# SOUTH DAKOTA’S

REGIONAL HAZE

STATE IMPLEMENTATION PLAN

South Dakota Department of Environment and Natural Resources

### Table of Content
Page

i Executive Summary ............................................................................................................. ....... vii

1.0 Introduction .................................................................................................................. ...... 1

1.1 Initial Visibility Protection Program ......................................................................1

1.2 Visibility Impairment ...............................................................................................2

1.3 1990 Amendments to Regi onal Haze Program ......................................................2

2.0 Class I Areas in South Dakota ........................................................................................... 3

2.1 Badlands National Park ...........................................................................................5

2.2 Wind Cave National Park ........................................................................................6

3.0 Baseline, Natural and Uniform Rate of Improvement .................................................... 7

3.1 Baseline Visibility Conditions ................................................................................11

3.2 Natural Visibility Conditions .................................................................................11

3.2.1 Default Natural Conditions .................................................................... 12

3.2.2 Improved Default Natural Conditions .................................................. 14

3.2.3 Baseline and Default Natural Conditions Comparison ....................... 16

3.2.4 Refined Natural Conditions ................................................................... 17

3.3 Uniform Rate of Improvement ..............................................................................17

4.0 IMPROVE Data for Class I Areas .................................................................................. 19

4.1 Aerosol Concentrations ..........................................................................................19

4.2 Extinction Comparison ...........................................................................................21

4.3 Visibility Impairment Quarterly Trends ..............................................................27

4.3.1 Number of Occurrences per Quarter .................................................... 27

4.3.2 Extinction Trends by Quarter ............................................................... 29

4.3.3 Visibility Impairment Trends ................................................................ 33

5.0 Source Apportionment ..................................................................................................... 37

5.1 Air Emission Inventory ..........................................................................................37

5.1.1 Baseline Emission Inventory .................................................................. 38

5.1.2 Current Emission Inventory .................................................................. 42

5.1.3 WRAP’s 2018 Projections ...................................................................... 42

5.1.4 Air Emission Inventories for Ot her States and Countries .................. 45

5.1.5 Future Emission Inventory by South Dakota ....................................... 47

5.2 Source Apportionment Analysis ............................................................................50

5.3 Regional Haze Contributions in South Dakota’s National Parks ......................52

5.3.1 Sulfate Contributions ............................................................................. 53

5.3.2 Organic Carbon Mass Contributions.................................................... 59

5.3.3 Nitrate Contributions ............................................................................. 63

5.3.4 Coarse Particulate Matter Contribution .............................................. 68

6.0 Best Available Retrofit Technology (BART) ................................................................. 72

6.1 Bart-Eligible Sources ..............................................................................................72

6.1.1 Northern States Power Company – Sioux Falls ................................... 74

6.1.2 Pete Lien and Sons, Inc. – Rapid City ................................................... 75

### Table of Content
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ii 6.1.3 Otter Tail Power Company – Big Stone I ............................................. 76

6.2 Otter Tail Power Company’s Modeling Results ..................................................78

6.3 Otter Tail Power Company’s Case -by-Case BART Analysis .............................81

6.3.1 Particulate BART Review ...................................................................... 82

6.3.1.1 Particulate Control Technologies ........................................... 82

6.3.1.2 Technically Feasible Particulate Control Technologies ........ 83

6.3.1.3 Particulate Control Effectiveness ........................................... 83

6.3.1.4 Particulate Control Technology Impacts ................................ 84

6.3.2 Sulfur Dioxide BART Review ................................................................ 84

6.3.2.1 Sulfur Dioxide Control Technologies ..................................... 84

6.3.2.2 Technically Feasible Sulfur Dioxide Control Technologies . 84

6.3.2.3 Sulfur Dioxide Control Effectiveness ..................................... 86

6.3.2.4 Sulfur Dioxide Control Technology Impacts ......................... 86

6.3.3 Nitrogen Oxide BART Review ............................................................... 88

6.3.3.1 Nitrogen Oxide Control Technologies .................................... 88

6.3.3.2 Technically Feasible Nitrogen Oxide Control Technologies . 88

6.3.3.3 Nitrogen Oxide Control Effectiveness .................................... 90

6.3.3.4 Nitrogen Oxide Control Technology Impacts ........................ 91

6.3.4 Visibility Impact Evaluations................................................................. 93

6.3.5 BART Emissions Limits for Big Stone I ............................................... 99

6.3.5.1 Particulate Matter BART Recommendation .......................... 99

6.3.5.2 Sulfur Dioxide BART Recommendation .............................. 100

6.3.5.3 Nitrogen Oxide BART Recommendation ............................. 101

6.4 BART Requirements ............................................................................................103

7.0 Reasonable Progress ....................................................................................................... 103

7.1 State and Federal Rules ........................................................................................104

7.2 2018 Projected Visibility Conditions ...................................................................105

7.3 Key Pollutants Contributing to Visibility Impairment .....................................106

7.4 Four Factor Analysis ............................................................................................109

7.4.1 Four Factor Analysis – GCC Dacotah ................................................ 110

7.4.2 Four Factor Analysis – Black Hi lls Corporation (Ben French) ........ 113

7.4.3 Four Factor Analysis – Pete Lien and Sons ........................................ 115

7.4.4 Four Factor Analysis – Summary ....................................................... 116

8.0 Long Term Strategy ....................................................................................................... 116

8.1 Class I Areas in Other States Impacted by South Dakota ................................117

8.2 States Impacting South Dakota’s Class I Areas .................................................118

8.3 Technical Basis for Modeling, Monito ring and Emissions Information ..........118

8.4 Identification of Anthropogenic So urces of Visibility Impairment ..................119

8.5 Factors in Developing Long Term Strategy .......................................................119

8.5.1 Emission Reductions from Ongoing Air Pollution Control Programs

................................................................................................................ 119

8.5.2 Measures to Mitigate Impacts of Construction Activities ................. 121

### Table of Content
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iii 8.5.3 Emission Limitations and Schedules to Achieve Reasonable Progress

Goals ...................................................................................................... 121

8.5.4 Retirement and Replacement Schedules ............................................. 121

8.5.5 Smoke Management.............................................................................. 122

8.5.6 Enforceable Emission Limits and Control Measures ........................ 123

8.5.7 Anticipated Net Effect on Visibili ty Due to Projected Changes ....... 123

9.0 Monitoring Strategy ....................................................................................................... 126

10.0 Consultation Requirements ........................................................................................... 129

10.1 Federal Land Manager Consultation ..................................................................129

10.1.1 Addressing Federal Land Manager Recommendations .................... 131

10.1.2 Continued Consultation with Federal Land Managers ..................... 131

10.2 Consultation with Other States............................................................................131

10.3 Public Input ...........................................................................................................133

11.0 Periodic Review .............................................................................................................. 134

11.1 Evaluation and Reassess Every 10 Years ...........................................................134

11.2 Report Every 5 Years ...........................................................................................135

11.3 Determination of Adequacy .................................................................................136

### List of Tables
Page

iv Table 3-1 – Baseline Visibility Conditions in South Dakota’s National Parks ......................... 11

Table 3-2 – Average Natural Background Concentration Levels .............................................. 13

Table 3-3 –Natural Background Conditions for South Dakota’s Class I Areas ....................... 14

Table 3-4 – Relative Humidity Correction Factor (f(RH)) ......................................................... 15

Table 3-5 –New Formula Natural Background Conditions for South Dakota’s Class I Areas 16

Table 3-6 – Comparison of Natura l versus Baseline Concentrations 1 ..................................... 16

Table 3-7 – Baseline versus Natu ral Background (Deciviews) .................................................. 17

Table 3-8 – Annual Uniform Rate of Improvement ................................................................... 18

Table 4-1 – Badlands National Park Baseline Aerosol Concentrations 1 ................................. 20

Table 4-2 – Wind Cave National Park Baseline Aerosol Concentrations 1 ............................... 20

Table 4-3 – Badlands National Park 1 ......................................................................................... 21

Table 4-4 – Wind Cave National Park 1 ...................................................................................... 22

Table 5-1 – South Dakota’s 2002 Baseline Emission Inventory Summary (Base 02b) 1, 2 ....... 40

Table 5-2 –South Dakota’s 2002 Planning Emission Inventory Summary (Plan 02d) 1, 2 ....... 41

Table 5-3 – Comparison of 2002 and 2009 South Dakota Point Source Emissions 1 ............... 42

Table 5-4 –2018 South Dakota Projected Em ission Inventory Summary (PRP 18b) 1, 2 .......... 46

Table 5-5 – Emission Ch anges projected for 2018 1 ................................................................... 47

Table 5-6 –2002 Contiguous State Planning Emission Inventory Summary (Plan 02d) 1, 2 .... 48

Table 5-7 –2018 Contiguous State Emi ssion Inventory Summary (PRP 18b) 1, 2 ..................... 49

Table 6-1– List of BART-Eligible Sources 1 ............................................................................... 74

Table 6-2– WRAP’s Modeling Results for Pete Lien and Sons 1 ............................................... 76

Table 6-3– WRAP’s Modeling Results for Otter Tail Power Company Big Stone I 1 ............... 77

Table 6-4– Otter Tail Power Company’ s Modeling Results for Big Stone I 1 ........................... 80

Table 6-5 – Comparison of Control Eff ectiveness for Particulate Controls .............................. 83

Table 6-6 – Comparison of Control Effect iveness for Sulfur Dioxide Controls ....................... 86

Table 6-7 – Comparison of Control Effect iveness for Sulfur Dioxide Controls ....................... 87

Table 6-8 – Estimated Energy Impact s for Sulfur Dioxide Controls ......................................... 87

Table 6-9 – Comparison of Control Effect iveness for Nitrogen Oxide Controls ...................... 90

Table 6-10 – Comparison of Control Effec tiveness for Nitrogen Oxide Controls .................... 92

Table 6-11 – Estimated Energy Impact s for Nitrogen Oxide Controls ...................................... 92

### List of Tables
Page

v Table 6-12 – Potential Impact of Existing Big Stone I (98 th Percentile) ................................... 93

Table 6-13 – Emission Rates for Each Control Option .............................................................. 94

Table 6-14 – Modeling Results for Each Control Option (98 th Percentile – Deciviews) ........... 95

Table 6-15 – Cost per Deciview Comparison ($/deciview) ......................................................... 97

Table 6-16 – Visibility Comparison between Wet and Dry Scrubbers ..................................... 100

Table 7-5– Four Factor Analysis for Black H ills Corporation Based on 30 Year Life .......... 113

Table 7-6– Four Factor Analysis for Black H ills Corporation Based on 10 Year Life .......... 114

Table 7-7– Visibility Impacts fr om Black Hills Corporation (8 th Highest).............................. 114

Table 7-8– Visibility Impacts fr om Pete Lien and Sons (8 th Highest) ..................................... 115

Table 9-1– IMPROVE Monitoring Sites at Class I areas in South Dakota ............................ 127

Table 9-2– Ambient Air Monitoring Site Parameters Next to IMPROVE Sites ..................... 128

### List of Figures
Page

vi Figure 2-1 – Class I Areas in the United States............................................................................ 4

Figure 2-2 –Badlands National Park’s Boundary........................................................................ 5

Figure 2-3 – Wind Cave National Park’s Boundary .................................................................... 6

Figure 2-4 –Prairie, Forest, and Bison at Wind Cave (Courtesy of National Park Service) ...... 7

Figure 2-5 – View from Lookout Tower (C ourtesy of National Park Service) ........................... 7

Figure 3-1 – Light Extinction-Ha ze Index-Visual Range Scale 1 ............................................... 8

Figure 3-2 – Comparison at Different Levels ............................................................................... 9

Figure 3-3 – Badlands’ IMPROVE an d State Monitoring Site ................................................. 10

Figure 3-4 – Wind Caves’ IMPROVE and State Monitoring Site ............................................. 10

Figure 3-5 – Uniform Ra te of Improvement ............................................................................... 18

Figure 4-1 – Badlands National Park Baseline Aerosol Extinction Comparison 1 .................. 23

Figure 4-2 – Wind Cave Baseline Ae rosol Extinction Percentage ............................................ 24

Figure 4-3 – National Park Extinction Comparison 1 ................................................................ 26

Figure 4-4 –Number of Occurrences by Quarter – 20% Most Impaired Days ......................... 27

Figure 4-5 – Badlands’ Quarterly Extinctio n Values for 20% Most Impaired Days................ 29

Figure 4-6 – Wind Cave’s’ Quarterly Extinc tion Values for 20% Most Impaired Days .......... 31

Figure 4-7 – Badlands’ Quarterly Data for 20% Most Impaired Days ..................................... 34

Figure 4-8 – Wind Cave’s Quarterly Da ta for 20% Most Impaired Days ................................. 36

Figure 5-1 – Sulfate Contribution for 20% Most Impaired Days .............................................. 54

Figure 5-2 – Sulfate Contribution for 20% Least Impaired Days ............................................. 57

Figure 5-3 – Organic Carbon Mass Contri bution for 20% Most Impaired Days ..................... 60

Figure 5-4 – Organic Carbon Mass Contri bution for 20% Least Impaired Days .................... 62

Figure 5-5 – Nitrate Contribution for 20% Most Impaired Days .............................................. 64

Figure 5-6 – Nitrate Contribution for 20% Least Impaired Days .............................................. 67

Figure 5-7 – Coarse Particulate Matter Cont ribution for 20% Most Impaired Days ............... 70

Figure 5-8 – Coarse Particulate Matter Co ntribution for 20% Least Impaired Days .............. 71

Figure 7-1 – Glide Slope by Pollutant for 20% Worst Visibility Days (Extinction) 1 .............. 108vii 

### Executive Summary

The Department of Environment and Natural Resources (DENR) worked with the Western Regional Air Partnership (WRAP) , states not members of WRAP , federal land managers, the Environmental Protection Agency (EPA), the regu lated community, and othe rs to develop this document as part of South Dakota’s Regional Haze State Implementati on Plan (SIP). This document along with the applicable Administra tive Rules of South Dakota (ARSD) and the addition of ARSD, Chapter 74:36:21 w ill be South Dakota’s Regional Haze State Implementation Plan and implemented by DENR to ensure South Dakota’s Regional Haze Program meets the goal of achievi ng natural conditions in the Ba dlands and Wind Cave National Parks by 2064 as specified in Title 40 of the Code of Federal Regulations (CFR) §51.308.

Chapter 1 provides background information on the in itial federal visibili ty protection program, describes the causes of visibility impairment , and describes the new federal regional haze program regulations. Chapter 2 provides informa tion on South Dakota’s two Class I areas. The

two Class I areas are the Badla nds National Park and Wind Cave National Park and both are

located in the western third of South Dakota.

Chapter 3 describes the process DENR followe d to determine natural conditions, baseline conditions, and the uniform rate of improvement for both Class I areas. Chapter 4 discusses the IMPROVE (Interagency Monitoring of Protected Visual Environments) monitoring data for both Class I areas. This chapter looked at the aerosols impacting both Class I areas, what time of year they occur, and if they are in creasing or decreasing over time.

Chapter 5 describes South Dakota’s emission invent ory for past, present, and future air emission inventories in South Dakota, what type of activ ities are emitting the air emissions, and if the air emissions are generated within South Dakota or from neighboring states and countries. Chapter 6

describes the BART review DENR conducted an d establishes the BART requirements for the BART-eligible sources in South Dakota. The BART review covers an analysis to determine BART-eligible sources, a modeling analysis to determine if the BART-eligible source contributes to visibility impairment in a Class I area, and the establishm ent of BART for those BART-eligible sources that reasonably contribute to visibility impairment in any Class I area.

The BART review identified one electrical gene rating unit subject to the BART requirements. Otter Tail Power Company’s Big St one I facility determined that it reasonably contributes to visibility impairment in Class I areas. DENR determined the control equipment considered BART for Big Stone I is the existing baghouse, a semi-dry flue gas desulfurization system, and selective catalytic reduct ion. The installation of the new cont rol equipment and establishment of BART emission limits, compliance demonstrati on, recordkeeping, and reporting requirements will be established in an air quality construc tion permit and eventually in Otter Tail Power Company’s Title V air quality operating permit. The installation of the new control equipment and other requirements will be completed within five years of EPA’s approval of South Dakota’s Regional Haze State Implementation Plan.viii Chapter 7 discusses South Dakota’s goals for demonstrating reasonable progress such as outlining existing rules that already help minimize air emissions that cause visibility impairment and the modeling WRAP conducted of the western United States to determine if states are meeting the reasonable progress goals in 2018. Su lfur dioxide emissions in South Dakota from 2002 through 2018 are expected to decline by 36%, nitrogen oxides emissions are expected to decline by 18%, organic carbon mass emissions are expected to decline by 6%, and elemental carbon emissions are expected to decline by 49%. Other states will also experience a reduction in air emissions that reasonably c ontribute to visibility impairment in Class I areas. Overall, sulfur dioxide emissions during the same time period are expected to decline by 26%, nitrogen oxide emissions are expected to decline by 29%, organic carbon mass are expected to decline by 6%, and elemental carbon emissions are expected to decline by 31%. These reductions are expected to demonstrate reasonabl e progress is being made to impr ove visibility at all Class I

areas.

Chapter 8 describes South Dakota’s long-term goa ls in achieving natural conditions by 2064. It also outlines DENR’s proposed rules (ARSD, Ch apter 74:36:21) to ensure new sources and modifications to existing sources will not reasonably c ontribute to visibility impairment at any Class I area. In addition, DENR will review , develop, and implement a Smoke Management Plan to address wildfires and prescribed fires.

Chapter 9 discusses DENR’s monitoring plan for tracking our progress in achieving natural conditions by 2064. Chapter 10 describes the cons ultation DENR went through with federal land managers, states, and the public, how DENR responded to each comment, and their future

involvement.

Chapter 11 describes the reviews and reporting DENR will perform to track South Dakota’s progress in attaining na tural conditions by 2064.1 

### 1.0 Introduction

1.1 Initial Visibility Protection Program

In August 1977, the federal Clean Air Act was amended by adding section 169A. In section 169A(a)(1), Congress established the following national goal for visi bility protection:

“Congress hereby declares as a national goa l the prevention of any future, and the remedying of any existing, impairment of visi bility in mandatory class I Federal areas which impairment results from man-made air pollution.”

To address this goal for each of the 156 mandato ry federal Class I areas across the nation, the federal Environmental Protection Agency (EPA) de veloped regulations to reduce the impact of large industrial sources on nearby Class I areas. It was recognized at the time that regional haze, which comes from a wide variety of sources that may be located far from a Class I area, was also a part of the visibility problem. However, monito ring networks and visibility models at that time were not developed to the de gree necessary to understand th e causes of regional haze.

The 1977 Clean Air Act Amendments also es tablished the Prevention of Significant Deterioration (PSD) permit program, which include d requirements for protecting visibility in national parks, national wilderness areas, nationa l monuments and national seashores. The PSD permit program included area specific (e.g., Class I, II and III) increments or limits on the maximum allowable increase in air pollutants (e. g., particulate matter and sulfur dioxide) and a preconstruction permit review process for new or modifying major sources that allows for

careful consideration of control technology, consultati on with federal land ma nagers on visibility impacts and public participation in permitting decisions. The PSD permit program was delegated to South Dakota on July 6, 1994, a nd later approved in South Dakota’s State Implementation Plan on January 22, 2008.

Under Section 169A(b) of the Clean Air Act, Congress established new requirements on major stationary sources in operat ion within a 15-year period pr ior to enactmen t of the 1977 amendments. Major stationary sources within th at timeframe that may reasonably be anticipated

to cause or contribute to visibili ty impairment in a Class I area mu st install best available retrofit technology (BART) as determined by the state. In determining BART, the state must take into consideration the costs of compliance, the ener gy and non-air 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 visi bility which may reasonably be anticipated to result from the use of such technology.

In 1980, EPA adopted regulations to address “reasona bly attributable visibility impairment”, or visibility impairment caused by one or a small group of man-made sources generally located in close proximity to a specific Class I area. At that time, EPA deferred writing rules to address regional haze, because they lacked the monitoring, modeling and scientific information needed to understand the nature of long range transport a nd formation of regional haze. South Dakota did not adopt the visibility rules of 1980 in its St ate Implementation Plan. Therefore, EPA is currently implementing the program in a Federal Implementation Plan.2 1.2 Visibility Impairment

Most visibility impairment occurs when polluti on in the form of small particles scatters or absorbs light. Air pollutants are emitted from a variety of natural and anthropogenic (man-made)

sources. Natural sources can in clude windblown dust and smoke fr om wildfires. Anthropogenic sources can include motor vehicles, electric utility and industrial fuel burning, prescribed burning, and manufacturing operations. More polluta nts mean more absorption and scattering of light, which reduce the clarity and color of scenery. Some types of particles such as sulfates and nitrates scatter more light, particularly duri ng humid conditions. Other particles like elemental carbon from combustion processes are hi ghly efficient at absorbing light.

Commonly, visibility is observe d by the human eye and the object may be a single viewing target or scenery. In the 156 Class I areas across the nation, a person’s visual range has been substantially reduced by ai r pollution. In eastern parks, the av erage visual range decreased from 90 miles to 15-25 miles. In the West, the visual ra nge decreased from an av erage of 140 miles to

35-90 miles.

Some particles that cause haze are directly emitte d into the air while others are formed when gases emitted into the air form particles as they are carried from the source of the pollutants. Some haze forming pollutants are also linked to human health problems and others to environmental damage. Exposure to very small part icles in the air has been linked with increased respiratory illness, decreased lung function, and premature death. In addition, particles such as

nitrates and sulfates contribute to acid deposition potentially ma king lakes, rivers, and streams unsuitable for some forms of aquatic life and impacting flora in the ecosystem. These same acid particles can also erode materials such as pa int, buildings or othe r natural and manmade

structures.

1.3 1990 Amendments to Regi onal Haze Program

In the 1990 Clean Air Act Amendments, Congre ss added section 169B to strengthen and reaffirm the national goal and address visibility impairment from a collection of sources whose emissions are mixed and transported over long dist ances to the Class I areas. Section 169B(e) calls for EPA to “carry out the Administrator’ s regulatory responsibilities under section 169A, including criteria for measuring ‘reasonabl e progress’ toward the national goal.”

In response to these mandates, EPA promulgated the regional haze rule on July 1, 1999. Under 40 CFR, § 51.308(d)(1), states must “establish goals (exp ressed in deciviews) that provide for reasonable progress towards achievi ng natural visibility conditi ons” for each Class I area within a state by 2064. The reasonable progress goals must provide for an improvement in visibility for the most impaired days over the period of the im plementation plan and ensure no degradation in visibility for the least impair ed days over the same period.

The purpose of this submittal is to address the State Implementation Plan requirements for the State of South Dakota found in 40 CFR § 51.308 – Regional Haze Program Requirements of 40 CFR Part 51 Subpart P – Protection of Visibilit y. The South Dakota Depa rtment of Environment3 and Natural Resources (DENR), the agency designa ted to administer and coordinate a statewide program of air pollution control, has general legal authority under South Dakota Codified Laws Title 34A-1 – Air Pollution Control to adopt and en force rules for visibil ity protection including regional haze visibility impairment.

This document along with the adopted rules is South Dakota’s State Implementation Plan for adopting a Regional Haze Program meets these goals . Pursuant to the requirements in 40 CFR § 51.308(a) and (b), the State Implementation Plan is intended to meet the requirements in EPA’s regional haze regulations that were adopted to comply with the requirements established in

Section 169B of the Clean Air Act. This docum ent addresses the following elements of South Dakota’s State Implementation Plan:

1. In accordance with 40 CFR § 51.308(d), the co re regional haze program requirements (e.g., identification of Class I areas; determination of baseline conditions, natural conditions, and uniform rate of progress; a nd baseline, current and future emissions inventories);

2. In accordance with 40 CFR § 51.308(e), who is subject to BART and BART controls, emissions limits, compliance determinations , recordkeeping, and reporting requirements;

3. In accordance with 40 CFR § 51.308(f), a commitment to conduct comprehensive periodic revisions of South Dakota’s Regional Haze State Implementation Plan;

4. In accordance with 40 CFR § 51.308(g), a commitm ent to periodically report the progress towards achieving reasonable progress goals;

5. In accordance with 40 CFR § 51.308(h), a commitment to determine the adequacy of the existing implementation plan; and

6. In accordance with 40 CFR § 51.308(i), the requi rements for continued coordination with states and federal land managers.

South Dakota is a member of WRAP which is a co llaborative effort of tr ibal governments, state governments and various federal agencies to help states and tribes develop and implement a regional haze program that complies with the EPA's regional haze regulations.



### 2.0 Class I Areas in South Dakota

In accordance with 40 CFR § 51.308(d), states must address regional haze in each Class I area

located within the state and in each Class I area located outside the state which may be affected by emissions from within the state. There ar e 156 national parks and wilderness areas in the

nation that are considered Class I areas in the Clean Air Act (see Figure 2-1). South Dakota is home to two of the 156 national parks and wilder ness areas. They are the Badlands National

Park and the Wind Cave National Park.4Figure 2-1 – Class I Areas in the United States---'"'"'.••---"......,..,:::::-""......;.•>-.ProducedbyNPSAi,ResourcesDivisionMandatoryClassIAreas.--G<.....:--.-.--_.---,0•RainbowLlOke,WI.ndIIn.dwe.8a)1.FL...-eClooss1Are_whereisnot...import_..,quality'''lilted....ue../NPSUnitsF\NSUnitFSUnits5 There are also national parks and wilderness area s considered Class I areas in our neighboring states. In Wyoming the Class I areas are located in the western part of the state. Montana’s Class I areas are located throughout the state but none are located in the southeastern corner

which borders South Dakota. North Dakota ha s probably the closest Class I area of any neighboring state. Minnesota’s Clas s I areas are located in the north eastern corner of the state.

Iowa and Nebraska do not have Class I areas.

2.1 Badlands National Park

The Badlands National Park is located in southwestern South Dakota and consists of 244,000 acres of sharply eroded buttes, pinnacles, and sp ires blended with the largest protected mixed grass prairie in the United Stat es (see Figure 2-2). The closes t industrial area from the park boundary is in Rapid City which is approxima tely 40 miles to the northwest. The general topography is plains; theref ore this site is well exposed to regional scale transport winds. The surrounding terrain is predominantly mixed grass prairie and bare rock and sand.

Figure 2-2 –Badlands National Park’s Boundary6 It was established as the Badlands National Monument in 1939, and was redesignated as a national park in 1978. The area of the park that is actually considered a Class I area is the Badlands Wilderness Area, which consists of 64,000 acres in the north unit.

2.2 Wind Cave National Park

Wind Cave National Park lies approximately 10 m iles north of Hot Springs in southwestern South Dakota (see Figure 2-3). It was the first ca ve to be designated a national park anywhere in the world and is currently the fourth longe st cave in the world with 119.58 miles (192.45 kilometers) of explored cave passageways.

Figure 2-3 – Wind Cave National Park’s Boundary

Aboveground, the park includes 28,295 acres of mixed- grass prairie, pondero sa pine forest, and associated wildlife (see Figure 2-4). The park ’s mixed-grass prairie is one of the largest remaining and home to bison, elk, pronghorn, mule deer, and prairie dogs. The view from7 Lookout Tower on Rankin Ridge displays a spect acular view of the mi xed-grass prairie and ponderosa pine forest (see Figure 2-5).

Figure 2-4 –Prairie, Forest, and Bison at Wind Cave (Courtesy of National Park Service)

Figure 2-5 – View from Lookout Tower (C ourtesy of National Park Service)



### 3.0 Baseline, Natural and Unif orm Rate of Improvement

In the mid-1980’s, the IMPROVE (Interagency M onitoring of Protected Visual Environments) program was established to measure visibility impairment in Class I areas throughout the United States. The monitoring site s are operated and maintained through a formal cooperative relationship between the EPA, National Park Serv ice, U.S. Fish and Wildlife, Bureau of Land Management, and U.S. Forest Service.

The objectives of the IMPROVE program include es tablishing the current visibility and aerosol conditions in Class I areas; identifying the chemi cal species and emission sources responsible for existing human-made visibility impairment; docum enting long-term trends for assessing progress towards the national visibility goals; and support the requirements of the regional haze rule by providing regional haze monitoring representing all visibility-protected Class I areas where practical.

The data collected at the IMPR OVE monitoring sites ar e used by federal land managers, industry planners, scientists, public interest groups, and air quality regulators to better understand and protect the visual air quality resource in Class I areas. Most importantly, the IMPROVE8 program scientifically documents for American citi zens, the visual air quality of their wilderness areas and national parks.

The IMPROVE network consists of aerosol and op tical samplers. Every IMPROVE site deploys an aerosol sampler to measure speciated fine aeroso ls and coarse mass. Se lect sites also deploy a transmissometer and nephelometers to measure li ght extinction and scattering respectively, as well as automatic camera systems to visually meas ure the scenery. Particul ate concentration data is obtained every 24 hours and converted into r econstructed light extinction through a complex calculation using the IMPROVE equa tion which may be viewed at:

http://vista.cira.colostate.edu/improve/Tools/ReconBext/reconBext.htm

Light extinction, the impairment of visibility, occu rs due to particles and gases that reflect and absorb light. Reconstructed li ght extinction (denoted as b ext ) is expressed in units of inverse mega meters (1/Mm or Mm-1).

In accordance with 40 CFR 51.308(d)(2), states are required to track visibility conditions in terms of the Haze Index (HI) metric expressed in the deciviews. The relationship between light extinction in Mm-1, Haze Index in deciviews, and visual range in kilometers is indicted by the scale in Figure 3-1.

Figure 3-1 – Light Extinction-Ha ze Index-Visual Range Scale 1

A comparison of the light extinction, haze index, and visual range at di fferent levels may be viewed in Figure 3-2 for the Badlands National Pa rk. Generally, a one deciview change in the Haze Index is likely humanly perceptible under ideal conditions regardless of background visibility conditions.

The IMPROVE data undergo quality assurance an d control procedures and analyses by its

contractors and the National Park Service before it is released. The aerosol and optical data are made publicly available approximately nine m onths after collection. In addition, seasonal analysis reports are prepared. IMPROVE program resources are available at:

http://vista.cira.colostate.edu/Improve.

There are two IMPROVE monitoring sites in Sout h Dakota. One is located at the Badlands

National Park and the other at Wind Cave Nationa l Park. The Badlands National Park operates an IMPROVE site (identified as “BADL1”) located on a gently sloping flat in the eastern portion of the Badlands National Park, approximately tw o miles northeast of Interior, South Dakota. DENR operates an ambient air monitoring site at the same location (see Figure 3-3). The site9 elevation is 2,415 feet and the lo west elevation in the area is the White River at 2,320 feet, approximately two miles south of the monitoring site.

The Wind Cave National Park operates an IMPROVE site (identified as “WICA1”) located near the park’s visitors center (see Figu re 3-4). Site elevation at the monitoring site is 4,240 feet and the general topography is hilly.

Figure 3-2 – Comparison at Different Levels
Deciview = 5; B ext = 16; visual range = 240 km

Deciview = 11; B ext = 30; visual range = 130 km Deciview = 19; B ext = 65; visual range = 60 km

Deciview = 23; B ext = 98; visual range = 40 km10 Figure 3-3 – Badlands’ IMPROVE and State Monitoring Site

Figure 3-4 – Wind Caves’ IMPROV E and State Monitoring Site11 3.1 Baseline Visibility Conditions

In accordance with 40 CFR § 51.308(d)(2)(i), baseline visibility conditions for the most impaired and least impaired days are calculated using available monitoring data from calendar year 2000 to 2004. The rule requires the state to establish the average degree of visibility impairment for the most and least impaired days for each calendar year from 2000 to 2004 and average these

annual values to determine the ba seline visibility conditions.

DENR determined the baseline visibility condi tions for the Badlands and Wind Cave National Parks based on IMPROVE data from the respec tive park. In the case where a day in the IMPROVE database did not have enough data to cal culate a deciview valu e, the data was not considered in determining the baseline visibility conditions. The baseline visibility conditions was determined by calculating the average deciview value for the 20% least impaired (best) and most impaired (worst) days for each of th e five years (2000 through 2004) and by averaging those five year values. The baseline visibility conditions for the Badlands and Wind Cave

National Parks are summarized in Table 3-1.

Table 3-1 – Baseline Visibility Conditio ns in South Dakota’s National Parks

Badlands National Park Wind Cave National Park

20% Least 20% Most 20% Least 20% Most

Calendar Year Deciviews Deciviews Deciviews Deciviews

2000 7.46 18.14 5.62 16.07

2001 7.45 17.63 5.11 15.47

2002 6.69 16.18 5.24 16.75

2003 6.34 17.81 5.02 16.12

2004 6.62 16.04 4.82 15.25 5-Year Average 6.91 17.14 5.16 15.84

The actual raw IMPROVE data used to determin e the baseline visibil ity conditions may be viewed at the following website:

http://views.cira.colostate.edu/web/DataWizard/

3.2 Natural Visibility Conditions

In accordance with 40 CFR § 51.308(d)(2)(iii), a co re requirement in the State Implementation Plan for the regional haze program is the establ ishment of natural visibility conditions for the 20% most impaired and 20% least impaired days. To assists states in determining natural visibility conditions, EPA published “ Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Program” , in September 2003. The guidance identifies the primary cause of regional haze for many parts of the country is due to light scatteri ng resulting from fine particles (e.g., particulate matter 2.5 microns in diameter or less). The fine particulate is composed of a variety of chemical species su ch as carbonaceous speci es (e.g., organics and12 elemental carbon) as well as ammonia, nitrate, sulfates, and soil. Coar se particulate which is particulate matter ranging in size from 2.5 to 10 mi crons in diameter can al so contribute to light scattering. These components can occur both natura lly and as the result of human activity.

The ultimate goal of the regional haze program is to remedy existing and prevent human-caused impairments of visibility and achieve natural conditions in ea ch Class I area by 2064. It is recognized that natural conditions are not consta nt; but change over time. To compensate for varying natural processes, natu ral visibility conditions are based on a long term average condition analogous to the 5-year average conditions for the 20% most impaired and 20% least impaired days. In addition, as the difference between current and natural conditions become smaller and methods of estimating natural conditions improve, natural conditions may change as the regional haze program for each state is re-evaluated.

The natural condition for each Class I area is defined as the level of visibility (in deciviews) for the 20% most impaired days and 20% least impa ired days that would exist if there were no manmade impairment. Since no visibility m onitoring data exists from the pre-manmade impairment period, the EPA developed guidanc e on how to estimate natural conditions. Generally, for each Class I area in the western United States, the natural condition for the 20% most impaired days is determined by adding two standard deviations to the annual average of IMPROVE monitoring data. Simila rly, the natural condition for the 20% least impaired days is determined by subtracting two standard devia tions to the annual average of the IMPROVE monitoring data.

EPA’s guidance on determining natural conditions provides two methods of estimating natural

conditions. The first method is considered the default natural conditions . In this method, EPA provides estimates of natural conditions for each Class I area. In the second method, states may estimate site specific natural cond itions if the state can provide sufficient evidence that supports

refined natural conditions.

3.2.1 Default Natural Conditions

EPA developed default values for natural conditi ons to assist states in determining natural

conditions. EPA’s estimates for the natural levels of fine particul ate constituents and of coarse particles were derived from the National Ac id Precipitation Assessment Program (NAPAP)

“

Acidic Deposition: State of Science and T echnology: Report 24 – Vi sibility: Existing and Historical Conditions – Cause and Effects” , published in October 1990. The estimate of natural conditions presented in the NAPAP report separates the regions of the United States into the

eastern half and western half. The eastern half consists of all states east of the Mississippi River, and up to one tier of states west of the Mississippi River. The western half includes the desert and mountain regions of the Mountain and Pacific Time zones. From this description, South

Dakota is located in the wester n region; but should be evaluated to determine which natural conditions best represent South Da kota since it is on the border of the eastern and western half.

The NAPAP report estimated natural background c oncentrations for six major components of fine aerosols: sulfates, organics , elemental carbon, amm onium nitrate, soil dus t, and water for the eastern and western regions of the United States . The NAPAP report also estimated the natural13 background for coarse particulate matter. The es timates of natural concentration were based on the following:

1. Compilations of natural versus manmade emission levels;

2. Ambient measurements in remote areas (especially in the Southern hemisphere); and

3. Regressions studies using manm ade and/or natural tracers.

EPA mentioned in the guidance the studies cited in the Appe ndix of the NAPAP report were conducted in relatively remote areas. Therefore, EPA believes it is reas onable to assume the contribution of fire to the particulate matter ma ss in the NAPAP estimates represents the natural regional contribution of fire. DENR is not su re it agrees with this assumption since fire suppression has occurred for many years disrupting th e natural fire process even in remote areas.

Table 3-2 lists the average natu ral background levels of aerosol s and light extinction and was derived from Table 2-1 of EPA’s guidance, which is different than the natural background levels established in the NAPAP report. The reason fo r the difference is noted in the footnotes for

Table 3-2. There was no value listed for sea salt.

Table 3-2 – Average Natural Background Concentration Levels

Aerosol Component East (μg/m 3 ) West (μg/m 3 )

Ammonium sulfate 1 0.23 0.12 Organic carbon mass 2 1.40 0.47

Elemental carbon 0.02 0.02

Ammonium nitrate 0.1 0.1

Soil Dust 0.5 0.5

Coarse Mass 3.0 3.0

1 – Values adjusted to represent chemical species in current IMPROVE light extinction algorithm; Trijonis estimates were 0.1 mi crograms per cubic meter (μg/m 3 ) and 0.2 μg/m 3 of ammonium bisulfate; and

2 – Values adjusted to represent chemical species in current IMPROVE light extinction algorithm; Trijonis estimates were 0.5 μg/m 3 and 1.5 μg/m 3 of organic compounds.

The average natural background concentrations leve ls in Table 3-2 were used in the formula displayed in Equation 3-1 to determ ine the natural light extinction (b ext ), which is used to characterize air pollution impacts on visibility. Light extinction is the fractional loss of the intensity of light per unit of distance caused by the scatteri ng and absorption of gases and particles in the air.

