# State of Kansas

Air Quality State Implementation Plan



# Regional Haze

October 26, 2009

Our Vision - Healthy Kansans living in safe and sus tainable environments

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# Department of Health and Environment Division of Environment Bureau of Air (785) 296-60242 Table of Contents

List of Tables.....................................

................................................... ................................................... .....................3
List of Figures ....................................

................................................... ................................................... ....................4
List of Appendices .................................

................................................... ................................................... ................5

Submittal Letter...................................

................................................... ................................................... ..................6
Executive Summary..................................

................................................... ................................................... .............7
1. Background and Overview of the Federal Regional Haze Regulation................................... ............................9 1.1 General Background / History of Federal Regiona l Haze Rule ........................................ ..................................9 1.2 States and Tribes without Class I Areas........

................................................... .................................................10
2. General Planning Provisions....................

................................................... ................................................... ......11
3. Regional Planning..............................

................................................... ................................................... .............12
4. State and Federal Land Manager Coordination....

................................................... .........................................14

5. Assessment of Baseline and Current Conditions a nd Estimate of Natural Conditions in Class I Areas . .....15
6. Monitoring Strategy ............................

................................................... ................................................... ...........17 6.1 Current Monitoring Strategy....................

................................................... ................................................... ...17 6.1.1 Measuring Visibility Data ....................

................................................... ..................................................1 7 6.1.2 Characterizing Visibility Data...............

................................................... .................................................20 6.1.3 Data Validation and Reporting................

................................................... ...............................................21 6.2 Special Monitoring Studies.....................

................................................... ................................................... ....21 6.3 Future Monitoring Strategy .....................

................................................... ................................................... ...22
7. Emissions Inventory ............................

................................................... ................................................... ...........23 7.1 Inventory Results ..............................

................................................... ................................................... ..........23 7.2 Point Sources ..................................

................................................... ................................................... ............24 7.2.1 Natural Gas Compressor Stations..............

................................................... .............................................25 7.2.2 Fuel Ethanol Manufacturing Facilities ........

................................................... ...........................................26 7.3 Nonpoint Sources...............................

................................................... ................................................... .........26 7.4 On-Road Mobile Sources.........................

................................................... ................................................... ...29 7.5 Nonroad Mobile Sources .........................

................................................... ................................................... ...29 7.6 Nonpoint Fires .................................

................................................... ................................................... ...........29 7.7 Reporting ......................................

................................................... ................................................... ..............30
8. Modeling Assessment............................

................................................... ................................................... ..........32 8.1 Model Inputs...................................

................................................... ................................................... ............33 8.2 Model Performance Evaluation ...................

................................................... ..................................................3 3 8.2.1 Sulfate (SO 4 ) Model Performance................................

................................................... ..........................34 8.2.2 Nitrate (NO 3 ) Model Performance ................................

................................................... .........................34 8.2.3 Organic Matter Carbon (OMC) Model Performance

................................................... .............................36 8.2.4 Other PM 2.5 (soil) Model Performance..........................

................................................... .........................36 8.3 Base G Model Simulations .......................

................................................... ................................................... ..37 8.4 Information from Modeling Performed by Other RP Os ................................................. ..................................39 8.4.1 MRPO .........................................

................................................... ................................................... ........39 8.4.2 VISTAS.......................................

................................................... ................................................... ........39 8.4.3 WRAP .........................................

................................................... ................................................... ........39 8.5 Control Strategy Simulations...................

................................................... ................................................... ...40
9. Best Available Retrofit Technology.............

................................................... ................................................... ..44 9.1 BART Eligible Sources in the State of Kansas...

................................................... ...........................................443

9.2 Determination of Sources Subject to BART.......

................................................... ...........................................46 9.3 Determination of BART Requirements for Subject- to-BART Sources.................................... ........................48 9.3.1 Kansas City Power & Light (KCP&L)............

................................................... .......................................49 9.3.2 Westar Energy................................

................................................... ................................................... .....50 9.4 Projected Emissions Reductions Resulting from I nstallation of BART Controls....................... ......................51 9.5 Enforceability of BART Requirements............

................................................... ..............................................51 9.6 Monitoring, Recordkeeping, & Reporting of BART Requirements ....................................... ..........................52
10. Reasonable Progress Goals / Long Term Strategy

................................................... .......................................54 10.1 Determining Visibility Impact .................

................................................... ................................................... .54 10.1.2 Light Extinction at Wichita Mountains .......

................................................... .........................................57 10.2 Selection of Kansas Sources for Reasonable Pro gress Evaluation ................................... ..............................60 10.3 Reasonable Progress Conclusions...............

................................................... .................................................72 10.4 Long-Term Strategy............................

................................................... ................................................... ......74 10.4.1 Share of Emission Reductions................

................................................... ..............................................74 10.4.1.1 Baseline Inventory........................

................................................... ..................................................7 4 10.4.2 Anthropogenic Sources of Visibility Impairme nt ................................................. ..................................74 10.4.3 Factors the State Must Consider.............

................................................... ..............................................75 10.4.3.1 Emission Reductions Due to Ongoing Air Pol lution Programs .................................... ....................75 10.4.3.2 Measures to Mitigate the Impacts of Constr uction Activities .................................. .........................81 10.4.3.3 Emission Limitations and Schedules of Comp liance ............................................. ...........................82 10.4.3.4 Source Retirement and Replacement Schedule s .................................................. .............................83 10.4.3.5 Agricultural and Forestry Smoke Management

................................................... ..............................83 10.4.3.6 Enforceability of Emission Limitations and Control Measures.................................. .......................83 10.4.3.7 Anticipated Net Effect on Visibility Resul ting from Projected Changes to Emissions........... ..........83

11. Consultation ..................................

................................................... ................................................... ................85

11.1 Consultation..................................

................................................... ................................................... ............85 11.1.1 Arkansas and Missouri .......................

................................................... ..................................................8 5 11.1.2 Texas .......................................

................................................... ................................................... ..........86 11.1.3 Oklahoma ....................................

................................................... ................................................... ......86
12. Plan Revisions and Progress Reports...........

................................................... ..................................................8 9
13. Determination of the Adequacy of the Existing Plan............................................... ........................................90

14. Reference Information .........................

................................................... ................................................... ........91

14.1 List of References ............................

................................................... ................................................... .........91 14.2 List of Acronyms and Abbreviations ............

................................................... ...............................................91

List of Tables Table 3.1 CENRAP Geographical Area .................

................................................... ..................................................1 2 Table 7.1 2002 Kansas Emissions Summary, by Source Category and Pollutant ............................. ..........................23 Table 7.2 2018 Kansas Projected Emissions Summary, by Source Category and Pollutant ................... ....................24 Table 7.3 Percent Changes in Kansas Air Emissions, by Source Category and Pollutant, from 2002 to 2018 ...........24 Table 7.4 Total 2018 Reductions in NO x and SO 2 from Kansas Emission Sources Subject to BART...... ..................25 Table 7.5 2002 Top PM 10 Emissions from Kansas Nonpoint (Area) Sources .....

................................................... .....27 Table 7.6 2002 Top VOC Emissions from Kansas Nonpoi nt (Area) Sources.................................. ...........................27 Table 7.7 2002 Top NO x Emissions from Kansas Nonpoint (Area) Sources .....

................................................... ......28 Table 7.8 2002 Top SO 2 Emissions from Kansas Nonpoint (Area) Sources.....

................................................... .......28 Table 8.1 Kansas NO x Sources Included in the CENRAP Control Strategy Ru n Using the 2018 Base G Inventory .41 Table 8.2 Kansas SO 2 Sources Included in the CENRAP Control Strategy Ru n Using the 2018 Base G Inventory..41 Table 9.1 Facilities with BART-Eligible Units in th e State of Kansas.................................. ......................................45 Table 9.2 Kansas BART-Eligible Emission Units with at Least One > 0.5 dv Visibility Impact Day on Sele cted Class I Areas during 2001–2003 .....................

................................................... ................................................47 Table 9.3 Kansas Facilities with Units Subject to B ART under the Regional Haze Rule................... ........................484

Table 9.4 BART Presumptive Limits and Operational S tandards for NO x and SO 2 at Subject-to-BART Emission Units in Kansas ....................................

................................................... ................................................... ........49 Table 9.5 Projected Emissions Reductions from 2002 Levels after Installation of BART Controls for the Subject-toBART Emission Units in Kansas......................

................................................... ..............................................51 Table 10.1 2018 Percent Total and Absolute Light Ex tinction Value for Worst 20% Visibility Days at Ele ven Class I Areas Due to Kansas Air Emission Sources ...........

................................................... ........................................56 Table 10.2 2018 Percent Total Light Extinction > 0. 5% Due to Kansas Sources for Worst and Best 20% Vis ibility Days for the Wichita Mountains Class I Area........

................................................... .........................................57 Table 10.3 Light Extinction Attributable to Kansas Emission Sources at Wichita Mountains Class I Area, by Source Category and Particulate Species ...................

................................................... .................................................59 Table 10.4 Kansas Emission Units Not Subject to BAR T Emitting at Least 500 Tons/Yr of NO x or SO 2 in 2002 ....62 Table 10.5 Refinements to AirControlNET Control Tec hnology Determinations ............................. .........................63 Table 10.6 Sources with Cost per Ton Reduced Greate r than $10,000/ton................................. ................................63 Table 10.7 Most Effective Control Technologies with Acceptable Control Costs for Kansas 500-Ton NO x and SO 2 Emission Units .....................................

................................................... ................................................... ........64 Table 10.8 Overall Visibility Improvements Resultin g from Application of Most Effective Controls at Se lected Kansas 500-Ton NO x and SO 2 Emission Units....................................

................................................... ...........66 Table 10.9 Selected Kansas 500-ton NO x and SO 2 Emission Units Showing Significant Visibility Impr ovement Resulting from Application of Most Effective Contro ls ................................................. ...................................67 Table 10.10 Ranked List of Kansas Facilities, Emiss ion Units, and Controls after Cost and Visibility S creening.....68 Table 10.11 Summary of Reasonable Progress Non-Cost Statutory Factors for Selected Kansas Point Source s .......69 Table 10.12 Ranked List of Sources under the Reason able Progress Analysis ............................. ..............................71 Table 10.13 Kansas Sources Identified in the Contro l Strategy PSAT Run ................................ ................................73 Table 10.14 Additional Measures Implemented under t he Long-Term Strategy to Meet Reasonable Progress G oals

................................................... ................................................... ................................................... ..................82 Table 10.15 Net 2002 to 2018 Improvement in Visibil ity at Selected Class I Areas Due to BART Controls in Kansas

................................................... ................................................... ................................................... ..................84 Table 11.1 Kansas Sources Identified by Oklahoma as Potentially Impacting Visibility at Wichita Mounta ins ........87

List of Figures

Figure 3.1 Geographical Areas of Regional Planning Organizations ...................................... ....................................12 Figure 6.1 Kansas Improve Protocol Monitoring Netwo rk ................................................. ........................................17 Figure 6.2 Tallgrass Prairie Improve Protocol Monit oring Site ......................................... .........................................18 Figure 6.3 Cedar Bluff Improve Protocol Monitoring Site............................................... ...........................................19 Figure 6.4 Sac and Fox Improve Protocol Monitoring Site............................................... ..........................................20 Figure 7.1 2002 Emissions of Pollutants Contributin g to Regional Haze from Kansas Nonpoint Sources.... .............26 Figure 8.1 Light Extinction for 20% Worst Visibilit y Days at Wichita Mountains by Particulate Species, Showing Observed (Left) versus Modeled (Right) Values ......

................................................... ......................................35 Figure 8.2 Percent Visibility Extinction for the Be st and Worst 20% Days at Wichita Mountains......... ....................36 Figure 8.3 URP Glide Path for Wichita Mountains Cla ss I Area with 2018 Projected Results – 20% Worst D ays....38 Figure 8.4 URP Glide Path for Wichita Mountains Cla ss I Area with 2018 Projected Results - 20% Best Da ys.......38 Figure 8.5 Comparison of 2018 Modeling Results from CENRAP, VISTAS, WRAP, and MRPO .................... .......40 Figure 8.6 Comparison of Modeling Results from Base G and Control Strategy Runs ....................... .......................42 Figure 10.1 2018 Percent Total Light Extinction at Eleven Class I Areas from Kansas Sources, by Specie s, for All Source Categories during the Worst 20% Days ........

................................................... ......................................55 Figure 10.2 2018 Percent Total Light Extinction at Eleven Class I Areas from Kansas Air Emission Sourc es, by Source Category, for All Species during the Worst 2 0% Visibility Days................................. .........................56 Figure 10.3 Glide Path for Wichita Mountains Wilder ness Area, Oklahoma, in Terms of Light Extinction.. ............58 Figure 10.4 Population Growth for the State Of Kans as 1980-2005 and Projected Growth 2010-2020 ........ .............815 List of Appendices (The appendices are located on the enclosed compact disc.)

1.1 Guide to Locating 40 CFR § 51.308 Requirements 1.2 EPA Checklist for Regional Haze SIPs Submitted Under 40 CFR 51.308 2.1 Summary of Legal Authority, Public Participatio n Process, and Public Comments and Responses on SIP Drafts 4.1 Summary of Federal Land Manager Comments and Re sponses 4.2 US Department of the Interior Comments on the K ansas Regional Haze SIP 4.3 US Department of Agriculture Comments on the Ka nsas Regional Haze SIP 7.1 2002 Emissions Inventory 7.2 2018 Emissions Inventory 7.3 Emissions Inventory Technical Documentation 7.4 Natural Gas Production Trends 8.1 Emissions Modeling (TSD Chapter 2) 8.2 Model Performance Evaluation (TSD Chapter 3) 8.3 Additional Supporting Analysis (TSD Chapter 5) 9.1 Identification of BART-Eligible Sources in the State of Kansas 9.2 Modeling Protocol Used to Determine Subject-to- BART Sources 9.3 Results of Modeling to Screen for Sources Subje ct to BART 9.4 Guidance for Facilities Conducting a BART Analy sis 9.5 BART Analysis for KCP&L - La Cygne Units 1 and 2 9.6 BART Analysis for Westar Energy - Gordon Evans Unit 2 and Jeffrey Units 1 and 2 (including May 200 9 addendum for GEEC) 9.7 BART Agreements 9.8 BART Exemption modeling – Monarch Cement Kansas City BPU – Quindaro Kansas City BPU – Nearman Westar Energy – Hutchinson Westar Energy – Lawrence 10.1 PSAT Tool-Generated Tables 10.2 2018 Visibility Projections for CENRAP Class I Areas (TSD Appendix D) 10.3 Calculations for Emissions Reductions for Kans as Reasonable Progress Goals 10.4 Kansas Prescribed Fire Emissions 11.1 Sunflower Visibility Analysis Performed by KDH E 11.2 Holcomb Class I Visibility Modeling Report67

Executive Summary In amendments to the Clean Air Act (CAA) in 1977, C ongress set a national goal to restore national parks and wilderness areas to pristine con ditions by preventing any future, and remedying any existing man-made visibility impairme nt. In 1999, the U.S. Environmental Protection Agency (EPA) finalized the federal Regio nal Haze Rule, which aims to fulfill the goals set forth in the CAA by the year 2064. The R egional Haze Rule addresses the combined effects of several pollution sources over large geo graphic areas. It was therefore necessary to use a regional planning approach. EPA designated five regional planning organizations (RPOs); the Central Regional Air Planning Association (CENRAP) was designated as the RPO repr esenting the central portion of the United States. Since its inception, the State of Kansas h as been actively involved in CENRAP. The Kansas Regional Haze Plan incorporates data analyse s, modeling results, and technical support documents prepared for CENRAP members by various co ntractors. In addition, CENRAP has served as a platform for consultation between state s, tribes, federal land managers (FLMs), and stakeholders. The federal Regional Haze Rule requires states to s ubmit revisions to their State Implementation Plans by December 17, 2007. The Regional Haze Rule applies to all states that contribute to visibility impairment, even those states that do no t have Class I areas. Technical analyses has shown that, while Kansas sources only moderately im pact most Class I areas in the CENRAP region, Kansas sources have been identified by Okla homa as potential contributors to visibility impairment at the Wichita Mountains Class I area. States are required by 40 CFR 51.308 to set reasona ble progress goals for achieving natural visibility conditions, to develop a long-term emiss ions reduction strategy, and to maintain a monitoring network and emissions inventory to suppo rt regional haze programs. In addition, Section 51.308(e) outlines the requirements for app lying Best Available Retrofit Technology (BART) to certain older emission sources that were not previously regulated by the CAA. In July of 2005, EPA published a revised final rule , including Appendix Y to 40 CFR part 51, entitled “Guidelines for BART Determinations under the Regional Haze Rule.” Kansas followed these guidelines in its selection of sources that a re subject to BART requirements. Kansas has five subject-to-BART emission units at three facili ties. The BART requirements are outlined in Chapter 9 of this document. In addition to requiring BART controls at subject f acilities, the state also evaluated other sources to address reasonable progress goals. Kansas compl eted a multi-step analysis for large, nonBART sources which considered the cost of complianc e, the time necessary for compliance, the energy and non-air quality environmental impacts, a nd the remaining useful life of the source. This analysis is referred to as the statutory facto r analysis, or four-factor analysis. Several additional sources that were not subject to BART ha ve agreed to implement controls as part of the long-term strategy as outlined in Chapter 12 of this document. At the onset of the regional haze consultation proc ess, states relied heavily on the Clean Air Interstate Rule (CAIR), a rule that addresses the i nterstate transport of air pollution to downwind states. CAIR covered 28 eastern states plus the Di strict of Columbia, and would have reduced SO 2 emissions by an estimated 5.4 million tons and NO x emissions by an estimated 2 million tons by 2015. Affected states had the choice of ei ther meeting the state’s emission budget by8

requiring power plants to participate in a cap and trade system, or by means of a measure of the state’s choosing.

Although Kansas was not included in the final CAIR rulemaking, the rule was a major component in the underlying assumptions used to det ermine source apportionment because of the reductions expected in neighboring states with Clas s I areas.

In July 2008, the D.C. District Court of Appeals va cated the CAIR rule in its entirety. On September 24, 2008 EPA filed a petition for reheari ng or for a remand of the case without vacatur. On December 23, 2008, the D.C. Court of A ppeals remanded the case to EPA without vacatur so that EPA could remedy CAIR’s flaws as we re discussed in their July ruling. At this time, it is unclear what the ramifications of this decision may be to the regional haze program. Kansas will continue to coordinate in regional effo rts to reduce visibility impairment at Class I areas by maintaining a visibility monitoring networ k and emissions inventory, and providing periodic progress reports and SIP revisions as requ ired by the Regional Haze Rule.9

1. Background and Overview of the Federal Regional Haze Regulation

1.1 General Background / History of Federal Regiona l Haze Rule

In amendments to the Clean Air Act (CAA) in 1977, C ongress added Section 169 (42 U.S.C. 7491) setting forth the following national visibili ty goal of restoring pristine conditions in certain national parks and wilderness areas, which it named Class I areas:

Congress hereby declares as a national goal the pre vention of any future, and the remedying of any existing, impairment of vi sibility in mandatory Class I Federal areas which impairment results fro m man-made air pollution. Over the following years, modest steps were taken t o address the visibility problems in Class I areas. The control measures taken mainly addressed plume blight from specific pollution sources, and did little to address regional haze is sues in the Eastern United States. Plume blight is the visual impairment of air quality that manife sts itself as a coherent plume. This results from specific sources, such as a power plant smoke stack , emitting pollutants into a stable atmosphere. The pollutants are then transported in some directi on with little or no vertical mixing. When the CAA was amended in 1990, Congress added Se ction 169B (42 U.S.C. 7492) authorizing further research and regular assessment s of progress. In 1993, the National Academy of Sciences concluded: “current scientific knowledge is adequate and control technologies are available for taking regulatory ac tion to improve and protect visibility” (1). In addition to authorizing creation of visibility t ransport commissions and setting forth their duties, Section 169B(f) of the CAA specifically man dated creation of the Grand Canyon Visibility Transport Commission (Commission) to mak e recommendations to the U.S. Environmental Protection Agency (EPA) for the regio n affecting the visibility of the Grand Canyon National Park. Following four years of rese arch and policy development the Commission submitted its report to EPA in June of 1 996. This report, as well as the many research reports prepared by the Commission, contri buted invaluable information to EPA in its development of the federal Regional Haze Rule. EPA’s Regional Haze Rule was adopted July 1, 1999, and went into effect on August 30, 1999. The Regional Haze Rule aims at achieving national v isibility goals by 2064. This rulemaking addressed the combined visibility effects of variou s pollution sources over a wide geographic region. This wide-reaching pollution net meant tha t many states, even those without Class I Areas, would be required to participate in haze red uction efforts. EPA designated five regional planning organizations (RPOs) to assist with the co ordination and cooperation needed to address the visibility issue. The Central Regional Air Pla nning Association (CENRAP) was designated as the RPO to represent those states that make up t he midsection of the contiguous United States. On May 24, 2002, the U.S. Court of Appeals D.C. Dis trict Court ruled on the challenge brought by the American Corn Growers Association against EP A’s Regional Haze Rule of 1999. The Court denied industry’s challenge to the haze rule goals of natural visibility and no degradation requirements and remanded to EPA the Best Available Retrofit Technology (BART) provisions of the rule.10

EPA revised the Regional Haze Rule pursuant to the remand. Amendments to the rule and guidelines for BART were finalized on June 15, 2005 . To facilitate the review of this State Implementation Plan (SIP) by the EPA, federal land managers (FLMs), stakeholders, and the public, a guide is provided for locating 40 CFR Sec tion 308 Requirements in this document (see Appendix 1.1). The EPA Checklist for Regional Haze SIPs Submitted under 40 CFR 51.308 can be found in Appendix 1.2.

1.2 States and Tribes without Class I Areas

In accordance with 40 CFR 51.308(d), the State of K ansas must address regional haze in each mandatory Class I area located outside the State wh ich may be affected by emissions from within the State. Kansas consulted with states and tribes in the CENRAP region as outlined in Chapter 3 and Chapter 11. The State of Oklahoma has determ ined that Kansas emission sources contribute to visibility impairment at the Wichita Mountains Class I area. Other states in the region did not find Kansas sources to be significan t contributors to visibility impairment in Class I areas, at the present. New determinations could be made in the future by other states.

List of Chapter 1 Appendices

1.1 Guide to Locating 40 CFR Section 308 Requiremen ts 1.2 EPA Checklist for Regional Haze SIPs Submitted under 40 CFR 51.30811

2. General Planning Provisions

Pursuant to 40 CFR 51.308(a) and (b), the State of Kansas submits this SIP revision to meet the requirements of EPA’s Regional Haze Rule which was adopted to comply with the Clean Air Act. Elements of this plan address the requirement s pursuant to 40 CFR 51.308(d) which include regional planning, state and federal land m anager (FLM) coordination, setting reasonable progress goals, consulting with states that contain Class I areas, and developing a long-term strategy. This plan also addresses the Best Availa ble Retrofit Technology (BART) components of 40 CFR 50.308(e). In addition, this SIP contain s a commitment to provide plan revisions, periodic progress reports, and adequacy determinati ons.

The State of Kansas has adopted this SIP in accorda nce with Kansas Air Quality Statutes 65- 3005 et. seq.

The State of Kansas provided public notice in the K ansas Register on July 17, 2008, of the opportunity to comment on the SIP. In addition, Kansas also provided a copy of the SIP to the Iowa Tribe in Kansas and Nebraska, the Kickapoo Tri be, the Prairie Band Potawatomi Nation, and the Sac and Fox Nation. The State of Kansas h eld a public hearing regarding the SIP on August 20, 2008, in Topeka. Public comments were a ddressed and are summarized in Appendix 2.1.

