1 Draft Technical Support Document

Missouri Area Designations for the 2010 SO 2 Primary National Ambient Air Quality Standard

Summary

Pursuant to section 107(d) of the Clean Air Act (CA A), the U.S. Environmental Protection Agency (EPA, or the Agency) must designate areas as either “unclassifiable,” “attainment,” or
“nonattainment” for the 2010 one-hour sulfur dioxid e (SO 2 ) primary national ambient air quality standard (NAAQS). The CAA defines a nonattainment a rea as one that does not meet the NAAQS or that contributes to a violation in a nearb y area. An attainment area is defined as any
area other than a nonattainment area that meets the NAAQS. Unclassifiable areas are defined as
those that cannot be classified on the basis of ava ilable information as meeting or not meeting the NAAQS.

July 2, 2016, is the deadline for the EPA to design ate certain areas established by the U.S.
District Court for the Northern District of Califor nia. This deadline is the first of three deadlines established by the court for the EPA to complete ar ea designations for the 2010 SO 2 NAAQS. This deadline applies to certain areas in Missouri because three emission sources meet the
conditions of the court’s order.

Missouri submitted updated recommendations on Septe mber 25, 2015. Table 1 below lists
Missouri’s recommendations and identifies the count ies or portions of counties in Missouri that the EPA intends to designate by July 2, 2016, based on an assessment and characterization of air quality through ambient air quality data, air dispe rsion modeling, other evidence and supporting information, or a combination of the above.

Table 1: Missouri’s Recommended and the EPA’s Inten ded Designations

Area Missouri’s

Recommended
Area Definition Missouri’s

Recommended Designation EPA’s Intended

Area Definition EPA’s

Intended Designation
Franklin County,
Missouri No

recommendation Unclassifiable The eastern and

western boundaries are
Boone and Boles Township
boundaries in St.
Charles and
Franklin Counties respectively. The northern boundary
is Missouri Route D and Highway 94
in St. Charles. The Nonattainment2 southern boundary
is Interstate 44 in
Franklin. Jackson County,
Missouri Within Jackson

County: The northern boundary is the county line separating Jackson County from Clay and Ray Counties. The Eastern boundary is the county line separating Jackson County from Lafayette County. The
Southern boundary is
Interstate 70 and
470. The Western boundary is Missouri Highway
291. Attainment Same as
Missouri’s
Recommendation Unclassifiable

Scott County,
Missouri Scott County Attainment Same as
Missouri’s
Recommendation Unclassifiable/

Attainment

Background

On June 3, 2010, the EPA revised the primary (healt h based) SO 2 NAAQS by establishing a new 1-hour standard at a level of 75 parts per billion (ppb) which is attained when the three-year average of the 99 th percentile of 1-hour daily maximum concentrations does not exceed 75 ppb. This NAAQS was published in the Federal Register on June 22, 2010 (75 FR 35520) and is
codified at 40 CFR 50.17. The EPA determined this i s the level necessary to protect public health with an adequate margin of safety, especially for c hildren, the elderly and those with asthma. These groups are particularly susceptible to the he alth effects associated with breathing SO 2 . The two prior primary standards of 140 ppb evaluated ov er 24 hours, and 30 ppb evaluated over an entire year, codified at 40 CFR 50.4, remain applic able. 1 However, the EPA is not currently designating areas on the basis of either of these t wo primary standards. Similarly, the secondary

1 40 CFR 50.4(e) provides that the two prior primary NAAQS will no longer apply to an area one year aft er its designation under the 2010 NAAQS, except that for a reas designated nonattainment under the prior NAAQS as of August 22, 2010, and areas not meeting the requirem ents of a SIP Call under the prior NAAQS, the prior NAAQS will apply until that area submits and EPA approves a SIP providing for attainment of the 2010 NAAQS. No areas in Missouri were designated nonattainment for the prio r NAAQS as of August 22, 2010.3

standard for SO 2, set at 500 ppb evaluated over 3 hours has not been revised, and the EPA is also not currently designating areas on the basis of the secondary standard.

General Approach and Schedule

Section 107(d) of the Clean Air Act requires that n ot later than 1 year after promulgation of a new or revised NAAQS, state governors must submit t heir recommendations for designations and boundaries to EPA. Section 107(d) also requires the EPA to provide notification to states no less than 120 days prior to promulgating an initial area designation that is a modification of a
state’s recommendation. If a state does not submit designation recommendations, the EPA may promulgate the designations that it deems appropria te without prior notification to the state, although it is our intention to provide such notifi cation when possible. If a state or tribe disagrees with the EPA’s intended designations, they are give n an opportunity within the 120 day period to demonstrate why any proposed modification is inappr opriate. The EPA is required to complete designations within 2 years after promulgation of a new or revised NAAQS, unless we determine that sufficient information is not available, in wh ich case the deadline is extended to 3 years. The 3-year deadline for the revised SO 2 NAAQS was June 2, 2013.

On August 5, 2013, the EPA published a final rule e stablishing air quality designations for 29
areas in the United States for the 2010 SO 2 NAAQS, based on recorded air quality monitoring data from 2009 - 2011 showing violations of the NAA QS (78 FR 47191). In that rulemaking, the EPA committed to address, in separate future action s, the designations for all other areas for which the Agency was not yet prepared to issue desi gnations. The EPA designated portions of Jefferson County and Jackson County, Missouri, as n onattainment in this set of designations.

Following the initial August 5, 2013 designations, three lawsuits were filed against the EPA in different U.S. District Courts, alleging the Agency had failed to perform a nondiscretionary duty under the CAA by not designating all portions of th e country by the June 2, 2013 deadline. In an effort intended to resolve the litigation in one of those cases, plaintiffs Sierra Club and the
Natural Resources Defense Council and the EPA filed a proposed consent decree with the U.S.
District Court for the Northern District of Califor nia. On March 2, 2015, the court entered the
consent decree and issued an enforceable order for the EPA to complete the area designations according to the court-ordered schedule.

According to the court-ordered schedule, the EPA mu st complete the remaining designations by three specific deadlines. By no later than July 2, 2016 (16 months from the court’s order), the EPA must designate two groups of areas: (1) areas t hat have newly monitored violations of the
2010 SO 2 NAAQS and (2) areas that contain any stationary sou rces that had not been announced as of March 2, 2015 for retirement and that accordi ng to the EPA’s Air Markets Database emitted in 2012 either (i) more than 16,000 tons of SO 2 or (ii) more than 2,600 tons of SO 2 with an annual average emission rate of at least 0.45 po unds of SO 2 per one million British thermal units (lbs SO 2 /mmBTU). Specifically, a stationary source with a c oal-fired unit that as of January 1, 2010 had a capacity of over 5 megawatts and othe rwise meets the emissions criteria, is excluded from the July 2, 2016 deadline if it had a nnounced through a company public announcement, public utilities commission filing, c onsent decree, public legal settlement, final4

state or federal permit filing, or other similar me ans of communication, by March 2, 2015, that it will cease burning coal at that unit.

The last two deadlines for completing remaining des ignations are December 31, 2017, and December 31, 2020. The EPA has separately promulgat ed requirements for state and other air agencies to provide additional monitoring or modeli ng information on a timetable consistent with these designation deadlines. We expect this informa tion to become available in time to help inform these subsequent designations. These require ments were promulgated on August 21, 2015 (80 FR 51052), in a rule known as the SO 2 Data Requirements Rule (DRR).

Updated designations guidance was issued by the EPA through a March 20, 2015 memorandum from Stephen D. Page, Director, U.S. EPA, Office of Air Quality Planning and Standards, to Air Division Directors, U.S. EPA Regions 1-10. This mem orandum supersedes earlier designation guidance for the 2010 SO 2 NAAQS, issued on March 24, 2011, and it identifies factors that the EPA intends to evaluate in determining whether area s are in violation of the 2010 SO 2 NAAQS. The guidance also contains the factors the EPA inte nds to evaluate in determining the boundaries for all remaining areas in the country, consistent with the court’s order and schedule. These factors include: 1) Air quality characterization vi a ambient monitoring or dispersion modeling results; 2) Emissions-related data; 3) Meteorology; 4) Geography and topography; and 5) Jurisdictional boundaries. This guidance was supple mented by two technical assistance
documents intended to assist states and other inter ested parties in their efforts to characterize air quality through air dispersion modeling or ambient air quality monitoring for sources that emit
SO 2 . Notably, the EPA released its most recent version s of documents titled, “SO 2 NAAQS Designations Modeling Technical Assistance Document ” (Modeling TAD) and “SO 2 NAAQS Designations Source-Oriented Monitoring Technical A ssistance Document” (Monitoring TAD)
in December 2013.

Based on ambient air quality data collected between 2012 and 2014, no violations of the 2010
SO 2 NAAQS have been recorded in any undesignated part of the state. 2 However, there are three sources in the state meeting the emissions criteria of the consent decree for which the EPA must complete designations by July 2, 2016. In this draf t technical support document, the EPA discusses its review and technical analysis of Miss ouri’s updated recommendations for the areas that we must designate. The EPA also discusses any intended modifications from the state’s
recommendation based on all available data before u s.

The following are definitions of important terms us ed in this document:

2 For designations based on ambient air quality moni toring data that violates the 2010 SO 2 NAAQS, the consent
decree directs the EPA to evaluate data collected b etween 2013 and 2015. Absent complete, quality assu red and certified data for 2015, the analyses of applicable areas for the EPA’s intended designations will be informed by data
collected between 2012 and 2014. States with monito rs that have recorded a violation of the 2010 SO 2 NAAQS during these years have the option of submitting co mplete, quality assured and certified data for cale ndar year 2015 by April 19, 2016 to the EPA for evaluation. If aft er our review, the ambient air quality data for the area indicates that no violation of the NAAQS occurred between 201 3 and 2015, the consent decree does not obligate th e EPA to complete the designation. Instead, we may designate the area and all other previously undesignated are as in the state on a schedule consistent with the prescribed timing of the court order, i.e., by December 31, 2017, or December 31,
2020.5

1) 2010 SO 2 NAAQS – The primary NAAQS for SO 2 promulgated in 2010. This NAAQS is 75 ppb, based on the 3-year average of the 99th per centile of the annual distribution of daily maximum 1-hour average concentrations. See 40 CFR 50.17. 2) Design Value – a statistic computed according to th e data handling procedures of the NAAQS (in 40 CFR part 50 Appendix T) that, by compa rison to the level of the NAAQS, indicates whether the area is violating the NAAQS. 3) Designated nonattainment area – an area which the E PA has determined has violated the
2010 SO 2 NAAQS or contributed to a violation in a nearby ar ea. A nonattainment designation reflects considerations of state recomm endations and all of the information
discussed in this document. The EPA’s decision is b ased on all available information including the most recent 3 years of air quality mo nitoring data, available modeling analysis, and any other relevant information. 4) Designated unclassifiable area – an area which the EPA cannot determine based on all
available information whether or not it meets the 2 010 SO 2 NAAQS. 5) Designated unclassifiable/attainment area – an area which the EPA has determined to
have sufficient evidence to find either is attainin g or is likely to be attaining the NAAQS.
The EPA’s decision is based on all available inform ation including the most recent 3 years of air quality monitoring data, available mod eling analysis, and any other relevant
information. 6) Modeled violation – a violation based on air disper sion modeling. 7) Recommended attainment area – an area a state or tr ibe has recommended that the EPA designate as attainment. 8) Recommended nonattainment area – an area a state or tribe has recommended that the EPA designate as nonattainment. 9) Recommended unclassifiable area – an area a state o r tribe has recommended that the EPA designate as unclassifiable. 10) Recommended unclassifiable/attainment area – an are a a state or tribe has recommended that the EPA designate as unclassifiable/attainment

. 11) Violating monitor – an ambient air monitor meeting all methods, quality assurance and siting criteria and requirements whose valid design value exceeds 75 ppb, based on data analysis conducted in accordance with Appendix T of 40 CFR part 50.6 Technical Analysis for the Franklin County, Missour i Area

Proposed Designation Summary

After careful evaluation of the state’s recommendat ion and supporting information, as well as all available relevant information, the EPA intends to designate the area around Ameren Labadie Energy Center as nonattainment for the 2010 SO 2 NAAQS. Specifically, the proposed
boundaries are:

The eastern and western boundaries are Boone and Bo les Township boundaries in St. Charles and Franklin Counties respectively. The nor thern boundary is Missouri Route D and Highway 94 in St. Charles. The southern boundar y is Interstate 44 in Franklin County.