Equation 3-1 – Natural Light Extinction Formula 

##                        10 6

. 0 10 4 3 3        CM soil LAC OCM nitrate RH f sulfate RH f b

ext Where:

 b ext = natural light extinction, in Mm -1 ;

 f (RH) = relative humidity correction factor;

 OCM = organic carbon mass, in μ/m 3 ;

 LAC = elemental carbon, in μ/m 3 ; and

 CM = coarse mass, in μ/m 3

.14 The natural condition for South Dakota’s Class I areas based on the formula in Equation 3-1 are listed in Table 3-3 and derived from Appendi x B in EPA’s guidance for estimating natural

conditions.

Table 3-3 –Natural Background Conditio ns for South Dakota’s Class I Areas

Class I

Area Bext 1 Annual Average 20% Least Impaired Days 20% Most Impaired Days

Badlands 16.06 4.74 deciview 2.18 deciview 7.30 deciview

Wind Cave 15.97 4.68 deciview 2.12 deciview 7.24 deciview

1 – Natural light extinction in inverse Mega meters (Mm -1 ).

3.2.2 Improved Default Natural Conditions

Since EPA’s guidance was written a revised natu ral light extinction form ula was developed and adopted by EPA as the basis for the regional haze metric used to track progress in reducing haze levels in Class I areas. The new IMPROVE equa tion accounts for the effect of particle size distribution on light extinction of small and large size sulfate, n itrate and organic carbon mass.

The revised formula is di splayed in Equation 3-2.

Equation 3-2 – Revised Natural Light Extinction Formula

)] ( [ 33

. 0 ] )[ ( 7

. 1 ] [ 6

. 0 ] [ ] [ 10 ] arg [ 1

. 6 ] [ 8

. 2 ] arg )[ ( 1

. 5 ] )[ ( 4

. 2 ] arg )[ ( 8

. 4 ] )[ ( 2

. 2

2 ppb NO Scattering Rayleigh salt sea RH f matter coarse soil carbon absorbing light mass organic e l mass organic small nitrate e l RH f nitrate small RH f sulfate e l RH f sulfate small RH f b

ss L s L s ext

           

The total sulfate, nitrate and organic compound concentrations are spli t into two fractions representing small and large size distributions of each component. The formula for the large and small sulfate, nitrate and organic mass is disp layed in Equation 3-3. In addition, the relative humidity correction factor in Equation 3-2 is also based on small size distribution ( f

S (RH)) and large size distribution ( f

L (RH)) for sulfate and nitrate and for sea salt ( f

SS (RH)). The relative humidity correction factors were derived from the “ Federal Land Managers’ Air Quality Related Values Workgroup (FLAG) ,” drafted June 27, 2008, and can be viewed in Table 3-4.

Equation 3-3 – Large and Small Formulas 

##      

  

    e L Total Small m ug Total for Total e L m ug Total for Total

m ug Total

e L

arg 20

arg 20

, 20 arg

3 3

3

      15 Table 3-4 – Relative Humidity Correction Factor (f(RH))

Class I Month

Size Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Badlands

Small 2.94 2.96 3.01 2.87 3.10 2.91 2.64 2.59 2.56 2.58 3.11 2.98 Large 2.31 2.31 2.31 2.21 2.34 2.25 2.08 2.05 2.02 2.05 2.38 2.33

Sea Salt 3.37 3.33 3.27 3.05 3.25 3.15 2.89 2.81 2.74 2.82 3.41 3.38

Wind Cave

Small 2.81 2.81 2.86 2.82 3.06 2.81 2.50 2.46 2.44 2.52 2.97 2.83 Large 2.23 2.22 2.22 2.18 2.32 2.18 2.00 1.97 1.95 2.00 2.30 2.24

Sea Salt 3.25 3.20 3.13 3.01 3.22 3.06 2.75 2.68 2.63 2.75 3.28 3.24

The result of the revised light extinction is us ed in the formula displayed in Equation 3-4 to estimate the annual average of the haze index values (HI), in deciviews. DENR calculated the

HI value for each month for each Class I area. The average HI value for each Class I area may

be viewed in Table 3-5.

Equation 3-4 – Annual Average Haze Index 

##   10 ln 10   ext b HI

Where:

 HI = annual average of the haze in dex values, in deciviews; and

 b ext = natural light extinction, in Mm -1

.

In EPA’s guidance, it was determined that th e frequency distribution behaves normally (10 th and

90 th percentile HI) for Class I areas. This allows the 20% least impaired and 20% most impaired days to be determined using the annual averag e haze index and the formul as in Equation 3-5 and 3-6, respectively. In EPA’s guidance, it was determ ined that the average standard deviation in

the East is 3 deciviews and in the West it is 2 deciviews. DENR stayed consistent with using

western values and used a standard deviation of 2 deciviews. The 10 th and 90 th percentile was calculated for each month for each Class I area. The results may be viewed in Table 3-5.

Equation 3-5 – Natural Least Impaired Days Formula

sd HI P 28

. 1 10

 

Equation 3-6 – Natural Most Impaired Days Formula

sd HI P 28

. 1 90   Where:

 P10 = Natural 20% least impaired days, in deciviews;

 P90 = Natural 20% most impaired days, in deciviews;

 HI = annual average haze index, in deciviews; and

 sd = standard deviation of the daily haze index values for that area, in deciviews.16 Table 3-5 –New Formula Natural Background Conditions for South Dakota’s Class I Areas

Class I Annual Average Natural Background

Area Haze Index Least Impaired Days Most Impaired Days

Badlands 4.88 deciview 2.32 deciview 8.06 deciview

Wind Cave 4.85 deciview 2.29 deciview 7.41 deciview

3.2.3 Baseline and Default Natural Conditions Comparison

The natural background concentration levels are es timated for long term average conditions. In some cases the natural background concentration le vel may have higher concentrations than the baseline concentrations or for any other 5- year period. If this occurs, EPA’s guidance recommends that the natural background con centration level should be replaced with the corresponding measured value.

DENR used the IMPROVE data from each national park to determine the baseline concentration and compared the concentrations to the natura l background concentrations in Table 3-2. Table 3-6 displays the comparison.

Table 3-6 – Comparison of Natura l versus Baseline Concentrations 1

Background

Natural Badlands Wind Cave

West Least Most Least Most Aerosol Component (μg/m 3 ) (μg/m 3 ) (μg/m 3 ) (μg/m 3 ) (μg/m 3 )

Ammonium sulfate 0.12 2 0.49 2.63 0.41 2.07 Organic carbon mass 0.47 3 0.62 3.17 0.50 3.55

Elemental carbon 0.02 0.08 0.26 0.07 0.30

Ammonium nitrate 0.10 0.16 0.76 0.12 0.98

Soil Dust 0.50 0.33 0.98 0.24 0.86

Coarse Mass 3.00 2.53 9.90 1.78 5.89

1 – Units are in micrograms per cubic meter (μg/m 3 );

2 – Values adjusted to represent chemical species in current IMPROVE light extinction algorithm; Trijonis estimate was 0.1 μg/m 3 of ammonium bisulfate; and

3 – Values adjusted to represent chemical species in current IMPROVE light extinction algorithm; Trijonis estimate was 0.5 μg/m 3 of organic compounds.

Based on the comparison, the aerosol components in the baseline data for 2000 through 2004 for the 20% least impaired days are less than the natu ral conditions for soil dust and coarse mass at

both the Badlands and Wind Cave National Parks (see bolded values in Table 3-6). Although the soil dust and coarse mass for the baseline data is less than the values for natural conditions, DENR will use the values established in EPA’s guidance for the initial Regional Haze State Implementation Plan and re-evaluate this in future State Implementation Plan reviews. Table 3-7 displays the natural conditi ons and compares it to th e baseline data for 2000-2004.17 Table 3-7 – Baseline versus Na tural Background (Deciviews)

Class I Baseline Natural Difference Baseline Natural Difference

Area 20% Least Impaired Days 20% Most Impaired Days

Badlands 6.91 2.32 4.59 17.14 8.06 9.08

Wind Cave 5.16 2.29 2.87 15.84 7.41 8.43

3.2.4 Refined Natural Conditions

EPA identifies any refined approach for determini ng natural visibility c onditions should be based on accurate, complete, and unbiased information and should be developed using a high degree of scientific rigor. The refined natural concentrat ion estimates must retain the distinction between natural and anthropogenic components. For ex ample, just like EPA’s default natural concentrations, the refined natural concentr ations should not exceed actual measured concentrations of that species over a 5-year period.

EPA indicates additional information will become available over the years to improve on the default natural concentrations such as the following:

1. Implementation of a coordinated fire da ta system or fire tracking system;

2. The collection of multiple years of speciated particulate matter data in mandatory Class I areas and the assessment of potential contributio ns by natural fire events using data from the fire tracking system;

3. Development of chemical analys is techniques to identify carbon attributed to fire versus other sources;

4. Development of improved emissions factors a nd tracking of fire ac tivity levels; and

5. Improved regional scale fire modeling or re mote sensing tools to retrospectively determine whether smoke from a fire impacted a Class I area air shed.

DENR agrees more refined natural species concen trations will be developed in the coming years that are more specific to a national park and will review this new information as it periodically reviews its Regional Haze State Implementation Plan.

3.3 Uniform Rate of Improvement

In accordance with 40 CFR § 51.308(d)(2)(iv)(A), th e initial implementati on plan shall address

the difference between the baseli ne and natural conditions for th e 20% most impaired and 20% least impaired days. In accordance with 40 CF R § 51.308(d)(1)(i)(B), the state is required to determine the rate of progress needed to attain natural visibility conditions by the year 2064. The rate of progress is based on the difference between the baseline visibility conditions and the natural visibility conditions for 20% most impaired days for each Class I area.

The uniform rate of visibility improvement, measured in deciview s, is determined by taking the difference between the baseline visibility condi tions and the natural vi sibility conditions and dividing by 60 years, which is th e time frame for attaining natural visibility conditions by 2064. The uniform rate of improvement is required to be considered as the state establishes its reasonable progress goals for atta ining natural visibility condi tions. The uniform rate of18 improvement for the Badlands and Wind Cave National Parks is based on the formula in Equation 3-7 and the baseline and natural back ground valued in Table 3-7. The results are displayed in Table 3-8. The uniform rate of improvement was calculated for the 20% most impaired days for each national park.

Equation 3-7 – Uniform Rate of Progress 

##   60 Pr 

  Natural Baseline ogress of Rate Uniform

Table 3-8 – Annual Uniform Rate of Improvement Description Badlands Wind Cave Annual Improvement 0.1620 deciviews 0.1420 deciviews

The uniform rate of improvement was used to establish the slope of reduction necessary to achieve the natural visibility conditions in 2064. The slope of reduction for the 20% most impaired days for the Badlands and Wind Cave National Parks are displayed in Figure 3-5.

The improvement needed by 2018 was calculate d based on the annual uniform rate of improvement identified for each Class I area. The baseline is based on calendar years 2000 through 2004. Therefore, there are 14 years from the baseline to the first planning period or 2018. The improvement needed for the 20% most impaired days by calendar year 2018 for each Class I area was determined by multiplying the a nnual uniform rate of improvement by 14 years then subtracting that from the baseline value for the 20% most impaired days in Table 3-7. The result is displayed in Figure 3-5.

Figure 3-5 – Uniform Rate of Improvement (a) Badlands National Park

0.00 3.00 6.00 9.00 12.00 15.00 18.00

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

YearDeciviews

Reasonable Progress 2018 (14.89 deciviews) Natural (7.44 deciviews)19 (b) Wind Cave National Park

0.00 3.00 6.00 9.00 12.00 15.00 18.00

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

YearDeciviews

Reasonable Progress 2018 (13.94 deciviews) Natural (7.41 deciviews)



### 4.0 IMPROVE Data for Class I Areas

The data from the IMPROVE monitoring sites identifies the composition of the pollutants impacting our Class I areas and consists of amm onia sulfates fine (ammS O4f), ammonia nitrates fine (ammNO3f), organic mass carbon (OMC), elem ental carbon fine (Ecf), soil, coarse mass (CM), and sea salt. The IMPROVE data has been collected at the Badlan ds National Park since

1988 and the Wind Cave National Pa rk since 2000. DENR is using the IMPROVE data to help determine what air pollutants are causing or contri buting to visibility impairment in the Class I areas and assist in evaluating if each stat e is achieving the reasonable progress goals.

4.1 Aerosol Concentrations

The average aerosol concentration (micrograms per cubic meter (ug/m 3 )) and visibility (deciviews) per year during the baseline pe riod (2000-2004) for the 20% least (P10) and 20% most (P90) impaired days are summarized in Tabl e 4-1 for the Badlands National Park and Table

4-2 for the Wind Cave National Par k. The last line in each Ta ble provide the default natural

conditions that should be achieved for th e 20% most impaired days by 2064.

The baseline aerosol concentrations at the Ba dlands and Wind Cave National Parks during the 20% most impaired days are all similar and wi thin 22% or less of each other except for the coarse mass and sea salt. If you neglect sea salt, the aerosol with the grea test dissimilarity is

coarse mass with the Badlands National Park’s coarse mass baseline concen trations being greater

than at the Wind Cave National Pa rk. This would be expected because of the drier conditions

associated with the Badlands National Park. Coar se mass is typically generated from crushing or grinding operations, dust from paved or unpaved roads, windblown dust, etc.20 Table 4-1 – Badlands National Park Baseline Aerosol Concentrations 1
a) Aerosol Concentrations for 20% Least Impaired

P10 ammSO4f ammNO3f OMC Ecf SOIL CM Sea Salt

Year (Deciview) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 )

2000 7.46 0.64 0.20 0.64 0.08 0.26 2.08 0.01

2001 7.45 0.57 0.21 0.64 0.09 0.39 2.60 0.00

2002 6.69 0.37 0.12 0.62 0.09 0.44 3.21 0.00

2003 6.34 0.44 0.11 0.61 0.06 0.25 2.38 0.00

2004 6.62 0.43 0.17 0.57 0.07 0.33 2.39 0.01 5-yr 6.91 0.49 0.16 0.62 0.08 0.33 2.53 0.00

Natural 2.32 0.12 0.10 0.47 0.02 0.50 3.00 0.00

b) Aerosol Concentrations for 20% Most Impaired

P90 ammSO4f ammNO3f OMC Ecf SOIL CM Sea Salt

Year (Deciview) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 )

2000 18.14 2.72 0.50 4.78 0.40 1.00 10.14 0.00

2001 17.63 3.13 0.95 2.38 0.26 1.29 9.79 0.00

2002 16.18 2.45 0.63 2.22 0.19 1.14 12.17 0.10

2003 17.81 2.27 0.91 4.03 0.29 0.73 11.65 0.06

2004 16.04 2.55 0.83 2.43 0.16 0.74 5.77 0.02 5-yr 17.16 2.63 0.76 3.17 0.26 0.98 9.90 0.04

Natural 7.44 0.12 0.10 0.47 0.02 0.50 3.00 0.00

1 – Units are in micrograms per cubic meter (μg/m 3 ), “P10” = 20% least impaired days, “P90” = 20% most impaired days, “ammSO4f” = ammonia sulfate fine; “ammNO3f” = ammonia nitrate fine, “OMC” = organic mass carbon, “Ecf” = Elemental carbon fine, and “CM” = coarse mass.

Table 4-2 – Wind Cave National Park Baseline Aerosol Concentrations 1
a) Aerosol Concentrations for 20% Least Impaired

P10 ammSO4f ammNO3f OCM Ecf SOIL CM Sea Salt

Year (Deciview) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 )

2000 5.62 0.49 0.15 0.59 0.09 0.18 1.24 0.00

2001 5.11 0.43 0.13 0.44 0.06 0.28 1.75 0.00

2002 5.24 0.36 0.10 0.48 0.07 0.30 2.57 0.01

2003 5.02 0.40 0.08 0.54 0.06 0.22 1.89 0.00

2004 4.82 0.38 0.12 0.44 0.07 0.22 1.44 0.00 5-yr 5.16 0.41 0.12 0.50 0.07 0.24 1.78 0.00

Natural 2.29 0.12 0.10 0.47 0.02 0.50 3.00 0.00

b) Aerosol Concentrations for 20% Most Impaired

P90 ammSO4f ammNO3f OCM Ecf SOIL CM Sea Salt

Year (Deciview) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 )

2000 16.07 1.86 0.68 4.33 0.37 0.97 6.57 0.00

2001 15.47 2.25 1.26 2.48 0.23 0.82 5.99 0.00

2002 16.75 2.26 0.87 4.15 0.31 0.98 6.78 0.0021 P90 ammSO4f ammNO3f OCM Ecf SOIL CM Sea Salt

Year (Deciview) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 ) (u/m 3 )

2003 16.12 2.03 0.86 4.00 0.24 0.75 6.60 0.01

2004 15.25 1.94 1.24 2.79 0.33 0.77 3.49 0.02 5-yr 15.93 2.07 0.98 3.55 0.30 0.86 5.89 0.01

Natural 7.41 0.12 0.10 0.47 0.02 0.50 3.00 0.00

1 – Units are in micrograms per cubic meter (μg/m 3 ), “P10” = 20% least impaired days, “P90” = 20% most impaired days, “ammSO4f” = ammonia sulfate fine; “ammNO3f” = ammonia nitrate fine, “OMC” = organic mass carbon, “Ecf” = Elemental carbon fine, and “CM” = coarse mass.

The aerosol concentrations that appear to need to be reduced the most to achieve natural

concentrations at both nationa l parks are ammonia sulfate and elemental carbon. Ammonia

sulfates are derived from fossil fuel combusti on and the combustion of organic mass such as forest fires and the burning of grass. Elemen tal carbon is also generated from fossil fuel combustion; but is generally used as the main indicator of emissions from fires and other

combustion sources such as diesel emissions.

Organic carbon mass and ammonia nitrate aerosol c oncentrations at the tw o national parks would

also need to be reduced since current concentrat ions are approximately seven to 10 times greater than natural conditions. Orga nic carbon mass is derived from biomass burning, automobile emissions, fossil fuel combusti on, gas-to-particle conversion of hydrocarbons, etc. Ammonia nitrates are generated from sim ilar sources that generate amm onia sulfates along with organic decomposition.

4.2 Extinction Comparison

Extinction (inverse mega meters (Mm -1 )) is useful in relating visibility directly to particle species

concentrations. DENR took the IMPROVE data for the baseline period (2000-2004) for the 20% least and 20% most impaired days and summari zed it in Table 4-3 for the Badlands National

Park and Table 4-4 for the Wind Cave National Par k, except for sea salt since the concentrations

for sea salt are minimal.

Table 4-3 – Badlands National Park 1
a) Baseline Aerosol Concentrat ions for 20% Least Impaired
Extinction (bext) ammSO4f ammNO3f OMC Ecf SOIL CM

Year (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 )

2000 21.28 4.53 1.50 1.88 0.82 0.26 1.25

2001 21.15 3.85 1.58 1.87 0.89 0.39 1.56

2002 19.58 2.57 0.91 1.82 0.91 0.44 1.93

2003 18.90 3.00 0.81 1.78 0.63 0.25 1.43

2004 19.44 3.01 1.32 1.64 0.66 0.33 1.43 5-yr 20.07 3.39 1.23 1.80 0.78 0.33 1.52 % Without Rayleigh 36% 14% 20% 9% 4% 17%22 b) Baseline Aerosol Concentrations for 20% Most Impaired
Extinction (bext) ammSO4f ammNO3f OMC Ecf SOIL CM

Year (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 )

2000 63.49 18.99 3.63 18.74 4.04 1.00 6.08

2001 59.32 23.25 7.41 7.93 2.56 1.29 5.87

2002 51.28 17.43 4.68 7.36 1.86 1.14 7.30

2003 61.53 16.19 7.18 16.22 2.90 0.73 6.99

2004 50.73 18.83 6.48 8.53 1.57 0.74 3.46 5-yr 57.27 18.94 5.88 11.76 2.59 0.98 5.94 % Without Rayleigh 41% 13% 25% 6% 2% 13%

1 – Units are in inverse Mega meters (Mm -1 ), “B ext ” = natural light extinction, “ammSO4f” = ammonia sulfate fine; “ammNO3f” = ammonia nitr ate fine, “OMC” = organic mass carbon, “Ecf” = Elemental carbon fine, and “CM” = coarse mass.

Table 4-4 – Wind Cave National Park 1

a) Aerosol Concentrations for 20% Least Impaired
Extinction (bext) ammSO4f ammNO3f OMC Ecf SOIL CM

Year (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 )

2000 17.71 3.12 1.07 1.72 0.87 0.18 0.74

2001 16.75 2.65 0.88 1.27 0.63 0.28 1.05

2002 16.95 2.27 0.68 1.38 0.74 0.30 1.54

2003 16.58 2.48 0.53 1.58 0.63 0.22 1.14

2004 16.26 2.41 0.82 1.27 0.67 0.22 0.86 5-yr 16.85 2.58 0.80 1.44 0.71 0.24 1.07 % Without Rayleigh 38% 12% 21% 10% 3% 16%

b) Aerosol Concentrations for 20% Most Impaired
Extinction (bext) ammSO4f ammNO3f OMC Ecf SOIL CM

Year (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 ) (Mm -1 )

2000 51.94 11.60 4.69 17.00 3.74 0.97 3.94

2001 48.76 14.58 9.25 8.22 2.28 0.82 3.59

2002 56.18 14.98 6.06 16.95 3.14 0.98 4.07

2003 51.05 12.66 6.19 15.05 2.40 0.75 3.96

2004 47.94 12.80 9.19 9.73 3.25 0.77 2.09 5-yr 51.18 13.32 7.07 13.39 2.96 0.86 3.53 % Without Rayleigh 32% 17% 33% 7% 2% 9%

1 – Units are in inverse Mega meters (Mm -1 ), “B ext ” = natural light extinction, “ammSO4f” = ammonia sulfate fine; “ammNO3f” = ammonia nitr ate fine, “OMC” = organic mass carbon, “Ecf” = Elemental carbon fine, and “CM” = coarse mass.

DENR included in each table the percentage of visibility impairment based on each aerosol’s contribution to the extinction after subtracting out the Rayleigh affect. The Rayleigh affect is the scattering of light by particles much smaller than the wavelength of light. The percentages of extinction per aerosol for the 20% least and most impaired days for the Badlands and Wind Cave National Parks are displayed in Figure 4-1 and 4-2, respectively.23 Figure 4-1 – Badlands National Park Baseline Aerosol Extinction Comparison 1
a) Baseline Aerosol Extinction Percen tage for 20% Least Impaired Days

36%

14% 20% 9%

4% 17% 0%

ammSO4f ammNO3f OCM Ecf SOIL CM Sea Salt

b) Baseline Aerosol Extinction Percen tage for 20% Most Impaired Days

41%

13% 25% 6% 2% 13% 0%

ammSO4f ammNO3f OCM Ecf SOIL CM Sea Salt

1 – “ammSO4f” = ammonia sulfate fine; “ammNO3f” = ammonia nitrate fine, “OMC” = organic mass carbon, “Ecf” = Elemental carbon fine, and “CM” = coarse mass.

In the 20% least impaired days for the Badlands National Park, the aerosol that contributed the greatest visibility impairment is ammonia sulfate at 36%, which is almost double the percentage of the second greatest contributor. The sec ond greatest contributor is organic carbon mass at 20%. The third greatest contribut or is coarse mass at 17% follo wed closely by ammonia nitrates at 14%. Ammonia sulfate, organic carbon mass, coarse mass and ammonia nitrate represent 87%24 of the aerosol concentrations im pacting the 20% least impaired days in the Badlands National

Park.

In the 20% most impaired days for the Badlands National Park, the aerosol that contributed the greatest visibility impairment again is ammonia su lfate at 41%. Its cont ribution is not double the percentage of the second greatest contributor; but is close. Th e second greatest contributor is organic carbon mass at 25%. The third greatest contributor is coarse ma ss and ammonia nitrates at 13%, each. Ammonia sulfate, organic ca rbon mass, coarse mass and ammonia nitrate represent 92% of the aerosol c oncentrations impacting the 20% most impaired days in the

Badlands National Park.

Figure 4-2 – Wind Cave Baseline Aerosol Extinction Percentage a) Baseline Aerosol Extinction Percen tage for 20% Least Impaired Days 1

38%

12% 21% 10% 3% 16% 0%

ammSO4f ammNO3f OCM Ecf SOIL CM Sea Salt

1 – “ammSO4f” = ammonia sulfate fine; “ammNO3f” = ammonia nitrate fine, “OMC” = organic mass carbon, “Ecf” = Elemental carbon fine, and “CM” = coarse mass.

In the 20% least impaired days for the Wind Cave National Park, the aeroso l that contributed the greatest visibility impairment is ammonia sulfate at 38%, which is almost double the percentage of the second greatest contributor. The sec ond greatest contributor is organic carbon mass at 21%. The third greatest contribut or is coarse mass at 16% followe d by ammonia nitrates at 12%. Ammonia sulfate, organic carbon mass, coarse mass and ammonia nitrate represent 87% of the aerosol concentrations impacting the 20% least impaired days in the Wind Cave National Park.

In the 20% most impaired days for the Wind Cave National Park, the aerosol that contributed the greatest visibility impairment is organic carbon mass at 33%, followed closely by ammonia sulfate at 32%. The third greatest contributor is ammonia nitrates at 17% followed by coarse mass at 9%. Ammonia sulfate, organic carbon ma ss, coarse mass and ammonia nitrate represent 91% of the aerosol concentrations impacting th e 20% most impaired days in the Wind Cave

National Park.25 b) Baseline Aerosol Extinction Percen tage for 20% Most Impaired Days 1

32%

17% 33%

7% 2% 9% 0%

ammSO4f ammNO3f OCM Ecf SOIL CM Sea Salt

1 – “ammSO4f” = ammonia sulfate fine; “ammNO3f” = ammonia nitrate fine, “OMC” = organic mass carbon, “Ecf” = Elemental carbon fine, and “CM” = coarse mass.

There is a good comparison between the 5-year average concentration for each aerosol at the Badlands and Wind Cave National Park during the 20% least impaired days (see Figure 4-3(a)). Although these concentrations represent the 20% leas t impaired days, the concentrations are still greater than natural c onditions. DENR did not an ticipate the two national parks to have similar

concentrations since the Badlands National Park is predominantly mixed prairie grasses, bare

rock and sand while the Wind Cave National Park is mixed prairie grasses and ponderosa pine

forest.

Local influences on the 20% least impaired days woul d tend to influence just the park it is next

to and not the other. If lo cal influences were impacti ng the 20% least impaired days, concentrations at both parks would not be that similar. However, th e 5-year averaging may

smooth this out.

Depending on the distance, concentrations from regional influence would be well mixed and uniform as it impacts South Dakota’s two Class I areas. A uniform regional influence would tend to influence both national parks similarly.

DENR will evaluate this in its l ong-term strategy to determine if there are any impacts from local sources hidden by the 5-year average and/or if regional influence is the main reason for the

elevated concentrations on the 20% least impaired days.26 Figure 4-3 – National Park Extinction Comparison 1
a) National Park Comparison for 20% Least Impaired Days

0% 5% 10% 15% 20% 25% 30% 35% 40%

ammSO4f OCM CM ammNO3f Ecf SOIL Sea Salt

Badlands Wind Cave

b) National Park Comparison for 20% Most Impaired Days

0% 5% 10% 15% 20% 25% 30% 35% 40% 45%

ammSO4f OCM ammNO3f CM Ecf SOIL Sea Salt

Badlands Wind Cave

1 – “ammSO4f” = ammonia sulfate fine; “ammNO3f” = ammonia nitrate fine, “OMC” = organic mass carbon, “Ecf” = Elemental carbon fine, and “CM” = coarse mass.

For the 20% most impaired days, the comparison is not as similar. Fr om Figure 4.3(b), ammonia sulfate is impacting visibility at the Badlands Na tional Park at a greater degree than it is at the

Wind Cave National Park. At the Wind Cave National Park, organic carbon mass and ammonia sulfate have the greatest impact and provide approximately the same percentage of visibility impairment. This indicates that fires contribut e more to visibility impairment at Wind Cave27 National Park then at Badlands National Park because of the higher organic carbon mass

contribution.

Ammonia sulfates and organic carbon mass are generated from similar sources. Ammonia

sulfates are derived from fossil fuel combusti on and the combustion of organic mass such as forest fires and the burning of grass. Orga nic carbon mass is derived from biomass burning, automobile emissions, fossil fuel combustion, ga s-to-particle conversion of hydrocarbons, etc. The contribution of ammonia sulfates and organi c carbon mass from fossil fuel combustion from

industrial sources and mobile sources should tend to be constant thr oughout the year. The contribution from the burning of organic mass or from heating should tend to occur at certain times of the year and be evident by quarter.

4.3 Visibility Impairment Quarterly Trends

Visibility impairment is impacted by the aerosol concentrations, type of aerosols, and time of year. DENR looked at various char ts to determine if there were any trends based on the time of year for the 20% most impaired days. DENR re viewed the charts by quarter. For this review, the first quarter represents th e winter months (January thr ough March); the second quarter represents the spring months (April through June ); the third quarter represents the summer months (July through September); and the fourth quarter represents the fall months (October through December).

4.3.1 Number of Occurrences per Quarter

The first type of chart DENR looked at was the number of occurrences per quarter for the 20% most impaired days. Figure 4-4 provides th e quarterly comparison for the Badlands National

Park and Wind Cave National Park.

Figure 4-4 –Number of Occurrences by Quarter – 20% Most Impaired Days a) Badlands National Park Occurrences by Quarter

0 2 4 6 8 10 12 14Occurrences

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

1st 2nd 3rd 4th28 b) Wind Cave National Park Occurrences by Quarter

0 2 4 6 8 10 12 14 16Occurrences

2000 2001 2002 2003 2004 2005 2006 2007 2008

1st 2nd 3rd 4th

Based on the Badlands National Park data, the 4 th quarter (fall months) c onsistently appear to have the least number of visibility impairment occurrences during the 20 % most impaired days, especially for the baseline period (2000-2004). The 4 th quarter did experience an increase in 2008, which will need to be reviewed in the futu re to see if the increase continues. The occurrences in the remaining quarters increase and decrease with the 3 rd quarter (summer months) having the most occurrences in the baselin e period and in the last four years of data. One thing to note is the 2 nd quarter (spring months) is showing an increase in occurrences in the last three years, which will also need to be reviewed if this trend continues.

The number of occurrences ranged from zero to 13 occurrences per quarter. The greatest number of occurrences peaked in the 1 st quarter of 1993 at 13. From 2 000 to 2008, the greatest number

of occurrences occurs in the 3 rd quarter ranging from six to 12 occurrences per year. The 2 nd and

4 th quarter saw a rise in 2008 with the 1 st quarter showing a decline.

Overall, in the last few years the 2 nd and 3 rd quarter tend to have the most occurrences while the

1 st and 4 th quarter have the least number of occurren ces. The number of occurrences in the 2 nd
quarter has increased to where they had th e most occurrences in 2008, followed by the 3 rd
quarter, 4 th quarter and 1 st quarter.

The number of occurrences in the Wind Cave Na tional Park range from zero to 15 occurrences per quarter during the 20% most impaired days. The greatest number of o ccurrences occurred in

the 3 rd quarter during the baseline period (2000-2004) and peaked in 2003 at 15 occurrences.

The 4 th quarter consistently had th e least number of occurrences in the baseline period and ranged from two to four occurrences per quarter. For the last four years, the greate st number of

occurrences occurred in the 3 rd quarter ranging from six to 10 occurrences per year. The 4 th
quarter appears to have the least amount of o ccurrences ranging from zero to four occurrences per year. However, in 2008 the number of occurrences in the 1 st quarter dropped to where it has

the least number of occurrences at two.29 4.3.2 Extinction Trends by Quarter

DENR also charted the average extinction value for each quarter for ammonia sulfate, ammonia nitrate, organic carbon mass, and coarse mass during the 20% most impaired days for each national park since these four air pollutants comp rise over 90% of the visi bility impairment in each park. Figure 4-5 and 4-6 display the quarter ly data from 2000, which is the start of the baseline period, to 2008 for the Badlands and Wind Cave National Parks, respectively. In some cases, there is no quarterly extinction value for a certain year, which m eans there were no days

that contributed to the 20% most im paired days during that quarter.

In the 1 st quarter, ammonia sulfate followed by ammonia nitrate ha ve the greatest impact on visibility impairment in the Badlands Nationa l Park. Organic carbon mass and coarse mass have minimal impact in the 1 st quarter with an extinction value of approximately 5.0 inverse mega meters or less per pollutant. However, in 2008 organic carbon mass did increase from the normal trend to exceed ammonia nitrate in impac ting visibility impairment but still had less impact then ammonia sulfate.

Figure 4-5 – Badlands’ Quarterly Extinc tion Values for 20% Most Impaired Days a) Badlands: 1 st Quarter Average Extinction Comparison

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00Mm-1

2000 2001 2002 2003 2004 2005 2006 2007 2008

Ammonia Sulfate Organic Carbon Mass Ammonia Nitrate Coarse Mass

In the 2 nd quarter, ammonia sulfate still has the greatest impact on visibility impairment in the

Badlands National Park. The 2 nd quarter differs from the 1 st quarter with organic carbon mass tending to contribute more than ammonia nitrate. However, in some cases, organic carbon mass, ammonia nitrate, and coarse ma ss have approximately equal share in visibility impairment.30 b) Badlands: 2 nd Quarter Average Extinction Comparison

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00Mm-1

2000 2001 2002 2003 2004 2005 2006 2007 2008

Ammonia Sulfate Organic Carbon Mass Ammonia Nitrate Coarse Mass

In the 3 rd quarter, organic carbon mass tends to cont ribute the greatest im pact on visibility impairment followed by ammonia sulfate. What is interesting is ammonia nitrate in the 3 rd
quarter consistently contributes the least to visibility impairment with coarse mass being consistently higher than ammonia nitrate. The 3 rd quarter is typically the driest months in the

Badlands National Park which would increase in coarse mass contributions from windblown dust and from traffic on paved and unpaved road s. In 2008, organic carbon mass increased dramatically due to a one da y extinction value in the 3 rd quarter of 192 inverse mega meters on July 2, 2008. Looking ahead to the 3 rd quarter for the Wind Cave National Park (see Figure 4- 6(d)), Wind Cave National Park experienced a high level of organic carbon mass on that same day.

c) Badlands: 3 rd Quarter Average Extinction Comparison

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00Mm-1

2000 2001 2002 2003 2004 2005 2006 2007 2008

Ammonia Sulfate Organic Carbon Mass Ammonia Nitrate Coarse Mass31 d) Badlands: 4 th Quarter Average Extinction Comparison

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00Mm-1

2000 2001 2002 2003 2004 2005 2006 2007 2008

Ammonia Sulfate Organic Carbon Mass Ammonia Nitrate Coarse Mass

In the 4 th quarter, ammonia sulfate conti nues to contribute th e greatest to visibility impairment in the Badlands National Park followed by ammonia ni trate. Organic carbon mass tends to be a significant contributor with extinc tion values greater than 5.0 inve rse mega meters. Coarse mass extinction values were greater than 5.0 inverse mega meters in the early 2000 but have since dropped below that level and have mini mal impacts on visibility in the 4 th quarter.

Figure 4-6 – Wind Cave’s’ Quarterly Extin ction Values for 20% Most Impaired Days a) Wind Cave: 1 st Quarter Average Extinction Comparison

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00Mm-1

2000 2001 2002 2003 2004 2005 2006 2007 2008

Ammonia Sulfate Organic Carbon Mass Ammonia Nitrate Coarse Mass

In the 1 st quarter, ammonia sulfate a nd ammonia nitrate have the gr eatest impact on visibility impairment in the Wind Cave National Park. Organic carbon mass and coarse mass do not appear to have as much impact in the 1 st quarter with extinction values of around 5.0 inverse mega meters or less.32 b) Wind Cave: 2 nd Quarter Average Extinction Comparison

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00Mm-1

2000 2001 2002 2003 2004 2005 2006 2007 2008

Ammonia Sulfate Organic Carbon Mass Ammonia Nitrate Coarse Mass

In the 2 nd quarter, ammonia sulfate ha s the greatest impact on visibi lity impairment in the Wind Cave National Park in the last five years. Organic carbon mass increased during that period with ammonia nitrate and coarse mass having minimal impact.

c) Wind Cave: 3 rd Quarter Average Extinction Comparison

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00Mm-1

2000 2001 2002 2003 2004 2005 2006 2007 2008

Ammonia Sulfate Organic Carbon Mass Ammonia Nitrate Coarse Mass

In the 3 rd quarter, organic carbon mass ha s the greatest impact on visibility impairment followed by ammonia sulfate. Coarse mass is next and consistently around 5.0 i nverse mega meters. Ammonia nitrate tends to have minimal impact in the 3 rd quarter. The high organic carbon mass average in 2008 was also due to a 179 inverse mega meter reading on July 2, 2008. This is the same date which resulted in a high reading at th e Badlands National Park, which is indicative of regional transport. On June 28, 2008, smoke from Canada forest fires were observed in the Black Hills region and probably is the source of the organic carbon mass concentrations on July 2, 2008.33 d) Wind Cave: 4 th Quarter Average Extinction Comparison

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00Mm-1

2000 2001 2002 2003 2004 2005 2006 2007 2008

Ammonia Sulfate Organic Carbon Mass Ammonia Nitrate Coarse Mass

In the 4 th quarter, ammonia sulfates a nd ammonia nitrate continue to contribute the greatest with one exception in 2005. In 2005, organic car bon mass increased based on an October 25, 2005 extinction value of 109 inverse mega meters. In this case, the same high reading was not observed in the Badlands National Park, which means the higher level may be caused locally. After researching possible causes, it was di scovered on October 25, 2005, a prescribed fire covering 1,215 acres was burned in the Wind Cave National Park which could be the contributor of the high organic carbo n mass concentration.

