ENVIRONMENTAL HEALTH SECTION 

Gold Seal Center, 918 E. Divide Ave . 

NORTH DAKOTA Bismarck, NO 58501-1947 

DEPARTMENT Of HEALTH 701 .328.5200 (fax) 

www.ndhealth.gov 

December 8, 2010 

tvlr. Carl Daly (8P-AR) 

Acting Director, Air Program 

U.S. EPA, Region 8 

1595 Wynkoop Street 

Denver, CO 80202-1129 

Re: Intent to Propose Partial FIP 

Dear Mr. Daly: 

This is in response to your letter of November 29, 2010 which informed the Department that the 

U.S. Environmental Protection Agency made a preliminary determir.ation to implement a partial 

Federal Implementation Plan (FIP) for Regional Haze in North Dakota. We believe the reasons 

listed in your letter for proposing the FIP are fundamentally flav.·ed, not science based, do not 

comply with the Clean Air Act, and serves to usurp State authority ar.d di3crdioll. 

The two facilities mentioned in your letter, M.R. Young Station and Leland Olds St.::tion, both 

have a nameplate generating capacity less than 750 MWe . Therefore, neither facility is subject 

to 40 CFR 51, Appendix Y, Guidelines for BART Determinations under the Regional Haze Rule 

(hereafter BART Guidelines). The BART Guidelines state "For sources other than 750 MW 

power plants, however, states retain the discretion to adopt approaches that differ from the 

guidelines." (70 FR 39158). 

Your letter indicates that adding selective catalytic reduction (SCR) to M.R. Young Station Units 

1 and 2 and Leland Olds Station Unit 2 would improve visibility in Theodore Roosevelt National 

Park by over 1.5 declviews (compared with SNCR). The Clean Air Act, Seeton \69A(g)(2) 

specifies the factors that must be considerd when making a Best Available Retrofit Technology 

(BART) determination. This section lists the fifth factor as "the degree of improvement in 

visibility which may reasonably be anticipated to result from the use of such technology." 

[Emphasis added] . Your estimate of 1.5 deciveiws improvement is flawed in two ways. First, it 

is our understanding that this value is based on the sum of the single source modeling 98th 

percentile results listed in the ND State Implementation Plan for Regional Jlaze (hereafter State 

SIP). As we explained in our Response to Public Comments (copy attached), single source 

modeling for visibility in North Dakota does not provide visibiiity results which may be 

reasonably anticipated to result from application of SCR. Single source modeling in the 

State SIP overpredicts the visibility improvement in North Dakota by as much as a factor of five 

Environmental Health Division of Division of Division of Division of 

Section Chief's Office Air Quality Municipal Facilities Waste Management Water Quality 

701 .328.5150 701.328.5188 701.328.5211 701.328.5166 701 .328.5210 

Printed on recycled paper. 
Mr. Daly 	 2 December 8, 20 10 

(see attachment). The Department has provided modeling results based on inclusion of all 

sources that cause visibility degradation in the ND Class I areas (note that Department's 

cwnulative visibility modeling produced results consistent with those provided by the Western 

Regional Air Partnership (WRAP) for ND Class I areas). This cumulative analysis indicates that 

the application of SCR to these units will only improve the average impairment of the 20% worst 

days by 0.02 deciviews or less for each unit versus selective non-catalytic reduction (SNCR). 

EPA's position of 1.5 deciviews improvement is vastly overstated. 

The Preamble to the BART Guideline states "Because each Class I area is unique, we believe 

states should have flexibility to assess visibility improvements due to BART controls by one or 

more methods, or combination of methods, and we agree with the commenters suggestions to do 

so." (70 FR 39129). It also states "We have pointed out, however, that states should have 

flexibility when evaluating the fifth statutory factor." (40 FR 39129). Further it states "Other 

ways that visibility improvement may be assessed to inform the control decisions would be to 

examine distribution of the daily impacts, determine if the time of year is important (e.g. high 

impacts are occurring during tourist season), consideration of the cost-effectiveness of visibility 

improvements (i.e. the cost per change in deciview), using the measures of deciview 

improvement identified by the State, or simply compare the worst case days for the pre- and 

post-control runs. States may develop other methods as well." (70 FR 39130) [Emphasis 

added]. It appears you are usurping flexibility given the State to evaluate visibility impacts in 

other ways by forcing adoption of the flawed single source 98th percentile modeling resul ts. 