The State of Kansas provided a second public notice in the Kansas Register on July 16, 2009, of the opportunity to comment on the revised SIP. In addition, Kansas also provided a copy of the revised SIP to the Iowa Tribe in Kansas and Nebrask a, the Kickapoo Tribe, the Prairie Band Potawatomi Nation, and the Sac and Fox Nation. Th e State of Kansas held a public hearing regarding the revised SIP on August 27, 2009, in To peka. Public comments were addressed and are summarized in Appendix 2.1.

List of Chapter 2 Appendices

2.1 Summary of Legal Authority, Public Participatio n Process, and Public Comments and Responses on SIP Drafts12

3. Regional Planning

In 1999, EPA and affected states/tribes agreed to c reate five RPOs to facilitate interstate coordination on Regional Haze SIPs. The State of K ansas is a member of the Central Regional Air Planning Association (CENRAP) RPO. Member stat es of CENRAP are listed in Table 3.1. Figure 3.1 is a map of all five regional planning o rganizations.

Table 3.1 CENRAP Geographical Area

Arkansas Iowa Kansas Louisiana Minnesota Missouri Nebraska Oklahoma Texas *Includes both state and tribal areas

Figure 3.1 Geographical Areas of Regional Planning Organizations13

The governing body of CENRAP is the Policy Oversigh t Group (POG). The POG is made up of 18 voting members representing the states and tribe s within the CENRAP region and non-voting members representing local agencies, EPA, Fish and Wildlife Service, Forest Service, and National Park Service. The POG facilitates communi cation with federal land managers, stakeholders, and CENRAP staff.

Since its inception, CENRAP has established an acti ve committee structure to address both technical and non-technical issues related to regio nal haze. The work of CENRAP is accomplished through five standing workgroups: Mon itoring, Emissions Inventory, Modeling, Communications, and Implementation and Control Stra tegies. Participation in workgroups is open to all interested parties. Ad hoc workgroups are formed by the POG to address specific issues. Ultimately, policy decisions are made by t he CENRAP POG.

CENRAP has adopted the approach that the Regional H aze Rule requires the states to “establish goals and emission reduction strategies for improvi ng visibility in all 156 mandatory Class I parks and wilderness areas.” The Regional Haze Rul e also encourages states and tribes to work together in regional partnerships.

This SIP utilizes data analyses, modeling results, and other technical support documents prepared for CENRAP members by contractors and provided thro ugh the CENRAP website or FTP site.

By coordinating with CENRAP and other RPOs, the Sta te of Kansas has worked to ensure that its long-term strategy, reasonable progress goals, and BART determinations provide sufficient reductions to mitigate impacts of sources from the State of Kansas on Class I areas.14

4. State and Federal Land Manager Coordination

Coordination between states and federal land manage rs (FLMs) is required by 40 CFR 51.308(i). FLMs are part of CENRAP’s POG and the membership on standing committees. FLMs have contributed to the development of technical and non -technical work as a result of that participation. In addition, opportunities have bee n provided by CENRAP for FLMs to review and comment on each of the technical documents deve loped by CENRAP and included in this SIP. The State of Kansas has provided agency conta cts to the FLMs as required. In development of this plan, the FLMs were consulted i n accordance with the provisions of 40 CFR 51.308(i)(2).

The State of Kansas sent copies of modeling protoco ls for BART screening, modeling results, and BART analyses to the FLMs. In addition, Kansas provided FLMs an opportunity for consultation, in person and at least 60 days prior to holding any public hearing on an implementation plan or plan revision.

During the consultation process, the FLMs were give n the opportunity to address their:

• Assessment of the impairment of visibility in any C lass I areas

• Recommendations on the development of reasonable pr ogress goals

• Recommendations on the development and implementati on of strategies to address visibility impairment.

The State of Kansas sent the draft SIP to the FLMs on November 1, 2007. The State of Kansas notified the FLMs of a public hearing to be held on August 20, 2008. A summary of FLM comments and responses are included in Appendix 4.1 to this plan. The letters received from the FLMs can be found in Appendix 4.2 and 4.3.

The State of Kansas sent the draft revised SIP to t he FLMs on July 16, 2009. The State of Kansas notified the FLMs of a public hearing held o n August 27, 2009. A summary of FLM comments and responses are included in Appendix 4.1 to this plan.

The State of Kansas will continue to coordinate and consult with the FLMs during the development of future progress reports and plan rev isions, as well as during the implementation of programs having the potential to contribute to v isibility impairment in the mandatory Class I

areas.

List of Chapter 4 Appendices

4.1 Summary of Federal Land Manager Comments and Re sponses 4.2 US Department of the Interior Comments on the K ansas Regional Haze SIP 4.3 US Department of Agriculture Comments on the Ka nsas Regional Haze SIP15

5. Assessment of Baseline and Current Conditions a nd Estimate of Natural Conditions in Class I Areas

The goal of the Regional Haze Rule is to restore na tural visibility conditions to the 156 Class I areas identified in the 1977 Clean Air Act Amendmen ts. Section 51.301(q) defines natural conditions: “Natural conditions include naturally occurring phenomena that reduce visibility as measured in terms of light extinction, visual range , contrast, or coloration.” Regional Haze SIPs must contain measures that make “reasonable progres s” toward this goal by reducing anthropogenic emissions that cause haze. Although Kansas does not have any Class I areas, this chapter is provided as background information to su pport the technical analyses presented throughout this document.

For each Class I area, there are three metrics of v isibility that are part of the determination of reasonable progress:

1) baseline conditions, 2) natural conditions, and 3) current conditions. Each of the three metrics includes the concentratio n data of the visibility pollutants as different terms in the light extinction algorithm, with respe ctive extinction coefficients and relative humidity factors. Total light extinction when conv erted to deciviews (dv) is calculated for the average of the 20 percent best and 20 percent worst visibility days.

“Baseline” visibility is the starting point for the improvement of visibility conditions. It is the average of the IMPROVE monitoring data for 2000 thr ough 2004 and can be thought of as “current” visibility conditions for this initial pl anning period. The comparison of initial baseline conditions to natural visibility conditions indicat es the amount of improvement necessary to attain natural visibility by 2064. Each state must estimate natural visibility levels for Class I areas within its borders in consultation with federal land managers and other s tates [40 CFR 51.308(d)(2)]. “Current conditions” are assessed every five years as part o f the SIP review where actual progress in reducing visibility impairment is compared to the r eductions committed to in the SIP.

EPA’s Guidance for Estimating Natural Visibility Conditio ns under the Regional Haze Program (2) provides states a “default” estimate of natural visibility. The default values of concentrations of visibility pollutants are based on a 1990 Nation al Acid Precipitation Assessment Program report(3). In the guidance, the United States is d ivided into “East” and “West” along the western boundary of the states one tier west of the Mississ ippi River. This division divides the CENRAP states into “East” (MN, IA, MO, AR, LA) with seven Class I areas, and “West” (NE, KS, OK, TX) with three Class I areas. In the two equation s, only sulfate and organic carbon have different values, but the calculated deciview diffe rence is significant.

In the guidance, EPA also provides that states may use a “refined approach” to estimate the values that characterize the natural visibility con ditions of the Class I areas. The purpose of such16

a refinement would be to provide more accurate esti mates with changes to the extinction algorithm that may include the concentration values , factors to calculate extinction from a measured particulate species and particle size, the extinction coefficients for certain compounds, geographical variation (by altitude) of a fixed val ue, and the addition of visibility pollutants. States can choose between the default and refined e quations. One equation is used to calculate baseline and current conditions of visibility due t o haze-causing pollutants and, with natural concentrations of the same pollutants; the same equ ation is used to calculate natural visibility.

The old (default) algorithm: b ext = 3 × f ( RH) × [Sulfate]
+ 3 × f (RH) ×

[Nitrate] + 4 × [Organic Carbon] + 10 × [Elemental Carbon] + 1 × [Fine Soil] + 0.6 × [Coarse Mass] + 10

The new (refined) algorithm: (Differences from the default are in bold)

b ext = 2.2 × f

S (RH) × [Small Sulfate] + 4.8 × f L (RH) × [Large Sulfate] + 2.4 × f

S (RH) × [Small Nitrate] + 5.1 × f L (RH) × [Large Nitrate] + 2.8 × f

S (RH) × [Small Organic Carbon] + 6.1 × f L (RH) × [Large Organic Carbon]
+ 10 × [Elemental Carbon]
+ 1 × [Fine Soil]
+ 1.7 × f

SS (RH) × [Sea Salt]
+ 0.6 × [Coarse Mass] + Rayleigh Scattering (Site Specific) + 0.33 × [NO 2 (ppb)]

The choice between use of the default or the refine d equation for calculating the visibility metrics for each Class I area is made by the state in which the Class I area is located [40 CFR 51.308(d)(2)]. Kansas consulted with other CENRAP states as those states assessed baseline and natural visibility conditions in their respective C lass I areas.17

6. Monitoring Strategy Section 51.308(d)(4) of the federal Regional Haze R ule requires a monitoring strategy for measuring, characterizing, and reporting regional h aze visibility impairment that is representative of all mandatory Class I areas. The monitoring str ategy relies, in large part, upon participation in the Interagency Monitoring of Protected Visual Envi ronments (IMPROVE) network. The IMPROVE website is located at http://vista.cira.colostate.edu/improve/

. 6.1 Current Monitoring Strategy

6.1.1 Measuring Visibility Data Shortly after creation of the Central Regional Air Planning Association (CENRAP), the organization’s Monitoring Workgroup identified larg e visibility data voids in southern Arkansas, Iowa, Kansas, southern Minnesota, Nebraska, and Okl ahoma. Only five IMPROVE sites were located in the CENRAP region. Between 2000 and 200 3, five more IMPROVE sites and 15 IMPROVE Protocol sites (i.e., sites not managed by IMPROVE directly but by individual government or tribal organizations) were establishe d in the CENRAP region. In conjunction with CENRAP and EPA Region 7, Kansas installed one IMPROVE protocol sampler at Cedar Bluff State Park in Trego County i n the western part of the State, and another at the Tallgrass Prairie National Preserve in the Flin t Hills region of eastern Kansas. A third IMPROVE Protocol sampler in Kansas is operated inde pendently at Reserve, Kansas, by the Sac and Fox Nation of Missouri in Kansas and Nebraska.

Figure 6.1 Kansas IMPROVE Protocol Monitoring Netwo rk18

6.1.1.1 Tallgrass Prairie The IMPROVE Protocol site at Tallgrass Prairie Nati onal Preserve is located in the heart of the Flint Hills of eastern Kansas. The 10,894 acre pre serve was established in 1996, with most of the land held in trust, but managed by the National Park Service. This area is within the largest remaining expanse of tall grass prairie in North Am erica. Management of this prairie region requires seasonal burning of grass in the early spring to inhibit the invasion of woody and non-native plants and to maximize the rate of weight gain in beef cattle early in the grazing season. Kansas conside rs monitoring in the Flint Hills to be a priority, and future addition of monitors at the Tallgrass Pr airie site is a possibility.

Tallgrass IMPROVE

Protocol Lat: 38.43411

Long: -96.56038 Chase

County Start:

9/2/2002

Figure 6.2 Tallgrass Prairie IMPROVE Protocol Monit oring Site

6.1.1.2 Cedar Bluff

The site at Cedar Bluff Reservoir in western Kansas serves as the State's background site for evaluating baseline levels of regional ambient air pollutants (i.e., PM 2.5 and ozone) in Kansas. The Cedar Bluff site is approximately 175 miles fro m the Tallgrass Prairie site, 200 miles from the Newkirk, Oklahoma site, and 240 miles from the Sac and Fox (Reserve, Kansas) site. Because of its remote location, this site was selec ted for installation of an IMPROVE Protocol sampler to fill a very large spatial data gap in th e CENRAP region. The site also hosts a CENRAP nephelometer. Preliminary analysis of data has indicated that the Cedar Bluff site is influenced by air masses originating in different r egions at different times of the year, due to its location in the center of North America and associa ted meteorology. The State of Kansas considers the IMPROVE Protocol sampler at this site to be a priority.19 Cedar Bluff IMPROVE

Protocol Lat: 38.77027

Long: -99.76361 Trego

County Start:

6/1/2002

Figure 6.3 Cedar Bluff IMPROVE Protocol Monitoring Site

6.1.1.3 Sac and Fox Nation of Missouri in Kansas and Nebraska

The Sac and Fox Nation of Missouri in Kansas and Ne braska also operates an IMPROVE Protocol sampler at Reserve, in northeast Kansas. This location hosted a satellite supersite during the last five months of 2002. Data from thi s site are used for modeling and to determine the transition zone between the eastern U.S. and th e central plains.

Sac and Fox Nation IMPROVE

Protocol Lat: 39.97915

Long: -95.56816 Sac and Fox

Reservation Start:

6/19/200220 Figure 6.4 Sac and Fox IMPROVE Protocol Monitoring Site

For information about the Sac and Fox IMPROVE proto col site, contact:

Sac and Fox Nation of Missouri Rick Campbell (785) 742-4705 rick.campbell@sacfoxenviro.org

6.1.2 Characterizing Visibility Data The State of Kansas does not have any mandatory Cla ss I Federal areas. In accordance with 40 CFR 51.308(d)(4)(iii), states without Class I areas must establish procedures by which monitoring data and other information are used in d etermining the contribution of emissions from within the state to regional haze visibility i mpairment at affected mandatory Class I Federal areas in other states. The procedures were establi shed through the work completed by contractors retained by CENRAP, and are only briefl y described here. IMPROVE monitoring data for the 2000-2004 period wa s used to define baseline, natural, and 2018 conditions for each of the Class I areas. PM 10 was speciated into six components (sulfate, particulate nitrate, organic carbon, elemental carb on, soil, and coarse mass) which were used to develop relative response factors (RRFs) between cu rrent and predicted concentrations for each component. The RRFs were multiplied by current bas eline values to estimate future concentrations. The visibility improvements for 20 18 were then calculated using the original or new IMPROVE equation. Additional information about these analyses can be found in Chapter 4 of the Technical Support Document (TSD) prepared by ENVIRON and the Causes of Haze Assessment work performed by Sonoma Technology, Inc . (4). These documents can be found at http://www.kdheks.gov/bar/index.html Kansas also relied upon source apportionment modeli ng (CAMx PSAT) in determining the State’s contribution to other Class I areas. This type of modeling provides the best available estimate of the potential visibility impacts Kansas may have on various surrounding Class I areas21

in 2018. Source apportionment modeling for the CEN RAP region is outlined in Chapter 10 of this document.

6.1.3 Data Validation and Reporting The filter samples from all IMPROVE modules from th e three IMPROVE-protocol sites in Kansas are sent for analysis to the Crocker Nuclear Laboratory at the University of California in Davis, and the resultant data are subjected to prel iminary review and quality assurance/quality control (QA/QC) procedures. Nephelometer data from the Cedar Bluff site are validated by the CENRAP contractor. Other visibility-related data co llected by the State of Kansas (PM 2.5 , SO 2 , NO 2 , and NH 3 ) are subjected to review and QA/QC procedures prio r to reporting. After validation, data from the three IMPROVE-proto col sites in Kansas are sent by the Crocker Nuclear Laboratory at the University of California in Davis for posting to the IMPROVE website and the Visibility Information Exchange Web System (VIEWS) website [http://vista.cira.colostate.edu/views/]. Nephelom eter data from the Cedar Bluff site are reported to the VIEWS database by the CENRAP contractor. Ot her visibility-related data collected by the State of Kansas (PM 2.5 , SO 2 , NO 2 , and NH 3 ) are reported to EPA's Air Quality System (AQS) database on a quarterly basis. For the State of Ka nsas, this fulfills the reporting requirement of visibility data under 40 CFR 51.308(d)(4)(iv).

6.2 Special Monitoring Studies CENRAP, in cooperation with member states and tribe s, studied the impacts of ammonia on visibility impairment in the CENRAP region. Prelim inary monitoring studies and monitoring data analysis suggest that ammonia contributes to v isibility impairment in the CENRAP geographical area. During two measurement periods in 2002 (August 24 – October 23 and November 18 – December 31), an intensive study was conducted to c haracterize ambient fine particulate matter (PM 2.5 ) at the Sac and Fox Nation IMPROVE Protocol site i n Reserve. The sampling station was configured in the same manner as the St. Louis, Missouri Supersite. Selected semicontinuous monitors remained in operation during th e six-week interim period. This special study was funded by CENRAP and EPA Region 7. Daily 24-hour mass reconstructions demonstrated the episodic nature and seasonal varia tions of sulfate (summer/fall) and nitrate (fall/winter). Ion balances for 24-hour sampling p eriods were consistent with conditions favorable for formation of ammonium nitrate. A sul fate transport episode was captured as well as elevated local ammonia levels possibly associate d with seasonal application of anhydrous ammonia to corn and soybean fields. From November 1, 2003 through June 28, 2006, the Sa c and Fox Nation also operated a passive ammonia monitoring station for a CENRAP ammonia mon itoring project. Denuder-based gasphase ammonia, nitric acid, and sulfur dioxide were monitored at the Reserve, Kansas site and six other sites within the CENRAP region. Twenty-four hour samples were collected on a onein-six day schedule. The denuder-based samples wer e analyzed by the Illinois State Water Survey Laboratory. IMPROVE Protocol samplers were in operation at all but one of the22

CENRAP ammonia study sites. This special ammonia s tudy was conducted to collect data for evaluation of the role of ammonia in regional haze formation in the CENRAP region.

6.3 Future Monitoring Strategy In order to assess progress in reducing visibility impairment in Class I areas, the existing IMPROVE and IMPROVE Protocol sites will be maintain ed contingent upon continued national funding. Data from the IMPROVE Protocol sites in K ansas will be used to characterize and model conditions within the State of Kansas. Data from IMPROVE monitors will be used to compare visibility conditions in Kansas to regional haze visibility impairment at Class I areas affected by emissions from Kansas to satisfy requir ements of 40 CFR 51.308(d)(4)(i). The State of Kansas will evaluate the monitoring network peri odically, including an evaluation of changes in technology and the need for new monitors. With continuation of adequate funding, the network will be reconfigured as necessary to enable assessment of reasonable progress toward goals for each of mandatory Class I area potentiall y affected by emissions from within the State of Kansas.23

7. Emissions Inventory Kansas is required by 40 CFR 51.308(d)(4)(v) to pro vide a statewide emissions inventory of pollutants that are reasonably anticipated to cause or contribute to visibility impairment in any mandatory Class I area(s).

7.1 Inventory Results As specified in the applicable EPA guidance, the po llutants inventoried by Kansas include volatile organic compounds (VOCs), nitrogen oxides (NO x ), fine particulates (PM 2.5 ), coarse particulates (PM 10 ), ammonia (NH 3 ), and sulfur dioxide (SO 2 ). An inventory was developed for the baseline year 2002; a summary of those inventor y results is presented in Table 7.1. The complete 2002 emission inventory can be found in Ap pendix 7.1. Included in this appendix are two other categories, fugitive dust and road dust, which are not included in the summaries below.

Table 7.1 2002 Kansas Emissions Summary, by Source Category and Pollutant

VOC NO x PM 2.5 PM 10 NH 3 SO 2 Source category tons/yr
Point 40,278 165,224 16,321 38,366 59,750 143,367 Nonpoint (except fires) 87,327 13,851 10,024 10,533 796 3,100
On-road mobile 74,519 100,152 1,607 2,179 2,816 3,097
Nonroad mobile 28,138 82,697 5,993 6,549 115 8,101 Nonpoint fire 35,046 29,322 117,597 129,187 19 11,051 Biogenic 575,073 49,616 N/A N/A N/A N/A

Totals 840,381 440,862 151,542 186,814 63,496 168,716

Methodologies for the 2002 emissions inventory are documented in Appendix 7.3. These 2002 emissions were grown to year 2018, prima rily using the Economic Growth Analysis System (EGAS6), MOBILE 6.2 vehicle emission modelin g software, and the Integrated Planning Model (IPM) version 2.93 for electric generating un its (EGUs). Table 7.2, a summary of those inventory results follows; the complete 2018 emissi ons inventory is submitted as Appendix 7.2. Methodologies for the 2018 emissions inventory are documented in Appendix 7.3. Table 7.3 presents percent changes in the inventory based on values in Tables 7.1 and 7.2, in relation to base year 2002. Discussions of the pro jected changes for different source categories follow.24

Table 7.2 2018 Kansas Projected Emissions Summary, by Source Category and Pollutant

VOC NO x PM 2.5 PM 10 NH 3 SO 2 Source category tons/yr
Point 54,007 145,647 23,669 50,165 71,623 81,664 Nonpoint (except fires) 104,983 15,822 9,143 9,534 1,247 3,860
On-road mobile 32,724 28,779 655 655 3,892 369
Nonroad mobile 15,156 38,044 2,696 2,954 52 126 Nonpoint fire 35,046 29,322 117,597 129,187 19 11,0 51 Biogenic 575,073 49,616 N/A N/A N/A N/A

Totals 816,989 307,230 153,760 192,495 76,833 97,07 0

Table 7.3 Percent Changes in Kansas Air Emissions, by Source Category and Pollutant, from 2002 to 2018

Source category VOC NO x PM 2.5 PM 10 NH 3 SO 2 Point 34.1% -11.8% 45.0% 30.8% 19.9% -43.0%
Nonpoint (except fires) 20.2% 14.2% -8.8% -9.5% 56.7% 24.5%

On-road mobile -56.1% -71.3% -59.2% -69.9% 38.2% -88.1%

Nonroad mobile -46.1% -54.0% -55.0% -54.9% -54.8% -98.4%
Nonpoint fire 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Biogenic 0.0% 0.0% N/A N/A N/A N/A

Totals -2.9% -30.3% 1.5% 3.0% 21.0% -42.5%

7.2 Point Sources The majority of visibility-impairing point source e missions in Kansas currently come from the electric utility sector. This sector represented 9 3% of the reported SO 2 emissions and 57% of the NO x emissions for the 2002 inventory year. The other large NO x emissions category in Kansas is the natural gas compression industry, which repr esented 28% of total NO x emissions for the 2002 inventory year. Unlike the larger non-municip al electric generating units (EGUs), which are generally located in the eastern third of Kansa s, several large natural gas compressor stations are located along pipelines crisscrossing the State , with numerous other stations clustered around the Hugoton and Panoma gas fields in the southwest. In 2002, 19 EGUs reported NO x emissions over 100 tons, whereas in the same period 95 natura l gas compressor stations reported NO x emissions over 100 tons.25

For the point source sector, Kansas projects signif icant reductions in NO x and SO 2 by 2018, primarily at the five EGU units in the State found to be subject to BART controls. Table 7.4 details the reductions predicted from these emissio n units.