This analysis indicates that ammonia sulfates an d ammonia nitrate contributions are the greatest

in the 1 st and 4 th quarter of each year at bot h national parks which is an indication the sources are being impacted by fuel combustion or even prescr ibed fires. Since it is occurring during the colder months, the sources of these emissions coul d also be caused by industrial and residential heating. Organic carbon mass tends to start contributing more in the 2 nd quarter and is the greatest contributor in the 3 rd quarter at both national parks. Th e driest months usually occur in

the 3 rd quarter, which is also when mo st wild fires typically occur.

Coarse mass contributions ar e the greatest during the 2 nd and 3 rd quarters. During these quarters, you would typically have greater coarse mass em issions from windblown dust, traffic on paved and unpaved roads, etc.

4.3.3 Visibility Impairment Trends

DENR charted the average visibility (deciviews) that occurred in each national park for each quarter during the 20% most impaired days. Figure 4-7 and 4-8 display the quarterly data for the

Badlands and Wind Cave Nationa l Parks, respectively.

The average visibility impairment for the 20% most impaired days per quarter per year in the Badlands National Park, measured in deciviews, a ppears to be declining in every quarter except

the 3 rd quarter. In the 3 rd quarter the slope appears to be flat. As seen in the quarterly extinction34 review, the aerosol wi th the greatest contribution in the 3 rd quarter is orga nic carbon mass and may be the reason the deciview values in the 3 rd quarter are flat.

Figure 4-7 – Badlands’ Quarterly Da ta for 20% Most Impaired Days a) Badlands: 1 st Quarter Visibility Impairment Trend

0.00 5.00 10.00 15.00 20.00 25.00

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007Deciviews

1st Linear (1st)

b) Badlands: 2 nd Quarter Visibility Impairment Trend

0.00 5.00 10.00 15.00 20.00 25.00

1988 1989 19 90 19 91 1992 1993 1994 199 5 1996 1997 19 98 1999 2000 2001 20 02 20 03 2004
2 005 20 06 2007 2008Deciviews

2nd Linear (2nd)35 c) Badlands: 3 rd Quarter Visibility Impairment Trend

0.00 5.00 10.00 15.00 20.00 25.00

1988 1989 1990 1991

1 9 9 2 1993 1994 1995 1996

1 9 9 7

1 9 9 8 1999
2 0 0 0 2001 2002
2 0 0 3 2004
2 0 0 5 2006 2007
2 0 0 8Deciviews

3rd Linear (3rd)

d) Badlands: 4 th Quarter Visibility Impairment Trend

0.00 5.00 10.00 15.00 20.00 25.00

1988

1 9 8 9 19 9 0 1991 1992 1993

1 9 9 4 1995 1996

1 9 9 7 1998 1999 2000 2001 2002 2003 2004
2 0 0 5 2006 2007 2008Deciviews

4th Linear (4th)

The average visibility impairment for the 20% mo st impaired days per quarter per year in the Wind Cave National Park, measured in deciviews, appear flat with a slight increase in the 1 st and

2 nd quarter. The slight increase in the 1 st quarter appears to be the greatest. A review of the quarterly extinction data for the 1 st quarter does not display an increase in any particular pollutant (see Figure 4.6(a)). There is some fluctuation in the ammonia sulfate and ammonia

nitrate extinction values but that does not appear to be enough to result in such an increase in the slope. This will need to be revi ewed in the future to see if the trend continues and what may be causing it.36 Figure 4-8 – Wind Cave’s Quarterly Data for 20% Most Impaired Days a) Wind Cave: 1 st Quarter Visibility Impairment Trend

0.00 5.00 10.00 15.00 20.00 25.00

2000 2001 2002 2003 2004 2005 2006 2007 2008Deciviews

1st Linear (1st)

b) Wind Cave: 2 nd Quarter Visibility Impairment Trend

0.00 5.00 10.00 15.00 20.00 25.00

2000 2001 2002 2003 2004 2005 2006 2007 2008Deciviews

2nd Linear (2nd)

c) Wind Cave: 3 rd Quarter Visibility Impairment Trend

0.00 5.00 10.00 15.00 20.00 25.00

2000 2001 2002 2003 2004 2005 2006 2007 2008Deciviews

3rd Linear (3rd)37 d) Wind Cave: 4 th Quarter Visibility Impairment Trend

0.00 5.00 10.00 15.00 20.00 25.00

2000 2001 2002 2003 2004 2005 2006 2007 2008Deciviews

2nd Linear (2nd)



### 5.0 Source Apportionment

5.1 Air Emission Inventory

In accordance with 40 CFR § 51.308(d)(4)(v), a stat ewide inventory of emissions of pollutants that are reasonably anticipated to cause or contribute to visibility impairment in any Class I area shall be included as part of the state’s m onitoring strategy. The i nventory must include emissions for a baseline year, emissions for the most recent year for which data is available, and estimates of future projected emissions.

DENR and WRAP based the em ission inventory on EPA’s “ Emissions Inventory Guidance for Implementation of Ozone and Particulate Matt er National Ambient Air Quality Standards (NAAQS) and Regional Haze Regulations .” The guidance establishes the baseline year as 2002. WRAP projected an emission i nventory for 2018. The most curre nt air emission inventory for South Dakota is 2009; but only contains air emissions from Title V air quality permitted sources.

The guidance specified what pollutants should be inventoried, which are reasonably anticipated

to cause or contribute to visibi lity impairment in a mandatory Cl ass I area. The air pollutants of concern are primary particulate ma tter (PM), sulfur dioxide (SO 2 ), nitrogen oxides (NO x ), volatile organic compounds (VOCs), and ammonia (NH 3 ). Particulate matter will be further separated into primary particulate matter coarse and fine. Primary particulate matter coarse is particulate matter 10 microns in diameter or less (PM10) minus primary particulate matter fine, which is particulate matter 2.5 microns in diam eter or less (PM2.5). Where available, DENR will include primary organic aerosol (organic ca rbon) and elemental carbon (EC). The definition

of VOC is defined in the Admini strative Rules of South Dakota, Section 74:36:01:01(77), which is derived from 40 CFR § 51.100.

The pollutants that are reasonably anticipated to cause or contribut e to visibility impairment are emitted by natural and anthropogenic sources. The goal of the regional haze program is to38 minimize the impacts from anthropogenic sources and bring our Class I ar eas into their natural condition. Determining natural condition is difficu lt since anthropogenic activity has influenced our Class I areas for many years. This influen ce includes mobile source s, electric generation, prescribed burning, manufacturing activities, fa rming, preventing and fighting fires, and many

other activities that result in the air emissions of the above pollutants.

In support of WRAP’s regional h aze air quality modeling efforts, the Regional Modeling Center developed annual emissions inventories for a 2002 actual emissions base case, a planning case to represent the 2000-04 regiona l haze baseline period using averag es for key emissions categories, and a 2018 base case of projected emissions dete rmined using factors known at the end of 2005. All emission inventories developed by WRAP used the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling syst em. Each of these inventorie s has undergone a number of revisions throughout the development process to arrive at the fina l versions used in Community Multi-Scale Air Quality (CMAQ) and CAMx air quality modeling. The WRAP emission inventories developed by the Regi onal Modeling Center include:

1. The 2002 base case emissions scenario, referred to as “2002 Base Case” or “Base02”. The purpose of the Base02 inventory is to repr esent the actual conditions in calendar year 2002 with respect to ambient air quality and the associat ed sources of criteria and particulate matter air pollutants. The Base02 emissions inventories are used to validate the air quality model and associated databases and to demonstrate acceptable model performance with respect to replicatin g observed particulate matter air quality.

2. The 2000-04 baseline period planning case emissions scenario is referred to as “Plan02”. The purpose of the Plan02 inventory is to re present baseline emission patterns based on average, or “typical”, conditions. This i nventory provides a basis for comparison with the 2018 projected emissions as well as to gauge reasonable progre ss with respect to future year visibility.

3. The 2018 base case emissions scenario is refe rred to as “2018 Base Case” or “Base18”. These emissions are used to represent condi tions in 2018 with respect to sources of criteria and particulate matter air pollutants taking into consid eration growth and controls. Modeling results based on this emission invent ory are used to defi ne the future year ambient air quality and visibility metrics.

5.1.1 Baseline Emission Inventory

WRAP developed a baseline emission inventory for point, all fires (anthropogenic and wild), biogenic sources, area, oil and gas, on-road mobile, off-road mobile, road dust, fugitive dust, and windblown dust sources for calendar year 2002. The emission inventories includes sulfur dioxide, sulfur dioxide and partic ulate, nitrogen oxide, nitrogen oxide and particulate, primary organic aerosol, elemental carbon, particulate ma tter 2.5 microns in diameter or less (fine), particulate matter 10 microns in diameter or less but greater than partic ulate matter 2.5 microns in diameter (coarse), ammonia, volatile or ganic compounds, and carbon monoxide. Information on how these inventories were developed and quality assurance measures may be reviewed at the following website:

http://vista.cira.colostate.edu/tss/results/Emissions.aspx39 There were two versions of the baseline em ission inventory conducte d by WRAP. The two

baseline versions were identified as “base 02a and 02b”. Version “a” of the 2002 base case inventory was developed based on prelimin ary 2002 modeling (Tonnesen et al., 2005). Improved 2002 emissions data for the United States , Mexico, and Canada were used to create a

final base 2002 annual emissions database for use in the CMAQ and CAMx model performance evaluations. Sources for emissions inventory and ancillary modeling data included WRAP emissions inventory contractors, other regional planning organizations, and EPA. Building from the WRAP preliminary 2002 modeling cases complete d earlier, several update s to the inventories and ancillary data were incorpor ated to create final 2002 emissions input files for the 2002 base case A, or Base02a. The purpose of the “base 02” scen ario is to represent the actual conditions in calendar year 2002 with respect to ambient air quality and the asso ciated sources of visibilityimpairing air pollutants. The second versions, ba se 02b, represents updates to the first version

and is summarized in Table 5-1 for e ach of the emission sources.

The 2000 through 2004 baseline period planning case em issions scenario is referred to as “plan 02”. As with the “base 02” inventories, “plan 02” underwent a number of revisions and

enhancements to arrive at the final versions used in visibility and source apportionment modeling. The “plan 02”series of inventories was developed to repr esent baseline period emissions patterns based on average, or “typ ical” conditions. The “p lan 02”inventory was developed from the “base 02”emissions m odeling scenarios by incorporating:

1. Replacement of actual 2002 fire emissions inve ntories with the baseline typical fire emissions inventories;

2. Replacement of the temporal profiles for la rge stationary point sources with profiles developed from an average of se veral years surrounding 2002; and

3. Corrections to the off-road mobile, on-road mobile, offshore Pacific shipping lane and WRAP oil and gas inventories.

The “plan 02d” emission inventory was based on the minor changes to the “plan 02c”emission inventory. The revi sions included:

1. Updating the current status of point sources related to the BART requirements under the regional haze rule; and

2. Correcting erroneous or missing Standard Industrial Classifica tion and/or source classification codes (SCC).

Table 5-2 provides a summary of the 2002 Sout h Dakota baseline planning emission inventory (plan 02d) for each of the emission sources. The base 02b and the plan 02d emissions data are similar except for the sulfur dioxi de and nitrogen oxide emissions from area sources. Based on a

Technical Memorandum from Paula Fields and Marty Wolf with ERG to WRAP Forums and Workgroups dated January 10, 2008, the South Dakota area source emissions from distillate fuel combustions was revised using data received during the PRP18 project. The end result was a reduction of just over 9,000 tons of sulfur dioxi de and 3,000 tons of nitrogen oxide emissions. The January 10, 2008, memorandu m may be viewed at:40Table 5-1 – South Dakota’s 2002 BaselineEmission Inventory Summary (Base 02b)1, 2Particulate MatterSourceSO2SO23NOxNOx3POAECFineCoarseAmmoniaVOCsCOPoint14,022 14,059 20,697 20,698 46 2 160 727 100 2,542 4,700All Fires278 318 1,371 1,388 3,172 409 1,338 544 494 3,135 49,109Biogenic Sources0 0 52,852 52,852 0 0 0 0 0 445,241 103,402Area10,159 10,387 5,978 5,987 1,887 317 2,129 2,177 118,920 42,372 24,239Oil/Gas48 8 367 367 0 0 0 0 033,72110On-Road Mobile872 922 29,224 29,224 472 632 180 169 842 13,741 221,726Off-Road Mobile5,733 6,066 39,039 39,039 942 3,234 0 0 25 12,764 92,508Road Dust0 4 0 5 255 18 4,061 38,164 0 0 0Fugitive Dust0 9 0 26 1,277 87 25,035 93,734 0 0 0Wind Blown Dust0 0 0 0 0 0 50,274 452,470 0 0 0Total31,07231,773149,528149,5868,0514,69983,177587,985120,381553,516495,6941– Derived from WRAP’s website athttp://vista.cira.colostate.edu/TSS/Results/HazePlanning.aspx. To get to the data, the individual needs toclick on “Emissions and Source Apportionment”, and click on “Emission Review Tool”;2– “SO2” means sulfur dioxide, “NOx”means nitrogen oxide, “POA” meansprimary organic aerosol, “EC” means elemental carbon,“VOCs” means volatile organic compounds, and “CO” means carbon monoxide;3– The emission total for sulfur dioxides and nitrogen oxides includes gas and particulate; and4– VOC emissions from secondary oil and gas production were estimated based on an analysis of the gas and gas flow rates.41Table 5-2 –South Dakota’s 2002 PlanningEmission Inventory Summary (Plan 02d)1, 2Particulate MatterSourceSO2SO23NOxNOx3POAECFineCoarseAmmoniaVOCsCOPoint14,024 14,037 20,698 20,699 10 0 216 727 100 2,542 4,700Big Stone I411,171 14,552 209 209 29 107 490All Fires367 469 1,698 1,713 4,574 717 839 754 562 3,853 64,326Biogenic Sources0 0 52,852 52,852 0 0 0 0 0 445,241 103,402Area1,071 1,198 2,897 2,903 1,792 306 1,804 156 118,877 40,511 23,029Oil/Gas56 6 361 361 0 0 0 0 033,72111On-Road Mobile872 922 29,224 29,224 278 339 0 169 842 13,741 221,726Off-Road Mobile5,733 6,066 39,039 39,039 942 3,234 0 0 25 12,764 92,508Road Dust0 4 0 5 255 18 4,061 38,164 0 0 0Fugitive Dust0 24 0 27 1,317 89 25,220 122,914 0 0 0Wind Blown Dust0 0 0 0 0 0 50,274 452,470 0 0 0Total22,07322,726146,769146,8239,1684,70382,414615,354120,406552,373509,7021– Derived from WRAP’s website athttp://vista.cira.colostate.edu/TSS/Results/HazePlanning.aspx. To get to the data, the individual needs toclick on “Emissions and Source Apportionment”, and click on “Emission Review Tool”;2– “SO2” means sulfur dioxide, “NOx”means nitrogen oxide, “POA” meansprimary organic aerosol, “EC” means elemental carbon,“VOCs” means volatile organic compounds, and “CO” means carbon monoxide;3– The emission total for sulfur dioxides and nitrogen oxides includes gas and particulate;4– Otter Tail Power Company’s Big Stone I emissions are includedin the “Point” emissions row but separated here for comparisonto Table5-4, 6-1 and 6-3; and5– VOC emissions from secondary oil and gas production were estimated based on an analysis of the gas and gas flow rates.42 http://www.wrapair.org/forums/ ssjf/documents/Pivot_Tables/2008

‐ 01_Plan02d_Tech_Memo%281

‐ 10%29.pdf

DENR revised the data for South Dakota for bot h the baseline and planning emission inventories to include oil and gas area source emissions. Through a compliance initiative in EPA’s Region VIII, it was determined that secondary oil a nd gas production in northwestern South Dakota was generating volatile organic compound emissions from storage tanks that needed to be addressed.

The oil companies quantified the volatile orga nic compound emissions which resulted in air emissions of 33,433 tons. DENR added the volatile organic compound emissions from a secondary oil recovery field to the 2002 baseline and planning emission inventory calculated by WRAP to account for the area volatile organic compound emissions from the oil and gas fields.

The 33,433 tons of volatile organic compound emissi ons in Table 5-1 and 5-2 were not included in the modeling conducted by WRAP. However, the increase in criteri a air pollutants (e.g., particulate matter, nitrogen oxide, and carbon m onoxide) from the reduction in volatile organic compound emissions were used in the modeli ng for 2018 projections and reasonable progress

purposes.

5.1.2 Current Emission Inventory

A complete air emission inventory is not available for the most recent year. DENR does

calculate an annual air emission i nventory for point sources that are required to pay fees under the Title V air quality permit program. The most current year is 2009. The point source data for 2009 is displayed in Table 5-3 and compared to the same data collected in WRAP’s 2002 baseline emission inventory to compare air emission trends from point sources.

Table 5-3 – Comparison of 2002 and 2009 South Dakota Point Source Emissions 1

Year PM10 2 SO 2 NOx VOCs CO

2002 WRAP 887 14,022 20,697 2,542 4,700

2009 DENR 1,125 13,321 15,611 3,694 2,907

Difference 238 -701 -5,086 1,152 -1,793

1 – “PM10” means particulate matter less than or equal to 10 microns in diameter or less, “SO2” means sulfur dioxide, “NOx” means nitrogen oxid e, “VOCs” means volatile organic compounds, and “CO” means carbon monoxide; and

2 - The PM10 emissions are based on coarse and fine particulate matter.

The comparison shows that air emissions increas ed from 2002 to 2009 for all pollutants except sulfur dioxide, nitrogen oxide and carbon monoxide.

5.1.3 WRAP’s 2018 Projections

WRAP projected an air emissi ons inventory for 2018 (PRP18a) for the same source types and pollutants as the base year. The projec tion methodology included the following steps:43 1. Adjustments: Emission increases for new facilities that have come on-line since 2002,

deletion of emissions for facilities that re tired in 2003 or 2004 and will not return to operation in the future; and other adjustment s (e.g., ratios to co rrect certain PM10 and

PM2.5 emission factors/Standard Classificati on Codes for combustion of natural gas);

2. Control Factors: Emission reductions due to known (e.g., on-the-books ) controls, consent decrees reductions, State Implementation Pl an control measures, and other relevant regulations that have gone into effect since 2002, or will go into effect before the end of 2018. These controls do not include impacts from any future control scenarios that have yet to be determined;

3. Growth Factors: Standard Cla ssification Code specific growth factors developed from the Economic Growth and Analysis System proj ection factor model; special analysis of electric generating unit growth rela tive to unit capac ity threshold;

4. Retirement & Replacement Rates: Effects of re tirement estimates using annual retirementrates based on expected equipment lifetimes. Retired equipment replaced by loweremitting new equipment. Unit lifetime examined for natural gas-fired electric generating

units. No retirements assumed for co al-fired electric generating units;

5. Permit Limits: Used in the cases where the projected emissions may have inadvertently exceeded an enforceable emission limit (e.g., em issions were adjusted downward to the permit limit, as applicable); and

6. Section 309 Flags: Point sour ces in the Grand Canyon Visibi lity Transport States (e.g., AZ, CA, CO, ID, NV, NM, OR, UT, and WY) whose 2002 facility-level sulfur dioxide

emissions are at least 100 tons per year.)

Just like the baseline inventory, WRAP im proved on the projections and produced a second version. The objective of the “PRP 18b” vers ion was to make a second revision to the 2018 emissions inventory projections for point and ar ea sources in the WRAP region to provide a more current assessment of the reasonable pr ogress toward visibility goals by the WRAP. The focus of this project was to address specific chan ges that have occurred since completion of the “PRP 18a” inventory in 2007. The resulting produc t is the second version of the WRAP region Preliminary Reasonable Progress emissions inventory for 2018, known as “PRP 18b”.

The “PRP 18b” inventory revisions included the following elements:

1. Included all updated BART information availa ble such as incorporating all available formal BART determinations; incorporating estimates of expected BART control levels

where BART determinations had not been finalized (BART estimates made for both sulfur dioxide and nitrogen oxide); and addressing all “BAR T-eligible” or “Subject to BART” sources, both for electric generating uni ts and for the non-electric generating unit universe;

2. Revised projections of “future” fossil-fuel pl ants needed to meet federal electrical generation demand forecasts in 2018 (e.g., used updated Energy Information Administration of the federal Departme nt of Energy projections of 2018 energy requirements – for the first time incor porated Renewable Energy Portfolios where available – determined that existing WRAP region electric generating capacity, when added to existing State and Local agency el ectric generating unit permits, was sufficient to meet 2018 demand without addition of any new future electric generating units);44 3. Incorporated all new rulema king, permit limits, and consent decrees instit uted since 2007; and

4. Corrected other outstanding issues that were identified by the federal, state, or local agencies within the WRAP domain as needi ng to be revised/updated such as modification of various inventory data to be consistent with the Pl an 02d emissions inventory (e.g., name changes, updated stack parameters, new or removed sources); revision of a limited number of area source categories (e.g., fuel combustion emissions in South Dakota and California, gasoline distribution emissions in Idaho, residential wood combustion emissions in Washington, cons truction dust in Clark County, Ne vada); revision of facility information (e.g., facility identifications, f acility names, unit identifications, process identifications, Standard Classi fication Codes, Standard Indu strial Classifications) based upon agency input; revision of stack parameters based upon agency input; and addition of WRAP Phase II oil and gas project emissions to “PRP 18a” area source emission summaries in order to provide relevant comp arisons to the emission totals in “PRP 18b”

which also contained oil and gas emission totals.

The 2018 projected air emissions for South Dakot a included three large facilities that are currently permitted but not constructed or have su bmitted an application to construct. The first facility is Big Stone II, which was a proposed 6 00 megawatt coal-fired pow er plant located next to an existing coal-fired power plant (Big Stone I) in the northeast corner of the state. A Prevention of Significant Deterioration air qua lity permit was issued to Big Stone II on November 20, 2008. The increase in air emission s from this facility would be limited to particulate matter, volatile or ganic compounds, and possibly a mmonia. There would be no

increase of air emissions for sulfur dioxide and nitrogen oxide because of decreases in air emissions from the Big Stone I facility. The air emission increases from this facility are included in the 2018 projections and are shown in Tabl e 5-4. However, on December 1, 2009, Otter Tail Power Company submitted a letter notifying DENR the Big Stone II facility will not be built and it relinquished all rights and ob ligations granted through and by the Prevention of Significant Deterioration permit. Therefore, the 2018 emi ssion inventory will need to be updated.

The other facility that was issued a Prevention of Significant Deterioratio n air quality permit was the Hyperion Energy Center that received a permit on August 20, 2009. The Hyperion Energy

Center will be located in Union County which is located in the s outheastern corner of the state and is a 400,000 barrel per day oil refinery and integrated gasification combine cycle power plant. The air emission increases from this faci lity are included in th e 2018 projections and are

shown in Table 5-4.

The third facility involves Ba sin Electric Power Cooperative’s NextGen application for another coal-fired power plant with a maximum capacity of 700 megawatts located in the north central area of the state. The applica tion is currently on hold; but the air emission increases from this facility are included in the 2018 projec tions and are shown in Table 5-4.

DENR has also received a Prevention of Signi ficant Deterioration permit application for a 300 megawatt natural gas fired comb ined cycle power generating facility in Brookings County, which is on eastern edge of South Dakota board ing Minnesota. The air emission increases from this facility will be included in the next 2018 projections and modeling analysis.45 Table 5-4 displays the 2018 pr ojected air emissions for South Dakota using the “PRP 18b” inventory. The specific contribution from each pr oject are displayed in Table 5-4 and derived from WRAP website at the following location:

http://www.wrapair.org/forums/ssjf/pivot.html

To review, click on the 2018 PRP 18 b zip file to review the pivot tables that when clicked on will display each facilities contribution.

As discussed for the baseline, through a comp liance initiative in EPA’s Region VIII, it was determined that secondary oil and gas producti on in northwestern South Dakota was generating volatile organic compound emissions from storage tanks that needed to be addressed. The

installation of four ther mal oxidizers in the northwestern po rtion of South Dakota resulted from the compliance initiative. Each of the thermal oxidizers are permitted under South Dakota’s minor air quality permit program and requires the thermal oxidizers to maintain a volatile organic compound destruction efficiency of 98.6% or greater. The installation of four thermal

oxidizers did increase the emission of fine particulate matter, nitr ogen oxide, and carbon monoxide. South Dakota’s minor air quality permit program is included in its State Implementation Plan.

DENR added volatile organic compound emissions to Table 5-4 to account for the volatile organic compounds that are not de stroyed by the thermal oxidizers. The fine particulate matter, nitrogen oxide and carbon monoxide emissions fr om the thermal oxidizers are included as area sources in WRAP’s projected air emi ssions in the “PRP 18b” inventory.

5.1.4 Air Emission Inventories for Other States and Countries

The visibility in the Class I areas in South Dakot a is influenced not only by air emissions from within South Dakota but from surrounding stat es, Canada, and sources outside WRAP’s modeling domain. The six contiguous states are North Dakota, Minnesota, Iowa, Nebraska, Wyoming and Montana. The 2002 plan year emi ssions (Plan 02d) and 2018 projected emissions (PRP 18b) from the respective states are shown in Table 5-6 and 5-7, respectively.

For the base year, South Dakota’s emissions when combined with the neighboring states’ emissions represent only three to 17 percent of the total emissi ons for each type of pollutant. For 2018, South Dakota’s emissions are similar at two to 18 percent of the total emissions for each type of pollutant. The small percentage for each type of pollutant is a good indication that South Dakota’s Class I areas are being influenced by emissions from sources beyond South Dakota’s borders. Based on WRAP’s attribution analysis, which will be discussed further, South Dakota’s Class I areas are also impacted by states beyond the contiguous states and other countries such as Canada. Emission inventory data for the states beyond the contiguous states and other countries

are available on WRAP’s website but we re not included in this document.46Table 5-4 –2018 South Dakota Projected Emission Inventory Summary (PRP 18b)1, 2Particulate MatterSourceSO2SO23NOxNOx4POAECFineCoarseAmmoniaVOCsCOPoint11,986 11,996 30,185 30,186 8 0 205 9,847 102 4,510 16,632Big Stone I3,425 15,323 318 112 509Big Stone II3,942 2,891 6,758 96 3,947Hyperion627 455 1,041 438 954NextGen1,534 1,621 1,155 114 4,638Existing2,458 9,895 575 3,750 6,584All Fires365 465 1,679 1,694 4,531 715 821 751 553 3,808 63,843Biogenic Sources0 0 52,852 52,852 0 0 0 0 0 445,241 103,402Area1,662 1,789 3,303 3,309 1,769 314 1,920 190 118,992 49,659 23,773Oil/Gas50 0 557 557 0 0 0 0 056216On-Road Mobile108 129 8,059 8,059 270 86 0 188 1,075 5,101 120,041Off-Road Mobile50 199 23,785 23,785 386 1,072 0 0 36 7,686 95,276Road Dust0 5 0 6 325 23 5,190 48,773 0 0 0Fugitive Dust0 26 0 27 1,322 90 25,840 129,009 0 0 0Wind Blown Dust0 0 0 0 0 89 50,274 452,470 0 0 0Total 14,171 14,609 120,420 120,475 8,611 2,389 84,250 641,228 120,758 516,567 422,9831– Derived from WRAP’s website athttp://vista.cira.colostate.edu/TSS/Results/HazePlanning.aspx. To get to the data, the individual needs toclick on “Emissions and Source Apportionment”and click on “Emission Review Tool”;2– “SO2” means sulfur dioxide, “NOx”means nitrogen oxide, “POA” meansprimary organic aerosol, “EC” means elemental carbon,“VOCs” means volatile organic compounds, and “CO” means carbon monoxide;3– Sulfur oxides (gas and particulate);4– Nitrogen oxides (gas and particulate); and5– VOC emissions from secondary oil and gas production were estimated based on an analysis of the gas and gas flow rates.47 Table 5-5 provides the percent of difference be tween 2002 planned emission inventory (Table 5- 6) and the 2018 projected emissions (Table 5-7) . From this you can see that both South Dakota and the contiguous states will decrease air emissions for most pollutants from 2002 to 2018. This decrease will represent improvements in visi bility in Class I areas in South Dakota and neighboring Class I areas.

Table 5-5 – Emission Ch anges projected for 2018 1

SD Contiguous States

Pollutant % Difference % Difference

SO 2 36% Decrease 26% Decrease

SO 2 2 36% Decrease 26% Decrease

NOx 18% Decrease 30% Decrease

NOx 3 18% Decrease 30% Decrease

POA 6% Decrease 6% Decrease

EC 49% Decrease 29% Decrease

PM fine 2% Increase 4% Increase

PM
coarse 4% Increase 1% Increase Ammonia No change 20% Increase

VOCs 6% Decrease 5% Increase

CO 17% Decrease 22% Decrease

1 – “SO 2 ” means sulfur dioxide, “NOx” means nitrogen oxide, “POA” means primary organic

aerosol , “EC” means elemental carbon, “PM” means particulate matter, “VOCs” means volatile organic compounds, and “CO” means carbon monoxide;

2 – Sulfur oxides (gas and particulate); and

3 – Nitrogen oxides (gas and particulate).

5.1.5 Future Emission Inventory by South Dakota

DENR conducts an annual air em ission inventory for stationary s ources that are re quired to pay air fees under the Title V air qua lity permit program. The air emission inventory consists of criteria air pollutants. The stationary sources re quired to report consist of major sources (actual air emissions that exceed 100 tons per year) and area sources. DENR will expand the air emission inventory to include all air emissions th at impact visibility from these stationary

sources.

DENR will continue to work with other organizations and states to ensure all inventory data used in future modeling will be accurate. The future emission inventories and the data provided by states in EPA’s National Emission Inventory database will be used to trac k the progress of South Dakota and neighboring states on co ntrolling and reducing air pollu tion that cause or contribute to visibility impairment in our Cla ss I areas and neighbor ing Class I areas.48Table 5-6 –2002 Contiguous State PlanningEmission Inventory Summary (Plan 02d)1, 2SourceSDNDMinnesotaIowaNebraskaWyomingMontanaTotalSD %SO222,073170,477 158,484 199,339 94,247 145,840 50,198840,6583%SO2322,726171,611 162,516 201,419 95,603 148,487 51,923854,285 3%NOx 146,769229,460 522,727 378,150 322,915 287,974 242,9782,130,973 7%NOx4146,823229,536 523,008 378,306 323,015 288,095 243,1422,131,925 7%POA 9,1688,840 33,414 13,953 10,709 29,194 48,089153,367 6%EC 4,7034,847 13,034 7,790 6,312 8,066 11,87356,625 8%PMfine82,41461,519 98,542 109,660 82,851 22,833 77,239535,058 15%PMcoarse615,354360,936 541,408 701,377 610,843 102,660 621,2763,553,854 17%Ammonia 120,406120,493 194,699 272,173 177,774 33,032 66,229984,806 12%VOCs 552,373334,020 1,127,795 574,151 561,172 816,904 1,181,3185,147,733 11%CO 509,702470,129 2,644,613 1,809,356 1,054,477 909,702 1,639,9499,037,928 6%1– Derived from WRAP’s website athttp://vista.cira.colostate.edu/TSS/Results/HazePlanning.aspx. To get to the data, the individual needs toclick on “Emissions and Source Apportionment”and click on “Emission Review Tool”;2– “SO2” means sulfur dioxide, “NOx”means nitrogen oxide, “POA” meansprimary organic aerosol, “EC” means elemental carbon, “PM”means particulate matter, “VOCs” means volatileorganic compounds, and “CO” means carbon monoxide;3– Sulfur oxides (gas and particulate); and4– Nitrogen oxides (gas and particulate).49Table 5-7 –2018 Contiguous State Emission Inventory Summary (PRP 18b)1, 2SourceSDNDMinnesotaIowaNebraskaWyomingMontanaTotalSD %SO214,17166,942 111,532 198,444 60,473 122,446 44,269618,2772%SO2314,60967,810 115,735 200,953 61,912 125,692 45,794632,505 2%NOx 120,420187,032 316,762 249,248 206,443 248,100 179,8781,507,883 8%NOx4120,475187,103 317,037 249,422 206,545 248,234 180,0431,508,859 8%POA 8,6117,126 31,649 12,774 9,686 28,464 46,502144,812 6%EC 2,3892,447 9,387 4,938 3,286 6,855 9,94839,250 6%PMfine84,25062,731 97,229 114,324 83,456 28,055 83,047553,092 15%PMcoarse641,228373,428 517,566 697,526 591,464 116,054 675,9853,613,251 18%Ammonia 120,758120,120 260,671 326,247 230,762 33,974 67,0301,159,562 10%VOCs 516,567337,735 1,160,320 580,816 566,667 1,005,916 1,174,5875,342,608 10%CO 422,983341,118 2,094,422 1,253,075 743,082 813,609 1,378,7787,047,067 6%1– Derived from WRAP’s website athttp://vista.cira.colostate.edu/TSS/Results/HazePlanning.aspx. To get to the data, the individual needs toclick on “Emissions and Source Apportionment”and click on “Emission Review Tool”;2– “SO2” means sulfur dioxide, “NOx”means nitrogen oxide, “POA” meansprimary organic aerosol, “EC” means elemental carbon, “PM”means particulate matter, “VOCs” means volatileorganic compounds, and “CO” means carbon monoxide;3– Sulfur oxides (gas and particulate); and4– Nitrogen oxides (gas and particulate).50 5.2 Source Apportionment Analysis

Visibility impairment occurs when pollutants em itted into the atmosphere scatter and absorb light thereby creating haze. These pollutants can remain suspended in the atmosphere for long periods and be transported l ong distances thereby contributing to regional-scale impacts on visibility in Class I areas. Air quality models are one of the tools that states can use to help understand how these impacts occur by identifying the sources contributing to haze and to select

the most effective emissions reduction strategies to improve visibility.

In order to determine the significant sources cont ributing to haze in South Dakota’s Class I areas, DENR relied on an apportionment analysis provided by WRAP, which can be reviewed on

WRAP’s website at:

http://vista.cira.colostate. edu/TSS/Results/HazePlanning.aspx

.

There were two techniques used by WRAP for analyzing source a pportionment of regional haze.

One was the Particulate Matter Source Apportionment Technology ( PSAT) analysis used for the attribution of sulfate and nitrate sources only. The second was the Weighted Emissions Potential (WEP) analysis used for attribution of sources of sulfate, nitrate, organic carbon, elemental carbon, fine particulate matter a nd coarse particulate matter.

The Particulate Matter Source A pportionment Technology analysis used the CAMx air quality

model to show nitrate-sulfate-ammonia chemistr y and applies this chem istry to a system of tracers or “tags” to track the chemical transformations, transpor t and removal of nitrogen oxides and sulfur dioxide. These pollutants are impor tant because they tend to originate from anthropogenic (human-caused) sources. Therefore, th e results from this analysis can be useful in determining contributing sources that may be controllable, both in-state and in neighboring

states. Emission scenarios used for the Part iculate Matter Source Apportionment Technology analyses were the “pla n02c” and “base 18b”.

The Weighted Emissions Potential an alysis is a screening tool that helps to identify sources in regions that have the potential to contribute to haze formation at specific Class I areas. Unlike the Particulate Matter Source Apportionment T echnology analysis, this method does not account for chemistry or deposition. The Weighted Emi ssions Potential analysis combines emissions inventories, wind patterns, and residence time of air mass over each area where emissions occur to estimate the percent contribu tion of different pollutants. Li ke the Particulate Matter Source Apportionment Technology analysis, the Weighted Emissions Potential analysis compares baseline (2000-2004) to 2018, to show the impr ovement expected by the 2018 uniform rate of progress for sulfate, nitrate, or ganic carbon, elemental carbon, fine particulate matter, and coarse particulate matter.

DENR believes the Particulate Matter Source Appor tionment Technology analysis is a better tool than Weighted Emissions Potential tool for identify ing the contribution of su lfates and nitrates to

South Dakota’s Class I areas because it accounts for chemistry and deposition and is better at identifying regional contribution of sources from outside the WR AP region. For these reasons,51 DENR relied on the Particulate Matter Source A pportionment Technology results as the primary source for determining apportionment for sulfates and nitrates and thus the better tool for identifying anthropogenic sources. The results fro m the Weighted Emissions Potential analysis were used by DENR primarily to identify the pol lutants more commonly associated with natural sources. Even though these sources are mostly unc ontrollable, it is still important to consider

their relative contribution to haze.

The primary tool utilized by DENR for modeling regional haze improvements by 2018 and for determining South Dakota’s Reasonable Progr ess Goals was the CMAQ model. The CMAQ model was used by WRAP to estimate 2018 visi bility conditions in South Dakota and all Western Class I areas based on application of the regional haze strategies presented by states to WRAP, including assumed cont rols on BART sources.

The modeling was conducted by the Regional Mode ling Center (RMC) at the University of

California Riverside under the oversight of WRAP’s Modeling Forum. A more in depth description of the CMAQ model used to proj ect 2018 visibility condi tions by WRAP and the results of the modeling can be found on WRAP’s website at:

http://vista.cira.colostate. edu/TSS/Results/HazePlanning.aspx

.

The CMAQ model was designed as a “one at mosphere” modeling system to encompass modeling of multiple pollutants and issues includ ing ozone, particulate matter, visibility, and air toxics. This is in contrast to many earlier air quality models that focused on a single pollutant. CMAQ takes into account emissions, advection and dispersion, photochemical transformation, aerosol thermodynamics and phase transfer, aque ous chemistry, and wet and dry deposition of trace species. The model requires inputs of thre e-dimensional wind grids, temperature, humidity, cloud/precipitation, and boundary layer parameters . The current version of CMAQ can only utilize output fields from the MM5 meteorol ogical model. MM5 meteorological model is a state-of-the-science atmosphere model that has pr oven useful for air quality applications and has been used extensively in past local, state, regional, and national modeling efforts. MM5 meteorological model has undergone extensive peer review, with a ll of its components continually undergoing development a nd scrutiny by the modeling community.