This nonattainment designation is based on an analy sis of modeling provided by the State of Missouri, an analysis of Sierra Club’s modeling, an d an analysis of Ameren’s modeling using regulatory defaults.

Introduction

The Franklin County area contains a stationary sour ce that according to the EPA’s Air Markets Database emitted in 2012 either more than 16,000 to ns of SO 2 or more than 2,600 tons of SO 2 and had an annual average emission rate of at least 0.45 pounds of SO 2 per one million British thermal units (lbs SO 2 /mmBTU). Specifically, in 2012, the Ameren Labadie Energy Center emitted 42,236 tons of SO 2 and had a facility-wide emissions rate of 0.571 lbs SO 2 /mmBTU. As of March 2, 2015, this stationary source had not me t the specific requirements for being
“announced for retirement.” Pursuant to the March 2 , 2015, court-ordered schedule, the EPA must designate the area surrounding the facility by July 2, 2016.

In its submission, Missouri recommended that the ar ea surrounding the Ameren Labadie Energy Center (Labadie) be designated as unclassifiable ba sed on varying modeling results from their own modeling, Ameren’s modeling, and Sierra Club’s modeling. MDNR’s assessment included characterization of air quality from the facility a nd other nearby sources which may have a potential impact in the area of analysis where maxi mum concentrations of SO 2 are expected along with an evaluation of historic and recent mon itoring around the facility. This modeling assessment and characterization was performed using air dispersion modeling software, specifically AERMOD, analyzing actual emissions. Af ter careful review of the state’s assessment, supporting documentation, and all avail able data, the EPA does not agree with the
state’s recommendation for the area and intends to designate the area as nonattainment.

The Ameren Labadie Energy Center is located in the eastern portion of Missouri in the northern portion of Franklin County. As seen in Figure 1 bel ow, the facility is located approximately 50 km west of downtown St. Louis, Missouri. EPA intend s to designate the area around Labadie Energy Center as nonattainment with the nonattainme nt area based on an initial proposed boundary from MDNR as seen in Figure 2. As seen in Figure 1, the Labadie Energy Center is located along the Missouri River, in the river bott om, with terrain features both to the north and7

south of the river bottom. Labadie sits at an elevation of approximately 475 feet, with surrounding hills at around 800 feet elevation approximately 3-4 km away. Also included in Figure 2 are nearby emitters of SO 2 , along with the state’s recommended area boundary for the proposed nonattainment designation in MDNR’s “Proposed Options for Area Boundary Recommendations” document, which was provided to EPA, that supported MDNR’s August 27, 2015, public hearing, and the EPA’s intended nonattainment designation for the area.

Figure 1: Labadie Energy Center location.8

Figure 2: The EPA’s intended designation for portio n of Franklin County and St. Charles County, Missouri

The discussion and analysis that follows below refe rences the state’s use of the Modeling TAD, the EPA’s assessment of the state’s modeling in acc ordance with the Modeling TAD, and the
factors for evaluation contained in the EPA’s March 20, 2015 guidance, as appropriate.

Detailed Assessment

Model Selection and Modeling Components9

The EPA’s Modeling TAD notes that for area designat ions under the 2010 SO 2 NAAQS, the AERMOD modeling system should be used, unless use o f an alternative model can be justified. In some instances the recommended model may be a mo del other than AERMOD, such as the BLP model for buoyant line sources. The AERMOD mode ling system contains the following
components:

- AERMOD: the dispersion model

- AERMAP: the terrain processor for AERMOD

- AERMET: the meteorological data processor for AERMO D

- BPIPPRIME: the building input processor

- AERMINUTE: a pre-processor to AERMET incorporating 1-minute automated surface observation system (ASOS) wind data

- AERSURFACE: the surface characteristics processor f or AERMET

- AERSCREEN: a screening version of AERMOD

The state used AERMOD version 14134, the most recen t AERMOD version at the time their analysis was performed, and a discussion of the ind ividual components will be referenced in the corresponding discussion that follows as appropriat e.

Modeling Parameter: Rural or Urban Dispersion

The EPA’s recommended procedure for characterizing an area by prevalent land use is based on evaluating the dispersion environment within 3 km o f the facility. According to the EPA’s modeling guidelines, rural dispersion coefficients are to be used in the dispersion modeling analysis if more than 50 percent of the area within a 3 km radius of the facility is classified as rural. Conversely, if more than 50 percent of the a rea is urban, urban dispersion coefficients should be used in the modeling analysis. When perfo rming the modeling for the area of analysis, the state determined that it was most appropriate t o run the model in rural mode. This determination was made by analyzing the land use su rrounding the area around Labadie which is predominately rural.

Modeling Parameter: Area of Analysis (Receptor Grid )

The EPA believes that a reasonable first step towar ds characterization of air quality in the area surrounding the Labadie Energy Center is to determi ne the extent of the area of analysis, i.e., the receptor grid. Considerations presented in the Mode ling TAD include but are not limited to: the
location of the SO 2 emission sources or facilities considered for mode ling; the extent of significant concentration gradients of nearby sourc es; and sufficient receptor coverage and density to adequately capture and resolve the model predicted maximum SO 2 concentrations.

The grid receptor spacing for the area of analysis chosen by the state is as follows:

- Origin to 1 km, 100 m spacing

- 1 km to 3.5 km, 250 m spacing

- 3.5 km to 10 km, 500 m spacing

- 10 km to 20 km, 1000 m spacing Where the origin was defined at the center of the f acility property.10

The receptor network contained 5,628 receptors and covered the northern portion of Franklin County in Missouri, the eastern portion of Warren C ounty in Missouri, the western portion of St. Louis County in Missouri, and the southern portion of St. Charles County in Missouri.

Figure 3, which was included in the state’s recomme ndation, shows the state’s chosen area of analysis surrounding the Labadie Energy Center, as well as a receptor grid for the area of analysis. Consistent with the Modeling TAD, recepto rs for the purposes of this designation effort were placed only in areas where it would also be fe asible to place a monitor and record ambient impacts. The impacts of the area’s geography and to pography will be discussed later within this
document.

For the Labadie area, the state analyzed six other SO 2 sources in the area and included two of the
six other SO 2 sources that are within 20 kilometers (km) of Laba die Energy Center in any direction. These six sources represent all the perm itted SO 2 sources within the 20 km radius. The state offered no further analysis for sources beyon d the 20 km radius. EPA does note that the Ameren Missouri Meramec Energy Center is the neares t DRR source and resides approximately 47 km to the southeast of the Labadie Energy Center . No other DRR sources are within 50 km of Labadie. The state determined that 20 km was the ap propriate distance in order to adequately characterize air quality from the facility and othe r nearby sources which may have a potential impact in the area of analysis where maximum concen trations of SO 2 are expected. In addition to the Labadie Energy Center, the other emitters of SO 2 included in the modeling analysis are: N.B West Contracting Company Inc. Pacific Plant and Pur ina Animal Nutrition Center. The four permitted sources omitted in the modeling within th e 20 km radius emitted less than 0.2 tons/yr respectively and are expected to be represented in the background value.11

Figure 3: Receptor Grid for the Labadie Energy Center Area of Analysis

Modeling Parameter: Source Characterization

The state characterized the sources within the area of analysis in accordance with the best practices outlined in the Modeling TAD. Specifically, the state used actual stack heights in conjunction with actual emissions for Labadie. The state also adequately characterized Labadie’s building layout and location, as well as the stack parameters, e.g., exit temperature, exit velocity, location, and diameter. Where appropriate, the AERMOD component BPIPPRIME was used to assist in addressing building downwash.

Modeling Parameter: Emissions

The EPA’s Modeling TAD notes that for the purposes of modeling to characterize air quality for use in designations, the recommended approach is to use the most recent 3 years of actual emissions data and concurrent meteorological data. However, the TAD does provide for the12

flexibility of using allowable emissions in the for m of the most recently permitted (referred to as PTE or allowable) emissions rate.

The EPA believes that continuous emissions monitori ng systems (CEMS) data provide acceptable historical emissions information when it is available and that these data are available for many electric generating units. In the absence of CEMS data, the EPA’s Modeling TAD highly encourages the use of AERMOD’s hourly varyin g emissions keyword HOUREMIS or through the use of AERMOD’s variable emissions fact ors keyword EMISFACT. When choosing one of these methods, the EPA believes that detaile d throughput, operating schedules, and emissions information from the impacted source(s) s hould be used.

In certain instances, states and other interested p arties may find that it is more advantageous or simpler to use PTE rates as part of their modeling runs. Specifically, a facility may have recently adopted a new federally enforceable emissions limit , been subject to a federally enforceable consent decree, or implemented other federally enfo rceable mechanisms and control technologies to limit SO 2 emissions to a level that indicates compliance wit h the NAAQS. These new limits or conditions may be used in the applica tion of AERMOD. In these cases, the Modeling TAD notes that the existing SO 2 emissions inventories used for permitting or SIP planning demonstrations should contain the necessar y emissions information for designationsrelated modeling. In the event that these short-ter m emissions are not readily available, they may be calculated using the methodology in Table 8-1 of Appendix W to 40 CFR Part 51 titled, “Guideline on Air Quality Models.”

As previously noted, the state included Labadie Ene rgy Center and two other emitters of SO 2 within 20 km in the area of analysis. This distance and these facilities were selected because the state believes that this area of analysis adequatel y represents the area where maximum
concentrations of SO 2 are expected and adequately includes the sources w hich might contribute to those concentrations. No other sources beyond 20 km were determined by the state to have the potential to cause significant concentration gradie nt impacts within the area of analysis. EPA does note the Ameren Missouri Meramec Energy Center , a DRR source, is 47 km to the southeast of Labadie Energy Center. The facilities in the area of analysis and their associated
annual actual SO 2 emissions between 2012 and 2014 are summarized in Table 2 below.

