# MEMORANDUM To: Environmental Protection Agency, Region 6 and Office ofAir Quality Planning & Standards From: H. Andrew Gray, Ph.D., Gray Sky Solutions Date : January 7, 2016 

### Re: Review of NRG's modeling of Parish S02 emissions I recently reviewed the S0 2 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, includ ing 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 to 40 CFR Part 51, Applicability of Appendix W Modeling Guidance for the 1 -hour S02 National Ambient Air Quality Standard (August 23, 2610); Modeling Guidance for 50 2 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 mode led design va l ue for the smaller stack (6.7 m diameter) was 10 percent higher than the design value for the larger stack (diameter= 7.315 m). 1deviation= 47 K). NRG's stack velocity ranged from 0 to 37.4 m/s for Unit 5 (the zero velocity values were during shutdown periods), with a three-year average of 23.7 m/s (not including zero emission hours; standard deviation = 7 m/s). Comparing AERMOD model results using constant stack temperature and velocity to NRG's variable stack data demonstrated that the use of constant stack data has a negligible effect ofthe model results. 4 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 meteorolog ical 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 ofthe 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 meteorological 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 ofthe 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 to 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 mode led design value 502 concentration from 49.33 1-1g/m 3 to 49.47 1-1g/m 3 (a difference of less than 0.5 percent). The three-year maximum 502 concentration increased from 98
.20 1-1g/m 3 to 98.46 1-1g/m 3

. 7 http://www.tceq.state.tx. us/permitting/airImodeling/aermod -datasets.html 2surface characteristics to be input, such as albedo , Bowen ratio , and surface roughness. NRG used the AERSURFACE program to develop this surface cha racteristic data for input to AERMET. NRG supplemented the AERSURFACE calculations with their own "Wedge " approach to compute the surface roughness data (using NRG 's own programs , CR_BLN , FIX-LU , and CLC

_ZO)
. NRG used the Texas land-use data set8 , 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 faci lity, which is 16 km to the south of the Sugar Land Ai rport met tower that NRG relied upon for surface meteorological data. 9 According to the AERSUFACE User's Guide 10, however, "[t]he coordinates input to AERSURFACE [for the site center] should be based on the locat ion of the meteorolog ical tower (measurement site) for the meteorological data to be processed w ith 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, wh i le 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 Gu ide strongly cautions against using the incorrect location for the center point for surface characteristics:

"NOTE: S i gnificant 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 texas se N LCD 092800 flat.bi n 9 NR G**~cl de** **d** the month; of M a y an d S eptember in its summer classification (the defa ult monthly assign ments for summer are June t hrough August}
. 10 AERS UR F ACE Use r's Gui de, U
. S. Environmenta l Protectio n Agency
. Offi ce of Ai r Qu ality Plann ing an d S tanda rds. Resea rch Triangle Park, North Carolina, EPA-454/B-08-001, Jan uary 2008
. 3up to a few kilometers are common, which could significantly compromise the representativeness of AERSURFACE calculations , especially for surface roughness. Users are encouraged to verify the coordinates of the meteorological tower before applying AERSURFACE ." (emphasis added)
. Here, NRG 's selection of the Parish location as the center of the study area , rather than the recommended location of the meteorological tower (Sugar Land Airport) , where the surface data were measured , had a substantia l 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 (z0) values that are input to AERMET are a weighted average of the NLCD92 z0 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
. 1 1 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 1a) , 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 roughn ess data i n Fig u re lb follows the defa ul t monthly assignments
. 4Surface Roughness (z0 }, using Parish (NRG} 0.6 0.5 0.4 0.3 0.2 

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0 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC • Month, Sector Figure 1a. Surface Roughness 

### (zo) 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



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# I JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV • Month, Sector 111111111111 DEC Figure 1b. 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 resu lted 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 (i ncluding the surface 5rough ness values f rom Figure 1a) with an AERMET data set developed using the same surface data and upper air meteorological data, but using Sugar Land Airport as the center point (and the resulting surface roughness heights shown in Figure 1 b) reveals that the NRG data exhibited s ignificantly higher mixing he ights (but identical wind speeds and temperatures). The prevalent higher mixing heights computed by AERMET in NRG 's modeling analysis 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 A ERMET 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 BP I P program ( which uti lizes the PRIME algorithm) to develop the necessary bu ilding 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 con centrations
. 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. Theref ore 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 S0 2 that may also impact the recepto r locations
. The background conce ntrations are added to the hourly modeled concentrations within AERMOD
. If backg ro und concentrations are used and the res ulting 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 ot her t han the surface characteristics
. Testing of the AERMET preprocessing program showed that increasi ng the anemometer height from 7.62 m to 10
.0 m resulted in slightly lower mechanica l mixing heights {the convective mixing heights were unchanged). 13 The three - year maximum concentration estimated by AERMOD using the Sugar Land Airport AER M ET data was 12 percent higher th an the three-yea r maxim um concentration estimated by AER M OD using NRG's AERM ET data. 14 The stack heights exceed th e minim um height for wh ich building downwas h has an effect on th e tra nspo rt of the emitted plumes. 6concentrations are compared with the acceptable 1-hour 802 NAAQS level (75 ppb = 196
.2 !Jg lm\ then the background effectively lowers the acceptable impact from the modeled source(s). The background concentrations are supposed to represent "clean" up-wind conditions. Measurements from a nearby upwind area can be used to determine appropriate background levels
. Sometimes, a baseline corresponding to the typical lower-end 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 _802 and CRBG_S02) from data collected at Italy TX, located about 320 km WNW of the Parish facility. 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 802 concentrations ranged from 1.4 to 16
.9 1Jg/m3 , with an average of 4.9 1Jg/m3

. Despite the occasional higher va lues , overall these background levels are significantly lower than the lowest measured design value concentration for 2011-2103 in Texas15 (7 .8 1Jg/m3 , measured in El Paso County). 16 Background concentrations are added to the impacts from the modeled sou rces . In terms of a demonstration of attainment with the 1-hour 802 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 !Jg lm\ in which case the selection of the background level will have a direct impact on the predicted NAAQS comp liance.

18 16 14 12 10 8 6 4 NRG Background $0 2 Concentration

# ~ 

# I ll I ll I l l 1 1 1 1 1 1 

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# Ill 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 • Winter • Spring • Summer Fall Figure 2. Background 502 Concentrations Used in the NRG Modeling

15 http:/ /www.epa.gov/airtrends/values.html 16 The median ofthe 48 seasonally and diurnally varying NRG background concentrations is 4.11lg/m 3

. Only 15 out of the 48 values are higher than the El Paso County value of 7.81lg/m 3

. 7Conclusions To evaluate the NRG modeling of the Parish facility , I used EPA's modeling guidance and the AERMOD dispersion model itself to assess the model's sensitivity to a number 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 S02concentration for Parish Units 5-8 was 163
.2 1Jg/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 1Jg/m3 , suggesting that a nonattainment designation for Parish is appropriate. In addition , ifthe 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 1Jglm 3 , which would exceed the allowable 1-hour S02 NAAQS level (196.2 1Jg/m3) . 8NRG 's model results (desig n value= 168.6 1Jglm3 , total facility, including background) suggest that the Parish facility would not cause a violation ofthe 1-hour S02 NAAQS
. As demonstrated in this analysis, however, using the appropriate stack diameter for Un it 7 and the recommended center location (Sugar Land Airport) during the development of the surface characteristics would increase the modeled design value well beyond the acceptable NAAQS level. Making these changes would also therefore change the 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.

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