Table 7.4 Total 2018 Reductions in NO x and SO 2 from Kansas Emission Sources Subject to BART

2002 NO x 1 2002

SO 2 1 2018

NO x 2 2018

SO 2 2 NO x

reduction SO 2

reduction Subject-to-BART unit

tons/yr
KCP&L - La Cygne 1 30,058 6,648 2,576 3,948 27,482 2,700
KCP&L - La Cygne 2 8,362 19,355 6,229 3,993 2,133 15,362

Westar - Gordon Evans 2 2,023 3,211 138 0.0 1,886 3,211 Westar - Jeffrey 1 9,602 20,459 4,268 3,532 5,334 16,927 Westar - Jeffrey 2 10,892 23,715 4,040 3,465 6,852 20,251

Total BART reductions 43,687 58,451

1 Data from EPA Clean Air Markets
2 Data from IPM 3.0 The remaining 2002 to 2018 emissions differences re flect the projected growth in emissions due to construction of new sources. The projections we re estimated by using EGAS 5.0 for the nonEGU sources and the Integrated Planning Model (IPM) , version 2.93 for the EGU sector

. At the time this document was being prepared, a 1,400 MW c oal-fired power plant was in the permitting process in Kansas. This power plant, lo cated in Holcomb in the southwest portion of the State, was analyzed for visibility impacts on t he Wichita Mountains Class I area. It was determined, using CAMx PSAT modeling, that visibili ty impairment in the Wichita Mountains attributed to this new source would be below 0.5 de lta deciview. The permit for the 1,400 MW power plant was denied by the Secretary of KDHE. H owever, on May 4, 2009, a settlement agreement was reached that allows for an 895 MW coa l-fired power plant to be constructed in Holcomb.

7.2.1 Natural Gas Compressor Stations From 1995 to 2005, production from the Hugoton gas field, the State’s largest natural gas production area, has decreased from approximately 4 60,000 billion cubic feet (Bcf) to 200,000 Bcf. Over the same period, actual NO x emissions reported from the compressor stations ha ve steadily decreased from 75,000 tons/yr to 50,000 to ns/yr. Kansas expects emissions from this sector to continue to decline as production decline s and equipment is replaced with new, more efficient designs. Additional information on this s ector can be found in Appendix 7.4.26

7.2.2 Fuel Ethanol Manufacturing Facilities In 2002, there were four ethanol plants in operatio n in Kansas, with a total production capacity of 164 million gallons per year (Mgal/yr). That numbe r grew to 14 facilities in 2007 with a total capacity of 814 Mgal/yr. Currently, there are 12 a ctive ethanol facilities, 3 facilities under construction, 1 facility that has been permitted bu t not yet built, 1 facility built but not active, a nd 1 facility whose permit application is pending. In 2008 and 2009, expansion of the fuel ethanol industry in Kansas has slowed dramatically. The ac tual emission rate of NO x for these plants is quite low. KDHE does not anticipate visibility imp acts due to the operation of additional facilities.

7.3 Nonpoint Sources Nonpoint source emissions were compiled from the fi nal 2002 National Emissions Inventory (NEI) database. Although PM 2.5 emissions values are not available from this data source, the NEI gives emissions estimates at a detailed level f or source categories, so that source attribution is more easily analyzed. (Note also the ratio of P M 2.5 to PM 10 , can for comparative purposes be approximated as 0.2). Only pollutants likely to co ntribute to regional haze (i.e., NO x , SO 2 , PM 10 , and VOC) were considered in this analysis. The rel ative contributions of these pollutants within the nonpoint source category are shown in Figure 7. 1.

Figure 7.1 2002 Emissions of Pollutants Contributin g to Regional Haze from Kansas Nonpoint Sources

0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000

P M1 0 VO C NO x S O 2to ns/y r27

PM 10 accounts for by far the largest nonpoint source ca tegory, and can be attributed primarily to agricultural crop production (including burning of crop residue), unpaved and paved road dust, and dust from construction activities. Tables 7.5 through 7.8 give the relative contributions from the top sources of nonpoint emissions for the State for each of the four haze-causing pollutants. These values are based on the 2002 National Emissio ns Inventory.

Table 7.5 2002 Top PM 10 Emissions from Kansas Nonpoint (Area) Sources

Source classification tons/yr % of nonpoint PM 10 % of total PM 10 Unpaved roads 275,026 37.9% 36.6% Agricultural crop production 253,845 35.0% 33.8% Agricultural burning 99,292 13.7% 13.2%
Road construction 48,050 6.6% 6.4%
Paved roads 32,892 4.5% 4.4% Mining and quarrying 7,539 1.0% 1.0%

Table 7.6 2002 Top VOC Emissions from Kansas Nonpoi nt (Area) Sources

Source classification tons/yr % of nonpoint VOC % of total VOC Agricultural burning 55,058 41.4% 22.7%
Residential fuel combustion 18,758 14.1% 7.7%
Gasoline service stations 13,398 10.1% 5.5%
Misc. commercial solvents 7,986 6.0% 3.3%
Misc. consumer solvents 7,185 5.4% 3.0%
Misc. industrial solvents 6,554 4.9% 2.7% Graphic arts solvents 6,476 4.9% 2.7% Surface coatings (solvent evap.) 5,704 4.3% 2.4% All other misc. solvent usage 4,044 3.0% 1.7%28 Table 7.7 2002 Top NO x Emissions from Kansas Nonpoint (Area) Sources

Source classification tons/yr % of nonpoint

NO x % of total NO x
Agricultural burning 29,099 68.8% 7.6%
Industrial fuel combustion 6,298 14.9% 1.6%
Residential fuel combustion 4,203 9.9% 1.1%

Table 7.8 2002 Top SO 2 Emissions from Kansas Nonpoint (Area) Sources

Source classification tons/yr % of nonpoint SO 2 % of total

SO 2 Industrial fuel combustion 24,218 66.6% 12.9% Agricultural burning 10,949 30.1% 5.9%

The nonpoint source category represents a large por tion of the total anthropogenic emissions inventory for VOC emissions. This pollutant from n onpoint sources is projected to grow by 20% in 2018 from the 2002 estimate. In 2018, the estim ate is for approximately 105,000 tons/yr of VOC from the nonpoint source category. Much of the nonpoint VOC category is from solvent utilization and residential heating. Because VOC i s not anticipated to be a large contributor to visibility impairment in the Class I areas surround ing Kansas, the remaining focus will be on NO x and SO 2 nonpoint source emissions.

NO x and SO 2 make up a relatively small proportion of the State ’s nonpoint emissions inventory, at 42,282 tons/yr and 36,385 tons/yr, respectively. With the exception of agricultural burning, the major contributing source categories for NO x are associated with residential, industrial, and commercial natural gas combustion. These categorie s are projected to grow at a moderate pace between 2002 and 2018. For SO 2 , the major contributing categories are industrial fuel (primarily coal and distillate oil) combustion. These categor ies are also projected to grow at a moderate pace between 2002 and 2018. The nonpoint industria l coal combustion category in the National Emissions Inventory is overestimated, both in the 2 002 and 2018 projected inventories, as most industrial sources utilizing coal are captured in t he State’s point source inventory. In addition, the distillate and residual oil combustion in the n onpoint sector are likely to remain unchanged or decrease between 2002 and 2018. At worst, if the 2 018 projections are correct, the nonpoint emissions for SO 2 are still only a fraction of the point source SO 2 emissions.29

7.4 On-Road Mobile Sources EPA’s MOBILE6.2 emissions model predicts reductions for NO x , SO 2 , and VOC from 2002 to 2018 of 71.3%, 88.1%, and 56.1%, respectively. The se reductions are due to vehicle turnover and full implementation of current federal regulati ons, including the federal emission standards for light-duty vehicles and light-duty trucks and t he Tier 2 Program. These rules are discussed in more detail in Chapter 10. Note that growth in the total vehicle miles traveled (VMT) metric for the 2002 to 2018 period for Kansas increased from 2 8,825 million vehicle miles in 2002 to 38,509 million vehicle miles in 2018, constituting a 34% increase.

7.5 Nonroad Mobile Sources The nonroad mobile emissions category includes airc raft operations, marine vessels, recreational boats, railroad locomotives, and a broad category o f other equipment ranging from large construction equipment to handheld string trimmers. Calculation methods for emissions from nonroad engine sources are based on information abo ut equipment population, engine horsepower, load factor, emission factor, and annua l usage. The EPA’s NONROAD 2005 model was used to estimate emissions for much of the nonr oad category. For those categories not included in the NONROAD model, separate estimations were made. All pollutants in the nonroad category are projecte d to decrease from 2002 to 2018. The majority of predicted emissions reductions in the n onroad category occur for SO 2 , with projected reductions of 98%. This large reduction is due to the requirement to use low sulfur diesel fuel by 2010. For the remaining pollutants, the reductions can be attributed to the use of newer equipment subject to more stringent emissions requi rements, including the Clean Air Nonroad Diesel Rule, locomotive emission standards, the Lar ge-Spark Ignition and Recreational Vehicle Rule, and Emissions Standards for New Nonroad Small Spark-Ignition Engines, Equipment, and Vessels. These rules are discussed in more detail in Chapter 10.

7.6 Nonpoint Fires Fires within the nonpoint source category in Kansas make up a large portion of the State’s emissions inventory for certain pollutants. The ma jority of the fires are rangeland burning in the Flint Hills area, along with wheat stubble burning in counties just west of the Flint Hills. Both of these burning categories are very episodic in natur e, with the rangeland burning occurring in the early spring and wheat stubble burning occurring af ter harvest in mid to late summer. Kansas is in the process of developing a Smoke Management Ini tiative, which will achieve reductions from both cropland and rangeland burning. The Smoke Man agement Initiative was developed after the completion of the emissions inventory and the a ssociated reductions were not captured in the 2018 estimations. The emissions used in the modeli ng for burning remained unchanged from 2002 to 2018. Kansas will continue to pursue methods and techniqu es to better characterize the emissions associated with agricultural burning, including the temporal and spatial allocation of these emissions. For more information on these efforts r efer to Appendix 10.4, Kansas Prescribed Fire Emissions.30

7.7 Reporting States are required by 40 CFR 51.308(d)(4)(v) to in clude in their SIPs a commitment to update their statewide emissions inventories periodically. In reference to the emissions inventory work carried out for regional haze purposes, Kansas expe cts to update its emissions inventory as new data become available.

The State of Kansas tracks air emissions over time as required by current EPA regulations and the Air Emissions Reporting Rule (AERR). This fede ral rule, proposed in December 2005 and finalized in December 2008, consolidates the curren t emission inventory reporting requirements, and will require that emissions be reported every t hree years from the following source categories in all parts of the State, excluding sou rces located on tribal lands:

• Point

• Nonpoint

• On-road mobile

• Nonroad mobile In addition, all visibility-impairing pollutants ar e required to be included for the reportable categories listed above. These pollutants will inc lude NO x , SO 2 , PM 10 , PM 2.5 , VOCs, and NH 3
. The rule states that beginning in 2009, emissions r eports will be due 12 months after the end of the year instead of the current 17 months. The rule can be found at: http://www.epa.gov/ttn/chief/aerr/ Kansas intends to follow the reporting requirements of the AERR where funding and staffing allow. Kansas commits to updating its point source emissions inventory annually and to analyze sectors identified in the regional haze planning pr ocess that need improvement. In the past, Kansas provided complete point source inventories, and partial supplemental inventories for the nonpoint (area), on-road mobile , and nonroad mobile source categories. Kansas chose to supplement EPA-generated nonpoint, on-road, and nonroad inventories with more accurate information when available. Thus, ex cept for point source categories, future inventories will likely continue to be a hybrid EPA /Kansas-generated product. It is anticipated that the initial five-year progre ss report will occur in 2014. The 2011 National Emissions Inventory will likely be the most current available inventory at that time and will be used as part of the progress report. It is expecte d that Kansas will also have access to a later point source inventory and continuous emissions mon itoring systems (CEMS) data for EGUs. Where this more up-to-date information is available , it will used to supplement the 2011 National Emissions Inventory.

Kansas will use the latest available inventory for the five-year progress report, and compare that with the projected 2018 inventories. Because the 2 018 projected inventory contains BART controls that may not yet be reflected in the 2011 inventory, these sources will be addressed individually in this review. For the remaining sec tors, EGAS growth rates will be used, where applicable, and projected growth will be compared w ith actual emissions. If this comparison31

indicates overall emissions are growing at a rate s ignificantly (i.e., more than 10%) higher, on an individual species basis than previously projected, Kansas will reassess the visibility impacts on potentially affected Class I areas and consult with the appropriate federal land manager (FLM) and EPA to identify additional measures. This coul d potentially include a SIP revision to address the visibility goal for the affected Class I area(s).

List of Chapter 7 Appendices

7.1 2002 Emissions Inventory 7.2 2018 Emissions Inventory 7.3 Emissions Inventory Technical Documentation 7.4 Natural Gas Production Trends32

8. Modeling Assessment

Modeling guidelines for conducting regional-scale m odeling for particulate matter and visibility are provided in 40 CFR Part 51 Appendix W. In Appe ndix W, EPA recommends the use of three models to simulate pollutants impairing visib ility: the Community Multiscale Air Quality (CMAQ) model, the Comprehensive Air quality Model w ith extensions (CAMx), and the Regional Modeling System for Aerosols and Depositio n (REMSAD). CENRAP contractors performed regional modeling using CMAQ and CAMx.

The CMAQ model is an Eulerian model that simulates the atmospheric and surface processes affecting the transport, transformation, and deposi tion of air pollutants and their precursors. An Eulerian model approximates the numerical solutions of partial differential equations of plumes on a fixed grid, while other models may lose accura cy or need re-gridding as the plumes expand.

CAMx is a computer modeling system for the integrat ed assessment of photochemical and particulate air pollution. CAMx incorporates all o f the technical attributes demanded of state-ofthe-art photochemical grid models, including two-wa y grid nesting, a subgrid-scale Plume-inGrid module to treat the early dispersion and chemi stry of point source NO x plumes, and a fast chemistry solver.

CAMx Mechanism 4 (M4) provides “one atmosphere” mod eling for fine and coarse PM and ozone. Aqueous phase chemistry is modeled using th e Regional Acid Deposition Model (RADM) mechanism. Inorganic sulfate/nitrate/ammoni um chemistry is modeled with ISORROPIA thermodynamic equilibrium aerosol model. Secondary organic aerosols are modeled using a semi-volatile module in CAMx called SOAP. Wet and dry deposition processes are included for gases and particles. Gridded depo sition information is outputted along with the concentrations.

In the July 1, 1999 publication of the Regional Haz e Rule in the Federal Register, EPA discussed the uses of regional modeling as follows:

• Analyses and determination of the extent of emissio ns reductions needed from individual
states

• Analyses and determination of emissions needed to m eet the reasonable progress goal for the Class I area

• Analyses to support conclusion that the long-term s trategy provides for reasonable
progress

• Analyses to calculate the resulting degree of visib ility improvement that would be achieved at each Class I area

• Analyses to compare visibility improvement between proposed control strategies33

8.1 Model Inputs

For regional haze, the full 2002 modeling year was chosen as the episode period to evaluate. This year corresponds to the baseline emissions inv entory available and is also included within the five-year monitoring baseline period used in es tablishing the glide slopes.

As one of the five national regional planning organ izations (RPOs), CENRAP chose to use the unified grid domain developed by all of the other R POs. This domain covers all RPO areas and was chosen to enable sharing of data and results be tween RPOs in a consistent manner. The grid consists of 36km grid cells and is 148 x 112 in siz e.
Generating the source inventory for modeling is int ertwined with the creation of the pollutant inventory. Each emission source and the pollutants it emits must be specifically identified. For photochemical and aerosol modeling, each source mus t be classified as a point, nonpoint, mobile (on-road or nonroad), or biogenic source, then spat ialized, temporalized, and speciated. In addition, three or more inventories need to be gene rated, including a base inventory for model performance evaluation, a typical inventory for the base year, and a future year inventory. Control strategy inventories are also developed to evaluate potential controls. In all, CENRAP developed multiple modeling inventories. The Base G inventory is the latest future year inventory and is considered the most reflective of future year emissions. The Base A through Base D inventories include known errors and should not be used in the analysis of future year visibility. Chapter 2 of the Technical Support Doc ument (Appendix 8.1) provides the methodologies for the development of the emissions inventories; Kansas-specific emission inventory information can be found in Chapter 7 of this SIP.

For meteorological inputs, the Fifth-Generation NCA R / Penn State Mesoscale Model (MM5) was selected. MM5 is the latest in a series that d eveloped from a mesoscale model used by Anthes at Penn State in the early 1970s, and was la ter documented by Anthes and Warner(5). Since that time, MM5 has undergone many changes des igned to broaden its usage. These changes include: (1) multiple-nest capability; (2) non-hydrostatic dynamics, which allows the model to be used at a few-kilometer scale; (3) mult itasking capability on shared and distributed memory machines; (4) four-dimensional data assimila tion capability; and (5) more physics options. The MM5 model is supported by several aux iliary programs, which are referred to collectively as the MM5 modeling system. Since MM5 is a regional model, it requires an initial condition as well as a lateral boundary condition t o run. To produce a lateral boundary condition for a model run, gridded data is needed to cover th e entire time period that the model is integrated.

8.2 Model Performance Evaluation

Model evaluations compared concentrations of variou s pollutants simulated by CMAQ and CAMx with observations from:

• Interagency Monitoring of Protected Visual Environm ents (IMPROVE)34

• Clean Air Status and Trends Network (CASTNet)

• Speciated Trends Network (STN)

• Aerometric Information Retrieval Systems (AIRS)

• South Eastern Aerosol Research and Characterization (SEARCH)

Model performance evaluation summaries follow. Det ailed model performance evaluations are found in Appendix 8.2

A detailed model performance evaluation was perform ed on the 2002 Base F CMAQ simulation. As specified in the EPA guidance, a multi-layered a pproach to model performance testing was performed, with focus on the operational and diagno stic analyses. Performance evaluations were performed on all the visibility-impairing particula te species, including sulfate, nitrate, elemental carbon, organic carbon, soil, and coarse mass. Per formance goals and criteria were established in the assessment of the modeling results. These g oals and criteria are explained in detail in the CENRAP Technical Support Document (Appendix 8.2). Because Kansas was identified as a contributing state to visibility impairment in the Wichita Mountains Class I area, particular attention has been paid to performance for this are a. Overall for the CENRAP domain, using the model perf ormance criteria established in the TSD, the model performance for both CMAQ and CAMx models for sulfate and elemental carbon can be characterized as good with most areas meeting th e performance criteria. Model performance for nitrate was variable, with a summer underestima tion and winter overestimation, with some periods and areas not meeting the performance crite ria. Organic mass carbon performance was fairly good with most areas meeting the performance criteria, while the coarse mass and soil performance was generally poor, especially in the s outhwest where there is a systematic soil underestimation. A more detailed pollutant-by-poll utant summary is provided below. The TSD contains a very detailed model performance, includi ng performance evaluations at each Class I area in CENRAP. 8.2.1 Sulfate (SO 4 ) Model Performance For the first 10 months of the year, SO 4 was underpredicted across the CENRAP region. For the remaining two months, there is a slight overpredict ion. Overall, the SO 4 performance met the performance goal approximately half of the time wit h all of the modeled predictions falling within the performance criteria. For the Wichita M ountains area on the 20% worst days, the model has a fractional bias of - 48% for SO 4 . Much of the underestimation occurred mainly during the summer months. During the winter months , when the predominant winds are from the north, SO 4 prediction is much better, as can be seen in Figur e 8.1 below.

8.2.2 Nitrate (NO 3 ) Model Performance Monthly NO 3 model performance across the CENRAP region is char acterized by a summer underestimation and winter overestimation bias. Be cause nitrates are generally a small portion of the visibility problem in the summer in the CENR AP region, this underestimation is of relatively minor concern. In the winter, however, nitrates can be a significant portion of the visibility impairment, thus performance during this period is important. Overall across the entire35

domain, nitrate in the winter was overstated with s ome periods overestimated to such a degree that the performance criteria are not being met. I n the Wichita Mountains for the 20% worst days, there are approximately eight days with a sig nificant amount of nitrate impacts. For all but three of these days, the model underpredicts nitrat e. On several other days the model overpredicts, with the worst overprediction occurri ng on Julian day 344 by a very significant amount. Because the CAMx PSAT modeling performed t o date has indicated Kansas as a contributor due to nitrates, Kansas investigated th is particular day further.

Figure 8.1 Light Extinction for 20% Worst Visibilit y Days at Wichita Mountains by Particulate

Species, Showing Observed (Left) versus Modeled (Ri ght) Values

Worst 20% Obs (left) vs Typ02g (right) at WIMO1

0 50 100 150 200 250

29 83 95 101 110 113 125 128 131 143 170 173 176 179 218 221 224 242 245 254 260 269 272 344 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM
bSOIL
bEC
bOC
bNO3
bSO4

From the PSAT results, the Kansas modeled nitrate c ontribution on Julian day 344 was approximately 18 Mm -1 , or approximately 15% of the modeled impact for th is day, versus the 2% modeled average over the worst 20% days. This la rge impact (15%) represents a significant portion of this 2% modeled average. The majority of the impact on this day was attributed to elevated point sources (35%), on-road mobile (23%), and nonroad (21%) sources. Looking at the hourly PSAT modeling results, it appears that m uch of this impact is attributed to nitrates generated several days before, and these nitrates r emained in the Wichita Mountains region on Julian day 344. Clearly for the Wichita Mountains, the performance is poor on several of the worst modeled visibility days. The nitrate predict ion is an area needing further investigation in future studies to better understand these performan ce issues and how they might be impacted by emissions inventory and modeled chemistry.36

8.2.3 Organic Matter Carbon (OMC) Model Performanc e Domain-wide, the performance for OMC at the IMPROVE sites is quite good throughout the year, with a slight winter overestimation and a sli ght summer underestimation. Both the performance goal and performance criteria were met for the IMPROVE sites for all months. For the Wichita Mountains, OMC is significantly underes timated (-69% overall). As seen in Figure 8.2, OMC accounts for nearly 15% of the monitored visibility impairment on the 20% worst days in 2002, which is more than nitr ates; thus this modeled underestimation is of concern. As is the case with nitrates, additional analysis for OMC is warranted.

Domain-wide for the IMPROVE monitoring network, ele mental carbon (EC) modeling exhibits a large underprediction bias in the summer months ( -40% to -60%) and a much lower absolute bias in the winter. Because the monitored and mode led EC concentrations are low overall, this underprediction bias has little effect on the overa ll visibility performance. At low concentrations a wider range of bias is also considered acceptable , and in this case the performance goals and criteria are met for the entire year even though th ere is a large underprediction bias. In the Wichita Mountains, the monitored EC fraction only r epresents 4% of the visibility impairment on the 20% worst days, thus the underprediction is relatively unimportant overall for this Class I

area.

Figure 8.2 Percent Visibility Extinction for the Be st and Worst 20% Days at Wichita Mountains

8.2.4 Other PM 2.5 (soil) Model Performance The domain-wide soil component is overestimated, an d more so in the winter months. July is the only month where the soil is underpredicted. This underprediction is likely due to high windblown dust events that impact some IMPROVE moni tors but are not accurately characterized by the model. For the Wichita Mounta ins, the soil component represents less than 1% of the worst 20% days based on monitored data, t hus the poor performance is not likely a37

factor for this Class I area. As seen in the overa ll performance, the modeled results do indicate an overprediction in the Wichita Mountains. Howeve r, this overestimation is still just a small fraction of the overall modeled visibility impact a t this Class I area.

8.3 Base G Model Simulations

The 2018 Base G modeling simulations represent the final version of the modeling simulations prepared by CENRAP. The latest 2018 version reflec ts the projected emissions growth as well as the known “on the books” controls that will occu r before 2018. For Kansas emission sources, this also includes estimated reductions for all fiv e of the electric generating units (EGUs) subject to BART. All EGU emissions were projected based on IPM runs, and included the impacts of the CAIR trading program and other federal programs . Remaining point and nonpoint (area) sources were projected using the EGAS model. The m obile on-road and nonroad projections were performed with the MOBILE 6 and NONROAD models , respectively. The results of this 2018 Base G modeling run, along with the 2002 typical modeling run, were used to estimate the projected visibility improveme nts at each Class I area within the CENRAP region. For regional haze, two metrics are importa nt: (1) the improvement of the average visibility for the 20% worst days, and (2) no degra dation occurring on the 20% best visibility days. These 20% best and worst days are chosen bas ed on the IMPROVE monitored days and are kept the same in the 2018 Base G run. The proj ected modeling results can then be compared to the 2018 uniform rate of progress (URP) glide pa th developed for each Class I area. This same analysis can also be performed for the 20% bes t visibility days.