Table 2: Actual SO 2 Emissions Between 2012 and 2014 from Facilities in the Labadie, Missouri Area of Analysis

Facility Name SO 2 Emissions (tons per year)

2012 2013 2014 Ameren Labadie Energy Center 42,236 38,384 33,091

Purina Animal Nutrition
Center 1.43 1.43 1.43 N.B. West Contracting Co
Inc. 3.58 3.58 5.43
Total Emissions 42,241 38,389 33,09813

For the Ameren Labadie Energy Center in the area of analysis, the state used actual emissions from the most recent 3-year data set, i.e., 2012 – 2014. These emissions data were obtained from
CEMS for Labadie. The other two sources did not hav e CEMS and those facilities’ hourly emissions data were derived from operational parame ters in the MDNR emission inventory system. It is noted that these sources emit at much lower rates than Labadie Energy center and have minor impacts in the modeling performed.

Modeling Parameter: Meteorology and Surface Charact eristics

The most recent 3 years of meteorological data (con current with the most recent 3 years of emissions data) should be used in designations effo rts. As noted in the Modeling TAD, the selection of data should be based on spatial and cl imatological (temporal) representativeness. The representativeness of the data are based on: 1) the proximity of the meteorological monitoring site to the area under consideration, 2) the complexity of terrain, 3) the exposure of the meteorological site, and 4) the period of time during which data are collected. Sources of meteorological data include National Weather Servic e (NWS) stations, site-specific or onsite data, and other sources such as universities, Feder al Aviation Administration (FAA), and military stations.

For the Labadie area of analysis, surface meteorolo gy from the Jefferson City NWS station in Callaway, Missouri, 117 km to the west, and coincid ent upper air observations from the NWS station in Lincoln, Illinois, 220 km to the northea st, were selected by MDNR as the best representation of meteorological conditions within the area of analysis.

The state used AERSURFACE version 13016 using data from the NWS station in Jefferson City, Missouri located at latitude 38.597N and longitude 92.162W to estimate the surface characteristics of the area of analysis. For surfac e roughness (sometimes referred to as “Zo”) the state estimated values for 12 spatial sectors out t o 1 km at a monthly temporal resolution for dry, wet, or average conditions for each respective year . The state also used a 10 km by 10 km area
centered on the site and estimated values for albed o (the fraction of solar energy reflected from the earth back into space), the Bowen ratio (the me thod generally used to calculate heat lost or heat gained in a substance). In Figure 4 below, the location of the Jefferson City, Missouri, NWS
surface station is shown relative to the Labadie En ergy Center area of analysis along with the Lincoln, Illinois, NWS upper air station.14

Figure 4: Labadie Area of Analysis and the Jefferson City, Missouri and Lincoln, Illinois,
NWS sites

As part of its recommendation, the state provided the 3-year surface wind rose for Jefferson City. In Figure 5, the frequency and magnitude of wind speed and direction are defined in terms of from where the wind is blowing. Surface winds generally follow the river valley in Jefferson City and are predominately from the southeast and northwest.15

Figure 5: Jefferson City Cumulative Annual Wind Ros e for Years 2012 – 2014

Meteorological data from the above surface and uppe r air stations were used in generating AERMOD-ready files with the AERMET processor. The o utput meteorological data created by the AERMET processor is suitable for being applied with AERMOD input files for AERMOD modeling runs. The state followed the methodology a nd settings presented in their protocol to process the raw meteorological data into an AERMOD- ready format and used AERSURFACE to best represent surface characteristics.

Hourly surface meteorological data records are read by AERMET and include all the necessary elements for data processing. However, wind data ta ken at hourly intervals may not always portray wind conditions for the entire hour, which can be variable in nature. Hourly wind data may also be overly prone to indicate calm condition s, which are not modeled by AERMOD. In order to better represent actual wind conditions at the meteorological tower, wind data of one minute duration was provided from the same instrume nt tower but in a different formatted file to be processed by a separate preprocessor, AERMINUTE. These data were subsequently integrated into the AERMET processing to produce fi nal hourly wind records of AERMODready meteorological data that better estimate actu al hourly average conditions and that are less prone to over-report calm wind conditions. This all ows AERMOD to apply more hours of meteorology to modeled inputs, and therefore produc e a more complete set of concentration estimates. As a guard against excessively high conc entrations that could be produced by16

AERMOD in very light wind conditions, the state set a minimum threshold of 0.5 meters per second in processing meteorological data for use in AERMOD. This approach is consistent with a March 8, 2013, EPA memo titled, “Use of ASOS mete orological data in AERMOD dispersion Modeling.” In setting this threshold, no wind speed s lower than this value would be used for determining concentrations. This threshold was spec ifically applied to the one minute wind data.

Modeling Parameter: Geography and Terrain

The terrain in the area of analysis is best describ ed as gently rolling with a 300-400 feet elevation

difference between the Missouri river bottom and hi lls beyond the river bottom. To account for these terrain changes, the AERMAP terrain program w ithin AERMOD was used to specify terrain elevations for all the receptors. The sourc e of the elevation data incorporated into the

model is from the USGS National Elevation Database.

Modeling Parameter: Background Concentrations of SO 2

The Modeling TAD offers two mechanisms for characte rizing background concentrations of SO 2 that are ultimately added to the modeled design val ues: 1) a “first tier” approach, based on monitored design values, or 2) a temporally varying approach, based on the 99 th percentile monitored concentrations by hour of day and season or month. For the Labadie area of analysis, the state chose a constant design value from a near by monitor in East St. Louis that excluded wind direction sectors impacted by sources explicit ly included in the modeling analysis, which is consistent with the “first tier” approach. The back ground concentration for this area of analysis was determined by the state to be 23.6 micrograms p er cubic meter ( μ g/m 3 ), or 9 ppb, 3 and that value was incorporated into the final AERMOD result s.

Summary of Modeling Results

The AERMOD modeling parameters for the Labadie area of analysis are summarized below in

Table 3.

Table 3: AERMOD Modeling Parameters for the Labadie Area of Analysis Labadie Area of Analysis

AERMOD Version 14134 Dispersion Characteristics Rural

Modeled Sources 3

Modeled Stacks 9

Modeled Structures 13

Modeled Fencelines 1 Total receptors 5628

3 The conversion factor for SO 2 (at the standard conditions applied in the ambient SO 2 reference method) is 1ppb = approximately 2.62 μ g/m 3

.17 Emissions Type Actual CEMS for Labadie, hourly estimates based on
actual annual emissions for
two other sources

Emissions Years 2012-2014 Meteorology Years 2012-2014 Surface Meteorology Station Jefferson City, Missour i Upper Air Meteorology Station Lincoln, Illinois Methodology for Calculating Background SO 2 Concentration Design Value excluding specific sectors Calculated Background SO 2 Concentration 9 ppb or 23.6 μ g/m 3

The results presented below in Table 4 show the mag nitude and geographic location of the highest predicted modeled concentration based on ac tual CEMS emissions and hourly estimates

based on actual annual emissions.

Table 4: Maximum Predicted 99th Percentile 1-Hour S O 2 Concentration in the Labadie Area of Analysis Based on Actual Emissions

Averaging
Period Data Period Receptor Location SO 2 Concentration ( μ g/m 3 )

UTM/Latitude UTM/Longitude Modeled (including background) NAAQS
99th Percentile 1-Hour Average 2012-2014 686096.4 4272076 234.5 196 .5* *Equivalent to the 2010 SO 2 NAAQS set at 75 ppb

The modeling conducted and provided by the state in dicates that the predicted 99 th percentile 1- hour average concentration within the chosen modeli ng domain is 234.5 μ g/m 3 , or 89 ppb. This

modeled concentration included the background concentration of SO 2 and is based on actual emissions from the facilities. Figure 6 below was i ncluded as part of the state’s recommendation and indicates that the predicted value occurred nor thwest of the facility. The state’s receptor grid is also shown in the figure.18

Figure 6: Maximum Predicted 99 th Percentile 1-Hour SO 2 Concentrations in the Labadie Area of Analysis Based on Actual Emissions19

Jurisdictional Boundaries:

Once the geographic area of analysis associated wit h the Labadie Energy Center, other nearby sources, and background concentration is determined , existing jurisdictional boundaries are considered for the purpose of informing our intende d nonattainment area, specifically with respect to clearly defined legal boundaries.

Based on the analysis in the initial MDNR proposed nonattainment area boundary, EPA proposes to determine that the area defined as follows repre sents an area that contains the modeled nonattainment receptors using actual emissions and the source causing these modeled violations, namely the Labadie Energy Center:

The eastern and western boundaries are Boone and Bo les Township boundaries in St. Charles and Franklin Counties respectively. The nor thern boundary is Missouri Route D and Highway 94 in St. Charles. The southern boundar y is Interstate 44 in Franklin.

The EPA believes that our intended nonattainment ar ea, consisting of portions of Franklin and St. Charles counties in Missouri, is comprised of c learly defined legal boundaries and we find these boundaries to be a suitably clear basis for d efining our intended nonattainment area. The three sources included in the modeling analysis are also contained within the proposed EPA boundary. The four permitted sources omitted in the modeling within the 20 km radius emitted less than 0.2 tons/yr respectively and are expected to be represented in the background value and are not expected to significantly contribute to mod eled violations.

Other Relevant Information

The EPA has received six additional sets of modelin g files for the Labadie Energy Center. Two were from the Sierra Club. One Sierra Club modeling analysis used allowable emission rates and
one used actual emissions. EPA also received four a dditional modeling runs from Ameren that were conducted by Ameren’s consultant, all using ac tual emissions but with varying meteorological and modeling options. These addition al modeling runs are briefly described below with additional discussion of EPA’s interpret ation of these runs and how this information factored into our designation decision.

The Sierra Club submitted a modeling demonstration evaluating compliance with the 1-hour SO 2 NAAQS for the Labadie Energy Center as part of a Se ptember 17, 2015, submittal to the EPA.

Several documents were enclosed with the Sierra Clu b modeling files. One of those documents was an evaluation document describing the modeling Sierra Club provided, prepared by Wingra Engineering. Sierra Club also provided several Wash ington University School of Law comment letters addressed to both MDNR and EPA, including a September 18, 2015, supplemental letter addressed to EPA Region 7, that addressed Ameren’s modeling presented during the MDNR public hearing. The Sierra Club provided the modeli ng files for this modeling analysis of Labadie Energy Center and also provided comments de scribing their evaluation of Ameren’s modeling.

EPA reviewed but is not considering the modeling su bmitted by Sierra Club that relied upon allowable emissions, as the EPA modeling TAD allows designations to be made using actual20

emissions, and a full and accurate assessment of th e area’s status can be made based on the actual emissions-based modeling in this case. There fore, no further discussion of the Sierra Club’s allowable emissions modeling will be provide d.

EPA reviewed the Sierra Club modeling analysis that used actual emissions and we find that this modeling analysis meets the EPA modeling TAD guidan ce and Appendix W. This Sierra Club modeling analysis used the current regulatory model s at the time of their submittal and was similar to what MDNR provided to EPA as described a bove. Notable differences between the Sierra Club modeling and MDNR modeling include a di fferent surface meteorology site, no building downwash, and flagpole receptors at 1.5 me ter height. The Sierra Club indicated they believe the Spirit of St. Louis NWS surface site is appropriate because of its proximity to Labadie and the surface characteristics at the Spir it of St. Louis NWS surface site are similar to

the Labadie site.