The Regional Modeling Center developed ai r quality modeling inputs including annual meteorology and emissions inventories for a 2002 act ual emissions base case, a planning case to represent the 2000-2004 regional haze baseline period using averages for key emissions categories, and a 2018 base case of projected emissions determined using factors known at the end of 2005. All emission inventories were pr epared for CMAQ using the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling syst em. Each of these in ventories underwent a number of revisions throughout the development process to arrive at the final versions used in CMAQ modeling. The development of each of th ese emission scenarios is documented under the emissions inventory sec tions on WRAP’s website at:

http://vista.cira.colostate. edu/TSS/Results/HazePlanning.aspx

.52 The 2018 visibility projections were made using the planning case to represent the 2000-2004 regional haze baseline period (Plan02c) and ba se case projected emissions (Base18b). The CMAQ modeling grid design was es tablished at 36-kilometers. Projections were made using relative response factors, which are defined as the ratio of the future-year modeling results to the current-year modeling results. The calculated relative response factors are applied to the baseline observed visibility conditions to project future-year observed visibility.

Generally, emissions inputs were prepared by indi vidual states and tribes for point, area, and most dust emissions categories. The followi ng WRAP forums were relied upon to summarize this data and provide it to the Regional Modeling Center:

1. Point source emissions were obtained from projects commissioned by the Stationary Sources Joint and Emissions forums;

2. Area source emissions were obtained from projects commissioned by the Stationary Sources Joint and Emissions forums;

3. Mobile source emissions were obtained fr om projects commissioned by the Emissions forum;

4. Fire (natural and anthropogenic) emissions were obtained from projects commissioned by the Fire Emissions Joint forum;

5. Ammonia, dust, and biogenic emissions we re obtained from projects commissioned by the Dust Emissions Joint and Modeling forums;

6. Emissions from Pacific offshore shipping were obtained from a project conducted by the Regional Modeling Center;

7. Other emissions from North America were obtained from projects commissioned by the Emissions and Modeling forums. Mexico’s emissions were based on a 1999 emission inventory and Canada’s were based on a 2000 emission inve ntory. Both were held constant for 2018; and

8. Boundary conditions reaching North America fr om the rest of the world were obtained from a project commissioned by the VISTAS Regional Planning Organization on behalf of the five regional Planning organizations working on regional haze.

5.3 Regional Haze Contributions in South Dakota’s National Parks

WRAP developed graphs showing the profile of th e relative contribution ofin-state versus outof-state sources contributing to air pollutant co ncentrations in South Dakota’s Class I areas for the 20% least and most impaired days during the 2002 baseline and 2018 projections using the

Particulate Matter Source A pportionment Technology and Weighted Emissions Potential analyses.

As previously mentioned, there are several differences between the Particulate Matter Source Apportionment Technology analysis a nd Weighted Emissions Potentia l analysis. The Particulate Matter Source Apportionment Technology focuses on sulfate and nitrate c ontribution taking into account chemistry and deposition; bu t also estimates the contribution from all regions such as the WRAP states, CENRAP states, Ca nada, Mexico, Pacific offshore (shipping), and “outside the domain” (global transport). CENRAP is a region al planning organization similar to the WRAP53 that is comprised of Nebraska, Kansas, Oklahoma, Texas, Minnesota, Iowa, Missouri, Arkansas,

and Louisiana.

The Weighted Emissions Potentia l analysis estimates the contri bution from Canada and Pacific offshore regions; but does not include other regional contri butions. Therefore, WRAP’s apportionment analysis is based on the Part iculate Matter Source Apportionment Technology results for identifying the contribu tion of sulfates and nitrates (t he primary anthropogenic source pollutants) and Weighted Emissions Potential results for identify ing the contribution of organic carbon mass, elemental carbon, fine particulat e matter, and coarse particulate matter.

5.3.1 Sulfate Contributions

Based on the IMPROVE data, ammoni a sulfate contributes to visi bility impairment in both the

Badlands and Wind Cave National Parks. At th e Badlands National Park, ammonia sulfate has the greatest impact and at the Wind Cave Nationa l Park it has the second greatest impact during the 20% most impaired days. Figure 5-1 and 5-2 illustrates the state and regional contribution of sulfate during the 20% most and least impaired da ys in South Dakota’s two Class I areas. The contributions are based on modeling of 2002 emi ssion inventories of actual emissions and projected emissions in 2018. The pie chart in e ach figure displays the regional contribution to

the total annual modeled sulfate mass at the respective sites for th e 2002 base year and 2018 projections. The bar chart id entifies what state or region is contributing, the amount of contribution, and what type of sources are contributing to sulfat e concentrations in the 2002 base year and 2018 projections. There ar e five source categories listed: 1) point; 2) area; 3) mobile; 4) anthropogenic fires (controlled burns ); and 5) natural fires and bi ogenic sources (mostly wildfire and windblown dust). In each figure, the first bar for each state and region is not labeled but represents the 2002 base year.

Based on the WRAP modeling, the su lfate concentrations for the 20% most impaired days (worst days) in the Badlands National Park will decr ease from 1.8 micrograms per cubic meter in 2002 to 1.6 micrograms per cubic meter in 2018 (see Fi gure 5-1(a)). The decrease appears to be

attributed to decreases of su lfate emission in the CENRAP re gion, Eastern U.S. region, South

Dakota and Colorado.

The WRAP modeling indicates the greatest sulfate contribution for the 20% most impaired days

at the Badlands National Park in 2002 is generated from the CENRAP region followed by Outside the Domain, Eastern U.S ., Canada, and North Dakota. If you exclude Outside Domain because the source categories were not identifie d, a majority of the sulfate contribution is generated from point sources followe d by area and mobile sources.

In 2018, the greatest sulfate cont ribution for the 20% most impa ired days at the Badlands National Park switches from the CENRAP region to Outside the Domain. This occurs because Outside the Domain’s sulfate contributions slig htly increase while the CENRAP region’s sulfate contribution decreases during the same period. Even with the decreases in sulfate emissions, the CENRAP region is the second greatest cont ributor followed by Canada, North Dakota and Eastern U.S. Again, point sources are the ma jor contributor followed by area sources with

mobile source contribution minimized in 2018.54 Figure 5-1 – Sulfate Contribution for 20% Most Impaired Days a) Regional Sulfate Co ntributions at Badlands

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

South Dakota’s sulfate contribution in 2002 at the Badlands National Park is minimal at less than 0.06 micrograms per cubic meter. The sources of sulfate emissions in South Dakota are generated from point, area, and mobile sources evenly in 2002. In 2018, South Dakota’s sulfate contribution switch mainly to point and area sour ces, and like other stat es and regions in the United States, mobile source contributions are mi nimal due to new changes in federal emission

standards from mobile sources.

Based on the WRAP modeling, the su lfate concentrations for the 20% most impaired days (worst days) in the Wind Cave National Park will decr ease from 1.4 micrograms per cubic meter in 2002 to 1.3 micrograms per cubic meter in 2018 (see Figu re 5-1(b)). The decrease appears to be55 attributed to decreases of su lfate emission in the CENRAP re gion, Eastern U.S. region, South

Dakota and Colorado.

The WRAP modeling indicates the greatest sulfate contribution for the 20% most impaired days at the Wind Cave National Park in 2002 is generated from Outside the Domain followed by the CENRAP region, Canada, Wyoming, and North Dakota. If you exclude Outside Domain because the source categories were not identifie d, a majority of the sulfate contribution is generated from point sources followed by area and mobile sources. The source category contribution is similar to what you se e at the Badlands National Park

In 2018, the greatest sulfate cont ribution for the 20% most impaired days at the Wind Cave

National Park remains from Outside the Domain. Th e next four greatest c ontributors is Canada, the CENRAP region, Wyoming and North Dakota. The CENRAP region’s sulfate contribution

decreases in 2018 which reduces its contribution lower than Canada ; but continues to be greater than Wyoming and North Dakota. Again, point sources are the major contributor followed by

area sources with mobile source contribution minimized in 2018.

South Dakota’s sulfate contribu tion in 2002 at the Wind Cave National Park is minimal at approximately 0.04 micrograms per cubic meter. The sources of sulfate emissions in South Dakota are generated from point, area, and m obile sources evenly in 2002. In 2018, South

Dakota’s sulfate contribution swit ch mainly to point and area s ources, and like other states and regions in the United States, mobile source cont ributions are minimal due to new changes in

federal emission standards from mobile sources.

Point sources contribute a majority to the sulfat e concentrations in S outh Dakota’s two national parks during the 20% most impaired days. The st ate or region that contributes to the sulfate concentrations the greatest is dependent on where the national park is located. For example, in the WRAP region, North Dakota contributes mo re to the Badlands National Park while Wyoming contributes more to the Wind Cave National Park.

Based on the WRAP modeling, the su lfate concentrations for the 20% least impaired days (best days) in the Badlands National Park will incr ease from 0.6 micrograms per cubic meter in 2002 to 0.7 micrograms per cubic meter in 2018 (see Fi gure 5-2(a)). Althoug h Wyoming is not the greatest sulfate contributor during the 20% least impaired days, the increase appears to be

attributed to increases of sulfate emi ssion in the Wyoming, Idaho, and Montana.56 b) Regional Sulfate Co ntributions at Wind Cave

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

The WRAP modeling indicates the greatest sulfate contribution for the 20% least impaired days at the Badlands National Park in 2002 is ge nerated from Outside the Domain followed by Wyoming, Canada, Idaho, and Montana. If you exclude Outside Domain because the source categories were not identified, a majority of th e sulfate contribution is generated from point

sources.

In 2018, the greatest sulfate cont ribution for the 20% least impaired days at the Badlands National Park does not change from 2002. The five greatest sulfate cont ributors are Outside the Domain, Wyoming, Canada, Idaho, and Montana. Again, point sources are the major contributor

of sulfate concentrations.57 Figure 5-2 – Sulfate Contributio n for 20% Least Impaired Days a) Regional Sulfate Co ntributions at Badlands

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

South Dakota’s sulfate contribu tion in 2002 at the Badlands Na tional Park for the 20% least impaired days is minimal at approximately 0.01 micrograms per cubic meter. The sources of sulfate emissions in South Dakota are generated fr om point, area, and mobile sources in 2002. In 2018, South Dakota’s sulfate cont ribution is less than 0.01 micrograms per cubic meter.

Based on the WRAP modeling, the su lfate concentrations for the 20% least impaired days (best days) in the Wind Cave National Park will also increase from 0.6 micrograms per cubic meter in 2002 to 0.7 micrograms per cubic meter in 2018 (see Figure 5-2(b)). Although Wyoming is not the greatest sulfate contributor during the 20% least impaired da ys, the increase appears to be

attributed to increases of sulf ate emission in the Wyoming, Idaho, and Montana, which is similar to what is predicted at the Badlands National Park.

b) Regional Sulfate Co ntributions at Wind Cave58 (WRAP TSS – http://vista.cira.colostate.edu/tss/ )

The WRAP modeling indicates the greatest sulfate contribution for the 20% least impaired days at the Wind Cave National Park in 2002 is generated from Outside the Domain followed by Wyoming, Canada, Idaho, and Montana. If you exclude Outside Domain because the source categories were not identified, a majority of th e sulfate contribution is generated from point

sources.

In 2018, the greatest sulfate cont ribution for the 20% least impaired days at the Wind Cave National Park does not change from 2002. The five greatest sulfate cont ributors are Outside the Domain, Wyoming, Canada, Idaho, and Montana. Again, point sources are the major contributor

of sulfate concentrations.

South Dakota’s sulfate contribu tion in 2002 at the Wind Cave Na tional Park for the 20% least impaired days is minimal at approximately 0.01 micrograms per cubic meter. The sources of59 sulfate emissions in South Dakota are generated fr om point, area, and mobile sources in 2002. In 2018, South Dakota’s sulfate contri bution stays about the same.

Point sources contribute a majority to the sulfat e concentrations in S outh Dakota’s two national parks during the 20% least impaired days. The st ate or region that contributes to the sulfate concentrations the greatest is not dependent on where the national park is located. For each national park, the greatest contributors are the same.

5.3.2 Organic Carbon Mass Contributions

Based on the IMPROVE data, organi c carbon mass also contributes to visibility impairment in

both the Badlands and Wind Cave National Parks. At the Wind Cave National Park, organic carbon mass has the greatest impact and at the Badl ands National Park it has the second greatest impact during the 20% most impaired days. Figure 5-3 and 5-4 illustrates the state and regional contribution of organic carbon mass during the 20 % most and least impaired days in South

Dakota’s two Class I areas. The contribut ions are based on modeling of 2002 emission

inventories of actual emissions and projected emissions in 2018. The bar chart identifies what state or region is contributing, the percentage of contribution, and what type of sources are contributing to organic carbon mass for the 2002 base year and 2018 projections. WRAP identified 12 source categories: 1) windblown dus t; 2) fugitive dust; 3) ro ad dust; 4) off-road mobile; 5) on-road mobile; 6) off-shore; 7) WR AP area oil and gas; 8) area; 9) biogenic; 10) natural fires; 11) anthropogenic fire; and 12) point sources.

The WRAP modeling indicates th e greatest percentage of orga nic carbon mass contribution for the 20% most impaired days at the Badlands and Wind Cave National Park in 2002 and 2018 is generated from within South Dakot a (see Figure 5-3). The percen tage at the Badlands and Wind Cave National Park is approximately 30 and 41 percent, respectively. The CENRAP region contributes approximately 17 pe rcent at the Badlands Natio nal Park; but only around eight percent at the Wind Cave Nationa l Park. Wyoming contributes approximately five percent at the Badlands National Park while up to eight percent at the Wind Cave National Park.

In all but the CENRAP region, th e source of organic ca rbon mass contributions is generated from natural fires. For example, approximately 23 percent of South Dakota’s 30 percent at the

Badlands National Park is attribut ed to natural fires. South Dakot a’s natural fire percentage at the Wind Cave National Park is even greater at 33 percent. In the CENRAP region, organic carbon mass contributions are generated from area sources such as woodstoves or other urban

related sources.

There appears to be slight decreases in orga nic carbon mass contributions from 2002 to 2018; but the reductions are minimal and mainly due to a decrease in off-road mobile and anthropogenic

fires.60 Figure 5-3 – Organic Carbon Mass Cont ribution for 20% Most Impaired Days a) Regional Organic Carbon Mass Cont ributions at Badlands

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

It is interesting that the WRAP modeling indi cates the greatest percen tage of organic carbon mass contribution for the 20% least impaired days at the Badlands National Park in 2002 and 2018 is generated from Montana (see Figure 5-4(a )) at approximately 35 percent. South Dakota, Oregon, and Idaho contribute approximately 20 percent, 12 percent, and seven percent, respectively. The source of organic carbon mass contributions is generated mainly from natural fires. Natural fire generated organic carbon mass from Montana contributes approximately 34 percent of the organic carbon mass in the Badlands National Park. There appears to be slight decreases in organic carbon mass contributions from 2002 to 2018; but the reductions are minimal and mainly due to a decrease in o ff-road mobile and anthropogenic fire.

For the Wind Cave National Park, the WRAP modeling for the 20% least impaired days agrees better with the 20% most impaired days in that the greatest percenta ge of organic carbon mass contribution in 2002 and 2018 is generated from within South Dakota (see Figure 5-4(b)) at approximately 42 percent. Montana, Wyomi ng, Idaho, and Oregon all contribute over eight percent. The major source of organic carbon mass c ontribution is generated from natural fires. There appears to be slight decreases in orga nic carbon mass contributions from 2002 to 2018; but the reductions are minimal and mainly due to a decrease in off-road mobile and anthropogenic

fire.61 b) Regional Organic Carbon Mass Contributions at Wind Cave

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

It appears from this information that natural fi res are the greatest cont ributor to visibility impairment from organic carbon mass in the two national parks. Based on South Dakota having the greatest contribution percenta ge for both the 20% most and least impaired days at the Wind Cave National Park, it appears natural fires within the Black Hills area have a greater impact on contributing to visibility impairment at the Wind Cave National Park then at the Badlands

National Park. DENR believes this will have to be reviewed further to determine the best method for minimizing the impacts natural fires a nd prescribed fires have on South Dakota’s two national parks.62 Figure 5-4 – Organic Carbon Mass Cont ribution for 20% Leas t Impaired Days a) Regional Organic Carbon Mass Cont ributions at Badlands

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

b) Regional Organic Carbon Mass Contributions at Wind Cave

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )63 5.3.3 Nitrate Contributions

Based on the IMPROVE data, ammonia nitrate cont ributes to visibility impairment in both the

Badlands and Wind Cave National Parks. Ammoni a nitrate contributions are not as great as ammonia sulfate or organic carbon mass but are significant enough to determine where the nitrates are being generated. Figure 5-5 and 5- 6 illustrates the state and regional contribution of sulfate during the 20% most and least impaired da ys in South Dakota’s two Class I areas. The contributions are based on modeling of 2002 emi ssion inventories of actual emissions and projected emissions in 2018. The pie chart in e ach figure displays the regional contribution to

the total annual modeled nitrate mass at the respective sites for the 2002 base year and 2018 projections. The bar chart id entifies what state or region is contributing, the amount of contribution, and what type of sources are contributing to nitrat e concentrations in the 2002 base year and 2018 projections. There ar e five source categories listed: 1) point; 2) area; 3) mobile; 4) anthropogenic fires (controlled burns ); and 5) natural fires and bi ogenic sources (mostly wildfire and windblown dust). In each figure, the first bar for each state and region is not labeled but represents the 2002 base year.

Based on the WRAP modeling, the n itrate concentrations for the 20% most impaired days (worst days) in the Badlands National Park will decr ease from 1.3 micrograms per cubic meter in 2002 to 1.2 micrograms per cubic meter in 2018 (see Fi gure 5-5(a)). The decrease appears to be

attributed to decreases of n itrate emission in the CENRAP region, South Dakota, Wyoming, and

North Dakota from mobile sources.

The WRAP modeling indicates the greatest nitrate contribution for the 20% most impaired days at the Badlands National Park in 2002 is ge nerated from Canada followed by Outside the Domain, the CENRAP region, South Dakota, and Wyoming. If you exclude Outside the Domain because the source categories were not identifie d, a majority of the nitrate contribution is generated from point, area, and mo bile sources in 2002 from influe nces outside of South Dakota;

and in South Dakota the nitrate co ntribution is from mobile, natura l fires and biogenic, and point

sources.

In 2018, the greatest nitrate cont ribution for the 20% most impa ired days at the Badlands

National Park remains from Canada followed by Outside the Domain, South Dakota, Wyoming, and North Dakota. The CENRAP region is no lo nger in the top five c ontributors because of nitrate decreases mainly due from mobile sources. The sources of nitrate contribution remain the

same from 2002 to 2018.

South Dakota’s nitrate contributi on in 2002 at the Badlands Nati onal Park is approximately 0.18 micrograms per cubic meter. The sources of nitr ates in South Dakota ar e generated from mobile, natural fires and biogenic, and point sour ces in 2002. In 2018, South Dakota’s nitrate contribution drops to 0.14 micrograms per cubi c meter due mainly to reduction in mobile

contributions. The reduction in mobile source co ntributions is due to new changes in federal

emission standards from mobile sources.64 Figure 5-5 – Nitrate Contributio n for 20% Most Impaired Days a) Regional Nitrate Co ntributions at Badlands

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

Based on the WRAP modeling, the n itrate concentrations for the 20% most impaired days (worst days) in the Wind Cave National Park will decr ease from 1.3 micrograms per cubic meter in 2002 to 1.1 micrograms per cubic meter in 2018 (see Figu re 5-5(b)). The decrease appears to be

attributed to decreases of nitrate emission in Wyoming, the CENRAP region, South Dakota,

North Dakota and Colorado from mobile sources.65 b) Regional Nitrate Co ntributions at Wind Cave

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

The WRAP modeling indicates the greatest nitrate contribution for the 20% most impaired days at the Wind Cave National Park in 2002 is generated from Canada followed by Wyoming, Outside the Domain, the CENRAP region, and South Dakota. If you exclude Outside the Domain because the source categories were not id entified, a majority of the nitrate contribution is generated from point, area, and mobile sour ces in 2002 from influences outside of South Dakota; and in South Dakota the ni trate contribution is from mob ile, natural fires and biogenic, and point sources.

In 2018, the greatest nitrate cont ribution for the 20% most impaired days at the Wind Cave

National Park remains from Canada followed by Wyoming, Outside the Domain, South Dakota, and North Dakota. The CENRAP region is no lo nger in the top five c ontributors because of nitrate decreases mainly due from mobile sources. The sources of nitrate contribution remain the

same from 2002 to 2018.66 South Dakota’s nitrate contribu tion in 2002 at the Wind Cave Na tional Park is approximately 0.13 micrograms per cubic meter. The sources of nitrates in South Dakota are generated mainly from mobile sources followed by natural fire s, biogenic and point sources in 2002. In 2018,

South Dakota’s nitrate contribu tion drops to 0.10 micrograms pe r cubic meter due mainly to

reduction in mobile contributions. The reduction in mobile source contributions is due to new changes in federal emission stan dards from mobile sources.

Based on the WRAP modeling, the n itrate concentrations for the 20% least impaired days (best days) in the Badlands National Park will decr ease from 1.7 micrograms per cubic meter in 2002 to 1.5 micrograms per cubic meter in 2018 (see Fi gure 5-6(a)). The decrease appears to be

attributed to decreases of nitr ate emission in the states and re gions is due to reductions from

mobile sources.

The WRAP modeling indicates the greatest nitrate contribution for the 20% least impaired days at the Badlands National Park in 2002 is ge nerated from Wyoming followed by Outside the Domain, Canada, Montana, and South Dakota. If you exclude Outside th e Domain because the source categories were not identified, a majority of the nitrate contribution is generated from point, area, and mobile sources in 2002 from infl uences outside of South Dakota; and in South Dakota the nitrate contribution is from mobile, na tural fires and biogenic, and point sources.

In 2018, the greatest nitrate cont ribution for the 20% most impa ired days at the Badlands National Park remains from Wyoming followed by Outside the Domain, Canada, Montana, and

South Dakota. The sources of nitrate c ontribution remain the same from 2002 to 2018.

South Dakota’s nitrate contributi on in 2002 at the Badlands Nati onal Park is approximately 0.11 micrograms per cubic meter. The sources of nitr ates in South Dakota are generated mainly from mobile sources followed by natural fires, bioge nic and point sources in 2002. In 2018, South Dakota’s nitrate contribution drops to 0.10 micrograms per cubic meter due mainly to reduction

in mobile contributions. The reduction in mobile source contributions is due to new changes in

federal emission standards from mobile sources.

Based on the WRAP modeling, the n itrate concentrations for the 20% least impaired days (best days) in the Wind Cave National Park will decr ease from 1.0 micrograms per cubic meter in 2002 to 0.9 micrograms per cubic meter in 2018 (see Figu re 5-6(b)). The decrease appears to be

attributed to decreases of nitr ate emission in the states and re gions is due to reductions from

mobile sources.67 Figure 5-6 – Nitrate Contributio n for 20% Least Impaired Days a) Regional Nitrate Co ntributions at Badlands

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

The WRAP modeling indicates the greatest nitrate contribution for the 20% least impaired days at the Wind Cave National Park in 2002 is generated from Wyoming followed by Outside the Domain, Canada, Utah, and Montana. If you ex clude Outside the Domain because the source categories were not identified, a majority of the nitrate contribution is ge nerated from point, area,

and mobile sources in 2002.68 b) Regional Nitrate Co ntributions at Wind Cave

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

In 2018, the greatest nitrate cont ribution for the 20% most impaired days at the Wind Cave National Park remains from Wyoming followed by Outside the Domain, Canada, Montana, and

Utah. The sources of nitrate contri bution remain the same from 2002 to 2018.

South Dakota’s nitrate contribu tion in 2002 at the Wind Cave Na tional Park is approximately 0.03 micrograms per cubic meter. The sources of nitrates in South Dakota are generated mainly from mobile sources in 2002. In 2018, South Dakota’s nitrate contribution drops to 0.02 micrograms per cubic meter due mainly to reducti on in mobile contributions. The reduction in

mobile source contributions is due to new cha nges in federal emission standards from mobile

sources.

5.3.4 Coarse Particulate Matter Contribution69 Based on the IMPROVE data, coarse particulate ma tter contributes to visibility impairment in

both the Badlands and Wind Cave National Parks. Coarse particulate matter contributions are not as great as ammonia sulfate or organic ca rbon mass but are signif icant enough to determine where the coarse particulate matte r is being generated. Coarse pa rticulate matter has the greater impact at the Badlands National Park then it does at the Wind Cave National Park during the 20% most impaired days. Figure 5-7 and 5-8 il lustrates the state and regional contribution of coarse particulate matter during the 20% most a nd least impaired days in South Dakota’s two

Class I areas. The contributions are based on mo deling of 2002 emission inventories of actual emissions and projected emissions in 2018. The bar chart identifies what state or region is contributing, the percentage of contribution, and wh at type of sources are contributing to coarse particulate matter for the 2002 base year and 2018 projections. WRAP identified 12 source categories: 1) windblown dust; 2) fugitive dust; 3) road dust; 4) off-road mobile; 5) on-road mobile; 6) off-shore; 7) WRAP area oil and gas; 8) area; 9) bi ogenic; 10) natural fires; 11) anthropogenic fire; and 12) point sources.

The WRAP modeling indicates the greatest percentage of coarse particulate matter contribution for the 20% most impaired days at the Badla nds and Wind Cave National Park in 2002 and 2018 is generated from within South Dakota (see Figure 5-7). The percentage at the Badlands and Wind Cave National Park is approximately 62 and 44 percent, respectively. The CENRAP region contributes approximatel y 21 percent at the Badlands National Park; and almost 25 percent at the Wind Cave Nationa l Park. Montana contributes approximately four percent at the Badlands National Park while up to 12 pe rcent at the Wind Cave National Park.

In all cases, the source of coarse particulate matter contributions is generated from windblown dust with some contribution from fugitive and road dust. For example, approximately 53 percent of South Dakota’s 61 percent in 2002 at the Badl ands National Park is attributed to windblown dust. South Dakota’s windblown dust percentage at the Wind Cave National Park is less at 32 percent; but that is to be exp ected because of the dryer condit ions and wide open areas in the

Badlands National Park.

The WRAP modeling indicates the greatest percentage of coarse particulate matter contribution for the 20% least impaired days at the Badla nds and Wind Cave National Park in 2002 and 2018 is also generated from within South Dakota (see Figure 5-8). The percentage at the Badlands and Wind Cave National Park is approximately 72 and 39 percent, respectively. The only other

notable contributor at th e Badlands National Park is Montana at approximately 12 percent. At the Wind Cave National Park, Montana’s influen ce is greater at approximately 29 percent. Wyoming contributes approximately 11 pe rcent at the Wind Cave National Park.70 Figure 5-7 – Coarse Particulate Matter Contribution for 20% Most Impaired Days a) Regional Coarse Particulate Matter Contri butions at Badlands

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

b) Regional Coarse Particulate Matter Contribut ions at Wind Cave

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )71 In the Badlands National Park, the source of coar se particulate matter cont ributions is generated

from windblown dust with some contribution fr om fugitive and road dust. For example, approximately 64 percent of South Dakota’s 72 percen t in 2002 at the Badlands National Park is

attributed to windblown dust. At Wind Cave National Park, windblown dust is still the major contributor but fugitive and road dust have a grea ter role in South Dakota and Montana; while in Wyoming point sources have a greater role. South Dakota’s windblown dus t percentage at the Wind Cave National Park is less at 25 percent; bu t that is to be expected because of the dryer conditions and wide open areas in th e Badlands National Park.

Figure 5-8 – Coarse Particulate Matter Contribution for 20% Least Impaired Days a) Regional Coarse Particulate Matter Contri butions at Badlands

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )72 b) Regional Coarse Particulate Matter Contri butions at Wind Cave

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )



### 6.0 Best Available Retrofit Technology (BART)

6.1 Bart-Eligible Sources

In accordance with 40 CFR § 51.308(e), South Dakota’ s State Implementation Plan is required to contain emission limitations representing BART and schedules for compliance with BART for each BART-eligible source that may reasonably be anticipated to cause or contribute to any impairment of visibility in a ny mandatory Class I area. A BART -eligible source is an existing stationary facility that is any of the following stationary sources of air pollutant that was not in operation prior to August 7, 1962, was in existe nce on August 7, 1977, and ha s the potential to emit 250 tons per year or more of any air polluta nt. Fugitive emissions must be included in the potential to emit, to the extent quantifiable.

1. Fossil-fuel fired steam electric plants of more than 250 million British thermal units per hour heat input,

2. Coal cleaning plants (thermal dryers),

3. Kraft pulp mills,

4. Portland cement plants,

5. Primary zinc smelters,

6. Iron and steel mill plants,

7. Primary aluminum ore reduction plants,

8. Primary copper smelters,

9. Municipal incinerators capable of charging more than 250 tons of refuse per day,73 10. Hydrofluoric, sulfuric, a nd nitric acid plants,

11. Petroleum refineries,

12. Lime plants,

13. Phosphate rock processing plants,

14. Coke oven batteries,

15. Sulfur recovery plants,

16. Carbon black plants (furnace process),

17. Primary lead smelters,

18. Fuel conversion plants,

19. Sintering plants,

20. Secondary metal production facilities,

21. Chemical process plants,

22. Fossil-fuel boilers of more than 250 million British thermal units per hour heat input,

23. Petroleum storage and transfer faciliti es with a capacity exceeding 300,000 barrels,

24. Taconite ore processing facilities,

25. Glass fiber processing plants, and

26. Charcoal production facilities.

In February 2004, DENR followed the procedures in 40 CFR Part 51, Appendix Y in identifying emission units at stationary faci lities in South Dakota meeting the above categories, identifying the startup date of the emission units, comparing the potential emissions to the 250 tons per year cutoff, and identifying the emissions units and pollutants that constitute the BART-eligible sources. The following terms are defined below:

1. “In Operation” means engaged in activity re lated to the primary design function of the source. The date the unit is permitted is not important to meet this test because the focus is on actual operation of the unit;

2. “In Existence” means that the owner or operator has obtained all necessary preconstruction approvals or pe rmits required by federal, st ate, or local air pollution emissions and air quality laws or regulations and either has (1) begun, or caused to begin, a continuous program of physical on-site construction of the f acility or (2) entered into binding agreements or contractual obligati ons, which cannot be canceled or modified

without substantial loss to the owner or operator, to undertak e a program of construction of the facility to be comp leted in a reasonable time;

3. “Date of Reconstruction” must occur during the August 7, 1962 to August 7, 1977 time period; and

4. “Potential to Emit” means the maximum cap acity of a stationary source to emit a pollutant under its physical and operational design. Any physical or operational limitation on the capacity of the source to emit a polluta nt including air polluti on control equipment and restrictions on hours of operation or on th e type or amount of material combusted, stored, or processed, shall be tr eated as part of its design if the limitation or the effect it would have on emissions is federally enfor ceable. Secondary emissions do not count in determining the potential to emit of a stationary source. However, fugitive emissions, to the extent quantifiable, must be counted for the 26 categories.74 In accordance with 40 CFR § 51.308(e)(1)(i), Table 6-1 provides a list of existing stationary facilities from the February 2004 analysis that may be considered a BA RT-eligible source and need further investigatio n to determine if they are subject to BART.

Table 6-1– List of BART-Eligible Sources 1

Maximum Potential to Emit BART

Unit Date Capacity TSP SO 2 NOx VOC Eligible Northern States Power Company – Sioux Falls

#1 – Babcock boiler 1969 330 MMBtus/hr 7 1 795 2 Yes

#2 – Babcock boiler 1969 330 MMBtus/hr 7 1 795 2 Yes

#3 – Babcock boiler 1969 330 MMBtus/hr 7 1 795 2 Yes

Total = 990 MMBtus/hr 21 3 2,385 6 Yes Pete Lien and Sons, Inc. – Rapid City

#6 – Vertical kiln 1966 - 561 0 13 1 Yes

#7 – Pebble lime crusher 1970 - 1 0 0 0 Yes #8 – Large hydrator 1965 - 97 0 0 0 Yes #12 – Lime bagging 1963 - 48 0 0 0 Yes

Total = 707 0 13 1 Yes Otter Tail Power Company – Big Stone I Power Plant
#1 – Babcock boiler 1975 5,609 MMBtus/hr 300 19,863 17,179 125 Yes

1 – “TSP” means total suspended particulate, “SO 2 ” means sulfur dioxide, “NOx” means nitrogen oxide, and “VOCs” means volatile organic compounds.

In accordance with 40 CFR Part 51, Appendix Y, the next step is to identify those BART-eligible sources that may “ emit any pollutant which may reasonably be anticipated to cause or contribute to any impairment of visibility .” For each source subject to BA RT, DENR is required to identify the best system of continuous emission control technology for each source after considering the following as specified in section 169A(g)(2) of the federal CAA:

1. Cost of compliance;

2. The energy and non-air quality enviro nmental impacts of compliance;

3. Any existing pollution control tech nology in use at the source;

4. The remaining useful life of the source; and

5. The degree of visibility improvement which may reasonably be anticipated from the use

of BART.

The results of the BART review are require d to be submitted in the Regional Haze State Implementation Plan identifying the BART emis sion limitations and timeline for demonstrating compliance. The timeline for demonstrating co mpliance shall not exceed five years after EPA approves the Regional Haze State Implementation Plan. DENR may establish design, equipment, work practice or other operational standards wh en limitations on measurement technologies make emissi on standards infeasible.

6.1.1 Northern States Power Company – Sioux Falls75 The three units at Northern States Power Comp any in Sioux Falls, South Dakota is considered fossil-fuel fired steam electric plant. The units were built in 1969 and have a maximum capacity greater than 250 million Btus per hour per unit. However, Northern States Power Company decommissioned these three units and they are no longer permitted to operate in Northern States Power Company’s Title V air quality permit. Ther efore, these three units at Northern States Power Company’s Sioux Falls s ite are not subject to BART.

6.1.2 Pete Lien and Sons, Inc. – Rapid City

Pete Lien and Sons operates a limestone quarry operation and lime plant in northwest Rapid City. There are four operations that were identified in the February 2004 analysis, not in operation prior to August 7, 1962, an d in existence on August 7, 1977. The four operations are a 1966 vertical kiln, 1970 pebble lime crusher, 1965 large hydrator, and 1963 lime bagging operation. Only the 1966 vertical kiln has the potential to emit over the 250 tons per year

threshold.

As identified in Pete Lien and Sons’ existing Title V air quality permit issued November 12, 2008, the 1970 pebble lime crusher was replaced with a 1982 pebble lime crusher and the 1963 bagging operation was replaced with a 2004 lime baggi ng operation. Therefore, these two units

will not be evaluated further.

Pete Lien and Sons falls under the “lime plant” category listed above. DENR researched the definition of “lime plant” to determine if the la rge hydrator is included in the definition of a lime plant. DENR determined that typically the de finition for the 26 categories coincides with the definitions under the New Source Performance Standards. Under 40 CFR Part 60, Subpart HH, a lime manufacturing plant means, “ ...any plant which used a rotary lime kiln to produce lime product from limestone by calcinations. ” Based on this definition of a lime plant, Pete Lien and

Sons would not be considered a lim e plant because the kiln in questi on is a vertical kiln and not a rotary kiln. In addition, only the kiln would be cons idered a “lime plant”.

DENR assumed the vertical kiln was cons idered a lime plant and on April 21, 2006, DENR requested that WRAP model Pete Lien and Sons emissions to determine if they would cause or contribute to any impairment of visibility in a Class I area. WRAP initiated this process by running CALMET/CALPUFF m odeling using WRAP’s “ CALMET/CALPUFF Protocol for BART Exemption Screening Anal ysis for Class I Areas in the Western United States ,” August 15, 2006. The basic assumptions in the protocol are:

1. Use of three years of modeling consis ting of calendar year 2001, 2002 and 2003;

2. Visibility impacts due to emissions of sulfur dioxide , nitrogen oxide and primary particulate matter emissions were calcula ted. Unless a state provided speciated particulate matter emissions, all PM emissions were modeled as PM 2.5 . In this case all

PM emissions were modeled as PM 2.5 ; 3. Visibility was calculated us ing the original IMPROVE equation and annual average natural conditions; and

4. CALPUFF version 6.112 was used in the analysis.76 The CALPUFF modeling procedures are outlined in WRAP’s BART Modeling Protocol, which can be reviewed at the following website:

http://pah.cert.ucr.edu/aqm/308/ba rt/WRAP_RMC_BART_Protocol_Aug15_2006.pdf

.

Table 6-2 provides a summary of the modeli ng outputs based on annual sulfur dioxide and nitrogen oxide emissions of 0.4 and 277 tons per year, respectively.

Table 6-2– WRAP’s Modeling Results for Pete Lien and Sons 1

Minimum Max

Delta 99th Days Annual 98th percentile

Class I Area State Distance (dv) (dv) >0.5 2001 2002 2003

Badlands SD 73 km 0.267 0.140 0 0.120 0.160 0.105 Boundary Waters MN 946 km 0.014 0.007 0 0.005 0.003 0.003 Bridger WY 489 km 0.021 0.003 0 0.001 0.002 0.001 Fitzpatrick WY 501 km 0.018 0.002 0 0.001 0.001 0.001

Grand Teton WY 570 km 0.005 0.001 0 0.000 0.000 0.000

Lostwood ND 509 km 0.040 0.009 0 0.006 0.005 0.007

Medicine Lake MT 488 km 0.030 0.011 0 0.006 0.005 0.010

North Absaroka WY 487 km 0.008 0.002 0 0.001 0.001 0.001

Teton WY 513 km 0.009 0.001 0 0.001 0.001 0.000

Theodore Roosevelt ND 311 km 0.049 0.023 0 0.014 0.016 0.015

Ul Bend MT 516 km 0.024 0.006 0 0.005 0.003 0.005 Voyageurs MN 921 km 0.012 0.006 0 0.004 0.002 0.003

Washakie WY 461 km 0.019 0.003 0 0.001 0.002 0.001

Wind Cave SD 52 km 0.366 0.203 0 0.128 0.137 0.139

Yellowstone WY 524 km 0.008 0.002 0 0.001 0.001 0.001

1 - “dv” means deciview and “km” means kilometers.