Figures 8.3 and 8.4 are examples of this analysis f or the Wichita Mountains Class I area; with the upper trend line (blue) representing the projected modeling results. In this case, the model prediction is indicating the 2018 URP will not be m et for the Wichita Mountains area.

Overall, for the CENRAP region, the 2018 projection s indicate that the central portion of the CENRAP area will meet the URP glide paths, while th e northern and southern Class I areas in CENRAP will not meet their respective glide paths. The State of Missouri’s Class I areas are projected to meet the URP glide path based upon the modeling projections that included all of Kansas’ BART reductions. For Kansas, the main conce rn is the Wichita Mountains Class I area, as emissions from Kansas have not been predicted to significantly impact Class I areas in other surrounding states. Additional discussion on Kansa s impacts and the 2018 modeling projections are included in Chapter 10.38

Figure 8.3 URP Glide Path for Wichita Mountains Cla ss I Area with 2018 Projected Results – 20% Worst Days

Uniform Rate of Reasonable Progress Glide Path Wichita Mountains - 20% Data Days

23.81 22.72

20.01

17.30

14.58

11.87

9.16 7.53 21.47

0 5 10 15 20 25 30

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 204 8 2052 2056 2060 2064 YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction

Figure 8.4 URP Glide Path for Wichita Mountains Cla ss I Area with 2018 Projected Results - 20% Best Days

Uniform Rate of Reasonable Progress Glide Path Wichita Mountains - Best 20% Days

9.78 9.78 9.78 9.78 9.78 9.78 9.78 9.78

9.23

0 2 4 6 8 10 12

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 204 8 2052 2056 2060 2064 YearHaziness Index (Deciviews)

Glide Path Natural Condition (Best Days) Observation Method 1 Prediction39

8.4 Information from Modeling Performed by Other RP Os

Chapter 5 of the TSD (Appendix 8.3) includes a disc ussion of the modeling being performed at the three RPOs surrounding CENRAP, the Visibility I mprovement State and Tribal Association of the Southeast (VISTAS), Midwest Regional Plannin g Organization (MRPO), and Western Regional Air Partnership (WRAP). These RPOs have a ll performed either CMAQ or CAMx modeling for both 2002 and 2018.

8.4.1 MRPO In general, the MRPO modeling was less optimistic i n 2018 for the Class I areas in states surrounding Kansas. This difference is likely a re sult of different emissions inventories. The 2018 CENRAP Base F and G emissions inventories incl uded BART reductions in the CENRAP region, while the MRPO inventory did not. The MRPO inventory was also not the latest available for the CENRAP region at the time of this run.

8.4.2 VISTAS The VISTAS modeling indicates very close agreement with the CENRAP modeling, with the VISTAS modeling being more optimistic in the Class I areas surrounding Kansas.

8.4.3 WRAP The WRAP modeling did not cover the Class I areas o f most interest to Kansas. For the Class I areas that were covered, the CENRAP modeling and WR AP modeling were in fairly close agreement.

Unfortunately, the Class I area of most interest to Kansas, the Wichita Mountains, was not included in any of the other surrounding RPO modeli ng. A comparison of all the modeling results to date is shown in Figure 8.5 above. The full discussion of regional visibility projection comparisons can be found in Chapter 5 of the TSD (A ppendix 8.3).40

Figure 8.5 Comparison of 2018 Modeling Results from CENRAP, VISTAS, WRAP, and MRPO

CMAQ Method 1 predictions with new IMPROVE algorith m at CENRAP+ sites Across RPOs

0% 20% 40% 60% 80% 100% 120% 140%BIBE1GUMO1WIMO1CACR1UPBU1HEGL1MING1BRET1VOYA2BOWA1MACA1SIPS1ISLE1SACR1WHIT1WHPE1GRSA1ROMO1WICA1BADL1THRO1LOST1Percent of target reduction achieved CENRAP 36k Base18g/Typ02g
VISTAS 12k 2018g2b/2002gt2a

WRAP 36k Base18b/Plan02b corrected

MwRPO 2018 R4S1a

CENRAP non-CENRAP

8.5 Control Strategy Simulations

CENRAP performed one control strategy simulation us ing the 2018 Base G inventory. This control run identified several Kansas point sources based on a Q/d (i.e., tons NO x plus tons SO 2 divided by distance) greater than or equal to 5 ana lysis with cost per ton reduced less than $5,000. The Kansas sources included in the control run are listed in Tables 8.1 and 8.2.

The control run shows improvements in all the Class I areas surrounding Kansas. Because most of the controls identified occur in the central por tion of the CENRAP region, most of the improvements are also seen in this area. Controls were identified in both Kansas and the surrounding states, and no source apportionment was performed in this control run. Therefore, the direct Kansas contribution to visibility improv ements in the surrounding Class I areas from Kansas emissions reductions could not be determined . There were 181,107 tons/yr of total NO x reductions identified in the overall control run, w ith the Kansas portion being 17,927 tons. For SO 2 , 725,025 tons/yr of overall reductions were identi fied, with the Kansas portion being 21,617 tons/yr.41

Table 8.1 Kansas NO x Sources Included in the CENRAP Control Strategy Ru n Using the 2018 Base G Inventory

Table 8.2 Kansas SO 2 Sources Included in the CENRAP Control Strategy Ru n Using the 2018 Base G Inventory

Plant ID Plant Name Control Measure Tons

SO 2 Tons Reduced Cost per

Ton Reduced 1770030 Westar Energy - Tecumseh FGD Wet Scrubber 2,631 2,368 $4,519

1770030 Westar Energy - Tecumseh FGD Wet Scrubber 4,199 3,779 $3,715

2090008 Kansas City BPU - Nearman FGD Wet Scrubber 8,999 8,099 $2,239

2090048 Kansas City BPU - Quindaro FGD Wet Scrubber 4,216 3,795 $3,522

2090049 Kansas City BPU - Kaw FGD Wet Scrubber 1,674 1,506 $4,658

2090049 Kansas City BPU - Kaw FGD Wet Scrubber 2,300 2,070 $4,095 Plant ID Plant Name Control Measure Tons

NO x Tons Reduced Cost per

Ton Reduced
2057022 Lafarge Midwest - Fredonia Mid-kiln Firing 1,416 425 $83

0010009 Monarch Cement Biosolid Injection Technology 1,559 359 $466

0450014 Westar Energy - Lawrence LNC3 1,688 984 $40 7 2090048 Kansas City BPU - Quindaro SCR 2,181 1,963 $738 1490001 Westar Energy - Jeffrey LNC3 5,585 1,767 $1 ,043 1490001 Westar Energy - Jeffrey LNC3 5,585 1,191 $1 ,560 0450014 Westar Energy - Lawrence LNC3 3,403 565 $1, 628 1490001 Westar Energy - Jeffrey LNC3 5,585 1,106 $1 ,755

0210002 Empire District Electric -

Riverton SCR 992 840 $1,581 1070005 KCP&L - La Cygne SCR 6,647 5,318 $2,308 2090008 Kansas City BPU - Nearman LNBO 3,501 371 $3 ,144 0550023 Sunflower Electric - Holcomb LNBO 3,683 390 $3,839

1250015 Heartland Cement SNCR - Urea Based 1,336 668 $1,657
0910057 AGC Flat Glass North America Oxy-Firing 2,3 30 1,981 $4,08842

For the Wichita Mountains, even with the controls i dentified in this control scenario, the modeling still does not predict the area will meet its URP target. This is also the case in other CENRAP Class I areas, such as in Texas and Minnesot a, where Kansas is less likely to contribute to visibility impairment. For specific comparisons at other Class I areas, refer to Figure 8.6 below.

Figure 8.6 Comparison of Modeling Results from Base G and Control Strategy Runs

CMAQ BaseGc1 vs BaseG Method 1 predictions for CENR AP+ sites

0% 20% 40% 60% 80% 100% 120% 140% 160% 180% 200%BIBE1GUMO1WIMO1CACR1UPBU1HEGL1MING1BRET1VOYA2BOWA1MACA1SIPS1ISLE1SACR1WHIT1WHPE1GRSA1ROMO1WICA1BADL1THRO1LOST1Percent of target reduction achieved BaseGc1 BaseG

CENRAP non-CENRAP
Kansas evaluated the cost effective and technically feasible controls identified in the CENRAP control scenario above. A summary of that evaluati on follows.

For the NO x controls identified in this control run for Kansas , the State has evaluated all of the sources and controls identified. Several of the so urces included in the control run will be controlled for NO x . They include:

• Westar Energy - Jeffrey Unit 3 – Low NO x burners/overfire air

• Westar Energy - Lawrence Units 3, 4, and 5 – Low NO x burners

The two units at BPU Kaw facility are currently in cold stand-by and Kansas does not anticipate these units will be placed back into operation with out additional SO 2 control requirements. Westar Energy - Tecumseh, was evaluated for SO 2 controls but it was determined they were not cost effective considering the predicted visibility improvements associated with those controls.

Three sources identified in the control run above w ill be subject to controls as part of ozone contingency measures being implemented in the Kansa s City metropolitan area:43

• Kansas City BPU – Nearman and Quindaro – Kansas Cit y NO x Emission Reduction Rule

• AGC Flat Glass North America – Kansas City NO x Emission Reduction Rule

Two Westar Energy - Jeffrey EGUs identified in this control run are subject to BART and will not be subject to additional NO x controls for reasonable progress. The remaining s ources identified in this control were evaluated as part o f reasonable progress and it was determined that further controls at this time would not be pursued. These evaluations can be found in Chapter 10.

List of Chapter 8 Appendices

8.1 Emissions Modeling (TSD Chapter 2) 8.2 Model Performance Evaluation (TSD Chapter 3) 8.3 Additional Supporting Analysis (TSD Chapter 5)44

9. Best Available Retrofit Technology

EPA’s 1999 Regional Haze Rule requires additional c ontrols for certain older emission sources. The State of Kansas is required to have those older sources that contribute to visibility impairment in Class I areas to install Best Availab le Retrofit Technology (BART) or implement an emissions trading or other alternative program t hat will achieve greater reasonable progress than would be achieved through the installation and operation of BART. On July 6, 2005, EPA published a revised final rule, including Appendix Y to 40 CFR part 51 “Guidelines for BART Determinations under the Regional Haze Rule,” herei nafter BART Guidelines, which provides direction to states on determining which of these o lder sources may need to install BART and how to determine BART.

The State of Kansas is requiring sources subject to BART to install, operate, and maintain BART rather than implement an emission trading program o r other alternative measure in place of BART.

9.1 BART Eligible Sources in the State of Kansas

Kansas BART-eligible sources were identified using the methodology in the BART Guidelines. For an emission source to be identified as BART eli gible, the State of Kansas used these criteria from the BART Guidelines:

• One or more emissions units at the facility fit wit hin one of the 26 categories listed in the BART Guidelines

• The emission unit was in existence on August 7, 197 7 and began operation at some point on or after August 7, 1962

• The limited potential emissions from all emission u nits identified in the previous two bullets were 250 tons or more per year of any of th ese visibility-impairing pollutants: SO 2 , NO x , or PM 10
. To identify the sources that met the criteria above , Kansas performed a multi-step search and analysis including a database query of the permitte d air sources in its point source emissions inventory database, and a survey of the facilities. Refer to detailed description of the identification process in Appendix 9.1. This analy sis indicated there were 19 facilities in Kansas with BART-eligible units. The 19 facilities, along with their BART-eligible units, are listed in Table 9.1.45 Table 9.1 Facilities with BART-Eligible Units in th e State of Kansas

BART Source Category Name Facility ID Facility Name BART-Eligible Emission Units

0090002 Aquila (now

Sunflower Electric) - Arthur Mullergren Unit 3 (Stacks 1 and 2)

1750001 Aquila (now

Sunflower Electric) - Cimarron River Unit 1

0570001 Aquila (now

Sunflower Electric) - Judson Large Unit 4

2090008 Kansas City BPU -

Nearman Unit 1

2090048 Kansas City BPU -

Quindaro Unit 1

Unit 2

1070005 KCP&L - La Cygne Unit 1

Unit 2

1130014 McPherson Municipal

Power Plan #2 Unit 1

0550026 Sunflower Electric -

Garden City Unit S2

1730012 Westar Energy -

Gordon Evans Unit 2 (Stacks 2 and 3)

1550033 Westar Energy -

Hutchinson Unit 4 (Stacks A and B)

1490001 Westar Energy -

Jeffrey Unit 1

Unit 2

0450014 Westar Energy -

Lawrence Unit 5 Fossil-Fuel Fired Electric Generating Units

0350012 Winfield Municipal Power Plant #2 Unit 4

Portland Cement Plants 0010009 Monarch Cement Co. No. 4 Kiln Stack, No.4 Kiln Clinker Cooler, No.5 Kiln Stack, No. 5 Kiln Clinker Cooler, Raw Material Unloading, Clinker Grinding and Cement Handling, Stone Quarry Processing

0150004 Frontier El Dorado

Refining Co. Boiler B-105, Boiler B-107, Plant Process Heaters, Refinery Flare System B-1303, Plant Cooling Towers, Storage Tanks, Gas Oil Hydrotreater Petroleum Refineries
1130003 National Cooperative Alky Heater HA-002, No .9 Boiler SB-009,46 Refinery Assoc. (NCRA) No.12 Boiler SB-012, Coker IR Comp.

CR-003, Plat Stab Boil Htr HP-003, Plat Charge Htr HP-006, Fugitive Emissions

1730070 Basic Chemicals

(now OxyChem - Wichita) Boiler 1; Boiler 2; Boiler 3; Chloromethanes Chemical Processing Plants 0570003 Koch Nitrogen Ammonia plant - primary reformer; Ammonia plant - other; Nitric acid plant - absorber tail gas; Ammonium nitrate plant – neutralizer

Glass Fiber Processing Plants 2090010 Owens Corning 70 furnace - N exhaust; 70 furnace - S exhaust; 70 riser/channel/forehearth; 70 A forming; 70 B forming; 70 C forming; 70 D forming; 70 curing oven charge end; 70 curing oven discharge end; J5 furnace; J5 riser/channel/forehearth; J6 A forming; J6 B forming; J6 C forming; J6 curing oven charge end; J6 curing oven discharge end; J6 smoke stripper; J6 north cooling (A); J6 south cooling (B); J6 asphalt coating; Raw material processing

9.2 Determination of Sources Subject to BART

Under the BART Guidelines, states have the followin g options regarding BART-eligible sources: (a) make BART determinations for all sources, or (b ) consider exempting some sources from BART because they do not cause or contribute to vis ibility impairment in a Class I area. The State of Kansas chose option (b). If a state choos es that option, then the BART Guidelines suggest three sub-options for determining that cert ain sources need not be subject to BART:

• Individual source attribution approach (dispersion modeling)

• Use of model plants to exempt sources with common c haracteristics

• Cumulative modeling to show that no sources in a st ate are subject to BART

The State of Kansas chose the first sub-option abov e, individual source attribution, to determine which sources cause or contribute to visibility imp airment, and therefore were subject to BART. The CALPUFF modeling protocol used for determining which BART-eligible facilities are subject to BART is included in Appendix 9.2. Pollu tants modeled were NO x , SO 2 , and PM 2.5
. Based on the relatively large distances between BAR T-eligible sources in Kansas and Class I areas outside of the State and discussions with oth er member states in CENRAP, Kansas determined that the 0.5 deciview (dv) threshold was appropriate for the subject-to-BART process (40 CFR Part 51 Appendix Y Section (III)(A)(1)). P reliminary dispersion modeling was conducted to determine which of the BART-eligible u nits would create a greater than 0.5 deciview impact for at least one day during the thr ee-year period modeled at nine Class I areas. The one day in three-year period threshold, as well as the Class I areas selected for modeling,47

were based on recommendations made by staff at EPA Regions 6 and 7. The nine Class I areas chosen are the following:

• Caney Creek Wilderness Area, Arkansas (CACR)

• Upper Buffalo Wilderness Area, Arkansas (UPBU)

• Great Sand Dunes Wilderness Area, Colorado (GRSA)

• Rocky Mountain National Park, Colorado (ROMO)

• Hercules-Glades Wilderness Area, Missouri (HEGL)

• Mingo Wilderness Area, Missouri (MING)

• Wichita Mountains Wilderness Area, Oklahoma (WIMO)

• Badlands National Park, South Dakota (BADL)

• Wind Cave National Park, South Dakota (WICA)

Sources with preliminary CALPUFF modeling outcomes of at least one day of 0.5 dv visibility impact in a Class I area over the period modeled (2 001-2003) are shown in Table 9.2.

Table 9.2 Kansas BART-Eligible Emission Units with at Least One > 0.5 dv Visibility Impact

Day on Selected Class I Areas during 2001–2003

CACR UPBU GRSA ROMO HEGL MING WIMO BADL WICA Source Number of days during 2001-2003 with visibility imp act >0.5 dv Kansas City BPU - Nearman Unit 1 23 21 3 1 30 16 15 3 2 Kansas City BPU - Quindaro Units 1 & 2 13 13 1 1 18 6 9 0 0
KCP&L - La Cygne Units 1 & 2 204 249 17 21 278 233 142 46 38

Monarch Cement Kilns 4 & 5 0 0 0 0 0 0 1 0 0
Westar Energy - Gordon Evans Unit 2 33 30 11 13 28 17 102 32 24
Westar Energy - Hutchinson Unit 4 14 7 6 5 6 3 17 9 4
Westar Energy - Jeffrey Units 1 & 2 150 161 27 28 182 158 165 82 55
Westar Energy - Lawrence Unit 5 14 14 1 1 17 7 9 2 1

Each of the facilities listed in Table 9.2 submitte d refined modeling results, based on CALPUFF modeling for individual source exemption provided i n the modeling protocol. Monarch Cement, Kansas City BPU - Quindaro, Kansas City BPU – Nearm an, Westar Energy - Hutchinson, and Westar Energy - Lawrence were able to show that the emissions from their BART-eligible units are not anticipated to cause or contribute to visib ility impairment in Class I areas. The submittals for these sources can be found in Appendix 9.8.48

BPU submitted the Black & Veatch-prepared document Best Available Retrofit Technology Engineering Analysis for Nearman Unit 1 in February 2007. In November 2007, the Kansas Department of Health and Environment (KDHE) discove red a potential issue with the hourly emission rates used in the initial modeling determi nation making Nearman a BART source. KDHE informed BPU of this potential issue and BPU r evised both the 24 hour maximum emission rates and the BART determination modeling they had performed.

On December 19, 2007 the KDHE received revised 24 h our maximum emission rates from BPU for Nearman. Along with the revised emissions rate , BPU also submitted additional CALPUFF modeling for purposes of a BART determination. Thi s new modeling indicated Nearman should not have been included as a BART source. The model ing BPU performed was based on the approved CALPUFF modeling protocol. It was therefo re determined that BPU is not a source subject to BART.

The facilities with BART-eligible units found to be subject to BART by the State of Kansas are shown in Table 9.3. These facilities were required to complete full BART analyses. Appendix 9.3 contains more detailed results of the modeling analyses for each subject-to-BART source.

Table 9.3 Kansas Facilities with Units Subject to B ART under the Regional Haze Rule

Facility ID Facility Name Emission Units Subject to BART

1070005 KCP&L - La Cygne Unit 1 Unit 2 1730012 Westar Energy - Gordon Evans Unit 2
1490001 Westar Energy - Jeffrey Unit 1 Unit 2

9.3 Determination of BART Requirements for Subject- to-BART Sources

As part of the BART determination, KDHE developed a BART guidance document for those sources that were required to complete a full BART analysis. This document accounted for Kansas specific considerations, including the State ’s authority to implement the regional haze rule. One of the more important guidance decisions in the document concerned electric generating units and facilities that met the presum ptive threshold outlined in the EPA guidance. The KDHE guidance document includes the following g uidance statement that was applied in several of the State’s BART analyses.

KDHE note: KDHE expects these presumptive levels of control will be cost effective in most cases. If your facility falls in the EGU cate gory described above and you propose controls at or beyond these presumptive levels, you need not take into account the49

remaining statutory factors, as BART will be met. If you propose controls above these presumptive levels, justification incorporating the statutory factors will be required.

KDHE elected to include this guidance based on an e xamination of how EPA set these presumptive limits coupled with the EGU’s in the st ate that this would apply to. One of the major driving factors that shaped this guidance was the consideration of the State’s authority to implement the regional haze rule which includes a “ no more stringent than” clause, see Appendix 2.1. KDHE believes this guidance provided an efficient means for presumptive BART units to meet BART while meeting the State’s author ity to implement the regional haze program.

BART determinations for the five subject-to-BART un its in Kansas were carried out by thirdparty contractors on behalf of the sources’ two own ers and submitted to the State for approval. Because all five of the BART units are electric gen erating units (EGUs) and are located at 750 MW facilities, the State stipulated that the minimu m BART control level would be the presumptive limits specified in the BART Guidelines . As discussed above, Kansas provided each owner with a guideline for conducting their determi nation, titled, Guidance for Facilities Conducting a BART Analysis, and found in Appendix 9.4. The resulting analyses are found in Appendix 9.5 (KCP&L) and Appendix 9.6 (Westar Energ y) and are discussed below.

The operational standards prescribed for the applic ation of BART for sources will be in terms of maximum emission rates for the primary visibility-i mpairing pollutants NO x and SO 2 . In all cases here, added PM 2.5 controls would help visibility only marginally, an d would not be cost effective. These standards, along with presumptive limits from the BART Guidelines, are summarized in Table 9.4 and have been included in A greements with each source.

Table 9.4 BART Presumptive Limits and Operational S tandards for NO x and SO 2 at Subject-toBART Emission Units in Kansas

Subject-to-BART Emission Unit BART Presumptive Limit BART Operational Standard NO x SO 2 NO x SO 2

lb/MMBtu KCP&L - La Cygne Unit 1 0.10 0.15 KCP&L - La Cygne Unit 2 0.23 0.16* 0.15 0.15* 0.13* 0.10*
Westar Energy - Jeffrey Unit 1 0.15 0.15 0.15 0.15 Westar Energy - Jeffrey Unit 2 0.15 0.15 0.15 0.15 * Weighted average

9.3.1 Kansas City Power & Light (KCP&L) KCP&L submitted the document, BART Five Factor Analysis: Kansas City Power & Ligh t La Cygne Generating Station, for La Cygne Units 1 and 2 in August 2007 (Appendi x 9.5), prepared by Trinity Consultants. Both Units 1 and 2 meet th e presumptive definition and the BART analysis submitted determined that presumptive limi ts were BART based on the BART guidance document provided by KDHE. KDHE concurred that pre sumptive limits were BART for this50

source. During the course of implementing an enfor ceable BART agreement, KCP&L proposed limits that were more restrictive than the presumpt ive BART limits. This proposal was made in order to be consistent with an agreement KCP&L had with the Sierra Club and with the knowledge that the Kansas City metro area has been close to nonattainment for ozone. KDHE agreed that the alternative emission limits propose d by KCP&L were better than the presumptive BART limits and KDHE has incorporated these limits into the KCP&L agreement. KCP&L proposes a more restrictive limit than the pr esumptive BART NO x emission rates for Units 1 and 2 of 0.10 lb/MMBtu and 0.23 lb/MMBtu, r espectively (and 0.16 lb/MMBtu weighted average), to 0.13 lb/MMBtu on a 30-day rolling weig hted average using the already permitted selective catalytic reduction (SCR) control for Uni t 1 and some form of pre- or post-combustion control (e.g., low NO x burner, low NO x burner with overfire air, or SCR) for Unit 2. Com pliance will be demonstrated via reconfiguring the continuo us emission monitor system (CEMS) software to generate a daily report showing the two -unit 30-day rolling average. The average must remain below 0.13 lb/MMBtu, excluding periods of startup and shutdown. In the event Unit 2 suffers an outage in excess of 10 weeks, KCP &L also proposes meeting the 0.10 lb/MMBtu presumptive limit for NO x at Unit 1.

