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Technical Support Document

US EPA Proposed Approval of the State of Kansas’

Regional Haze SIP

Prepared By: Tracey Casburn, Environmental Scientist, US EPA, 

Region 7

August 12, 2011
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Table of Contents

Consultation Page 6

Emissions Inventory Page 7

Planned Burning Emissions Inventory Page 8

Ammonia Emissions Inventory Page 9

Mobile Source Emissions Inventory Page 9

Fugitive Dust Emissions Inventory Page 10

Point Source Emissions Inventory Page 10

Nonpoint Source Emissions Inventory Page 12

Affected Class I Areas and Source Apportionment Page 15

Best Available Retrofit Technology (BART) Page 20

BART Eligible Sources Page 23

BART Subject Sources Page 26

BART Determination for Westar JEC Units 1&2 Page 29

BART Determination for Westar GEC Unit 2 Page 34

BART Alternative for GEC Unit 2 Page 38

BART Determination for KCP&L Units 1&2 Page 42

Reasonable Progress/Long Term Strategy Page 46
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List of Figures

Figure 1-Geographical Area of Regional Planning Organizations Page 6

Figure 2- 2002 Emissions of Pollutants Contributing to Regional Haze from Kansas Page 13

Nonpoint Sources

Figure 3- 2002 Percent Total Light Extinction at Eleven Class I Areas from Kansas Page 16

Sources, by Species, for All Source Categories during the Worst 20% Days

Figure 4- 2002 Percent Total Light Extinction at Eleven Class I Areas from Kansas Page 17

Air Emission Sources, by Source Category, for All Species during the Worst 

20% Visibility Days

Figure 5- 2018 Percent Total Light Extinction at Eleven Class I Areas from Kansas Page 18

Sources, by Species, for All Source Categories during the Worst 20% Days

Figure 6- 2018 Percent Total Light Extinction at Eleven Class I Areas from Kansas Page 19

Air Emission Sources, by Source Category, for All Species during the Worst

20% Visibility Days

Figure 7 – 2002 VOC emissions by CENRAP State and Source Sector Page 22

Figure 8- 2002 Ammonia emissions by CENRAP state and Source Sector Page 23

Figure 9- Map of BART-eligible Sources in Kansas Page 26

Figure 10- Map of Class I Areas Analyzed Page 27

List of Tables

Table 1- Baseline 2002 Kansas Emissions Summary, by Source Category and Pollutant Page 7

Table 2- 2018 Kansas Projected Emissions Summary, by Source Category and Pollutant Page 8

Table 3- Total Acres Burned in Kansas with Estimated Annual Emissions Page 9

Table 4- 2002 Locomotive Emissions in Kansas (tons/yr) Page 10

Table 5- 2002 Nonroad Mobile Source Emissions in Kansas by Equipment Type (tons/yr) Page 10

Table 6- Total 2018 Reductions in NOx and SO2 from Kansas Emission Sources Subject to Page 11

Table 7- Summary of Wichita Mountains Visibility Impact Results, in Percent Light Extinction Page 11

Increase, and in Deciview Increase

Table 8-2009 Emissions Summary of Ethanol and EGUs Page 12

Table 9- 2002 Top PM10 Emissions from Kansas Nonpoint (Area) Sources Page 13

Table 10-2002 Top VOC Emissions from Kansas Nonpoint (Area) Sources Page 14

Table 11- 2002 Top NOx Emissions from Kansas Nonpoint (Area) Sources Page 14
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Table 12- 2002 Top SO2 Emissions from Kansas Nonpoint (Area) Sources Page 15

Table 13- 2018 Percent Total Light Extinction > 0.5% Due to Kansas Sources for Page 20

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

Table 14- Facilities with BART-eligible Units in the State of Kansas Page 25

Table 15- List of 19 BART-eligible Source and Their Distances from each of the Page 27

9 Class I Areas Analyzed. 

Table 16- Kansas BART-Eligible Emission Units with at Least One > 0.5 dv Page 28

Visibility Impact Day on Selected Class I Areas during 2001–2003

Table 17- BART Presumptive Limits and Operational Standards for NOx and SO2 Page 29

at Subject-to-BART Emission Units in Kansas

Table 18- Visibility Impairment Attributable to JEC Units 1 and 2 and GEC Unit 2 (2001-2003 Page 30

Table 19-Pollutant Specific Contributions to Existing Visibility Impairment for Page 30

JEC Unit 1 and 2 (2001-2003)

Table 20- Visibility Improvement from the Implementation of Presumptive SO2 BART Page 31

Table 21- Summaries of Cost effectiveness of NOx controls at JEC units 1 and 2 Page 32

Table 22-Summary of Modeled Impacts from NOx Control for JEC Unit 1 (2001-2003) Page 33

Table 23- Summary of Modeled Impacts from NOx Control for JEC Unit 2 (2001-2003) Page 33

Table 24-Pollutant Specific Contributions to Existing Visibility Impairment Page 34

for GEC Unit 2 (2001-2003)

Table 25- Summary of Emission Rates Comparing Existing Control to a Fuel Page 35

Switch at GEC Unit 2

Table 26- Summary of Cost Effectiveness for Switching from No. 6 Oil to one Page 35

percent sulfur fuel

Table 27- Summary of Modeled Impacts from SO2 control at GEC Unit 2 (2001-2003) Page 36

Table 28- Summary of Cost Effectiveness for GEC Unit 2 NOx Control (SCR) Page 37

Table 29- Summary of Modeled Visibility Impacts from SCR control Page 38

Table 30- Comparison of Presumptive BART (1% Sulfur Fuel and LNB) to the Page 40

BART Alternative

Table 31- Comparison of Presumptive BART (1% Sulfur Fuel and LNB) to the Page 41

BART Alternative at Five Class I area

Table 32-Visibility Impairment Attributable to KCP&L Units 1 and 2 (2001-2003) Page 42
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Table 33- Pollutant Specific Contributions to Existing Visibility Impairment Page 42

for KCP& L Units 1 and 2

Table 34- Visibility Improvement from the Implementation of Presumptive BART Page 43

Table 35-Summary of Cost Effectiveness of NOx Control at KCP&L Units 2 Page 44

Table 36- Summary of NOx Control at KCP&L Unit 2 Page 44

Table 37- Kansas Emission Units Not Subject to BART Emitting at Least Page 47

500 Tons/Yr of NOx or SO2 in 2002

Table 38- Sources with Cost per Ton Reduced Greater than $10,000/ton Page 47

Table 39- Most Effective Control Technologies with Acceptable Control Costs Page 48

for Kansas 500-Ton NOx and SO2 Emission Units

Table 40- Overall Visibility Improvements Resulting from Application of the Most Page 50

Effective Controls at Selected Kansas 500-Ton NOx and SO2 Emission Units.

Table 41- Selected Kansas 500-ton NOx and SO2 Emission Units Showing Significant Page 51

Visibility Improvement Resulting from Application of Most Effective Controls

Table 42- Summary of Each Unit’s Cost per ton per Unit of dv Improvement Page 52

Table 43- Summary of Reasonable Progress Non-Cost Statutory Factors Page 53

For Selected Kansas Point Sources

Table 44- Ranked List of Sources under the Reasonable Progress Analysis Page 54

Table 45- Control or Work Practice Strategies for Westar Units to Meet Kansas Long Page 55

Term Strategy Requirements

Table 46- Estimated NOx and SO2 Emission Reductions for Implementation of Controls Page 56

or Work Practices required by Kansas’ Long Term Strategy
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Consultation

Because the pollutants that lead to regional haze can originate from sources located 

across broad geographic areas, EPA encouraged the States and Tribes to address visibility

impairment from a regional perspective. Five regional planning organizations (RPOs) were 

developed to address regional haze and related issues. These organizations first evaluated 

technical information to better understand how their States and Tribes impact visibility (regional 

haze) at national park and wilderness areas (Class I areas) across the country, and then pursued 

the development of regional strategies to reduce emissions of particulate matter and other 

pollutants leading to regional haze issues. The State of Kansas participated in the planning 

efforts of the Central Regional Air Planning Association (CENRAP) which is affiliated with the 

Central States Air Resource Agencies (CENSARA). This RPO includes nine states - Nebraska, 

Kansas, Oklahoma, Texas, Minnesota, Iowa, Missouri, Arkansas, and Louisiana. 

The RPOs, such as CENRAP, provided air quality modeling to the States to help them in 

determining whether sources located within the State can be reasonably expected to cause or 

contribute to visibility impairment in a Class I area. The modeling relied on baseline year (2002) 

and future planning year (2018) emissions inventories that were prepared with the participation 

from each of the CENRAP states. States relied on these inventories to develop control strategies 

to meet the visibility improvement goals of the Regional Haze Rule (Rule) and to develop their 

State Implementation Plans (SIPs). This technical support document also relies heavily on the 

data provided by the CENRAP.

Figure 1-Geographical Area of Regional Planning Organizations
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Emissions Inventory 

The inventory (2002 and 2018) provided in the State’s Regional Haze SIP includes: 

Volatile Organic Compounds (VOCs), nitrogen oxides (NOx), sulfur dioxide (SO2), fine 

particulate matter (PM2.5), coarse particulate matter (PM10) and ammonia (NH3). The 2002 

emissions inventory and its improvements were developed by CENRAP and its contractors as 

part of the development of a baseline inventory for the 2002 modeling inventory. The 

improvements were prepared by Sonoma Technology, Inc. (STI), a contractor retained to 

develop and improve three inventory categories of the baseline 2002 inventory: planned burning 

emissions inventory, ammonia inventory, mobile source and fugitive dust emissions inventory.

The complete 2002 baseline emissions inventory can be found in Appendix 7.1 of the SIP.

Table 1- Baseline 2002 Kansas Emissions Summary, by Source Category and Pollutant

To estimate the 2018, future year emissions, the 2002 emissions were grown using the 

Economic Growth Analysis System (EGAS), MOBILE 6.2 vehicle emissions software, and the 

Integrated Planning Model (IPM) version 2.93 for EGUs. The complete 2018 emissions 

inventory can be found in Appendix 7.2 of the SIP. 
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Table 2- 2018 Kansas Projected Emissions Summary, by Source Category and Pollutant

Planned Burning Emissions Inventory

Agricultural and prescribed burning activities, referred to as planned burning, likely 

contribute to episodes of impaired visibility in the CENRAP region. STI developed planned 

burning emissions inventories for the CENRAP region, including Kansas. In Kansas, planned 

burning is an important component of the nonpoint source category, with a significant amount of 

emissions. STI used a “bottom-up” approach in preparing these emissions estimates. This 

preparation included using the First Order Fire Effects Model (FOFEM), incorporating emission 

factors and fuel loadings gathered from published literature, geographic information systems 

(GIS) databases of land cover and vegetation, and activity data gathered through telephone 

surveys.

In Kansas, a significant amount of the burning occurs on rangeland and cropland. To best 

characterize the amounts burned, STI performed an agricultural burning survey of the county 

agricultural extension service offices within the state. This survey included rangeland burning 

questions designed to determine the fraction of rangeland acreage typically burned each year and 

the timing of such burn events. Of the 105 total counties surveyed, 59 responded, which 

represents a 56% response rate. The results of these surveys can be found in Appendix 7.3 of the 

SIP.

Assuming the responding counties comprise a representative sample, these two 

categories, wheat stubble burning and rangeland burning, together represent approximately 93% 

of the acres burned in Kansas. As can be seen in Table 3, these two categories also represent the 

majority of the burning inventory emissions. The baseline 2002 source category “Area Source 

Fire” was grown to reflect the information gathered by STI and is represented in Appendix 7.1 of 

the SIP.

Although area source fire emissions were shown to be significant in amount, 

photochemical modeling, discussed in greater detail below, did not show these emissions to have 

a significant impact on visibility at Class I areas.
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Table 3- Total Acres Burned in Kansas with Estimated Annual Emissions

Ammonia Emissions Inventory

It is widely recognized that the formation of secondary particulate matter, which is 

generated from chemical transformations in the atmosphere of gaseous precursor species such as 

ammonia, NOx, sulfur oxides (SOx), and VOCs, contributes significantly to regional haze issues 

in the CENRAP region. In Kansas, agriculture-related ammonia emissions, coming from sources 

such as confined animal feeding operations (CAFOs) and crop fertilization, are significant in 

amount. Because ammonia can have an impact on the formation of secondary particulate species, 

CENRAP and Kansas spent considerable resources on developing an accurate ammonia 

inventory. STI developed a comprehensive inventory for CENRAP. 