The modeling conducted by WRAP demonstrated th at Pete Lien and Sons did not cause or contribute to visibility impairme nt at a Class I area. After re viewing the modeling inputs, DENR

determined the vertical kiln should be modeled again because of errors in the UTM coordinates and emission rates. However, before the m odeling could be re-run, th e vertical kiln was

shutdown and dismantled in 2009.

Although Pete Lien and Sons’ existing Title V air quality permit still identif ies the vertical kiln as a unit, permit condition 1.1 specifies in the foot note of Table 1-1 that Pete Lien and Sons is required to shutdown and dismantle the vertical k iln before the initial startup of Unit #45. Pete Lien and Sons fulfilled this commitment by notif ying DENR on March 13, 2009, that the vertical kiln was shutdown and dismantled. Therefore, Pe te Lien and Sons’ shutdown and dismantled the unit subject to BART and DENR di d not re-model the vertical kiln.

6.1.3 Otter Tail Power Company – Big Stone I77 Unit #1 at the Big Stone I Powe r Plant was built in 1975, has a maximum capacity greater than 250 million Btus per hour, and has the potential to emit greater than 250 tons per year of any air pollutant. The next step in this analysis is to determine if Unit #1’s emissions may reasonably be anticipated to cause or c ontribute to any impairment of visibi lity in a Class I area. On April 21, 2006, DENR requested that WRAP model Un it #1’s emissions from Otter Tail Power Company’s Big Stone I Power Plant.

WRAP initiated this process by running CALMET/CALPUFF modeling using WRAP’s “CALMET/CALPUFF Protocol for BART Exempti on Screening Analysis for Class I Areas in the Western United States,” August 15, 2006. Th e basic assumptions in the protocol are:

1. Use of three years of modeling of 2001, 2002 and 2003;

2. The sulfur dioxide, nitrogen oxide and part iculate emission rates represent the 24-hour average actual emission rate from the highest emitting day of the meteorological period modeled, not including periods of st artup, shutdown, or malfunctions;

3. Visibility impacts due to emissions of sulfur dioxide , nitrogen oxide and primary particulate matter emissions were calcula ted. Unless a state provided speciated particulate matter emissions, all PM emissions were modeled as PM 2.5 ; 4. Visibility was calculated us ing the original IMPROVE equation and annual average natural conditions; and

5. CALPUFF version 6.112 was used in the analysis.

The CALPUFF modeling procedures are outlined in WRAP’s BART Modeling Protocol and can be reviewed at the following website:

http://pah.cert.ucr.edu/aqm/308/ba rt/WRAP_RMC_BART_Protocol_Aug15_2006.pdf

.

Table 6-3 provides a summary of the modeli ng outputs based on annual sulfur dioxide and nitrogen oxide emissions of 12,409 and 15,580 tons per year, respectively. The annual sulfur dioxide and nitrogen oxide emissions were de rived from WRAP’s BART protocol identified

above.

Table 6-3– WRAP’s Modeling Results for Otter Tail Power Company Big Stone I 1

Min Max

Delta 99th Days Annual 98th percentile

Class I Area State Distance (dv) (dv) >0.5 2001 2002 2003

Badlands SD 470 km 3.047 1.076 21 0.364 0.417 0.683 Boundary Waters MN 431 km 1.653 1.133 63 0.951 0.659 1.034 Bridger WY 1,041 km 0.147 0.003 0 0.001 0.001 0.000 Fitzpatrick WY 1,050 km 0.079 0.005 0 0.001 0.001 0.000
Grand Teton WY 1,112 km 0.029 0.003 0 0.001 0.001 0.000

Lostwood ND 585 km 0.779 0.370 7 0.263 0.175 0.204

Medicine Lake MT 690 km 0.678 0.345 7 0.256 0.211 0.218
North Absaroka WY 1,013 km 0.121 0.026 0 0.011 0.008 0.001
Teton WY 1,052 km 0.049 0.008 0 0.004 0.002 0.001

Theodore Roosevelt ND 555 km 2.061 0.840 27 0.581 0.443 0.68778 Min Max

Delta 99th Days Annual 98th percentile

Class I Area State Distance (dv) (dv) >0.5 2001 2002 2003

Ul Bend MT 902 km 0.840 0.196 3 0.089 0.065 0.043 Voyageurs MN 438 km 1.658 0.915 52 0.666 0.703 0.729
Washakie WY 1,006 km 0.090 0.018 0 0.007 0.005 0.001

Wind Cave SD 572 km 1.545 0.631 13 0.224 0.263 0.261
Yellowstone WY 1,049 km 0.068 0.018 0 0.009 0.004 0.001

1 - “dv” means deciview and “km” means kilometers.

WRAP had determined that Big Stone I would be reasonably anticipated to contribute to an impairment of visibility at the Badlands Na tional Park in South Dakota, Theodore Roosevelt National Park in North Dakota, and Boundary Wa ters Wilderness and Voyageurs National Park

in Minnesota.

6.2 Otter Tail Power Company’s Modeling Results

Otter Tail Power Company was notified of the results and requested an opportunity to verify the results after identifying several errors in act ual emission rates and stack parameters. The department allowed Otter Tail Power Company to re-run the models usin g the correct emission rates and stack parameters. On March 19, 2008, Otter Tail Power Company submitted an individual source analysis using CALMET/CALPU FF; but after review by the state, EPA, and federal land managers (U.S. Fish and Wildlife Se rvice, U.S. Forest Service and National Park Service) it was determined that a BART mode ling protocol should be submitted and approved by all parties, Otter Tail Power Company would r un the model using the approved protocol, and submit before Otter Tail Power Comp any’s results could be approved.

Otter Tail Power Company submitted the BART modeling protocol on January 16, 2009. After

several conference calls and di scussions, a revised protocol identified as June 2009, was submitted July 1, 2009. After several submitta ls and conference calls, Otter Tail Power Company committed to make the following changes to the protocol in an email dated August 31,

2009:

1. Although Otter Tail Power Company attached the CALMET switches it would use, it committed to using the CALMET switches recommended and approved by EPA andFederal Land Managers (FLMs) dated August 20, 2009. However, to ensure the most upto-date CALMET switches are used, DENR is requiring Otter Tail Power Company to

use the CALMET switches identified in EPA’s memorandum dated August 31, 2009, from Tyler J Fox, Group Leader, Air Quality Modeling Group, to EPA Regional Modeling Contacts. The date on the listi ng of CALMET switches is August 28, 2009. The memorandum may be viewed in Attachment C.

2. Otter Tail Power Company committed to use the CALPUFF switches that Penny Shamblin, with Hunton and Williams, subm itted to DENR by email on August 19, 2009. Although the document contains CALMET switc hes, only the CALPUFF switches (see Attachment D) in this email will be used by Otter Tail Power Company in the BART analysis. The CALMET switches mentioned above will be the ones used in the analysis.79 3. Otter Tail Power Company proposes to revise the June 2009 modeli ng protocol by using a 12 kilometer MM5 grid and a 4 kilometer CALMET grid rather than the 4 kilometer MM5 grid and 4 kilometer CALMET grid identi fied in the June 2009 modeling protocol. DENR reviewed other acceptable modeling prot ocols and is acceptable to this change.

4. Although Otter Tail Power Company may r un POSTUTIL option MNITRATE=2 for its own purposes, the modeling results DENR w ill accept for the BART analysis will be

MNITRATE=1.

The CALPUFF switches Otter Tail Power Company is recommending contains five switches that are different than those recommended by EPA as de faults. The following identifies the variable, EPA’s default, recommended default by Otter Tail Power Company, and DENR’s response:

1. “NSPEC” – Identifies the number of species modeled. The EPA default is 5 and Otter Tail Power Company is proposing 11, whic h follows the FLM guidance on particle speciation and size. DENR is agreeable to this change.

2. “NSE” – Number of species emitted. The EPA default is 3 and Otter Tail Power Company is proposing 9.

3. “MSPLIT” – Allows puffing. The EPA default is 0 (No) and Otter Tail Power Company is proposing 1 (Yes). Puff splitting in necessary due to the distance from Big

Stone I to a federal Class I area. DENR is agreeable to this change.

4. “MESHDN” – Grid receptor spacing. The EPA default is 1; however, Otter Tail Power Company is stating this is “Not Applicabl e”. DENR is agreeable to this change.

5. “BCKNH3” – Ammonia background. The EPA de fault is 10 parts per billion and Otter Tail Power Company is recommending 1 pa rt per billion. During the June 3, 2009, conference call, EPA stated it was okay with this change. DENR is agreeable to this change.

On September 18, 2009, the department determin ed that Otter Tail Power Company’s BART modeling protocol as identified above. See A ppendix A for the approval letter and the BART modeling protocol dated June 2009.

The modeling results identified that Otter Tail Power Company’s Big Stone I Power Plant would be reasonably anticipated to cont ribute to an impairment of visi bility at the Boundary Waters and Voyageurs federal Class I areas in northern Minnesota and the Isle Royale federal Class I area in Michigan. The reasonably anticipa ted to contribute to an impa irment is based on visibility impacts greater than 0.5 deciview based on the 98 th percentile at the three federal Class I areas. See Appendix B for the modeling report dated October 2009, and Table 6-4 for a summary of the modeling results.80 Table 6-4– Otter Tail Power Company’ s Modeling Results for Big Stone I 1

Min Max Delta 99 th 98 th

Class I Area State Distance (dv) (dv) (dv)

Badlands SD 470 km 2.202 0.698 0.481 (0.5) Boundary Waters MN 431 km 3.574 1.351 1.079 (1.1) Lostwood ND 585 km 1.110 0.722 0.409 (0.4)

Theodore Roosevelt ND 555 km 2.232 0.772 0.459 (0.5) Voyageurs MN 438 km 2.162 1.376 0.724 (0.7) Wind Cave SD 572 km 1.671 0.591 0.325 (0.3) Isle Royale MI 1,049 km 1.806 0.789 0.665 (0.7)

1 - “dv” means deciview and “km” means kilometers.

Otter Tail Power Company results did not matc h up entirely with the modeling conducted by WRAP. In particular, Otter Tail Power Compa ny’s modeling also showed that Big Stone I would reasonably contribute to impairment at the Isle Royale National Park in Michigan. DENR believes Otter Tail Power Company’s modeling best represent the visibility impacts from Big Stone I since the original modeling did not have the correct emission rates and stack parameters and the CALPUFF modeling conducted by Otte r Tail Power Company included puff splitting, which helps improve the accuracy of the m odel when used for great distances.

In accordance with the 40 CFR Part 51, Appendix Y, DENR used a contribution threshold of 0.5 deciviews for determining if Otter Tail Power Co mpany’s Big Stone I facility is subject to BART. The guideline provides th e state the discretion to set a threshold below 0.5 deciviews if “the location of a large number of BART-eligible sources within the state and proximately to a Class I area justifies this approach. The di scretion was based on the following factors:

1. It equates to the 5 percent extinction threshold for new sources under the PSD New Source Review rules;

2. It is consistent with the thre shold selected by other states in the west, which all selected 0.5 deciviews; and

3. It represents the limit of perceptible change.

DENR chose the 0.5 deciview threshold because th ere is only one source th at is BART-eligible and it is greater than 300 kilometers from any Cl ass I area. Therefore, DENR will establish this threshold in its proposed ARSD Chapter 74: 36:21 – Regional Haze Program. Otter Tail Power Company’s Big Stone I power plant exceeded th is threshold and is subject to BART. In accordance with 40 CFR § 51.308(e)(1)(i), the only s ource subject to BART in South Dakota is Otter Tail Power Company’ s Big Stone I facility.

In accordance with 40 CFR § 51.308(e)(1)(ii), DENR requested that Otter Tail Power Company complete a Case-by-Case BART analysis, which includes determining the visibility improvements expected at each of th ese Class I areas (see Appendix C).81 6.3 Otter Tail Power Company’s Ca se-by-Case BART Analysis

In accordance with 40 CFR 51.301, Best Available Retrofit Technology (B ART) is defined as “an emission limitation based on the degree of reduction achievable through the application of the best system of continuous emission reduction for each pollutant which is emitted by an existing stationary facility. The em ission limitation must be established, on a case-by-case basis, taking into consideration the technology availa ble, the costs of comp liance, the energy and nonair quality environmental impacts of compliance, any pollution control equipment in use or in existence 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.”

In accordance with 40 CFR § 51.308(e)(1)(ii)(B), the determination of BART for fossil fuel fired power plants having a total ge nerating capacity greater than 750 megawatts must be made pursuant to the guidelines in Appendix Y of this part (Guidelines for BART Determinations under the Regional Haze Rule). Appendix Y identifie s a five step process in determining BART. The five steps are as follows:

1. STEP 1—Identify All Available Retrofit Cont rol Technologies: In identifying ‘‘all’’ options, one should identify the most stringen t option and a reasonabl e set of options for analysis that reflects a comprehensive list of available technologies. It is not necessary to list all permutations of availabl e control levels that exist for a given technology. The list is complete if it includes the maximum le vel of control each technology is capable of achieving. Where a New Source Performance Standard (NSPS), under 40 CFR Part 60, exists for a source category, one should include a level of c ontrol equivalent to the NSPS as one of the control options;

2. STEP 2—Eliminate Technically Infeasible Options: One evaluates the technical feasibility of the contro l options identified in Step 1. One should document a demonstration of technical infeasibility and should explain, based on physical, chemical, or engineering principles, w hy technical difficulties would preclude the successful use of the control option on the emissions unit under review. One may then eliminate such technically infeasible control options from further considerat ion in the BART analysis;

3. STEP 3—Evaluate Control Effectiveness of Remaining Control Technologies: One

evaluates the control effectiveness of all th e technically feasible control alternatives identified in Step 2 for the pollutant and emissions unit under review. Two key issues in this process include: (1 ) Make sure that you express the de gree of control using a metric that ensures an ‘‘apples to apples’’ compar ison of emissions performance levels among options; and (2) Give appropriate treatment a nd consideration of control techniques that can operate over a wide range of emission performance levels;

4. STEP 4—Evaluate Impacts and Document the Results: Once the available and technically feasible control technology options are identified, one should conduct the following analyses when you make a BART determ ination: (1) Impact analysis part 1 – costs of compliance; (2) Impact analysis part 2 – energy impacts, (3) Impact analysis part 3 – non-air quality environmental impacts; a nd (4) Impact analysis part 4 – remaining useful life; and

5. STEP 5—Evaluate Visibility Impacts: On e should evaluate the net visibility improvement form the available and technical ly feasible control technology options.82 This is accomplished by m odeling the pre-control and post-control emission rates according to an accepted methodology.

In determining what is considered BART, Appendi x Y identifies that the state should develop a chart (or charts) displaying each of the alternatives and include: (1) Expected emission rate (e.g., tons per year, pounds per hour); (2) Emissions performance level (e.g., percent pollutant removed, emissions per unit product, pounds per m illion Btus, parts per million); (3) Expected emissions reductions (e.g., tons pe r year); (4) Costs of complianc e (e.g., total annualized costs in dollars, cost effectiveness (dolla r per ton), incremental cost eff ectiveness (dolla r per ton), any other cost-effectiveness measures (dollar per deci view)); (5) Energy impacts; (6) Non-air quality environmental impacts; and (7) Modeled visibility impacts.

Otter Tail Power Company’s Big Stone I facil ity does not have a total generating capacity greater than 750 megawatts. Theref ore, DENR is not required to follow these guidelines. As such, DENR will follow the steps identified in Appendix Y with some slight differences. For example, in identifying the available control technologies, DENR is not listing any of the permutations of the control levels for each id entified control technology as suggested by EPA’s guidance. DENR will use the init ial step to identify control technologies without including the control levels. Step 3 is used to evaluate the control effectivene ss or permutations of the control levels for those control technologi es that are considered feasible to install or maintain as identified in Step 2.

6.3.1 Particulate BART Review

6.3.1.1 Particulate Control Technologies

Step 1 requires the identification of all availabl e retrofit control technolo gies. The particulate

matter emissions from fossil-fuel fired units can be categorized as either filterable or condensable particulate. The filtera ble particulate matter exists as a solid or liquid particle in the

exhaust of a boiler as it leaves the stack. As such, the filterable particulate may be collected by placing a control device in the flue gas stream pr ior to the stack. Condensable particulates are emitted out the stack in a gaseous state but rapidly condense into particles when released into the atmosphere and cooled. Therefore, condensable particulates may not be readily collected by placing a control device in the stack.

Those control technologies being reviewed unde r Step 1 are those that would control the filterable particulate matter. Otter Tail Power Company identified the following control options for particulate matter.

1. Existing fabric filter (baghouse);

2. New fabric filter (baghouse);

3. Compact hybrid particulate collector; and

4. Electrostatic precipitator.

DENR also identified two more control technologi es that may be used to control particulate

emissions and are listed below:83 1. Wet scrubber; and

2. Cyclone(s)/Multicyclone(s).

6.3.1.2 Technically Feasible Particulate Control Technologies

Step 2 requires the eliminati on of any control tec hnologies identified in Step 1 that are technically infeasible. A compact hybrid particulat e collector is a combination of an electrostatic precipitator and a baghous e in series. The compact hybrid pa rticulate collector is generally operated with a higher air-to-cl oth ratio than a typical baghous e. Since Otter Tail Power Company already has a baghouse inst alled at Big Stone I, Otter Ta il did not further consider the compact hybrid particulate collector.

Even though Otter Tail Power Company identified a reason for not selecting the compact hybrid particulate collector, the reasoning do es not identify that the technol ogy is infeasible to install. Since both an electrostatic precipitator and a ba ghouse are both technicall y feasible options and without further evidence, DENR co nsiders the compact hybrid partic ulate collector as a feasible control technology.

DENR determined that the following particulate c ontrol technologies were fe asible for Otter Tail Power Company:

1. Existing fabric filter (baghouse);

2. New fabric filter (baghouse);

3. Compact hybrid particulate collector;

4. Electrostatic precipitator;

5. Wet scrubber; and

6. Cyclone(s)/Multicyclone(s).

6.3.1.3 Particulate Control Effectiveness

Step 3 requires the evaluation of control e ffectiveness for each control technology. DENR

evaluated the control effec tiveness by comparing the effectiveness in Table 6.5.

Table 6-5 – Comparison of Control E ffectiveness for Particulate Controls

Emission Rate Control Efficiency

Otter Tail 1 RBLC 3 PFDR 4 IEA 5

Rank Control (lbs/MMBtus) 2 (lbs/MMBtus) 2 (%) (%)

#1 Baghouse 0.015 0.010 to 0.03 95 to 99.9 >99 to >99.9999

#2 Electrostatic Precipitator 0.015 0.015 to 0.03 80 to 99.5 >99 to >99.99

#3 COHPAC 6 Not Provided 0.015 Not Identified Not Identified

#4 Wet Scrubber(s) Not Provided Not Identified 75 to 99 90 to 99.9

#5 Cyclone(s)/ Multicyclone(s) Not Provided Not Identified 50 to 95 75 – 9984 1 – The identified emission rates were identified in Otter Tail Power Company’s BART analysis;

2 – “lbs/MMBtus” means pounds per million British thermal units;

3 – The identified emission rates were obtained from EPA’s Reasonable Achievable Control Technology, Best Available Control Technol ogy, and Lowest Achievable Emission Rate Clearinghouse (RBLC) considering data for permits issued after calendar year 2000;

4 – The control efficiencies, in percent removal, are derived from page 473 of “Particulates and Fine Dust Removal Process and Equipment by Marshal Sittig”;

5 – The control efficiencies, in percent removal, are derived from the IEA Clean Coal Centre’s Webpage at http://www.iea-coal.org.uk/site/ieacoal/home ; and

6 – “COHPAC” means Compact Hybrid Particulate Collector.

6.3.1.4 Particulate Control Technology Impacts

In Step 4, DENR looked at impacts associated wi th the control alternativ es such as cost of compliance, energy impacts, non-air quality enviro nmental impacts, and th e remaining useful life of the project. These impacts are intended to provide rational in choosing between the alternative control options when determining what is considered BART. Otter Tail Power Company already has installed a nd is operating a baghouse, which is the top particulate control technology. Therefore, there is no additional compliance cost, en ergy impacts, etc. that Otter Tail Power Company would have to endure. As such, no additional impacts analysis will be conducted to determine the appropriate co ntrols for particulate matter.

6.3.2 Sulfur Dioxide BART Review

6.3.2.1 Sulfur Dioxide Control Technologies

Step 1 requires the identification of all availabl e retrofit control technologies. Otter Tail Power Company identified the following cont rol options for sulfur dioxide:

1. Fuel switching;

2. Semi-dry flue gas desulfurization; and

3. Wet flue gas desulfurization.

DENR also identified the following control techno logies that may be us ed to control sulfur

dioxide emissions:

1. Coal cleaning;

2. Coal upgrading;

3. Hydrated lime injection; and

4. Emerging control technologies such as Enviroscrub, Elec tro catalytic oxidation, and Airborne process.

6.3.2.2 Technically Feasible Sulfur Dioxide Control Technologies

Fuel switching is a viable method to reduce sulfur dioxide emissions by sw itching to a fuel with lower sulfur content. Otter Tail Power Compa ny’s Big Stone facility’s primary fuel source is

subbituminous coal obtained from the Powder River Basin in Wyoming. Powder River Basin85 subbituminous coal has one of the lowest sulfur c ontents available in the United States. As such, Otter Tail Power Company has alre ady implemented fuel switching.

Coal cleaning is typically performed by physical gravimetric separation which is capable of reducing sulfur, ash and impurities from the coal. The effectiveness of gravimetric separation is dependent on the ash content and the distribu tion of fuel bound sulfur between organic and inorganic. If the sulfur compounds are predominan tly inorganic materials, then coal cleaning is fairly effective, but if the sulfur compounds ar e predominantly organic materials, then coal cleaning is not effective. Physical cleaning or gravimetric separation may be effective with bituminous coals that contain high levels of inor ganic sulfur and ash. However, gravimetric coal cleaning is not technically feasible for low sulfur , low ash, and low inorgani c-sulfur content coal

such as the coal from the Powder River Basi n in Wyoming. Otter Tail Power Company’s Big Stone facility’s primary fuel source is subbitumi nous coal obtained from the Powder River Basin in Wyoming. As such, coal cleaning is not a technical feasible option for Otter Tail Power Company.

Coal upgrading such as a process developed by Evergreen Energy (formerly KFx) called the KFuel process enriches the coal by utilizing hi gh pressure and temperat ure conditions to reduce moisture and inorganic materials. Typically, the K-Fuel process is utilized to reduce the moisture content and increase the coal heating value, however, the process may remove some sulfur compounds. Evergreen Energy constructed a K-Fu el production facility in Gillette, Wyoming which may produce approximately 750,000 tons per year of K-Fuel. Otter Tail Power Company burned approximately 2,268,000 tons of coal in 2008. As such, coal upgrading is not a technically feasible option for Otter Tail Po wer Company because there is not enough being produced to supply Otter Tail Power Company’ s needs. In addition, based on Evergreen Energy’s webpage, this facility has b een idle since calendar year 2008.

Hydrated lime injection is a system that injects hydrated lime prior to the particulate collection system. The hydrated lime absorbs the sulfur diox ide and is collected in the particulate control device. Hydrated lime is also referred to as calcium hydroxide. The sulfur dioxide reacts with the calcium hydroxide to form calcium sulfate or calcium sulfite. Fly ash from the Powder River Basin has a calcium content of up to 30 percent. Since the Powder River Basin coal is already providing additional calcium to adsorb sulfur di oxide, the hydrated lime will not likely provide

additional sulfur dioxide removal. Otter Ta il Power Company’s primary fuel source is

subbituminous coal obtained from the Powder River Basin in Wyoming. As such, hydrated lime injection is not considered a technically feasib le option for Otter Tail Power Company since the concept is already taking place by using Power River Basin coal.

Emerging control technologies su ch as Enviroscrub, Electro catal ytic oxidation, and the Airborne process have not been commercially available and have not been demonstrated for long-term levels of performance. As noted in 40 CFR Part 51, Appendix Y, a control technology needs to be commercially available to be considered technically feasible. As such these emerging technologies are not considered technically feasible options for Otter Tail Power Company.

DENR determined that the following sulfur dioxi de control technologies were feasible for Otter Tail Power Company:86 1. Semi-dry flue gas desulfurization; and

2. Wet flue gas desulfurization.

6.3.2.3 Sulfur Dioxide Control Effectiveness

Step 3 requires the evaluation of control e ffectiveness for each control technology. DENR

evaluated the control effec tiveness by comparing the effectiveness in Table 6.6.

Table 6-6 – Comparison of Control Eff ectiveness for Sulfur Dioxide Controls

Emission Rate Control Efficiency

Otter Tail 1 RBLC 3 Basin 4 EPA 5

Rank Control (lbs/MMBtus) 2 (lbs/MMBtus) 2 (lbs/MMBtus) 2 (%)

#1 Wet Flue Gas

Desulfurization 0.043 to 0.15 0.1 to 0.167 0.05 90 to 98

#2 Semi-Dry Flue

Gas

Desulfurization 0.09 to 0.15 0.038 to 0.16 0.07 80 to 90

1 – The identified emission rates were identified in Otter Tail Power Company’s BART analysis;

2 – “lbs/MMBtus” means pounds per million British thermal units;

3 – The identified emission rates were obtained from EPA’s Reasonable Achievable Control Technology, Best Available Control Technol ogy, and Lowest Achievable Emission Rate Clearinghouse (RBLC) considering data for permits issued after calendar year 2000;

4 – The emission rates are based on the BACT analysis provided by Basin Electric Power Cooperative’s proposed NextGen project in South Dakota; and

5 – The control efficiencies, in percent removal, are from EPA’s “Air Pollution Control Technology Fact Sheet on Flue Gas Desulfurization Systems”.

6.3.2.4 Sulfur Dioxide Control Technology Impacts

Step 4 requires DENR to look at impacts associated with the control alternativ es such as cost of compliance, energy impacts, non-air quality enviro nmental impacts, and th e remaining useful life of the project. These impacts are intended to provide rational in choosing between the alternative control options when determining what is considered BART.

Otter Tail Power Company identified cost estimates for each of the control options. In addition, Otter Tail Power Company identified cost estimat ed for two different op erating scenarios for

each of the two control altern atives. Table 6-7 summarizes Otter Tail Power Company’s

estimated costs.

In 40 CFR Part 51, Appendix Y – Guidelines fo r BART Determination Under the Regional Haze Rule, in the section titled “How should I determine visibility impacts in the BART

determination” it notes that the model should use the 24-hour average actual emission rate from the highest emitting day of the meteorological period modeled (for the pre-control scenario). The 18,000 tons per year of sulfur dioxide is based on the highest average 24-hour average emission rate (4,832 pounds per hour) fo r calendar years 2001 through 2003 and operating 85% of the87 time or 7,746 hours per year. Based on the BART guidelines, the baseline emissions are 18,000

tons per year.

Table 6-7 – Comparison of Control Eff ectiveness for Sulfur Dioxide Controls

Control Option Capital Cost O&M 1 Annual Cost 2 Reduction 3 Cost

Effectiveness 4

WFGD #1 5 $171,800,000 $9,600,000 $29,050,000 17,100 $1,699

WFGD #2 6 $171,800,000 $9,490,000 $28,900,000 14,870 $1,944

SDFGD #1 7 $141,300,000 $7,660,000 $23,570,000 16,120 $1,462

SDFGD #2 8 $141,300,000 $7,480,000 $23,330,000 14,870 $1,569

1 – O&M represents the operational and maintenance cost estimate for the control alternative;

2 – Annual cost is the annualized cost for each c ontrol alternative taking into account both the capital and operational and maintenance costs;

3 – Reduction represents the amount of sulfur dioxi de reduced in tons per year annual from the baseline level of 18,000 tons of sulfur dioxide per year;

4 – Cost Effectiveness represents the annualized co st divided by the identified emission reductions (dollar per ton);

5 – WFGD #1 represents a wet flue gas desulfurization system meeting an emission rate of 0.043 pounds per million British thermal units;

6 – WFGD #2 represents a wet flue gas desulfurization system meeting an emission rate of 0.15 pounds per million British thermal units;

7 – SDFGD #1 represents a semi-dry flue gas desulfurization system meeting an emission rate of 0.9 pounds per million British thermal units; and

8 – SDFGD #2 represents a semi-dry flue gas desulfur ization system meeting an emission rate of 0.15 pounds per million British thermal units.

Otter Tail Power Company did not identify the cost effectiveness on a dollar per visibility

reduction. DENR considered this cost eff ectiveness in Step 5 of the analysis.

Otter Tail Power Company identified the energy im pacts cost associated for each of the control options. Table 6-8 summarizes Otter Tail Po wer Company’s estimated energy impacts.

Table 6-8 – Estimated Energy Impacts for Sulfur Dioxide Controls

Control Energy Demand Percent of Generation

Wet Flue Gas Desulfurization 9,500 kilowatts 2.0 percent Semi-Dry Flue Gas Desulfurization 3,325 kilowatts 0.7 percent

The non-air quality environmental impacts of the two c ontrol alternatives in clude the solid and aqueous waste streams. The semi-dry flue ga s desulfurization system would be installed upstream of the existing baghouse. The baghouse woul d be used to collect the injected lime and reacted sulfur dioxide emissions along with othe r existing particulate matter emissions. Otter Tail Power Company did not identify how much a dditional particulate matter would be collected by the baghouse due to the use of the semi-dry flue gas desulfurization system. At this time, it is

assume the additional material collected in the baghouse is negligible compared to the existing collection. Otter Tail Power Company estimates th at the wet flue gas desulfurization system would generate an additional 44,700 tons of gyps um solids which would need to be properly disposed.88 In conducting its cost analysis, Otter Tail Powe r Company used 30 years as the life expectancy averaging period for the control alternatives. Since the useful life of Otter Tail Power Company’s Big Stone I facility is expected to be longer than 30 years, there is no difference between the control options base d on useful life.

6.3.3 Nitrogen Oxide BART Review

6.3.3.1 Nitrogen Oxide Control Technologies

Step 1 requires the identification of all availabl e retrofit control technologies. Otter Tail Power Company identified the following co ntrol options for nitrogen oxide:

1. Low-nitrogen oxide burners (LNBs);

2. Over-fire air (OFA);

3. Separated over-fire air (SOFA);

4. Selective non-catalyt ic reduction (SNCR);

5. Rich reagent injection (RRI); and

6. Selective catalytic reduction (SCR).

DENR also identifies the following control technol ogies that may be used to control nitrogen

oxide emissions:

1. Flue-gas recirculation;

2. Oxygen enhanced combustion;

3. Catalytic absorption/oxidation;

4. Gas reburn; and

5. Emerging control technologi es such as Enviroscrub, Electro-catalytic oxidation, NOxStar, and Cascade processes.

6.3.3.2 Technically Feasible Nitrogen Oxide Control Technologies

Low-nitrogen oxide burners limit nitrogen oxide formation by controlling the stoichiometric and temperature profiles of the combustion process. Low-nitrogen oxide burners attempt to delay the complete mixing of fuel and air as long as possibl e within the constraints of the furnace design. This is the reason flames from low-nitrogen oxi de burners are longer than conventional burners. Cyclone furnace’s length and diameter are not de signed with sufficient size to allow for lownitrogen oxide burners to be installed allowing stable combustion. As such, low-nitrogen oxide burners are not considered a technically f easible option for Otte r Tail Power Company.

Flue-gas recirculation reduces the formation of thermal nitrogen oxide emissions in a boiler by limiting the amount of oxygen availabl e for oxidation in the fuel rich zone of the boiler. Fluegas recirculation is not known to reduce nitroge n oxide emissions any further when added with an over-fire air system. Therefore, Otter Tail Power Company did not conduct any further review of flue-gas recirculation. However, this reasoning does not justify that flue-gas89 recirculation is not a feasible technology to cons ider. Therefore, DENR will consider the fluegas recirculation as a feas ible control technology.

Catalytic absorption/oxidation such as SCONOx or EMx systems is a nitrogen oxide control technology that utilizes a propr ietary catalytic oxidation a nd absorption technology which oxidizes nitrogen oxide (NO) a nd carbon monoxide (CO) to nitrog en dioxide (NO2) and carbon dioxide (CO2), respectively. Th e nitrogen dioxide is then abso rbed onto an absorption media

while carbon dioxide is released to the atmosphere. Once the absorption media becomes saturated, the nitrogen dioxide is desorbed and treated by a proprietary catalyst. The SCONOx system is being considered as a cross over tec hnology to coal-fired boilers , but to date has only been applied to “clean flue gas” systems such as natural-gas fired combustions turbines. The catalytic absorption/oxidation system requires a high operating temperature and low particulate loading. Therefore, the system w ould have to be installed after th e particulate control device and require a flue gas reheater. DENR was unable to find a coal-fired system that was using a catalytic absorption/oxidation system or find that this system was being marketed commercially

for coal fired boilers. As noted in 40 CFR Part 51, Appendix Y, a control technology needs to be commercially available to be considered tec hnically feasible. As such the catalytic absorption/oxidation system is not considered a technically feasible option for Otter Tail Power Company.

Gas reburning is a nitrogen oxide control t echnology that uses a second combustion zone following the primary combustion zone in the boiler. In a cyclone boiler, such as the one being operated at Otter Tail Power Company’s Big Stone I facility, burning th e coal produces molten slag along the cyclone barrels. The molten slag catches subsequent coal until the combustion is complete. Generally, cyclone burners operate n ear the slag-tapping limits . Therefore, using natural gas or another fuel source as the reburn fuel may inhibit the molten slag formation. In addition, by trying to lower the air to fuel ratio more than achiev ed by the existing over-fire air systems may cause slag “freezing” at low load levels. As such gas reburn is not considered a technically feasible option for Otter Tail Power Company.

Oxygen enhanced combustion is a nitrogen oxide combustion control technology that reduces the formation of thermal nitrogen oxi des in the boiler. Developed by Praxair Technology Inc., this method uses oxygen in the burner instead of air to achieve additional nitrogen oxide reductions. To date, the largest demonstration of this t echnology is a 30 megawatt pilot demonstration at Babcock and Wilcock’s Clean Environmental Developm ent facility in Alliance, Ohio. As noted

on Babcock and Wilcock’s website - http://www.babcock.com/ , the project was a pilot test of the technology and the next step is to demonstrate the t echnology at a commercial scale. As noted in 40 CFR Part 51, Appendix Y, a control technology needs to be commercially available to be considered technically feasible. As such the oxygen enhanced combustion is not considered a technically feasible option for Otter Tail Power Company.

Emerging control technologies su ch as Enviroscrub, Electro catal ytic oxidation, and the Airborne process have not been commercially available and have not been demonstrated for long-term levels of performance. As noted in 40 CFR Part 51, Appendix Y, a control technology needs to be commercially available to be considered technically feasible. As such these emerging technologies are not considered technically feasible options for Otter Tail Power Company.90 DENR determined that the following nitrogen oxi de control technologies were feasible for Otter Tail Power Company:

1. Over-fire air (OFA);

2. Separated over-fire air (SOFA);

3. Selective non-catalyt ic reduction (SNCR);

4. Rich reagent injection (RRI);

5. Selective catalytic reduction (SCR) ; and

6. Flue-gas recirculation.

6.3.3.3 Nitrogen Oxide Control Effectiveness

Step 3 requires the evaluation of control e ffectiveness for each control technology. DENR

evaluated the control effec tiveness by comparing the effectiveness in Table 6.9.

Table 6-9 – Comparison of Control Eff ectiveness for Nitrogen Oxide Controls

Emission Rate Control Efficiency

Otter Tail 1 RBLC 3 Basin 4 EPA 5 IEA 6

Rank Control (lbs/MMBtus) 2 (lbs/MMBtus) 2 (lbs/MMBtus) 2 (%) (%)

#1 SCR and

SOFA 7 0.10 0.05 to 0.1 0.05 35 to 90 80 to 90

#2 RRI, SNCR

and SOFA 8 0.20 0.07 to 0.15 0.10 35 to 90 30 to 50

#3 SNCR and

SOFA 9 0.35 0.07 to 0.15 0.10 35 to 90 30 to 50

#4 Separated

over-fire air 0.50 Not Identified Not Identified 30 to 70 Not

Identified

#5 Over-fire air 0.65 Not Identified Not Identified 30 to 70 Not

Identified

#6 Flue Gas

Recirculation Not Identified Not Identified Not Identified 30 to 70 Not

Identified

1 – The identified emission rates were identified in Otter Tail Power Company’s BART analysis;

2 – “lbs/MMBtus” means pounds per million British thermal units;

3 – The identified emission rates were obtained from EPA’s Reasonable Achievable Control Technology, Best Available Control Technol ogy, and Lowest Achievable Emission Rate Clearinghouse (RBLC) considering data for permits issued after calendar year 2000;

4 – The emission rates are based on the BACT analysis provided by Basin Electric Power Cooperative’s proposed NextGen project in South Dakota which is for a new pulverized-fired boiler equipped with a low-NOx burner combustion technolog y. The emission rates were primarily based on if the system used selective catalytic re duction or selective non-catalytic reduction;

5 – The emission rates are from page 27 of the EPA’s Technical Bulletin – “Nitrogen Oxides; Why and How they are Controlled”

. 6 – The emission rates were obtained from the IEA Clean Coal Centre’s Webpage - http://www.ieacoal.org.uk/site/ieacoal/home . The emission rates were primarily based on if the system used selective catalytic reduction or selective non-catalytic reduction.91 7 – SCR and SOFA refers to selective cata lytic reduction and separated over-fire air;

8 – RRI, SNCR, and SOFA refers to rich reagen t injection, selective non-catalytic reduction and separated over-fire air, respectively; and

9 – SNCR and SOFA refers to selective non-catal ytic reduction and separated over-fire air.

6.3.3.4 Nitrogen Oxide Control Technology Impacts

Step 4 requires DENR to look at impacts associated with the control alternativ es such as cost of compliance, energy impacts, non-air quality enviro nmental impacts, and th e remaining useful life of the project. These impacts are intended to provide rational in choosing between the alternative control options when determining what is considered BART.

Otter Tail Power Company identified cost estim ates for five contro l options. Table 6-10 summarizes Otter Tail Power Company’s estimated costs.