For SO 2 control, KCP&L proposes a more restrictive emissio n limit than the presumptive limit of 0.15 lb/MMBtu (weighted average), to 0.10 lb/MMB tu on a 30-day rolling weighted average, by using some form of scrubbing technology (wet scr ubber and spray dry absorber were mentioned). Compliance will be demonstrated by rec onfiguring the CEMS software to generate a daily report showing the two-unit 30-day rolling average. The average must remain below 0.10 lb/MMBtu, excluding periods of startup and shutdown

. 9.3.2 Westar Energy Westar Energy submitted the document, Jeffrey Energy Center and Gordon Evans Energy Center: BART Five Factor Analysis, for its Jeffrey Units 1 and 2 and Gordon Evans Uni t 2 in August 2007 (Appendix 9.6), prepared by Trinity Con sultants. In May 2009 Westar amended the document with additional modeling analysis for Gordon Evans. Westar Energy proposes to meet the presumptive BART NO x emission rates for Jeffrey Units 1 and 2 of 0.15 l b/MMBtu using new low NO x burner systems for each unit. For Gordon Evans Un it 2, which is a natural gas/oil-burning unit that meets the presumptive pla nt and unit size threshold, there is no prescribed presumptive limit. KDHE indicated to We star in early discussions that presumptive NO x controls consisting of “current combustion control technology” would be expected under the Regional Haze Rule. Westar’s original analysis and amendment went through the standard BART selection process which resulted in identifyin g a low NO x burner system. However, since the concurrent analysis for SO 2 reduction led to a state-approved alternative mean s of control through fuel switching to natural gas, and since fu el switching results in visibility improvements in all five Class I areas modeled by Westar Energy (30% for Wichita Mountains, for example), Kansas endorses this alternative BART control for N O x . Westar Energy proposes to meet the SO 2 presumptive limit of 0.15 lb/MMBtu for Jeffrey Uni ts 1 and 2 by rebuilding the wet scrubber on each unit. For Gordon Evans, which KDHE indicated51

would be required to meet a presumptive control (as an oil-fired unit) of burning oil with 1% sulfur content or less by weight, Westar Energy pro poses switching fuel to natural gas, with 1% sulfur fuel oil available for emergency backup use only. Westar currently has an existing supply of No.6 fuel oil on site and will be allowed to exh aust this emergency backup supply, with any future fuel oil purchases being 1% sulfur content o r less by weight. Kansas endorses this alternative BART control for SO 2 ; the switch to natural gas would virtually elimina te SO 2 emissions from Unit 2 in all cases, with the except ion being an emergency when fuel oil would be allowed only for the duration of the emergency.

9.4 Projected Emissions Reductions Resulting from I nstallation of BART Controls The application of BART to all subject-to-BART sour ces provides an estimated emission reduction from the baseline year, 2002, of 43,686 t ons per year of nitrogen oxides and 58,451 tons per year of sulfur dioxide. These reductions are detailed in Table 9.5.

Table 9.5 Projected Emissions Reductions from 2002 Levels after Installation of BART Controls

for the Subject-to-BART Emission Units in Kansas.

Projected BART Emissions Reductions

(tons/yr) Subject-to-BART Emission Unit
NO x SO 2 KCP&L - La Cygne Unit 1 27,481.6 2,700.0 KCP&L - La Cygne Unit 2 2,133.2 15,362.4 Westar Energy - Gordon Evans Unit 2 1,885.6 3,210.5 Westar Energy - Jeffrey Unit 1 5,333.6 16,927.3 Westar Energy - Jeffrey Unit 2 6,852.1 20,250.7 Totals 43,686.1 58,450.9

9.5 Enforceability of BART Requirements

• Kansas negotiated Agreements with two sources that are subject to BART, Westar and KCP&L. The agreements contain the applicable emiss ion limits, compliance schedules, and monitoring requirements which will be federally enforceable upon EPA’s approval of this SIP. The Secretary of Health and Environment has the authority to sign Agreements and enforce them under Kansas Statutes. K.S.A. 65- 3003 provides that the responsibility for air quality conservation and control of air pol lution is placed with the Secretary of Health and Environment and the Secretary shall admi nister the Kansas Air Quality Act through the Division of Environment. K.S.A 65-3005 provides that the Secretary shall have the power to: (c) Issue such orders, permits a nd approvals as may be necessary to effectuate the purposes of this act and enforce the same by all appropriate administrative and judicial proceedings and (p) Enter into contrac ts and agreements with other state agencies or subdivisions, municipalities, the feder al government or its agencies or private entities as is necessary to accomplish the purposes of the Kansas Air Quality Act. K.S.A. 65-3011 provides that the Secretary may issue an or der requiring action to implement a52

compliance plan. K.S.A. 65-3012 provides authority to enforce an administrative order in district court.

The Agreements between affected sources and the Sta te of Kansas require that each source subject to BART install and operate BART controls a s expeditiously as practicable, but in no event later than five years after approval of this SIP or plan revision by EPA. The Agreements also include a requirement that each source maintai n the control equipment and establish procedures to ensure such equipment is properly ope rated and maintained. The emissions limits in the agreements and compliance verification requi rements will be incorporated into each facility’s Title V operating permit when they are r eopened or approved. Amendments to the Agreements confirm and improve the monitoring, reco rd keeping and reporting requirements and enforceability of the Agreements.

The Agreements and Amendments for Westar and KCP&L are found in Appendix 9.7. If the 5- year progress report and/or the 10-year SIP revisio n indicate that additional controls are necessary, Kansas will consider adoption of a Regio nal Haze Regulation. The Regional Haze Regulation would adopt relevant sections of 40 CFR part 51.301 and 40 CFR Part 51 Appendix Y by reference and would outline the process by whi ch determinations would be made and enforced for BART and Reasonable Progress sources.

The Agreements between KDHE and the affected BART s ources currently exclude emissions associated with startup, shutdowns, and malfunction s (SSM) in the agreed upon emission limits. As part of the five-year review, KDHE will analyze SSM events and characterize the actual emission rates including and excluding these period s for the affected BART sources. Should the actual emissions rates including the SSM periods ex ceed the agreed upon emission rate limits, and be found to be adversely affecting visibility a t Class I areas, KDHE commits to address these emissions with a SIP modification.

9.6 Monitoring, Recordkeeping, & Reporting of BART Requirements

Monitoring, recordkeeping, and reporting requiremen ts to ensure compliance with the terms and conditions of 40 CFR Part 51 Appendix Y are require d for all units subject to BART as authorized by Kansas Air Quality Regulation 28-19-5 12. Existing monitoring and recordkeeping requirements in place at each unit will provide KDH E with sufficient data to ensure compliance with BART requirements. As stated above, amendments to the Agreements confirm and improve the monitoring, record keeping and reporting requir ements.

All but one unit subject to BART are required to ca librate, operate, and maintain a certified Continuous Emission Monitoring system (CEMS) follow ing procedures outlined in either 40 CFR 60 or 40 CFR 75, depending on applicable requir ements currently in place at each emission unit. Nitrogen oxide and sulfur dioxide emissions are monitored and recorded following procedures outlined in either 40 CFR Part 60 or 40 CFR 75. Semi-annual excess emission reports and monitoring systems performance reports are submitted and records are maintained53

following procedures in either 40 CFR 60 or 40 CFR 75. For the unit that will use fuel switching to meet the requirements of BART, the owner or oper ator will monitor and record the types and amounts of fuel oils fired and submit them as part of the semi-annual report.

List of Chapter 9 Appendices

9.1 Identification of BART-Eligible Sources in the State of Kansas 9.2 Modeling Protocol Used to Determine Subject-to- BART Sources 9.3 Results of Modeling to Screen for Sources Subje ct to BART 9.4 Guidance for Facilities Conducting a BART Analy sis 9.5 BART Analysis for KCP&L - La Cygne Units 1 and 2 9.6 BART Analysis for Westar Energy - Gordon Evans Unit 2 and Jeffrey Units 1 and 2 (including May 2009 addendum for GEEC) 9.7 BART Agreements 9.8 BART Exemption modeling – Monarch Cement Kansas City BPU – Quindaro Kansas City BPU – Nearman Westar Energy – Hutchinson Westar Energy - Lawrence54

10. Reasonable Progress Goals / Long Term Strategy The Regional Haze Rule stipulates that each state “ must address regional haze in each mandatory Class I Federal area located within the state and i n each mandatory Class I Federal area located outside the state which may be affected by emission s from within the state” [40 CFR 51.308(d)]. Although there are no Class I areas located within Kansas, the State is still required to address regional haze by determining any Class I area(s) th at may be significantly impacted by emissions from sources within the State. As part of the CENRA P RPO process, regional modeling was performed that showed several surrounding Class I a reas were being affected by sources in Kansas. It was projected that several of these Cla ss I areas would not meet a linear uniform rate of progress in 2018. With this information, Kansas anticipated the surrounding states would request that we consult with them to address the re quirements to meet reasonable progress at their Class I areas. Kansas prepared the following reasonable progress analysis to meet the requirements of the rule and to be prepared for the consultation process that was anticipated in light of the CENRAP modeling analysis.

10.1 Determining Visibility Impact Kansas is required by 40 CFR 51.308(d)(3)(iii) to d ocument the technical basis for the State’s apportionment of emission reductions necessary to m eet reasonable progress goals in each Class I area affected by the State’s emissions.

In order to address the issue of source attribution of regional haze for its member states, CENRAP contracted with ENVIRON to carry out PM Sour ce Apportionment Technology (PSAT) modeling, a well known “probing tool” for th e CAMx photochemical model. ENVIRON delivered its results in the form of a cust omized Microsoft Access database query tool, hereinafter the PSAT tool, which allows users to select among various inputs to produce charts and tables. Visibility impact can be repres ented in terms of absolute light extinction (B ext ), inverse megameters (Mm -1 ), and percent total light extinction. Data can be queried from source categories within individual states on individual o r grouped Class I area receptors, for the years 2002, 2000-2005 (baseline), and 2018 (end of curren t planning period). The PSAT tool used for this document is the third version posted, dated Ju ly 18, 2007 and available at http://www.cenrap.org/projects.asp

Kansas used the PSAT tool to find projected absolut e and percent total light extinction values at eleven Class I areas. The analysis helped determin e which Class I areas may be impacted by Kansas sources, and also provides a quantifiable ba sis of discussion for meeting the reasonable progress goals for Class I areas potentially impact ed by emission sources within Kansas.

Figures 10.1 and 10.2 below show projected 2018 per cent total extinction values for the worst 20% visibility days for nine Class I areas nearest Kansas, and two Class I areas in Texas. The Texas Class I areas were included because Kansas pa rticipated in that State’s consultation process. Figure 10.1 breaks down source contributi on by particulate species over all source categories, while Figure 10.2 shows source category contributions over all particulate species.55

Table 10.2 shows the numerical values for percent t otal extinction as well as for absolute extinction in terms of inverse megameters (Mm -1 ) for the 12 Class I areas.

Note that the nine Class I areas chosen here (besid es the two Texas areas) are the same as those selected by EPA Region 7 for Kansas for CALPUFF mod eling of the State’s BART-eligible emission sources. They comprise the set of Class Iareas nearest to Kansas in all directions around the State border. The eleven areas are:

• Caney Creek Wilderness Area, Arkansas (CACR)

• Upper Buffalo Wilderness Area, Arkansas (UPBU)

• Great Sand Dunes Wilderness Area, Colorado (GRSA)

• Rocky Mountain National Park, Colorado (ROMO)

• Hercules-Glades Wilderness Area, Missouri (HEGL)

• Mingo Wilderness Area, Missouri (MING)

• Wichita Mountains Wilderness Area, Oklahoma (WIMO)

• Badlands National Park, South Dakota (BADL)

• Wind Cave National Park, South Dakota (WICA)

• Big Bend National Park, Texas (BIBE)

• Guadalupe Mountains National Park, Texas (GUMO)

Figure 10.1 2018 Percent Total Light Extinction at Eleven Class I Areas from Kansas Sources,

by Species, for All Source Categories during the Wo rst 20% Days

0.0 1.0 2.0 3.0 4.0 5.0 6.0

CA C R UPBU GRS

A ROMO HEGL MING WIMO BA DL W ICA BIBE G

UM OPercent total extinction (%)

CM

Soil

EC

POA

NO3

SO456

Figure 10.2 2018 Percent Total Light Extinction at Eleven Class I Areas from Kansas Air Emission Sources, by Source Category, for All Speci es during the Worst 20% Visibility Days

0.0 1.0 2.0 3.0 4.0 5.0 6.0

CACR UP B U GRSA ROMO H E G L MI NG W I MO BADL WI

C A BIBE G UMOPercent total extinction (%) Nonpoint (area)

Nonroad mobile

On-road mobile

Natural Low-level point Elevated point

Table 10.1 shows actual values for the overall perc ent extinction values (total bar heights) for each of the Class I areas presented in Figures 10.1 and 10.2.

Table 10.1 2018 Percent Total and Absolute Light Ex tinction Value for Worst 20% Visibility

Days at Eleven Class I Areas Due to Kansas Air Emis sion Sources

Class I area Percent total

extinction (%) Absolute total

extinction (Mm -1 ) CACR 2.05% 1.65 UPBU 1.53% 1.25 GRSA 2.06% 0.55 ROMO 1.62% 0.47 HEGL 2.50% 2.15 MING 1.71% 1.65 WIMO 4.90% 3.53 BADL 2.23% 0.93 WICA 2.37% 0.87 BIBE 1.33% 0.57 GUMO 3.21% 1.45

All CENRAP states relied upon the regional modeling work performed by CENRAP and their contractors for determining the impact that sources within a state might have on Class I areas in57

the region. For Kansas, the modeling indicated tha t Kansas sources were most likely to have the highest impact at the Wichita Mountains in Oklahoma , with the Guadalupe Mountains in Texas being the next highest impacted area by Kansas sour ces. KDHE choose to focus its reasonable progress analysis primarily on the Wichita Mountain s because it was the location with modeling showing the highest impact from Kansas sources and was the closest Class I area where modeling indicated the linear uniform rate of progr ess for 2018 was unlikely to be met. KDHE choose not to perform a detailed analysis and discu ssion on each additional surrounding Class I area as KDHE believes that the emission reductions realized from Kansas BART sources and through the reasonable progress analysis will posit ively impact not only the Wichita Mountains but the remaining Class I areas. It is also import ant to note that CENRAP modeling indicates approximately a three percent or less light extinct ion from Kansas sources in the remaining Class I areas making a detailed analysis for each area a lower priority. Kansas instead chose to focus primarily on the Wichita Mountains, but did perform modeling and indicated the maximum impacted Class I area for each reasonable progress source analyzed as can be seen in Table 10.9.

10.1.2 Light Extinction at Wichita Mountains Figures 10.1 and 10.2 reveal that the largest contr ibutors to haze for Wichita Mountains from Kansas sources are nitrates (NO 3 ) from point sources and nonpoint (area) sources. To get a more precise idea of relative contributions, the PSAT to ol was used to generate tables for individual species, for the best 20% visibility days as well a s for the worst 20% visibility days. The Regional Haze Rule requires reasonable progress goa ls to ensure no degradation in visibility for the least impaired days at each Class I area as wel l as improvement of the worst [40 CFR 51.308(d)(1)]. Table 10.2 summarizes the PSAT tool -generated tables, which are found in Appendix 10.1. Table 10.2 shows percent total exti nction values greater than 0.5% to represent percent total extinction for the respective source category and species combinations. Values of less than 0.5% were considered to be insignificant.

Table 10.2 2018 Percent Total Light Extinction > 0. 5% Due to Kansas Sources for Worst and

Best 20% Visibility Days for the Wichita Mountains Class I Area

Source category / particulate species Percent total extinction > 0.5% (%)

Worst 20% visibility days (total extinction = 72.01 Mm -1 ) Point sources – NO 3 0.9572 Point sources – SO 4 0.8404 Area sources – POA 0.7210

Best 20% visibility days (total extinction = 15.14 Mm -1 ) Point sources – NO 3 0.7386 Point sources – SO 4 1.6518 Area sources – SO 4 0.5526 Area sources – POA 1.6600 Area sources – EC 0.649758

Appendix D of the Technical Support Document was co nsulted to find light extinction values for Wichita Mountains (see Appendix 10.2). Figure 10.3 shows the glide path for Wichita Mountains in inverse megameters, in order to compar e with the percent total extinction values derived from the PSAT tool.

Figure 10.3 shows that the 2018 extinction value on the Wichita Mountains glide path is 73.97 Mm -1 , while the 2064 (natural) extinction value is 21.2 3 Mm -1 . These values are derived from CMAQ, which is a different photochemical model than CAMx / PSAT.

Figure 10.3 Glide Path for Wichita Mountains Wilder ness Area, Oklahoma, in Terms of Light Extinction


### Uniform Rate of Reasonable Progress Glide Path Wichita Mountains - 20% Data Days

108.20

97.03

73.97

56.39

42.99

32.78

24.99 21.23 87.81

0 20 40 60 80 100 120

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 204 8 2052 2056 2060 2064 YearBext (1/Mm)

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction

The PSAT-derived value for 2018 total extinction at Wichita Mountains from Kansas sources is 72.01 Mm -1 , and is less conservative than the CMAQ value show n on the glide slope. The CMAQ value will be used here. Table 10.3 shows the absolute light extinction values attributable to Kansas emission sources by source c ategory and particulate species at Wichita Mountains, which result from combining percent tota l extinction with total extinction values.

PSAT modeling shows that by the end of the current planning period (2018), Kansas emission sources are projected to contribute only moderately to haze conditions at Wichita Mountains. On the haziest days, Kansas contributions are predicte d to be chiefly due to point sources (0.71 Mm 1 by nitrates and 0.62 Mm -1 by sulfates), and to a lesser extent area sources (0.53 Mm -1 by59

primary organic aerosols), primarily from direct em issions from burning activities or natural gas combustion. On the clearest days, Kansas contribut ions will again be due chiefly to point sources (nitrates and sulfates), with minor contrib utions of nitrates from area, biogenic, and nonroad mobile source categories.

Table 10.3 Light Extinction Attributable to Kansas Emission Sources at Wichita Mountains Class I Area, by Source Category and Particulate Sp ecies

Source category / particulate

species Percent total extinction > 0.5% 2018

projected total light extinction Kansas

attributable light extinction % Mm -1 Worst 20% visibility days
Point sources - NO 3 0.9572 73.97 0.71
Point sources - SO 4 0.8404 73.97 0.62
Area sources - POA 0.7210 73.97 0.53 Best 20% visibility days
Point sources – NO 3 0.7386 21.23 0.16
Point sources – SO 4 1.6518 21.23 0.35
Area sources – SO 4 0.5526 21.23 0.12
Area sources – POA 1.6600 21.23 0.35
Area sources – EC 0.6497 21.23 0.14

These amounts of projected light extinction are not large. For example, if the entire modeled 2018 percent extinction contribution from Kansas (4 .9%) were removed, the visibility at Wichita Mountains would improve by only 0.5 deciviews (dv). Calculations for this example are the following:

Uniform rate of progress for 2018 at WIMO = 73.97 M m -1 Kansas modeled 2018 contribution from all sources = 4.9% x 73.97 Mm -1 = 3.62 Mm -1 Converting to deciviews: 73.97 Mm -1  20.0 dv, 70.35 Mm -1  19.5 dv Visibility Improvement: 20.0 dv - 19.5 dv = 0.5 dv

Because modeled overall percent light extinction ex ceeds the threshold for visibility impact at Wichita Mountains, and the projected 2018 visibilit y at Wichita Mountains fails to fall below the glide path, additional measures for reducing visibi lity-impairing emissions at Wichita Mountains from Kansas sources beyond those achieved by instal ling controls at Kansas sources subject to BART will be needed in the future.60

10.2 Selection of Kansas Sources for Reasonable Pro gress Evaluation Under the Regional Haze Rule 40 CFR 51.308(d), “sta tes must address regional haze in each mandatory Class I Federal area located within the S tate and in each mandatory Class I Federal area located outside the State which may be affecte d by emissions from within the State. To meet the core requirements for regional haze for these a reas, the State must submit an implementation plan containing the following plan elements and sup porting documentation for all required analyses: (1) Reasonable progress goals. (2) Calculations of baseline and natural visibility conditions . (3) Long-term strategy for regional haze . (4) Monitoring strategy and other implementation plan requirements .” This language was the basis for Kansas to develo p this
process. According to the Rule, “In establishing a reasonabl e progress goal for any mandatory Class I Federal area within the state, the state must: cons ider the costs of compliance, the time necessary for compliance, the energy and non-air quality envi ronmental impacts of compliance, and the remaining useful life of any potentially affected s ources, and include a demonstration showing how these factors were taken into consideration in selecting the goal” [40 CFR 51.308(d)(1)(i)(A)]. This part of the Regional Haz e Rule is the basis for the four factor analysis.

EPA’s Guidance for Setting Reasonable Progress Goals unde r the Regional Haze Program

, states:

In determining reasonable progress, CAA Section 169 A(g)(1) requires states to take into consideration a number of factors. However, [states ] have flexibility in how to take into consideration these statutory factors and any other factors that [states] have determined to be relevant. For example, the factors could be used to select which sources or activities should or should not be regulated, or they could be used to determine the level or stringency of control, if any, for selected sources or activities, or some combination of both. The factors may be considered both individual ly and/or in combination (6).

In addition, EPA’s guidance suggests the following measures:

• Identify the key pollutants and sources and/or sour ce categories that are contributing to visibility impairment at each Class I area. The so urces of impairment for the most impaired and least impaired days may differ.

• Identify the control measures and associated emissi on reductions that are expected to result from compliance with existing rules and othe r available measures for the sources and source categories that contribute significantly to visibility impairment.

• Determine what additional control measures would be reasonable based on the statutory factors and other relevant factors for the sources and/or source categories.

• Estimate through the use of air quality models the improvement in visibility that would result from implementation of the control measures found to be reasonable and compare this to the uniform rate of progress.61

In order to perform this analysis for point sources , the State of Kansas developed a multi-step process, to apply the statutory factor analysis in a manner that is both equitable and simple. The first several steps used readily available actual e missions, visibility impact modeling, and cost of controls (i.e., cost of compliance) estimates to id entify, screen, and rank the State’s large emission facilities. Geographic location was not c onsidered, since this process was carried out before state consultations had begun.

Each of the facilities remaining from the initial s creening were then scrutinized for the statutory factors of time necessary, energy and non-air quali ty environmental impacts, and remaining useful life, resulting in a ranked list of faciliti es that would potentially be called on to install controls if further emission reductions are necessa ry to meet the reasonable progress goal at a given Class I area.