In Kansas, over 50% of the ammonia emissions come from livestock emissions, including 

CAFOs and free range grazing. In 2002, it is estimated that 91,000 tons per year (tpy or 

tons/year) of ammonia came from these two source categories. In addition, it is estimated that 

65,000 tpy of ammonia emissions came from fertilizer emissions. The remainder of the ammonia 

emissions in Kansas is from biogenic and point sources categories. One of the important 

considerations in the development of the ammonia inventory was the temporal allocation of the 

ammonia emissions, both seasonally and diurnally. STI did considerable work in developing 

temporal profiles for the ammonia inventory in Kansas. These temporal profiles were then 

utilized during photochemical modeling to assess the impact of ammonia emissions on visibility

impairment. Although ammonia emissions were considered by the State to be significant to the 

formation of visibility impairing pollutants such as particulate matter, photochemical modeling, 

discussed in greater detail below, did not show that these ammonia formed pollutant emissions 

have a significant impact on visibility at Class I areas.

Mobile Source Emissions Inventory

In Kansas, the emissions inventory for the on-road mobile and nonroad mobile source 

categories are fairly significant in amount for certain pollutants. STI prepared detailed 

inventories for these source categories, including refined spatial and temporal data. Table 4 has a 

summary of the locomotive emissions in Kansas, while Table 5 shows emissions from other 

nonroad source categories. There are minimal emissions from recreational boating in Kansas, 
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thus it is not summarized here. Photochemical modeling, discussed in greater detail below, did 

not show these emissions to have a significant impact on visibility at Class I areas.

Table 4- 2002 Locomotive Emissions in Kansas (tons/yr)

Table 5- 2002 Nonroad Mobile Source Emissions in Kansas by Equipment Type (tons/yr)

Fugitive Dust Emissions Inventory

The final emissions category that STI analyzed dealt with fugitive PM2.5 emissions from 

agricultural sources. These emissions come from sources such as tilling operations. In Kansas, it 

is estimated that there are over 50,000 tpy of PM2.5 emissions from agricultural tilling 

operations. As was the case for ammonia emissions, the temporal distribution of these emissions 

is important as they are seasonal in nature. Photochemical modeling, discussed in greater detail 

below, did not show fugitive dust emissions from agriculture to have a significant impact on 

visibility at Class I areas.

Point Source Inventory

The majority of visibility-impairing point source emissions in Kansas currently come 

from the electric utility sector. This sector represented 93% of the reported SO2 emissions and 

57% of the NOx emissions for the 2002 inventory year. The other large NOx emissions category

in Kansas is the natural gas compression industry, which represented 28% of total NOx emissions 

for the 2002 inventory year. For the point source sector, reductions in NOx and SO2 by 2018 are 

projected primarily at the five EGU units the State found to be subject to BART controls. Table 

6 details the reductions predicted from these emission units.
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Subject-to-BART unit

2002 

NOx

1

2002

SO2

1

2018 

NOx

2

2018 

SO2

2

NOx

reduction

SO2

reduction

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

Table 6- Total 2018 Reductions in NOx and SO2 from Kansas Emission Sources Subject to

1 Data from EPA Clean Air Markets 2 Data from IPM 3.0

At the time this document was being prepared, an 895 MW coal-fired EGU was in the 

permitting process in Kansas. This EGU, located in Holcomb in the southwest portion of the 

State, was analyzed for visibility impacts on the WIMO. The State has asserted that CAMx 

PSAT modeling showed that visibility impairment in the WIMO attributed to this new source 

would be below 0.5 delta deciview (Δdv). The permit for the 895 MW EGU was approved by

the Secretary of the Kansas Department of Health and Environment. The visibility modeling 

results for the power plant at Holcomb is provided in Appendix 11.2 of the SIP.

Table 7- Summary of Wichita Mountains Visibility Impact Results, in Percent Light Extinction Increase, and in 

Deciview Increase

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 
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southwest. In 2002, 19 EGUs reported NOx emissions over 100 tons, whereas in the same period 

95 natural gas compressor stations reported NOx emissions over 100 tons. From 1995 to 2005, 

production from the Hugoton gas field, the State’s largest natural gas production area, has 

decreased from approximately 460,000 billion cubic feet (Bcf) to 200,000 Bcf. Over the same 

period, actual NOx emissions reported from the compressor stations have steadily decreased from 

75,000 tons/yr to 50,000 tons/yr. Kansas expects emissions from this sector to continue to 

decline as production declines and equipment is replaced with new, more efficient designs. 

Additional information on this sector can be found in Appendix 7.4 of the SIP.

In 2002, there were four ethanol plants in operation in Kansas, with a total production 

capacity of 164 million gallons per year (Mgal/yr). That number grew to 14 facilities in 2007 

with a total capacity of 814 Mgal/yr. Currently, there are 12 active ethanol facilities, 3 facilities 

under construction, 1 facility that has been permitted but not yet built, 1 facility built but not 

active, and 1 facility whose permit application is pending. In 2008 and 2009, expansion of the 

fuel ethanol industry in Kansas slowed. The actual emission rate of NOx for these plants is quite 

low as compared to EGUs. 

NOx PM10 SOx

EGU's 48,176.37 3,611.84 51,595.27

Ethanol Plants 374.03 294.27 59.93

Table 8-2009 Emissions Summary of Ethanol and EGUs

Nonpoint Source Inventory

Nonpoint source emissions were compiled from the final 2002 National Emissions 

Inventory (NEI) database. Although PM2.5 emissions values are not available from this data 

source, the NEI gives emissions estimates at a detailed level for source categories, so that source 

attribution is more easily analyzed. (Note also the ratio of PM2.5 to PM10, can for comparative 

purposes be approximated as 0.2). Only NOx, SO2, PM10, and VOC were considered in this 

analysis. The relative contributions of these pollutants within the nonpoint source category are 

shown in Figure 2 (below). The attribution of nonpoint source pollution on visibility at Class I 

areas is shown in Figure 4 (provided on page 17). 
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Figure 2- 2002 Emissions of Pollutants Contributing to Regional Haze from Kansas Nonpoint Sources

As can be seen by Figure 2, PM10 accounts for the largest nonpoint source category, 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 9 through 12 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 Emissions Inventory. 

Figure 4 (provided on page 17 of this document) indicates that the visibility impairment 

attributed to nonpoint source pollution from sources located in Kansas is almost equivalent to the 

visibility impairment attributed to point source pollution from sources in Kansas. However, 

although PM10 emissions are the highest of the nonpoint source category emissions, compared to 

NOx, VOC and SO2, Figure 3 (provided on page 16 of this document) indicates that a majority of 

the visibility impairment causing pollution is SO2 and NOx and not necessarily PM10. So 

although nonpoint sources in Kansas may contribute to visibility impairment in Class I areas, 

nonpoint source PM10 is not significant. 

Source classification tons/yr % of nonpoint PM10 % of total PM10

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 9- 2002 Top PM10 Emissions from Kansas Nonpoint (Area) Sources

The nonpoint source category represents a large portion of the total anthropogenic 

emissions inventory for VOC emissions. VOC emissions from nonpoint sources are projected to 

grow by 20% in 2018 from the 2002 estimate. In 2018, the estimate is for approximately

105,000 tons/yr of VOC from the nonpoint source category. Much of the nonpoint VOC is from 

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

P M1 0 VOC NOx S O2

tons/yr
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solvent utilization and residential heating. Figure 3 below demonstrates that VOC is not 

anticipated to be a large contributor to visibility impairment in the Class I areas surrounding 

Kansas so the remaining focus will be on NOx and SO2 nonpoint source emissions.

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%

Table 10-2002 Top VOC Emissions from Kansas Nonpoint (Area) Sources

NOx and SO2 make up a relatively small proportion of the State’s nonpoint emissions 

inventory. With the exception of agricultural burning, the major contributing source categories 

for NOx are associated with residential, industrial, and commercial natural gas combustion. 

These categories are projected to grow at a moderate pace between 2002 and 2018. For SO2, the 

major contributing categories are industrial fuel (primarily coal and distillate oil) combustion. 

These categories are also projected to grow at a moderate pace between 2002 and 2018. The 

nonpoint industrial coal combustion category in the NEI may be overestimated, both in the 2002 

and 2018 projected inventories, as most industrial sources utilizing coal are captured in the 

State’s point source inventory. In addition, the distillate and residual oil combustion in the 

nonpoint sector are likely to remain unchanged or decrease between 2002 and 2018. At worst, if 

the 2018 projections are correct, the nonpoint emissions for SO2 are still only a fraction of the 

point source SO2 emissions.

Source classification tons/yr

% of nonpoint 

NOx

% of total NOx

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 11- 2002 Top NOx Emissions from Kansas Nonpoint (Area) Sources
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Source classification tons/yr % of nonpoint 

SO2

% of total 

SO2

Industrial fuel combustion 24,218 66.6% 12.9%

Agricultural burning 10,949 30.1% 5.9%

Table 12- 2002 Top SO2 Emissions from Kansas Nonpoint (Area) Sources

Affected Class I Areas and Source Apportionment

There are no Class I areas hosted by the State of Kansas. States such as Kansas, that do 

not host Class I areas, are not required to identify reasonable progress goals or calculate baseline 

and natural visibility conditions at Class I areas. However, States without Class I areas are still 

required to address their apportionment of visibility impact, from the emissions generated by 

sources within the State’s borders on Class I areas hosted by other States. The following are the 

Class I areas nearest to the State of Kansas in all directions around the State’s border:

 Caney Creek Wilderness Area, Arkansas (CACR)

 Upper Buffalo Wilderness Area, Arkansas (UPBU)

 Great Sands 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, Texas (WICA)

 Big Bend National Park, Texas (BIBE)

 Guadalupe Mountains National Park, Texas (GUMO)

In order to address the issue of source attribution of regional haze for its member states, 

CENRAP contracted with ENVIRON to carry out PM Source Apportionment Technology

(PSAT) modeling, a well known “probing tool” for the CAMx photochemical model. 

ENVIRON delivered its results in the form of a customized 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 represented in terms of absolute light extinction (Bext), 

inverse megameters (Mm-1), and percent total light extinction. Data can be queried from source 

categories within individual states on individual or grouped Class I area receptors, for the years 

2002, 2000-2005 (baseline), and 2018 (end of current planning period). The PSAT tool used for 

this document is the August 27, 2007 version and is available at 

http://www.cenrap.org/html/projects.php

ENVIRON used IMPROVE monitoring data for the 2000-2004 period to define baseline, 

natural, and 2018 conditions for each of the 11 Class I areas. PM10 was speciated into six 

components (sulfate, particulate nitrate, organic carbon, elemental carbon, soil, and coarse mass) 

which were used to develop relative response factors (RRFs) between current and predicted 

concentrations for each component. The RRFs were multiplied by current baseline values to 

estimate future concentrations. The visibility improvements for 2018 were then calculated using 
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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 STI. These documents can be found at 

http://www.cenrap.org/html/projects.php

The EPA used the PSAT tool to find projected absolute and percent total light extinction 

values at eleven Class I areas. The analysis helped determine which Class I areas may be 

impacted by Kansas sources, and also provides a quantifiable basis of discussion for meeting the 

reasonable progress goals for Class I areas potentially impacted by emission sources within 

Kansas.

The 20 % worst day estimated percent light extinction, at these eleven Class I areas, 

attributed to emissions from sources in Kansas (shown by pollutant species and source category) 

is given below. The modeling (as shown in Figures 4 and 6) indicated that Kansas sources are 

most likely to have the highest impact at the WIMO Class I area. 