In 40 CFR Part 51, Appendix Y – Guidelines for BART Determination Under the Regional Haze Rule, in the section titled “How should I determine visibility impacts in the BART

determination” it notes that the model should use the 24-hour average actual emission rate from the highest emitting day of the meteorological period modeled (for the pre-control scenario). The 18,000 tons per year of nitrogen oxide is based on the highest average 24-hour average emission rate (4,855 pounds per hour) fo r calendar years 2001 through 2003 and operating 85% of the time or 7,746 hours per year. Based on the BART guidelines, the baseline emissions are 18,000

tons per year.92 Table 6-10 – Comparison of Control Effe ctiveness for Nitrogen Oxide Controls

Control Option Capital Cost O&M 1 Annual Cost 2 Reduction 3 Cost

Effectiveness 4

SCR and

SOFA 5 $81,800,000 $4,110,000 $13,210,000 16,000 $825

RRI, SNCR

and SOFA 6 $16,200,000 $7,260,000 $11,390,000 13,910 $818

SNCR and

SOFA 7 $11,900,000 $2,120,000 $3,990,000 10,780 $197

SOFA 8 $4,800,000 $152,000 $650,000 7,640 $85

Over-fired air $0 $106,000 $140,000 4,510 $31

1 – O&M represents the operational and maintenance cost estimate for the control alternative;

2 – Annual cost is the annualized costs for each c ontrol alternative taking into account both the capital and operational and maintenance costs;

3 – Reduction represents the amount of nitrogen ox ide reduced in tons per year annual from the baseline level of 18,000 tons of nitrogen oxide per year;

4 – Cost Effectiveness represents the annualized co st divided by the identified emission reductions (dollar per ton);

5 – SCR and SOFA refers to selective cata lytic reduction and separated over-fire air;

6 – RRI, SNCR, and SOFA refer to rich reagen t injection, selective non-catalytic reduction and separated over-fire air;

7 – SNCR and SOFA refers to selective non-cataly tic reduction and separated over-fire air; and

8 – SOFA refers to separated over-fire air.

Otter Tail Power Company did not identify a co st effectiveness on a dollar per visibility

reduction. DENR considered this cost e ffectiveness in Step 5 of the analysis.

Otter Tail Power Company identified the energy im pacts cost associated for each of the control options. Table 6-11 summarizes Otter Tail Power Company’s es timated energy impacts.

Table 6-11 – Estimated Energy Impacts for Nitrogen Oxide Controls

Control Energy Demand Percent of Generation Selective catalytic reduction and Separated over-fire air 400 to 1,000 kilowatts Less than 0.2 percent

Rich reagent injection, Selective non-catalytic reduction and Separated over-fire air 150 to 400 kilowatts Less than 0.1 percent

Selective non-catalytic reduction and Separated over-fire air 150 to 400 kilowatts Less than 0.1 percent

Separated over-fire air 1 kilowatt Negligible

Over-fire air 1 kilowatt Negligible

The over-fire air and the separate d over-fire air will increase the amount of unburned carbon in the flyash, which will increase the amount of flyash that needs to be properly disposed. Otter Tail Power Company considers this increase neglig ible compared to the existing amount flyash being properly disposed.93 The selective non-catalytic reduction and the sele ctive catalytic reduction will generate a small

amount of unreacted ammonia or urea to be emitted. Even though ammonia and urea are not considered regulated air pollutants, these emissi ons are involved in the formation of ammonium sulfates and ammonium nitrates, which contribute to the amount of visibility impairment.

In conducting its cost analysis, Otter Tail Powe r Company used 30 years as the life expectancy averaging period for the control alternatives. Since the useful life of Otter Tail Power Company’s Big Stone I facility is expected to be longer than 30 years, there is no difference between the control options base d on useful life.

6.3.4 Visibility Impact Evaluations

In accordance with 40 CFR Part 51, Appendix Y, a s ource that has an impact equal to or greater

than 1.0 deciviews is considered to “cause” a visibility impairment and that establishing a

threshold for what is considered to “contribute” to a visibility impairment should not be any higher than 0.5 deciviews. DENR is proposing to define “contribut e” to visibility impairment as a change in visibility impairment in a mandatory Class I federal area of 0.5 deciviews or more, based on a 24-hour average, above the average na tural visibility baseline. A source exceeds the

threshold when the 98 th percentile (eighth highest value) of the modeling results, based on one year of the three years of meteorological data modeled, exceeds the 0.5 deciviews.

Otter Tail Power Company modeled its existing ope rations impact on seven Class I areas that are located in Michigan, Minnesota, North Dakota, and South Dakota. Table 6-12 identifies the potential impact based on the 98 th percentile for the existing Bi g Stone I facility has while emitting approximately 18,000 tons of sulfur dioxide, 18,000 tons of nitrogen oxides, and 300 tons of particulate matter per year.

Table 6-12 – Potential Impact of Existing Big Stone I (98 th Percentile)

Class I Area 2002 1,2 2006 1,2 2007 1,2

Boundary Waters 0.574 (0.6) 0.790 (0.8) 1.079 (1.1) Voyageurs 0.623 (0.6) 0.574 (0.6) 0.724 (0.7)

Wind Cave 0.305 (0.3) 0.120 (0.1) 0.325 (0.3)

Theodore Roosevelt 0.215 (0.2) 0.459 (0.5) 0.322 (0.3)

Lostwood 0.232 (0.2) 0.385 (0.4) 0.409 (0.4)

Badlands 0.452 (0.5) 0.481 (0.5) 0.471 (0.5) Isle Royale 0.629 (0.6) 0.506 (0.5) 0.665 (0.7)

1 – The modeling was conducted using the meteor ological data for calendar years 2002, 2006, and 2007; and

2 – The results are represented in deciviews. Otter Tail Power Company identified the deciview valued identified in the model to three decimal pl aces which is consistent with how WRAP reported the visibility impacts in Table 6-3. The value in parentheses represen ts the value that is used to compare to the proposed contribution threshold of 0.5.

Based on the modeling results, Otte r Tail Power Company’s Big Stone I facility contributes to visibility impairment at Boundary Waters, Voya geurs, Theodore Roosevelt, Badlands, and Isle Royale because they have a deciview impact of 0.5 or greater.94 Otter Tail Power Company conducted visibility modeling for 10 different control option

scenarios and each scenario for three calendar years worth of meteorological data. The 10 different control option scenarios simultaneously considered the emissions of nitrogen oxide, sulfur dioxide, and particulate matter. Table 6- 13 identifies the emission rates used in the modeling for each different control option.

Table 6-13 – Emission Rates for Each Control Option Option Control Equipment SO2 11 NOx 12 PM10 13

#1 OFA and Dry FGD #1 1 841.4 3645.9 84.1

#2 OFA and Wet FGD #1 2 841.4 3645.9 84.1

#3 OFA and Dry FGD #2 3 504.8 3645.9 84.1

#4 OFA and Wet FGD #2 4 241.2 3645.9 84.1

#5 SOFA and Dry FGD #1 5 841.4 2804.5 84.1

#5a SOFA and Dry FGD #2 6 504.8 2804.5 84.1

#5b SOFA and Wet FGD #2 7 241.2 2804.5 84.1

#6 SNCR, SOFA, and Dry FGD #1 8 841.4 1963.2 84.1

#7 RRI, SNCR, SOFA, and Dry FGD #1 9 841.4 1121.8 84.1

#8 SCR, SOFA, and Dry FGD #1 10 841.4 560.9 84.1

1 – OFA and Dry FGD #1 refers to over-fire air and se mi-dry flue gas desulfurization system meeting an emission rate of 0.15 pounds per million British thermal units;

2 – OFA and Wet FGD #1 refers to over-fire air and wet flue gas desulfurization system meeting an emission rate of 0.15 pounds per million British thermal units;

3 – OFA and Dry FGD #2 refers to over-fire air and se mi-dry flue gas desulfurization system meeting an emission rate of 0.09 pounds per million British thermal units;

4 – OFA and Wet FGD #2 refers to over-fire air and wet flue gas desulfurization system meeting an emission rate of 0.043 pounds per million British thermal units;

5 – SOFA and Dry FGD #1 refers to separated ove r-fire air and semi-dry flue gas desulfurization system meeting an emission rate of 0. 15 pounds per million British thermal units;

6 – SOFA and Dry FGD #2 refers to separated ove r-fire air and semi-dry flue gas desulfurization system meeting an emission rate of 0. 09 pounds per million British thermal units;

7 – SOFA and Wet FGD #2 refers to separated over-fi re air and wet flue gas desulfurization system meeting an emission rate of 0.043 po unds per million British thermal units;

8 – SNCR, SOFA, and Dry FGD #1 refers to selectiv e non-catalytic reduction, separated over-fire air, and semi-dry flue gas desulfurization system m eeting an emission rate of 0.15 pounds per million British thermal units;

9 – RRI, SNCR, SOFA, and Dry FGD #1 refers to rich reagent injection, selective non-catalytic reduction, separated over-fire air, and semi-dry flue gas desulfurization system meeting an emission rate of 0.15 pounds per mil lion British thermal units;

10 – SCR, SOFA, and Dry FGD #1 refers to selective catalytic reduction, separated over-fire air, and semi-dry flue gas desulfurization system meeting an emission rate of 0.15 pounds per million British thermal units;

11 – SO2 represents the sulfur dioxid e emission rate in pounds per hour;

12 – NOx represents the nitrogen oxide emission rate in pounds per hour; and

13 – PM10 represents the particulate matter less than 10 microns emission rate in pounds per hour.

Table 6-14 provides the resu lts of the modeling (98 th percentile) using th e different control options and emissions rates in Table 6-13. Ag ain, Otter Tail Power Company identified the95 deciview valued identified in the model to three decimal places which is consistent with how WRAP reported the visibility impacts in Table 6-3. The value in parentheses represents the value that DENR used to compare to th e proposed contribution threshold of 0.5.

Table 6-14 – Modeling Results for Each Control Option (98 th Percentile – Deciviews) Option Control Equipment Class I Area 2002 2006 2007

#1 OFA and Dry FGD #1 1 Boundary Waters 0.330 (0.3) 0.548 (0.5) 0.657 (0.7) Voyageurs 0.329 (0.3) 0.399 (0.4) 0.460 (0.5) Isle Royale 0.377 (0.4) 0.296 (0.3) 0.339 (0.3) Badlands 0.223 (0.2) 0.176 (0.2) 0.241 (0.2) Theodore Roosevelt 0.092 (0.1) 0.247 (0.2) 0.190 (0.2)

#2 OFA and Wet FGD #1 2 Boundary Waters 0.360 (0.4) 0.546 (0.5) 0.667 (0.7) Voyageurs 0.349 (0.3) 0.494 (0.5) 0.521 (0.5) Isle Royale 0.367 (0.4) 0.273 (0.3) 0.323 (0.3) Badlands 0.234 (0.2) 0.199 (0.2) 0.254 (0.3) Theodore Roosevelt 0.099 (0.1) 0.244 (0.2) 0.161 (0.2)

#3 OFA and Dry FGD #2 3 Boundary Waters 0.319 (0.3) 0.534 (0.5) 0.620 (0.6) Voyageurs 0.307 (0.3) 0.391 (0.4) 0.450 (0.5) Isle Royale 0.363 (0.4) 0.287 (0.3) 0.323 (0.3) Badlands 0.219 (0.2) 0.172 (0.2) 0.230 (0.2) Theodore Roosevelt 0.087 (0.1) 0.234 (0.2) 0.173 (0.2)

#4 OFA and Wet FGD #2 4 Boundary Waters 0.350 (0.4) 0.521 (0.5) 0.611 (0.6) Voyageurs 0.312 (0.3) 0.464 (0.5) 0.502 (0.5) Isle Royale 0.351 (0.4) 0.250 (0.3) 0.290 (0.3) Badlands 0.225 (0.2) 0.191 (0.2) 0.234 (0.2) Theodore Roosevelt 0.084 (0.1) 0.230 (0.2) 0.138 (0.1)

#5 SOFA and Dry FGD #1 5 Boundary Waters 0.264 (0.3) 0.433 (0.4) 0.524 (0.5) Voyageurs 0.263 (0.3) 0.314 (0.3) 0.364 (0.4) Isle Royale 0.298 (0.3) 0.235 (0.2) 0.272 (0.3) Badlands 0.169 (0.2) 0.137 (0.1) 0.191 (0.2) Theodore Roosevelt 0.076 (0.1) 0.199 (0.2) 0.156 (0.2)

#5a SOFA and Dry FGD #2 6 Boundary Waters 0.250 (0.3) 0.419 (0.4) 0.493 (0.5) Voyageurs 0.249 (0.2) 0.306 (0.3) 0.354 (0.4) Isle Royale 0.285 (0.3) 0.226 (0.2) 0.256 (0.3) Badlands 0.165 (0.2) 0.133 (0.1) 0.180 (0.2) Theodore Roosevelt 0.069 (0.1) 0.186 (0.2) 0.141 (0.1)

#5b SOFA and Wet FGD #2 7 Boundary Waters 0.274 (0.3 0.407 (0.4) 0.478 (0.5) Voyageurs 0.244 (0.2) 0.365 (0.4) 0.393 (0.4) Isle Royale 0.274 (0.3) 0.195 (0.2) 0.227 (0.2) Badlands 0.174 (0.2) 0.147 (0.1) 0.182 (0.2) Theodore Roosevelt 0.066 (0.1) 0.180 (0.2) 0.108 (0.1) #6 SNCR, SOFA, Boundary Waters 0.200 (0.2) 0.318 (0.3) 0.388 (0.4)

and Dry FGD #1 8 Voyageurs 0.196 (0.2) 0.228 (0.2) 0.267 (0.3) Isle Royale 0.221 (0.2) 0.174 (0.2) 0.199 (0.2) Badlands 0.120 (0.1) 0.098 (0.1) 0.143 (0.1)96 Option Control Equipment Class I Area 2002 2006 2007 Theodore Roosevelt 0.063 (0.1) 0.150 (0.2) 0.121 (0.1) #7 RRI, SNCR, SOFA, Boundary Wat ers 0.137 (0.1) 0.202 (0.2) 0.256 (0.3)

and Dry FGD #1 9 Voyageurs 0.130 (0.1) 0.157 (0.2) 0.176 (0.2) Isle Royale 0.142 (0.1) 0.115 (0.1) 0.134 (0.1) Badlands 0.090 (0.1) 0.066 (0.1) 0.099 (0.1) Theodore Roosevelt 0.050 (0.1) 0.101 (0.1) 0.080 (0.1) #8 SCR, SOFA, Boundary Waters 0.097 (0.1) 0.136 (0.1) 0.170 (0.2)

and Dry FGD #1 10 Voyageurs 0.086 (0.1) 0.107 (0.1) 0.123 (0.1) Isle Royale 0.092 (0.1) 0.077 (0.1) 0.098 (0.1) Badlands 0.079 (0.1) 0.060 (0.1) 0.070 (0.1) Theodore Roosevelt 0.036 (0.0) 0.070 (0.1) 0.064 (0.1)

1 – OFA and Dry FGD #1 refers to over-fire air and se mi-dry flue gas desulfurization system meeting an emission rate of 0.15 pounds per million British thermal units;

2 - OFA and Wet FGD #1 refers to over-fire air and we t flue gas desulfurization system meeting an emission rate of 0.15 pounds per million British thermal units;

3 - OFA and Dry FGD #2 refers to over-fire air and se mi-dry flue gas desulfurization system meeting an emission rate of 0.09 pounds per million British thermal units;

4 - OFA and Wet FGD #2 refers to over-fire air and wet flue gas desulfurization system meeting an emission rate of 0.043 pounds per million British thermal units;

5 – SOFA and Dry FGD #1 refers to separated ove r-fire air and semi-dry flue gas desulfurization system meeting an emission rate of 0. 15 pounds per million British thermal units;

6 – SOFA and Dry FGD #2 refers to separated ove r-fire air and semi-dry flue gas desulfurization system meeting an emission rate of 0. 09 pounds per million British thermal units;

7 – SOFA and Wet FGD #2 refers to separated over-fi re air and wet flue gas desulfurization system meeting an emission rate of 0.043 po unds per million British thermal units;

8 – SNCR, SOFA, and Dry FGD #1 refers to selectiv e non-catalytic reduction, separated over-fire air, and semi-dry flue gas desulfurization system m eeting an emission rate of 0.15 pounds per million British thermal units;

9 - RRI, SNCR, SOFA, and Dry FGD #1 refers to rich reagent injection, selective non-catalytic reduction, separated over-fire air, and semi-dry flue gas desulfurization system meeting an emission rate of 0.15 pounds per mil lion British thermal units; and

10 - SCR, SOFA, and Dry FGD #1 refers to selective catalytic reduction, separated over-fire air, and semi-dry flue gas desulfurization system meeting an emission rate of 0.15 pounds per million British

thermal units.

Based on the modeling results in Table 6-14, Ot ter Tail Power Company would have to use Option #6, #7, or #8 to not reasonably contribut e to visibility impairment in the Boundary Waters, Voyageurs, Isle Royale, Badla nds, and Theodore Roosevelt National Parks.

Otter Tail Power Company did not provide a co st per deciview reduction for each of the proposed control options. DENR calculated a cost per deciview reduction by summing the

annualized cost of each of the control alternat ives associated with the control options and dividing by the visibility reducti on identified by the modeling from the baseline condition. Table 6-15 provides a cost per deciview comparison.97 Table 6-15 – Cost per Deciview Comparison ($/deciview)

Option Control Equipment Class I Area 2002 2006 2007

#1 OFA and Boundary Waters $ 96,188,525 $ 96,983,471 $ 55,616,114 Dry FGD #1 1 Voyageurs $ 79,829,932 $ 134,114,286 $ 88,901,515 Isle Royale $ 93,134,921 $ 111,761,905 $ 71,993,865 Badlands $ 102,489,083 $ 79,950,820 $ 102,043,478 Theodore Roosevelt $ 190,813,008 $ 110,707,547 $ 177,803,030
Cumulative $ 15,998,637 $ 16,108,442 $ 13,542,989

#2 OFA and Boundary Waters $ 135,700,935 $ 119,016,393 $ 70,485,437

Wet FGD #1 2 Voyageurs $ 105,985,401 $ 363,000,000 $ 143,054,187 Isle Royale $ 110,839,695 $ 124,635,193 $ 84,912,281 Badlands $ 133,211,009 $ 102,978,723 $ 133,824,885 Theodore Roosevelt $ 250,344,828 $ 135,069,767 $ 180,372,671
Cumulative $ 20,625,000 $ 21,337,252 $ 17,224,199

#3 OFA and Boundary Waters $ 92,980,392 $ 92,617,188 $ 51,655,773 Dry FGD #2 3 Voyageurs $ 75,031,646 $ 129,562,842 $ 86,532,847 Isle Royale $ 89,135,338 $ 108,264,840 $ 69,327,485 Badlands $ 101,759,657 $ 76,731,392 $ 159,127,517 Theodore Roosevelt $ 185,234,375 $ 105,377,778 $ 98,381,743

Cumulative $ 15,466,406 $ 15,588,429 $ 12,795,467

#4 OFA and Boundary Waters $ 130,312,500 $ 108,513,011 $ 62,371,795

Wet FGD #2 4 Voyageurs $ 93,858,521 $ 265,363,636 $ 131,486,486 Isle Royale $ 105,000,000 $ 114,023,438 $ 77,840,000 Badlands $ 128,590,308 $ 100,655,172 $ 123,164,557 Theodore Roosevelt $ 222,824,427 $ 127,467,249 $ 158,641,304
Cumulative $ 19,140,984 $ 19,590,604 $ 15,617,978

#5 SOFA and Boundary Waters $ 77,354,839 $ 67,170,868 $ 43,207,207 Dry FGD #1 5 Voyageurs $ 66,611,111 $ 92,230,769 $ 66,611,111 Isle Royale $ 72,447,130 $ 88,487,085 $ 61,017,812 Badlands $ 84,734,392 $ 69,709,302 $ 85,642,857 Theodore Roosevelt $ 172,517,986 $ 92,230,769 $ 144,457,831
Cumulative $ 13,411,633 $ 13,018,458 $ 11,045,601

#5a SOFA and Boundary Waters $ 74,753,086 $ 65,283,019 $ 41,331,058 Dry FGD #2 6 Voyageurs $ 64,759,358 $ 90,373,134 $ 65,459,459 Isle Royale $ 70,406,977 $ 86,500,000 $ 59,217,604 Badlands $ 84,390,244 $ 69,597,701 $ 83,230,241 Theodore Roosevelt $ 165,890,411 $ 88,717,949 $ 133,812,155
Cumulative $ 13,070,696 $ 12,727,273 $ 10,544,188

#5b SOFA and Boundary Waters $ 99,000,000 $ 77,545,692 $ 49,417,637

Wet FGD #2 7 Voyageurs $ 78,364,116 $ 142,105,263 $ 89,728,097 Isle Royale $ 83,661,972 $ 95,498,392 $ 67,808,219 Badlands $ 106,834,532 $ 88,922,156 $ 102,768,166 Theodore Roosevelt $ 199,328,589 $ 106,451,613 $ 138,785,04798 Option Control Equipment Class I Area 2002 2006 2007 Cumulative $ 16,019,417 $ 15,730,932 $ 12,724,936

#6 SNCR, SOFA, Boundary Waters $ 73,048,128 $ 57,881,356 $ 39,536,903 and Voyageurs $ 63,981,265 $ 78,959,538 $ 59,781,182 Dry FGD #1 8 Isle Royale $ 66,960,784 $ 82,289,157 $ 58,626,609 Badlands $ 82,289,157 $ 71,331,593 $ 83,292,683 Theodore Roosevelt $ 179,736,842 $ 88,414,239 $ 135,920,398
Cumulative $ 13,115,699 $ 12,262,118 $ 10,368,121

#7 RRI, SNCR, Boundary Waters $ 79,450,801 $ 59,047,619 $ 42,187,120 SOFA, and Voyageurs $ 70,425,963 $ 83,261,391 $ 63,357,664 Dry FGD #1 9 Isle Royale $ 71,293,634 $ 88,797,954 $ 65,386,064 Badlands $ 95,911,602 $ 83,662,651 $ 93,333,333 Theodore Roosevelt $ 210,424,242 $ 96,983,240 $ 143,471,074
Cumulative $ 14,711,864 $ 13,467,804 $ 11,280,052

#8 SCR, SOFA, Boundary Waters $ 76,603,774 $ 55,871,560 $ 40,198,020 and Voyageurs $ 68,044,693 $ 78,244,111 $ 60,798,669 Dry FGD #1 10 Isle Royale $ 68,044,693 $ 85,174,825 $ 64,444,444 Badlands $ 97,962,466 $ 86,793,349 $ 91,122,195 Theodore Roosevelt $ 204,134,078 $ 93,933,162 $ 141,627,907
Cumulative $ 14,329,412 $ 13,101,470 $ 10,900,955

1 – OFA and Dry FGD #1 refers to over-fire air and se mi-dry flue gas desulfurization system meeting an emission rate of 0.15 pounds per million British thermal units;

2 - OFA and Wet FGD #1 refers to over-fire air and we t flue gas desulfurization system meeting an emission rate of 0.15 pounds per million British thermal units;

3 - OFA and Dry FGD #2 refers to over-fire air and se mi-dry flue gas desulfurization system meeting an emission rate of 0.09 pounds per million British thermal units;

4 - OFA and Wet FGD #2 refers to over-fire air and wet flue gas desulfurization system meeting an emission rate of 0.043 pounds per million British thermal units;

5 – SOFA and Dry FGD #1 refers to separated ove r-fire air and semi-dry flue gas desulfurization system meeting an emission rate of 0. 15 pounds per million British thermal units;

6 – SOFA and Dry FGD #2 refers to separated ove r-fire air and semi-dry flue gas desulfurization system meeting an emission rate of 0. 09 pounds per million British thermal units;

7 – SOFA and Wet FGD #2 refers to separated over-fi re air and wet flue gas desulfurization system meeting an emission rate of 0.043 po unds per million British thermal units;

8 – SNCR, SOFA, and Dry FGD #1 refers to selectiv e non-catalytic reduction, separated over-fire air, and semi-dry flue gas desulfurization system m eeting an emission rate of 0.15 pounds per million British thermal units;

9 - RRI, SNCR, SOFA, and Dry FGD #1 refers to rich reagent injection, selective non-catalytic reduction, separated over-fire air, and semi-dry flue gas desulfurization system meeting an emission rate of 0.15 pounds per mil lion British thermal units; and

10 - SCR, SOFA, and Dry FGD #1 refers to selective catalytic reduction, separated over-fire air, and semi-dry flue gas desulfurization system meeting an emission rate of 0.15 pounds per million British

thermal units.99 Based on the cost per deciview re duction numbers in Table 6-15, the most cost effective controls options are #5A, #6 and #8. The cost effective c ontrol costs are generally within 10 percent of

each other.

6.3.5 BART Emissions Limits for Big Stone I

EPA identifies in 40 CFR Part 51, Appendix Y that in determining the “bes t” available retrofit technology, the state has discretion to determine the order in which the state should evaluate control options for BART. The state should pr ovide a justification fo r adopting the technology

that is selected as the ‘‘best’ ’ level of control, including an explanation of the Clean Air Act

factors that led the state to choose that option over other control levels.

To complete the BART process, the state should establish enforceable emission limits that reflect the BART requirements and require compliance with in a given period of time. In particular, the

state should establish an enforceable emission li mit for each subject emission unit at the source and for each pollutant subject to review that is emitted from the source. In addition, the state should require compliance with th e BART emission limitations no late r than five years after EPA approves South Dakota’s State Implementation Pl an for regional haze. If technological or economic limitations in the application of a m easurement methodology to a particular emission

unit make a conventional emissions limit infeas ible, the state may instead prescribe a design, equipment, work practice, operation standard, or combination of these types of standards.

6.3.5.1 Particulate Matter BART Recommendation

Otter Tail Power Company alrea dy installed and is operating a baghouse, which is the top particulate control technology. Therefore, there is no addi tional compliance cost, energy impacts, etc. that Otter Tail Power Company woul d have to endure. As such, DENR considers the continual use of the baghouse as BART for particulate matter.

Otter Tail Power Company proposes an emission limit of 84.1 pounds per hour which they based on an emission rate of 0.015 pounds per million Btu and a maximum fuel heat input of 5,609 million Btus per hour. Otter Tail Power Company proposes to comply with the pounds per hour limit using a 30-day rolling average. Each day, Otter Tail Power Company will multiply the emission rate, in pounds per million Btus as dete rmined by the most recent annual performance test, by the heat input to the bo iler, as determined by a continuous emission monitoring system, and dividing by the number of hours the boiler operated that day.

In the December 11, 2006, application, Otter Ta il Power Company proposed to replace the advanced hybrid particulate colle ctor control system with the current day baghouse. In that application, Otter Tail Power Company noted that the baghouse would have a maximum filterable particulate matter emission rate of 0.012 pounds per million Btu of fuel heat input. The emission rate equates to 67.3 pounds per hour at 5,609 million Btus per hour heat input In May 2009, Otter Tail Power Company conducted a performan ce test on the baghouse. The test results noted an average filterable particulate matter emission rate of 0.011 pounds per million Btus and 57.6 pounds per hour.100 DENR considers the emission limit represen ting BART as 67.3 pounds per hour. The hourly emission limit includes periods of startup and shutdown. DENR is also establishing a BART emission limit of 0.012 pounds per million Btus , which includes periods of startup and shutdown. Compliance with both emission limits sh all be based on an annual stack performance test using the average of three 1-hour test runs.

6.3.5.2 Sulfur Dioxide BART Recommendation

Otter Tail Power Company is proposing the sec ond ranked control option (semi-dry flue gas desulfurization system) to cont rol sulfur dioxide emissions. Since control options #6, #7, and #8, which were the only three options that reduced th e visibility less than the contribution level of 0.5 deciviews, did not include the top ranked sulfur dioxide control alternative an analysis of the visibility impacts of the other control alternatives was consid ered. Even though the top ranked control option (wet flue gas desu lfurization system) reduces the sulfur dioxide emissions more than the second ranked control opti on, neither of the two control op tions is considered a better control option when considering th e visibility impacts. For example, Table 6-16 displays the comparison of the visibility impacts for contro l option #3 to control op tion #4 and control option #5a to control option #5b. These options were chosen because the emission rates for nitrogen oxide and particulate matter were constant, while the sulfur dioxide emissions varied as noted by

the two different contro l alternatives.

Table 6-16 – Visibility Comparison between Wet and Dry Scrubbers Control Option Class I Area 2002 2006 2007

#3 OFA and Dry FGD #2 1 Boundary Waters 0.319 0.534 0.620 Voyageurs 0.307 0.391 0.450 Isle Royale 0.363 0.287 0.323

Badlands 0.219 0.172 0.230

Theodore Roosevelt 0.087 0.234 0.173

#4 OFA and Wet FGD #2 2 Boundary Waters 0.350 0.521 0.611 Voyageurs 0.312 0.464 0.502 Isle Royale 0.351 0.250 0.290

Badlands 0.225 0.191 0.234

Theodore Roosevelt 0.084 0.230 0.138 Comparison Review Boundary Waters ↑ ↓ ↓ Voyageurs ↑ ↑ ↑ Isle Royale ↓ ↓ ↓

Badlands ↑ ↑ ↑

Theodore Roosevelt ↓ ↓ ↓

#5a SOFA and Dry FGD #2 3 Boundary Waters 0.250 0.419 0.493 Voyageurs 0.249 0.306 0.354 Isle Royale 0.285 0.226 0.256

Badlands 0.165 0.133 0.180

Theodore Roosevelt 0.069 0.186 0.141

#5b SOFA and Wet FGD #2 4 Boundary Waters 0.274 0.407 0.478 Voyageurs 0.244 0.365 0.393101 Control Option Class I Area 2002 2006 2007 Isle Royale 0.274 0.195 0.227

Badlands 0.174 0.147 0.182

Theodore Roosevelt 0.066 0.180 0.108 Comparison Review Boundary Waters ↑ ↓ ↓ Voyageurs ↓ ↑ ↑ Isle Royale ↓ ↓ ↓

Badlands ↑ ↑ ↑

Theodore Roosevelt ↓ ↓ ↓

1 - OFA and Dry FGD #2 refers to over-fire air and se mi-dry flue gas desulfurization system meeting an emission rate of 0.09 pounds per million British thermal units;

2 - OFA and Wet FGD #2 refers to over-fire air and wet flue gas desulfurization system meeting an emission rate of 0.043 pounds per million British thermal units;

3 – SOFA and Dry FGD #2 refers to separated ove r-fire air and semi-dry flue gas desulfurization system meeting an emission rate of 0.09 pounds per million Britis h thermal units; and

4 – SOFA and Wet FGD #2 refers to separated over-fi re air and wet flue gas desulfurization system meeting an emission rate of 0.043 po unds per million British thermal units.

As noted in the table, approximately 40 percen t of the modeling, the top ranked control option generated a higher visibility impact than the second ranked control option. Whereas, approximately 60 percent of th e modeling, the second ranked cont rol option generated a higher visibility impact than the top ranked control opt ion. Therefore, based on the visibility modeling

there is no discernable difference between these two control options. As such, DENR considers that the semi-dry flue gas desulfurizati on system is considered BART.

Otter Tail Power Company proposes an emission limit of 505 pounds per hour based upon a 30- day rolling average, which is based on the em ission rate of 0.09 pounds per million Btu of fuel heat input at 5,609 million Btus per hour heat input.

The presumptive emission limit established by EPA for scrubber systems is 0.15 pounds per million Btus of fuel heat input. The limit proposed by Otter Tail Power Company is more stringent than the presumptive limit identified by EPA. DENR considers the emission limit representing BART should be 505 pounds pe r hour and 0.09 pounds per million Btus, which would include periods of startup, shutdown a nd malfunction. Compliance with these emission

limits shall be based on the c ontinuous emission monitoring system and on a 30-day rolling

average.

6.3.5.3 Nitrogen Oxide BART Recommendation

Otter Tail Power Company is propo sing the fourth ranked control op tion (separated over-fire air) to control nitrogen oxide emissions. In review ing the higher ranked control options, each option reduces the amount of nitrogen oxide emissions a nd the visibility impacts more than the fourth ranked control option (separated over-fire air). However, each of these higher ranking control options comes with a higher financial cost.102 In establishing the nitrogen oxide presumptiv e BART requirements, EPA identified that $1,500 per ton of nitrogen oxide removed was considered cost effective. (Federal Register Volume 70 Number 128 on pages 39134 and 39135). EPA considers this threshold cost effective for a coal fired unit greater than 200 megawa tts existing at a facility with a combined capacity greater than 750 megawatts.

Otter Tail Power Company’s Big Stone I facil ity does not have a cap acity greater than 750 megawatts and is not applicable to the es tablished nitrogen oxide presumptive BART requirements. However, Otter Tail Power Compa ny’s Big Stone I’s coal fired unit is greater than the 200 megawatt. As noted in Table 6-10, the cost of the control options on a $ per ton basis are all less than $9 00 per ton. As such DENR considers all the identified co ntrol options as cost effective on a $ per ton basis.

As noted in Table 6-15, the cost on a $ per deciview basis indicat es that control options #5a, #6 and #8 are the most cost effective. Options #5a, #6 and #8 consider th e operation of separated over-fire air, selective no n catalytic reduction and selective ca talytic reduction. It should be noted that the $ per deciview includes the cost for both sulfur dioxide and nitrogen oxide.

As noted in Table 6-14, contro l options #6, #7, #8, were the only options that resulted in modeling less than 0.5 deciviews of visibility impairment. Again, it should be noted the modeling results includes the emissi ons of particulate matter, sulfur dioxide, and nitrogen oxide.

None of the nitrogen oxide contro l alternatives have identified energy, non-air environmental, or

have issues with the current life expectancy of the Big Stone I co al fire unit to preclude the use of any of the control options. As such DENR cons iders all the identified control options as being acceptable options based on impacts to energy, non-air environmental and life expectancy.

Based on the visibility modeling, the first ranked control option (selective catalytic reduction) reduces the visibility more than any other co ntrol option. The selec tive catalytic reduction system also reduces the visibili ty an additional 34 percent over the second ranked control option and an additional 65 percent over the fourth ranked control op tion. The selective catalytic

reduction is also considered cost effective on a $ per ton basis, is represented as part of the control option #8 that is one of the most cost effective optio ns on a $ per deciview reduction basis and one of the options that modeling dem onstrates less than 0.5 de civiews of visibility impairment. DENR considers selective catalytic reduction and separate over-fire air system as

BART.

The presumptive emission limit established by EPA for a selective catalytic reduction system installed on a cyclone coal fired unit is 0.10 pounds per million Btus of fuel heat input (Federal Register Volume 70 Number 128 on page 39172). DENR considers the emission limit representing BART should be 561 pounds pe r hour and 0.10 pounds per million Btus, which would include periods of startup, shutdown a nd malfunction. Compliance with the emission

limits shall be based on the c ontinuous emission monitoring system and on a 30-day rolling

average.103 6.4 BART Requirements

Otter Tail Power Company’s Big Stone I reasonably contributes to visibility impairment at Class I areas and is considered a BART-eligible so urce subject to BART. Therefore, DENR is adopting BART requirements in its Administ rative Rules of South Dakota under Chapter 74:36:21 – Regional Haze Program.

These requirements will be part of South Dakot a’s Regional Haze State Implementation Plan and will be enforceable because they will esta blish emission limits representing BART; in accordance with 40 CFR § 51.308(e)(1)(v), the BART control equipment will be required to be properly operated and maintained; and test ing, monitoring, recordk eeping, and reporting requirements will be established to ensure co mpliance with BART. One method of determining if control equipment is being properly operated and maintained is through monitoring the

emissions from the unit. In Otter Tail Powe r Company’s case, continuous emission monitoring sulfur dioxide and nitrogen oxi de is already required in th eir existing permit. The minimum requirements for the operation, maintenance, and monitoring requirements will be established in

ARSD 74:36:21:07. In accordance with 40 CFR § 51.308(e)(1)(iv), DENR will require BART to be installed and operating as expeditiously as practicable, but no later than 5 years from EPA’s approval of South Dakota’s Regional Haze Program . The deadline for installing BART will be

established in ARSD 74:36:21:06.

In accordance with 40 CFR § 51.308(e)(5), once the requirements of BART are achieved, Otter Tail Power Company will be subject to the requi rements of South Dakota’s State Implementation

Plan in the same manner as other sources.



### 7.0 Reasonable Progress

In accordance with 40 CFR § 51.308(d)(1), for each mandatory Class I area located within the state, the state must establish goals, expressed in deciviews, that pr ovide reasonable progress towards achieving natural visibi lity conditions by 2064. The r easonable progress goals must provide improvement in visibility for the 20% most impaired days over the period of the implementation plan and ensure no degradation in visibility for the 20% least impaired days over the same period. In accordance with 40 CFR § 51.308(d)(1)(v), the reas onable progress goals established by the state are not directly enforceab le but will be considered in the evaluation of the adequacy of the measures a state would im plement to achieve natu ral conditions by 2064. In accordance with 40 CFR § 51.308(d)(1)(vi), the st ate may not adopt a reasonable progress goal that represents less visibility improvement than is expected to result from implementation of other requirements of the federal Clean Air Ac t during the applicable planning period.

The EPA published the Guidance for Setting Reasonable Pr ogress Goals under the Regional Haze Rule, 2007 , for setting reasonable progress goals. The basic steps include:

1. Establish baseline and natural visibility conditions; 2. Determine the glide path or uniform rate of progress; 3. Identify and analyze the measures aimed at achieving the uniform rate of progress using the following approaches:104 a. Identify the key pollutants, sources and/or source categories that are contributing to visibility impairment at each Class I area. The sources of impairment for the most impaired and least impaired days may differ; b. Identify the control measures and associated emission reductions th at are expected to result from compliance with existing rules and other available measurements for the sources and source categories that contribute significantly to visibility impairment;

c. Determine what additional control m easures would be reasonable based on the statutory factors and other re levant factors for the sources and/or source categories you have identified; d. Estimate through the use of air quality mode ls the improvement in visibility that would result from implementation of the control measures you have found to be reasonable and compare this to th e uniform rate of progress; and

4. Establish the reason able progress goals.

DENR determined natural visibility conditions (see Table 3-7) and the uniform slope of

reduction for each Class I ar ea (see Figure 3-5).

