1 Draft Technical Support Document

Iowa 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 1-hour sulfur dioxide (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 Iowa beca use three emission sources meet the conditions
of the court’s order.

Iowa submitted updated recommendations on September 18, 2015. Table 1 below lists the Iowa
recommendations and identifies the counties in Iowa that the EPA intends to designate by July 2, 2016, based on an assessment and characterization o f air quality through ambient air quality data, air dispersion modeling, other evidence and support ing information, or a combination of the
above.

Table 1: Iowa’s Recommended and the EPA’s Intended Designations
Area Iowa’s

Recommended
Area Definition Iowa’s

Recommended Designation EPA’s Intended

Area Definition EPA’s Intended

Designation

Woodbury County, Iowa Woodbury County Attainment Same as State’s
Recommendation Unclassifiable

Wapello County, Iowa Wapello County Attainment Same as State’s
Recommendation Unclassifiable

Des Moines County, Iowa Des Moines

County Attainment Same as State’s
Recommendation Unclassifiable

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 3-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 codified2

at 40 CFR 50.17. The EPA determined this is the lev el necessary to protect public health with an adequate margin of safety, especially for children, the elderly, and those with asthma. These groups are particularly susceptible to the health e ffects associated with breathing SO 2 . The two prior primary standards of 140 ppb evaluated over 2 4 hours, and 30 ppb evaluated over an entire year, codified at 40 CFR 50.4, remain applicable. 1 However, the EPA is not currently designating areas on the basis of either of these t wo primary standards. Similarly, the secondary
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 CAA requires that not later t han 1 year after promulgation of a new or revised NAAQS, state governors must submit their re commendations 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 designat ion 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, it is given a n 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 EPA
determines that sufficient information is not avail able, in which 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 a portion of Muscatine County, Iowa as nonattainment 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.

1 40 CFR 50.4(e) provides that the two prior primary NAAQS will no longer apply to an area 1 year after 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 Iowa areas were designated nonattainment for the prior N AAQS as of August 22, 2010.3

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 accord ing 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 oth erwise meets the emissions criteria, is excluded from the July 2, 2016, deadline if it had announced through a company public announcement, public utilities commission filing, c onsent decree, public legal settlement, final 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 Iowa. 2 However, there are three

2 For designations based on ambient air quality moni toring data that violate 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 has been informed by
data collected between 2012 and 2014. States with m onitors 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 cal endar year 2015 by April 19, 2016, to the EPA for evaluation. If af ter our review, the ambient air quality data for th e area indicates4

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 Iowa ’s updated recommendations for the areas that we must designate. The EPA also discusses any inten ded 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:

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 99 th percentile 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 the state’s recommendations and all of the
information discussed in this document. The EPA’s d ecision is based on all available information including the most recent 3 years of ai r quality monitoring data, available modeling analysis, and any other relevant informati on. 4) Designated unclassifiable area – an area for 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.

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 Technical Analysis for the MidAmerican – George Nea l South Area

(Woodbury County, Iowa)

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 an area around MidAmerican Energy George Neal South Generating Facility as unc lassifiable for the 2010 SO 2 NAAQS. Specifically, the area is comprised of the entirety of Woodbury County, Iowa.

The unclassifiable designation is based on the fact that although IDNR provided modeling to the EPA that demonstrated attainment for the area, some emission limits used by IDNR in this modeling analysis are not currently federally enfor ceable. 3

Introduction

The Woodbury County, Iowa, area contains a stationa ry source that according to the EPA’s Air
Markets Database emitted in 2012 either more than 1 6,000 tons of SO 2 or more than 2,600 tons
of SO 2 and had an annual average emission rate of at leas t 0.45 pounds of SO 2 per one million British thermal units (lbs SO 2 /mmBTU). Specifically, in 2012, the MidAmerican Ene rgy Company’s George Neal South electric generating fac ility emitted 14,272 tons of SO 2 and had an
emissions rate of 0.638 lbs SO 2 /mmBTU. As of March 2, 2015, this stationary source had not met the specific requirements for being “announced for retirement.” Pursuant to the March 2, 2015 court-ordered schedule, the EPA must designate the area surrounding this facility by July 2,
2016.