Figure 3- 2002 Percent Total Light Extinction at Eleven Class I Areas from Kansas Sources, by Species, for All 

Source Categories during the Worst 20% Days
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Figure 4- 2002 Percent Total Light Extinction at Eleven Class I Areas from Kansas Air Emission Sources, by Source 

Category, for All Species during the Worst 20% Visibility Days
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Figure 5- 2018 Percent Total Light Extinction at Eleven Class I Areas from Kansas Sources, by Species, for All 

Source Categories during the Worst 20% Days
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Figure 6- 2018 Percent Total Light Extinction at Eleven Class I Areas from Kansas Air Emission Sources, by Source 

Category, for All Species during the Worst 20% Visibility Days

Figures 3 through 6 reveal that the largest contributors to haze for WIMO from Kansas 

sources are nitrates (NO3). To get a more precise idea of relative contributions, the PSAT tool 

was used to generate tables for individual species, for the best 20% visibility days as well as for 

the worst 20% visibility days. Table 13 summarizes the PSAT tool-generated tables, which are 

found in Appendix 10.1 of the State’s SIP. Table 13 shows percent total extinction values 

greater than 0.5% to represent percent total extinction for the respective source category and 

species combinations on the worst and best 20% visibility days. Values of less than 0.5% were 

considered to be insignificant. This tool confirms that on the worst 20% visibility days at 

WIMO, point sources of nitrates, followed by point sources of sulfates and primary organic 

aerosol (POA) have the greatest impact of pollutants attributed to sources in Kansas. Sources of 

POA can be wildfires, mobile sources, industrial and commercial combustion, residential heating 

and open burning, burning of construction debris, industrial and commercial processes, 

agricultural burning, and fugitive dust. 
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Source category / particulate species Percent total extinction > 0.5% (%)

Worst 20% visibility days (total extinction = 72.01 Mm-1)

 Point sources – NO3 0.9572

 Point sources – SO4 0.8404

 Area sources – POA 0.7210

Best 20% visibility days (total extinction = 15.14 Mm-1)

 Point sources – NO3 0.7386

 Point sources – SO4 1.6518

 Area sources – SO4 0.5526

 Area sources – POA 1.6600

 Area sources – EC 0.6497

Table 13- 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

Best Available Retrofit Control Technology

Section 169A of the CAA directs States to evaluate the use of retrofit controls at certain 

larger, often uncontrolled, older stationary sources in order to address visibility impacts from 

these sources. Specifically, the CAA requires that certain categories of existing stationary

sources built between 1962 and 1977 procure, install, and operate the “best available retrofit 

technology”, or BART, as determined by the State. 1 States are directed to conduct BART 

determinations for the sources that cause or contribute to any visibility impairment in a Class I 

area. 

On July 6, 2005, EPA published the Guidelines for BART Determinations Under the 

Regional Haze Rule at Appendix Y to 40 CFR Part 51 (hereinafter referred to as the “BART 

Guidelines”) to assist States in determining which of their sources should be subject to the 

BART requirements and in determining appropriate emissions limits for each such source. In 

 

1

The set of “major stationary sources” potentially subject to BART are listed in CAA section 169A(g)(7). The 26 

source categories are: (1) Fossil-fuel fired steam electric plants of more than 250 million British thermal units per 

hour heat input, (2) Coal cleaning plants (thermal dryers), (3) Kraft pulp mills, (4) Portland cement plants, (5) 

Primary zinc smelters, (6) Iron and steel mill plants, (7) Primary aluminum ore reduction plants, (8) Primary copper 

smelters, (9) Municipal incinerators capable of charging more than 250 tons of refuse per day, (10) Hydrofluoric, 

sulfuric, and nitric acid plants, (11) Petroleum refineries, (12) Lime plants, (13) Phosphate rock processing plants, 

(14) Coke oven batteries, (15) Sulfur recovery plants, (16) Carbon black plants (furnace process), (17) Primary lead 

smelters, (18) Fuel conversion plants, (19) Sintering plants, (20) Secondary metal production facilities, (21) 

Chemical process plants, (22) Fossil-fuel boilers of more than 250 million British thermal units per hour heat input, 

(23) Petroleum storage and transfer facilities with a capacity exceeding 300,000 barrels, (24) Taconite ore 

processing facilities, (25) Glass fiber processing plants, and (26) Charcoal production facilities.
21

making a BART determination for a fossil fuel-fired generating plant with a total generating 

capacity in excess of 750 megawatts, a State must use the approach set forth in the BART 

Guidelines. A State is not required to follow the BART Guidelines in making BART 

determinations for other types of sources. The BART Guidelines provide five steps toward 

identifying BART control for these very large EGUs. 

1. Identify all available retrofit control technologies;

2. Eliminate technically infeasible control technologies;

3. Evaluate the control effectiveness of remaining control technologies;

4. Evaluate impacts and document the results;

5. Evaluate visibility impacts

In the BART determination process, states must address all significant visibility

impairing pollutants. The EPA determined that presumptively, the most significant visibility

impairing pollutants are SO2, NOx, and PM. As indicated by the BART Guidelines2, 

consideration of whether VOC or NH3 emissions impair visibility in particular Class I areas is on 

a state-by-state basis. In its SIP the State determined that it did not need to consider VOC or 

NH3 emissions when conducting its BART analyses. Based on its own review of VOC and NH3 

emissions in the State and the pollutant’s impacts on visibility at Class I areas, the EPA agrees 

with the State’s findings. The EPA’s analysis is described below.

Figure 7 compares 2002 VOC emission sources from each of the CENRAP states by

source sector. As explained by Table 2 (above), and confirmed by Figure 7, a majority of the 

anthropogenic VOC emission from Kansas sources are emitted by nonpoint sources such as area 

sources, area fire sources, and off road vehicles. Another major source of VOC emissions from 

the State can be attributed to on road vehicles. Since neither on road, off road, or area sources are 

included in the 26 major source categories describe by the BART rule, and since VOC emissions 

from nonpoint sources in Kansas are not expected to contribute significantly to visibility

impairment (shown in Figure 3) the EPA agrees with the State that it needn’t consider VOC 

emission reductions as part of its BART determinations.

 

2

Appendix Y of Part 51- States should exercise judgment in deciding whether the following pollutants impair 

visibility in an area :( 4) Volatile organic compounds (VOC), and (5) Ammonia and ammonia compounds. A State 

should use its best judgment in deciding whether VOC or ammonia emissions from a source are likely to have an 

impact on visibility in an area. Certain types of VOC emissions, for example, are more likely to form secondary 

organic aerosols than others. Similarly, controlling ammonia emissions in some areas may not have a significant 

impact on visibility. A State need not provide a formal showing of an individual decision that a source of VOC or 

ammonia emissions is not subject to BART review. Because air quality modeling may not be feasible for individual 

sources of VOC or ammonia, a state should also exercise its judgment in assessing the degree of visibility impacts 

due to emissions of VOC and emissions of ammonia or ammonia compounds. A state should fully document the 

basis for judging that a VOC or ammonia source merits BART review, including its assessment of the source's 

contribution to visibility impairment.
22

Figure 7 – 2002 VOC emissions by CENRAP State and Source Sector

Figure 8 compares 2002 NH3 emission sources from each of the CENRAP states by source 

sector. As explained by Table 2 (above) a majority of the anthropogenic emission from Kansas 

sources are emitted by point and onroad mobile sources. A review of the 2002 NEI data shows 

that a majority of the point source ammonia emissions come from “Agricultural Services”. 

Individually, these point sources generally have less than 250 tpy of emissions. Further review of 

the 2002 NEI data shows that only one large point source of NH3 is in one of the 26 major 

source categories the EPA has required states to consider when evaluating BART. This source is 

the Frontier Eldorado Refining Company and is discussed further in the BART-eligibility

discussion below. Based on this information the EPA agrees with the State that it needn’t 

consider NH3 emission reductions as part of its BART determinations.
23

Figure 8- 2002 Ammonia emissions by CENRAP state and Source Sector

BART Eligible Sources

The EPA has reviewed the State’s process for determining if a source is BART-eligible 

and found that the State appropriately identified nineteen facilities as having units that were 

BART-eligible. The State utilized the methodology in the BART Guidelines for determining 

which sources were BART-eligible. The following criterion was used to identify an emission 

source as BART-eligible:

 One or more emissions units at the facility fit within one of the 26 categories listed in 

the BART Guidelines;

 The emission unit was in existence on August 7, 1977 and began operation at some 

point on or after August 7, 1962; and

 The limited potential emissions from all emission units identified in the previous two 

bullets were 250 tons or more per year of any of these visibility-impairing pollutants: 

SO2, NOx, or PM10.

To identify the sources that met the criteria above, a multi-step search was conducted 

including a database query of the permitted air sources and a survey of the facilities. The first 

step to the BART-eligible screening was done by querying the point sources based on the 

following criteria: 

 The facility is operating;

 The facility is coded as being class A (controlled emissions > 100 tpy), A1 (actual 

emissions < 100 tpy, potential emissions >100 tpy), or A2 (actual/potential emission 

> major source threshold);
24

 The facility is in one of the Standard Industrial Classification (SIC) codes or has 

processes within one of the Source Classification Codes (SCCs) that meet one of the 

26 major source categories.

The second step was to eliminate sources from the fossil fuel-fired boilers category with 

less than a 250 MMBtu/hr heat input rate. The boiler values were summed for each of the 

facilities. Facilities with aggregated boiler capacity of less than 250 MMBtu/hr were then 

eliminated. This resulted in a list of 97 facilities. Then, for the 97 facilities on the list, year 2000 

actual emissions at the emission unit level were obtained and combined with 1999 Toxics 

Release Inventory (TRI) ammonia emissions data at the facility level. At this point the 

petroleum storage and transfer facilities with storage capacity <300,000 barrels were eliminated, 

along with any facilities where the potential to emit and operation/reconstruction date criteria 

were not met. 

The third step included sending the facilities surveys. Each of the 97 facilities that met 

the Regional Haze Rule’s source category criteria was sent a survey under a request for 

information about the air emission units at their facilities. The facilities were requested to submit 

potential to emit data for NOx, SO2, PM10, VOCs, and NH3 for each identified emission unit. The 

survey consisted of 4 steps:

1. Evaluate dates

2. Verify BART category

3. Enter potential emissions (tons/yr)

4. Provide boiler and tank information, if applicable

In Appendix 9.2 of the SIP, Kansas acknowledged that although it asked the facilities to 

provide VOC and NH3 emissions information, it did not intend on using that information in its 

BART-subject analysis. Since only a fraction of the VOCs emission that would be reported 

actually form secondary organic aerosols and because the screening model (CALPUFF3) cannot 

simulate formation of particles from anthropogenic VOCs, nor their visibility impacts it, the data 

would not be used in the BART determinations. NH3 emissions were included as background in 

the modeling but emissions data from specific sources was not used as part of the evaluation 

process.

Each of the facilities returned the survey forms, which were then analyzed to determine 

BART-eligibility. The analysis indicated there were 19 facilities in Kansas with BART-eligible 

units. The nineteen facilities identified by this process are listed in Table 14.

 

3 CALPUFF is a multi-layer, multi-species non-steady-state puff dispersion model that simulates the effects of timeand space-varying meteorological conditions on pollution transport, transformation and removal. CALPUFF can be 

applied on scales of tens to hundreds of kilometers. It includes algorithms for subgrid scale effects (such as terrain 

impingement), as well as longer range effects (such as pollutant removal due to wet scavenging and dry deposition, 

chemical transformation, and visibility effects of particulate matter concentrations).

http://www.epa.gov/ttn/scram/dispersion_prefrec.htm#calpuff
25

BART Source 

Category 

Name

Facility ID Facility Name BART-Eligible Emission Units

Fossil-Fuel 

Fired Electric 

Generating 

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

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

Petroleum 

Refineries

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

1130003 National Cooperative Refinery 

Assoc. (NCRA)

Alky Heater HA-002, No.9 Boiler SB-009, No.12 

Boiler SB-012, Coker IR Comp. CR-003, Plat Stab 

Boil Htr HP-003, Plat Charge Htr HP-006, 

Fugitive Emissions

Chemical 

Processing 

Plants

1730070 Basic Chemicals (now 

OxyChem - Wichita) Boiler 1; Boiler 2; Boiler 3; Chloromethanes

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

Table 14- Facilities with BART-eligible Units in the State of Kansas
26

Figure 9- Map of BART-eligible Sources in Kansas

BART Subject Sources

The EPA has reviewed the State’s process for determining if a source was BART-subject 

and has found that the State used a satisfactory method for determining which of the BARTeligible sources were BART-subject. The State completed a modeling analysis of all 19 sources 

determined to be BART-eligible, using CALPUFF. The State established a screening threshold 

of 0.5 dv (the same threshold described in the BART guidelines). If the modeling results showed 

that a source had at least a 0.5 dv or greater visibility impact on at least one day in a three year 

period (2001-2003) further BART-subject analysis was required. The one day in three-year 

period threshold, as well as the Class I areas selected for modeling, were based on 

recommendations made by staff at EPA Regions 6 and 7 in 2005. The nine Class I areas that 

were determined to be significant for determining impacts from potential BART-subject sources 

were:

 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)
27

Figure 10- Map of Class I Areas Analyzed

Table 15- List of 19 BART-eligible Source and Their Distances from each of the 9 Class I Areas analyzed. 