The Sierra Club modeling, using actual CEMS emissio ns, indicates magnitudes of impact that are comparable to the MDNR modeling. The Sierra Clu b’s modeling indicates a 235.7 μ g/ m 3 99 th percentile impact, which included a 23.5 μ g/ m 3 background value. This impact is almost identical to the MDNR modeling impact of 234.5 μ g/ m 3 . Because the Sierra Club used a different meteorological dataset, the location of p eak impacts differed from that of the MDNR modeling. The Sierra Club’s modeled maximum impacts were to the south and west of the Labadie Energy Center, while the MDNR’s modeled max imum impacts were to the northwest of the plant. Overall, EPA believes the Sierra Club mo deling supports and complements the MDNR modeling analysis, with the overall conclusion supp orting a nonattainment recommendation. As seen in Figure 7 all modeled violating receptors in both the MDNR and Sierra Club modeling using actual emissions are contained within the pro posed nonattainment boundary. However, EPA does not find compelling evidence that the Sier ra Club modeling is more representative than the MDNR modeling or vice versa.21

Figure 7: Proposed nonattainment area (shaded) and modeled violating receptors (MDNR – red receptors, Sierra Club – green receptors, Ame ren using two meteorological datasets – blue receptors)

MDNR also included modeling that Ameren provided as part of the MDNR public comment process in Appendix G of Missouri’s designation rec ommendation submittal. The Ameren modeling, performed by AECOM, uses the latest versi on 15181 of AERMOD and includes four model runs, two runs using beta options currently n ot approved for use in regulatory decision making without prior approval and justification and two runs using default regulatory options. For each pair of runs, two surface meteorological d atasets were used, one at Jefferson City NWS site and one at the Spirit of St. Louis NWS site. N otable differences between this Ameren22

modeling and MDNR modeling are Ameren’s modeling us es a newer version of AERMOD, incorporates hourly varying stack temperatures and flow rates, an hourly varying background value from Nillwood, Illinois, and the merging of a djacent Labadie Stacks 3 and 4 in the hourly varying emission input file.

EPA received a request from MDNR to consider the us e of beta options to model the emissions from the Labadie Energy Center on December 9, 2015. The EPA notes that the usage of beta options, such as ADJ_U* and LOWWIND3, in AERMOD for any regulatory application requires adherence with Appendix W, Section 3.2.2. This is further explained in the EPA’s December 10, 2015 Memorandum titled, “Clarification on the Approval Process for Regulatory Application of the AERMOD Modeling System Beta Opti ons.” Specific to LOWWIND3, this beta option currently has only one reasonable pathw ay for appropriate EPA Regional Office approval with EPA’s Model Clearinghouse concurrence . This pathway, specifically contained as condition number 2 in Appendix W, Section 3.2.2(b), is one in which an application specific statistical performance evaluation is conducted. In an application specific statistical performance evaluation, air quality modeling for the particular type of facility in question would have to be evaluated against representative air quality monito rs that are appropriately sited for the given application. However, LOWWIND3 at this time has not yet fully received scientific peer-review, i.e., criteria “i” for condition number 3 of Append ix W, Section 3.2.2(e) and requires more rigor in its approval as an alternative model. Through a proposed rulemaking to revise Appendix W and promulgate new regulatory options in AERMOD, we have received a number of public comments specific to the LOWWIND3 beta options and are working to complete our review of those comments and then to finalize the appropriate LOWWIND3 option with the necessary peer-reviewed journal articles as part of final App endix W rulemaking package. Due to the potential changes that may occur prior to finalizat ion of the Appendix W rulemaking package in conjunction with the fact that, at this time, LOWWI ND3 has not been demonstrated to have statistically improved performance over that of the regulatory default version of AERMOD for the particular type of facility or has not yet full y received scientific peer-review, the EPA does not believe that the air quality modeling results o btained from the use of this beta option can be

used at this time as a reliable indicator of attain ment status in the area around the Labadie Energy

Center.

The Sierra Club provided comments on Ameren’s model ing approaches to EPA on September 18, 2015, and noted as part of their comments that Ameren had run AERMOD with their inputs in a regulatory default mode and the result using J efferson City NWS data was 282 μ g/ m 3 . This Ameren modeling using regulatory defaults was provi ded to EPA and we note the 282 μ g/ m 3

was a 1 st high value, while the 99 th percentile concentration was 226.9 μ g/ m 3 , which is similar in magnitude to the MDNR and the Sierra Club modeling and still above the NAAQS. EPA believes the Ameren default regulatory option model ing also provided weight of evidence supporting a nonattainment designation. However, EP A is not relying on this Ameren modeling for establishing nonattainment boundaries or design ations as we believe further justification would be needed to support the background value use d and the merging of adjacent stacks.

MDNR also included as part of their designation rec ommendation submittal monitoring data in the vicinity of Labadie. Historic monitoring occurr ed at two locations including the Augusta site23

from 1987-1994 and the Augusta Quarry site from 199 4-1998. In addition, two new monitors

were installed at different locations than the hist oric monitors (Northwest and Valley) and began collecting data on April 22, 2015. The data collect ed from the new monitors are for a short period and the resulting monitoring data have not y et been quality assured by Ameren, the entity responsible for operating these special purpose mon itors. Because the monitoring data from the monitors are not yet quality assured and are for a limited period, the EPA performed no further analysis on these monitoring data for designation p urposes. EPA Region 7 did perform an analysis of the historic monitoring data by looking at hourly emission rates during periods of elevated hourly concentrations to better understand the historic conditions that led to these elevated hourly SO 2 readings. Based on this analysis, the EPA determin ed that, although annual emissions decreased around the 1997 timeframe, the ambient SO 2 concentrations were impacted by several factors independent of annual emissions, including hourly emission rates and meteorological conditions. EPA further determined t hat the conditions that led to the historic elevated concentrations still exist. For example, a maximum hourly SO 2 reading of 80 ppb was measured on March 16, 1997, when the average Ameren Labadie emission rate was 6,813 lb SO 2 per hour. An emission rate of 6,813 lb SO 2 per hour is well within Ameren Labadie’s current hourly emission rates and would equate to less than 30,000 tons of SO 2 per year. Thus, based on our analysis, EPA determined that it is possible th at exceedences and even violations could occur despite the reductions in annual SO 2 emission that have occurred.

Conclusion

After careful evaluation of the state’s recommendat ion and supporting information, as well as all available relevant information, the EPA intends to designate the area around Ameren Labadie Energy Center as nonattainment for the 2010 SO 2 NAAQS. Specifically, the proposed
boundaries are:

The eastern and western boundaries are Boone and Bo les Township boundaries in St. Charles and Franklin Counties respectively. The nor thern boundary is Missouri Route D and Highway 94 in St. Charles. The southern boundar y is Interstate 44 in Franklin County.

This nonattainment designation is based on an analy sis of modeling provided by the state of Missouri, and is supported by further analysis of S ierra Club’s modeling and an analysis of Ameren modeling using regulatory defaults which als o indicate nonattainment. Nonattainment boundaries are supported by the modeling MDNR has p erformed and this modeling indicates all modeled violating receptors are included within the proposed EPA boundary. The three sources included in the modeling analysis are also containe d within the proposed EPA boundary. The four permitted sources omitted in the modeling with in the 20 km radius emitted less than 0.2 tons/yr respectively and are expected to be represe nted in the background value and are not expected to significantly contribute to modeled vio lations. Although MDNR has not relied upon their modeling in their final recommendation to EPA , other than to state they believe there is uncertainty with their modeling conclusions, we fin d that the MDNR modeling followed the recommended EPA TAD modeling guidance for the desig nation process. We also considered modeling submitted to EPA by the Sierra Club and Am eren which also indicated modeled violations of the NAAQS at magnitudes similar to th e MDNR modeling. We did not rely upon24

these modeling runs to establish a boundary, althou gh we did verify modeled violating receptors in the Sierra Club modeling are contained within th e proposed boundary. EPA will consider any additional information submitted by MDNR in making a final designation.

At this time, our intended designations for the sta te only apply to this area and the other areas presented in this technical support document. Consi stent with the conditions in the March 2, 2015, consent decree, the EPA will evaluate and des ignate all remaining undesignated areas in Missouri by either December 31, 2017, or December 3 1, 2020.25 Technical Analysis for the Jackson County, Missouri (Sibley) Area

Proposed Designation Summary

After careful evaluation of the state’s recommendat ion and supporting information, as well as all available relevant information, the EPA intends to designate the area around Sibley Generating
Station as unclassifiable for the 2010 SO 2 NAAQS. Specifically, the area is the portion of Jackson County, Missouri, that is bounded by the Ja ckson County line on the north from Clay and Ray Counties, the county line separating Jackso n County from Lafayette County on the east, Interstate 70 and 470 on the south, and Missouri Hi ghway 291 on the west.

This designation is based on an evaluation of the M DNR modeling submitted in support of an
attainment recommendation with additional considera tion of Sierra Club’s modeling that also supported the MDNR conclusion around the Sibley Gen erating Station but not elsewhere.

Introduction

Jackson County, Missouri, contains a stationary sou rce that according to the EPA’s Air Markets Database emitted in 2012 either more than 16,000 to ns of SO 2 or more than 2,600 tons of SO 2 and had an annual average emission rate of at least 0.45 pounds of SO 2 per one million British thermal units (lbs SO 2 /mmBTU). Specifically, in 2012, the Sibley Generati ng Station emitted 6,095 tons of SO 2 and had a facility wide emissions rate of 0.550 lb s SO 2 /mmBTU. As of March 2, 2015, this stationary source had not met the spe cific requirements for being “announced for retirement.” Pursuant to the March 2, 2015 court-or dered schedule, the EPA must designate the area surrounding the facility by July 2, 2016.

In its submission, Missouri recommended that the ar ea surrounding the Sibley Generating Station, specifically a portion of Jackson County, be designated as attainment based on an assessment and characterization of air quality from the facility and other nearby sources which may have a potential impact in the area of analysis where maximum concentrations of SO 2 are expected. This assessment and characterization was performed using air dispersion modeling software, specifically AERMOD, analyzing actual emi ssions. After careful review of the state’s assessment, supporting documentation, and all avail able data, the EPA does not agree with the
state’s recommendation for the area and intends to designate the area as unclassifiable.

The Sibley Generating Station is located in western Missouri in the eastern portion of Jackson County, approximately 36 km east of downtown Kansas City, Missouri, right along the Missouri River with Ray County, Missouri, directly to the no rtheast. Figure 8 depicts the state’s recommended area for the attainment designation aro und Sibley and EPA’s intended unclassifiable designation for the area.26

Figure 8: The EPA’s intended designation for Jackso n County, Missouri, area around Sibley Generating Station

The discussion and analysis that follows below refe rences the state’s use of the Modeling TAD, the EPA’s assessment of the state’s modeling in acc ordance with the Modeling TAD, and the
factors for evaluation contained in the EPA’s March 20, 2015 guidance, as appropriate.

Detailed Assessment

Model Selection and Modeling Components

The EPA’s Modeling TAD notes that for area designat ions under the 2010 SO 2 NAAQS, the AERMOD modeling system should be used, unless use o f an alternative model can be justified. In some instances the recommended model may be a mo del other than AERMOD, such as the BLP model for buoyant line sources. The AERMOD mode ling system contains the following
components:

- AERMOD: the dispersion model

- AERMAP: the terrain processor for AERMOD

- AERMET: the meteorological data processor for AERMO D

- BPIPPRIME: the building input processor

- AERMINUTE: a pre-processor to AERMET incorporating 1-minute automated surface observation system (ASOS) wind data

- AERSURFACE: the surface characteristics processor f or AERMET

- AERSCREEN: a screening version of AERMOD27

The state used AERMOD version 14134, the most recen t AERMOD version at the time their analysis was performed and the individual component s will be referenced in the corresponding discussion that follows as appropriate.

