EXHIBIT 7: G. Hoffnagle, TRC Environmental 

Corporation, Evaluation of Craig 

BART Modeling for Regional Haze 

Analysis 

to 

Tri-State Generation and Transmission Association, Inc.’s 

Detailed Comments to EPA Proposed Rule Published 

at 77 Fed. Reg. 18052 to 18098 

Submitted May 25, 2012 

Docket ID No. EPA-R08-OAR-2011-0770 
Evaluation of Craig BART Modeling for Regional Haze Analysis 

Rebuttal Report by Gale F. Hoffnagle, Sr. Vice President and Technical Director 

TRC Environmental Corporation 

OVERVIEW 

The intent of this report is to discuss the inaccuracy inherent in the air quality modeling for 

visibility impact of the Craig Station at the Mount Zirkel Wilderness Area and to address the 

nitrate contribution to visibility impairment and the role of Northwest Colorado NOx emissions 

in visibility extinction in Colorado Class I Areas. I adopt and incorporate the general comments 

that I made in my first report and in my testimony before the Air Quality Control Commission in 

connection with the November 18 – 19, 2010 hearing on BART issues. 

Reality Check 

The 5 year average visibility from the IMPROVE monitoring data collected at Mount Zirkel and 

the WRAP modeling in visibility extinction at Mount Zirkel (see technical Support Document 

for Mount Zirkel) is as follows: 

TABLE 1 (in Inverse Megameters) 

Mount Zirkel 20% Best Days 20% Worst Days 

Measured (TOTAL) 11.7 Mm-1 28.6 Mm-1 

Measured Nitrates 0.51 Mm-1 2.2 Mm-1 

Natural Visibility (EPA) 10.56 Mm-1 19.04 Mm-1 

Figure 1: Total and Component Extinction at Mount Zirkel (APCD TSD on Mount 

Zirkel); note, extinction from nitrates (red bar) is a minor contributor. 

 TRI-STATE 

(May 25, 2012) 

 Exhibit 7 
2 

 WRAP Nitrates Modeling 

The Western Regional Air Quality Partnership (WRAP) provided modeling of the entire West to 

evaluate the sources of contribution to the nitrate visibility extinction at Mt. Zirkel. Those 

results show the sources sequentially, as follows: 

– 97.8% the Total is Anthropogenic 0.50 Mm-1 2.15 Mm-1 

– 41.5% of “Anthro” is from Colorado 0.21 Mm-1 0.89 Mm-1 

– 79.2% of Colorado share are Point Sources 0.16 Mm-1 0.82 Mm-1 

 71.3% of Colorado Point Sources are 0.12 Mm-1 0.59 Mm-1 

 External Combustion 

Use of Inverse Megameters 

As I testified at the November hearing, we use inverse megameters to make it possible to linear 

comparison of extinction values which are less than 1 Deciview, i.e. negative numbers. The use 

of Deciviews also makes it difficult to compare modeled to measured values. Figure 2 is offered 

to explain to the reader this relationship. One Deciview equals 10 Mm-1 and a visual range of 

400 kilometers, a longer visual range than is possible given the natural scattering by atmospheric 

gases. For comparison, 10 Inverse Megameters is equal to 1 Deciview and represents a visual 

range of 400 kilometers. When one looks at the above listing of Colorado’s share of visibility 

extinction at Mount Zirkel as modeled by the WRAP, one sees that all of the values of nitrate 

extinction are less than 1 Deciview and thus will not by themselves affect visibility. 

Figure 2: Relationship of Extinction, Deciviews and Visual range (NPS Introduction to 

Visibility) 

Eliminating NOx Emissions from Colorado Power Plants will not be Humanly Perceptible 

By the WRAP model calculations which are listed at the top of this page, above, the largest 

potential contribution from Colorado power plant sources is 0.59 inverse megameters (because 

the Deciview is a log number when visibility impairment is very small the Deciviews go 

negative thus the equivalent of 0.59 Mm-1 is -28.3 Deciviews). If we take into account that the 

“natural visibility” based on EPA Guidance is 0.55 Deciviews (10.56 Mm-1) for the 20% Best 
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days and 6.44 Deciviews (19.04 Mm1-) for the 20% Worst days, the WRAP’s modeling 

concludes that power plant contribution of nitrates is substantially smaller. Under the WRAP’s 

modeling, power plants derived nitrates are therefore responsible for 22.9% of the total nitrates 

and 1% of the total visibility impairment on the Best days and 2% of the visibility impairment on 

the Worst days. This value would be for all power plants in Colorado, not just Craig Station. 