Highlights indicate the Class I area that the source was evaluated for to determine Impacts.
28

The modeling showed that eight of the nineteen BART-eligible sources met the screening 

criteria (0.5 dv or greater visibility impact on at least one day in a three year period). Those 

sources are identified below in Table 16.

Source CACR UPBU GRSA ROMO HEGL MING WIMO BADL WICA

Number of days during 2001-2003 with visibility impact >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

Table 16- Kansas BART-Eligible Emission Units with at Least One > 0.5 dv Visibility Impact Day on Selected 

Class I Areas during 2001–2003

The State required each of those eight sources to submit refined modeling to the State for 

further review. The refined modeling analysis for each source is given in Appendix 9.8 of the 

State’s Regional Haze SIP. Each facility’s refined modeling results were based on CALPUFF 

modeling for individual source exemption provided in the State’s BART modeling protocol. 

Monarch Cement, Kansas City BPU - Quindaro, Kansas City BPU – Nearman, 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 visibility impairment in Class I

areas. The remaining facility’s refined modeling results did show that emissions from their 

BART-eligible units were anticipated to cause or contribute to visibility impairment in Class I

areas. Five units at three sources were determined to be BART-subject and required BART 

determinations. Those five units are given below:

 Unit 1 at Kansas City Power and Light (KCP&L), La Cygne, Facility ID 1070005

 Unit 2 at Kansas City Power and Light, La Cygne, Facility ID 1070005

 Unit 1 at Westar Energy (Westar), Jeffrey Energy Center (JEC), Facility ID 1490001

 Unit 2 at Westar Energy, Jeffrey Energy Center, Facility ID 1490001

 Unit 2 at Westar Energy, Gordon Evans Energy Center (GEC), Facility ID 1730012

It should be mentioned that BPU submitted the Black & Veatch-prepared document Best 

Available Retrofit Technology Engineering Analysis for its Nearman Facility Unit 1 to the State 

in February 2007. In November 2007, the State determined that there was a potential issue with 
29

the hourly emission rates used in the initial modeling determination resulting in Nearman Unit 1 

qualifying as a BART source. The State informed BPU of this potential issue and BPU revised 

both the 24 hour maximum emission rates and the BART determination modeling they had 

performed. On December 19, 2007 the State received the revised 24 hour maximum emission 

rates from BPU for Nearman Unit 1. Along with the revised emissions rate, BPU also submitted 

additional CALPUFF modeling for purposes of a BART determination. This new modeling 

indicated Nearman Unit 1 should not have been included as a BART source. The modeling BPU 

performed was based on the approved CALPUFF modeling protocol. It was therefore 

determined that BPU’s Nearman Unit 1 is not a source subject to BART because it was not 

anticipated to have an visibility impairment of greater than 0.5 dv based on a 98th percentile. 

BART determinations for the five subject-to-BART units in Kansas were carried out by 

third-party contractors on behalf of the sources’ two owners and submitted to the State for 

approval. Because all five of the BART units are EGUs and are located at 750 MW facilities, the 

State stipulated that the minimum BART control level would be the presumptive limits specified 

in the BART Guidelines. Kansas provided each owner with a guideline for conducting their 

determination, titled “Guidance for Facilities Conducting a BART Analysis” (found in Appendix 

9.4 of the SIP). Although the guidance stated that if a facility was considered a presumptive 

EGU, and proposed controls at or beyond the presumptive emission limits, then the facility need 

not take into account the remaining statutory factors (as the State assumed BART would be met), 

the EPA has determined that each of the BART determinations did consider each of the five 

statutory factors. As mentioned above, the State is required to evaluate EGUs greater than 750 

MW in accordance with the BART guidelines. The BART Guidelines provide five steps 

(discussed previously) toward identifying BART control for these very large EGUs. The 

resulting analyses are found in Appendix 9.5 (KCP&L) and Appendix 9.6 (Westar) and are 

discussed below. 

The BART emission rates (established after consideration of each of the five statutory

factors, discussed in detail below) are summarized in Table 17 and have been included in 

Consent Agreements with each source.

Subject-to-BART Emission Unit BART Presumptive Limit BART Operational Standard

NOx SO2 NOx SO2

lb/MMBtu

KCP&L - La Cygne Unit 1 0.10 0.16* 0.15 0.15* 0.13* 0.10* KCP&L - La Cygne Unit 2 0.23 0.15

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

Table 17- BART Presumptive Limits and Operational Standards for NOx and SO2 at Subject-to-BART Emission 

Units in Kansas

BART Determination for Westar JEC Units 1 and 2

The State determined that JEC Units 1 and 2, located in St. Mary’s, Kansas and GEEC 

Unit 2, located in Colwich, Kansas, meet the BART eligibility criteria and contribute greater 

than 0.5 ∆dv to visibility impairment in a federally protected Class I area when compared to a 

natural background. Therefore, these three units are subject to BART. JEC Units 1 and 2 are 
30

each 720 MW coal-fired boilers. GEEC Unit 2 is a 383MW oil-fired boiler (The GEEC facility

has a capacity greater than 750 MW). Therefore each of the units is a presumptive BART unit.

The emission limits (described in Table 17 above) determined to represent BART for 

JEC Units 1 and 2 are maximum emission rates for the visibility-impairing pollutants NOx and 

SO2 because they are coal fired units. Because GEC Unit 2 is an oil fired unit, it is subject to a 

fuel switch as BART. The State determined that added PM2.5 controls would only improve 

visibility marginally, and would not be cost effective. 

A summary of the visibility impairment attributable to the JEC Units 1 and 2 and GEEC 

Unit 2 is provided in Table 18. 

Wichita 

Mountains

Hercules 

Glades 

Wilderness

Caney Creek 

Wilderness Mingo NWR Upper Buffalo Wilderness

98th 

% 

∆dv

Days 

> 0.5 

∆dv

98th 

% 

∆dv

Days > 

0.5 

∆dv

98th 

% 

∆dv

Days 

> 0.5 

∆dv

98th 

% 

∆dv

Days 

> 0.5 

∆dv

98th 

% 

∆dv

Days 

> 0.5 

∆dv

JEC Unit 1 and Unit 2 0.99 59 0.90 63 0.73 37 0.49 21 0.85 53

GEEC Unit 2 1.08 85 0.40 16 0.38 14 0.17 4 0.42 16

Table 18- Visibility Impairment Attributable to JEC Units 1 and 2 and GEC Unit 2 (2001-2003). “BART Five 

Factor Analysis- Westar Energy” Trinity Consultants

SO2 BART Determination

Table 19-Pollutant Specific Contributions to Existing Visibility Impairment for JEC Unit 1 and 2 (2001-2003). 

“BART Five Factor Analysis- Westar Energy” Trinity Consultants

As shown in Table 19, the most significant visibility impairment attributable to these 

units is dominated by NOx emissions followed by SO2. PM visibility impairment attribution 

from these units is not significant. Because visibility impairment from PM is insignificant, the 

remainder of this section will focus the control strategies to reduce NOx and SO2.

The five factor analysis identified several available control technologies for SO2. This 

list included Dry Sorbent Injection (DSI), Wet Scrubbing, Dry Scrubbing and Circulating Dry

Scrubbing (CDS). It was found that all were technically feasible with scrubbing ranking as the 

control with the highest removal efficiency (Wet and Dry scrubbing have removal efficiencies 

that are very similar). Because scrubbing technology has the highest removal efficiency of the 
31

above mentioned technologies, it was determined that the remainder of the analysis would 

evaluate only scrubbing for SO2 BART control. As the State had determined that the highest 

efficiency control technology would be BART, no cost comparison of lower efficiency controls 

was needed.

The only non-air quality environmental impact raised as a potential issue was the 

handling of the waste product that results from scrubbing. It was determined that this issue was 

related more to cost and did not prohibit the implementation of scrubbing. The remaining useful 

life of the units was considered as well. It was determined that the useful life of the units were 

anticipated to be at least as long as the capital cost recovery period, which is 20 years, so the 

useful life of the units was not a hindrance to control for SO2 BART. 

Next, the analysis considered the visibility improvement from scrubbing. As shown in 

Table 20, the implementation of scrubbing the units will result in at least a 0.68 dv improvement 

at the WIMO and a total visibility improvement of 2.8 dv improvement across all five Class I

areas analyzed (considering maximum visibility impacts).

Table 20- Visibility Improvement from the Implementation of Presumptive SO2 BART. “BART Five Factor 

Analysis- Westar Energy” Trinity Consultants

Based on the consultant’s analysis, the State determined that the SO2 BART emission rate 

for JEC Unit 1 and Unit 2 would be 0.15 lb/MMBtu based on the operation of wet scrubbers. 

The State required (through consent agreements) the facility to meet this limit for each unit on a 

30-day rolling average, excluding periods of startup, shutdown and malfunction (SSM). 

Compliance will be demonstrated using data from the existing continuous emissions monitoring 

systems (CEMS). Excluding the language on startup, shutdown and malfunction (as discussed in 

the Federal Register notice) in the Consent Agreements and in the State’s SIP, the EPA finds that 

the proposed control strategy meets the presumptive limits established in the BART guidelines 

and sufficiently considers each of the five statutory factors. 

NOx BART Determination

For NOx control, the State indentified Flue Gas Recirculation (FGR), Overfire Air 

(OFA), Low NOx Burners (LNB), Selective Catalytic Reduction (SCR) and Selective Non-
32

Catalytic Reduction (SNCR) as being reasonably available, technically feasible technologies. 

The most efficient of these technologies was identified as being SCR followed by LNB systems. 

Because they were identified as being the most efficient, SCR and LNB were the only control 

technologies evaluated for cost. 

The life expectancy considerations of these two units were discussed previously in this 

document. The State considered ammonia slip as a potential non-air environmental impact from 

SCR and SNCR NOx control but did not determine that it was significant enough an issue to 

eliminate SCR or SNCR from consideration. 

In the BART guidelines, EPA states that most EGUs can meet the presumptive NOx

limits through the use of current combustion control technology, i.e. LNB. For units that cannot 

meet these rates using such technologies, the State should consider whether advanced 

combustion control technology should be considered. The EPA calculated that for all types of 

boilers, other than cyclone boilers, combustion control technology is generally more costeffective than post-combustion controls. The EPA estimated that approximately 75 percent of the 

BART units (non-cyclone) could meet the presumptive NOx limits at a cost of $100 to $1,000 per 

ton of NOx removed based on the use of combustion control technology4. The EPA estimated, 

for the units that could not meet the presumptive limits using combustion control technology, 

that almost all of these sources could meet the presumptive limits using advanced combustion 

controls; the EPA estimated that the cost of such controls are usually less than $1,500 per ton 

removed56.

Table 18- Cost Effectiveness Calculations for JEC Units 1 and 2. “BART Five Factor Analysis- Westar Energy” 

Trinity Consultants.

Table 17 indicates that the cost effectiveness of LNB systems for JEC Unit 1 and

Unit 2 is less than $1,500 per ton of NOX removed. Tables 17 also indicates that the costs for 

SCR for JEC Unit 1 and Unit 2 are over $1500 per ton of NOX removed (JEC Unit 1 SCR cost = 

$2,211/ton and JEC Unit 2 SCR cost = $1,738/ton). As shown in Table 18 and 19 the visibility

improvement from implementation of LNB at Unit 1 is estimated to be 0.57 dv at WIMO and 

1.82 dv across all five Class I areas analyzed (considering maximum visibility impacts). The 

addition of SCR would only benefit 0.27 dv for an incremental cost increase of $6,613/ton. 

