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 DearMr. Daly: This is in response to your letter ofNovember 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 complywiththe CleanAirAct, 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 f rom the guidelines." (70 FR 39158). Your letter indicates that adding selective catalytic reduction (SCR) to M.R
. Young Station Units 1and 2 and Leland Olds Station Unit 2 would improve visibility in Theodore RooseveltNational 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 ofsuch technology." [Emphasis added]
. Yourestimateof 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 offive 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 Printedon recycledpaper.

### Mr. Daly 

### 2 December 8, 2010 (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 AirPartnership (WRAP)forNDClass I areas). This cumulative analysis indicates that the application ofSCRto these units will only improvethe average impairmentofthe 20% worst days by 0.02 deciviews or less for each unit versus selective non-catalytic reduction (SNCR). EPA'spositionof 1.5 deciviews improvementis 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, orcombination ofmethods, 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 ofthe daily impacts, determine ifthe time ofyear is important (e.g. high impacts are occurring during tourist season), consideration ofthe cost-effectiveness ofvisibility 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 otherways by forcing adoptionofthe flawed single source 98th 

### percentilemodelingresults. Second, even ifone accepts the premise ofsingle source 98th 

### percentile modeling, your estimate of 1.5 deciviews improvement from the selection ofSCR 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 ofSCR over SNCR is flawed because these two stations are located a significantdistance from eachother and have differing stack parameters. The maximwn impacts assumed by EPA would be located at different receptors and occurondifferent 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 StationUnit 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 ofthe average background would have resulted in a significantly lower visibility improvementprediction 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 likelyhave 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 ofCalpuffis 5.8 (update was partially prompted due to discovery ofcodingerrors in theprevious version). It

### is likelythat 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 CalpuffVersion 5.8 would have provided a visibility improvement well below 1.5 deciviews, and likely below observerperceptibility (1.0 deciview). We note also that the modeled visibility improvements referenced by EPA tended to occur during months with lower visitation to TheodoreRooseveltNational 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 BACTdetermination 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 ofboiler (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 ofthe beliefthat due to the unique Hue gas characteristics from burning North Dakota lignite, boiler configuration and unwillingness ofSCRvendors 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 ConsentDecree. 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 ConsentDecreefor 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 ofless 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 ofvisibility improvement, for 

### most EGUs greater than 200 MW, regardless ofthe size ofthe plant at which they are located. A 

### State is free to reach a different conclusion ifthe State believes that an alternativedetermination isjustified based on a consideration ofthefive statutoryfactors." [Emphasis added] (70 FR 39131)
. The preamble also states "We agree with the suggestion that the use ofa comparisonthreshold, as is done for determining ifBART-eligible 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 ofimprovement 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 "Youhave flexibility to assess visibility improvements due to BARTcontrols by one or more methods. You may consider the frequency, magnitude, and duration components of improvement. 

### Suggestions [emphasis added] for making the detennination are:

- Comparethe 98th 

### percentile day for the pre- and post-control runs." (70 FR39170). 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 modelingdata especially since neither source is subjectto BARTGuidelines. We are also confused on how you arrived at 17,000 tons/yr ofreduction from the use ofSCR 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 ofanticipated annual emissionsfrom 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 FR39167). 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 expectemissionsto increase above these levels in thefuture. Overestimating the removal efficiency of SCR could also contribute to an overestimate ofthe 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/shutdownand malfunction
. In summary, we believe: 1) Your estimate of 1.5 deciviews improvement at Theodore Roosevelt National Park grossly overstates the amount ofimprovement and is not consistent with the Clean Air Act. 2) The amountofemissions reductions by SCRversus SNCRis overstated. 3) We have completed the BACT Process which has not been challenged. We believe it is the decision ofrecord until overturned by a process laid out in the Consent Decree or the courts.Mr. Daly 

### 5 December 8, 20I 0 4) Issuance ofa 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)
. Weurge you to stopthe FIPprocessuntil all ofthese 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 contractorto pursue the collection ofinformationto support EPA's "preliminary" position. EPA's objectivity and willingness to make a decision based on the facts, science and the lawappears to be questionable. Ifyou have anyquestions,pleasecontactmeat (701)328-5188. Respectfully.

# ~7C)~ TerryL. O'Clair, P.E. Director Division ofAir Quality 

### TLO/TB:csc xc: David Glatt, Chief

- Environmental Health Section Margaret Olson, AsstAttorney GeneralResponse: 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 ofcompliance, the energy and nonairquality environmental impacts ofcompliance, any existingpollution control technology in use at the source, the remaining useful life ofthe source, and the degree of improvement in visibility which may reasonably be anticipated to result from the use ofsuch technology;" [emphasis added]. We believe the cumulative modelingprovides a muchmore accurate estimate ofthe degree of improvement in visibility which may reasonably be anticipated to result from the useofSCR. 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. Deciviewis relatedto light extinctionusing theequation dv

## = 10 x In(bext/10)
dv deciview
. bex!== light extinction in units ofinverse mega-meters (Mm· l) In BART single-source modeling, the incremental impact ofthe 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 ofacomplete inventory ofall other source emissions which affect visibility. Therefore, calculated delta-deciview for the subject source for the cumulative case will be lowerthan 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 5Mm- I 

### to total light extinction and that the natural visibility background is 20 Mm- I

. 

