay Mesa meteorological station, the area surrounding 

the project site is not surrounded by buildings. However, there are significant structures 

adjacent to the project site, including the combustion gas turbines, heat recovery steam 

generators, dry cooling tower and administration building for the Otay Mesa Energy Center 

located directly east of the Project at distances between 0.1 and 0.6 km. 

The information provided in the Applicant’s December 1, 2011 letter demonstrates that the 

albedo and Bowen ratio values for the project and meteorological station sites are very 

similar. 

The importance of surface roughness in the AERMOD dispersion model is to properly 

interpret the meteorological observations at the monitoring site. The surface roughness 

around the meteorological station is used,

13 along with monitored wind speeds, directions, 

and temperatures by AERMOD’s meteorological processor, AERMET, “in determining the 

magnitude of mechanical turbulence and the stability of the boundary layer”14 being 

monitored. It is only after the monitored meteorological data have been properly interpreted 

that the data can be used by AERMOD to correctly simulate air dispersion from various 

project sites within reasonable proximity to the meteorological monitoring stations. 

 

13 EPA. AERSURFACE User’s Guide, page 6, January 2008. 14 EPA. AERSURFACE User’s Guide, page 1, January 2008. 
Gerardo Rios -12- March 7, 2012 

Surface roughness is therefore used by AERMOD to properly interpret airflow measurements 

at the monitoring site and apply them to the dispersion calculations. 

Assessment of the representativeness of the Otay Mesa meteorological data 

EPA guidance describes the factors that should be taken into account in assessing siting of 

meteorological monitors.15 Although this guidance is principally useful in determining where 

to site a new monitor, it is also helpful in assessing the adequacy of existing data. 

The factors recommended for consideration in monitor siting are: 

 Proximity 

 Height of Measurement 

 Boundary Layer Profile Considerations 

 Surface Characteristics 

The goal of the analysis is to determine whether the proposed monitoring data is adequately 

representative of the area of interest.16 Because the preferred regulatory dispersion model 

(AERMOD) is a steady state model, one set of meteorological conditions must be selected to 

represent the entire modeling domain. The determination of whether data are adequate for 

this purpose is a qualitative evaluation that requires the application of experience and 

judgment. 

Factor 1: Proximity. 

“In general, the representativeness of the meteorological data used in an air quality 

modeling analysis is dependent on the proximity of the meteorological monitoring site 

to the “area-of-interest”.17

“In some instances, even though meteorological data are acquired at the location of the 

pollutant source, they may not correctly characterize the important atmospheric 

dispersion conditions; e.g., dispersion conditions affecting sources located on the coast 

are strongly affected by off-shore air/sea boundary conditions - data collected at the 

source would not always reflect these conditions.”18

The Otay Mesa meteorological station is very close to the project site—3.2 km. Both the site 

and the station are approximately the same distance from the Pacific Ocean, and there are no 

significant nearby bodies of water to affect dispersion conditions at either site. There are no 

intervening terrain features between the project site and the meteorological station. The 

principal factor for assessing representativeness of the meteorological data, proximity, 

therefore weighs strongly in favor of the Otay Mesa data.

Factor 2: Height of Measurement. 

 

15 EPA, Meteorological Monitoring Guidance for Regulatory Modeling Applications. p. 3-1 16 This is not the same as the project site. See the discussion of Factor 1 (Proximity) below. 

17 EPA, Meteorological Monitoring Guidance for Regulatory Modeling Applications. p. 3-3 18 EPA, Meteorological Monitoring Guidance for Regulatory Modeling Applications. p. 3-3
Gerardo Rios -13- March 7, 2012 

“Representativeness is a function of the height of the measurement. For example, one 

can expect more site-to-site variability in measurements taken close to the surface 

compared to measurements taken aloft. As a consequence, upper-air measurements are 

generally representative of much larger spatial domains then are surface 

measurements.”19 

Measurements at the Otay Mesa meteorological station are made at a height of 10 m, which is 

the standard measurement height for a permanent NWS station of the type routinely accepted 

by EPA. This factor supports the use of the Otay Mesa data.

Factor 3: Boundary Layer Profile Considerations. 

“Where appropriate, data representativeness should be viewed in terms of the 

appropriateness of the data for constructing realistic boundary layer profiles and three 

dimensional meteorological fields. Factors that should be considered in selecting a 

monitoring site in complex terrain include: the aspect ratio and slope of the terrain, the 

ratios of terrain height to stack height and plume height, the distance of the source 

from the terrain feature, and the effects of terrain features on meteorological 

conditions, especially wind speed and wind direction.”20

Factor 3A: Aspect ratio and slope of the terrain. 

The aspect ratio and slope of the terrain surrounding the meteorological station is flat, sloping 

slightly upwards to the east. The aspect ratio and slope of terrain to the south and west of the 

project site is the same as for the meteorological station. However, the terrain rises to the 

north and east of the project site. As a result, wind speed and direction data taken at the 

project site would be, to some extent, affected by the terrain. Meteorological data taken at the 

site would be expected to be less representative of the area of interest than data collected at 

the Otay Mesa station, which is less affected by the terrain. This factor supports the use of the 

Otay Mesa data. 