Based on these facts the State determined that it was reasonable to determine that NOx BART 

for JEC Units 1 and 2 is the implementation of LNBs. 

 

4

70 CFR 39135 column 2 

5

70 CFR 31935 column 3

6 Technical Support Document for BART NOx Limits for Electric Generating Units and Technical Support 

Document for BART NOx Limits for Electric Generating Units Excel Spreadsheet, Memorandum to Docket OAR 

2002-0076, April 15, 2005
33

Table 21- Summaries of Cost effectiveness of NOx controls at JEC units 1 and 2. “BART Five Factor AnalysisWestar Energy” Trinity Consultants

Table 22-Summary of Modeled Impacts from NOx Control for JEC Unit 1 (2001-2003). “BART Five Factor 

Analysis- Westar Energy” Trinity Consultants

Table 23- Summary of Modeled Impacts from NOx Control for JEC Unit 2 (2001-2003). “BART Five Factor 

Analysis- Westar Energy” Trinity Consultants

Based on the consultant’s analysis, the State has determined that the NOx BART emission 

rate is 0.15 lb/MMBtu for both JEC Unit 1 and Unit 2. The State has required the facility

(through the previously discussed consent agreement) to meet this limit for both JEC Unit 1 and 

Unit 2 by installing LNB systems. The State eliminated SCR as NOx BART due to the high 

incremental cost of SCR over LNB systems ($11,496,886 as an average over the two units) and 

the minimal increase in visibility improvement (0.05 dv improvement for both units). The EPA 

finds that the proposed control strategy meets the presumptive limits established in the BART 

guidelines and sufficiently considers each of the five statutory factors. We also believe that the 
34

State reasonably concluded that NOx BART is LNB in light of the incremental cost and the 

minimal impacts on visibility associated with SCR. 

BART Determination for Westar GEC Unit 2

SO2 BART Determination

Table 24-Pollutant Specific Contributions to Existing Visibility Impairment for GEC Unit 2 (2001-2003). “BART 

Five Factor Analysis- Westar Energy” Trinity Consultants

As shown in Table 24 (above), the most significant visibility impairing pollutant 

attributable to this unit is NOx followed by SO2. PM visibility impairment attribution from this 

unit is not significant. Because visibility impairment from PM is insignificant, the remainder of 

this section will focus on control strategies to reduce NOx and SO2.

The five factor analysis first identified several available control technologies for SO2. 

These were DSI, Wet Scrubbing, Dry Scrubbing, CDS, and fuel switching. DSI, Dry and Wet 

Scrubbing, as well as CDS are technologies collectively known as flue gas desulfurization (FGD) 

systems. FGD applications have not been used historically for SO2 control in the U.S. electric 

industry on oil-fired units. The EPA took this into account when establishing the presumptive 

SO2 emission rate7for oil-fired units and determined that the presumptive emission rate should 

be based on the sulfur content of the fuel oil, rather than on FGD. Therefore, FGDs are 

considered technically infeasible for the control of SO2 from GEEC Unit 2 and were not 

considered for BART for GEC Unit 2. 

The EPA identified, in the BART guidelines, that one percent sulfur fuel oil is the 

presumptive BART limit for oil-fired units. The one percent sulfur oil is an alternative to the 

No. 6 fuel oil that is currently combusted by GEEC Unit 2. The lower sulfur content of the one 

percent sulfur fuel oil would result in approximately a 33 percent reduction in SO2 emissions 

from GEC Unit 2 (see Table 25) as compared to the combustion of the current No. 6 fuel oil, 

which contains approximately 1.5 percent sulfur. Fuel switching to 1 percent sulfur fuel oil is a 

technically feasible option for the control of SO2 from GEC Unit 2.

 

7

Summary of Comments and Responses on the 2004 and 2001 Proposed Guidelines for Best Available Retrofit 

Technology (BART) Determinations Under the Regional Haze Regulations EPA Docket Number OAR-2002-0076.
35

Unit Emission Rate Scenario Emission Rate

SO2 NOX PM10*

(lb/hr) (lb/hr) (lb/hr)

GEEC Unit 2 Existing Emission Rate 5,766.7 4,818.3 431.5

1 Percent Sulfur Fuel Oil 3,844.5 4,818.3 326.3

Table 25- Summary of Emission Rates Comparing Existing Control to a Fuel Switch at GEC Unit 2. “BART Five 

Factor Analysis- Westar Energy” Trinity Consultants

*PM10 emissions are calculated based on AP-42 emission factors.

The analysis also considered the cost of SO2 BART control of GEC Unit 2. The cost 

effectiveness of switching to one percent sulfur fuel oil has been evaluated. The cost of the fuel 

switching that was used in the cost effectiveness calculations was determined by calculating the 

cost of the current No. 6 fuel oil and determining the increased cost of switching to one percent 

sulfur fuel oil. It was assumed in this analysis that the fuel switch will not require any capital 

expenses. The fuel costs for one percent fuel oil was determined from the fuel costs published 

by the Energy Information Administration. The fuel cost for the No. 6 fuel oil is the market 

price on February 14, 2007.

The annual tons reduced that were used in the cost effectiveness calculations were 

determined by subtracting the estimated controlled annual emission rates from the existing 

annual emission rates. The existing annual emission rates was the highest 365 day rolling totals 

as determined from CEMS data from 2002-2004. The controlled annual emission rate was 

estimated by reducing the existing annual emission rate by 33 percent.

In the BART guidelines, EPA calculated that that the majority of BART-eligible units 

could meet the presumptive limits at a cost of $400 to $2,000 per ton of SO2 removed, based on 

the use of wet scrubbers and SDA systems8. Table 26 indicates that the cost of switching to one 

percent sulfur fuel oil is well above this range. 

Estimated No. 6 

Oil Hourly 

Usage Rate*

Estimated 

No. 6 Oil 

Annual Fuel 

Usage†

No. 6 Oil Fuel 

Cost

Estimated 

Annual No. 6 

Oil Fuel Cost

Estimated 1% 

S Fuel Oil 

Hourly Usage 

Rate*

Estimated 1% 

S Fuel Oil 

Annual Fuel 

Usage‡

1% S Fuel Oil

Cost

Estimated 

Annual 1% S 

Fuel Oil Cost

Mgal/hr Mgal/yr Cents/gal $/yr Mgal/hr Mgal/yr Cents/gal $/yr

27.40* 108,011† 85 91,809,180 27.96‡ 110,215† 117.1 129,061,884

Annual Cost of Fuel 

Switching

SO2 Cost 

Effectiveness

($/yr) ($/ton)

37,252,704 25,969

Table 26- Summary of Cost Effectiveness for Switching from No. 6 Oil to one percent sulfur fuel. “BART Five 

Factor Analysis- Westar Energy” Trinity Consultants

*4110 MMBtu/hr/150 MMBtu/Mgal; ‡4110 MMBtu/hr/147 MMBtu/Mgal; †Annual fuel usage is based on the 

hourly fuel usage rate and 3,942 annual operating hours (Assuming unit operates at an annual 45% capacity factor, 

45% * 8,760 hours = 3,942 hours)

 

8

70 FR 39132 column 3
36

There were no non-air quality environmental impacts raised as potential issues for fuel 

switching. The analysis did consider the remaining useful life of the units. It was determined 

that the remaining useful life of GEC Unit 2 was not a deterrent for considering SO2 BART 

control at GEC Unit 2 it was assumed that fuel switching would not require capital costs, and 

therefore did not impact the annualized cost. 

Finally, the analysis considered the visibility improvement from a fuel switch. As shown 

in Table 26, the implementation of a fuel switch at GEC Unit 2 will result in at least a 0.14 dv 

improvement at the WIMO and a total visibility improvement of 0.70 dv improvement across all 

five Class I areas analyzed (considering maximum visibility impacts).

The State, after initial consideration of each of the five statutory factors, determined that 

SO2 BART for GEC Unit 2 could be a fuel switch to one percent sulfur fuel oil. However, after 

consideration of a “BART Alternative” proposed by Westar (and discussed later in this 

document) the State’s final SO2 BART determination for GEC Unit 2 is a fuel switch to natural 

gas combustion.

Table 27- Summary of Modeled Impacts from SO2 control at GEC Unit 2 (2001-2003). “BART Five Factor 

Analysis- Westar Energy” Trinity Consultants

NOx BART Determination

For NOx control, the State indentified FGR, OFA, LNB, SCR and SNCR as being 

reasonably available, technically feasible technologies. The most efficient of these technologies 

was identified as being SCR followed by LNB systems. Because it was identified as being the 

most efficient, SCR was the only control technology evaluated for cost. The capital cost and 

operating costs of SCR were estimated based on the State’s SCR installation experience. The 

capital costs were annualized over a 20-year period and then added to the annual operating costs 

to obtain the total annualized costs. The annual tons reduced that were used in the cost 

effectiveness calculations were estimated by subtracting the estimated controlled annual 

emission rates from the existing annual emission rates. The existing annual emission rates were 

the highest 365 day rolling totals as determined from CEMS data from 2002-2004. 

Wichita Mountains

Hercules Glades 

Wilderness

Caney Creek 

Wilderness Mingo NWR

Upper Buffalo 

Wilderness

Maxim

u

m Im

pact

(Δ

d

v)

98% Im

pact (Δ

d

v)

#

Days > 0.5 Δ

d

v

VisibilityIm

provement*

Maxim

u

m Im

pact

(Δ

d

v)

98% Im

pact (Δ

d

v)

#

Days > 0.5 Δ

d

v

VisibilityIm

provement*

Maxim

u

m Im

pact

(Δ

d

v)

98% Im

pact (Δ

d

v)

#

Days > 0.5 Δ

d

v

VisibilityIm

provement*

Maxim

u

m Im

pact

(Δ

d

v)

98% Im

pact (Δ

d

v)

#

Days > 0.5 Δ

d

v

VisibilityIm

provement*

Maxim

u

m Im

pact

(Δ

d

v)

98% Im

pact (Δ

d

v)

#

Days > 0.5 Δ

d

v

VisibilityIm

provement*

Existing 

Emission 

Rate 2.16 1.08 85 - 1.31 0.40 16 - 1.07 0.38 14 - 0.71 0.17 4 - 2.22 0.42 16 -

One 

Percent 

Sulfur 

Fuel Oil 2.02 0.94 71 13% 1.19 0.34 10 13% 0.87 0.34 9 10% 0.65 0.14 2 16% 2.04 0.38 15 10%
37

The controlled annual emission rates were estimated by multiplying estimated control 

efficiency for the SCR (90 percent) by the existing annual emission rates. A sample of the 

controlled annual emission rate is shown as follows: 2,352tpy *(100%  90%) =235 tpy

The cost effectiveness for the SCR was determined by dividing the annual cost by the 

annual tons reduced. The cost is summarized in Table 28. The cost of the SCR is greater than 

$5,300/ton of NOX removed. Compared to the cost effectiveness range for NOx BART control 

(established by the EPA and previously discussed) the State determined that the cost of SCR was 

prohibitive.

Current 

Annual 

Emission 

Rate

Controlled 

Annual 

Emission 

Rate*

Estimated 

Reduced 

Emissions

Capital 

Cost†

Annualized 

Capital 

Cost‡

Annualized 

Fixed 

O&M‡

Annualized 

Variable 

O&M‡

Total 

Annualized 

Cost

Cost 

Effectiveness

(tpy) (tpy) (ton/yr) ($) ($/yr) ($/yr) ($/yr) ($/yr) ($/ton)

SCR 2,352 235 2,117 81,000,000 9,514,260 218,932 1,627,628 11,360,820 5,367

Table 28- Summary of Cost Effectiveness for GEC Unit 2 NOx Control (SCR). “BART Five Factor AnalysisWestar Energy” Trinity Consultants

*The annual emission rate represents a control efficiency of 90%.

†The SCR capital cost was determined from recent SCR installation experience

‡The costs are annualized in 2006 dollars. 