Modeling Parameter: Rural or Urban Dispersion

The EPA’s recommended procedure for characterizing an area by prevalent land use is based on evaluating the dispersion environment within 3 km o f the facility. According to the EPA’s modeling guidelines, rural dispersion coefficients are to be used in the dispersion modeling analysis if more than 50 percent of the area within a 3 km radius of the facility is classified as rural. Conversely, if more than 50 percent of the a rea is urban, urban dispersion coefficients should be used in the modeling analysis. When perfo rming the modeling for the area of analysis, the state determined that it was most appropriate t o run the model in rural mode. This determination was made by analyzing the land use in the area around the Sibley Generating Station which is predominately rural.

Modeling Parameter: Area of Analysis (Receptor Grid )

The EPA believes that a reasonable first step towar ds characterization of air quality in the area surrounding the Sibley Generating Station is to det ermine the extent of the area of analysis, i.e., the receptor grid. Considerations presented in the Modeling TAD include but are not limited to:
the location of the SO 2 emission sources or facilities considered for mode ling; the extent of significant concentration gradients of nearby sourc es; and sufficient receptor coverage and density to adequately capture and resolve the model predicted maximum SO 2 concentrations.

The grid receptor spacing for the area of analysis chosen by the state is as follows:

- Origin to 1 km, 100 m spacing

- 1 km to 3.5 km, 250 m spacing

- 3.5 km to 10 km, 500 m spacing

- 10 km to 20 km, 1000 m spacing Where the origin was defined at the center of the f acility property.

The receptor network contained 4,022 receptors and covered the northeastern portion of Jackson County in Missouri, the southeastern portion of Pla tt County in Missouri, the southwestern portion of Ray County in Missouri, and the northwes tern portion of Lafayette County in
Missouri.

Figures 9 and 10 show the state’s chosen area of an alysis surrounding the Sibley Generating Station, as well as the receptor grid for the area of analysis. While the Modeling TAD allows receptors for the purposes of this designation effo rt to be placed only in areas where it would also be feasible to place a monitor and record ambi ent impacts, the state chose to leave all receptors in the analysis, including receptors loca ted in areas where monitors would not normally be placed. The impacts of the area’s geography and topography will be discussed later within this
document.

For the Sibley area, the state has included 11 othe r emitters of SO 2 that are permitted to emit SO 2 within 20 kilometers (km) of the Sibley Generating Station and an additional four other SO 228

emitters over 10 tons within 50 km in any direction . No other SO 2 sources with emissions over 10 tons per year were identified by the state withi n 50 km. Although the state’s analysis included sources of emissions out to 50 km, the modeling rec eptor grid extended out to 20 km. The state determined that this was the appropriate distance i n order to adequately characterize air quality from the facility and other nearby sources which ma y have a potential impact in the area of analysis where maximum concentrations of SO 2 are expected. In addition to the Sibley Generating Station, the other emitters of SO 2 included in the area of analysis are: Blue Valley Station, Missouri City Station, Little Blue Valley Sewer District, Missouri Rock, Alliant Tech Systems Inc., St. Mary’s Hospital of Blue Springs, Audubon Materials Sugar Creek Plant, Kansas City Aggregate LLC Independence Quarry, Cour tney Ridge Landfill, the two APACKansas Sugar Creek plants, KCPL Hawthorn, Veolia En ergy, BPU Quindaro, and BPU
Nearman.29

Figure 9: Sibley 20 km Area of Analysis30

Figure 10: Receptor Grid for the Sibley Area of Analysis

Modeling Parameter: Source Characterization

The state characterized the sources within the area of analysis in accordance with the best practices outlined in the Modeling TAD. Specifically, the state used actual stack heights in conjunction with actual emissions. The state also adequately characterized the source’s building layout and location, as well as the stack parameters, e.g., exit temperature, exit velocity, location, and diameter. Where appropriate, the AERMOD component BPIPPRIME was used to assist in addressing building downwash.

Modeling Parameter: Emissions

The EPA’s Modeling TAD notes that for the purposes of modeling to characterize air quality for use in designations, the recommended approach is to use the most recent 3 years of actual emissions data and concurrent meteorological data. However, the TAD does provide for the flexibility of using allowable emissions in the form of the most recently permitted (referred to as PTE or allowable) emissions rate.

The EPA believes that continuous emissions monitoring systems (CEMS) data provide acceptable historical emissions information when it is available and that these data are available for many electric generating units. In the absence of CEMS data, the EPA’s Modeling TAD highly encourages the use of AERMOD’s hourly varying emissions keyword HOUREMIS or through the use of AERMOD’s variable emissions factors keyword EMISFACT. When choosing one of these methods, the EPA believes that detailed throughput, operating schedules, and emissions information from the impacted source(s) should be used.31

In certain instances, states and other interested p arties may find that it is more advantageous or simpler to use PTE rates as part of their modeling runs. Specifically, a facility may have recently adopted a new federally enforceable emissions limit , been subject to a federally enforceable consent decree, or implemented other federally enfo rceable mechanisms and control technologies to limit SO 2 emissions to a level that indicates compliance wit h the NAAQS. These new limits or conditions may be used in the applica tion of AERMOD. In these cases, the Modeling TAD notes that the existing SO 2 emissions inventories used for permitting or SIP planning demonstrations should contain the necessar y emissions information for designationsrelated modeling. In the event that these short-ter m emissions are not readily available, they may be calculated using the methodology in Table 8-1 of Appendix W to 40 CFR Part 51 titled, “Guideline on Air Quality Models.”

As previously noted, the state included Sibley Gene rating Station, 10 other emitters of SO 2 within 20 km of the area of analysis, and four othe r sources within 50 km of the area of analysis. Fifty kilometers is the maximum extent AERMOD can r eliably provide model predictions. This
distance and these facilities were selected because the state believes that this area of analysis adequately represents the area where maximum concen trations of SO 2 are expected and this set of sources adequately includes the sources which mi ght contribute to those concentrations. No other sources were determined by the state to have the potential to cause significant concentration gradient impacts within the area of a nalysis. The facilities in the area of analysis
and their associated annual actual SO 2 emissions between 2012 and 2014 are summarized bel ow.

Table 5: Actual SO 2 Emissions Between 2012 and 2014 from Facilities in the Sibley Area of Analysis

Facility Name SO 2 Emissions (tons per year)

2012 2013 2014

Sibley Generating Station 6,095 6,218 4,847

Blue Valley Station 4,608 3,787 2,105

Missouri City Station 684 741 0

Missouri Rock Inc. 1 1 1

Little Blue Valley Sewer District 2 2 0

Alliant Tech Systems Inc. 2 1 1
St. Mary's Hospital of Blue Springs 0 0 0

Audubon Materials Sugar Creel Plant 115 83 117

Kansas City Aggregate LLC 2 2 2
APAC-Kansas Sugar Creek (095-0048) 1 1 1

Courtney Ridge Landfill 0 0 1
APAC-Kansas Sugar Creek (095-0061) 3 3 3

KCPL Hawthorn 1,576 1,727 1,441

Veolia Energy 6,702 7,934 7,782

BPU Quindaro 2,757 2,905 3,68432 BPU Nearman 4,611 4,928 5,332

Total Emissions 27,160 28,334 25,318

For Sibley, BPU Nearman, BPU Quindaro, and KCPL Haw thorn, the state used actual hourly emissions from the most recent 3-year data set, i.e ., 2012 – 2014. These emissions data were obtained from CEMS. For Veolia Energy, which is loc ated in a separate SO 2 nonattainment area, the state used actual emissions from 2014, as repor ted to the state emission inventory, and calculated a constant emission rate for all periods modeled. Note that the Veolia hourly emission rate was derived by taking the annual emissions and spreading those over 8760 hours which may not represent actual hourly emissions during certai n periods. Blue Valley Station has three coal fired boilers and is required, in Missouri Rule 10 CSR 10-6.261, to switch to natural gas by January 1, 2017. In addition, Blue Valley is subjec t to the boiler MACT and has indicated to Missouri they will switch to natural gas by January 21, 2016, well ahead of the July 2, 2016 designation date, therefore PTE emissions reflectin g natural gas were modeled. It is noted that Missouri Rule 10 CSR 10-6.261 has an initial compli ance date after July 2, 2016. This rule was submitted to EPA for incorporation into Missouri’s SIP on October 9, 2015 but has not yet been acted on by EPA.. Blue Valley has stated it intends to complete the fuel switch before July 2, 2016, but this requirement is not contained in a fe derally enforceable document, thus EPA is not accepting the MDNR attainment modeling that relies upon this fuel switch assumption. Missouri City Station ceased burning coal in 2013 and intend s to shut down in 2016 and was not included in the state’s modeling although it did emit SO 2 in 2012 and 2013 and does not have a federally enforceable requirement to shutdown. Little Blue Va lley Sewer District, Missouri Rock, Alliant Tech Systems Inc., St. Mary’s Hospital of Blue Spri ngs, Audubon Materials Sugar Creek Plant, Kansas City Aggregate LLC Independence Quarry, Cour tney Ridge Landfill, and the two Kansas APAC plants were all modeled at actual emissions.

Modeling Parameter: Meteorology and Surface Charact eristics

The most recent 3 years of meteorological data (con current with the most recent 3 years of emissions data) should be used in designations effo rts. As noted in the Modeling TAD, the selection of data should be based on spatial and cl imatological (temporal) representativeness. The representativeness of the data are based on: 1) the proximity of the meteorological monitoring site to the area under consideration, 2) the complexity of terrain, 3) the exposure of the meteorological site, and 4) the period of time during which data are collected. Sources of meteorological data include National Weather Servic e (NWS) stations, site-specific or onsite data, and other sources such as universities, Feder al Aviation Administration (FAA), and military stations.

For the Sibley area of analysis, surface meteorolog y from the NWS station at the Kansas City International Airport, Missouri, 50 km to the west- northwest, and coincident upper air observations from the NWS in Topeka, Kansas, 126 km to the west-southwest were selected as best representative of meteorological conditions wi thin the area of analysis.

The state used AERSURFACE version 13016 using data from the NWS station at Kansas City International Airport, Missouri, located at latitud e 39.29 and longitude -94.73, to estimate the surface characteristics of the area of analysis. Fo r surface roughness (sometimes referred to as33

“Zo”) the state estimated values for 12 spatial sectors out to 1 km at a monthly temporal resolution for dry, wet, or average conditions for each respective year. The state also used a 10 km by 10 km area centered on the site and estimated values for albedo (the fraction of solar energy reflected from the earth back into space), the Bowen ratio (the method generally used to calculate heat lost or heat gained in a substance). In the figure below, the location of the Kansas City International Airport NWS station is shown relative to the Sibley Generating Station area of analysis.