Factor 3B: Ratios of terrain height to stack height and plume height 

The terrain to the east of the project site rises to more than a hundred meters above the stack 

within two kilometers. However, the plume height is above the terrain height, so this 

subfactor is not a significant factor in assessing meteorological monitor location. 

Factor 3C: Distance of the source from the terrain feature 

The nearest terrain feature that could affect meteorological conditions is the elevated terrain 

of the San Ysidro Mountains to the east of both the project site and the meteorological station. 

The project site is approximately 1.5 km from the nearest ridge. The meteorological station is 

approximately 4.5 km from the same ridge, which is the closest terrain feature to the 

meteorological station. This factor supports the use of the Otay Mesa data. 

 

19 EPA, Meteorological Monitoring Guidance for Regulatory Modeling Applications. p. 3-3 20 EPA, Meteorological Monitoring Guidance for Regulatory Modeling Applications. p. 3-3
Gerardo Rios -14- March 7, 2012 

Factor 3D: Effects of terrain features on meteorological conditions, especially wind speed 

and wind direction. 

The most important consideration in siting a wind direction sensor in complex terrain is that 

the measured direction should not be biased in a particular direction that is not experienced by 

the pollutant plume. 

The same large-scale topographic features located to the east and north that influence the 

meteorological data monitoring station also influence the proposed project site in the same 

manner. This factor supports the use of the Otay Mesa data. 

Factor 4: Surface Characteristics 

“In steady-state modeling applications, one typically focuses on the meteorological 

conditions at the release height of the source or sources, or the plume height in the 

case of buoyant sources. Representativeness for steady-state modeling applications 

must necessarily be assessed in concert with the steady-state assumption that 

meteorological conditions are constant within the space-time domain of the 

application; as typically applied, measurements for a single location, somewhere near 

the source, are assumed to apply, without change, at all points in the modeling 

domain. Consistency would call for site selection criteria consistent with the steady 

state assumption; i.e., to the extent possible, sites should perhaps be selected such that 

factors which cause spatial variations in meteorological conditions, are invariant over 

the spatial domain of the application, whatever that might be. Such factors would 

include surface characteristics such as ground cover, surface roughness, the presence 

or absence of water bodies, etc. Similarly, the representativeness of existing thirdparty data bases should be judged, in part, by comparing the surface characteristics in 

the vicinity of the meteorological monitoring site with the surface characteristics that 

generally describe the analysis domain.”21

The presence of buildings surrounding the Otay Mesa station would affect the data (the 

increased surface roughness of the urban setting would be expected to reduce windspeeds). 

AERMOD takes this effect into account by adjusting for surface roughness at the monitoring 

site. When the analysis domain is viewed as a whole, this factor supports the use of the Otay 

Mesa data. 

Conclusion 

The single most important factor in determining representativeness, proximity to the source, 

strongly supports a determination that the Otay Mesa meteorological data are representative. 

Other factors that support this determination are the similar distances to major terrain features, 

including the nearby mountains and the ocean. 

In conclusion, the Applicant believes that the use of five years of meteorological data from 

the Otay Mesa station is fully consistent with EPA guidance, is fully consistent with EPA past 

practice, and is adequately representative of the Project area. 

 

21 EPA, Meteorological Monitoring Guidance for Regulatory Modeling Applications. p. 3-2 
Gerardo Rios -15- March 7, 2012 

If you have any questions regarding this information, please contact the Applicant’s 

representative David Jenkins at (317) 431-1004, or Gary Rubenstein or me at (916) 444-6666. 

Sincerely, 

Steve Hill 

cc: John McKinsey, Stoel Rives LLP 

David Jenkins, Apex Power Group 

 Steve Moore, San Diego Air Pollution Control District 

Attachments 

Enclosure: CD 
Otay Mesa – Annual, 2004 
Otay Mesa – 1st Quarter, 2004 
Otay Mesa – 2nd Quarter, 2004 
Otay Mesa – 3rd Quarter, 2004 
Otay Mesa – 4th Quarter, 2004 
Otay Mesa – Annual, 2005 
Otay Mesa – 1st Quarter, 2005 
Otay Mesa – 2nd Quarter, 2005 
Otay Mesa – 3rd Quarter, 2005 
Otay Mesa – 4th Quarter, 2005 
Otay Mesa – Annual, 2006 
Otay Mesa – 1st Quarter, 2006 
Otay Mesa – 2nd Quarter, 2006 
Otay Mesa – 3rd Quarter, 2006 
Otay Mesa – 4th Quarter, 2006 
Otay Mesa – Annual, 2007 
Otay Mesa – 1st Quarter, 2007 
Otay Mesa – 2nd Quarter, 2007 
Otay Mesa – 3rd Quarter, 2007 
Otay Mesa – 4th Quarter, 2007 
Otay Mesa – Annual, 2008 
Otay Mesa – 1st Quarter, 2008 
Otay Mesa – 2nd Quarter, 2008 
Otay Mesa – 3rd Quarter, 2008 
Otay Mesa – 4th Quarter, 2008