The non-air environmental impacts were evaluated for SCR. The five factor analysis 

briefly describes some concern with electricity consumption of SCR and the potential for SCR to 

potentially cause environmental impacts related to the usage and storage of ammonia. Storage of 

aqueous ammonia above 10,000 lbs is regulated by a risk management program (RMP), since the 

accidental release of ammonia has the potential to cause serious injury and death to persons in 

the vicinity of the release. Ammonia can also be emitted in the exhaust of boilers that operate 

with SCR or SNCR for NOx control due to ammonia slip. Ammonia slip from SCR and SNCR 

systems occurs either from ammonia injection at temperatures too low for effective reaction with 

NOx, leading to an excess of un-reacted ammonia, or from over-injection of reagent leading to 

uneven distribution; which also leads to an excess of un-reacted ammonia. Ammonia released 

from SCR and SNCR systems will react with sulfates and nitrates in the atmosphere to form 

ammonium sulfate which are sources of regional haze.

The remaining useful life of GEEC Unit 2 does not impact the annualized capital costs of 

potential controls because the useful life of the unit is anticipated to be at least as long as the 

capital cost recovery period, which is 20 years.

The State compared the visibility improvement for existing emission rates to the emission 

rates associated with SCR. The results of this analysis are given in Table 29 (Table 31 shows the 

visibility improvement expected of LNB and 1% sulfur coal). The existing emission rates and 

emission rates associated with SCR were modeled using CALPUFF. The existing emission rates 

were the same rates that were modeled for the BART applicability analysis. The emission rate 

associated with the SCR for GEC Unit 2 was 0.12 lb/MMBtu. The emission rate for SCR was 

determined by reducing the existing hourly equivalent of the maximum 24-hour emission rate by 

a control efficiency of 90 percent. 
38

Comparisons of the existing visibility impacts and the visibility impacts associated with 

SCR, including the maximum modeled visibility impact, 98th percentile modeled visibility

impact, and the number of days with a modeled visibility impact greater than 0.5 Δdv, for each 

Class I area are provided in Table 29 for GEC Unit 2. As shown in Table 29, the installation of 

SCR results in a 98th percentile modeled visibility impact of 0.09 to 0.60 dv as compared to 0.17 

to 1.08 dv (depending on the Class I area) at the existing emission rate, and attributable to GEC 

Unit 2. However, as previously documented in Table 28, the cost of SCR for this unit is 

estimated at over $5,300/ton. This cost is high compared to the relatively minimal associated 

visibility improvement.

Table 29- Summary of Modeled Visibility Impacts from SCR control. “BART Five Factor Analysis- Westar 

Energy” Trinity Consultants

Since the cost of SCR was high given the associated visibility improvements, the State 

determined that LNB could achieve at least the presumptive emission rate at GEC Unit 2 and 

therefore LNB would be NOx BART for GEC Unit 2. However, since the concurrent analysis 

for SO2 reduction (discussed later in this document) demonstrated that control through fuel 

switching to natural gas resulted in both SO2 and NOx emission reductions, and in visibility

improvements beyond those gained by presumptive BART, the State determined, and EPA 

agrees, that the fuel switch to natural gas meets the NOx BART requirements.

BART Alternative for GEC Unit 2

Based on the SO2 and NOx BART analyses, the State had determined that BART for SO2 

for GEC Unit 2 was likely the combustion of one percent sulfur fuel oil and BART for NOX was 

the installation of LNB. However, Westar proposed an alternative to the controls determined to 

meet BART for SO2 and NOX for GEC Unit 2. In order for control strategies to be acceptable as 

an alternative to what is determined to meet BART, the alternatives must show greater visibility

Wichita Mountains Hercules Glades 

Wilderness Caney Creek Wilderness Mingo NWR Upper Buffalo Wilderness

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement

Existing 

Emission 

Rate 2.16 1.08 85 - 1.31 0.4 16 - 1.07 0.36 14 - 0.71 0.17 4 - 2.22 0.42 16 -

SCR 1.34 0.60 28 45% 1.09 0.20 5 51% 0.65 0.21 4 46% 0.34 0.09 0 48% 1.07 0.20 8 51%

* Improvement is based on the 98% impact visibility improvement (Δdv) of SCR over the existing emission rate.
39

improvement on average than what is determined to meet BART based on the following 

visibility metrics9: 

 The maximum visibility impact 

 The 98th percentile visibility impact 

 The number of days where the visibility impacts are greater than 0.5 ∆dv 

The State chose to implement this test by evaluating whether the values for the metrics listed 

above for an alternative BART control strategy were equal to or better than the values for the 

BART control strategy for each Class I area. 

As an alternative to combusting one percent fuel oil to reduce SO2 and LNB to reduce 

NOx for GEC Unit 2, Westar proposed to combust natural gas in GEC Unit 2. Westar proposed 

to demonstrate compliance with the alternative BART control strategy for GEC Unit 2 agreeing 

to submit annual certifications of compliance verifying that natural gas was the only fuel 

combusted in GEC Unit 2 for the year, except as provided below. 

In order to assure electric system reliability, Westar requires the availability of an 

emergency fuel for backup, as well as the ability to burn a limited amount of the fuel periodically 

during non-emergencies to assure that the emergency system functions adequately. When the 

natural gas company implements an Operational Flow Order (OFO) or declares an emergency 

which could result in an impact to electric system reliability, Westar will combust No. 6 fuel oil 

for the time period of the emergency. Westar will diminish the existing supply of No. 6 fuel oil, 

once diminished the emergency fuel will be replaced with a fuel oil containing 1percent or less 

sulfur content. 

The modeled visibility impacts of the BART control strategy and the proposed alternative 

BART control strategy are summarized in Table 30. The visibility improvement associated with 

the BART and alternative BART control options are also shown in Table 30; this value was 

calculated as the difference between the existing visibility impairment and the visibility

impairment for the BART and alternative BART control options as measured by the 98th

percentile modeled visibility impact. The visibility impacts for each metric are lower in all five 

Class I areas for the alternate BART control strategy and are shown in Table 31.

Because the maximum visibility impact, the 98th percentile visibility impact and the 

number of days where the visibility impacts are greater than 0.5 ∆dv are equal to or better than 

the values for the presumptive BART control strategy (even though the emissions of NOx are 

higher with the alternative than the presumptive BART strategy), for each Class I area, the State 

determined that the BART alternative met the requirements of the Rule. 

Based on the consultant’s analysis, the State has determined that the fuel switch to natural 

gas provides greater reasonable progress than NOx and SO2 BART presumptive limits combined. 

The State has required the facility (through previously discussed consent agreement) to establish 

 

9

40 CFR § 51.308(e)- Best Available Retrofit Technology (BART) requirements for regional haze visibility 

impairment. The State must submit an implementation plan containing emission limitations representing BART and 

schedules for compliance with BART for each BART-eligible source that may reasonably be anticipated to cause or 

contribute to any impairment of visibility in any mandatory Class I Federal area, unless the State demonstrates that 

an emissions trading program or other alternative will achieve greater reasonable progress toward natural visibility 

conditions.
40

compliance with this strategy by reporting to the State fuel oil usage at Unit 2 in accordance with 

K.A.R. 28-19-512. The EPA is proposing to find that the proposed control strategy meets the 

presumptive limits established in the BART guidelines and sufficiently considers each of the five 

statutory factors. EPA also is proposing to find that Kansas reasonably concluded that the BART 

alternative will provide for greater reasonable progress than BART.

Presumptive BART 

Case-1% Sulfur, LNB at 

0.8 lb/MMBTu 

Presumptive BART Case1% Sulfur, LNB at 0.2 

lb/MMBTu 

Alternative BART CaseNatural Gas 

Maximum (in 

dv) 1.575 1.02 0.744

98% (in dv) 0.804 0.474 0.344

NOx (lb/hr) 3288.0 822.0 2136.0

SO2 (lb/hr) 3844.4 3844.4 1.7

PM (lb/hr) 324.7 326.3 30.6

Table 30- Comparison of Presumptive BART (1% Sulfur Fuel and LNB) to the BART Alternative
41

Wichita Mountains Hercules Glades 

Wilderness Caney Creek Wilderness Mingo NWR Upper Buffalo Wilderness

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement

Existing Emission Rate 2.16 1.08 85 - 1.31 0.4 16 - 1.07 0.36 14 - 0.71 0.17 4 - 2.22 0.42 16 -

Existing BART-LNB +1% sulfur 

fuel oil 2.02 0.94 71 13% 1.19 0.34 10 13% 0.87 0.34 9 10% 0.65 0.14 2 16% 2.04 0.38 15 10%

Altnernative-Natural Gas 1.66 0.69 44 36% 0.93 0.21 4 48% 0.49 0.25 0 34% 0.49 0.08 0 55% 1.62 0.28 11 33%

* Improvement is based on the 98% impact visibility improvement (Δdv) of SCR over the existing emission rate.

Table 31- Comparison of Presumptive BART (1% Sulfur Fuel and LNB) to the BART Alternative at Five Class I area. “BART Five Factor Analysis- Westar 

Energy” Trinity Consultant
42

BART Determination for KCP&L Units 1 and 2

The State determined that KCP&L Units 1 and 2, located in La Cygne, Kansas met the 

BART eligibility criteria and contribute greater than 0.5 ∆dv to visibility impairment in a 

federally protected Class I area when compared to a natural background. Therefore, these units 

are subject to BART. KCP&L Unit 1 is an 840 MW boiler with a scrubber for SO2 and PM 

control and overfire air that minimizes the formation of NOx. Unit 2 is a 710 MW boiler that 

has an electrostatic precipitator (ESP) for PM control. Unit 1 burns a blend of Powder River 

Basin (PRB) coal and local coal. Unit 2 burns 100 percent PRB coal. Both units are presumptive 

units for BART.

The emission limits determined to represent BART for KCP& L Units 1 and 2 are 

maximum emission rates for the visibility-impairing pollutants NOx and SO2 because they are 

coal fired units.

A summary of the visibility impairment attributable to the KCP& L Units 1 and 2 is 

provided in Table 32. 

Table 32-Visibility Impairment Attributable to KCP&L Units 1 and 2 (2001-2003). “BART Five Factor AnalysisKansas City Power & Light- La Cygne” Trinity Consultants

SO2 BART Determination

Table 33- Pollutant Specific Contributions to Existing Visibility Impairment for KCP& L Units 1 and 2. “BART 

Five Factor Analysis- Kansas City Power & Light- La Cygnes” Trinity Consultants

As shown in Table 33, the most significant visibility impairment attributable to these 

units is pretty evenly dominated by NOx and SO2. PM visibility impairment attribution from 

these units is not significant. Because visibility impairment from PM is insignificant, the 

remainder of this section will focus the control strategies to reduce NOx and SO2.
43

The five factor analysis identified several available control technologies for SO2. This 

list included DSI, Wet Scrubbing, Dry Scrubbing and CDS. It was found that all were 

technically feasible with scrubbing ranking as the control with the highest removal efficiency 

(Wet and Dry scrubbing have removal efficiencies that are very similar). Because scrubbing 

technology has the highest removal efficiency of the above mentioned technologies, it was 

determined that the remainder of the analysis would evaluate only scrubbing for SO2 BART 

control. The State had determined that the highest efficiency control technology would be 

BART, and no cost comparison of lower efficiency controls was needed.

The only non-air quality environmental impact raised as a potential issue was the 

handling of the waste product that results from scrubbing. It was determined that this issue was 

related more to cost and did not prohibit the implementation of scrubbing. The remaining useful 

life of the units was considered as well. It was determined that the useful life of the units were 

anticipated to be at least as long as the capital cost recovery period, which is 20 years, so the 

useful life of the units was not a hindrance to control for SO2 BART. 

Next, the analysis considered the visibility improvement from scrubbing. As shown in 

Table 34, the implementation of scrubbing the units will result in at least a 0.81 dv improvement 

at the WIMO and a total visibility improvement of 5.32 dv improvement across all five Class I 

areas analyzed (considering maximum visibility impacts).