7.1 State and Federal Rules

South Dakota’s current air quality rules under Ad ministrative Rules of South Dakota (ARSD)

article 74:36 – Air Pollution Cont rol Program, currently protects and improves visibility in Class I areas. Examples of existing ru les that protect and improve visibi lity in Class I areas are listed

below:

1. ARSD § 74:36:01:05 – Applicable requirements of Clean Air Act defined: Subsection (12) states “ Any national ambient air quality sta ndard or increment or visibility requirement under Part C of Title I of the Cl ean Air Act, but only as it would apply to temporary sources permitted pursuant to § 504(e) of the Clean Air Act ”;

2. ARSD § 74:36:01:10 – Modification defi ned: Subsection (3) states “ The change requires or changes a case-by-case determination of an emission limit or other standard, a source-specific determination for temporary sources of ambient impacts, or a visibility or increment analysis ”;

3. ARSD § 74:36:02:01 – Air quality goals: S ubsection (3) states one of the goals is

“ optimization of visibility ”;

4. ARSD § 74:36:04 – Operating permits for minor sources and § 74:36:05 – Operating permits for Part 70 sources: The permits issu ed under these chapters require sources to meet all applicable emission limits, demonstrate compliance, monitoring, recordkeeping and reporting requirements to ensure compliance with all applicable requirements of the Clean Air Act;

5. ARSD §§ 74:36:06 – Regulated Air Pollu tant Emissions; 74:36:07 – New Source Performance Standards; 74: 36:08 – National Emission Stan dards for Hazardous Air Pollutants, and ARSD § 74:36:12 – Control of Vi sible Emissions: These chapters restrict air emissions from regulated entities that contri bute to visibility impairment and prohibits certain open burning practices such as open burni ng waste oil, rubber, waste tires, asphalt shingles, railroad ties, etc.;105 6. ARSD § 74:36:09 – Prevention of Significant De terioration: This chapter requires a visibility analysis to prevent sources subjec t to these requirements from contributing to visibility impairment in Class I Areas;

7. ARSD § 74:36:10 – New Source Review: This ch apter requires a visibility analysis to prevent sources subject to these requirements from contributing to visibility impairment in Class I Areas; and

8. ARSD § 74:36:18 – Regulations fo r State Facilities in the Rapid City Area: This chapter restricts visible emissions from fugitive sources.

The chapters and sections listed above are in cluded in South Dakota’s State Implementation

Plan.

DENR adopted rules that will establish BART emission limits, recordkeeping requirements, monitoring requirements, and reporting requirement s for BART-eligible sources that will reduce their impacts on Class I areas. In addition, DENR adopted rules that will require new major sources and a modification to an existing majo r source that are not subject to New Source Review to conduct a visibility im pact analysis to ensure the proposal will not contribute to adverse impact on visibility in an mandatory Class I area.

On the federal side, gains in visibility should ha ve already occurred from the implementation of the Acid Rain Program and future gains will occur from the implementation of federal emission

standards established for mobile s ources and federal fuel standards.

7.2 2018 Projected Visibility Conditions

The reasonable progress goals ar e interim goals that represent incremental improvement in visibility over time and are compared to th e uniform rate of progr ess for achieving natural visibility by 2064. The first year in determining if states are m eeting their reasonable progress goals is 2018. WRAP gathered th e reductions that will occur th rough this timeframe from states and federal regulations and modele d the results to project where st ates will be at in 2018.

The information WRAP gathered was entered in to a CMAQ model for the Class I areas in the WRAP region to project visibility improvements. The CMAQ model was used to estimate 2018 visibility conditions in South Dakota and all We stern Class I areas. DENR relied on the results of the CMAQ modeling in determining the re asonable progress achieved by South Dakota, surrounding states, and federal regu lations in South Dakota’s Cla ss I areas. DENR originally used the modeling results from “Plan02d” to calc ulate its reasonable progress for the 20% most impaired days and to show no degradation on th e 20% least impaired days. WRAP discovered an error in the modeling runs for some of the Class I area, incl uding the Badlands National Park which resulted in a “Plan02d_rev” modeling run. Th e corrected version, “Plan02d_rev” was used in the final results in Table 7-1 and Figure 7-1.

Table 7-1 provides a summary of WRAP’s modeling result s and compares the results to the

deciview level needed to achieve the 2018 uniform rate of progress for the 20% most impaired days and determine if there is any degradation in the 20% least impaired days in South Dakota’s Class I areas. The modeling resu lts indicate the 2018 uniform rate of progress goal for the 20%106 most impaired days will not be achieved; but there will be no degradation of the 20% least impaired days.

Table 7-1– 2018 Reasonable Progress Summary for South Dakota’s Class I Areas (a) 20% Most Impaired Days

Class I Uniform Reasonable Uniform Progress

Area Baseline 1 Progress 2 Progress 3 Achieved

Badlands 17.14 deciview 15.02 d eciview 16.30 deciview 38%

Wind Cave 15.84 deciview 13.94 deciview 15.28 deciview 33%

(b) 20% Least Impaired Days

Class I

Area Baseline 1 Reasonable Progress 3 Degradation?

Badlands 6.91 deciview 6.64 deciview No

Wind Cave 5.16 deciview 5.02 deciview No

1 – Baseline values derived from Table 3-7;

2 – Uniform progress derived from Figure 3-5; and

3 – Reasonable progress derived from WRAP’s modeling results.

7.3 Key Pollutants Contributing to Visibility Impairment

As indicated by the 2018 visibili ty projections using CMAQ modeli ng, the Class I areas in South Dakota are projected to not meet the uniform rate of progress goal for 2018 for the 20% most impaired days. The CMAQ modeling is conserva tive in several respects. The CMAQ modeling

does not include the BART emissions limits for Otter Tail Power Company’s Big Stone I facility. In addition, the CMAQ modeling includes Big Stone II and NextGen emissions, which are two new coal-fired power plants. The Big St one II facility will no longer be constructed and the NextGen facility is on hold.

In order to determine if there are other contribu tors to not meeting the reasonable progress goals, it is necessary to break down these results to iden tify individual pollutants. Figures 7-1 provides a breakdown of individual pollutant contributio n (measured by extinction) by showing the glide slope of each pollutant in South Dakota’s Cla ss I area from the baseline to 2018, and 2064, for the 20% most impaired days. Below each figure is a table that shows the 2018 projections for each pollutant, and whether the projection is under the 2018 uniform rate of progress goal and the percent improvement toward the 2018 uniform rate of progress goal.

The glide path for the Badlands National Park indicates the air pollu tants not achieving the necessary levels for the 2018 uni form progress goal to be achi eved are organic carbon mass, ammonia sulfate, ammonia nitrate

, and coarse mass. However, ammonia nitrate and coarse mass are very close to the 2018 goal. Organic carbon mass and ammoni a sulfate appear to be the pollutants of most concern in reaching the 2018 goal.

The glide path for the Wind Cave National Park indicates the air pollu tants not achieving the necessary levels for the 2018 uni form progress goal to be achi eved are organic carbon mass,107 ammonia sulfate, and ammonia nitrates. At the Wind Cave National Pa rk, it appears organic carbon mass and ammonia sulfate are the greatest concern since the extinction value for both are the furthest from where they need to be to achieve the uniform rate of progress goal for 2018.

Next, DENR reviewed WRAP’s at tribution analysis to determin e the major contributors of ammonia sulfate, organic carbon mass, and ammonia nitrate in South Dakota’s two Class I areas. For the Badlands and Wind Cave National Parks, the major contributors of ammonia sulfate are

from sources not in South Dakota. South Da kota’s ammonia sulfate contribution for 2002 and 2018 is minimal at both national parks at approx imately 0.04 micrograms per cubic meter. South Dakota’s contribution represents 3% of the ammonia sulfate concentrations for 2018 at both national parks. Of the 3%, approximately 1.5% is generated from point sources and 1.5% is generated from mobile and other sources.

The major contributor of organic carbon mass in bot h national parks is natural fires with point source contributions being minima l. Organic carbon mass emissions from natural and prescribed fires will be evaluated as part of a smoke mana gement plan which is part of DENR’s long term

strategy.108 Figure 7-1 – Glide Slope by Pollutant for 20% Worst Visibility Days (Extinction) 1
(a) Badlands National Park

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

(b) Wind Cave National Park

(WRAP TSS – http://vista.cira.colostate.edu/tss/ )

1 – “NO 3 ” means nitrates, “SO 4 ” means sulfates, “OMC” means organic mass carbon, “EC” means elemental carbon, and “CM” means coarse mass.109 Ammonia nitrate was only a concern for the Wind Cave National Park since it was on the glide path at the Badlands National Park. The major c ontributors to ammonia n itrate at the Wind Cave National Park are Canada followed by Wyoming, Outside the Domain, and South Dakota. South

Dakota’s ammonia nitrate contribution fo r 2002 and 2018 is approximately 0.135 and 0.105 micrograms per cubic meter, respectively. Sout h Dakota’s contribution re presents 10% of the

ammonia nitrate concentration for 2018 at the Wind Cave National Park. Of the 10%, approximately 4% is generated from point sour ces and 6% is generated from mobile and other

sources.

South Dakota’s contribution of ammonia sulfat e, organic carbon mass, and ammonia nitrate concentrations is approximately 1.5% for ammoni a sulfate, minimal for organic carbon mass, and 4% for ammonia nitrate. Therefore, minima l gain would be encountered from reduction in sulfur dioxide, organic carbon mass, and nitrogen oxide emissions from point sources within

South Dakota.

7.4 Four Factor Analysis

In accordance with 40 CFR § 51.308(d)(1)(ii), if th e state establishes a reasonable progress goal that provides for a slower rate of improvement in vi sibility than the rate th at would be needed to

attain natural conditions by 2064, the state must demonstrate ba sed on the four factor analysis that the rate of progress for the state’s implemen tation plan to attain na tural conditions by 2064 is not reasonable; and the progress go al adopted by the state is reas onable. DENR looked at the air pollutants being emitted from point sources that were not meeting the glide path for each national park. Based on Figure 7-1(a), the air pollut ant not meeting the glide path at the Badlands National Park is ammonia sulfate and organi c carbon mass. Based on Figure 7-1(b), the air pollutant not meeting the glide path at the Wind Cave National Park is ammonia sulfate, organic carbon mass, and ammonia nitrate.

In accordance with 40 CFR § 51.308(d)(1)(i)(A), in establishing the reasonable progress goals for each mandatory Class I federal area within th e state the state must consider the costs of compliance, the time necessary for compliance, the energy and non-air quality environmental impacts of compliance, and the remaining useful li fe of any potential affected sources. This

consideration is also known as th e four factor analysis. The f our factor analysis must also include a demonstration showing how these factors were taken into consideration in selecting the goal.

There are three facilities in th e Rapid City area which EPA i ndicates require a four factor analysis and they are: 1) GCC Dacotah; 2) Blac k Hills Corporation (Ben French); and 3) Pete Lien and Sons, Inc. The four factor analysis will be conducted for sulfur dioxide and nitrogen

oxide.110 7.4.1 Four Factor Analysis – GCC Dacotah

WRAP conducted a four factor analysis for GCC Dacotah’s two wet kilns at DENR’s request and finalized the document on May 9, 2009 (see Appe ndix F). After reviewing the calculations in Table 4-2 of the document, DENR determined some of the cost effectiveness values for GCC Dacotah are incorrect. Table 7-2 provides a correct ed version of the cost effectiveness of the feasible control options using the emi ssion reduction listed in the document.

WRAP’s analysis did not include the analysis of a selective non-catal ytic reduction (SNCR) system because at the time, SNCR were not a pr oven technology for wet kilns at Portland cement plants. EPA commented after the analysis was co mpleted that the review should include a SNCR because the SNCR is being used a wet kilns in Europe and at the Ash Grove Cement plant in Midlothian, Texas. Although DENR does not agree that one pl ant in the Nation operating a

SNCR on a wet kiln for several mont hs constitute the system is capable of using a SNCR, DENR agreed to conduct a four factor analysis for SNCRs. DENR used EPA’s November 2007 “Alternative Control Techniques Document Update – NOx Emissi ons from New Cement Kilns”,

EPA-453/R-07-006 to estimate the cost of a SNCR system even though this document was developed for the review of dry kilns and not wet kiln.

The “Capital Cost ($1,000)” column represents the capital invest ment for purchasing the control equipment. The “Annual Cost ($1,000)” is the amor tized cost of the capita l investment plus the annual cost to operate the control equipment. WRAP based the amortized cost of the capital

investment on the control device and/or wet k iln operating 30 years a nd a 7% interest rate. EPA’s cost numbers for a SNCR system was based on 2005 dollars. WRAP’s cost numbers were based on 2007 dollars. Therefore, EPA’s 2005 cost numbers were updated to 2007 cost numbers by using a 3% annual infl ationary rate. The “Cost per Ton” column is based on the “Annual Cost” divided by the “Reductions”.111 Table 7-2– Four Factor Analysis for GCC Dacotah

Control Capital Annual Cost per Ton

Control 2002 Efficiency Reductions Cost Cost Range

Pollutant Option tpy % % tpy tpy ($1000) ($1000) $/ton $/ton

Wet Kiln #4

NOx LNB (indirect) 707 30 40 212 283 $526 $129 $608 $456

LNB (direct) 707 - 40 283 $1873 $331 - $1,170

Biosolids Injection 707 - 23 163 - - 1 1

CemStar 707 20 60 141 424 $1,599 $299 $2,121 $705

Mid-Kiln 707 20 50 141 354 $2,748 -$315 22

LoTOx TM 707 80 90 566 636 - - 1 1

SCR 707 80 566 $14,813 $4,137 $7,309

SNCR 707 30 40 212 283 - $878 3 $4,142 $3,102

SO 2 Wet FGD 26 90 99 23 26 $9,133 $1,370 $59,565 $52,692

Wet Kiln #5

NOx LNB (indirect) 388 30 40 116 155 $526 $129 $1,112 $832

LNB (direct) 388 40 - 155 $1873 $331 - $2,135

Biosolids Injection 388 23 - 89 - - 1 1

CemStar 388 20 60 78 233 1599 299 $3,833 $1,283

Mid-Kiln 388 20 50 78 194 $2,748 -$315 22

LoTOx TM 388 80 90 310 349 - - 1 1

SNCR 388 30 40 116 155 - $878 3 $7,569 $5,665

SCR 388 80 310 $14,813 $4,137 $13,345

SO 2 Wet FGD 431 90 99 388 427 $9,133 $1,370 $3,531 $3,208

1 – The document did not list a cost per ton because they did not identify any capital or annual costs;

2 – DENR did not list a cost per ton because the annual cost was a negative number; and

3 – EPA’s November 2007 update indicates the average annualized cost of an SNCR to an SCR is approximately 1/5 the cost. (Average annualized cost of facility numbers 1, 2, 3, 4, 5, 6, 18, 19, 20, and 31, divided by average annualized cost of fac ility numbers 36, 37, 40, 43, and 46). Using this ratio, WRAP’s estimated annualized cost of $4,137,0 00, and the inflationary rate, the annualized cost is estimated to be $878,000 ($4,137,000 x 0.2 x 1.0609 = $878,000).

Based on the cost per ton estimat es, DENR determined a wet flue gas desulfurization unit for controlling sulfur dioxide emissions from Wet Ki ln #4 and a selective catalytic reduction system for controlling nitrogen oxide emissions from Wet Kiln #5 is not cost eff ective. DENR looked at a biosolids injection system and determined a cheap supply of biosolid s was not available in Rapid City and shipping bioso lids to GCC Dacotah would make this option economically infeasible especially when looking at only a 23 percent reduction in ni trogen oxide emissions. Based on DENR’s research, the CemStar and LoTOx TM options have not been demonstrated to112 work for wet cement kilns and the low-NOx burners will not work since th e wet kilns are direct fired. Therefore, DENR does not be lieve these options are a viable option. That leaves the MidKiln and SNCR as a viable option for cont rolling nitrogen oxide emissi ons from both wet kilns, a selective catalytic reduct ion system for controll ing nitrogen oxide emi ssions from Wet Kiln #4, no viable options for controlling sulfur dioxide emissions from Wet Kiln #4, and a wet flue gas desulfurization system for c ontrolling sulfur dioxide em issions from Wet Kiln #5.

The cost per ton analysis is based on calenda r year 2002 air emissions for the two wet kilns which operated on average approximately 8,282 hours pe r year. In the last five years, the two wet kiln have operated an average of 4,160 hours pe r year with the last two years not operating. To determine if these control options are still co st effective if the two wet kilns are only operated 4,160 hours per year, DENR calculated the cost per ton for those controls that are viable for each wet kiln and pollutant. The results may be viewed in Table 7-3.

Table 7-3– Four Factor Analysis for GCC Dacotah at 4,160 Hours per Year

Control Capital Annual Cost per Ton

Control Annual Efficiency Reductions Cost Cost Range

Pollutant Option tpy % % tpy tpy ($1000) ($1000) $/ton $/ton

Wet Kiln #4

SO 2 Wet FGD 14 90 99 13 14 $9,133 $1,370 $105,385 $97,857

NOx SCR 370 - 80 - 296 $14,813 $4,137 - $13,976

SNCR 370 30 40 111 148 - $878 7,910 5,932

Wet Kiln #5

SO 2 Wet FGD 208 90 99 187 206 $9,133 $1,370 $7,326 $6,650

NOx SCR 187 - 80 - 150 $14,813 $4,137 - $27,580

SNCR 208 30 40 62 83 - $878 14,161 10,578

Based on operating approximately 50% of the time the wet kilns operated in 2002, the wet flue gas desulfurization system for Wet Kiln #5 and the SNCR for Wet Kiln #4 are on the border of being a viable option.

DENR modeled GCC Dacotah’s two wet kilns to determine if the emissions reasonably contribute to visibility impairment in the Badl ands and Wind Cave national Park. The modeling analysis is based on 2002 actual emissions. The modeling report is located in Appendix G and a summary of the modeling results is displayed in Table 7-4. The modeling results represent the 8 th
highest reading (dec iviews) per year.

Table 7-4– Visibility Impac ts from GCC Dacotah (8 th Highest)

Year Badlands Wind Cave

2002 0.32 deciviews 0.36 deciviews

2006 0.32 deciviews 0.36 deciviews

2007 0.31 deciviews 0.46 deciviews

Based on the modeling results, the current air em issions from GCC Dacotah’s wet kilns do not reasonably contribute to visibili ty impairment in the Badlands and Wind Cave National Parks.113 DENR believes the cost of reductions is not r easonable for either wet kiln when considering GCC Dacotah’s visibility impact and the remaining useful life used in the analysis is suspect when considering GCC Dacotah has not operated th e two wet kilns in the last two years. In addition, EPA promulgated new standards on September 9, 2010, for Portland Cement Manufacturing (Federal Regist er Volume 75, #174, page 54970) and DENR is unsure what impacts that will have on the useful life of the wet kiln(s).

7.4.2 Four Factor Analysis – Black Hi lls Corporation (Ben French)

WRAP conducted a four factor analysis for the 25 megawatt subbituminous coal-fired electric power plant at Black Hills Cor poration’s Ben French facility and finalized the document on May 9, 2009 (see Appendix F). After reviewing the calcul ations in Table 4-2 of the document, DENR

determined that some of the cost effectiveness values for Black Hills Corporation are incorrect. Table 7-5 provides a corrected vers ion of the cost effectiveness of the feasible control options using the emission reduction listed in the document.

The “Capital Cost ($1,000)” column represents the capital invest ment for purchasing the control equipment. The “Annual Cost ($1,000)” is the amor tized cost of the capita l investment plus the annual cost to operate the control equipment. WRAP based the amortized cost of the capital

investment on the control device and/or the coal fired electric power pl ant operating 30 years and

a 7% interest rate. The “Cost per Ton” column is based on the “Annual Cost” divided by the

“Reductions”.

Table 7-1– Four Factor Analysis for Black Hills Corporation Based on 30 Year Life

Control Capital Annual Cost per Ton

Control 2002 Efficiency Reductions Cost Cost Range

Pollutant Option tpy % % tpy tpy ($1000) ($1000) $/ton $/ton

NOx LNB 907 30 75 272 680 $1,250 $195 $717 $287

LNB

w/OFA 907 50 65 454 590 $1,780 $298 $656 $505

SNCR 907 30 75 272 680 $1,290 $770 $2,831 $1,132

SCR 907 40 90 363 816 $3,000 $754 $2,077 $924 $4,250 $1,068 $2,942 $1,309

SO 2 Dry

Sorbent Injection 785 10 40 79 314 $4,300 $1,700 $21,519 $5,414

Spray Dryer

Absorber 785 90 707 $11,600 $2,670 $3,777

Wet FGD 785 90 707 $14,600 $2,760 $3,904

It appears the WRAP analysis is usable in a general sense. However, Black Hills Corporation identified the WRAP report as highly generali zed without consideration of physical site constraints and expected life of the plant. According to Black H ills Corporation, the expected life114 of the Ben French facility is 10 years with cu rrent regulations. This may change as EPA’s regulations change.

DENR conducted a cost per ton analysis based on operating for 10 years instead of 30 years as assumed by WRAP. DENR assumed the difference between the amortized cost of the capital

investment and the annual cost is the annual operation and mainte nance cost. Table 7-6 provides the results for this analysis.

Table 7-2– Four Factor Analysis for Black Hills Corporation Based on 10 Year Life

Control Capital Annual Cost per Ton

Control 2002 Efficiency Reductions Cost Cost Range

Pollutant Option tpy % % tpy tpy ($1000) ($1000) $/ton $/ton

NOx LNB 907 30 75 272 680 $1,250 $272 $1,000 $400

LNB

w/OFA 907 50 65 454 590 $1,780 $408 $899 $692

SNCR 907 30 75 272 680 $1,290 $850 $3,125 $1,250

SCR 907 40 90 363 816 $3,000 $939 $2,587 $1,151 $4,250 $1,331 $3,667 $1,631

SO 2 Dry

Sorbent Injection 785 10 40 79 314 $4,300 $1,966 $24,886 $6,261

Spray Dryer

Absorber 785 90 707 $11,600 $3,387 $4,791

Wet FGD 785 90 707 $14,600 $3,662 $5,180

The 10 year evaluation does not change the outco me of the analysis. It appears from both evaluations the control equipment would be economical to install ba sed on a cost per ton basis, except for the dry sorbent injection system if th e anticipated sulfur dioxide emission reductions are at the lower level (e .g., 10% efficiency).

DENR modeled Black Hills Corporation’s coal-fire d electric power plant to determine if the emissions reasonably contribute to visibility impairment in the Badlands and Wind Cave national Park. The modeling analysis is based on 2002 act ual emissions. The modeli ng report is located in Appendix H and a summary of the modeling re sults is displayed in Table 7-7. The modeling results represent the 8 th highest reading (deci views) per year.

Table 7-3– Visibility Impacts fr om Black Hills Corporation (8 th Highest)

Year Badlands Wind Cave

2002 0.21 deciviews 0.22 deciviews

2006 0.23 deciviews 0.23 deciviews

2007 0.20 deciviews 0.30 deciviews115 Based on the modeling results, the current air em issions from Black Hills Corporation’s coalfired electric power plant does not reasonably contribute to visibility impairment in the Badlands

and Wind Cave National Parks.

7.4.3 Four Factor Analysis – Pete Lien and Sons

WRAP did not conduct a four factor analysis on Pete Lien and Sons operations. Pete Lien and

Sons’ sulfur dioxide emissions are less than one ton per year and will have no impact on visibility in any Class I area. In 2002, nitrogen oxide emissions were approximately 272 tons per year which has not changed much over the year s based on the 2009 nitrogen oxide emissions at approximately 287 tons per year.

On May 12, 2008, Pete Lien and Sons submitted a PSD application for a new preheater-type rotary lime kiln and ancillary equipment for its f acility in Rapid City. A Best Available Control Technology (BACT) analysis for ni trogen oxide was included in th e application which indicated that post control options such as non-selective catalytic redu ction and selective catalytic reduction systems were found to be technically in feasible because of te mperatures, location of injection nozzles, etc. The PSD a pplication also looked at low-NOx burners and determined they were also not technically feasible since the rotary kiln is a direct -fired lime kiln. DENR reviewed the application at the time and ag reed with the conclusion that BACT for a lime rotary kiln was good combustion practices.

DENR reviewed EPA’s RACT/BACT/LAER Clear inghouse (RBLC) to determine if any new rotary lime kilns had been permitted since Pete Lien and Sons’ PSD application had been

submitted. There were three entries. One occurr ed in Texas, Ohio, and Wisconsin. The one for Texas only involved carbon monoxide. In Ohio a nd Wisconsin, the BACT analysis for nitrogen oxide determined that no control technologies we re cost effective and good combustion practices

were considered BACT.

DENR conducted a modeling analysis to determin e if the emissions from Pete Lien and Sons’ lime kiln contribute to visibility impairment at the Badlands and Wind Cave National Parks. The impact is based on 2002 actual emissions. The mode ling report is locate d in Appendix I and a summary of the modeling results is displayed in Table 7-8. The modeling results represent the 8 th
highest reading (dec iviews) per year.

Table 7-4– Visibility Impacts fr om Pete Lien and Sons (8 th Highest)

Year Badlands Wind Cave

2002 0.05 deciviews 0.06 deciviews

2006 0.06 deciviews 0.05 deciviews

2007 0.07 deciviews 0.05 deciviews

Based on the modeling results, the air emissions fr om Pete Lien and Sons’s lime kiln does not reasonably contribute to visibili ty impairment in the Badlands and Wind Cave National Parks.116 7.4.4 Four Factor Analysis – Summary

DENR conducted a four factor analysis on GCC Dacotah’s two wet kilns, Black Hills Corporation’s coal-fired electric power plant, and Pete Lien and Sons’ lime kiln. As part of the analysis, DENR modeled the actual emissions from these units at each facility to determine if they reasonably contribute to visibility impairment in the Badlands and Wind Cave National

Parks.

DENR does not plan on requiring controls on these three facili ties at this time because the visibility modeling indicates the un its at these facilities do not reas onably contribute to visibility impairment in the national parks. The results of the visibility modeling is substantiated by the

results of WRAP’s attributi on analysis which concluded S outh Dakota’s contribution to

ammonia sulfate and ammonia nitrate is minimal.

DENR will continue to review th ese three facilities and others facilities as the goal of achieving natural visibility conditions in our national parks by 2064 is eval uated on a periodic basis.



### 8.0 Long Term Strategy

In accordance with 40 CFR § 51.308(d)(3), each state must submit a long term strategy to address regional haze visibility impairments for each Class I area within the state and for each

Class I area outside the state whic h may be affected by emissions fr om the state. The long term strategy must include enforceable emission limitations, compliance schedules, and other measures as necessary to achieve the reasonabl e progress goals established by the state for each

Class I area.

The long term strategy must meet the following requirements:

1. Where the state has emissions that are reasonab ly anticipated to cont ribute to visibility impairment in any Class I area located in a nother state or states, the state must consult with the other state(s) in order to develop coordinated emission ma nagement strategies. The state must also consult with any othe r state having emissions that are reasonably anticipated to contribute to vi sibility impairment in any manda tory Class I area within the

state;
2. Where other states cause or contribute to im pairment in a Class I area, the state must demonstrate that it has included in its impl ementation plan all measures necessary to

obtain its share of the emission reductions need ed to meet the progress goal for the area. If the state has participated in a regional pl anning process, the state must ensure it has

included all measures needed to achieve its apportionment of emission reduction obligations agreed upon through that process;

3. The state must document the technical basis, including modeling, monitoring and emissions information, on which the state is relying to determine its apportionment of emission reduction obligations necessary for achieving reasonable progress in each mandatory Class I area it affects. The stat e may meet this requirement by relying on technical analyses developed by the regiona l planning organization and approved by all state participants. The state must identify the baseline emissions inventory on which its117 strategies are based. The baseli ne emissions inventory year is presumed to be the most recent year of the consolidate periodic emissions inventory;

4. The state must identify all anthropogenic sour ces of visibility impa irment considered by the state in developing its l ong term strategy. The state shoul d consider major and minor stationary sources, mobile sources, and area sources; and

5. The state must consider, at a minimum, the following factors in developing its long term

strategy:

a. Emission reductions due to ongoing air po llution control programs, including measures to address reasonably attributable visibility impairment;

b. Measures to mitigate the impact s of construction activities;

c. Emissions limitations and schedules for compliance to achieve the reasonable progress goal;

d. Source retirement and replacement schedules;

e. Smoke management techniques for agricultu ral and forestry management purposes including plans as currently exist within the state for these purposes;

f. Enforceability of emissions limitations and control measures; and

g. The anticipated net effect on visibility due to projected changes in point, area, and mobile source emissions over the peri od addressed by the long-term strategy.

8.1 Class I Areas in Other States Impacted by South Dakota

In accordance with 40 CFR § 51.308(d)(3)(i), the long term strategy for each state that causes or contributes to impairment in a Cl ass I area is required to demonstr ate that it has included in its State Implementation Plan all measures necessary to obtain its share of the emission reductions needed to meet the progress goals for the Class I ar ea. If the state has par ticipated in a regional planning process, the state must ensure it has included all measures needed to achieve its apportionment of emission reduction obliga tions agreed upon th rough that process.

DENR participated in WRAP and worked with ot her states that are not members of WRAP in developing its State Implementation Plan. Otter Tail Power Company’s Big Stone I facility is the only source in South Dakota that is reasonable anticipate d to contribute to visibility impairment at the Badlands National Park in South Dakota; Theodore National Park in North Dakota; Boundary Waters and Voyageurs Class I areas in northern Minnesota and the Isle Royale federal Class I area in Michigan. Otte r Tail Power Company developed a case-by-case BART analysis which DENR reviewed to establish the BART emission limits for Big Stone I. The case-by-case BART analysis and DENR’s revi ew was submitted to the appropriate states for

their comments.

DENR will establish the BART proc edures in the Administrative Rules of South Dakota that are equivalent to federal regulation in 40 CFR Part 51, adopt the BART emission limits applicable to BART-eligible coal fired power plants (which includes Big Stone I) in the rule, and adopt the BART emission limits in an air quality construction permit and eventually in Otter Tail Power Company’s Title V air quality operating permit for the Big Stone I facility. DENR believes the BART requirements represents South Dakota’s emission reductions for those Class I areas impacted by Big Stone I.118 8.2 States Impacting South Dakota’s Class I Areas

In accordance with 40 CFR § 51.308(d)(3)(ii), the long term strategy for each state that causes or contributes to impairment in a Cl ass I area is required to demonstr ate that it has included in its State Implementation Plan all measures necessary to obtain its share of the emission reductions needed to meet the progress goals for the Class I ar ea. If the state has par ticipated in a regional planning process, the state must ensure it has included all measures needed to achieve its apportionment of emission reduction obliga tions agreed upon th rough that process.

DENR has worked with states c ontributing to visibility impair ment in South Dakota’s Class I areas through WRAP and also with those states that are not part of WRAP. DENR believes at this time that the controls they are adopti ng under their BART analysis, State Implementation Plan, and other measures states are taking will minimize their impacts on South Dakota’s Class I areas. Based on WRAP’s emission inventory for 2002 and 2018, these control measures will reduce sulfur dioxide emissions by 26%, nitroge n oxide emissions by 29%, organic carbon mass by 6% and elemental carbon by 31% (der ived from Table 5-6 and 5-7).

8.3 Technical Basis for Modeling, Monitoring and Emissions Information

In accordance with 40 CFR § 51.308(d)(3)(iii), as pa rt of the long term st rategy, each state is required to document the technical basis, including modeling, monitoring and emissions information, on which the state is relying to determine its apportionment of emission reduction obligations necessary for achieving reasonable progress in each manda tory Class I area it affects. The state may meet this requirement by relying on technical analyses developed by the regional planning organization and approved by all state participants. The st ate must identify the baseline emissions inventory on which its strategies are based. The baseline emissi ons inventory year is presumed to be the most recent year of the consolidated periodic emissions inventory.

South Dakota is a member of WRAP and reli ed on the modeling, monitoring and emissions information and technical analyses developed by WRAP to accomplish this requirement. DENR relied on the use of CALPUFF for single s ource BART screening modeling and WRAP’s CMAQ and Particulate Matter Source Apportio nment Technology modeling in its cumulative impact analyses. The BART mode ling conformed to the requiremen ts of the BART guidelines. The WRAP CMAQ and Particulate Matter Source Apportionment Technology modeling conformed with EPA’s modeling guidelines. On the monitoring side, DENR used the IMPROVE monitoring data available on the IMPROVE website for its Class I areas.

DENR used WRAP’s Plan02d emi ssions inventory for the baseline emissions year 2002 which reflects a composite interpreta tion of emissions for the base 2000-2004 period; and WRAP’s CMAQ PRP18b (Preliminary Reasonable Progress 2018 Scenario A) emissions inventory which reflects projected year 2018 emissions. The pr ojected year 2018 emissions represents base period emissions projected to 2018, accounting for esti mates of the effect of BART controls and assuming other growth and control factors.

Currently, WRAP is maintaining this documentation at the following website:119 http://vista.cira.colostate. edu/TSS/Results/HazePlanning.aspx

DENR will continue to work with WRAP in its effort to update emission inventories and run

models to determine if South Dakota is meeti ng its reasonable progress and long term strategy goals.

8.4 Identification of Anthropogenic So urces of Visibility Impairment

In accordance with 40 CFR § 51.308(d)(3)(iv), as part of the long term stra tegy, each state must identify all anthropogenic sources of visibility impairment considered by the state in developing its long term strategy. Th e state should consider major and mi nor stationary sources, mobile

sources and area sources.

DENR worked through WRAP and through a BART analysis to identify major and minor stationary sources. WRAP was also used to co nsider mobile and area source emissions. One item that does appear to be the greatest contri butor is activities contributing to organic mass

carbon emissions such as wild fire s and prescribed fires.

8.5 Factors in Developing Long Term Strategy

In accordance with 40 CFR § 51.308(d)(3)(v), states must consider, at a minimum, the following factors in developing its long term strategy:

1. Emission reductions due to ongoing air pollution control programs, including measures to address reasonably attributable visibility impairment;

2. Measures to mitigate the impact s of construction activities;

3. Emissions limitations and schedules for comp liance to achieve the reasonable progress goal;

4. Source retirement and replacement schedules;

5. Smoke management techniques for agricultu re and forestry management purposes including plans as currently exist within the state for these purposes;

6. Enforceability of emissions limitations and control measures; and

7. The anticipated net effect on visibility due to projected changes in point, area, and mobile source emissions over the period addr essed by the long- term strategy.

It is expected that for some areas of the count ry, such as parts of the eastern United States,

emission reductions achieved for the acid rain program and for meeting the PM2.5 NAAQS, will lead to substantial improvements in visibility as well. Subsection 1 in this section makes clear

that states must take these other emission reduc tions into account in de veloping their long-term strategies for regional haze.

8.5.1 Emission Reductions from Ongoing Air Pollution Control Programs

In accordance with 40 CFR § 51.308(d)(3)(v)(A), an assessment of emission reductions due to ongoing air pollution control programs is required. Existing air pollution control programs in120 place which assist in reducing air emissions a nd help achieve reasonable progress toward the national visibility goal include the following South Dakota ai r quality rules under ARSD § 74:36 – Air Pollution Control Program are listed below:

1. ARSD § 74:36:01:05 – Applicable requirements of Clean Air Act defined: Subsection (12) states “ Any national ambient air quality sta ndard or increment or visibility requirement under Part C of Title I of the Cl ean Air Act, but only as it would apply to temporary sources permitted pursuant to § 504(e) of the Clean Air Act ”;

2. ARSD § 74:36:01:10 – Modification defi ned: Subsection (3) states “ The change requires or changes a case-by-case determination of an emission limit or other standard, a source-specific determination for temporary sources of ambient impacts, or a visibility or increment analysis ”;

3. ARSD § 74:36:02:01 – Air quality goals: S ubsection (3) states one of the goals is

“ optimization of visibility ”;

4. ARSD § 74:36:04 – Operating permits for minor sources and § 74:36:05 – Operating permits for Part 70 sources: The permits issu ed under these chapters require sources to meet all applicable emission limits, demonstrate compliance, monitoring, recordkeeping and reporting requirements;

5. ARSD §§ 74:36:06 – Regulated Air Pollu tant Emissions; 74:36:07 – New Source Performance Standards; 74: 36:08 – National Emission Stan dards for Hazardous Air Pollutants, and ARSD § 74:36:12 – Control of Visible Emissions: These chapter restricts air emissions from regulated entities that caus e visibility impairment and prohibits certain open burning practices such as open burning waste oil, r ubber, waste tires, asphalt shingles, railroad ties, etc.;

6. ARSD § 74:36:09 – Prevention of Significant De terioration: This chapter requires a visibility analysis to prevent sources subjec t to these requirements from contributing to visibility impairment in Class I Areas;

7. ARSD § 74:36:10 – New Source Review: This ch apter requires a visibility analysis to prevent sources subject to these requirements from contributing to visibility impairment in Class I Areas; and

8. ARSD § 74:36:18 – Regulations fo r State Facilities in the Rapid City Area: This chapter restricts visible emissions from fugitive sources.

The chapters and sections listed above are incl uded in South Dakota’s State Implementation

Plan.

In addition, EPA implemented a reasonably attri butable visibility impact (RAVI) protection program in 1987 with a Federal Implementation Plan (FIP) for South Dakota to meet the general visibility plan requirements and long -term strategies of 40 CFR §§ 51.302 and 51.306, respectively. The existing federal RAVI program is compatible with the regional haze program

and no revisions are needed at this time. DE NR will coordinate with EPA to conduct joint periodic reviews and revisions of the long-term RAVI stra tegy as required by 40 CFR § 51.306(c). DENR may consider incorporation of the RAVI program into South Dakota’s State Implementation Plan in the future.121 8.5.2 Measures to Mitigate Impacts of Construction Activities

In accordance with 40 CFR § 51.308(d)(3)(v)(B), stat es are required to consider measures to mitigate the impacts of construc tion activities. States, for example, should include these

activities in emission inventories used for l ong-term strategy development. South Dakota regulates fugitive emissions by rule in ARSD § 74 :36:18 – Regulations for State Facilities in the Rapid City Area. This chapter restricts visible emissions from fugitive sources in the Rapid City

area.