Figure 11: Sibley Generating Station Area of Analysis and the Kansas City International Airport, Missouri NWS

As part of its recommendation, the state provided the 3-year surface wind rose for Kansas City International Airport. In Figure 12, the frequency and magnitude of wind speed and direction are defined in terms of from where the wind is blowing. Winds are predominantly from the SSW and

NNW.34

Figure 12: Kanas City International Airport Cumulat ive Annual Wind Rose for Years

2012 – 2014

Meteorological data from the above surface and uppe r air stations were used in generating AERMOD-ready files with the AERMET processor. The o utput meteorological data created by the AERMET processor is suitable for being applied with AERMOD input files for AERMOD modeling runs. The state followed the methodology a nd settings presented in the EPA modeling TAD in the processing of the raw meteorological dat a into an AERMOD-ready format and used AERSURFACE to best represent surface characteristic s.

Hourly surface meteorological data records are read by AERMET and include all the necessary elements for data processing. However, wind data ta ken at hourly intervals may not always35

portray wind conditions for the entire hour, which can be variable in nature. Hourly wind data may also be overly prone to indicate calm condition s, which are not modeled by AERMOD. In order to better represent actual wind conditions at the meteorological tower, wind data of one minute duration was provided from the same instrume nt tower but in a different formatted file to be processed by a separate preprocessor, AERMINUTE. These data were subsequently integrated into the AERMET processing to produce fi nal hourly wind records of AERMODready meteorological data that better estimate actu al hourly average conditions and that are less prone to over-report calm wind conditions. This all ows AERMOD to apply more hours of meteorology to modeled inputs and therefore produce a more complete set of concentration estimates. As a guard against excessively high conc entrations that could be produced by AERMOD in very light wind conditions, the state set a minimum threshold of 0.5 meters per second in processing meteorological data for use in AERMOD. This approach is consistent with a March 8, 2013 EPA memo titled, “Use of ASOS meteo rological data in AERMOD dispersion Modeling.” In setting this threshold, no wind speed s lower than this value would be used for determining concentrations. This threshold was spec ifically applied to the one minute wind data.

Modeling Parameter: Geography and Terrain

The terrain in the area of analysis is best describ ed as gently rolling with the Sibley Generation Station located within the Missouri river valley at a base elevation of 728 feet, with surrounding terrain approaching 950 feet. To account for these terrain changes, the AERMAP terrain program within AERMOD was used to specify terrain elevation s for all the receptors. The source of the elevation data incorporated into the model is the U SGS National Elevation Database.

Modeling Parameter: Background Concentrations of SO 2

The Modeling TAD offers two mechanisms for characte rizing background concentrations of SO 2 that are ultimately added to the modeled design val ues: 1) a “first tier” approach, based on monitored design values, or 2) a temporally varying approach, based on the 99 th percentile monitored concentrations by hour of day and season or month. For the Sibley area of analysis, the state chose a first tier approach. The state pe rformed a sector based analysis on the JFK monitor located in Wyandotte County, Kansas in the Kansas City metropolitan area. The state’s approach was to exclude those sectors where this mo nitor was impacted by sources explicitly included in the modeling. Their analysis indicated a 180-200 degree sector best represented an air shed not impacted by sources being explicitly m odeled and a 4 th high value of 13 ppb was derived from this sector. The background concentrat ion for this area of analysis was determined by the state to be 34.1 micrograms per cubic meter ( μ g/m 3 ), or 13 ppb, 4 and that value was incorporated into the final AERMOD results. EPA has reviewed the state’s sector based analysis and agrees that using a background value from the J FK monitor is representative of the area and excluding those impacts from explicitly modeled sou rces is allowed for in Appendix W and the modeling TAD.

4 The conversion factor for SO 2 (at the standard conditions applied in the ambient SO 2 reference method) is 1ppb = approximately 2.62 μ g/m 3

.36

Summary of Modeling Results

The AERMOD modeling parameters for the Sibley area of analysis are summarized below in

Table 6.

Table 6: AERMOD Modeling Parameters for the Sibley Area of Analysis Sibley Area of Analysis

AERMOD Version 14134 Dispersion Characteristics Rural

Modeled Sources 15

Modeled Stacks 60

Modeled Structures 11

Modeled Fencelines 1 Total receptors 4022

Emissions Type Actual CEMS for Sibley, BPU Nearman, BPU Quindaro, and KCPL Hawthorn; various for

others

Emissions Years 2012-2014 Meteorology Years 2012-2014

Surface Meteorology Station Kanas City International Airport, Missouri Upper Air Meteorology Station Topeka NWS, Kansas Methodology for Calculating Background SO 2 Concentration Design Value excluding specific sectors Calculated Background SO 2 Concentration 13 ppb or 34.1 μ g/m 3

The results presented below in Table 7 show the mag nitude and geographic location of the highest predicted modeled concentration based on ac tual emissions.

Table 7: Maximum Predicted 99 th Percentile 1-Hour SO 2 Concentration in the Sibley Area of Analysis Based on Actual Emissions

Averaging Period Data Period Receptor Location SO 2 Concentration ( μ g/m 3 )

UTM/Latitude UTM/Longitude Modeled (including background) NAAQS
99 th Percentile 1-Hour Average 2012-2014 377714.91 4328276.50 167.1 196.5* *Equivalent to the 2010 SO 2 NAAQS set at 75 ppb

The state’s modeling indicates that the predicted 9 9 th percentile 1-hour average concentration within the chosen modeling domain is 167.1 μ g/m 3 , or 63.8 ppb. This modeled concentration37

included the background concentration of SO 2 and is based on actual emissions from the facilities. This highest predicted value occurred on the western edge of the receptor domain where impacts from the Veolia Energy source appear to dominate. Sibley Generating Station also has its highest modeled impacts to the east 1-5 km from the facility and to the north approximately 15 km from the facility in an area of elevated terrain. The impacts from Sibley are all below the NAAQS with modeled peaks from Sibley Generating Station at approximately 100

μ g/m 3 . Figure 13 below was included as part of the state’s recommendation and indicates the highest predicted value. The state’s receptor grid is also shown in the figure.

Figure 13: Maximum Predicted 99 th Percentile 1-Hour SO 2 Concentrations in the Sibley

Area of Analysis Based on Actual Emissions38

Jurisdictional Boundaries:

Once the geographic area of analysis associated wit h the Sibley Generating Station, other nearby sources, and background concentration is determined , existing jurisdictional boundaries are considered for the purpose of informing our intende d unclassifiable area, specifically with respect to clearly defined legal boundaries.

In the case of Sibley Generating Station there is a nearby nonattainment area to the southwest approximately 27 km away. This nonattainment area, which is also located in Jackson County, Missouri, contains Veolia Energy, the primary sourc e contributing to monitored nonattainment and the source impacting the western boundary of th e Sibley monitoring domain. Because this nonattainment area is being addressed in a separate SIP action, and all nearby sources, including other sources in areas subject to the court-ordered deadline for designation on July 2, 2016, and potential DRR sources, are accounted for in the MDN R modeling for Sibley Generating Station, EPA believes the state’s recommended boundary descr ibed earlier is appropriate and justified.

The EPA believes that our intended unclassifiable a rea, consisting of the partial Jackson County area in Missouri, is comprised of clearly defined l egal boundaries and we find these boundaries to be a suitably clear basis for defining our inten ded unclassifiable area.

Other Relevant Information

The Sierra Club submitted modeling demonstrations e valuating compliance with the 1-hour SO 2 NAAQS for the Sibley Generating Station as part of a September 17, 2015 package submittal to EPA. Included with the modeling files were several comment letters including an evaluation document describing the modeling Sierra Club provid ed, prepared by Wingra Engineering, asserting that violations of the NAAQS are present in the area around Sibley Generating Station. Two Sierra Club modeling demonstrations were provid ed, one using actual emissions and another using allowable emissions. Both Sierra Club modeling scenarios show violations of the

1-hr SO 2 NAAQS, although the Sierra Club’s modeling scenari o using actual emissions indicate violations around the Veolia Energy Center only.

Although Sierra Club submitted modeling based on al lowable emission rates, we have concerns that the allowable modeling, as presented, does not represent true SO 2 concentrations in the area, and we are unable to reliably determine whether the area is in attainment or nonattainment based on the allowable modeling. While the modeling TAD does not preclude the use of allowable emissions, for designations allowable emissions are generally used in the case where controls and limits have been recently established, and not to establish actual SO 2 concentrations a monitor might record. 5

5 Designations are intended to address current actual air quality (i.e., modeling simulates a monitor), and, thus, are unlike attainment plan modeling, which mu st provide assurances that attainment will occur. F or the purposes of designations, modeling can be used as a surrogate to ambient monitoring to characteriz e air quality for the designations process. The EPA r ecommends modeling the most recent 3 years of actua l emissions. Emissions Input section (Page 9) http://www3.epa.gov/airquality/sulfurdioxide/pdfs/S O2ModelingTAD.pdf39

The Sierra Club modeling used the Kansas City Downt own NWS for surface data and the Topeka NWS station for upper air data and included 1-minute ASOS data in their AERMET runs. The most significant difference between the S ierra Club analysis and the MDNR analysis for AERMET processing was that the Sierra Club used the Kansas City Downtown NWS data while MDNR chose to use the Kansas City Internation al Airport data. Both the Sierra Club and MDNR used Topeka as the upper air station. The Sier ra Club contends that the Kansas City Downtown NWS is more appropriate because of its pro ximity to Sibley and other important sources in the modeling area. The MDNR meanwhile co ntends that the site characteristics between their surface station choice and Sibley are more representative. EPA notes the merit of both arguments but is not making a formal determina tion on which dataset is more representative in this analysis. Other differences identified in t he Sierra Club modeling include no inclusion of building downwash as Sierra Club did not have acces s to this information, 1.5 meter flagpole receptors, and fewer emission points than the MDNR modeling demonstration, the most notable being BPU Quindaro which was included in the MDNR r un.

For the AERMOD runs, Sierra Club chose to use a muc h larger area of analysis that included a receptor grid out to 50 km from the Sibley Generati ng Station, well beyond the 20 km distance that MDNR chose. While a 50 km receptor domain is p ermitted in the AERMOD modeling system, this Sierra Club grid also includes recepto rs in an existing 1-hr SO 2 nonattainment area in Jackson County MO. As seen in Figure 14, the exi sting nonattainment area in Jackson County, Missouri is an area approximately 13 km to the sout heast of Nearman and 40 km to the southwest of the Sibley Station.40

Figure 14: Existing Jackson County Missouri SO 2 Nonattainment area (hashed in magenta)
with Kansas and Nearman to the West.

The Jackson County, Missouri nonattainment area is being addressed under a separate nonattainment SIP that will require a demonstration that the area demonstrates and maintains compliance with the NAAQS. MDNR submitted the nonat tainment SIP for Jackson County to EPA on October 9, 2015, and the agency is currently reviewing this SIP. In establishing the current Jackson County nonattainment area, the emis sions from Sibley Station were considered and it was determined that Sibley Station contribut ions did not warrant an expanded nonattainment area that would include the Sibley St ation. Although Sierra Club asserts in their comments significant contributions from Sibley Stat ion, it is unclear from the Sierra Club modeling analysis what the actual Sibley Station so urce contributions are, or where they occur, when predicted exceedances occur in the nonattainme nt area and the area south of the Sibley Station. Without further description and analysis o f both when and where Sibley Station contributions occur, we cannot determine if Sibley Station should be included in a separate

nonattainment area. What is clear from the Sierra C lub analysis is that no modeled violations appear to exist within 20 km surrounding the Sibley Station facility.

