January 7> 2016 

Guy Donaldson> Chief 

Air Planning Section 

U.S. Envirorunental Protection Agency, Region 6 

1445 Ross Avenue, Suite 1200 

Dallas> Texas 75202-2733 Re: Review of Sulfur Dioxide Air Dispersion Modeling Submitted by NRG Power 

LLC for the W.A. Parish Electric Generating Station 

Dear Section Chief Donaldson: 

On September 17, 2015, and again on December 14, 2015, Sierra Club submitted 

air dispersion modeling conducted by Wingra Engineering, S.C. that demonstrated that 

sulfur dioxide ("S02") emissions from the W.A. Parish Electric Generating Station in 

Thompsons, Texas cause downwind S02 ambient air concentrations to exceed the 75 

parts per billion National Ambient Air Quality Standard ("NAAQS"), which translates to 

196.2 micrograms per cubic meter ("Jlg/m3'} In particular> the modeling demonstrated 

that the W .A. Parish plant causes downwind S02 concentrations as high as 231.2 Jlg/m3. 

Accordingly> the area surrounding W.A. Parish should be designated nonattairunent 

under EPA's 1-hour S02 NAAQS. 

On July 24> 2015> however, NRG Texas Power submitted modeling conducted by 

a third-party consultant> suggesting that the W.A. Parish power plant does not cause 

exceedances of the S02 NAAQS, and therefore should not be designated as 

nonattairunent. 

Enclosed, please find the results of an independent review ofNRG>s modeling 

analyses conducted by H. Andrew Gray, Ph.D., of Gray Sky Solutions. Dr. Gray's 

review concludes that NRG's modeling analysis relies on incorrect stack parameters and 

inappropriate surface data inputs. Correcting these errors results in S02 concentrations 

that are approximately 35% higher than NRG's modeling predicts. In fact, using the 

appropriate stack parameters and the recommended surface characteristics would increase 
the modeled design value to at least 221 !lg/m3- well beyond the acceptable NAAQS 

level. As Sierra Club's previously submitted modeling demonstrates, those exceedances 

are even greater when nearby sources of S02 are taken into account. Accordingly, the 

area surrounding W.A. Parish should be designated nonattainment under the NAAQS. 

We urge EPA to consider this information as it undertakes area designations in 

Texas for the 2010 revised primary S02 NAAQS. This information is being provided to 

both EPA's Office of Air Quality Planning and Standards and Region 6. In the 

meantime, please let me know if I can provide any additional information. 

Thank you for your attention to and consideration of this matter, and please do not 

hesitate to contact me if you would like to discuss further. 

Joshua: Smith 

Staff A mey 

Sierra Club 

85 Second St., Second Floor 

San Francisco, CA 94108 

Phone: (415) 977-5560 

Fax: (415) 977-5793 

joshua.smith@sierraclub.org 
Re: Review of NRG's modeling of Parish S02 emissions 

I recently reviewed the S02 modeling analysis conducted by NRG for the W.A. Parish 

Electric Generating Station located in Thompsons, Texas. The modeling analysis was 

performed using the AERMOD dispersion model (and its meteorological preprocessors 

AERMINUTE and AERMOD). The review considered whether the appropriate data 

were used and whether the recommended modeling protocols were followed. 1 A 

number of sensitivity tests were performed using NRG modeling files to support my 

observations . 

A set of modeling files2 was obtained (but no summary report was provided), which 

included input and output files for AERMOD and a number of preprocessors, including 

AERMINUTE, AERMET, AERSURFACE, AERMAP, and BPIP. The modeling process, 

assumptions, input data, and outputs were examined. A brief summary of my findings is 

presented below. 

Stack parameters 

NRG modeled Parish Unit 7 with a stack diameter of 7.315 m (matching Units 5 and 6). 

Visual inspection using satellite images, however, indicates that the Unit 7 stack has a 

smaller diameter than either Unit 5 or 6; the diameter of the Unit 7 stack is 

approximately 6. 7 m. As discussed below, the use of a larger diameter within AERMOD 

increases the estimated momentum flux from the stack which results in a higher 

computed plume rise, and materially lower modeled peak ambient concentrations for 

this unit.3 

NRG used variable stack temperatures and velocities, which varied hourly depending 

on the emission rate and ambient conditions. For example, NRG's stack temperature 

for Unit 5 varied from 266 to 496 K, with a three-year average of 416 K (standard 

1 AERMOD User's Guide; AERMOD Implementation Guide; USEPA Appendix W t o 40 CFR Part 51, Applicability of 

Appendix W M odeling Guidance for the 1-hour S02 National Ambient Air Quality Standard (August 23, 2010); 

Modeling Guidance for S02 NAAQS Designations; and USEPA S02 NAAQS Designations Technical Assistance 

Document (December 2013). 