In its submission, the Iowa Department of Natural R esources (IDNR) recommended that the area surrounding MidAmerican Energy Company’s George Nea l South electric generating facility, specifically the entirety of Woodbury County, be de signated 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 using AERMOD, analyzing allo wable emissions. After careful review of the state’s assessment, supporting documentation, a nd all available data, the EPA does not agree
with the state’s recommendation for the area and in tends to designate the area, i.e., Woodbury County, as unclassifiable.

The George Neal South facility is operated by MidAm erican Energy Company and is located in western Iowa in the western portion of Woodbury Cou nty. In addition to George Neal South, MidAmerican also operates the nearby George Neal No rth facility. As seen in Figure 1, the George Neal North and South facilities are located approximately 15 km south of the Sioux City, Iowa, area. The facility is located along the Misso uri River on the Iowa side of the Nebraska-

3 See Attachment 2 of the March 20, 2015, document t itled “Updated Guidance for Area Designations for t he 2010 Primary Sulfur Dioxide National Ambient Air Quality Standard” from Stephen D. Page, Director of the Of fice of Air Quality Planning and Standards.6

Iowa state border. Figure 1 shows nearby emitters o f SO 2 the boundaries of Woodbury County,
the state’s recommended area for the attainment des ignation and the EPA’s intended area for the unclassifiable designation.

Figure 1: Location of the MidAmerican George Neal S outh Facility. The boundaries of Woodbury County, Iowa, the area EPA intends to desi gnate as unclassifiable

. The location of the MidAmerican George Neal South Facility is la beled in red and the nearby MidAmerican George Neal North Facility is labeled i n blue. Also, the Sioux City Tile and Brick Facility is labeled in blue.

The discussion and analysis that follows references the state’s use of the Modeling TAD, the EPA’s assessment of the state’s modeling in accorda nce with the Modeling TAD, and the factors for evaluation contained in the EPA’s March 20, 201 5 guidance, as appropriate.

Detailed Assessment

Air Quality Data

This factor considers the SO 2 air quality monitoring data in the area surroundin g the MidAmerican George Neal South facility. IDNR stated in their designation recommendation7

document that while an SO 2 monitor is located in Woodbury County, it is not s ited to assess the maximum 1-hr impacts from George Neal South and has not been in operation long enough to produce a (three-year) design value. Therefore this monitoring information was not relied upon in EPA’s proposed designation of this area.

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, the most recen t version available at the time of modeling analysis. A discussion of the individual c omponents 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 with 3 km of 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. As previously mentioned, the facility is located in the Missouri River valley along the Nebraska-Iowa border
and the rural determination was made based on the l and cover around the George Neal South facility.

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 George Neal South Facility is to de termine the extent of the area of analysis, i.e., 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.8

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

- 50 meters along the George Neal South and North Fac ilities fenceline

- 50 meters from the fenceline to 0.5 km

- 100 meters extending from 0.5 km to 1.5 km

- 250 meters extending from 1.5 km to 3.0 km

- 500 meters extending from 3.0 km to 5.0 km

The receptor network contained 10,014 receptors and covered the western portion of Woodbury County in Iowa and the eastern portion of Dakota Co unty in Nebraska.

Figure 2 shows the state’s chosen area of analysis surrounding the George Neal South Facility, as well as the receptor grid for the area of analysis. Consistent with the Modeling TAD, receptors for the purposes of this designation effort were pl aced only in areas where it would also be feasible to place a monitor and record ambient air impacts. The impacts of the area’s geography and topography will be discussed later within this document.

Figure 2: Receptor Grid for the George Neal South A rea of Analysis

The state performed an analysis to locate any addit ional major sources of SO 2 within 20 km of the George Neal South Facility. The state determine d that this 20 km was the appropriate distance in order to adequately characterize air qu ality from the facility and other nearby sources which may have a potential impact in the area of an alysis where maximum concentrations of SO 29

are expected. For the George Neal South area, the s tate included one other significant emitter of
SO 2 within 20 km of the George Neal South Facility in any direction. In addition to the George Neal South Facility, the other significant emitter of SO 2 included in the area of analysis is the George Neal North Generating Facility, located less than 5 km to the northwest, and which includes three emission units and a natural gas aux iliary boiler.