EPA notes that the Sierra Club provided a table wit h maximum 99 th percentile modeled impacts and individual facility impacts as well as impacts from all facilities combined, but it does not

address contribution at the time of modeled exceeda nces. Table 8 contains the Sierra Club41

modeling summary provided in their comments and the table indicates that impacts from Sibley emissions alone (Sibley boilers 50, 60, 70) are bel ow the NAAQS across all receptors. However, as Table 8 indicates, when actual emissions from Ve olia Energy and other Kansas City sources are included (All with Sibley boilers 50, 60, 70), the model predictions indicate NAAQS exceedances around the Veolia Energy Center due mai nly to Veolia emissions. Overall the Sierra Club model results extending out 20 km around the S ibley Generating Station are similar to the MDNR modeling.

While EPA believes the Sierra Club modeling meets t he requirements of the EPA modeling TAD in terms of inputs and model settings, as previousl y stated the existing nonattainment area is being addressed by the nonattainment SIP and the Si erra Club did not provide enough information for EPA to determine the Sibley Station ’s and other nearby sources’ impact on the area 20+ km southwest of the Sibley Station. Becaus e EPA does not have the maximum daily contributions files (MAXDCONT) as part of the model ing outputs from Sierra Club, EPA cannot directly determine if the Sibley Generating Station and other nearby sources in the area contribute during those periods of modeled violatio ns around the Veolia Energy Center. It is also clear the area MDNR recommends as attainment, and w hich EPA is proposing to designate as unclassifiable, models attainment in both the Sierr a Club and MDNR modeling. For these reasons, EPA is not relying upon the Sierra Club mo deling for determining contributions outside the proposed boundary for the Sibley area, but rath er is relying on the MDNR analysis because EPA believes the area addressed is appropriate in t he MDNR demonstration given the

information available at this time.42

Table 8: Sierra Club Modeling Results presented for the Sibley Area

Conclusion

After careful evaluation of the state’s recommendat ion and supporting information, as well as all available relevant information, the EPA intends to designate the area around Sibley Generating
Station as unclassifiable for the 2010 SO 2 NAAQS. Specifically, the boundaries are the Jackso n County line on the north from Clay and Ray Counties , the county line separating Jackson County from Lafayette County on the east, Interstate 70 an d 470 on the south, and Missouri Highway
291 on the west.

This conclusion is based on an evaluation of the MD NR modeling submitted in support of an
attainment recommendation with additional considera tion of Sierra Club modeling that also supported the MDNR conclusion regarding the impacts extending out 20 km around the Sibley Generating Station but not elsewhere. EPA believes all contributing sources are addressed in the MDNR modeling and that the boundary area proposed b y MDNR is appropriate. However, although MDNR modeling indicates attainment, not al l sources have federally enforceable limits for the emission rates assumed in MDNR’s modeling a nd EPA therefore is proposing
unclassifiable for this area. EPA is unable at this time, based on available information, to determine whether the area is meeting or not meetin g the NAAQS. Should MDNR submit additional information documenting that the limits used in the modeling represent federally enforceable limits, EPA believes the MDNR modeling would support an unclassifiable/attainment designation.43

At this time, our intended designations for the sta te only apply to this area and the other areas presented in this technical support document. Consi stent with the conditions in the March 2, 2015, consent decree, the EPA will evaluate and des ignate all remaining undesignated areas in Missouri by either December 31, 2017, or December 3 1, 2020.44 Technical Analysis for the Scott County, Missouri ( Sikeston) Area

Proposed Designation Summary

After careful evaluation of the state’s recommendat ion and supporting information, as well as all available relevant information, the EPA intends to designate the area around Sikeston Power
Station as unclassifiable/attainment for the 2010 S O 2 NAAQS. Specifically, the area is comprised of the entirety of Scott County, Missouri

.

This conclusion is based on the MDNR modeling submi ttal which demonstrates attainment throughout the entirety of Scott County.

Introduction

Scott County, Missouri contains a stationary source that according to the EPA’s Air Markets Database emitted in 2012 either more than 16,000 to ns of SO 2 or more than 2,600 tons of SO 2 and had an annual average emission rate of at least 0.45 pounds of SO 2 per one million British thermal units (lbs SO 2 /mmBTU). Specifically, in 2012, the Sikeston Power Station emitted 5,242
tons of SO 2 and had a facility wide emissions rate of 0.620 lb s SO 2 /mmBTU. As of March 2, 2015, this stationary source had not met the specif ic requirements for being “announced for retirement.” Pursuant to the March 2, 2015 court-or dered schedule, the EPA must designate the area surrounding the facility by July 2, 2016.

In its submission, Missouri recommended that the ar ea surrounding the Sikeston Power Station, specifically the entirety of Scott County, be desig nated as attainment based on an assessment and characterization of air quality from the facility a nd other nearby sources which may have a potential impact in the area of analysis where maxi mum concentrations of SO 2 are expected. This assessment and characterization was performed using air dispersion modeling software, specifically AERMOD, analyzing actual emissions. Af ter careful review of the state’s assessment, supporting documentation, and all avail able data, the EPA agrees that the area is attaining the standard, and intends to designate Sc ott County as unclassifiable/attainment.

The Sikeston Power Station is located in eastern Mi ssouri in the southern portion of Scott County. As seen in Figure 15 below, the facility is located approximately 30 km west of Illinois and just west of Sikeston, Missouri. Also included in this figure is the state’s recommended area for the attainment designation and the EPA’s intend ed unclassifiable/attainment designation for
the area.45

Figure 15: The EPA’s intended designation for Scott County, Missouri46

The discussion and analysis that follows below refe rences the state’s use of the Modeling TAD, the EPA’s assessment of the state’s modeling in acc ordance with the Modeling TAD, and the
factors for evaluation contained in the EPA’s March 20, 2015 guidance, as appropriate.

Detailed Assessment

Model Selection and Modeling Components

The EPA’s Modeling TAD notes that for area designat ions under the 2010 SO 2 NAAQS, the AERMOD modeling system should be used, unless use o f an alternative model can be justified. In some instances the recommended model may be a mo del other than AERMOD, such as the BLP model for buoyant line sources. The AERMOD mode ling system contains the following
components:

- AERMOD: the dispersion model

- AERMAP: the terrain processor for AERMOD

- AERMET: the meteorological data processor for AERMO D

- BPIPPRIME: the building input processor

- AERMINUTE: a pre-processor to AERMET incorporating 1-minute automated surface observation system (ASOS) wind data

- AERSURFACE: the surface characteristics processor f or AERMET

- AERSCREEN: a screening version of AERMOD

The state used AERMOD version 14134 and a discussio n of the individual components follows as appropriate.

Modeling Parameter: Rural or Urban Dispersion

The EPA’s recommended procedure for characterizing an area by prevalent land use is based on evaluating the dispersion environment within 3 km o f the facility. According to the EPA’s modeling guidelines, rural dispersion coefficients are to be used in the dispersion modeling analysis if more than 50 percent of the area within a 3 km radius of the facility is classified as rural. Conversely, if more than 50 percent of the a rea is urban, urban dispersion coefficients should be used in the modeling analysis. When performing the modeling for the area of analys is, the state determined that it was most appropriate t o run the model in rural mode. This determination was made by analyzing the land use in the area surrounding the Sikeston Power Station, which is predominately rural.

Modeling Parameter: Area of Analysis (Receptor Grid )

The EPA believes that a reasonable first step towar ds characterization of air quality in the area surrounding the Sikeston Power Station is to determ ine the extent of the area of analysis, i.e., the receptor grid. Considerations presented in the Mode ling TAD include but are not limited to: the
location of the SO 2 emission sources or facilities considered for mode ling; the extent of significant concentration gradients of nearby sourc es; and sufficient receptor coverage and density to adequately capture and resolve the model predicted maximum SO 2 concentrations.

The grid receptor spacing for the area of analysis chosen by the state is as follows:47

- Origin to 1 km, 100 m spacing

- 1 km to 3.5 km, 250 m spacing

- 3.5 km to 10 km, 500 m spacing

- 10 km to 20 km, 1000 m spacing

- Beyond 20 km to northern and eastern edges of Scott County, 1000 m spacing Where the origin was defined at the center of the f acility property.

The receptor network contained 5,326 receptors and covered all of Scott County in Missouri, the northeastern portion of Mississippi County in Misso uri, the northern portion of New Madrid County in Missouri, the northwestern portion of Sto ddard County in Missouri, and the southern portion of Cape Girardeau County in Missouri.

For the Sikeston area, the state has included five other emitters of SO 2 between 20 and 50 kilometers (km) of Sikeston Power Station. Fifty ki lometers is the maximum extent AERMOD can reliably provide model predictions. No other fa cilities were included within 20 km of Sikeston Power station because the only sources in this zone use natural gas. The state determined that this was the appropriate distance i n order to adequately characterize air quality from the facility and other nearby sources which ma y have a potential impact in the area of analysis where maximum concentrations of SO 2 are expected. In addition to the Sikeston Power Station, the other emitters of SO 2 included in the area of analysis are: Buzzi Unicem , QC Corp., Havco Wood Products, Noranda Aluminum, and AECI New Madrid Plant.

Figures 16 and 17, which were included in the state ’s recommendation, show the state’s chosen area of analysis surrounding the Sikeston Power Sta tion, as well as the receptor grid for the area of analysis. Receptors for the purposes of this des ignation effort were placed uniformly, including in areas where it would not be feasible t o place a monitor and record ambient impacts. The impacts of the area’s geography and topography will be discussed later within this
document.48

Figure 16: Sikeston 20 km Area of Analysis (“Intera ctive sources” are those identified by the EPA’s interactive mapping tool fo r SO 2 emission sources)49

Figure 17: Receptor Grid for the Sikeston Area of Analysis

M odeling Parameter: Source Characterization

The state characterized the sources within the area of analysis in accordance with the best practices outlined in the Modeling TAD. Specifically, the state used actual stack heights in conjunction with actual emissions. The state also adequately characterized the source’s building layout and location, as well as the stack parameters, e.g., exit temperature, exit velocity, location, and diameter. Where appropriate, the AERMOD component BPIPPRIME was used to assist in addressing building downwash.

Modeling Parameter: Emissions50

The EPA’s Modeling TAD notes that for the purposes of modeling to characterize air quality for use in designations, the recommended approach is to use the most recent 3 years of actual emissions data and concurrent meteorological data. However, the TAD does provide for the flexibility of using allowable emissions in the for m of the most recently permitted (referred to as PTE or allowable) emissions rate.

The EPA believes that continuous emissions monitori ng systems (CEMS) data provide acceptable historical emissions information when it is available and that these data are available for many electric generating units. In the absence of CEMS data, the EPA’s Modeling TAD highly encourages the use of AERMOD’s hourly varyin g emissions keyword HOUREMIS or through the use of AERMOD’s variable emissions fact ors keyword EMISFACT. When choosing one of these methods, the EPA believes that detaile d throughput, operating schedules, and emissions information from the impacted source(s) s hould be used.