These WRAP model results led the APCD to report in February 2009 to conclude that 

“Removing all Colorado SO2 and NOx emissions yields, at most, ~1 Deciview of visibility 

improvement”. 

Craig Station cannot possibly be responsible for all of the power plant-related visibility impact at 

Mount Zirkel Wilderness Area; for example, work by the APCD indicates that the Hayden 

Station is tied to an equivalent modeled impact at Mount Zirkel. Plus, there are other power 

plant emissions in Colorado. Even by controlling 75% of the emissions at Craig by putting on 

SCR, there would only be calculated to be reductions of 0.03 Mm-1 on the 20% Best days and 

0.15 Mm-1 of reductions on the 20% Worst days, if Craig were responsible for all the power 

plant impact at Mount Zirkel, but that cannot be the case, because there are other Colorado 

power plant emissions. These changes would not be observable at Mount Zirkel and are less 

than the natural visibility reduction of the atmosphere without pollutants. 

The Model Options 

The Interagency Workgroup on Air Quality Modeling (IWAQM) guidance (called FLAG) and 

the Colorado protocol are based upon conservative principals of modeling analysis because of 

their application to a wide number of sources and situations. The reasons that the modeling may 

over estimate the measured concentrations can be found among the conservative assumptions 

that are inherent in the proscribed techniques. Several factors which I believe should be applied 

to the modeling of NOx emissions from any source, as follows: 

Measured ammonia concentrations: 

 Nitrate partitioning: 

 Ammonia limiting Method: 

 Puff splitting: 

 Visibility calculations method: 

 Ozone Concentration: 

As I will show, these improvements and perhaps more are necessary in order to give decision 

makers reasonable understanding of the issues. The other option for decision makers is to 
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recognize the tendency for CALPUFF to over predict impacts and thus the benefits of emission 

reductions and to temper reliance on such model results. 

Measured Versus Modeled Visibility Impacts 

As I suggested in my November testimony, I have compared measured visibility impairment 

from the IMPROVE monitoring network to the CALPUFF modeled visibility impairment at the 

Mount Zirkel Wilderness Area. This shows an indication of the extent of the over predictive 

nature of the current CALPUFF modeling performed by APCD. I understand that under the 

auspices of APCD and the Regional Air Quality Counsel, a similar exercise is conducted in 

ozone modeling where the modeled ozone concentrations are compared to the monitored ozone 

values for those same days and the model is calibrated to the monitored data to help improve the 

model performance. 

The measured data come from the IMPROVE website and consist of the measured extinction 

coefficient (Bext in Mm-1) to compare “Total Measured” visibility impairment to the “Total 

Modeled” visibility impairment. Also obtained was the percentage of nitrate of the total 

particulate (these are given on the web site in micrograms /cubic meter). Measurements are made 

every third day. 

2005 APCD Modeling of Craig 1 and 2 

The modeled data for the 2005 APCD modeling come from page 51 of the Technical Support 

Document “BART CALPUFF Class I Federal Area individual Source Attribution......Craig 

Station Units 1 and 2”. This lists the 25 highest days of modeled visibility impact for 2002 

including the day, receptor, Total modeled Deciviews, background modeled Deciviews, Delta 

Deciviews and the % Nitrate contributing to the impairment. 

 The first result to review is the measured versus modeled data for Total Visibility impairment. 

That is done as shown in Figure 3, below. Figure 3 shows that the CALPUFF modeling for 

Craig units 1 and 2 cause impairment equal to a major component of the actual measured 

impairment shown in the data from the IMPROVE data base. Figure 3 shows the total visibility 

extinction from all sources of impairment (Total Visibility Impairment at the IMPROVE site). 