2 Parish Modeling Archive, dated September 2015 (files transferred November 20, 2015). 

3 Comparison of model results for Unit 7 using stack diameters of 6.7 m and 7.315 m showed that the modeled 

design value for t he smaller stack (6.7 m diameter) was 10 percent higher than the design value for the larger st ack 

(diameter= 7.315 m). 

1 
Receptors 

NRG used a set of gridded receptors with 100 m spacing in the area surrounding the 

peak concentrations (with additional coarser spaced receptors further away from the 

source).5 NRG used the AERMAP preprocessor program to determine receptor 

elevations. NRG used a flagpole height of 0.0 m for all receptors. 

Testing of the AERMOD model using different flagpole heights (1.5 m and 0.0 m) 

showed that there was very little difference in the estimated peak concentrations.6 

Meteorological Data 

The meteorological preprocessor, AERMET, requires hourly surface meteorological 

data and upper air wind and temperature profile data as input. In addition, the 

AERMINUTE program is used to augment the hourly wind data with one-minute ASOS 

wind data. NRG used hourly surface data and one-minute ASOS wind data measured 

at the Houston Sugar Land Memorial Airport, located 16 km north of the Parish facility. 

NRG also used the upper air sounding data from the Lake Charles, LA Airport. These 

two airports are recommended by TCEQ as the source of AERMET meteo"rological 

input data for sources in Fort Bend County.7 

AERMET computes a number of micrometeorological parameters that are required by 

AERMOD, such as the friction velocity, Monin-Obukhov length, convective velocity 

scale, temperature scale, mixing height, and surface heat flux. In addition to the hourly 

wind speed, wind direction, temperature and cloud cover data, AERMET requires 

4 The modeled design value for Unit 5 using a constant stack temperature (439.8 K) and velocity (25.9 m/s) was 

within 0.02 percent of the modeled design value for Unit 5 using NRG's variable stack data. The modeled threeyear maximum concentration was approximately 7 percent lower when using the constant stack data relative t o 

the modeled maximum using variable stack data. 

5 NRG used a total of 6,909 receptors. 

6 AERMOD was run for Parish Unit 5 using both 0.0 m and 1.5 m for the receptor flagpole heights. Raising the 

flagpole height from 0.0 m to 1.5 m increased the modeled design value 502 concentration from 49.33 llg/m3 to 

49.47 J.1g/m3 (a difference of less than 0.5 percent). The three-year maximum 502 concentration increased from 

98.20 jlg/m3 to 98.46 Jlg/m3• 

7 http://www. t ceq.state. tx.us/ permitting/air /modeling/aermod-datasets.html 

2 
together with the surface roughness assignment table (z0 vs. USGS NLCD92 land-use 

categories) from AERSURFACE to develop weighted average monthly surface 

roughness values for input to AERMET. For its center of the study area in its 

AERSURFACE calculations, NRG used the location of the Parish facility, which is 16 

km to the south of the Sugar Land Airport met tower that NRG relied upon for surface 

meteorological data.9 

According to the AERSUFACE User's Guide10, however, "[t]he coordinates input to 

AERSURFACE [for the site center] should be based on the location of the 

meteorological tower (measurement site) for the meteorological data to be processed 

with the output surface characteristics." The use of meteorological and surface 

roughness data from different locations creates a mismatch between the measured 

wind and temperature data and the land use data. The AERSURFACE User's Guide 

acknowledges the difficulty of establishing representative data for the modeled region: 

"Determining effective surface characteristics for the purpose of 

processing meteorological data for use with the AERMOD model presents 

many challenges. AERMOD is a steady-state plume model which 

assumes spatially uniform meteorological conditions across the modeling 

domain for each hour of meteorology, while land cover across the domain 

is typically very heterogeneous. A sound understanding of the important 

physical processes represented in the AERMOD model algorithms 

(Cimorelli, et al., 2004) and the sensitivity of those algorithms to surface 

characteristics is needed in order to properly interpret the available data and make an appropriate determination." 

The AERSURFACE User's Guide strongly cautions against using the incorrect 

location for the center point for surface characteristics: 

"NOTE: Significant discrepancies have been identified between station 

coordinates reported by the National Climatic Data Center (NCDC) and 

the actual location of the meteorological instrument tower for National 

Weather Service (NWS) sites. Discrepancies of several hundred meters 

8 t exas se N LCD 092800 flat.bin 

9 NRG t he of May and September in its summer classification (the default monthly assignments 

for summer are June through August). 