Table 34- Visibility Improvement from the Implementation of Presumptive BART. “BART Five Factor AnalysisKansas City Power & Light- La Cygnes” Trinity Consultants

Based on the consultant’s analysis, the State determined that the SO2 BART emission rate 

for KCP&L Unit 1 and Unit 2 would be 0.15 lb/MMBtu (as a weighted average) based on the 

operation of wet scrubbing technology. However, during the process of developing the consent 

agreement, KCP&L proposed a more restrictive emission limit than the presumptive limit of 0.15 

lb/MMBtu (weighted average), to 0.10 lb/MMBtu on a 30-day rolling weighted average. 

Compliance will be demonstrated by reconfiguring 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.

Compliance will be demonstrated using data from the existing CEMS. Excluding the 

language on SSM in the Consent Agreement and in the State’s SIP (as discussed in the Federal 

Register notice) the EPA finds that the proposed control strategy meets the presumptive limits 

established in the BART guidelines and sufficiently considers each of the five statutory factors. 
44

NOx BART Determination

For NOx control, the State indentified FGR, OFA, LNB, SCR and SNCR as being 

reasonably available, technically feasible technologies. The most efficient of these technologies 

was identified as being SCR followed by LNB systems. Because it was identified as being the 

most efficient SCR was evaluated for cost. Because it was a combustion control technology

capable of achieving the presumptive BART level for NOx, LNB was also evaluated for cost. 

At the time of the five factor analysis, KCP&L was in the process of constructing an SCR 

system on KCP&L Unit 1. Since SCR provides the highest level of control there was no need to 

evaluate the cost for other NOx controls for Unit 1. The life expectancy considerations of these 

two units were discussed previously in this document. The State considered ammonia slip as a 

potential non-air environmental impact from SCR control but did not determine that it was 

significant enough an issue to eliminate SCR or from consideration.

Table 35-Summary of Cost Effectiveness of NOx Control at KCP&L Units 2. “BART Five Factor Analysis- Kansas 

City Power & Light- La Cygnes” Trinity Consultants

Table 36- Summary of NOx Control at KCP&L Unit 2. “BART Five Factor Analysis- Kansas City Power & Light- La 

Cygnes” Trinity Consultants

Kansas stated in its SIP that the EPA is on record stating that most EGUs can meet the 

presumptive NOx limits through the use of current combustion control technology, i.e. LNB. For 

units that cannot meet these rates using such technologies, the State should consider whether 

advanced combustion control technology should be considered. The EPA estimated that 

approximately 75 percent of the BART units (non-cyclone) could meet the presumptive NOx 

limits at a cost of $100 to $1,000 per ton of NOx removed based on the use of combustion control 
45

technology10. The EPA estimated, for the units that could not meet the presumptive limits using 

combustion control technology, that almost all of these sources could meet the presumptive 

limits using advanced combustion controls; the EPA estimated that the cost of such controls are 

usually less than $1,500 per ton removed1112. Kansas went on to conclude that since the cost 

effectiveness of SCR (and advanced combustion control technology) implementation at KCP&L 

is greater than the $1,500 cost effectiveness threshold to meet the presumptive emission limits 

for a coal fired unit, LNB are NOx BART for KCP&L Unit 2. Although Kansas’ recitation of the 

Federal Register and guidance is correct, use of the above estimated cost ranges at which many 

BART units across the nation could meet presumptive NOx limits as a cost threshold to 

eliminate, outright, more stringent limits associated with technology such as SCR, is 

inappropriate.

Based on the consultant’s analysis, the State had determined that the NOx BART 

emission rates were the presumptive emission rates of 0.10 lb/MMBtu and 0.23 lb/MMBtu for 

Unit 1 and Unit 2, respectively (or 0.16 lb/MMBtu as a weighted average), which resulted in a

combined (SO2 and NOx) modeled visibility improvement of 78-81% (98th percentile visibility

impact) and a reduction of the number of days with a visibility impact greater than 0.5 dv from a 

range of 57-138 days to 3-14 days. During the course of negotiating an enforceable BART 

agreement, KCP&L proposed limits that were more restrictive than the presumptive BART 

limits. This proposal was made in order to be consistent with an agreement KCP&L has with the 

Sierra Club and with the knowledge that the Kansas City metro area has been close to 

nonattainment for ozone. The State agreed that the alternative emission limits proposed by

KCP&L were better than the presumptive BART limits and KDHE incorporated these limits into 

the KCP&L consent agreement. The agreement includes an emission rate of 0.13 lb/MMBtu on a 

30-day rolling weighted average using the already permitted SCR control for Unit 1 and some 

form of pre- or post-combustion control (e.g., low NOx burner, low NOx burner with overfire air, 

or SCR) for Unit 2. At the 0.13 lb/MMBtu weighted average rate for both units, which is beyond 

the presumptive NOx rate of 0.23 lb/MMBtu, EPA would not anticipate additional significant 

visibility improvement for the additional significant cost of installing SCR on Unit 2. 

Compliance will be demonstrated via reconfiguring the 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 the facility will meet the 0.10 lb/MMBtu presumptive limit for NOx at Unit 

1. Excluding the language on SSM in the Consent Agreement and in the State’s SIP (as 

discussed in the Federal Register notice) the EPA finds that the proposed control strategy meets 

or exceeds the presumptive limits established in the BART guidelines and sufficiently considers 

each of the five statutory factors. 

 

10 70 CFR 39135 column 2

11 70 CFR 31935 column 3

12 Technical Support Document for BART NOx Limits for Electric Generating Units and Technical Support 

Document for BART NOx Limits for Electric Generating Units Excel Spreadsheet, Memorandum to Docket OAR 

2002-0076, April 15, 2005
46

Reasonable Progress/Long Term Strategy

Since Kansas does not host a Class I area, it is not required to set Reasonable Progress 

Goals (RPGs). However, it is required to determine the emission reductions needed from 

sources within the State that are necessary to meet the RPGs of Class I areas hosted by other 

states. Kansas must provide the emission reduction strategy it will undertake to obtain those 

emissions in its Long Term Strategy (LTS). A six step process was used to identify which point 

sources needed to be controlled as part of the LTS. The results of each of these steps of the 

process will be described in sequence below. 

First, the State identified all point sources with emissions of greater than 500 tpy NOx

and/or SO2 by using the 2002 base year inventory (previously described in this TSD). The State 

chose 500 tpy as a screening criterion because it was determined by modeling (previously 

discussed in this TSD) that a source emitting less than 500 tpy of either pollutant would not 

significantly impact (great than 0.5 delta dv) Class I areas hosted by another State. Kansas 

identified a total of 30 NOx units and 28 SO2 units. Of this set of units, 8 NOx and 10 SO2 units 

were removed from further review for the following reasons:

 6 of the NOx units and 6 of the SO2 units were already identified as BART-subject;

 2 of the NOx units and 2 of the SO2 units had installed controls since 2002 and 

emitted less than 500 tpy of either pollutant.

 2 of the SO2 units were determined to have no commercially available controls.

The remaining set of 22 NOx units included 11 EGUs, 6 cement kilns, 2 gas compressor

engines, 1 refinery fluid-bed catalytic cracking unit (FCCU), 1 ammonia plant, and 1 glass 

furnace, all located at 15 separate facilities. The 18 SO2 units were comprised of 13 EGUs, 4 

cement kilns, and 1 refiner FCCU, all located at 12 facilities. A list of these sources is provided 

below in Table 37.

Source ID Facility Unit 2002 NOx 2002 SO2

ton/yr

0910057 AGC Flat Glass North America Glass furnace 1,375 [234.2] *

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]
47

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

* Values within brackets indicate 2002 emissions less than 500 tpy.

Table 37- Kansas Emission Units Not Subject to BART Emitting at Least 500 Tons/Yr of NOx or SO2 in 2002

During the second step, the State matched each of the remaining units with the emission 

control technology selected for it by a CENRAP contractor, Alpine Geophysics, utilizing the 

least marginal cost. For units that were not identified by Alpine Geophysics, the units were 

matched with control technologies, control efficiencies and control cost as determined by EPA’s 

AirControlNET version 4.113. Units whose cost of control was determined to be $10,000/ton 

reduced or greater were screened out in this step. It was agreed by members of CENRAP that 

$10,000/ton was an excessive cost of control. Eight SO2 emission units were removed from the 

list of candidate units, and are listed in Table 38, which shows each unit’s $/ton over 

$10,000/ton.

SO2 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

Table 38- Sources with Cost per Ton Reduced Greater than $10,000/ton

Calculations for fuel switching at Westar’s Hutchinson 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 Information Administration14. 

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 million 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 

 

13 “Final CENRAP Control Strategy Analysis Plan - 9 May 2006” page 36. 

http://www.cenrap.org/html/projects.php

14 http://www.eia.doe.gov/
48

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 prices. Negative cost results for 

both units (-$135/ton and -$37/ton, respectively) imply that the residual oil burned in 2002 was 

purchased at a lower price than the amount used for the analysis. Also, although fuel switching 

for these two units was selected as a control strategy for SO2, some control of NOx was achieved 

as well, and was included in the CALPUFF modeling in next step of the analysis.

Source ID Facility Unit

Selected 

control 

measure

Control 

efficiency 

(%)

Cost per ton 

reduced ($2002 

AirControlNET 

or $2005 Alpine)

Source

NOx 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 Alpine
49

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

SO2 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 Alpine

Table 39- Most Effective Control Technologies with Acceptable Control Costs for Kansas 500-Ton NOx and SO2

Emission Units

As part of the third step, the 22 NOx and 10 SO2 units within 17 facilities remaining were 

evaluated for visibility impacts at Class I areas. Essentially the same CALPUFF protocol was 

followed as for BART screening, so modeling was carried out on a facility-by-facility basis, and 
50

NOx and SO2 impacts were calculated together. Post-control model inputs for emissions were 

calculated using the control efficiencies included with each control technology selected in the 

second step of this analysis (previously described). Instead of looking at number of days with 

greater than 1.0 dv impact as was done for BART screening, in this analysis actual deciview 

values for each facility’s modeled impacts were pulled from the post-processing file and 

examined by the State. Pre- and post-control 98th percentile deciview values for the Class I area 

with greatest impact were recorded, and are presented in Table 40. Respective differences in 

deciview are labeled as visibility improvements and the Class I areas with greatest impact are 

shown.

Source 

ID Facility

Max. 98th 

percentile 

pre-control

Max. 98th 

percentile 

post-control

Visibility 

improvemen

t (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 Hercules-Glades

0150004 Frontier El Dorado 

Refinery 0.068 0.053 0.015 Wichita Mountains

1250015 Heartland Cement 0.069 0.053 0.016 Hercules-Glades

2090048 Kansas City BPU -

Quindaro 0.215 0.082 0.133 Hercules-Glades

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 -

Fredonia 0.111 0.105 0.006 Wichita 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 Hercules-Glades

1770033 Westar Energy -

Tecumseh 0.308 0.094 0.214 Hercules-Glades

Table 40- Overall Visibility Improvements Resulting from Application of Most Effective Controls at Selected 

Kansas 500-Ton NOx and SO2 Emission Units. Note that Kansas City BPU Nearman was not evaluated in this table 

because at the time the modeling was performed the Nearman facility was determined to be a BART source.
51

As a refinement to the modeling, the State re-ran CALPUFF for the remaining sources 

considering the impacts of NOx and SO2 separately. The State considered the pollutant 

emissions’ visibility impacts separately because potential controls for a facility, to meet 

reasonable progress goals in a Class I area hosted by another State, could be pollutant dependent.

Source 

ID Facility

Max. 98th 

percentile 

pre-control

Max. 98th

percentile 

post-control

Visibility 

improvement

Class I area 

impacted

Dv

NOx SO2 NOx SO2

1330001 Ash Grove Cement 0.110 0.090 0.024 Upper Buffalo

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 Mountains

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

Table 41- Selected Kansas 500-ton NOx and SO2 Emission Units Showing Significant Visibility Improvement 

Resulting from Application of Most Effective Controls

In the fourth step, the State calculated the cost per ton per unit of dv improvement 

($/ton/dv). The State estimated that the single value of $/ton/dv combined the cost and visibility

improvement in a way that its numerical value increases: 

a. as the cost of controls increases and 

b. as the visibility improvement decreases. 