Recall the bar graph on page one above tells us the WRAP analysis concludes a small fraction of 

the total visibility impairment is attributed to nitrates, yet Figure 3 reveals that the CALPUFF 

modeling would have us believe that Craig Units 1 and 2 are a major contributor. 
5 

The results of the overview comparison show that the 25 highest modeled days of Craig impact 

occur in the cold weather season as expected due to the conditions that are necessary for NOx to 

convert to nitrates (cooler atmospheric temperatures and moisture), and not in the warm weather 

season when the maximum visibility impairment actually occurs. Thus, even if the CALPUFF 

modeling were more accurate, reductions in Craig NOx emissions would not be projected to 

affect in any meaningful way the worst case visibility impairment. It should be noted that the 

magnitude of the modeled Craig impairment is similar to the measured values for the days when 

the modeled values are the maximum 25 modeled values, leaving no room for other sources to 

make contributions. As shown above at the top of page 2, the WRAP modeling states that all 

utility sources would add only 22.9% of the Total extinction. 

Among the 25 maximum modeled days there were ten days when there were simultaneous 

Measured and Modeled value. The comparison of measured and modeled days shows that, on 

average, the modeled accounts for 98% of the measured and ranges from 80% to 140%. 

But, to get a true comparison of the CALPUFF results to IMPROVE monitored data, one must 

zero in on nitrates and that is what is shown in Figure 4. 
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For Nitrates the comparison is even more biased: 

The bias of the modeled data is even more evident when one compares it to the nitrate readings 

in the IMPROVE data. The modeled visibility impact is 11.9 times the measured values for 

nitrates on the 10 days with simultaneous data. There is only one day where the measured 

nitrates even approach the modeled values (not a simultaneous day). As a result the model can be 

estimated to over predict the measured nitrate values by more than a factor of 11 and thus any 

resultant visibility improvement from emission reductions. 

There are two obvious ways in which the above comparisons are not precise. The model predicts 

visibility impacts at receptors throughout the Wilderness Area while the measurement occurs at 

the southern end of the Wilderness Area. A review of the receptor locations for the 25 days 

shows that some are closer to Craig Station, more are further away and two are very close to the 

monitor location. Thus, no appreciable difference between measured and modeled results is 

expected due to location differences. 

The second element of precision is the actual emissions on the 25 days versus the 24 hour 

maximum emissions used in the modeling. Craig Units 1 and two actually emitted more NOx on 
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the 25 days in question than used by APCD in the 2005 modeling. In addition, Craig Station Unit 

3 was also operating at near full capacity on those 25 days. If Craig 3 had been included in that 

modeling the model would have overestimated the Craig visibility impact by a factor of 15 or 

more. 

In 2010, APCD redid the modeling for all the Craig units together. The comparison shows that 

the model overestimates Total visibility impairment by a factor of 1.9 and nitrate visibility 

impairment by a factor of 13.7 for the 7 days with simultaneous measured and modeled values. 

In addition there are 6 days in 2002 when the model predicted that both Craig and Hayden made 

simultaneous impacts on visibility at Mount Zirkel. On those 6 days the model overestimated 

Total impact by a factor of 2 and nitrate impact by a factor of 20.8. 

2010 APCD Modeling of all Three Craig Units 

In 2010 APCD reran the CALPUFF model for all three Craig units. The emissions comparisons 

are as follows: 

Emissions (lbs/hour) 2005 modeling 2010 modeling 

 Modeled Actual Modeled Actual 

Unit 1 1466.8 1595.6 1519.9 1500 

Unit 2 1466.8 1766.5 1489.7 1791 

Unit 3 Not Modeled 1511.4 1679 1279 

Total 2933.6 4874.5 4688.7 4570 

Actual emissions on the top modeled impact days exceeded the modeled emissions in the 2005 

modeling and Craig 3 is missing. If actual emissions were used in the modeling the model over 

prediction would have been higher. The emissions assumptions used in the 2010 CALPUFF 

modeling were close to the level of actual plant wide emissions; therefore the comparisons made 

in this report of “modeled” to “measured” are accurate. 

The top 22 modeled days of each year were evaluated and compared to the measured data for 

those days. The result of this comparison is shown in Figures 5 and 6, below: 
8 

A comparison on the days with measurements is shown as follows: 
9 

It is clear that on many of these days (14 out of 19 days) the Total visibility reduction calculated 

for Craig Station is greater than the total measured extinction, sometimes by startling amounts. 