10 AERSURFACE User's Guide, U.S. Environmental Protection Agency. Office of Air Quality Planning and Standards. 

Research Triangle Park, North Carolina, EPA-454/B-08-001, January 2008. 

3 
surface data were measured, had a substantial effect on the computation of the surface 

characteristics that were input to AERMET. The Bowen ratios computed by NRG, using 

Parish as the center point, are between 25 and 60 percent higher than would be 

obtained using Sugar Land as the center point in all months except January, June and 

July. In those three months, in which NRG selected the dry option (all other months 

were wet or average), NRG's Bowen ratios are 30 to 40 percent higher than would be 

obtained using Sugar Land (using the average option). The monthly albedo values 

estimated by NRG were all slightly lower than those obtained with Sugar Land Airport 

as the center point. However, the most significant differences between using Parish 

and Sugar Land as the center point, are the resulting surface roughness lengths. 

The surface roughness length (zo) values that are input to AERMET are a weighted 

average of the NLCD92 zo values, weighted by the proportion of land use categories in 

each sector. The weighted average surface roughness values that NRG input to 

AERMET are much higher than would have been be obtained if the Sugar Land Airport 

location were used instead, as shown in Figures 1a and 1b.11 The average surface 

roughness length across the Sugar Land data set (Figure 1b) is 0.09 m, whereas NRG's 

average surface roughness, using Parish as the center point (Figure 1 a), is 0.25 m, 

almost 3 times as large as the Sugar Land average, with many of the Parish (NRG) 

values being more than ten times the corresponding Sugar Land values. 

11 The surface roughness data in Figure lb follows the default monthly assignments. 

4 
0.3 

0.2 

Ill Ill Ill Ill Ill Ill Ill Ill Ill Ill Ill Ill 

0.1 

0 

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 

• Month, Sector 

Figure 1 a. Surface Roughness (z0) Computed by NRG, and input to AERMET 

(grouped by month and sector), using Parish as the Center Point. 

Surface Roughness (z0), using Sugar Land Airport 

0.6 

0.5 

0.4 

0.3 

0.2 

0

: llldill1111 Ill dillt111 Ill tiiiJIJIIJJitiJJJIJJt llltJIIJJiil 11 1111 

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV 

• Month, Sector 

llhlllhl ll 

DEC 

Figure 1 b. Surface Roughness (z0) (grouped by month and sector), using Sugar 

Land Airport as the Center Point. 

NRG's selection of mismatched surface and meteorological data had a significant effect 

on the dispersion model results. Higher surface roughness lengths resulted in higher 

estimated mixing heights (due to increased vertical dispersion) within AERMET, which 

in turn, resulted in lower modeled S02 concentrations within AERMOD. Comparison of 

NRG's AERMET data developed using Parish as the center point (including the surface 

5 
using Parish as the center point during the development of the surface characteristics 

resulted in much lower modeled peak concentration impacts than would have been 

obtained if Sugar Land Airport were used as the center point. As a test, the AERMOD 

dispersion model was run (for Parish Unit 5) once using NRG's AERMET output data 

and then a second time using an AERMET data set that was developed using Sugar 

Land Airport as the center point.12 The AERMOD modeling, using the lower mixing 

heights (which are lower due to a distinctly different set of surface characteristics, and to 

a far lesser extent due to a slightly higher anemometer height), resulted in a design 

value S02 concentration that was 31 percent higher than when using NRG's AERMET 

data.13 

Building Downwash 

NRG used the BPIP program (which utilizes the PRIME algorithm) to develop the 

necessary building downwash parameters for each of the modeled Parish units. 

Testing of the model for Parish Units 5 and 7 with and without building downwash 

showed that there were no differences between modeled concentrations.14 The 

modeled design values and all other peak concentrations for the modeling without 

building downwash effects were completely identical to the modeled results with the 

building downwash included. Therefore the modeling of building downwash effects is 

not needed for this model application. 

Background Concentrations 

Background concentrations can be provided to the AERMOD model to account for nonmodeled sources of S02 that may also impact the receptor locations. The background 

concentrations are added to the hourly modeled concentrations within AERMOD. If 

background concentrations are used and the resulting modeled design value 

12 The anemometer height was set to 10.0 m for the Sugar Land AERMET runs, and 7.62 m for the NRG AERMET 

runs. All other input data were identical other than the surface characteristics. Testing of the AERMET 

preprocessing program showed that increasing the anemometer height from 7.62 m to 10.0 m resulted in slightly 

lower mechanical mixing heights (the convective mixing heights were unchanged). 