As previously noted in this section, the state used a modeling grid extending out to 5.0 km, which is less than the 20 km area of analysis used to evaluate nearby sources. While no
additional SO 2 sources beyond 5 km were identified, the modeling results from Figure 5 indicate
that elevated levels of SO 2 occur near the edge of the receptor grid to the no rthwest of the George Neal Facility. Without extending the recepto r grid beyond 5 km, EPA has concerns that areas outside of the current modeling grid have the potential to exceed the NAAQS in the vicinity of George Neal, and is therefore recommend ing an unclassifiable designation for Woodbury County, Iowa based on this uncertainty and other issues identified in this TSD.

Modeling Parameter: Source Characterization

The state characterized the sources within the area of analysis in accordance with the practices outlined as acceptable in the Modeling TAD. Specifi cally, the state used actual stack heights in conjunction with allowable emissions limits. Actual stack heights were modeled with allowable
emission limits in this case since the actual stack heights were below the GEP stack height. The state also adequately characterized the George Neal South and North building layout and location, as well as the stack parameters, e.g., ex it temperature, exit velocity, location, and diameter. Where appropriate, the AERMOD component B PIPPRIME 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 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 control10

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 George Neal South Facility and the three emission units from George Neal North and the natural gas au xiliary boiler which were within 20 km in the area of analysis. One other SO 2 source (Sioux City Brick and Tile – average SO 2 emissions of 73.97 tpy) between 10 km and 20 km was identifie d by the state in its analysis of nearby sources within 20 km. Sioux City Tile and Brick was evaluated by the state. The state compared
the emissions from this source to the total emissio ns in the analysis area, and determined that the emissions from Sioux City were significantly lower than the overall emissions in the area and therefore unlikely to alter the predicted maximum c oncentrations of SO 2 . Emissions from Sioux City Brick and Tile are adequately represented by t he background concentration. This 20 km
distance and these emission units were selected bec ause the state believes that the area of analysis, previously described, adequately includes the sources which might contribute to those
concentrations.

Table 2 lists the actual emissions from the four co al-fired George Neal facilities from 2012-2014.
The emissions data were obtained from EPA’s Clean A ir Markets Division for the purposes of this TSD. The state, however, has chosen to model t hese facilities based on methodologies that are described in the following paragraphs. The natu ral gas auxiliary boiler emissions of SO 2 are not significant in comparison and are not shown in Table 2.

Table 2: Actual SO 2 Emissions in 2012 – 2014 from Facilities in the Ge orge Neal Facility Area of Analysis

Facility Name SO 2 Emissions (tons per year)

2012 2013 2014 George Neal South Unit 4 14,272 10,049 6,813 George Neal North Unit 1 1,018 874 841 George Neal North Unit 2 2,091 2,491 2,890 George Neal North Unit 3 5,868 5,055 2,769
Total Emissions 23,249 18,469 13,313

The first approach was used for George Neal South U nit 4 and George Neal North Unit 3. In 2014, MidAmerican installed SO 2 scrubbers on George Neal South Unit 4 and George N eal North Unit 3 (note the reduced emissions in 2014 in Table 2). The corresponding permitted
emission limit after the installation of the scrubb er technology was based on a 30

‐ day rolling11

average of 2,760 lb/hr 4 and 2,200 lb/hr 5 for George Neal South Unit 4 and George Neal North Unit 3, respectively. IDNR performed an evaluation of these 30

‐ day average rolling permit limits for both emission units to develop a critical 1-hou r emission rate which would preserve the variability of the hour

‐ to

‐ hour emission profile with scrubber controls, yet b e conservative so as to protect the ambient air quality standard for the attainment demonstration. IDNR used the EPA Guidance for 1

‐

Hour SO 2 Nonattainment Area State Implementation Plan Submi ssions memorandum dated April 23, 2014, as guidance in est ablishing these critical 1-houremission rates. Based on that guidance, IDNR reviewed CEMS d ata for similar MidAmerican emission units with similar control technology to establish an appropriate emission rate for modeling George Neal South Unit 4 and George Neal North Unit 3. IDNR stated that surrogate units must be used since George Neal South Unit 4 and George N eal North Unit 3 do not have 3 years of corresponding SO 2 CEMS data after the 2014 installation of the scrub ber controls.