On average, the modeled Craig extinction is larger than the measured. 

Turning to nitrates the results are as follows: 
10 

Figure 8 shows the days for which we can make a direct comparison. Figure 8 shows the 

modeled visibility extinction significantly over predicts the measured visibility extinction due to 

nitrates. 
11 

The average model over prediction is by a factor of 11.8 assuming that Craig is the only source 

of nitrates on those days which is clearly not correct. As before, the WRAP modeling indicated 

that utility sources were only responsible for 22.9% of the extinction. 

Issues Raised by Dr. Middleton et al. 

Reducing NOx at Craig will improve Visibility 

As demonstrated above, a comparison of the modeled visibility from CALPUFF to the measured 

visibility data from the IMPROVE network show that this is simply not true. Any benefits will 

be insignificant in terms of extinction and no visible change will occur. 

Cumulative Visibility Impacts 

The same over prediction of nitrate extinction occurs at each Class I area. The nitrate 

contribution can be seen in the following figure from the APCD SIP document: 
12 

Figure 9: Total and Component extinction at 6 Colorado IMPROVE sites (APCD SIP) 

Note that all measurements, except Rocky Mountain National Park, have equivalent or less 

nitrates than Mount Zirkel. A major source of Rocky Mountain national park nitrates is known to 

be the East slope and not the West slope. The nitrate portion of visibility impairment at the 

nearer areas to Craig are significantly smaller than at Mount Zirkel, yet the APCD modeling 

yields nearly the same vastly over stated amounts of nitrates at those locations. 

 As distances increase and more terrain obstacles occur between the Craig and the Class I area, 

the model accuracy goes down. Thus, the supposed effects on visibility are not additive. 

Combine the Units 

The modeling reviewed above combines the units and shows no significant combined visibility 

impact. 

Improve Ground Level Ozone 

There is no evidence that the substantially rural Moffat County has any ozone non-attainment 

issue. Colorado started measuring ozone in Rifle and Mesa County in2008. The 4th max values in 

that year were 0.066 and 0.070 respectively. It will take two more years and a change in the 

NAAQS to see if there is a non-attainment issue there. But the Colorado River valley is a far cry 

from the Yampa River valley. As with all ozone ground level issues, tall stacks like Craig’s 

would make only small contributions to any ozone concentrations that do exist in the town of 
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Craig. The implication that Craig NOx reductions will help Mesa County or the East slope with 

attaining the NAAQS is an artifact of over reliance on modeling. 

Reduce Nitrogen Deposition 

Dr. Middleton comments that nitrates are rising in the intermountain West. The data from Mount 

Zirkel reflect this rise, as follows: 

However, the emissions from Craig have not risen over the period of record of the IMPROVE 

station at Mount Zirkel. Even if in the 1995 to 1999 period Craig were the only contributor, 

which it wasn’t, it is clear that the rise in nitrates is not due to Craig. This is especially 

interesting since the modeled years were 2001, 2002 and 2003 when higher nitrates, clearly not 

from Craig existed. In fact, NOx emissions at Craig decreased in 2003 and 2004 with the 

addition of low NOx burners and overfire air which would have led to a decreased portion of the 

above extinction. 
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Conclusion 

The APCD BART CALPUFF modeling for Craig Station overestimates nitrate impact by more 

than a factor of 10 and in some cases by more than a factor of 20. This means that the application 

of controls on nitrogen dioxide emissions at Craig will have no discernable effect on visibility at 

the Mount Zirkel Wilderness Area and by extension on any other Class I area. The chemistry, 

transport and other conservative assumptions in the BART modeling protocol and the Forest 

Service guidance are so conservative as to be of little help to the decision maker in addressing 

real issues. The analysis by WRAP is supported by this analysis of measured visibility values 

from the IMPROVE monitoring data base versus modeled visibility impacts from the CALPUFF 

modeling. There is so little impact of nitrates at Mount Zirkel on visibility that reductions in 

nitrogen oxide emissions do not and cannot improve visibility, i. e. additional controls will not 

change or improve the visibility at Mount Zirkel. Similarly, the impact of Craig on other Class I 

areas, ground level ozone and nitrogen deposition, as posited by Dr. Middleton, is unfounded 

because it is based on faulty modeling or supposition.