13 The three-year maximum concentration estimated by AERMOD using the Sugar Land Airport AERMET data was 

12 percent higher than the three-year maximum concentration estimated by AERMOD using NRG's AERMET data. 

14 The stack heights exceed the minimum height for which building downwash has an effect on the transport of 

the emitted plumes. 

6 
concentrations can be developed from monitoring from the edge of a "polluted" area. 

Wind direction data can also be used to isolate measured concentrations from periods 

when there was very little contribution from nearby sources. 

NRG used seasonally variable diurnal profiles for the background concentrations, as 

shown in Figure 2. The background concentration profiles were developed (using 

NRG's own programs, PREP _S02 and CRBG_S02) from data collected at Italy TX, 

located about 320 km WNW of the Parish faci lity. As can be seen in Figure 2, the NRG 

diurnal profiles include a significant amount of variation between day and night, 

especially in the winter and autumn months. The background S02 concentrations 

ranged from 1.4 to 16.9 IJQ/m3, with an average of 4.9 IJQ/m3. Despite the occasional 

higher values, overall these background levels are significantly lower than the lowest 

measured design value concentration for 2011-2103 in Texas 15 (7.8 1Jg/m3, measured in 

El Paso County).16 

Background concentrations are added to the impacts from the modeled sources. In 

terms of a demonstration of attainment with the 1-hour S02 NAAQS, the choice of 

background levels is only important if the design value for the modeled sources is just 

below the NAAQS level (75 ppb = 196.2 1-Jglm\ in which case the selection of the 

background level will have a direct impact on the predicted NAAQS compliance. 

18 

16 

14 

12 

10 

8 

6 ~ I 

1 

I I 

2 3 

I I I 

4 5 6 7 

NRG Background 502 Concentration 

I I I I 

8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 

• Winter Spring Summer Fall 

Figure 2. Background 502 Concentrations Used in the NRG Modeling 

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

I 

24 

16 The median of the 48 seasonally and diurnally varying NRG background concentrations is 4.lllg/m3. Only 15 out 

of the 48 values are higher than the El Paso County value of 7.8 11g/m3• 

7 
of input parameters and determine whether a change in the input parameter would 

make any difference to the model results (or the conclusions drawn from those model 

results). For some of the parameters evaluated, a change in the input value has a 

negligible effect on the modeled concentrations. For example, adjusting the receptor 

flagpole heights from 0 to 1.5 m has a very small effect on the modeled S02 

concentrations. Similarly, the use of variable stack temperature and velocity also had a 

negligible impact on the results. 

Some of NRG's inputs, however, were found to have a more significant effect on the 

model results. For example, using a stack diameter that is too large (7.315 m rather 

than 6.7 m) was shown to underpredict the Unit 7 stack's contribution to the modeled 

design value by about 10 percent. NRG's modeled design value for the total Parish 

facility will therefore be underpredicted by about 3 percent due to the larger Unit 7 stack 

diameter. 

The selection of the center location for the computation of surface characteristics by the 

AERSURFACE processor has a far greater effect on the model results than any of the 

other input parameters tested. The choice of the Parish location, rather than the 

recommended location (Sugar Land Airport), had a considerable effect on the estimated 

surface characteristics, especially the weighted average surface roughness heights. It 

was found that using the Parish location as the center point resulted in mixing heights 

that were much too high, which resulted in a significant underprediction of modeled S02 

concentrations. · 

The NRG modeled design value S02 concentration for Parish Units 5-8 was 163.2 

j.Jg/m3. If the Sugar Land Airport location had been used as the center point during the 

development of the surface characteristics, as recommended in the AERSURFACE 

guidelines, the modeled design value for Units 5-8 would be approximately 31 percent 

higher. Indeed, the use of the surface characteristics recommended by EPA guidelines 

results in a modeled design value of approximately 214.5 lJg/m3, suggesting that a 

nonattainment designation for Parish is appropriate. In addition, if the Unit 7 stack was 

modeled with the correct diameter (6.7 m rather than 7.315 m), then the modeled 

design value for the Parish facility would increase by another 3 percent. Making these 

two changes in the inputs to the model would result in a greater than 35 percent 

increase in the modeled design value concentration. It is estimated that the modeled 

design value concentration for Parish Units 5-8 (not including background) would 

increase to 221 lJg/m3, which would exceed the allowable 1-hour S02 NAAQS level 

(196.2 lJglm\ 

8 
conclusion regarding the source

s compliance with the NAAQS. It should be concluded 

that emissions from the Parish source, on their own, will likely cause a violation of the 1-

hour S02 NAAQS. 

9