In certain instances, states and other interested p arties may find that it is more advantageous or simpler to use PTE rates as part of their modeling runs. Specifically, a facility may have recently adopted a new federally enforceable emissions limit , been subject to a federally enforceable consent decree, or implemented other federally enfo rceable mechanisms and control technologies to limit SO 2 emissions to a level that indicates compliance wit h the NAAQS. These new limits or conditions may be used in the applica tion of AERMOD. In these cases, the Modeling TAD notes that the existing SO 2 emissions inventories used for permitting or SIP planning demonstrations should contain the necessar y emissions information for designationsrelated modeling. In the event that these short-ter m emissions are not readily available, they may be calculated using the methodology in Table 8-1 of Appendix W to 40 CFR Part 51 titled, “Guideline on Air Quality Models.”

As previously noted, the state included the Sikesto n Power Station and five other emitters of SO 2 within 50 km of the Sikeston Power Station. Of the five other facilities, three are close to the northern edge of the Scott County boundary and two are located to the south in New Madrid County Missouri. This 50 km distance and these faci lities were selected because the state believes that its selected area of analysis adequat ely represents the area where maximum
concentrations of SO 2 are expected and the 50 km distance adequately inc ludes the sources which might contribute to those concentrations. No other sources were determined by the state to have the potential to cause significant concentrati on gradient impacts within the area of analysis. The facilities in the area of analysis and their as sociated annual actual SO 2 emissions between
2012 and 2014 are summarized below. Note the natura l gas-fired sources below with zero actual
emissions were evaluated but not included in the mo deling because of a lack of SO 2 emissions.

Table 9: Actual SO 2 Emissions Between 2012 and 2014 from Facilities in the Sikeston Area of Analysis Facility Name SO 2 Emissions (tons per year)
2012 2013 2014
Sikeston Power Station 5,242 5,967 6,651

Unilever Ice Cream 0 0 051 Viking-Cives Midwest Inc. 0 0 0 Crowder Gin Company Inc. 0 0 0

Havco Wood Products Inc. 4 4 4 Q.C. Corporation 30 30 30 Buzzi Unicem Cape Girardeau 916 655 557
Noranda Aluminum 5,260 5,062 5,323
AECI New Madrid Plant 14,400 16,822 16,672
Total Emissions 25,852 28,539 29,237

For Sikeston Power Station and the AECI New Madrid Plant, the state used actual hourly emissions from the most recent 3-year data set, i.e ., 2012 – 2014. These emissions data were obtained from CEMS. For the remaining sources all b ut Noranda Aluminum were modeled at their respective actuals. Noranda Aluminum was mode led at allowable emissions based on a recent PSD permit application. http://dnr.mo.gov/env/apcp/permits/docs/noranda-stj ude2010cp.pdf

Modeling Parameter: Meteorology and Surface Charact eristics

The most recent 3 years of meteorological data (con current with the most recent 3 years of emissions data) should be used in designations effo rts. As noted in the Modeling TAD, the selection of data should be based on spatial and cl imatological (temporal) representativeness. The representativeness of the data are based on: 1) the proximity of the meteorological monitoring site to the area under consideration, 2) the complexity of terrain, 3) the exposure of the meteorological site, and 4) the period of time during which data are collected. Sources of meteorological data include National Weather Servic e (NWS) stations, site-specific or onsite data, and other sources such as universities, Feder al Aviation Administration (FAA), and military stations.

For the Sikeston area of analysis, surface meteorol ogy from the NWS station at the Cape Girardeau NWS, Missouri, 38 km to the north, and co incident upper air observations from the NWS in Springfield, Missouri, approximately 330 km to the west were selected as best representative of meteorological conditions within the area of analysis.

The state used AERSURFACE version 13016 using data from the NWS station at Cape Girardeau, Missouri, located at latitude 37.22 and longitude -89.57, to estimate the surface characteristics of the area of analysis. For surfac e roughness (sometimes referred to as “Zo”) the state estimated values for 12 spatial sectors out t o 1 km at a monthly temporal resolution for dry, wet, or average conditions for each respective year . The state also used a 10 km by 10 km area
centered on the site and estimated values for albed o (the fraction of solar energy reflected from the earth back into space), the Bowen ratio (the me thod generally used to calculate heat lost or heat gained in a substance). In the figure below, t he location of the Cape Girardeau NWS station
is shown relative to the Sikeston Power Station are a of analysis.52

Figure 18: Sikeston Power Station Area of Analysis and the Cape Girardeau, Missouri
NWS

As part of its recommendation, the state provided the 3-year surface wind rose for the Gape Girardeau NWS Kansas City International Airport. In Figure 19, the frequency and magnitude of wind speed and direction are defined in terms of from where the wind is blowing. Winds are predominantly from the SSW and NNW.53

Figure 19: Cape Girardeau NWS Cumulative Annual Win d Rose for Years 2012 – 2014

Meteorological data from the above surface and uppe r air stations were used in generating AERMOD-ready files with the AERMET processor. The o utput meteorological data created by the AERMET processor is suitable for being applied with AERMOD input files for AERMOD modeling runs. The state followed the methodology a nd settings presented in the EPA modeling TAD in the processing of the raw meteorological dat a into an AERMOD-ready format and used AERSURFACE to best represent surface characteristic s.

Hourly surface meteorological data records are read by AERMET and include all the necessary elements for data processing. However, wind data ta ken at hourly intervals may not always portray wind conditions for the entire hour, which can be variable in nature. Hourly wind data54

may also be overly prone to indicate calm condition s, which are not modeled by AERMOD. In order to better represent actual wind conditions at the meteorological tower, wind data of one minute duration was provided from the same instrume nt tower but in a different formatted file to be processed by a separate preprocessor, AERMINUTE. These data were subsequently integrated into the AERMET processing to produce fi nal hourly wind records of AERMODready meteorological data that better estimate actu al hourly average conditions and that are less prone to over-report calm wind conditions. This all ows AERMOD to apply more hours of meteorology to modeled inputs and therefore produce a more complete set of concentration estimates. As a guard against excessively high conc entrations that could be produced by AERMOD in very light wind conditions, the state set a minimum threshold of 0.5 meters per second in processing meteorological data for use in AERMOD. This approach is consistent with a March 8, 2013 EPA memo titled, “Use of ASOS meteo rological data in AERMOD dispersion Modeling.” In setting this threshold, no wind speed s lower than this value would be used for determining concentrations. This threshold was spec ifically applied to the one minute wind data.

Modeling Parameter: Geography and Terrain

The terrain in the area of analysis is best describ ed as gently rolling, with the Sikeston Power Station located within the Missouri river valley at a base elevation of 728 feet and surrounding terrain approaching 950 feet. To account for these terrain changes, the AERMAP terrain program within AERMOD was used to specify terrain elevation s for all the receptors. The source of the elevation data incorporated into the model is the U SGS National Elevation Database.

Modeling Parameter: Background Concentrations of SO 2

The Modeling TAD offers two mechanisms for characte rizing background concentrations of SO 2 that are ultimately added to the modeled design val ues: 1) a “first tier” approach, based on monitored design values, or 2) a temporally varying approach, based on the 99 th percentile monitored concentrations by hour of day and season or month. For the Sikeston area of analysis, the state chose a first tier approach. The backgrou nd concentration for this area of analysis was determined by the state to be 23.6 micrograms per c ubic meter ( μ g/m 3 ), or 9 ppb, 6 and that value was incorporated into the final AERMOD results.

Summary of Modeling Results

The AERMOD modeling parameters for the Sikeston are a of analysis are summarized below in

Table 10.

Table 10: AERMOD Modeling Parameters for the Sikest on Area of Analysis Sikeston Area of Analysis

AERMOD Version 14134

6 The conversion factor for SO 2 (at the standard conditions applied in the ambient SO 2 reference method) is 1ppb = approximately 2.62 μ g/m 3

.55 Dispersion Characteristics Rural

Modeled Sources 6

Modeled Stacks 39

Modeled Structures 14

Modeled Fencelines 1 Total receptors 5,326

Emissions Type Actual CEMS for Sikeston and
AECI New Madrid Plant

Emissions Years 2012-2014 Meteorology Years 2012-2014 Surface Meteorology Station Cape Girardeau, Missour i Upper Air Meteorology Station Springfield, Missouri Methodology for Calculating Background SO 2 Concentration Design Value excluding specific sectors Calculated Background SO 2 Concentration 9 ppb or 23.6 μ g/m 3

The results presented below in Table 11 show the ma gnitude and geographic location of the highest predicted modeled concentration based on ac tual emissions.

Table 11: Maximum Predicted 99th Percentile 1-Hour SO 2 Concentration in the Sikeston Area of Analysis Based on Actual Emissions

Averaging Period Data Period Receptor Location SO 2 Concentration ( μ g/m 3 )

UTM/Latitude UTM/Longitude Modeled (including background) NAAQS
99th Percentile 1-Hour Average 2012-2014 799209.50 4085535.25 97.6 196.5* *Equivalent to the 2010 SO 2 NAAQS set at 75 ppb

The state’s modeling indicates that the predicted 9 9 th percentile 1-hour average concentration within the chosen modeling domain is 97.6 μ g/m 3 , or 37.2 ppb. This modeled concentration

included the background concentration of SO 2 , and is based on actual emissions from the facilities modeled, except for Noranda which used a llowable emissions. Figure 20 below was included as part of the state’s recommendation and indicates that the predicted value occurred approximately 2-3 km away to the southwest. The sta te’s receptor grid is also shown in the figure.56

Figure 20: Maximum Predicted 99 th Percentile 1-Hour SO 2 Concentrations in the Sikeston, Missouri Area of Analysis Based on Actual Emissions57

Jurisdictional Boundaries:

Once the geographic area of analysis associated wit h the Sikeston Power Station, other nearby sources, and background concentration is determined , existing jurisdictional boundaries are considered for the purpose of informing our intende d unclassifiable/attainment area, specifically with respect to clearly defined legal boundaries.

The Sikeston area has no former designation boundar ies. The analysis provided by MDNR has addressed all significant sources close to the stat e’s recommended boundaries. The analysis

included the Sikeston Power Station and demonstrate d through dispersion modeling that the entirety of Scott County is in attainment. No other CD or DRR sources exist within the recommended attainment boundary.

The EPA believes that our intended unclassifiable/a ttainment area, consisting of the entirety of Scott County, has clearly defined legal boundaries, and we find these boundaries to be a suitably clear basis for defining our intended unclassifiabl e/attainment area.

Other Relevant Information

EPA received no other information from 3 rd parties for the Sikeston area.

Conclusion

After careful evaluation of the state’s recommendat ion and supporting information, as well as all available relevant information, the EPA intends to designate the area around Sikeston Power
Station as unclassifiable/attainment for the 2010 S O 2 NAAQS. Specifically, the area is comprised of the entirety of Scott County, Missouri

.

The rationale for this conclusion is based on the M DNR modeling submittal which demonstrates attainment throughout the entirety of Scott County. This demonstration includes all surrounding
SO 2 sources, including sources just outside of Scott C ounty that could potentially contribute significantly to SO 2 concentrations within Scott County. The recommende d
unclassifiable/attainment area also includes Sikest on Power Station within its boundary. No consideration was given to other information as EPA did not receive 3 rd party information for
this area.

At this time, our intended designations for the sta te only apply to this area and the other areas presented in this technical support document. Consi stent with the conditions in the March 2, 2015, court-ordered schedule, the EPA will evaluate and designate all remaining undesignated areas in Missouri by either December 31, 2017, or D ecember 31, 2020.