Second, even if one accepts the premise of single source 98th percentile modeling, your estimate 

of 1.5 deciviews improvement from the selection of SCR over SNCR is vastly overstated due to 

several factors, as follows: 

1) 	 The simple addition of single-source visibility results from the M.R. Young 

Station Units 1 and 2 and Leland Olds Station Unit 2 to determine total visibility 

improvement from the selection of SCR over SNCR is flawed because these two 

stations are located a significant distance from each other and have differing stack 

parameters. The maximwn impacts assumed by EPA would be located at 

different receptors and occur on different days. Thus, total visibility improvement 

for the two stations is likely overstated and would never be experienced by an 

observer. 

2) 	 The referenced visibility modeling results for M.R. Young Station and Leland 

Olds Station Unit 2 are based on a natural background reflecting the 20% cleanest 

days. Current EPA guidance allows the use of an annual average natural 

background for visibility improvement analyses. Use of the average background 

would have resulted in a significantly lower visibility improvement prediction for 

each facility. 

3) 	 The referenced visibility modeling results for M.R. Young Station and Leland 

Olds Station Unit 2 were obtained using the old "IMPROVE" algorithm. Based 

on Department experience, use of the new "IMPROVE" algorithm (reflecting 

updated science) would likely have resulted in less predicted visibility change. 
Mr. Daly 3 December 8, 2010 

4) The referenced visibility modeling results were obtained using Calpuff Version 

5.7. The currently recommended version of Calpuff is 5.8 (update was partially 

prompted due to discovery of coding errors in the previous version). 

It is likely that a single source modeling analysis based on the combined M.R. Young Station and 

Leland Olds Unit 2, an annual average natural background, the new IMPROVE algorithm, and 

Calpuff Version 5.8 would have provided a visibility improvement well below 1.5 deciviews, 

and likely below observer perceptibility (1.0 deciview). We note also that the modeled visibility 

improvements referenced by EPA tended to occur during months with lower visitation to 

Theodore Roosevelt National Park. 

Your determination that SCR is a viable option for controlling nitrogen oxides (NOx) emissions 

from the three units is in direct conflict with a recent BACT decision made by state. The 

Department made a BACT determination for the M.R. Young Station that states that SCR (high 

dust, low dust and tail-end) is not technically feasible. Because Leland Olds Unit 2 is the same 

type of boiler (cyclone fired), we believe this determination will apply to Leland Olds Unit 2. 

The process for determining technical feasibility is the same for BART as it is for BACT. 

Obviously, the Department is of the belief that due to the unique Hue gas characteristics from 

burning North Dakota lignite, boiler configuration and unwillingness of SCR vendors to provide 

a catalyst life guarantee make SCR technically infeasible; EPA should concur with the 

Department's determination. EPA cannot make a definitive statement that SCR is technically 

feasible due to the fact that the BACT determination stands on its merits and has not been 

challenged. It will continue to be the controlling decision for M.R. Young Station until 

overturned by the process specified in the Consent Decree. Any proposed FIP that includes SCR 

as the selected control technology would be viewed as an attempt to circumvent the appeal 

process laid out in the Consent Decree for Minnkota. 

The preamble to the BART Guideline States "In addition, while States are not required to follow 

these guidelines for EGUs located at power plants with a generating capacity of less than 750 

MW, based on our analysis detailed below, we believe that States will find these same 

presumptive controls to be highly-cost effective, and to result in a significant degree of visibility 

improvement, for most EGUs greater than 200 MW, regardless of the size of the plant at which 

they are located. A State is free to reach a different conclusion if the State believes that an 

alternative determination is justified based on a consideration of the five statutory factors." 