The process steps are as follows:

1. Identify all Kansas emission units that had greater than or equal to 500 tons for NO x and/or SO 2 2. Identify the most effective control technologies an d screen for excessive cost 3. Model visibility impacts and screen for low-impact facilities 4. Calculate, screen, and rank based on cost per ton p er deciview 5. Screen for non-cost statutory factors, i.e., time n ecessary for compliance, energy and nonair quality environmental impacts of compliance, an d remaining useful life 6. Re-sort and make final ranked list of potential fac ilities

Step 1: Identify 500 ton NO x and SO 2 emission units Using the 2002 base year inventory, a database quer y was run on the Kansas point source emissions inventory to find all emission units whos e NO x and/or SO 2 emissions were 500 tons per year or more. Kansas chose to use 500 tons for two reasons. First, this is the level agreed upon in discussions among CENRAP members for this p urpose; and second, visibility impacts from modeling that Kansas has performed on larger s ources indicate a 500 ton source would not significantly impact (> 0.5 delta deciview) a surro unding Class I area. The latter reason applies for all locations within the State as Kansas contai ns no Class I areas. The closest Class I area is Hercules Glades, Missouri, and is a distance of 151 km from the Kansas state line. A total of 30 NO x units and 28 SO 2 units were found. Of this set of emission units, 8 NO x and 10 SO 2 units were removed from the initial candidate list for th e following reasons:

The remaining set of 22 NO x units included 11 electric generating units (EGUs) , 6 cement kilns, 2 gas compressor engines, 1 refinery fluid-bed cata lytic cracking unit (FCCU) , 1 ammonia plant, and 1 glass furnace, all located at 15 facilities. The 18 SO 2 units were comprised of 13 EGUs, 4

Reason for exclusion NO x units SO 2 units Already subject to BART 6 6 Controls installed since 2002 (now <500 tons) 2 2 Source has no commercially available controls 0 262

cement kilns, and 1 refinery FCCU, all located at 1 2 facilities. These data are detailed in Table 10.4.

Step 2: Identify most effective control technologie s and screen for excessive cost Next, each of the 500 ton or greater units was alig ned with the emission control technology selected for it by the CENRAP contractor, Alpine Ge ophysics, utilizing the least marginal cost. For units not identified by Alpine, EPA’s AirContro lNET version 4.1 was used to identify control technologies, control efficiencies, and cos ts. The most appropriate control identified by the AirControlNET program was selected. Refinement s to this selection process were made for two facilities, and are summarized in Table 10.5.

Table 10.4 Kansas Emission Units Not Subject to BAR T Emitting at Least 500 Tons/Yr of NO x or SO 2 in 2002

2002 NO x 2002 SO 2 Source ID Facility Unit ton/yr 0910057 AGC Flat Glass North America Glass furnace 1,375 [234.2] 1 1330001 Ash Grove Cement Kiln 2,121 747 0210002 Empire District Electric -

Riverton Unit 7 582 2,393

0210002 Empire District Electric -

Riverton Unit 8 1,040 866

0150004 Frontier El Dorado Refinery FCCU 688 856 1250015 Heartland Cement Kiln 928 1,007 2090048 Kansas City BPU - Quindaro Unit 1 1,599 1,288 2090048 Kansas City BPU - Quindaro Unit 2 1,330 2,123 2090008 Kansas City BPU – Nearman Unit 1 3,860 7,625 0930012 Kinder Morgan - Lakin Station EU-2 579 [0.1] 0570003 Koch Nitrogen Ammonia plant 585 [0.5]

2057022 Lafarge Midwest - Fredonia Kiln 1 596 660 2057022 Lafarge Midwest - Fredonia Kiln 2 883 978 0010009 Monarch Cement Kiln 4 652 [74.7] 0010009 Monarch Cement Kiln 5 972 [254.6] 0670035 ONEOK - Ulysses Station Clark 1 619 [0.1] 0550023 Sunflower Electric - Holcomb Unit 1 3,781 1,669 1730012 Westar Energy - Gordon Evans Unit 1 [208.5] 618 1550033 Westar Energy - Hutchinson Unit 4 [209.2] 734 1490001 Westar Energy – Jeffrey Unit 3 10,481 23,206 0450014 Westar Energy – Lawrence Unit 3 738 1,965 0450014 Westar Energy – Lawrence Unit 4 2,037 1,430 0450014 Westar Energy – Lawrence Unit 5 3,762 4,354 1770030 Westar Energy – Tecumseh Unit 7 1,531 2,693 1770030 Westar Energy – Tecumseh Unit 8 1,877 4,515

1 Values within brackets indicate 2002 emissions les s than 500 tons per year.63

Table 10.5 Refinements to AirControlNET Control Tec hnology Determinations

Emission unit Alpineselected control Control

actually selected Comment

Sunflower Electric - Holcomb Unit 1 Low NO x

burner with overfire air Low NO x

burner Source stated boiler

configuration prohibits use of overfire air

AGC Flat Glass North America Oxy-firing Selective noncatalytic reduction Source stated extra O 2 impacts

glass quality adversely

Also, in conformance with cost levels agreed upon b y CENRAP members as excessive, control technologies whose cost exceeded $10,000/ton reduce d at a given emission unit were screened out at this step. As a result, eight SO 2 emission units were dropped from the list of candi date units, and are listed in Table 10.6, which shows ea ch unit’s cost per ton reduced that was over $10,000/ton.

Table 10.6 Sources with Cost per Ton Reduced Greate r than $10,000/ton

SO 2 emission unit Cost per ton reduced Frontier El Dorado Refinery FCCU $14,069 Empire District Electric - Riverton Unit 7 $11,066 Heartland Cement Kiln $28,435 Westar Energy - Lawrence Unit 4 $40,598 Sunflower Electric - Holcomb Unit 1 $10,767 Ash Grove Cement Kiln $24,305 Lafarge Midwest - Fredonia Kiln 1 $20,127 Lafarge Midwest - Fredonia Kiln 2 $13,586

Calculations for fuel switching at Westar’s Hutchin son Energy Center Unit 4 and Gordon Evans Energy Center Unit 1 involved analysis of the price of natural gas and #6 residual oil based on publicly available information from the Energy Info rmation Administration (7). Calculations for Hutchinson Unit 4 included switching to all natural gas with the equivalent heat input of the 4,195 thousand gallons (Mgal) of #6 oil and 1,240 m illion cubic feet (MMcf) of natural gas burned in 2002. Gordon Evans Unit 1 included fuel switching to all natural gas based on 3,930 Mgal #6 oil and 865 MMcf natural gas in 2002. The price of natural gas used in the calculations was $1,200/Mgal for #6 oil and was $8,000/MMscf for natural gas. Prices from June 2005 to November 2006 were used to reflect more current pri ces. Negative cost results for both units (-$135/ton and -$37/ton, respectively) imply that t he residual oil burned in 2002 was purchased at a lower price than the amount used for this anal ysis. Also, although fuel switching for these two units was selected as a control strategy for SO 2 , some control of NO x was achieved as well, and was included in the CALPUFF modeling in Step 3 below.64

Table 10.7 shows a summary of Step 2 results.

Table 10.7 Most Effective Control Technologies with Acceptable Control Costs for Kansas 500- Ton NO x and SO 2 Emission Units

Source ID Facility Unit Selected control

measure Control

efficiency (%) Cost per ton

reduced ($2002 AirControlNET or $2005 Alpine) Source

NO x sources

0910057 AGC Flat

Glass North America Glass

Furnace SNCR 40.0 $1,041 AirControlNET

1330001 Ash Grove

Cement Cement

Kiln LNB 25.0 $509 AirControlNET

0210002 Empire District

Electric - Riverton Unit 7 LNBO 55.9 $1,398 Alpine

0210002 Empire District

Electric - Riverton Unit 8 LNC3 53.1 $873 Alpine

0150004 Frontier El

Dorado Refinery FCCU LNB + FGR 55.0 $5,314 Alpine

1250015 Heartland

Cement Cement

Kiln Mid-kiln firing 30.0 $83 Alpine

2090008 Kansas City

BPU – Nearman Unit 1 LNB+OFA+NN 45.2 $750 BPU – 2006 dollars

2090048 Kansas City

BPU - Quindaro Unit 1 NGR 50.0 $579 Alpine

2090048 Kansas City

BPU - Quindaro Unit 2 LNB 40.3 $849 AirControlNET

0930012 Kinder Morgan

- Lakin Station EU-2 A/F + IR 30.0 $2,027 AirControlNET

0570003 Koch Nitrogen Ammonia Plant OT + WI 65.0 $688 Alpine

2057022 Lafarge

Midwest - Fredonia Kiln 1 Mid-kiln firing 30.0 $83 Alpine

2057022 Lafarge

Midwest - Fredonia Kiln 2 Mid-kiln firing 30.0 $83 Alpine

0010009 Monarch

Cement Kiln 4 Biosolid injection 23.0 $466 Alpine
0010009 Monarch Kiln 5 Biosolid 23.0 $466 Alpine65 Cement injection

0670035 ONEOK -

Ulysses Station Clark 1 A/F + IR 30.0 $323 Alpine

0550023 Sunflower

Electric - Holcomb Unit 1 LNB 16.0 $1,383 AirControlNET

1490001 Westar Energy

- Jeffrey Unit 3 LNC3 58.3 $1,560 Alpine

0450014 Westar Energy

- Lawrence Unit 3 LNC1 33.1 $683 Alpine

0450014 Westar Energy

- Lawrence Unit 4 LNC1 43.3 $325 Alpine

0450014 Westar Energy

- Lawrence Unit 5 LNC3 58.3 $1,628 Alpine

1770030 Westar Energy

- Tecumseh Unit 7 LNC1 33.1 $432 Alpine

1770030 Westar Energy

- Tecumseh Unit 8 LNC3 53.1 $518 Alpine

SO 2 sources

0210002 Empire District

Electric - Riverton Unit 8 FGD wet scrubber 90.0 $5,782 Alpine

2090008 Kansas City

BPU – Nearman Unit 1 Semi-Dry scrubber 88.5 $2,024 BPU - 2006 dollars

2090048 Kansas City

BPU - Quindaro Unit 1 FGD wet scrubber 90.0 $5,825 Alpine

2090048 Kansas City

BPU - Quindaro Unit 2 FGD wet scrubber 90.0 $3,522 Alpine

1730012 Westar Energy

- Gordon Evans Unit 1 Fuel switching 99.9 ($37) KDHE

1550033 Westar Energy

- Hutchinson Unit 4 Fuel switching 99.9 ($135) KDHE

1490001 Westar Energy

- Jeffrey Unit 3 FGD wet scrubber 75.0 $1,695 AirControlNET

0450014 Westar Energy

- Lawrence Unit 3 FGD wet scrubber 90.0 $5,339 Alpine

0450014 Westar Energy

- Lawrence Unit 5 FGD wet scrubber 79.2 $9,265 AirControlNET

1770030 Westar Energy

- Tecumseh Unit 7 FGD wet scrubber 90.0 $4,519 Alpine

1770030 Westar Energy

- Tecumseh Unit 8 FGD wet scrubber 90.0 $3,715 Alpine66

Step 3: Model visibility impacts and screen for low -impact facilities

Visibility impact modeling with NO x and SO 2 impacts combined For the 22 NO x and 10 SO 2 units within 17 facilities remaining, the next ste p involved measuring visibility impacts at each of the same nine Class I areas chosen for finding facilities subject to BART. Essentially the same CALPUFF protocol was fo llowed as for BART screening, so modeling was carried out on a facility-by-facility basis, and NO x and SO 2 impacts were calculated together. Post-control model inputs for emissions were calculated using the control efficiencies included with each control technology selected in Step 2. Instead of looking at number of days with greater than 1 dv impact as was done for BART screening, in this analysis actual deciview values for each facility’s nine mod eled impacts were pulled from the postprocessing file and examined. Pre- and post-co ntrol 98 th percentile deciview values for the Class I area with greatest impact were recorded, an d are presented in the following table. Respective differences in deciview are labeled as v isibility improvements and the Class I areas with greatest impact is shown.

In addition, facilities whose highest pre-control 9 8 th percentile impacts were less than 0.100 dv were screened out in this step. These are shown in the CALPUFF results table below in gray shading:

Table 10.8 Overall Visibility Improvements Resultin g from Application of Most Effective

Controls at Selected Kansas 500-Ton NO x and SO 2 Emission Units

Source ID Facility Max. 98th percentile pre-control Max. 98th

percentile post-control Visibility

improvement (pre - post) Class I area

impacted

dv dv dv

0910057 AGC Flat Glass

North America 0.065 0.043 0.022 Upper Buffalo

1330001 Ash Grove

Cement 0.110 0.086 0.024 Upper Buffalo

0210002 Empire District

Electric - Riverton 0.257 0.165 0.092 HerculesGlades

0150004 Frontier El

Dorado Refinery 0.068 0.053 0.015 Wichita Mountains

1250015 Heartland Cement 0.069 0.053 0.016 HerculesGlades

2090048 Kansas City BPU

- Quindaro 0.215 0.082 0.133 HerculesGlades

0930012 Kinder Morgan -

Lakin Station 0.021 0.015 0.006 Wichita Mountains

0570003 Koch Nitrogen 0.028 0.010 0.018 Wichita Mountains 2057022 Lafarge Midwest 0.111 0.105 0.006 Wichita67 - Fredonia Mountains
0010009 Monarch Cement 0.074 0.066 0.008 Upper Buffalo

0670035 ONEOK -

Ulysses Station 0.026 0.018 0.008 Wichita Mountains

0550023 Sunflower

Electric - Holcomb 0.189 0.173 0.016 Wind Cave

1730012 Westar Energy -

Gordon Evans 0.117 0.006 0.111 Wichita Mountains

1550033 Westar Energy -

Hutchinson 0.039 0.008 0.031 Wichita Mountains

1490001 Westar Energy -

Jeffrey 1.174 0.341 0.833 Wichita Mountains

0450014 Westar Energy -

Lawrence 0.428 0.285 0.143 HerculesGlades

1770033 Westar Energy -

Tecumseh 0.308 0.094 0.214 HerculesGlades Note that Kansas City BPU Nearman was not evaluated in this table because at the time this modeling wa s performed, the Nearman facility was determined to b e a BART source (see Chapter 9). The facility is included below in Table 10.9.
Visibility impact modeling with NO x and SO 2 impacts separated As a refinement to Step 3, CALPUFF was rerun for th e five largest remaining sources, all of which are EGUs, and the impacts of NO x and SO 2 were calculated separately.

The following table summarizes Step 3 results.

Table 10.9 Selected Kansas 500-ton NO x and SO 2 Emission Units Showing Significant Visibility

Improvement Resulting from Application of Most Effe ctive Controls

Source ID Facility Max. 98th percentile pre-control Max. 98 th

percentile post-control Visibility

improvement Class I area

impacted

Dv NO x SO 2 NO x SO 2 1330001 Ash Grove Cement 0.110 0.090 0.024 Upper Bu ffalo

0210002 Empire District Electric -

Riverton 0.257 0.205 0.145 0.052 0.112 Hercules-Glades

2090048 Kansas City BPU -

Quindaro 0.215 0.174 0.142 0.041 0.073 Hercules-Glades

2090008 Kansas City BPUNearman 0.378 0.318 0.198 0.060 0.180 Hercules-Glades

2057022 Lafarge Midwest -

Fredonia 0.111 0.105 0.006 Wichita Mountains

0550023 Sunflower Electric -

Holcomb 0.189 0.170 0.016 Wind Cave

1730012 Westar Energy - Gordon

Evans 0.117 0.010 0.111 Wichita Mountains68

1490001 Westar Energy - Jeffrey 1.174 1.06 0.469 0. 114 0.705 Wichita Mountains

0450014 Westar Energy -

Lawrence 0.428 0.329 0.310 0.099 0.118 Hercules-Glades

1770033 Westar Energy -

Tecumseh 0.308 0.271 0.159 0.037 0.149 Hercules - Glades

Step 4: Calculate, screen, and rank based on cost p er ton per deciview The final calculation is the derivation of cost per ton per unit of change in deciview, the metric used to sort the remaining sources for meeting reas onable progress goals. The single value of cost per ton per deciview combines cost and visibil ity improvement in such a way that its numeric value increases: (1) as cost of controls in creases; and (2) as visibility improvement decreases. Thus, the facility with the lowest cost per ton per deciview would be the first to be reviewed for possible controls to meet reasonable p rogress goals if further emission reductions of NO x or SO 2 are needed.

For the five higher-impact sources (from Step 3), N O x and SO 2 impacts were kept separate for this step, since future needs may call for cuts in NO x only or SO 2 only. Following is a summary table, Table 10.10, showing Step 4 results.

Table 10.10 Ranked List of Kansas Facilities, Emiss ion Units, and Controls after Cost and Visibility Screening

Source ID Facility Pollutant Emission unit(s) Cost per

ton 1 Visibility

improvement Class I

area (98 th percentile) Cost per ton

per dv

$2002 Dv $2002/ton-dv

1330001 Ash Grove Cement NO x Cement kiln $509 0.024 Upper Buffalo $21,208

0210002 Empire District

Electric - Riverton NO x Units 7 & 8 $984 2 0.052 HerculesGlades $18,923

0210002 Empire District

Electric - Riverton SO 2 Unit 8 $5,326 0.112 HerculesGlades $47,554

2090048 Kansas City BPU -

Quindaro NO x Units 1 & 2 $660 0.041 HerculesGlades $16,098

2090048 Kansas City BPU -

Quindaro SO 2 Units 1 & 2 $4,045 0.073 HerculesGlades $55,411

2090008 Kansas City BPU -

Nearman NO x Unit 1 $743 3 0.060 HerculesGlades $12,383

2090008 Kansas City BPU -

Nearman SO 2 Unit 1 $2,024 3 0.213 Caney Creek $9.502

2057022 Lafarge Midwest -

Fredonia NO x Kilns 1 & 2 $76 0.006 Wichita Mountains $12,667

0550023 Sunflower Electric -

Holcomb NO x Unit 1 $1,383 0.016 Wind Cave $86,43869

1730012 Westar Energy -

Gordon Evans SO 2 Unit 1 ($37) 0.111 Wichita Mountains ($333)

1490001 Westar Energy -

Jeffrey NO x Unit 3 $1,437 0.114 Wichita Mountains $12,605

1490001 Westar Energy -

Jeffrey SO 2 Unit 3 $1,695 0.705 Wichita Mountains $2,404

0450014 Westar Energy -

Lawrence NO x Units 3, 4, & 5 $989 0.099 HerculesGlades $9,990

0450014 Westar Energy -

Lawrence SO 2 Units 3 & 5 $7,791 0.118 HerculesGlades $66,025

1770030 Westar Energy -

Tecumseh NO x Units 7 & 8 $450 0.037 HerculesGlades $12,162

1770030 Westar Energy -

Tecumseh SO 2 Units 7 & 8 $3,699 0.149 HerculesGlades $24,826

1 Alpine Geophysics reported costs in $2005, which h ave here been adjusted to 2002 dollars using a fact or derived the ratio of Consumer Price Index average price dat a values for the two years, or 179.9/195.3 = 0.9211 5 (8)
2 Empire submitted estimates of $2,427 (60% efficie nt) and $1,826 (30% efficient) for NOx controls on Units 7 and 8, respectively. The values shown are from Alpine, however, since further visibility modeling was not carried out for the source.
3 Cost supplied by Kansas City BPU in an engineerin g analysis report. Costs are in 2006 dollars.

Step 5: Screen for non-cost statutory factors

The table below presents a summary of the three non -cost statutory factors analyzed for the source remaining after cost and visibility impact w as considered.

Table 10.11 Summary of Reasonable Progress Non-Cost Statutory Factors for Selected Kansas Point Sources

Source ID Facility Pollutant Emission unit(s) Selected

control

measure Compliance

Timeframe Non-air

quality environmental impacts Remaining

useful life

NO x

1330001 Ash Grove

Cement NO x Cement kiln LNB Potential permitting issues, control device energy requirements 10-30 years

0210002 Empire District

Electric - Riverton NO x Unit 7 LNBO

0210002 Empire District

Electric - Riverton NO x Unit 8 LNC3 3-4 years following SIP approval

Potential

permitting issues, reduction in electricity production capacity 5-10 years70

2090048 Kansas City

BPU - Quindaro NO x Unit 1 NGR

2090048 Kansas City

BPU - Quindaro NO x Unit 2 LNB 30-50 years

2090008 Kansas City

BPU - Nearman NO x Unit 1 LNB+OFA+NN Potential permitting issues, reduction in electricity production capacity 30-50 years

2057022 Lafarge

Midwest - Fredonia NO x Kilns 1 & 2 Mid-kiln firing Control device
energy requirements 10-30 years

0550023 Sunflower

Electric - Holcomb NO x Unit 1 LNB

1490001 Westar Energy

- Jeffrey NO x Unit 3 LNC3

0450014 Westar Energy

- Lawrence NO x Units 3 & 4 LNC1

1770030 Westar Energy

- Tecumseh NO x Unit 7 LNC1

1770030 Westar Energy

- Tecumseh NO x Unit 8 LNC3 Potential permitting issues, reduction in electricity production capacity 30-50 years

SO 2

0210002 Empire District

Electric - Riverton SO 2 Unit 8 FGD wet scrubber 5-10 years

2090048 Kansas City

BPU - Quindaro SO 2 Units 1 & 2 FGD wet scrubber 3-4 years

following SIP approval Potential

permitting &
wastewater issues, reduction in electricity production capacity

2090008 Kansas City

BPU - Nearman SO 2 Unit 1 Semi-Dry scrubber 3-4 years

following SIP approval Potential

permitting issues, reduction in electricity production capacity

1730012 Westar Energy

- Gordon Evans SO 2 Unit 1 Fuel switching Currently feasible —

1490001 Westar Energy

- Jeffrey SO 2 Unit 3 FGD wet scrubber

1770030 Westar Energy

- Tecumseh SO 2 Units 7 & 8 FGD wet scrubber 3-4 years

following SIP approval Potential

permitting &
wastewater issues, reduction in electricity production capacity 30-50 years71

The two EGUs at Empire District - Riverton, Units 7 and 8, have startup dates of 1950 and 1954, respectively, and it is likely they will be retired before 2018. It is unknown why the IPM 3.0 future year modeling did not reflect this, but mere ly indicated reduced (controlled) SO 2 emissions for Unit 7 starting in 2010. In addition , there is currently a question about Westar Energy’s ability to use wet scrubbers at its Jeffre y facility, which is comprised of Units 1 and 2 (subject to BART) and 3 (under scrutiny here), due to environmental concerns for wastewater sulfur levels. Step 6: Source ranking The final step is source ranking, which is simply l isting the sources from Step 5 in increasing order of cost per ton per deciview, and trimming th e list at a natural break in the results, which occurred at $15,000 per ton per dv. The final ranke d list is given below in Table 10.12.