INDR used Walter Scott, Jr. Energy Center Unit 3 an d Louisa Generating Station coal-fired boilers as surrogate units to George Neal South Uni t 4 and George Neal North Unit 3. Walter Scott, Jr. Energy Center Unit 3 and Louisa Generati ng Station have CEMS data available that reflect scrubber operation. The steps below outline the approach IDNR used to determine the ratio that was applied to the 30-day average emissi on limit:

1. Collect 5

‐ years of suitable hourly CEMS data from Walter Scot t and Louisa.
2. Calculate the 99 th percentile 1

‐ hr emission rate over the 5

‐ year period.
3. Calculate the 99 th percentile 30

‐ day rolling average over the 5

‐ year period.
4. Calculate the ratio of the 99 th percentile 30

‐ day rolling average from Step 3 to the 99 th percentile 1

‐ hr value calculated from Step 2.
5. Apply that calculated ratio to the George Neal Sout h Unit 4 and George Neal Unit 3 30

‐ day average rolling limit that does not have correspond ing CEMS data to back-calculate the corresponding critical hourly emission rate to mode l (the permitted 30

‐ day average rolling limit divided by the calculated ratio).

Based on the procedure outlined above, the ratios a t Walter Scott, Jr. Energy Center Unit 3 and Louisa Generating Station are approximately 0.817 a nd 0.808, respectively. The average of the two ratios, 0.81255, was divided into the 30

‐ day average rolling limits for George Neal South Unit 4 and George Neal North Unit 3 to compute the critical hourly SO 2 emission rates used in the modeling analysis. The critical hourly emission rates used in the modeling are shown in
Table 3.

The second approach was used for George Neal North Units 1 & 2. IDNR used PTE limits for
SO 2 based on a consent decree 6 between MidAmerican and the Sierra Club that requi res the two units to cease combusting coal and switch to natura l gas only by April 16, 2016. However, the

4 IDNR permit 05-A-655-P3 issued on April 2, 2012.

5 IDNR permit 95-A-313-P7 issued on October 23, 2014

. 6 Consent Decree between Sierra Club and MidAmerican Energy, United States District Court, Southern Dis trict of Iowa, Case No. 13-CV-21, filed on January 22, 2013.12

consent agreement between MidAmerican and the Sierr a Club is not federally enforceable. 7 In addition, for the George Neal North natural gas aux iliary boiler which was scheduled to become operational in the fall of 2015, IDNR based the PTE on federally enforceable limits for SO 2 . The facilities in the state’s area of analysis and thei r associated PTE rates (lb/hr) as described in this paragraph are listed in Table 4.

Table 3: Modeled SO 2 Emissions based on 30-day average emissions limits from new controls from George Neal South Unit 4 and North Un it 3 in the Woodbury County, Iowa Area of Analysis

Company ID Facility Name SO 2 Emissions (lb/hr), (based on 30-day emission limit variability analysis)

MidAmerican George Neal

South Unit 4 3,396.7

MidAmerican George Neal

North Unit 3 2,707.6

Table 4: Modeled SO 2 Emissions based on PTE from Facilities in the Wood bury Co, Iowa Area of Analysis

Company ID Facility Name SO 2 Emissions (lb/hr), based on PTE

Mid-American George Neal

North Unit 1 0.8018

Mid-American George Neal

North Unit 2 1.812

Mid-American George Neal

North Unit Auxiliary Boiler 0.03

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, the F ederal Aviation Administration (FAA), and military stations.

7 See Attachment 2 of the March 20, 2015 document ti tled “Updated Guidance for Area Designations for th e 2010 Primary Sulfur Dioxide National Ambient Air Quality Standard” from Stephen D. Page, Director of the Of fice of Air Quality Planning and Standards.13

For the George Neal area of analysis, surface meteo rology from the NWS station in Sioux City, Iowa, approximately 15 km to the north, and coincid ent upper air observations from the NWS station in Omaha, Nebraska, approximately 150 km to the south were selected as best representative of meteorological conditions within the area of analysis (Figure 3).