In addition, as part of South Dakota’s State Implementation Pla n, DENR is proposing rules that will require new major sources and modifications to major sources to conduct a visibility analysis. A new major source or modification to a major source will have to determine what controls will be necessary to maintain emissions at a level that will not cause visible emission equal to or greater than 0.5 deciviews at a Class I area. The new major source or modification to a major source will be required to install the control equipment, establish emission limits, recordkeeping requirements, and reporting requirements.

8.5.3 Emission Limitations and Schedules to Achieve Reasonable Progress Goals

In accordance with 40 CFR § 51.308(d)(3)(v)(C), stat es are required to consider air emissions limitations and schedules for compliance to achi eve the reasonable progress goal in developing its long terms strategy. This requirement impacts South Dakota’s only BART-eligible source (Otter Tail Power Company’s Big Stone I). Th e BART requirements, BART emission limits, and compliance deadlines for Otter Tail Power Company’s Big Stone I facility will be

established in South Dakota’s rules. The evalua tion of non-BART sources as part of the long term strategy will be reviewed in the next pl anning period since WRAP’s attribution analysis

indicates South Dakota’s sources have minimal impact on our Class I areas.

8.5.4 Retirement and Replacement Schedules

In accordance with 40 CFR § 51.308(d)(3)(v)(D), st ates are required to consider any source retirement and replacement schedu les in developing its long term strategy, particularly, where

these schedules would have a si gnificant impact on regional emi ssion loadings and on a state’s ability to achieve reas onable progress.

DENR is not aware of any anticip ated major source retirements or replacements that would have a significant impact on regional emissions loadings and on a state’s ability to achieve reasonable progress. The replacement of existing units at f acilities will be managed in conformance with the state’s existing State Implementation Plan.

The 2018 modeling conducted by WRAP included two new coal-fired electric power plants and one oil refinery to be located in South Dakota. Although the PSD permit has been issued for one

of the new coal-fired electric power plants, the applicant notifie d DENR that it is no longer going to build the plant. The second coal-fired power electric power pl ant requested that DENR put its application on hold until further notice. Therefor e, the next modeling exercise for determining122 visibility in 2018 will need to be adjusted to reflect this deve lopment and the current modeling results for 2018 are probably conservative.

8.5.5 Smoke Management

In accordance with 40 CFR § 51.308(d)(3)(v)(E), states are required to consider smoke management techniques for agriculture and fo restry management purposes including plans as currently exist within the state fo r these purposes in developing its long term strategy. As part of the long term strategy, DENR will investigate the impacts a smoke management plan for wild fires and prescribed burns will have on the 20% most impaired days within the first planning period of 2013.

Currently very little agricultural burning ta kes place in South Dakota and the majority of agricultural land lies in the eastern two-thirds of the state, while both Class I areas are in the western third. In addition, DENR did not observe any of the 20% most impaired days that were attributed to agricultural burning in the eastern half of South Dakota. Therefore, agricultural burning does not appear to have much of an impact at our Class I areas. However, there is some burning of grass in and around the Class I areas whic h will be investigated to determine if this practice warrants being covered unde r a smoke management plan.

Over the years the National Park Service a nd U.S. Forest Service have conducted planned prescribed burns on federal lands at both Class I areas, which have affected the air quality in both parks. The last prescribed burn at the Wind Ca ve National Park is one example in which the smoke from the fire had a negative impact on DENR’s air monitoring equipment. DENR is currently waiting to review the IMPROVE data for t hose days to see what kind of impact the fire had on the organic carbon mass concentration an d to some extent the ammonia sulfide and

ammonia nitrate levels. In a ddition, DENR has observed there is evidence that large fires contribute to the 20% most impaired days during the baseline period.

DENR has taken the initial steps in developi ng a smoke management plan by contacting those groups that DENR believes would need to be involved, including the South Dakota Department of Agriculture, National Park Service a nd U.S. Forest Service, among others. The response from these agencies has been positive and all have offered to assist in developing a smoke management plan for South Dakota. More recen tly, DENR has been in contact with the South Dakota Division of Wildland Fire Suppression, whic h maintains a prescribed fire database of fires throughout South Dakota a nd along our borders in neighboring states. DENR will use this database to track fires and compare the fire data (e.g., size of fire, material being burned, distance from the Class I areas, dates) to the IM PROVE data from our Class I areas to see what the impacts are to the visibility.

It is DENR’s intention to investigate these pr escribed burns as well as other wildfires and planned prescribed burns to determine at what level (e.g., size of burn, distance from the Class I areas, combustible material) should a wildfire or prescribed fire be included in the smoke management plan and what best management prac tices can be used to minimize their impacts on the 20% most impaired days in the Class I areas. Th e results of this analysis will be adopted in the Regional Haze State Implementation Plan as pa rt of our long term strategy. DENR will work123 with the federal land managers, other stat e agencies, and local governments during the development and implementation of the smoke management plan.

8.5.6 Enforceable Emission Limits and Control Measures

In accordance with 40 CFR § 51.308(d)(3)(v)(F), states are required to consider the enforceability of emission limits and control meas ures in developing its long term strategy. In developing enforceable emissions limits and cont rol measures, the state should ensure they are written in a way that EPA and citizens ma y enforce them as a practical matter.

The BART requirements, including the BART emission limits for Big Stone I, will be established in South Dakota’s rules and adopted into South Dakota’s State Implementation Plan. This will allow states, the public, and any interest ed party to comment on the rules to ensure the BART requirements are enforceable in a practica l matter. In addition, the BART emission limits and specific control measures that will be estab lished in Otter Tail Powe r Company’s Big Stone I air quality permit will be open to states, the pub lic, and any interested party for comment and ensure the BART permit requirements are enforceable in a practical matter.

Currently, DENR developed a Title V air quality permit program which is required prior to

construction for new sources and modifications to existing sources. DENR established a construction permit program that separates the co nstruction permit from the Title V air quality permit program. The construction permit program wa s submitted to EPA to be included in South Dakota’s State Implementation Plan. The BART emission limits and control measures will be included in a construction permit and eventua lly in the Title V air quality permit.

DENR is also establishing requirements under the Regional Haze Program to require new major sources and modifications to major sources to de monstrate through a visibili ty analysis that the new major source or modification to a major source will not contribute to visibility impairment in any mandatory Class I area. Contribute to visibility impairme nt is defined by a change in visibility impairment in a mandatory Class I area of 0.5 deciviews or more, based on a 24-hour average, above the average natural visibility ba seline. A source exceeds the threshold with the

98 th percentile (eighth highest valu e) of the modeling results based on one year of the three years of meteorological data modeled exceeds the 0.5 deciviews. The emission limits and control measures used in the visibility analysis are re quired to be included in the sources permit which will include an opportunity for states, the public , and any interested party to comment on to ensure the requirements are enforceable in a prac tical matter. The rules will assist DENR in ensuring the sources in South Dakota will not contri bute to visibility impairment in any Class I

area.

8.5.7 Anticipated Net Effect on Visib ility Due to Projected Changes

In accordance with 40 CFR § 51.308(d)(3)(v)(G), when developing its long term strategy states are required to consider the antici pated net effect on visi bility due to projected changes in point, area, and mobile source emissions over the period addressed by the long term strategy. WRAP projected the net effect on visi bility from emission reductions and increases by point, area and mobile sources throughout the WRAP regi on through 2018. The first emission projection124 inventory was compiled in 2006. The inventory was revised in 2007 to make preliminary evaluations of reasonable progress towards Cla ss I areas visibility goals. The 2007 inventory focused on the most significant point and area sour ces of visibility impa iring pollution. This effort included updating projecti ons of electric generating units and incorporating known and presumed BART emission levels.

During the spring of 2009, the WRAP once again updated emission inventory projections for point and area sources in the WRAP region to gi ve the most current assessment of reasonable progress towards visibility goals. Again, the updated projection inventory reflected new information about BART determinations and project ion of future fossil fuel plants needed to achieve 2018 federal electrical generation demands.

The results of the CMAQ modeling which has already been discussed shows anthropogenic emissions sources generally declining across th e West through 2018. However, natural sources such as wildfires and dust, international source s in Mexico and Canada, global transport of emissions and off shore shipping in the Pacific Ocean all appear to offset improvements in visibility from controls on manmade sources . In spite of the la rge number of growing uncontrollable sources in the WRAP region, howev er, South Dakota does see a net visibility improvement at the South Dakota Class I areas through 2018. The net effect of all of the reductions in the WRAP region, known at the time of the most recent model run is demonstrated in the WRAP Class I Summary Tables shown below for each of the Class I areas in South

Dakota. Table 8-1 provides a summary of the results for each Class I area for the 20% most impaired days.

Table 8-1– CMAQ Modeling Visibility Sum mary for 20% Most Impaired Days (a) Badlands National Park RRF Calculations Method: Specific Days (EPA)

Emissions Scenarios: 2000-04 Baseline (plan02d_rev) and 2018 PRPb (prp18b)

Monitored Estimated Projected

Baseline to

Baseline to 2018

2018 Baseline to 2018 Change In

Uniform 2018 Change In Anthropogenic

2000-04 2064 Rate of 2018 Change In Upwind Upwind

Baseline Natural Progress Visibility Statewide Weighted Weighted

Conditions Conditions Target Conditions Emissions Emissions 4 Emissions 4

(Mm-1) 1 (Mm-1) 2 (Mm-1) 3 (Mm-1) (tons/%) (%) (%)

Sulfate 18.85 1.19 13.13 15.61 -8,115

-36% -30% -30%

Nitrate 5.85 0.86 4.51 5.23 -26,347

-18% -27% -37%

Organic

Carbon 11.78 4.10 9.68 11.73 -555

-6% -3% -7%

Elemental 2.59 0.34 2.02 2.13 -2,404 -30% -45%125 RRF Calculations Method: Specific Days (EPA)

Emissions Scenarios: 2000-04 Baseline (plan02d_rev) and 2018 PRPb (prp18b)

Monitored Estimated Projected

Baseline to

Baseline to 2018

2018 Baseline to 2018 Change In

Uniform 2018 Change In Anthropogenic

2000-04 2064 Rate of 2018 Change In Upwind Upwind

Baseline Natural Progress Visibility Statewide Weighted Weighted

Conditions Conditions Target Conditions Emissions Emissions 4 Emissions 4

(Mm-1) 1 (Mm-1) 2 (Mm-1) 3 (Mm-1) (tons/%) (%) (%)

Carbon -51%

Fine Soil 0.98 0.95 0.97 0.94 1,837

6% 3% 9%

Coarse

Material 5.94 4.04 5.48 Not Applicable 5 25,873

16% 2% 8%

Sea Salt 0.19 0.19 0.19 Not Applicable 5 Not Applicable Not Applicable Not Applicable

Total Light

Extinction 57.18 22.67 45.98 52.73 Not Applicable Not Applicable Not Applicable

Deciview 17.14 8.06 15.02 16.32 Not Applicable Not Applicable Not Applicable

1 – Baseline values derived from Table 4.3(b), except for the deciview values. The deciview value was derived from Table 3-7;

2 – Deciview value derived from Table 3-7;

3 – 2018 Uniform Rate of Progress Target for Best 20 % Days is not defined. The Deciview value was derived from Figure 3-5(a);

4 – Results based on Weighted Emissions Pote ntial analysis using the 2000-04 Baseline (plan02d _rev ) & 2018 PRPb (prp18b) emissions scenarios; and

5 – Visibility projections not availabl e due to model performance issues.126 (b) Wind Cave National Park RRF Calculations Method: Specific Days (EPA) Emissions Scenarios: 2000-04 Baseline (plan02d) and 2018 PRPb (prp18b)

Monitored Estimated Projected

Baseline to

Baseline to 2018

2018 Baseline to 2018 Change In

Uniform 2018 Change In Anthropogenic

2000-04 2064 Rate of 2018 Change In Upwind Upwind

Baseline Natural Progress Visibility Statewide Weighted Weighted

Conditions Conditions Target Conditions Emissions Emissions 4 Emissions 4

(Mm-1) 1 (Mm-1) 2 (Mm-1) 3 (Mm-1) (tons/%) (%) (%)

Sulfate 13.32 1.09 9.53 11.33 -8,115

-36% -21% -22%

Nitrate 7.07 1.21 5.41 6.12 -26,347

-18% -24% -30%

Organic

Carbon 13.39 4.4 10.77 12.93 -555

-6% -1% -5%

Elemental

Carbon 2.96 0.4 2.28 2.32 -2,404

-51% -21% -41%

Fine Soil 0.86 0.97 0.88 0.93 1,837

6% 8% 16%

Coarse

Material 3.53 3.8 3.59 Not Applicable 5 25,873

16% 5% 13%

Sea Salt 0.00 0.03 0.03 Not Applicable 5 Not Applicable Not Applicable Not Applicable

Total Light

Extinction 51.18 21.90 41.71 47.19 Not Applicable Not Applicable Not Applicable

Deciview 15.84 7.41 13.94 15.12 Not Applicable Not Applicable Not Applicable

1 – Baseline values derived from Table 4.4(b), except for Deciview. The Deciview value was derived from Table 3-7;

2 – Deciview value derived from Table 3-7;

3 – 2018 Uniform Rate of Progress Target for Best 20 % Days is not defined. The Deciview value was derived from Figure 3-5(b);

4 – Results based on Weighted Emissions Poten tial analysis using the 2000-04 Baseline (plan02d) & 2018 PRPb (prp18b) emissions scenarios; and

5 – Visibility projections not availabl e due to model performance issues.



### 9.0 Monitoring Strategy

In accordance with 40 CFR § 51.308(d)(4), the State Implementation Plan for the Regional Haze Program is required to include a monitoring st rategy for measuring, char acterizing and reporting of regional haze visibility impairment that is repres entative of all Class I areas within the state.127 The monitoring strategy must be coordinated with the monitoring strategy required in 40 CFR § 51.305. In accordance with 40 CFR § 51.305, the monitoring strategy must take into account current and anticipated vi sibility monitoring research, the ava ilability of appropriate monitoring techniques, and such guidance as provided by EP A. In addition, the monitoring strategy must provide for the consideration of available visibi lity data and must provide a mechanism for its use in decisions making. Compliance with this requirement may be met through the participation in the IMPROVE network.

DENR has been and will continue to participate in the IMPROVE network for both of its Class I areas. The IMPROVE network currently collects and reports aerosol monitoring data which will be used to track long term reasonable progress. Because the long term tracking program with an implementation period nominally set for 60 years, the state expects that the IMPROVE network will provide data based on the following goals:

1. Maintain a stable configurati on of the individual monitors an d sampling sites and stability in network operations for the purpose of continuity in tracking reasonable progress trends;

2. Assure sufficient data capture at each s ite of all visibility-impairing species;

3. Comply with EPA quality control and assurance requirements; and

4. Prepare and disseminate periodic re ports on IMPROVE network operations.

DENR is relying on the IMPROVE network to meet these monitoring operation and data collection goals, with the fundamental assumptio n that network data co llection operations will not change, or if changed, will remain directly comparable to those operated by the IMPROVE network during the 2000 to 2004 baseline period. Technical analyses and reasonable progress goals in this implementation plan are based on da ta from these sites. As such, DENR will work with EPA and the Federal Land Managers to ensure these monitors continue to operate and any changes to the IMPROVE network will not jeopar dize the use of the data in the monitoring

strategy.

The state of South Dakota depends on the fo llowing IMPROVE program-operated monitors at the following sites listed in Table 9-1 for tracking reasonable progress:

Table 9-1– IMPROVE Monitoring Sites at Class I areas in South Dakota IMPROVE Monitoring Sites Class I Area

BAD1 Badlands National Park

WICA1 Wind Cave National Park

In accordance with 40 CFR § 51.308(d)(4)(i), DENR will also operate additional non-IMPROVE monitors that may be used in assessing if r easonable progress goals in South Dakota’s Class I areas are being met. These may include PM2.5 speci ation or Federal Reference Methods, and/or more portable monitoring systems than operated at an IMPROVE site. This data is collected throughout the state but the ambient air quality monito ring sites of particular interest are the ones

located next to the IMPROVE sites in the Class I areas in South Dakota. The data collected by these sites, along with data from the others si tes throughout the state are reported to EPA’s AIRS128 database. Table 9-2 provides a summary of what DENR is currently monitoring next to the

IMPROVE sites in the Cla ss I area in South Dakota.

Table 9-2– Ambient Air Monitoring Site Parameters Next to IMPROVE Sites

Monitoring Site Parameter Sampling &Analysis

Method Operating

Schedule

Badlands National Park AQS# Sulfur Dioxide Instrumental pulsed

florescent Continuous

Nitrogen Dioxide Instrumental

chemiluminescence Continuous

Ozone Instrumental ultra violet Continuous

PM 2.5 Met One BAM – 1020 Very Sharp Cut Cyclone

Gravimetric Continuous

PM 10 Thermal Anderson Series

FH62 C14 BETA

Gravimetric Continuous

Wind Speed Electronic signal Continuous Wind Direction Electronic signal Continuous

Ambient Temperature Electronic signal Continuous

Delta Temperature Electronic signal Continuous

Ambient Pressure Barometric pressure

transducer Continuous

Solar Radiation Pyranometer Continuous

Relative Humidity Hygroscopic Plastic Film Continuous

Wind Cave National Park AQS# Sulfur

Dioxide Instrumental Pulsed

Florescent Continuous

Nitrogen Dioxide Instrumental

Chemiluminescence Continuous

Ozone Instrumental Ultra Violet Continuous

PM 2.5 Met One BAM – 1020 Very Sharp Cut Cyclone

Gravimetric Continuous

PM 10 Thermal Anderson Series

FH62 C14 BETA

Gravimetric Continuous

Wind Speed Electronic signal Continuous Wind Direction Electronic signal Continuous

Ambient Temperature Electronic signal Continuous

Ambient Pressure Barometric Pressure Continuous129 Monitoring Site Parameter Sampling &Analysis

Method Operating

Schedule

Transducer

Relative Humidity Hygroscopic Plastic Film Continuous

In accordance with 40 CFR § 51.308(d)(4)(ii), DE NR will use data reported by the IMPROVE program as part of the regi onal technical support analysis tools found at the Visibility Information Exchange Web System (VIEWS), as well as other analysis tools that are available. DENR will participate in the ongoing regional analysis activities to collectively assess and verify the progress toward reasonable pr ogress goals, also supporting in terstate consu ltation as the regional haze rules are implement ed and collaborate with EPA, states, tribes, and federal land managers to ensure the continue d operation of these technical support analys is tools and systems

. In accordance with 40 CFR § 51.308(d)(4)(iv), DENR will depend on the routine timely reporting of haze monitoring data by the IM PROVE program for the reasonable progress tracking sites to the EPA air quality data system and VIEWS. DENR will collaborate with EPA, states, tribes, and federal land managers to en sure the continued operation of these technical support analysis tools and systems.

In accordance with 40 CFR § 51.308(d)(4)(vi), DENR w ill track data related to the regional haze plan implementation for sources for which the state has regulatory aut hority and will depend on the IMPROVE program and working with states a nd other organizations to collect and analyze efforts and data support systems for monitoring and emissions inventory data, respectively. To ensure the availability of data and analyses to report on visibility condi tions and progress toward Class I area visibility go als, the state of South Dakota will co llaborate with EPA, states, tribes,

and FLMs to ensure the continued operation of the IMPROVE program.



### 10.0 Consultation Requirements

10.1 Federal Land Manager Consultation

In accordance with 40 CFR § 51.308(i)(1), a state is required to provide written notification to the federal land managers the title of the official to which the federal land managers of any Class I area can submit any recommendations on the implementation of the state’s Regional Haze Program. DENR provided the state’s contac t to the federal land managers through its

involvement with WRAP.

WRAP represents a conglomeration of stake holders representing federal land managers, industry, states, tribes, environmental groups an d the general public. Th rough participation in this process, a significant portion of the cons ultation process with federal land managers and other states has been met. In the WRAP proce ss these stakeholders participated in various forums to help develop a coordi nated emissions inventory and an alysis of the impacts sources have on regional haze in the west. Coordination and evaluation of monitoring data and modeling processes were also overseen by WRAP partic ipants. Through these coordinated technical evaluations, a regional haze orient ed evaluation of South Dakota's Class I areas was constructed.130 South Dakota has been a participating member of the WRAP since its inception. The WRAP completed a long-term strategic plan in 2003. Th e Strategic Plan provid es the overall schedule and objectives of the annual work plans and ma y be revised as appropriate. Among other things, the Strategic Plan (1) identifies major products an d milestones; (2) serves as an instrument of coordination; (3) provides the direction and tr ansparency needed to foster stakeholder participation and consensus-based decision ma king, which are key features of the WRAP process; and (4) provides guidance to the indi vidual plans of WRAP forums and committees.

Much of the WRAP’s effort is focused on regional technical analysis that serves as the basis for developing strategies to meet the regional haze rule requirements to demonstrate reasonable progress towards natural visibility conditions in Class I areas. This includes the compilation of emission inventories, air quality modeling, a nd ambient monitoring and data analysis. The WRAP is committed to using the most recent and scientifically acceptable data and methods. The WRAP does not sponsor basic research, but WRAP committees a nd forums interact with the research community to refine and incorporate th e best available tools and information pertaining

to western haze.

In accordance with 40 CFR § 51.308(i)(2), a state is required to provide the federal land managers with an opportunity fo r consultation, in person and at least 60 days prior to holding any public hearing on the state’s regional haze program or revisions to the program. The consultation shall include an opportu nity to discuss the following:

1. Assessment of impairment of visibility in any mandatory Class I area; and

2. Recommendations on the development of the reasonable progress goal and on the development and implementation of strategi es to address visibility impairment.

DENR is committed to providing the federal la nd managers opportunities to provide input as South Dakota’ State Implementation Plan for the regional haze program is developed and implemented. This includes providing the federa l land managers with at least 60 days prior notice to any public hearing. On January 15, 201 0, DENR fulfilled this obligation and submitted South Dakota’s draft Regional Haze Program to the following Federal Land Managers:

1. Tim Allen, U.S. Fish & Wildlife Service, Lakewood, Colorado;

2. Trent Wickman, USDA Forest Service, Great Lakes National Forests – Eastern Region;

3. John Bunyak, National Park Service, Air Resources Division, Lakewood, Colorado;

4. John Notar, National Park Service, Ai r Resources Division, Lakewood, Colorado;

5. Brian Kenner, National Park Servi ce, Badlands National Park; and

6. Ken Hyde, National Park Servi ce, Wind Cave National Park.

In addition, DENR took this opportunity to solicit comm ents from the following:

1. Laurel Dygowski, EPA Region VIII;

2. Amy Platt, EPA Region VIII;

3. Monica Morales, EPA Region VIII;

4. Catherine Nueschler and Anne Jackson, State of Minnesota;131 5. Teresa Cooper and Asad Khan, State of Michigan;

6. Shelley Schneider and Katryna Schaf, State of Nebraska;

7. Dana Mount and Tom Bachman, State of North Dakota;

8. Curtis Taipale, State of Colorado;

9. Dave Klemp, State of Montana;

10. Tina Anderson, State of Wyoming;

11. Jim Strain, South Dakota Department of Agriculture;

12. Gene Nelson, GCC Dacotah, Rapid City, SD;

13. Tim Rogers, Black Hills Cor poration, Rapid City, SD;

14. Danielle Weibers, Pete Lien and Sons, Rapid City, SD;

15. Clint Allen, Hills Materials Company, Rapid City, SD; and

16. Terry Graumann, Otter Tail Po wer Company, Big Stone I.

DENR requested comments by March 16, 2010. DENR received comments from the United States Department of Agriculture – Forest Service, United Stat es Department of Interior – National Park Service, Otter Tail Power Co mpany, and the United States Environmental Protection Agency (EPA) – Region 8.

10.1.1 Addressing Federal Land Manager Recommendations

In accordance with 40 CFR § 51.308(i)(3), in deve loping any implementation plan or revision,

the state must include a descri ption of how it addressed any comments provided by federal land managers. The comments from the federal la nd managers, Otter Tail Power Company, and EPA and DENR response to those comments may be reviewed in Appendix D.

10.1.2 Continued Consultation with Federal Land Managers

In accordance with 40 CFR § 51.308(i)(4), DENR must provide procedures for continuing

consultation between the state and federal land ma nagers on the implementation of the visibility protection program including the development and review of implementation plan revisions and 5-year progress reports and on the implementa tion of other programs having the potential to contribute to impairment of visibi lity in a Class I area. DENR is committed to working with the federal land managers to protect the Class I ar eas in South Dakota and in neighboring states. This will be accomplished with our continued involvement in re gional organizations and through our contacts with the federal land managers.

DENR has already involved the federal land ma nagers on other programs that may impact visibility in a Class I area through our PSD ai r quality permit program. Again, DENR has an open door policy in which the federal land mana gers can submit recommendations in an ongoing

basis.

10.2 Consultation with Other States

In accordance with 40 CFR § 51.308(d)(1)(iv), in developing reasonable progress goals the state

must consult with those states which may reasonably be anticipate d to cause or contribute to visibility impairment in a Class I area with in the state. In accordance with 40 CFR §132 51.308(d)(3)(i), where a state’s emis sions are reasonably anticipated to cause or contribute to impairment in a Class I area located in another state or states, th at state must consult with the

other state or states in order to develop coordinated emission management strategies. DENR accomplished these requirements through WRAP and by contacting and working with states that are not part of WRAP.

As noted previously, DENR has been a participan t in WRAP since its inception and considers its involvement as fulfilling part of the require ments for consultation. Within WRAP, the Implementation Work Group (IWG) was formed to address states’ issues regarding Regional

Haze and conducted numerous face-to-face meeti ngs and monthly calls. All western states, EPA, Tribes and Federal Land Managers particip ated in the WRAP activ ities and were involved throughout the process.

DENR accomplished the requirement of working w ith states impacting Class I areas in South Dakota through WRAP and by contacting and working w ith states that are not part of WRAP to develop emission reductions. WRAP gathered in formation from what states were doing to

reduce air emissions that contribute to visibili ty impairment and provided that information to other states. The same information was used by WRAP in the 2018 projection models to determine the impacts those reductions will have on each Class I area.

Beyond WRAP, South Dakota was involved with th e Northern Class I Areas workgroup which had monthly conference calls and included Mi nnesota, Michigan, Iowa, along with other Midwestern states. In addition, South Dakota consulted with Mi nnesota directly starting in August of 2007 through emails and phone calls, which continued through December of 2009 when Minnesota submitted its Regional Haze Stat e Implementation Plan to EPA. DENR also consulted directly with the St ate of Nebraska over the past few years through email and phone calls, mostly in regards to impacts the Gerald Gentleman Power Plant has on visibility impairment in Class I areas in South Dakota and th eir plans to control emi ssions from the Gerald

Gentlemen Power Plant. As noted in a P ublic Notice dated May 28, 2009, the Nebraska Department of Environmental Quality determined BART shall be the replacement of the existing burner equipment system on Unit 2, a coal-fired electric generating unit, with a new Low NOx burner equipment system incl uding overfire air ports.

Otter Tail Power Company’s Big St one I facility is the only s ource in South Dakota that is reasonably anticipated to contribute to visibility impairment of a Cl ass I area in another state. Otter Tail Power Company’s BART analysis for Bi g Stone I demonstrated that its air emissions were reasonably anticipated to contribute to impa irment at the Badlands National Park in South Dakota; Theodore National Park in North Dakota; Boundary Waters and Voyageurs Class I areas in northern Minnesota and the Isle Royale fede ral Class I area in Michigan. DENR notified

these states and submitted Otter Tail Powe r Company’s case-by-case BART analysis and DENR’s review of the BART analysis for thei r comments. DENR did not receive any comments from Minnesota or Michigan.

DENR reviewed the BART analysis and determ ined the proper air emission limits for the regulated air pollutants that are reasonably anticipa ted to contribute to impairment in the Class I areas. DENR will established the BART proce dures in the Administrative Rules of South133 Dakota that are equivalent to federal regulation in 40 CFR Pa rt 51 and will adopt the BART emission limits in an air quality constructi on permit and eventually in Otter Tail Power Company’s Title V air quality operating permit for the Big Stone I facility. DENR believes the BART requirements for Big Stone I meets South Dakota’s obligation for emission reductions for those Class I areas impact ed by Big Stone I.

As stated above, DENR also sent South Dakota’ s draft Regional Haze State Implementation Plan to the following states on January 15, 2010:

1. Catherine Nueschler and Anne Jackson, State of Minnesota;

2. Teresa Cooper and Asad Khan, State of Michigan;

3. Shelley Schneider and Katryna Schaf, State of Nebraska;

4. Dana Mount and Tom Bachman, State of North Dakota;

5. Curtis Taipale, State of Colorado;

6. Dave Klemp, State of Montana; and

7. Tina Anderson, State of Wyoming.

DENR did not receive any comments from these states.

DENR did not experience any situation in which we disagreed with anot her state on a reasonable progress goal. DENR will continue to work with states to ensure South Dakota’s Class I areas achieve natural conditions by 2064 and air emi ssions from within South Dakota do not impair other state’s progress in ac hieving natural condition in their Class I areas by 2064.

10.3 Public Input

In accordance with 40 CFR § 51.308(d)(1)(ii), if th e state establishes a reasonable progress goal that provides a slower rate of im provement in visibility than the rate that would be needed to attain natural condition by 2064, the state must pr ovide the public an oppo rtunity to review as part of the implementation plan an assessment of the number of years it would take to attain natural conditions if visibility im provement continues at the rate of progress selected by the state

as reasonable.

Based on the modeling analysis WRAP conducted on visibility improvement in 2018, the reasonable progress goal will not be met for or ganic carbon mass, ammo nia nitrates, ammonia sulfates, and coarse particulates. The major contributor of ammonia sulfates and ammonia nitrates emissions at the two national parks is transported in from out of state. DENR has worked with other states through WRAP or indi vidually to ensure thei r contribution in South Dakota is minimized. However, until all of the states implement their approved regional haze rules it is hard to determine if the modeling assumptions used by WRAP in the analysis are correct. For instance, the WRAP analysis does not reflect the BART emission limits that will be implemented by Big Stone I or the BART emissi on limits other states are still developing for

their BART sources. DENR believes as states start implementing the Regional Haze Programs,

the ammonia sulfate and ammonia nitrate concentra tions will be reduced to meet the glide path sometime between now and 2018. Therefore, DENR believes that South Dakota can still meet its134 reasonable progress goals and achieve natural conditions by 2064. DENR will evaluate the progress on a periodic basis.

Although DENR believes it will still achieve natu ral conditions by 2064, EP A states DENR must include a projection of when WRAP’s modeling projects natural conditi ons will be achieved. Based on WRAP’s modeling results, which as stated above does not represent the final reductions in each state’s regional haze program, natural conditions in South Dakota may not be

achieved in the Badlands and Wind Cave Na tional Parks until 2265 and 2236, respectively.

DENR believes this is unrealistic and will contin ue to evaluate the projection as states begin implementing their Regional Haze State Implementation Plans.

DENR has also committed through this document to develop and implement a Smoke Management Plan by 2013. DENR will use the time from now until then to evaluate wildfires and prescribed fires to determine which size, distan ce, fuel material, etc. needs to be included in the Smoke Management Plan and the Best Manage ment Practices for minimizing the impacts of wildfires and prescribed fires on South Dakota’s two Class I areas.

DENR is also required to provide public input when adopting rules. DENR will provide the public an opportunity to comment on the propos ed regional haze program and provide testimony at a public hearing that will be held in front of the Board of Minerals and Environment. The comments from the public and others and DENR response to those comments may be reviewed in Appendix E.



### 11.0 Periodic Review

11.1 Evaluation and Reassess Every 10 Years

In accordance with 40 CFR § 51.308(f), DENR w ill review, revise, and submit revisions to South Dakota’s State Implementation Plan by July 31, 2018, and every ten years thereafter. The

review shall consist of DENR ev aluating and reassessing all of th e elements required in 40 CFR § 51.308(d), taking into account improvements in monitoring data collection and analysis techniques, control technologies, an d other relevant factors. Th e evaluation and reassessing shall address at least the following:

1. In accordance with 40 CFR § 51.308(d)(2)(iv)(B), current visibility conditions for the 20% most impaired and 20% least impaire d days, and actual progress made towards

natural conditions duri ng the previous implementation pe riod. The period for calculating current visibility conditions is the most re cent five year period preceding the required date of the implementation plan submittal for which data are available. Current visibility

conditions must be calculated ba sed on the annual average level of visibility impairment for the most and least impaired days for each of these five years. Current visibility conditions are the average of these annual values;

2. The effectiveness of the long-term strategy for achieving reasonable progress goals over the prior implementation period(s); and

3. Affirmation of, or revision to, the reasona ble progress goal in accordance with the procedures set forth in 40 CFR § 51.308(d )(1). If DENR established a reasonable135 progress goal for the prior period which provi ded a slower rate of progress than that

needed to attain natural cond itions by the year 2064, DENR must evaluate and determine the reasonableness, based on the factors in 40 CFR § 51.308(d)(1)(i)(A), of additional measures that could be adopted to achieve th e degree of visibility improvement projected by the analysis contained in the first im plementation plan described in 40 CFR § 51.308(d)(1)(i)(B).

DENR will also coordinate with EPA to conduct th ese reviews jointly to satisfy the requirements of 40 CFR § 51.306(c).

11.2 Report Every 5 Years

In accordance with 40 CFR § 51.308(g), DENR will ev aluate and report its progress towards the reasonable progress goal for each mandatory Clas s I federal area located within South Dakota and in each mandatory Class I federal area locate d outside the state which may be affected by emissions from within the state. The first progress report is due 5 years from submittal of DENR’s initial implementation plan for Sout h Dakota’s Regional Haze Program and every 5 years thereafter. The progress reports will be in the form of an implementation plan revision that complies with the procedural requirement s of 40 CFR §§ 51.102 and 51.103. The periodic progress reports shall contain at a minimum the following elements:

1. A description of the status of implemen tation of all measures included in the implementation plan for achieving reasonabl e progress goals for mandatory Class I

federal areas both within and outside South Dakota;

2. A summary of the emissions reduction s achieved throughout South Dakota through implementation of the measures de scribed in 40 CFR § 51.308(g)(1);

3. For each mandatory Class I federal area w ithin South Dakota, DENR will assess the following visibility conditions and changes with values for most impaired and least impaired days expressed in terms of 5- year averages of these annual values:

a. The current visibility conditions for the most impaired and least impaired days;

b. The difference between current visibility c onditions for the most impaired and least impaired days and baseline visibility conditions;

c. The change in visibility impairment for th e most impaired and least impaired days over the past 5 years;

4. An analysis tracking the change over the past 5 years in emissions of pollutants contributing to visibility impairment from a ll sources and activities within South Dakota. Emissions changes should be identified by type of source or activity. The analysis must be based on the most recent updated emissi ons inventory, with estimates projected forward as necessary and appropriate, to account for emissions changes during the applicable 5-year period;

5. An assessment of any significant changes in anthropogenic emissions within or outside South Dakota that have occurred over the pa st 5 years that have limited or impeded progress in reducing pollutant emissions and improving visibility;

6. An assessment of whether the current implementation plan elements and strategies are sufficient to enable South Dakota, or other states with mandatory Class I federal areas136 affected by emissions from South Dakota, to meet all established reasonable progress goals.

7. A review of DENR's visibility monitoring st rategy and any modificat ions to the strategy

as necessary.

DENR will coordinate with EPA as it develops its long term stra tegy for reasonably attributable visibility impairment under 40 CFR § 51.306(c).

11.3 Determination of Adequacy

In accordance with 40 CFR § 51.308(h), at the same time that DENR is required to submit any 5- year progress report to EPA in accordance with 40 CFR § 51.308(g), DENR will also take one of the following actions based upon the information presented in the progress report:

1. If DENR determines the existing implementa tion plan requires no further substantive

revision at this time in order to achieve esta blished goals for visibility improvement and emissions reductions, DENR must provide EPA with a negative declaration that further revision of the existing implementation plan is not needed at this time;

2. If DENR determines that the implementation plan is or may be inadequate to ensure reasonable progress due to emissions from sources in another state(s) which participated in a regional planning process, DENR must provide notification to EP A and to the other state(s) which participated in the regional planning pr ocess with DENR. DENR must also collaborate with the other state(s) thr ough the regional planning process for the purpose of developing additional strategies to address the plan's deficiencies;

3. Where DENR determines that the implementation plan is or may be inadequate to ensure reasonable progress due to emissions from sour ces in another country, DENR shall provide notification, along with availabl e information, to EPA; and

4. Where DENR determines that the implementation plan is or may be inadequate to ensure reasonable progress due to emissions from sour ces within South Dakota, DENR shall revise its implementation plan to address the plan's de ficiencies within one year from the date the progress report is due.

# Appendix A

Otter Tail Power Company’s BART Modeling Protocol

and Approval Letter

# Appendix B

Otter Tail Power Company’s Visibility Impact Analysis

# Appendix C

Otter Tail Power Company’s Case-by-Case BART Analysis

# Appendix D

Federal Land Managers’ Comments

and DENR’s Response

# Appendix E

Public Notice Comments

and DENR’s Response

# APPENDIX F

WRAP’s FOUR FACTOR ANALYSIS

FOR

GCC DACOTAH

AND BLACK HILLS CORPORATION (BEN FRENCH)

# APPENDIX G

VISIBILITY MODELING RESULTS FOR

GCC DACOTAH

# APPENDIX H

VISIBILITY MODELING RESULTS FOR

BLACK HILLS CORPORATION

BEN FRENCH

# APPENDIX I

VISIBILITY MODELING RESULTS FOR

PETE LIEN AND SONS, INC