Table 10.12 Ranked List of Sources under the Reason able Progress Analysis

Rank Source

ID Facility Emission unit(s) Pollutant Visibility improvement Cost per ton per deciview

Dv $2002/ton-dv

1 1730012 Westar Energy -

Gordon Evans Unit 1 SO 2 0.111 ($333)

2 1490001 Westar Energy –

Jeffrey Unit 3 SO 2 0.705 $2,404

3 2090008 Kansas City BPU -

Nearman Unit 1 SO 2 0.213 $9,502 a

4 0450014 Westar Energy –

Lawrence Units 3, 4, &

5 NO x 0.099 $9,990

5 1770030 Westar Energy –

Tecumseh Units 7 & 8 NO x 0.037 $12,162

6 2090008 Kansas City BPU -

Nearman Unit 1 NO x 0.060 $12,383

7 1490001 Westar Energy –

Jeffrey Unit 3 NO x 0.114 $12,605

8 2057022 Lafarge Midwest –

Fredonia Kilns 1 & 2 NO x 0.006 $12,667

a Cost is based on 2006 dollars at Caney Creek. Herc ules-Glades cost is $11,244 again in 2006 dollars.72

10.3 Reasonable Progress Conclusions The results of this process are described below. K ansas determined that controls or fuel switching on the sources listed below are reasonabl e and will result in significant visibility improvements at the Wichita Mountains Wilderness Ar ea:

• Westar Energy –

o Gordon Evans Unit 1 — Westar will implement fuel sw itching to natural gas at all times, with the only exception being a g as curtailment order from the gas supplier, in which case the facility will b e allowed to utilize backup #6 fuel oil.

o Jeffrey Unit 3 — Westar will install controls for b oth NO x and SO 2
. Emissions limits will be established at control lev els of 0.15 lb/MMBtu for SO 2 and 0.15 lb/MMBtu for NO x . o Lawrence Units 3, 4, & 5, and Tecumseh Units 7/9 & 8/10 — Westar has agreed to controls or emission limits at each of th ese units and are outlined in Table 10.14 in section 10.4.3.3.

For the remaining facilities identified in the tabl e above:

• BPU - Nearman Unit 1. This source primarily impact s the Class I areas in Missouri and Arkansas. Through the consultation process wit h Missouri and Arkansas it was determined that no additional controls beyond expec ted BART and on the books controls would be needed for the Class I areas in t hese states. However, with the vacatur of the Clean Air Interstate Rule (CAIR), an on the books rule covering many sources in Missouri and Arkansas, that occurred on July 11, 2008, and subsequent December 23, 2008, remanding of the case back to EP A without vacatur so that EPA could remedy CAIR’s flaws as were discussed in the courts July ruling, it may be necessary to revisit the consultation process with Missouri and Arkansas and reconsider whether controls on Nearman Unit 1 shoul d be required. This consultation would occur once a final CAIR decision is made and would be initiated by Missouri and/or Arkansas.

• Lafarge Midwest - Fredonia Kilns 1 & 2- Kansas held a conference call with representatives from each of the four cement facili ties in the State. A request for information was made for feedback regarding the tec hnical feasibility and cost estimates for the controls identified by Alpine and AirControlNET. The 2018 estimates show a growth in emissions for three of t he state’s facilities to be in the range of 40-60 % increases between 2002 and 2018. Industry representatives did not agree with these estimates. Additionally, informat ion received from the information request raised concerns regarding design and lay-ou t constraints of some of the control technologies identified. These considerati ons combined with the small level of improvements in visibility gained by controls at this facility (0.006 dv for Wichita73 Mountains), led to the decision not to require cont rols at this time. Additional technical and cost evaluations will be conducted du ring the five-year progress review.

Overall, the State expects to achieve reductions of approximately 11,500 tons/yr of reductions in NO x and 26,000 tons/yr of reductions in SO 2 from the sources required to control as part of the regional haze reasonable progress goals. Table A10 .3.1 in Appendix 10.3 shows the derivation for these values.

CENRAP has also performed a control strategy run (d iscussed in Chapter 8) that included sources identified above along with several additio nal sources. This control run identified the following Kansas sources based on selection criteri a approved by the CENRAP Policy Oversight Group (POG). The selection criteria and modeled co ntrols can be found on the CENRAP website at http://www.cenrap.org/projects.asp . The Kansas sources identified are shown in Table 10.13 below.

Table 10.13 Kansas Sources Identified in the Contro l Strategy PSAT Run

Source ID Facility Pollutant: NO

x 2057022 Lafarge Midwest - Fredonia 0010009 Monarch Cement 0450014 Westar Energy - Lawrence 2090048 Kansas City BPU - Quindaro 1490001 Westar Energy - Jeffrey 0910057 AGC Flat Glass North America 0210002 Empire District - Riverton 1070005 KCP&L - La Cygne 2090008 Kansas City BPU - Nearman 0550023 Sunflower Electric - Holcomb 1250015 Heartland Cement Pollutant: SO 2 1770030 Westar Energy - Tecumseh 2090008 Kansas City BPU - Nearman 2090048 Kansas City BPU - Quindaro 2090049 Kansas City BPU - Kaw

Kansas City BPU - Kaw has been on cold stand-by sin ce 2001 (Unit 1) and 2003 (Unit 3); Unit 2 was retired in 1992. Any additional controls requi red for this facility would be determined and implemented should the facility restart.

The State of Kansas is currently finalizing a NO x Emission Reduction Rule as part of the implementation of the Kansas City Ozone Maintenance Plan (see section 10.4.3.1.9). The timeframe for implementation of the NO x Emission Reduction Rule will achieve emission74

reductions sooner than would have been achieved und er the Regional Haze Rule, therefore, we are not pursuing further NO x controls from the Nearman facility at this time.

Kansas commits to review emissions changes and pote ntial new technology developments that may apply to the sources identified above as part o f the five-year progress report. If a determination is made that controls are feasible, c ost-effective, and needed for visibility improvements, the State will explore additional con trols at that time.

10.4 Long-Term Strategy

Kansas is required by 40 CFR 51.308(d)(3) to submit a long-term strategy that addresses visibility impairment for each mandatory Class I Fe deral area within and outside the State which may be affected by emissions from within the State. The long-term strategy must include enforceable emissions limitations, compliance sched ules, and other measures necessary to achieve the reasonable progress goals established b y states where the Class I areas are located. This section describes how Kansas meets the long-te rm strategy requirements.

10.4.1 Share of Emission Reductions

Kansas is required by 40 CFR 51.308(d)(3)(ii) to de monstrate that its implementation plan includes all measures necessary to obtain its fair share of emission reductions needed to meet reasonable progress goals.

The technical analysis discussed in Chapter 10 demo nstrates that the State’s long-term strategy, when coordinated with other state/tribes’ strategie s, is sufficient to meet reasonable further progress goals.

10.4.1.1 Baseline Inventory

Kansas is required by 40 CFR 51.308(d)(3)(iii) to i dentify the baseline inventory on which the long-term strategy is based.

Kansas used the 2002 CENRAP Base G Emissions Invent ory as its baseline inventory. See Table 7.1, Chapter 7.

10.4.2 Anthropogenic Sources of Visibility Impairme nt

Kansas is required by 40 CFR 51.308(d)(3)(iv) to id entify all anthropogenic sources of visibility impairment considered by the State in developing it s long-term strategy.

Appendix 7.1 provides the 2002 emissions inventory used in developing this SIP.75

10.4.3 Factors the State Must Consider

Kansas is required by 40 CFR 51.308(d)(3)(v) to con sider several factors in developing its longterm strategy. These are discussed below.

10.4.3.1 Emission Reductions Due to Ongoing Air Pol lution Programs

Kansas is required by 40 CFR 51.308(d)(3)(v)(A) to consider emission reductions from ongoing air pollution control programs.

Kansas considered the following ongoing programs in developing its long-term strategy: onboard refueling vapor recovery (ORVR), on-board dia gnostics (OBD), federal on-road and nonroad emission standards, low sulfur fuel standar ds, the Kansas City Ozone Maintenance Plan, the Clean Air Interstate Rule (CAIR), National Emis sion Standards for Hazardous Air Pollutants (NESHAP), and Agreements between the State and cert ain facilities. Significant reductions in NO x , PM, and SO 2 are expected due to existing and new federal standards for on-road and nonroad engines and fuels

. 10.4.3.1.1 On-Board Refueling Vapor Recovery (ORV R) In 1994, federal standards were promulgated requiri ng new vehicles to be equipped with onboard refueling vapor recovery (ORVR) technology. The phase-in of ORVR was completed as follows:

• Light duty vehicles (<6,000 lbs) began in 1998 and were completed in 2000

• Pickup trucks and SUVs (6,001-8,500 lbs) began in 2 001 and were completed in 2003

• Heavy duty vehicles (8,501-10,000lbs) began in 2004 and will be completed with the 2006 model year

10.4.3.1.2 On-Board Diagnostics (OBD) The first version of On-Board Diagnostic systems (O BD I) was implemented in 1988. A second version (OBD II) was developed to expand on the ear lier technology. The Clean Air Act Amendments of 1990 mandated that beginning in 1996, all light-duty cars and trucks be equipped with OBD II systems. Beginning in the mod el year 2004, all medium duty vehicles weighing up to 14,000 pounds were also required to be equipped with OBD II. Beginning with the model year 2010, all heavy-duty vehicles weighi ng over 14,000 pounds are required to be equipped with OBD II.

10.4.3.1.3 Tier 2 Vehicle and Gasoline Sulfur Pro gram Under the Tier 2 program, which was adopted in 1999 , new emission standards were developed for passenger cars, light duty trucks, and larger p assenger vehicles which were placed in a new classification called “medium-duty passenger vehicl es.” The medium-duty vehicles include pickup trucks, sports utility vehicles (SUVs), and vans . The phase-in of new standards began with model year (MY) 2004, and was completed in MY 2007 for cars and light-duty trucks, and in76

2008 for medium-duty vehicles. By 2007, the emissi on limit for NO x was 0.07 grams per mile (g/mi). In addition to more stringent emission sta ndards for vehicles, the Tier 2 program also required reductions in sulfur levels in gasoline to be phased in between the years 2000 and 2006. The sulfur levels in gasoline were capped at 300 pa rts per million (ppm) and limited to an average of 120 ppm in 2004, and by 2006 the cap was lowered to 80 ppm with a limit on average sulfur levels of 30 ppm. 10.4.3.1.4 Clean Air On-Road Diesel Rule (2007 Hi ghway Rule) In December of 2000, the EPA promulgated the Clean Air On-Road Diesel Rule, also called the 2007 Highway Rule. The rule has two components, em ission standards and diesel fuel regulation. The new emission standards include lim its on PM, NO x , and non-methane hydrocarbons (NMHC). The PM standard took effect i n the 2007 model year, while the NO x and NMHC standards will be phased in between 2007 and 2 010. The diesel fuel regulation limits the sulfur content in on-highway diesel fuel to 15 ppm. Ultra low sulfur diesel fuel became available nationwide in October 2006.

10.4.3.1.5 Clean Air Nonroad Diesel Rule The first federal standards (Tier 1) for new nonroa d diesel engines over 50 horsepower (hp) were adopted in 1994 and were phased in between 1996 and 2000. In 1998 EPA finalized a new rule, which applied Tier 1 to equipment under 37 hp and a pplied more stringent Tier 2 and Tier 3 standards to all equipment with phase-in schedules between 2000 and 2008. The Tier 1–3 standards consisted primarily of engine design stan dards, with no or very limited use of exhaust after-treatment. In May 2004, EPA finalized the Cl ean Air Nonroad Diesel Rule, also known as Tier 4 standards. Tier 4 standards will be phased in over the period of 2008 to 2010, and will consist of exhaust after-treatment (oxidation catal ysts) and other control technologies. Another component of the Tier 4 standards will reduce the s ulfur content of nonroad diesel fuel to enable the use of sulfur-sensitive control technology. Th e sulfur content was to be reduced to 500 ppm by June 2007 and reduced to 15 ppm by June 2010. W hen fully implemented, the Tier 4 standards are expected to reduce NO x and PM emissions by 90%.

10.4.3.1.6 Locomotive Emission Standards The first emission standards regulating locomotive engines (Tier 0-2) were adopted in 1997. The Tier 0-2 standards regulated the emission of NO x , PM, CO, and hydrocarbons (HC) for new engines or any engine built after 1973 being remanu factured. The rule became effective in 2000 and was implemented by the following schedule:

• Tier 0 standards applied to locomotive engines buil t between 1973 and 2001

• Tier 1 standards applied to engines built between 2 002 and 2004

• Tier 2 standards applied to engines built in 2005 a nd later years

On March 2, 2007, EPA published a proposed ruling f or locomotives and marine engines. The proposed rule would require stricter emission stand ards for locomotives being remanufactured starting in 2010. The rule also established Tier 3 standards for newly built locomotive and diesel77

marine engines starting in 2009. Tier 4 standards, which require exhaust after-treatments, will become effective for marine engines in 2014 and for locomotives in 2015. 10.4.3.1.7 Large Spark-Ignition and Recreational Ve hicle Rule In 2002, EPA adopted new standards for emissions of NO x , HC, and carbon monoxide (CO) from several groups of previously unregulated nonro ad engines, including spark-ignition (SI) engines powered by: gasoline, liquid propane gas an d compressed natural gas rated over 19 kilowatts (kW), snowmobiles, off-highway motorcycle s, all terrain vehicles, and diesel marine engines over 37 kW. The emission standards were ph ased in between 2004 and 2007.

10.4.3.1.8 Proposed Emission Standards for New Nonr oad Small Spark-Ignition Engines, Equipment, and Vessels In April 2007, EPA released proposed exhaust emissi on standards for marine spark-ignition engines and small land-based nonroad engines. The new standards apply to SI nonroad engines rated below 25 horsepower (19 kW) used in household and commercial applications, including lawn and garden equipment, utility vehicles, genera tors, and a variety of other construction, farm, and industrial equipment. The new standards also apply to spark-ignition engines used in marine vessels, including outboard engines, persona l watercraft, and stern-drive/inboard engines. For SI nonroad engines, the EPA proposed HC+NO x exhaust emission standards of 10 g/kW-hr for Class I engines starting in the 2012 model year and 8 g/kW-hr for Class II engines starting in the 2011 model year. The proposed standards for SI marine engines above 40 kW are 16 g/kWhr for HC+NO x and 200 g/kW-hr for CO. For marine engines below 4 0 kW, the standards increase gradually based on the engine’s maximum po wer. The new standards include requirements to control fuel tank permeation, fuel line permeation, and diffusion emissions for nonroad and marine engines. 10.4.3.1.9 Kansas City Ozone Maintenance Plan The Kansas City Maintenance Area (KCMA) is currentl y designated as an attainment area for the 8-hour ozone standard and as a maintenance area under the previous 1-hour ozone standard. Based on these designations, the KCMA is required t o have a maintenance plan under Section 110(a)(1) of the Clean Air Act (CAA) and the provis ions of the EPA’s Phase 1 Implementation Rule for the 8-hour Ozone Standard (40 CFR Section 51.905(a)(3) and (4)). KDHE prepared a maintenance plan to meet all of the requirements fo r the 8-hour ozone standard for its portion of the KCMA. The 8-hour ozone maintenance plans constitute revis ions to the State Implementation Plans and provide for continued maintenance of the 8-hour ozo ne standard for a period of 10 years, ending in 2014. The plans also provide contingency contro l measures to be implemented if a violation of the 8-hour ozone standard occurs. On June 15, 2 007, one of the monitors in the KCMA registered an 8-hour average ozone concentration in exceedance of the ozone standard, thereby violating the standard. The contingency measures w ill be implemented in two phases.

The control measure in Phase I, Measure #1, is to r educe NO x emissions from point sources in Johnson and Wyandotte counties. This will be imple mented via a new set of Kansas78

Administrative Regulations, K.A.R. 28-19-713 throug h 28-19-713d. These new regulations will affect a total of three facilities in Johnson and W yandotte counties. Two are power generating facilities, and the remaining one is a flat glass m anufacturing plant.

The two power generating facilities are Nearman Cre ek Power Station and Quindaro Power Station, both of which are owned by the Kansas City Board of Public Utilities (BPU), and located in northeastern Wyandotte County. When K.A .R. 28-19-713 through 28-19-713d are implemented, the combined NO x emissions from these two sources will be reduced b y approximately 2,948 tons/year (8.08 tons/day).

The flat glass manufacturing facility is AGC Flat G lass North America, located near Spring Hill in southern Johnson County. When K.A.R. 28-19-713 through 28-19-713d are implemented, emissions are projected to be reduced by approximat ely 292 – 487 tons/year (0.8 – 1.33 tons/day), depending on the control technology impl emented.

The control measure in Phase I, Measure #2, is to r educe idle time of heavy-duty diesel vehicles in Johnson and Wyandotte counties. This will also b e implemented via a new set of Kansas Administrative Regulations, K.A.R. 28-19-712 throug h 28-19-712d. These new regulations will apply to all owners and operators of commercial, pu blic and institutional diesel vehicles in Johnson and Wyandotte counties having a gross vehic le weight rating greater than 14,001 pounds.

In the event that technical feasibility or other co nditions change after the submittal date of this SIP that would result in any of the Phase I conting ency measures not being able to be implemented, the State of Kansas will evaluate the need to propose alternate measures that would result in equivalent or greater emissions red uctions. The EPA’s desired timeline for adoption and implementation of control measures is as expeditious as practicable, but no longer than 24 months. It is anticipated that all of thes e control measures can meet the desired timeframe.

Control options being considered for the Kansas por tion of the KCMA for Phase II include:

• Reductions in NO x emissions from point sources >100 tons of actual annual emissions from the entire facility averaged over the last three ye ars of complete, quality assured inventory data from Wyandotte and Johnson Counties. This woul d be accomplished through either NO x Emission Reduction Rules or signed agreements with the affected sources.

• Reduction in NO x emissions from point sources >1000 tons of actual annual emissions from the entire facility averaged over the last three ye ars of complete, quality assured inventory data in areas located south of the KCMA (Miami and Linn Counties). Based on the current emissions inventory, this would affect two sources. Because of this fact, these two counties would not be incorporated into the KCMA. This would be accom plished through either a regional NO x administrative regulation or signed agreements wit h the affected sources.

• Open burning restrictions in Wyandotte and Johnson Counties79

• Lower threshold for major sources of VOC, to 75 ton s/yr in Wyandotte and Johnson Counties. KDHE would evaluate remaining large VOC e mitters subject to existing VOC RACT rules to determine if further reductions could be achieved. (VOC RACT rules can be found at K.A.R. 28-19-63–74, -76, -77, -714, -717, and -719.)

• VOC control for 46 sources associated with the sour ce classification code Architectural and Industrial Maintenance Coatings, including traffic coatings in Wyandotte and Johnson Counties.

• Diesel engine chip re-flash regulation in Wyandotte and Johnson Counties

Control measures will be selected from the above li st based on emission reduction benefits, cost effectiveness, and timeframe of implementation. In order to aid in determining the most beneficial control measures, photochemical modeling may be used as a tool for evaluation. Adoption and implementation of controls shall take place no later than 18–24 months after KDHE makes a determination, based on quality-assure d ambient data, that a trigger established by this plan has been exceeded.

10.4.3.1.10 Clean Air Interstate Rule At the onset of the regional haze consultation proc ess, states relied heavily on the Clean Air Interstate Rule (CAIR), a rule that addresses the i nterstate transport of air pollution to downwind states. CAIR covered 28 eastern states plus the Di strict of Columbia, and would have reduced SO 2 emissions by an estimated 5.4 million tons and NOx emissions by an estimated 2 million tons by 2015. Affected states had the choice of ei ther meeting the state’s emission budget by requiring power plants to participate in a cap and trade system, or by means of a measure of the state’s choosing.

Although Kansas was not included in the final CAIR rulemaking, the rule was a major component in the underlying assumptions used to det ermine source apportionment because of the reductions expected in neighboring states with Clas s I areas.

In July 2008, the D.C. District Court of Appeals va cated the CAIR rule in its entirety. On September 24, 2008 EPA filed a petition for reheari ng or for a remand of the case without vacatur. On December 23, 2008, the D.C. District Co urt of Appeals remanded the case to EPA without vacatur so that EPA could remedy CAIR’s fla ws as were discussed in their July ruling. At this time, it is unclear what the ramifications of this decision may be to the regional haze program. Kansas will continue to engage with state s in the CENRAP region and will participate in future consultation processes if necessary to ad dress reasonable progress goals at Class I areas.

10.4.3.1.11 NESHAP MACT Standards

National Emission Standards for Hazardous Air Pollu tants (NESHAP) have been promulgated in recent years that will not only achieve reductions in hazardous air pollutants (HAPs), but will also reduce visibility impairing pollutants such as SO 2 , NO x , and PM. Emission standards for stationary reciprocating internal combustion engine s (RICE) and industrial, commercial, and80

institutional boilers are NESHAP’s most notable Max imum Achievable Control Technology (MACT) standards related to reductions in pollutant s contributing to regional haze. Additional MACT-related reductions are also expected from the following industries in Kansas: cellulose products manufacturing, hazardous waste combustion, and secondary aluminum production.

10.4.3.1.12 Kansas City Power & Light (KCP&L) Col laboration Agreement On January 31, 2006, the MoDNR issued a Prevention of Significant Deterioration (PSD) permit for KCP&L’s Iatan project, which included the insta llation of new pollution control technology on Iatan Unit 1, to set a permit limit on the heat input rate of Iatan Unit 1, and to construct a second pulverized coal-fired boiler (Iatan Unit 2). Upon issuance of the PSD permit, the Sierra Club filed a complaint with the Missouri Air Conser vation Commission (MACC) to appeal the issuance of the Iatan PSD permit, urging that the M DNR require more stringent emission limits at Iatan Units 1 and 2. On March 19, 2007, KCP&L s igned a collaboration agreement with the Sierra Club and the Concerned Citizens of Platte Co unty. As part of the agreement, KCP&L agreed to more stringent emission limits for Iatan Units 1 and 2 for NO x , SO 2, opacity, and sulfuric acid. The emission limits that relate to regional haze purposes are as follows:

• Iatan Unit 1

o NO x – 0.09 lbs/MMBtu, based on a 30-day rolling average

o SO 2 – 0.07 lbs/MMBtu, based on a 30-day rolling averag e

• Iatan Unit 2

o NO x – 0.07 lbs/MMBtu, based on a 30-day rolling average

o SO 2 – 0.06 lbs/MMBtu, based on a 30-day rolling averag e

In addition to tighter controls at Iatan, KCP&L agr eed to accept emissions limits for their two BART-eligible units at La Cygne, Kansas (La Cygne U nits 1 and 2) that will be lower than presumptive limits in the Regional Haze Rule for NO x, SO 2 , filterable PM 10 , and total PM 10
. These emission limits are as follows:

• NO x – 0.13 lbs/MMBtu, based on a 30-day rolling averag e, excluding periods of startup and shutdown

• SO 2 – 0.1 lbs/MMBtu, based on a 30-day rolling average , excluding periods of startup and shutdown

• PM 10 (filterable) – 0.015 lbs/MMBtu, based on either an average of 3 one-hour stack tests annually, or a Continuous Assurance Monitoring (CA M) plan before baghouses go online

• PM 10 (total) – 0.024 lbs/MMBtu, based on either an aver age of 3 one-hour stack tests annually, using EPA Method 202 or a CAM plan before baghouses go online

10.4.3.1.13 Visibility Requirements under the New S ource Review Program Section 40 CFR 52.21(o) requires owners or operator s of new major sources or modifications to provide an analysis of visibility impairment as par t of the prevention of significant deterioration process. New sources or modifications also require notification and consultation with federal81

land managers (FLMs) of Class I areas which may be affected. Kansas has adopted the federal regulation by reference at K.A.R. 28-19-350. 10.4.3.2 Measures to Mitigate the Impacts of Constr uction Activities Kansas is required by 40 CFR 51.308(d)(3)(v)(B) to consider measures to mitigate the impacts of construction activities.

When EPA first promulgated the Regional Haze Rule i n 1999, emissions related to construction activities such as windblown dust and nonroad diese l engines were a major concern. This was especially a problem in rapidly growing metropolita n areas such as Los Angeles and Phoenix. Construction activities are directly related to pop ulation growth. Kansas has not experienced rapid growth and is not forecasted to in the future . Figure 10.4 below shows the population growth for Kansas between the years of 1980 and 200 5, with projected figures out to 2020 appearing in red triangles (9).