[Emphasis added] (70 FR 39131). The preamble also states "We agree with the suggestion that 

the use of a comparison threshold, as is done for determining if BART -eligi ble sources should be 

subject to a BART determination, is an appropriate way to evaluate visibility improvement. 

However, we believe the States have flexibility in setting absolute thresholds, target levels 

of improvement must be weighed among the five factors, and States are free to determine 

the weight and significance to be assigned to each factor." [Emphasis added] (70 FR 39129­

39130). 

The Department has made its BART determination after evaluating all five statutory factors. 

Our decision included visibility improvement data based on a cumulative modeling analysis 

which we believe is more consistent with the Clean Air Act than the results from the single 
Mr. Daly 	 4 December 8, 2010 

source modeling methodology. As stated in the BART Guideline "You have flexibility to assess 

visibility improvements due to BART controls by one or more methods. You may consider the 

frequency, magnitude, and duration components of improvement. Suggestions [emphasis 

added] for making the detennination are: 

- Compare the 98th percentile day for the pre- and post-control runs." (70 FR 39170). 

It appears EPA is trying to limit the visibility analysis methods available to the State to only 

those suggested in the BART Guideline. This is contrary to statements in the preamble. The 

guideline clearly allows us to use other visibility modeling data especially since neither source is 

subject to BART Guidelines. 

We are also confused on how you arrived at 17,000 tons/yr of reduction from the use of SCR 

versus SNCR. Our SIP suggests approximately 12,000 tons/yr of reduction. The BART 

guideline states "The baseline emissions rate should represent a realistic depiction of anticipated 

annual emissions from the source. In general, for the existing sources subject to BART, you will 

estimate the anticipated annual emissions based upon actual emissions from a baseline period." 

(70 FR 39167). As can be seen from the attached table, the baseline emission rate in our SIP for 

each unit represents a realistic upper bound based on emissions from 2000 - 2009. We do not 

expect emissions to increase above these levels in the future. 

Overestimating the removal efficiency of SCR could also contribute to an overestimate of the 

emissions reduction. Determining a removal efficiency for SCR on North Dakota lignite is 

hypothetical at best since SCR has been determined to be technically infeasible as described 

earlier in this letter. Hypothetically, the Department has estimated that advanced separated 

overfire air (ASOFA) plus SCR would reduce NOx emissions by 90%. We believe this is 

reasonable since EPA used 80% removal for SCR in the preliminary BART detennination for 

the Four Comers Power Plant (75 FR 64226) and the BART limits must apply at all times 

including startup/shutdown and malfunction. 

In summary, we believe: 

1) 	 Your estimate of 1.5 deciviews improvement at Theodore Roosevelt National Park 

grossly overstates the amount of improvement and is not consistent with the Clean Air 

Act. 

2) 	 The amount of emissions reductions by SCR versus SNCR is overstated. 

3) 	 We have completed the BACT Process which has not been challenged. We believe it is 

the decision of record until overturned by a process laid out in the Consent Decree or the 

courts. 
Mr. Daly 	 5 December 8, 20 I 0 

4) 	 Issuance of a FIP for BART is an attempt to remove any state discretion from the BART 

process which is contrary to statements in the July 6, 2005 Federal Register (70 FR 

39104-39172). 

We urge you to stop the FIP process until all of these issues are properly reconciled. 

Your letter expresses a willingness to work with the state, however, this appears to be a hollow 

offer given that EPA Region 8 has taken the unprecedented action of withholding grant funds 

and using those grant funds to hire a contractor to pursue the collection of information to support 

EPA's "preliminary" position. EPA's objectivity and willingness to make a decision based on 

the facts, science and the law appears to be questionable. 

If you have any questions, please contact me at (701)328-5188. 

Respectfully. 