### Under single

-source modeling, deltadeciview forthe subject source would be calculated: delta-dv

### =[10 xIn(25 / 10)]

- [10 xIn(20 /10)]

### =9.16

- 6.93 

### =2.23 WRAP and the NDDH have found that adding acomplete emissions inventory in the cumulative modeling will typically result in abackground more than double the natural visibility conditions. So to complete the example for the cumulative modeling case, we assume a background of50 Mm- I 

### and the same subject source. Delta-deciview for the subject source would be calculated: delta-dv == 

### [10 xIn(55 / 10)]

- [10 xIn(50 /10)] == 

### 17.05

- 16
.09 =0.96 Therefore, inclusion ofthe complete visibility-affecting emissions inventory in the cumulative modeling produces a smaller, but more realistic, observer-detected difference of0.96 deciview from the subject source. In fact, for this example, the cumulative modeling result falls below the generally recognized observer-detectable threshold ofabout 1
.0 deciview
. Thus, the example illustrates that the impact ofthe subject source plume against aclean 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 adirty background representing the cumulative effect ofmany visibility-affecting sources. The plot includes the two points calculated above. The plot illustrates the general dependency ofthe 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 of6.6 difference in deltadeciview for the cleanest background compared with the dirtiest background (3.15 /0.48 == 

### 6.56).

3

### Delta-dv Change vs. 

### Background Visibilityfor Example Source (SMm-1)


### 4**~** 

### 3

> "0

I El 2 Q) 

## o

1



## o 

# o 5 clean natural background, only

cumulative, dirty background

_ _ _ __ _ _ \.
__ _ barelyperceplibl

### ~ by an observer 

# 1**~**

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. Forthis illustration, the NDDHgrouped 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 TheodoreRooseveltNational Park from the 3-source group, based on BART controls. Calpuffsystem versions 5.8, the new , IMPROVE equation, annual average naturalbackground, and consistent annual emission rates (forthe three noted sources) were applied for both analyses
. The

## 90th percentile visibility day from the single-source modelingresults was used to emulate the 20'% worstday 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. 

### 4Results of the NDDH modeling analyses are summarized in the table below. The modeling analyses discussed above are compared in the first two columns ofresults.

20%Worst Day Avg. Cumulative Modeling 90th Percentile Day Single-Source

Modeling 90th PercentileDay Single-Source ModelingUsing 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 ofBART controls to the three generating stations based on single-source modeling is about twice that found from cumulative modeling. Theseresults 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 BARTmodelingprotocol. Consistent with EPArecommendations at the time (2005), the North Dakota BART protocol specified the use ofCalpuffVersion 5.7, the old IMPROVE equation, and a natural background reflecting cleanest days
. In addition, the protocol specified use ofmaximum 24-houremission rates, per the BART Rule. As indicated in the table, use ofthis 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 overpredicts by a factor of5 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 ofthe relationship between deciview and light extinction, itbecomes clear that BART single-sourcemodeling could have gr:eatly overstated the more'realistic results obtained from recent cumulativemodeling for NorthDakota.
. Note that use of the ND BART single source'modelingproduces a visibility improvement at Theodore Roosevelt National Park (2.295 dv)which achieves compliance with the uniform rate ofprogress goal (2.3 dv as discussed in Section 5 ofthe North Dakota SIP)
. Ifone 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 

### 5modeled sources, and that the need to address additional (non-BART) visibility-affecting emissions reductions in NorthDakotais 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 ofthe annual distribution ofdaily visibility predictions. Obviously, the 98th percentile day metric from single-source modeling would provide an even greater exaggeration ofactua] visibility change than the 90th percentile, in the context ofthe 20% worst-day average metric required to measureprogress with respectto visibility goals underthe regionalhazerule. 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 costofSCR is very high on a dollar per ton basis and on incremental cost basis
. Therefore, the cumulativevisibility modeling results were weighted significantly in our decision not to require SCR. Comment5: S02 BART section, p. 71: The S02BARTdetermination for Stanton Station Unit 1may 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 Comment49. 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 BARTdetenninations. Response: Seeresponse to Comments 22-25, 27, 31-33. Comment7: 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 localNDDH 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 tobe reviewed by EPA was a draft dated April 2007 (i
.e., we never received the final October 2008 versionfor review). As modeling science has improved, there havebeen a number of technical changes in the CALPUFF modeling system and EPNFLM recommended default settings since NDDH proposed.the 

### CMAQ/CALPUFF hybrid modeling approach in 2007
. In the Reasonable Progress modeling, the hybrid 

### CALPUFF/CAMx modelingresults 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 ifcontained in a regulatory modeling protocol 

### 6

### NO

## xEMISSIONS

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 NO

## xEMISSIONS 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 EMISSION REDUCTION DIFFERENCE (TPY)

4,268

2,881

4,962 12,112