Between the years 1990 and 2000, over half of Kansa s counties underwent a decline in population, mostly in rural counties but also in pa rts of the Kansas City metropolitan area (10). Population growth is projected to remain at a stead y pace and construction activities are not expected to cause a significant impact to visibilit y. In fact, construction permitting in Kansas and new regulations on diesel equipment will achiev e reductions in the future.

Construction projects in Kansas that disturb one ac re or more are required to obtain a general permit under the National Pollutant Discharge Elimi nation System (NPDES). The permitting program was implemented to protect the waters of th e State from sediment and other contaminants, and may also reduce the amount of par ticulate matter emissions from these activities.

Figure 10.4 Population Growth for the State Of Kans as 1980-2005 and Projected Growth 2010- 2020

Kansas Population (in thousands)

0 500 1,000 1,500 2,000 2,500 3,000 3,500

1980 1985 1990 1995 2000 2005 2010 2015 202082

The NPDES permits require permitted entities to dev elop a storm water pollution prevention plan containing best management practices to contro l erosion and runoff. Many of the best management practices employed to prevent erosion an d runoff are also effective at preventing windblown dust. For example, the use of wind fence s, sprinkling, or using vegetative cover such as geotextiles can reduce the amount of airborne pa rticles.

Emissions from diesel engines in the construction i ndustry are expected to decline with the implementation of new federal standards for both on -road and nonroad engines. Additionally, the use of ultra-low sulfur diesel fuel, which is n ow mandatory for on-road use and is scheduled for all nonroad use in 2010, will achieve reduction s in the future. 10.4.3.3 Emission Limitations and Schedules of Comp liance

Kansas is required by 40 CFR 51.308(d)(3)(v)(C) to consider emissions limitations and schedules for compliance to achieve reasonable prog ress goals.

Emissions reductions by Westar through emissions li mitations or work practices are summarized in Table 10.14. The enforceable mechanisms and sch edules of compliance for these measures are contained in the Agreement for the affected fac ilities, found in Appendix 9.7.

Table 10.14 Additional Measures Implemented under t he Long-Term Strategy to Meet Reasonable Progress Goals

Emission limit or work practice Facility/Unit NO x SO 2 Westar - Gordon Evans Unit 1 Natural gas only Westar - Hutchinson Unit 4 Natural gas only Westar - Jeffrey Unit 3 0.15 lb/MMBtu 0.15 lb/MMBtu Westar - Lawrence Unit 3 0.18 lb/MMBtu Westar – Lawrence Unit 4 0.18 lb/MMBtu 0.15 lb/MMBt u Westar – Lawrence Unit 5 0.15 lb/MMBtu 0.15 lb/MMBt u Westar - Murray Gill Unit 1 Natural gas only Westar - Murray Gill Unit 2 Natural gas only Westar - Murray Gill Unit 3 Natural gas only Westar - Murray Gill Unit 4 Natural gas only Westar - Neosho Unit 7 Natural gas only Westar - Tecumseh Unit 7/9 0.18 lb/MMBtu Westar - Tecumseh Unit 8/10 0.18 lb/MMBtu83

10.4.3.4 Source Retirement and Replacement Schedul es Kansas is required by 40 CFR 51.308(d)(3)(v)(D) to consider source retirement and replacement schedules in developing reasonable progress goals. The Integrated Planning Model (IPM) runs projected the closure of several gas-fired boilers in Kansas. However, communication with owners of these sources revealed that these project ions are incorrect. Kansas is aware of two coal-fired EGU sources that could potentially be re tired within the next 10 years. The first, Kansas City BPU - Kaw, has two units that have been on cold stand-by since 2001 (Unit 1) and 2003 (Unit 3). Unit 2 was retired in 1992. This s ource would be subject to existing SIP requirements pertaining to PSD permitting should BP U decide to restart. In addition, as part of its long-term planning process, BPU is evaluating o ptions for adding new capacity and may decide to retire another existing facility in the f uture. The second source, Empire District Electric - Riverton Units 7 and 8, have startup dat es of 1950 and 1954, respectively, and will likely be retired before 2018. Beyond these two so urces, Kansas is not aware of additional sources scheduled for retirement or replacement. A ny additional sources that retire or are replaced will be managed in conformance with the ex isting Kansas SIP requirements pertaining to PSD and NSR permitting. 10.4.3.5 Agricultural and Forestry Smoke Managemen t Kansas is required by 40 CFR 51.308(d)(3)(v)(E) to consider smoke management techniques for the purposes of agricultural and forestry managemen t in developing reasonable progress goals. Kansas will work to implement smoke management tech niques to address rangeland burning. See Appendix 10.4 for Kansas Prescribed Fire Emissi ons. 10.4.3.6 Enforceability of Emission Limitations and Control Measures

Kansas is required by 40 CFR 51.308(d)(3)(v)(F) to ensure that emission limitations and control measures used to meet reasonable progress goals are enforceable.

Kansas has ensured that all emission limitations an d control measures are enforceable by embodying these in the Agreements found in Appendix 9.7. The agreements contain the applicable emission limits and compliance schedules , which will be federally enforceable upon EPA’s approval of this SIP. The emissions limits a nd compliance verification requirements will be incorporated into each facility’s Title V operat ing permit when they are reopened or approved.

10.4.3.7 Anticipated Net Effect on Visibility Resul ting from Projected Changes to Emissions

Kansas is required by 40 CFR 51.308(d)(3)(v)(G) to address the net effect on visibility resulting from changes projected in point, area, and mobile s ource emissions by 2018.

The 2002 to 2018 projected visibility improvement a t the nine Class I areas selected for analysis and discussed in Chapter 8 will, for the State of K ansas, result chiefly from the implementation of NO x and SO 2 controls on the five electric generating units (EG Us) subject to BART. These84

projected visibility improvements are shown in Tabl e 10.15, based on the ENVIRON PSAT tool, and shown in terms of light extinction.

The impact on the Wichita Mountains from Kansas sou rces is expected to be reduced by 1.03715 Mm -1 , which represents a 23% change in Kansas’ impact o n the Wichita Mountains between 2002 and 2018. Further improvement will come from the “beyond-BART ” controls at sources referred to in Chapter 10.

Table 10.15 Net 2002 to 2018 Improvement in Visibil ity at Selected Class I Areas Due to BART Controls in Kansas

Class I area Net 2002-2018 light extinction difference

(improvement) from Kansas sources (Mm -1 ) Caney Creek (Arkansas) 0.63493 Upper Buffalo (Arkansas) 0.44533 Great Sand Dunes (Colorado) 0.03322 Rocky Mountain (Colorado) 0.06051 Hercules-Glades (Missouri) 0.56911 Mingo (Missouri) 0.58719 Wichita Mountains (Oklahoma) 1.03715 Badlands (South Dakota) 0.12856 Wind Cave (South Dakota) 0.16741

List of Chapter 10 Appendices 10.1 PSAT Tool-Generated Tables 10.2 2018 Visibility Projections for CENRAP Class I Areas (TSD Appendix D) 10.3 Calculations for Emissions Reductions for Kans as Reasonable Progress Goals 10.4 Kansas Prescribed Fire Emissions85

11. Consultation

Kansas does not contain any Class I Areas. Kansas participated in state consultation processes with Arkansas, Missouri, Texas, and Oklahoma. A su mmary of these consultation processes is given below. In each case, the states established a threshold to determine whether neighboring states would be expected to contribute emissions re ductions for meeting their Class I areas’ reasonable progress goals. Kansas fell below the e stablished thresholds for all but one Class I area. Kansas is anticipated to contribute to visib ility impairment at the Wichita Mountains Wilderness Area in Oklahoma.

11.1 Consultation

Kansas is required by 40 CFR 51.308(d)(3)(i) to con sult with other states/tribes to develop coordinated emission strategies. This requirement applies both where emissions from the state are reasonably anticipated to contribute to visibil ity impairment in Class I areas outside the state and when emissions from other states/tribes are rea sonably anticipated to contribute to visibility impairment in Class I areas within the state/tribe.

Kansas consulted with other states and tribes by pa rticipation in CENRAP in an effort to develop coordinated strategies to meet reasonable progress goals. In addition, Kansas participated in discussions focused on Class I areas in Arkansas, M issouri, Texas, and Oklahoma. Following is a summary of the calls, and the conclusions reached through the consultation process.

11.1.1 Arkansas and Missouri

The States of Arkansas and Missouri elected to comb ine their consultation processes for the central Class I areas contained within their bounda ries:

• Caney Creek Wilderness Area (Arkansas)

• Upper Buffalo Wilderness Area (Arkansas)

• Hercules Glades Wilderness Area (Missouri)

• Mingo Wilderness Area (Missouri)

Arkansas and Missouri developed a consultation plan in which they outlined the consultation process and timeline, described the methodology for determining the significantly contributing states, and delineated the roles and responsibiliti es of the various agencies involved in the consultation process. Three conference calls were scheduled to facilitate consultation, and were held on April 3, May 11, and June 7, 2007.

Arkansas and Missouri’s consultation plan included a methodology in which three criteria were used to determine whether a neighboring state signi ficantly contributes to visibility impairment at on or more of the Class I areas listed above. I f any state was indicated in two of the three criteria, they were determined to be significant co ntributors. A fourth index, quantity of emissions over distance (Q/d), was also used for in formational purposes. The states of Arkansas86

and Missouri did not request emission reduction com mitments from the State of Kansas beyond its BART reductions.

11.1.2 Texas The State of Texas contains the following Class I a reas:

• Big Bend National Park

• Guadalupe Mountains National Park

Texas initiated their consultation process in July 2007, with three conference calls that took place on July 11, 18, and 31. Texas developed and distri buted a series of technical papers before the calls, outlining their positions on the estimation of natural conditions, uniform rate of progress, IPM, and reasonable progress. Of particular intere st to Kansas, Texas Commission on Environmental Quality (TCEQ) staff have recommended that course mass and fine soil contributions to haze be considered natural (i.e., non-anthropogenic), and therefore held constant when projecting to 2018. In addition, TCEQ staff i ntends to present two glide slopes for each Class I area in their Regional Haze SIP. The first would be a standard glide slope with a 2064 target of natural visibility conditions at the Clas s I areas; the second glide slope would have a target of zero U.S. anthropogenic contribution by 2 064.

TCEQ chose a threshold of 3% total contribution to light extinction at their two Class I areas for determining which states would participate in consu ltation. Although Kansas contributed slightly more than 3% at Guadalupe Mountains (3.21% ), over 50% of that impact can be attributed to soil and coarse mass, which are being discounted by Texas as non-anthropogenic sources. Texas informed Kansas that it will not ex pect Kansas to contribute emissions reductions for meeting their Class I areas’ reasona ble progress goals for the first planning period beyond the BART reductions for Kansas included in t he PSAT modeling.

11.1.3 Oklahoma

The State of Oklahoma contains the Wichita Mountain s Wilderness Area. Oklahoma initiated the process of consultation for Wichita Mountains i n August 2007, with a series of conference calls. Oklahoma distributed their consultation pla n, which included an overview of the consultation objectives, technical information used to identify contributing states, and outlined the roles and responsibilities of each of the parti cipants in the consultation process. Kansas participated in calls held by Oklahoma on August 14 , August 30, and September 13, 2007. Instead of using percent total extinction, Oklahoma selected a threshold of absolute extinction from all sources and particulate species greater th an 1.0 Mm -1 to determine which states should participate in their consultation process. Kansas’ overall 2018 absolute extinction contribut ion to Oklahoma’s Wichita Mountains Wilderness Area is pro jected to be 3.53 Mm -1 (and percent extinction to be 4.90%), which Kansas recognizes as a potentially significant impact to visibility at that Class I area.87

In applying the criteria for meeting reasonable pro gress goals at Wichita Mountains, Oklahoma identified three Kansas facilities that they conclu ded had the potential to impact visibility in the Wichita Mountains. The Kansas sources identified a re listed in the table below.

Table 11.1 Kansas Sources Identified by Oklahoma as Potentially Impacting Visibility at Wichita Mountains

Source ID Facility / Emission Units 1 0450014 Westar Energy - Lawrence Units 3, 4, and 5 0550023 Sunflower Electric - Holcomb Unit 1 (and pr oposed Units 2 and 3) 1490001 Westar Energy – Jeffrey Unit 3 (Units 1 and 2 are already subject to BART)

1 Oklahoma named only facilities; unit information i s supplied editorially

These three sources were identified for potential N O x impacts only, since one of the selection criteria used by Oklahoma was the “area of influenc e” (AOI) tool, a source contribution mapping tool developed by CENRAP contractor Alpine Geophysi cs prior to PSAT, and based largely on back trajectory analysis. The Wichita Mountains AO I for nitrates runs along or through 72 counties, more or less through the center of Kansas . Only 4 counties in extreme southeast Kansas lie along or inside the AOI boundary for sul fates. Thus, nearly all the candidate Kansas sources considered by Oklahoma at the start of thei r analysis were large NO x emitters. All three of these sources have also been addressed in Kansas ’ own analysis of reasonable progress, described in Chapter 10.

As part of the first consultation call, Oklahoma re quested any additional information Kansas could provide on potential visibility impacts, cont rol applicability—both technical feasibility and costs for controls, future life of source, and any known or projected growth. Kansas provided this information on August 24, 2007. Information p rovided included CALPUFF modeling Kansas performed on the sources for prior regional haze purposes, along with CALPUFF and CAMx modeling that was performed as part of a visib ility analysis for a proposed expansion at Sunflower Electric - Holcomb. A summary of that in formation follows. Sunflower Electric Power had planned to build two 7 00 MW EGUs alongside their current 349 MW EGU (Unit 1), located in Holcomb, Kansas. Curre nt plans now call for one 895 MW coalfired power plant to be constructed in Holcomb. Em issions from the existing boiler are controlled by low NO x burners, a spray dry absorber scrubber and a low r atio, reverse-air baghouse. The existing boiler is permitted to burn Powder River Basin (PRB) coal. Sunflower proposes to install Holcomb Unit 2, a supercritical 895 MW pulverized coal-fired boiler. The existing coal, lime, and ash handling equipment wit h the addition of equipment to double throughput capability will be utilized. The Holcom b Unit 2 boiler will fire PRB subbituminous coal and low-sulfur bituminous coal as primary fuel and natural gas as a backup fuel. Kansas performed CAMx PSAT modeling on this expansi on as originally proposed (three 700MW EGUs), relying on the 2002 Base F CENRAP emis sions datasets, along with the 2002 MM5 dataset to perform the CAMx modeling (see Appen dix 11.1). Version 4.42 of CAMx was used with the PSAT/OSAT “point source override” fea ture. The worst-case normal operating88

rate, excluding startups, shutdowns, malfunctions, and maintenance activities, was modeled. It was determined that the rates would be 0.09 lb/MMBt u for SO 2 and 0.05 lb/MMBtu for NO x for each unit. Because these two pollutants dominate t he visibility impacts, no other pollutants were modeled. CAMx requires emissions to be speciated a nd expressed in moles per hour; therefore, the emissions rates used in CAMx were NO - 5,769 mo les/hr, NO 2 - 641 moles/hr, and SO 2 - 12,427 moles/hr (note this represents all three ini tially proposed units operating - Sunflower is now only proposing one 895 MW unit). Results of th e modeling indicated a maximum visibility impact at the Wichita Mountains Class I area of 0.4 7 delta deciview. In addition to the CAMx modeling review, Sunflower Electric was required to submit a FLAG visibility analysis to the State as part of the per mit application. This analysis included both a CALPUFF Method 2 and Method 6 evaluation of the vis ibility impacts. The method 2 results indicated a maximum 30.6 % extinction in the Wichit a Mountains. The method 6 results indicated a 98% impact of 0.331 delta deciview. Th e maximum Method 6 impact was 1.107 delta deciview. The source concluded, and Kansas c oncurred, that the proposed Holcomb expansion is not expected to adversely affect the v isibility at the Wichita Mountains. A full description of modeling and results can be found in Appendix 11.2. In summary, Kansas has not yet been asked by any ot her state to reduce emissions beyond those required under BART during the consultation process es. However, going into the consultation process, modeling provided by CENRAP indicated that Class I areas in both Texas and Oklahoma were being impacted by Kansas emissions. These states, and perhaps others impacted by the vacatur of the Clean Air Interstate Rule (CA IR), may be required to request additional emission reductions from Kansas in the future. Cer tainly, additional emission reductions from Kansas sources will be the subject of consultation discussions in the future.

List of Chapter 11 Appendices

11.1 Sunflower Visibility Analysis Performed by KDH E 11.2 Holcomb Class I Visibility Modeling Report89

12. Plan Revisions and Progress Reports

Kansas is required by 40 CFR 51.308(f) to revise it s regional haze implementation plan and submit a plan revision to EPA by July 31, 2018, and every ten years thereafter. In accordance with the requirements listed in 40 CFR 51.308(f) of the federal rule for regional haze, Kansas commits to revising and submitting this regional ha ze implementation plan by July 31, 2018 and every ten years thereafter.

In addition, 40 CFR 51.308(g) requires periodic rep orts evaluating progress towards the reasonable progress goals established for each mand atory Class I area. In accordance with the requirements listed in 40 CFR 51.308(g) of the fede ral rule for regional haze, Kansas commits to submitting a report on reasonable progress to EPA e very five years following the initial submittal of the SIP. The report will be in the form of a SI P revision. The reasonable progress report will evaluate the progress made towards the reasonable p rogress goal for each mandatory Class I area located outside Kansas, which may be affected by em issions from within Kansas

. All requirements listed in 40 CFR 51.308(g) shall be ad dressed in the SIP revision for reasonable progress. The first five-year progress report will be completed by October 26, 2014.90

13. Determination of the Adequacy of the Existing Plan

Depending on the findings of the five-year progress report, Kansas commits to taking one of the actions listed in 40 CFR 51.308(h). The findings o f the five-year progress report will determine which action is appropriate and necessary.

List of Possible Actions – 40 CFR 51.308(h)

1) Kansas would determine that the existing SIP requir ed no further substantive revision in order to achieve established goals. Kansas would p rovide to the Administrator a declaration that further revision of the SIP will n ot be needed at that time. 2) Kansas would determine that the existing SIP may be inadequate to ensure reasonable progress due to emissions from other states which p articipated in the regional planning process. Kansas would provide notification to the A dministrator and the states that participated in regional planning. Kansas would co llaborate with states through the regional planning process to address the SIP’s defi ciencies. 3) Kansas would determine that the existing SIP may be inadequate to ensure reasonable progress due to emissions from another country. Ka nsas would provide notification, along with available information, to the Administra tor. 4) Kansas would determine that the existing SIP is ina dequate to ensure reasonable progress due to emissions within Kansas. Kansas would revis e its SIP to address the plan’s deficiencies within one year.91

14. Reference Information

14.1 List of References

1. Protecting Visibility in National Parks and Wildern ess Areas. National Research Council. Washington, DC: 1993. 2. Guidance for Estimating Natural Visibility Conditio ns under the Regional Haze Rule. U.S. Environmental Protection Agency. Research Tr iangle Park: 2003. 3. Trijonis, J., et. al. Visibility: Existing and Historical Conditions- Cau ses and Effects.

State of the Science/Technology Report 24, Volume I II of the National Acid Precipitation Assessment Program. Washington DC: 1990. 4. Analysis of the Causes of Haze for the Central States Phase II. Sonoma Technology, Inc. Petaluma: 2005. 5. Anthes, R.A. and T.T. Warner. 1978. Development of Hydrodynamic Models Suitable for Air Pollution and Other Mesometeorological Stu dies. Monthly Weather Review, 106, 1045-1078. 6. Guidance for Setting Reasonable Progress Goals unde r the Regional Haze Rule. US Environmental Protection Agency. Research Triangl e Park: 2007. 7. Petroleum Marketing Monthly February 2007. Energy I nformation Administration. Accessed online: http://www.eia.doe.gov/pub/oil_gas/petroleum/data_p ublications/petroleu m_marketing_monthly/historical/2007/2007_02/pdf/pm mall.pdf 8. Consumer Price Index: All Urban Consumers, US City Average. Bureau of Labor and Statistics. Accessed online: http://www.bls.gov/cpi/ 9. U.S. Census Bureau. 2007 Statistical Abstract. 10. U.S. Census Bureau. County and City Data Book, 200 0.

14.2 List of Acronyms and Abbreviations

A/F Air/fuel (adjustment) AERR Air Emissions Reporting Rule AIRS Aerometric Information Retrieval Systems AOI Area of influence AQS Air Quality System BART Best available retrofit technology Bcf Billion cubic feet BPU (Kansas City) Board of Public Utilities CAA Clean Air Act CAIR Clean Air Interstate Rule CAMx Comprehensive Air Quality Model with extensio ns CASTNet Clean Air Status and Trends Network CEMS Continuous emissions monitor CENRAP Central Regional Air Planning Association92

CM Coarse mass CMAQ Community Multiscale Air Quality CO Carbon monoxide dv Deciview EC Elemental carbon EGAS Economic Growth Analysis System EGU Electric generating units EPA United States Environmental Protection Agency FCCU Fluid-bed catalytic cracking unit FGD Flue gas desulfurization FGR Flue gas recirculation FLM Federal land managers FOFEM First Order Fire Effects Model GCVTC Grand Canyon Visibility Transport Commission GVWR Gross vehicle weight rating IMPROVE Interagency Monitoring of Protected Visual Environments IPM Integrated Planning Model IR Ignition retard LNB Low NO x burner LNBO Low NO x burner with overfire air LNC1 Low NO x coal-and-air nozzles with cross-coupled overfire a ir LNC3 Low NO x coal/air nozzles with close-coupled and separated overfire air LTS Long term strategy MACT Maximum achievable control technology Mgal/yr Million gallons per year Mm -1 Inverse megameters MM5 Mesoscale Model (5 th generation) MRPO Midwest Regional Planning Organization NEI National Emissions Inventory NESHAP National emission standards for hazardous ai r pollutants NGR Natural gas reburn NH 3 Ammonia NO 2 Nitrogen dioxide NO 3 Nitrate NO x Nitrous oxides OBD On-board diagnostics OMC Organic matter carbon ORVR On-board refueling vapor recovery OT Oxygen trim PM 2.5 Particulate matter (fine) PM 10 Particulate matter (coarse) POA Primary organic aerosol POG Policy Oversight Group93

ppb Parts per billion ppm parts per million PSAT PM Source Apportionment Technology PSD Prevention of significant deterioration QA/QC Quality assurance/quality control RACT Reasonably achievable control technology RADM Regional Acid Deposition Model REMSAD Regional Modeling System for Aerosols and De position RH Relative humidity RHR Regional Haze Rule RICE Reciprocating internal combustion engines RPO Regional planning organization RRF Relative response factor SCC Source classification code SCR Selective catalytic reduction SEARCH South Eastern Aerosol Research and Character ization SIC Standard industrial classification SIP State Implementation Plan SMOKE Sparse matrix operator kernel emissions SNCR Selective non-catalytic reduction SO 2 Sulfur dioxide SO 4 Sulfate SSM Startup, shutdowns and malfunctions STI Sonoma Technology, Inc. STN Speciated Trends Network TSD Technical Support Document ULSD Ultra-low sulfur diesel URP Uniform rate of progress VIEWS Visibility Information Exchange Web System VISTAS Visibility Improvement State and Tribal Asso ciation of the Southeast VMT Vehicle miles traveled VOC Volatile organic compound WI Water injection WRAP Western Regional Air Partnership94 

# Appendices

The appendices for the Regional Haze SIP are locate d on the enclosed compact disc.