~7C)~ Terry L. O'Clair, P.E. 


Director 


Division of Air Quality 


TLO/TB:csc 

xc: 	 David Glatt, Chief- Environmental Health Section 


Margaret Olson, Asst Attorney General 

Response: The Clean Air Act in Section l69A(g)(2) states: "in detennining best available 

retrofit technology the State (or the Administrator in detennining emission limitations which 

reflect such technology) shall take into consideration the costs of compliance, the energy and 

nonair quality environmental impacts of compliance, any existing pollution control technology in 

use at the source, the remaining useful life of the source, and the degree of improvement in 

visibility which may reasonably be anticipated to result from the use of such technology;" 

[emphasis added]. We believe the cumulative modeling provides a much more accurate estimate 

of the degree of improvement in visibility which may reasonably be anticipated to result 

from the use of SCR. 

The difference between cumulative and BART single-source modeling results starts with the 

logarithmic relationship between deciview and light extinction, which is based on the proven 

concept that an observer will detect visibility changes more easily in clean air than in dirty air. 

Deciview is related to light extinction using the equation 

dv = 10 x In(bext /10) 

dv deciview . 


bex ! == light extinction in units of inverse mega-meters (Mm·l

) 


In BART single-source modeling, the incremental impact of the subject source is based on a 

background of natural visibility conditions only. In cumulative modeling, as conducted by 

WRAP, the incremental impact of the subject source is based on a background of natural 

2 

visibility conditions plus the impact of a complete inventory of all other source emissions which 

affect visibility. Therefore, calculated delta-deciview for the subject source for the cumulative 

case will be lower than for the single-source case. 

A simple hypothetical example can illustrate the difference in single-source and cumulative 

visibility modeling. Assume that a subject source is contributing 5 Mm-I to total light extinction 

and that the natural visibility background is 20 Mm-I

. Under single-source modeling, deltadeciview for the subject source would be calculated: 

delta-dv = [10 x In(25 / 10)] - [10 x In(20 /10)] = 9.16 - 6.93 = 2.23 

WRAP and the NDDH have found that adding a complete emissions inventory in the cumulative 

modeling will typically result in a background more than double the natural visibility conditions. 

So to complete the example for the cumulative modeling case, we assume a background of 50 

Mm-I and the same subject source. Delta-deciview for the subject source would be calculated: 

delta-dv == [10 x In(55 / 10)] - [10 x In(50 /10)] == 17.05 - 16.09 = 0.96 

Therefore, inclusion of the complete visibility-affecting emissions inventory in the cumulative 

modeling produces a smaller, but more realistic, observer-detected difference of 0.96 deciview 

from the subject source. In fact, for this example, the cumulative modeling result falls below the 

generally recognized observer-detectable threshold of about 1.0 deciview. Thus, the example 

illustrates that the impact of the subject source plume against a clean background would be much 

more noticeable to an observer than the impact of the same plume against the more realistic 

dirtier background. And, obviously, any change in visibility-affecting emissions from the 

subject source would have a smaller impact on the observer under the cumulative modeling 

scenano. 

In the figure below, delta-deciview has been plotted for several background deciview levels, 

based on the subject source, above. The included background levels range from a clean natural 

background to a dirty background representing the cumulative effect of many visibility-affecting 

sources. The plot includes the two points calculated above. The plot illustrates the general 

dependency of the observed visibility change (delta-deciview) on the background level, and the 

fact that an observer's perception of visibility change can vary greatly depending on the 

background deciview level. In fact, for this example, there is a factor of 6.6 difference in deltadeciview for the cleanest background compared with the dirtiest background (3.15 /0.48 == 6.56). 