The State determined that the facility with the lowest $/ton/dv would be the first to be 

reviewed for possible controls to meet reasonable progress goals in Class I areas hosted by other 

States. 
52

Source 

ID Facility Pollutant Emission unit(s)

Cost per 

ton1

Visibility 

improvement

Class I area 

(98th

percentile)

Cost per 

ton per dv

$2002 Dv $2002/tondv

1330001 Ash Grove Cement NOx

Cement 

kiln $509 0.024 Upper Buffalo $21,208

0210002 Empire District 

Electric - Riverton NOx

Units 7 

& 8 $9842

0.052 HerculesGlades $18,923

0210002 Empire District 

Electric - Riverton SO2 Unit 8 $5,326 0.112 HerculesGlades $47,554

2090048 Kansas City BPU -

Quindaro NOx

Units 1 

& 2 $660 0.041 HerculesGlades $16,098

2090048 Kansas City BPU -

Quindaro SO2

Units 1 

& 2 $4,045 0.073 HerculesGlades $55,411

2090008 Kansas City BPU -

Nearman NOx Unit 1 $7433

0.060 HerculesGlades $12,383

2090008 Kansas City BPU -

Nearman SO2 Unit 1 $2,0243

0.213 Caney Creek $9,502

2057022 Lafarge Midwest -

Fredonia NOx

Kilns 1 

& 2 $76 0.006 Wichita Mountains $12,667

0550023 Sunflower Electric 

- Holcomb NOx Unit 1 $1,383 0.016 Wind Cave $86,438

1730012 Westar Energy -

Gordon Evans SO2 Unit 1 ($37) 0.111 Wichita Mountains ($333)

1490001 Westar Energy -

Jeffrey NOx Unit 3 $1,437 0.114 Wichita Mountains $12,605

1490001 Westar Energy -

Jeffrey SO2 Unit 3 $1,695 0.705 Wichita Mountains $2,404

0450014 Westar Energy -

Lawrence NOx

Units 3, 

4, & 5 $989 0.099 HerculesGlades $9,990

0450014 Westar Energy -

Lawrence SO2

Units 3 

& 5 $7,791 0.118 HerculesGlades $66,025

1770030 Westar Energy -

Tecumseh NOx

Units 7 

& 8 $450 0.037 HerculesGlades $12,162

1770030 Westar Energy -

Tecumseh SO2

Units 7 

& 8 $3,699 0.149 HerculesGlades $24,826

Table 42- Summary of Each Unit’s cost per ton per Unit of dv Improvement

1 Alpine Geophysics reported costs in $2005, which have here been adjusted to 2002 dollars using a factor derived 

the ratio of Consumer Price Index average price data values for the two years, or 179.9/195.3 = 0.92115 (8)

2

 Empire submitted estimates of $2,427 (60% efficient) 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 engineering analysis report. Costs are in 2006 dollars.

As part of the fifth step, Kansas evaluated non-cost factors such as non-air environmental 

impacts, the remaining life of the unit and the compliance timeframe. Table 43 presents a 

summary of the factors for the sources remaining after cost and visibility impact was considered. 
53

Source 

ID Facility Pollutant Emission unit(s)

Selected 

control 

measure

Compliance

Timeframe

Non-air

quality

environmental

impacts

Remaining

useful life

NOx

1330001 Ash Grove 

Cement NOx

Cement 

kiln LNB

3-4 years 

following 

SIP approval

Potential 

permitting

issues, control 

device energy

requirements

10-30 

years

0210002

Empire 

District 

Electric -

Riverton

NOx Unit 7 LNBO

Potential 

permitting

issues, 

reduction in

electricity 

production

capacity

5-10 years

0210002

Empire 

District 

Electric -

Riverton

NOx Unit 8 LNC3

2090048

Kansas 

City BPU -

Quindaro

NOx Unit 1 NGR Potential 

permitting

issues, 

reduction in

electricity 

production

capacity

30-50 

years

2090048

Kansas

City BPU -

Quindaro

NOx Unit 2 LNB

2090008

Kansas 

City BPU -

Nearman

NOx Unit 1 LNB+OFA+NN 30-50 

years

2057022

Lafarge 

Midwest -

Fredonia

NOx

Kilns 1 & 

2

Mid-kiln firing

Control device 

energy

requirements

10-30 

years

0550023

Sunflower 

Electric -

Holcomb

NOx Unit 1 LNB

Potential 

permitting

issues, 

reduction in

electricity 

production

capacity

30-50 

years

1490001

Westar 

Energy -

Jeffrey

NOx Unit 3 LNC3

0450014

Westar 

Energy -

Lawrence

NOx

Units 3 & 

4

LNC1

1770030

Westar 

Energy -

Tecumseh

NOx Unit 7 LNC1

1770030

Westar 

Energy -

Tecumseh

NOx Unit 8 LNC3

SO2

0210002

Empire 

District 

Electric -

Riverton

SO2 Unit 8 FGD wet 

scrubber 3-4 years 

following 

SIP approval

Potential 

permitting & 

wastewater 

issues, 

reduction in

electricity 

production

capacity

5-10 years

2090048

Kansas 

City BPU -

Quindaro

SO2

Units 1 & 

2

FGD wet 

scrubber

30-50 

years
54

2090008

Kansas 

City BPU -

Nearman

SO2 Unit 1 Semi-Dry 

scrubber

3-4 years 

following 

SIP approval

Potential 

permitting

issues, 

reduction in

electricity 

production

capacity

1730012

Westar 

Energy -

Gordon 

Evans

SO2 Unit 1 Fuel switching Currently 

feasible —

1490001

Westar 

Energy -

Jeffrey

SO2 Unit 3 FGD wet 

scrubber

3-4 years 

following 

SIP approval

Potential 

permitting & 

wastewater 

issues, 

reduction in

electricity 

production

capacity

1770030

Westar 

Energy -

Tecumseh

SO2

Units 7 & 

8

FGD wet 

scrubber

Table 43- Summary of Reasonable Progress Non-Cost Statutory Factors for Selected Kansas Point Sources

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 merely indicated reduced (controlled) SO2

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 Jeffrey facility at Unit 3 due to environmental 

concerns for wastewater sulfur levels.

In the final step, the State ranked the remaining sources listing the sources from the 

previous step in increasing order of $/ton/dv and using $15,000/ton/dv as a max allowable cost. 

The final ranked list is given below in Table 44.

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 SO2 0.111 ($333)

2 1490001 Westar Energy –

Jeffrey Unit 3 SO2 0.705 $2,404

3 2090008 Kansas City BPU -

Nearman Unit 1 SO2 0.213 $9,502*

4 0450014 Westar Energy –

Lawrence

Units 3, 4, & 

5

NOx 0.099 $9,990

5 1770030 Westar Energy –

Tecumseh

Units 7/9 & 

8/10 NOx 0.037 $12,162

6 2090008 Kansas City BPU -

Nearman Unit 1 NOx 0.060 $12,383

7 1490001 Westar Energy –

Jeffrey Unit 3 NOx 0.114 $12,605
55

8 2057022 Lafarge Midwest –

Fredonia Kilns 1 & 2 NOx 0.006 $12,667

Table 44- Ranked List of Sources under the Reasonable Progress Analysis

*Cost is based on 2006 dollars at Caney Creek. Hercules-Glades cost is $11,244 again in 2006 dollars

The results of this process are described below. Kansas determined that controls or fuel 

switching on the sources listed below are reasonable and will result in significant visibility

improvements at the WIMO.

Facility/Unit Emission rate or work practice

Gordon Evans Energy Center-Unit 1

a fuel switch to natural gas at all times, with the 

exception of a gas curtailment order from the gas 

supplier, in which case the facility will be allowed to 

utilize backup # 6 fuel oil

Hutchinson -Unit 4

a fuel switch to natural gas at all times, with the 

exception of a gas curtailment order from the gas 

supplier, in which case the facility will be allowed to 

utilize backup # 6 fuel oil

Murray Gill- Units 1,2,3 and 4

a fuel switch to natural gas at all times, with the 

exception of a gas curtailment order from the gas 

supplier, in which case the facility will be allowed to 

utilize backup # 6 fuel oil

Neosho- Unit 7

a fuel switch to natural gas at all times, with the 

exception of a gas curtailment order from the gas 

supplier, in which case the facility will be allowed to 

utilize backup # 6 fuel oil

Jeffery Energy Center-Unit 3 an emission limit of 0.15 lbs/MMBtu for both SO2 and 

NOx

Lawrence -Unit3 an emission limit of 0.18 lbs/MMBtu for SO2

Lawrence- Unit 4 an emission limit of 0.18 lbs/MMBtu for SO2; an 

emission limit of 0.15 lbs/MMBtu for NOx

Lawrence -Unit 5 an emission limit of 0.15 lbs/MMBtu for both SO2 and 

NOx

Tecumseh-Unit 7/9 an emission limit of 0.18 lbs/MMBtu for SO2

Tecumseh-Units 8/10 an emission limit of 0.18 lbs/MMBtu for SO2

Table 45- Control or Work Practice Strategies for Westar Units to Meet Kansas Long Term Strategy Requirements

 Murray Gill, Hutchinson and Tecumseh Units- were added to the list due to their 

inclusion in a previous Consent Agreement Westar has with the Sierra Club. 
56

 BPU - Nearman Unit 1-this source primarily impacts the Class I areas in Missouri and 

Arkansas. Through Kansas’ consultation process with Missouri and Arkansas it was 

determined that no additional controls beyond expected BART and on the books 

controls would be needed to meet the Reasonable Progress Goals for the Class I areas 

in these states. However, with the vacatur of the Clean Air Interstate Rule (CAIR) 

and subsequent remanding of the case back to EPA without vacatur, Kansas suspects 

that it may be necessary to revisit this issue through the consultation process with 

Missouri and Arkansas. This discussion would occur once a final CAIR decision (or 

replacement rule) is finalized by the EPA and would be initiated by Missouri and/or 

Arkansas.

 Lafarge Midwest - Fredonia Kiln Unit 1 & 2- The facility and the State have concerns 

regarding design and lay-out constraints of some of the control technologies 

identified for this type of facility. The small level of improvement in visibility gained 

by control at this facility (0.006 dv for Wichita Mountains), in combination with the 

control system design concerns, led to the State to decide not to require controls at 

this time. Additional technical and cost evaluations will be conducted during the 

five-year progress review. 

Consent Agreements (given in Appendix 9.7 to the SIP) provide a mechanism to enforce

these determinations and sets the compliance schedules for these measures. The controls detailed 

above are expected to achieve approximately 10,409 tpy of NOx and 22,812 tpy of SO2

reductions.

Facility Unit

2002 NOx

Emissions 

(tpy)

2002 SO2

Emissions 

(tpy)

Post Control 

NOx (tpy)

Post Control 

SO2(tpy)

NOx 

Reductions 

(tpy)

SO2 

Reductions 

(tpy)

Gordon Evans 1 258.7 617.7 211.9 0.5 46.8 617.2

Hutchinson 4 267.1 734.3 158.5 0.6 108.5 733.7

Jeffrey 3 10,807.4 23,206.0 4,913.1 4,913.1 5,894.3 18,292.9

Lawrence 3 728.4 1,965.4 0.0 1,965.4 728.4 0.0

Lawrence 4 1,986.5 1,430.0 835.4 835.4 984.1 594.7

Lawrence 5 3,546.3 4546.3 2,564.7 2,564.7 981.6 1,789.0

Murray Gill 1 0.0 0.0 0.0 0.0 0.0 0.0

Murray Gill 2 4.5 0.0 4.0 0.0 0.5 0.0

Murray Gill 3 181.6 452.1 148.6 0.3 33.0 4,51.8

Murray Gill 4 103.8 333.3 85.2 0.2 18.7 333.1

Neosho 7 0.0 0.0 0.0 0.0 0.0 0.0

Tecumseh 7 1,530.6 2,692.7 691.6 2,692.7 839.0 0.0

Tecumseh 8 1,876.9 4,514.9 1,103.1 4,514.9 773.8 0.0

Total 10,408.7 22,812.4

Table 46- Estimated NOx and SO2 Emission Reductions for Implementation of Controls or Work Practices Required 

by Kansas’ Long Term Strategy