3 

Delta-dv Change vs. Background Visibility for Example Source (SMm-1) 

4 

~ 

3 

> 

"0 

I 

El 2 

Q) 

o 

1 

o 

o 5 


clean natural 

background, only 

cumulative, dirty 

background 

~ 

_ _ ___ _ _ \. __ _ barely perceplibl 1 by an observer

~ 

10 15 20 25 


Back round dv 


To further illustrate the difference in single-source and cumulative visibility analyses, the NDDH 

conducted additional modeling using actual sources. For this illustration, the NDDH grouped the 

BART-applicable Coal Creek, Leland Olds, and Milton R Young Generating Stations (in North 

Dakota) as an effective single source. Single-source and cumulative modeling analyses were 

conducted to detennine the incremental visibility improvement at Theodore Roosevelt National 

Park from the 3-source group, based on BART controls. Calpuff system versions 5.8, the new , 

IMPROVE equation, annual average natural background, and consistent annual emission rates 

(for the three noted sources) were applied for both analyses. The 90th percentile visibility day 

from the single-source modeling results was used to emulate the 20'% worst day average from the 

cumulative modeling results. (Given that the typical distribution of 20% worst day visibilities 

tends to be skewed toward the high end, the 90th percentile day may somewhat understate the 

20% worst day average). Note that the post-BART emissions inventory for the cumulative 

analysis included changes only to the three sources referenced above. 

4 

Results of the NDDH modeling analyses are summarized in the table below. The modeling 

analyses discussed above are compared in the first two columns of results. 

20% Worst Day 

A vg. Cumulative 

Modeling 

90th Percentile Day 

Single-Source 

Modeling 

90th Percentile Day 

Single-Source 

Modeling Using 

2005 ND BART 

Protocol 

Baseline (dv) 16.954 6.552 5.583 

Post-BART (dv) 16.493 5.641 3.288 

Improvement (delta-dv) 0.461 0.9 11 2.295 

As shown in the table, visibility improvement from the addition of BART controls to the three 

generating stations based on single-source modeling is about twice that found from cumulative 

modeling. These results are consistent with the hypothetical example discussed above . 

Also shown in the table are results of a third modeling scenario, i.e., single-source modeling 

based on the North Dakota BART modeling protocol. Consistent with EPA recommendations at 

the time (2005), the North Dakota BART protocol specified the use of Calpuff Version 5.7, the 

old IMPROVE equation, and a natural background reflecting cleanest days. In addition, the 

protocol specified use of maximum 24-hour emission rates, per the BART Rule. As indicated in 

the table, use of this protocol resulted in a much greater "apparent" improvement in visibility, 

about a five-fold increase in the result from the cumulative modeling. This illustration, 

therefore, is another basis for the NDDH statement in the SIP that BART single-source modeling 

over predicts by a factor of 5 to 7. 

All BART modeling conducted by the NDDH and industry was based on the North Dakota 

BART protocol. Given differences in the North Dakota BART protocol (compared to later 

protocols), combined with the logarithmic nature of the relationship between deciview and light 

extinction, it becomes clear that BART single-source modeling could have gr:eatly overstated the 

more' realistic results obtained from recent cumulative modeling for North Dakota. . 

Note that use of the ND BART single source' modeling produces a visibility improvement at 

Theodore Roosevelt National Park (2.295 dv) which achieves compliance with the uniform rate 

of progress goal (2.3 dv as discussed in Section 5 of the North Dakota SIP). If one was to accept . . 

the premise that these single-source modeling results are realistic, it would logically follow that 

North Dakota has met the uniform rate of progress based on BART controls for the three 

5 

modeled sources, and that the need to address additional (non-BART) visibility-affecting 

emissions reductions in North Dakota is therefore less compelling. 

The 20% worst-day average metric from cumulative modeling and the 90th percentile day metric 

from single-source modeling have been compared in this illustration as they constitute a 

comparable moment of the annual distribution of daily visibility predictions. Obviously, the 98th 

percentile day metric from single-source modeling would provide an even greater exaggeration 

of actua] visibility change than the 90th percentile, in the context of the 20% worst-day average 

metric required to measure progress with respect to visibility goals under the regional haze rule. 

The Leland Olds StatiOll and M.R. Young Station are not subject to the BART Guideline (see 

response to Comment 43.B regarding the M.R. Young Station). In the BART Guideline (40 

CFR 51, Appendix Y, Section I.H) it states "For sources other than 750 MW power plants, 

however, states retain the discretion to adopt approaches that differ from the guidelines." The 

Department is exercising this discretion for these sources since the cost of SCR is very high on a 

dollar per ton basis and on incremental cost basis. Therefore, the cumulative visibility modeling 

results were weighted significantly in our decision not to require SCR. 

Comment 5: S02 BART section, p. 71: The S02 BART determination for Stanton Station Unit 

1 may result in too high a limit when burning Powder River Basin (PRB) coal. Please see our 

Comment #49 below for more detail. 

Response: See response to Comment 49. 

Comment 6: NOx BART section, p. 73: We do not agree that SNCR satisfies the BART 

requirements for-Leland Olds Unit 2 and M.R. Young Units 1& 2. See our coinments below on 

the related BART detenninations. 

Response: See response to Comments 22-25, 27, 31-33. 

Comment 7: Section 8.5.1, Hybrid Modeling System, pp. 95-96: The NDDH utilized a hybrid 

modeling approach for determining the status of its Class I areas with respect to the rate of 

progress visibility goals. This approach involved nesting a local NDDH CALPUFF modeling 

domain within the WRAP National CMAQ domain, and applying the CALPUFF model in a 

retrospective sense to more realistically define plume geometry for local point sources. The 

hybrid modeling results were used in a weight of evidence analysis to evaluate the effect of 

emission sources located outside of North Dakota. Please note that the last version of this 

modeling protocol to be reviewed by EPA was a draft dated April 2007 (i.e., we never received 

the final October 2008 version for review). As modeling science has improved, there have been 

a number oftechnical changes in the CALPUFF modeling system and EP NFLM recommended 

default settings since NDDH proposed. the CMAQ/CALPUFF hybrid modeling approach in 

2007. In the Reasonable Progress modeling, the hybrid CALPUFF/CAMx modeling results were 

adjusted based on IMPROVE monitoring data, and it is not clear whether the use of these 

obsolete settings affected the weight of evidence factors or the Reasonable Progress 

demonstration. The settings "NDDH used in the CALPUFF model within the hybrid modeling 

system would not be considered technically sound if contained in a regulatory modeling protocol 

6 

NOx EMISSIONS 

COMPANY PLANT 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Baseline 

BASIN ELECTRIC POWER COOP. LELAND OLDS 2 9,330 12,608 11,068 8,695 10,410 10,231 6,393 8,478 8,172 6,604 12,023 


MINNKOTA POWER COOP. : M.R. YOUNG 1 7,584 9,220 8,459 8,325 9,738 8,423 7,093 8,687 8,163 6,529 9,032 


MINNKOTA POWER COOP. M.R. YOUNG 2 17,727 13,287 14,278 14,578 13,655 15,106 14,609 12,089 8,624 7,427 15,507 

SCR VERSUS SNCR 


NOx EMISSIONS REDUCTIONS 


SOURCE 

LELAND OLDS 2 

M.R. YOUNG 1 

M.R. YOUNG 2 

TOTAL 

BASELINE 

£MISSIONS 

(TPY) 

12,023 

9,032 

15,507 

CONTROL 


TECHNOLOGY 


SCR +ASOFA 


SNCR +ASOFA 


SCR +ASOFA 


SNCR + ASOFA 


SCR + ASOFA 


SNCR + ASOFA 


REMOVAL 


EFFICIENCY 


(%) 

90.0 

54.5 

90.0 

58.1 

90.0 

58.0 

EMISSIONS 

REDUCTION 

(TPY) 

10,821 

6,553 

8,129 

5,248 

13,956 

8,994 

EM ISSION REDUCTION 


DIFFERENCE 


(TPY) 


4,268 

2,881 

4,962 

12,112