The state used AERSURFACE version 13016 using data from the NWS station in Sioux City, Iowa located at 42.40N, 96.38W to estimate the surf ace characteristics of the area of analysis. The state estimated values for 12 spatial sectors a t a monthly temporal resolution. AERSURFACE was processed three times, once each for dry, average, and wet surface moisture conditions. The output for the individual months fr om the three AERSURFACE runs were then manually combined into one output file. The state a lso 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 sub stance), and the surface roughness (sometimes referred to as “Zo”). In the figure below generated by the EPA, the location of the Sioux City, Iowa NWS station and Omaha, NE upper air station is shown relative to the George Neal area of analysis.

Figure 3: George Neal South Area of Analysis and th e Sioux City, Iowa NWS and Omaha, NE NWS upper air locations

.

As part of its recommendation, the state provided t he 3-year surface wind rose for Sioux City, Iowa. In Figure 4, the frequency and magnitude of w ind speed and direction are defined in terms of from where the wind is blowing. Winds are predom inately from the northwest and southeast.14

Figure 4: Sioux City, Iowa Cumulative Annual Wind R ose 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 EPA’s Modeling TAD for area designations under the 2010 SO 2 NAAQS in the processing of the raw meteorological data into an AERMOD-ready format, an d 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 1 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 by15

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 2013 EPA memo titled, “Use of ASOS meteorol ogical 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 1-minute wind data.

Modeling Parameter: Geography and Terrain

The terrain in the area of analysis is best describ ed as relatively flat since the George Neal facility lies in the Missouri River Valley. This es pecially true for the terrain on the Iowa side of the border. To the west of the facility lies the Mi ssouri River along with rolling hills in eastern Nebraska. To account for these terrain changes, the AERMAP terrain program within AERMOD was used to specify terrain elevations for all the receptors. The source of the elevation data incorporated into the model was the USGS National E levation 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 George Neal area of analysis, IDNR chose th e “first tier” approach but derived a statewide default background concentration using an average of the concentrations of four monitors using 2009-2011 data. The derived average background concentration was based on monitors from the following four cities in Iowa: Ce dar Rapids, Davenport, Des Moines, and Keosauqua. While the averaging of multiple monitors is not outlined in the Modeling TAD, EPA Region 7 believes that this methodology provides a conservative background concentration for the George Neal area, which is located in rural nor thwest Iowa. In contrast, the four monitors used in the average background concentration are lo cated near higher populated areas and other
sources of SO 2 emissions. In fact, IDNR no longer uses this avera ging technique for sources in rural areas for this reason. IDNR is now using the Lake Sugema monitor for sources in rural
areas since this monitor is located in a rural area . The Lake Sugema monitor has a design value of 7 μg/m 3 , which is much lower than the background design va lue proposed in this analysis 8

. In summary, the background concentration for this a rea of analysis was determined by the state using the described “first tier” multiple monitor a veraging technique to be 32 micrograms per cubic meter ( μ g/m 3 ), or 12.2 ppb, 9 and that value was incorporated into the final AER MOD
results.

8 http://www.iowadnr.gov/Portals/idnr/uploads/air/dis pmodel/background_concentrations_tsd.pdf

9 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

.16

Summary of Modeling Results

The AERMOD modeling parameters for the George Neal area of analysis are summarized below
in Table 5.

Table 5: AERMOD Modeling Parameters for the George Neal, Iowa Area of Analysis George Neal, Iowa Area of Analysis

AERMOD Version 14134 Dispersion Characteristics Rural

Modeled Sources 2
Modeled Stacks 5

Modeled Structures 119

Modeled Fencelines 2 Total receptors 10,014 Emissions Type PTE

Emissions Years Emission limits were effective in 2014 for George Neal South Unit 4 and George Neal
North Unit 3. Emission limits
are to be effective in 2016 for George Neal North Units 1 &

2 Meteorology Years 2012-2014 Surface Meteorology Station Sioux City, Iowa Upper Air Meteorology Station Omaha, Nebraska Methodology for Calculating Background SO 2 Concentration Statewide default from
monitors Calculated Background SO 2 Concentration 32 μ g/m 3

The results presented below in Table 6 show the mag nitude and geographic location of the highest predicted modeled concentration based, in p art, on emission limits from a consent decree between MidAmerican Energy and the Sierra Club.

Table 6: Maximum Predicted 99 th Percentile 1-Hour SO 2 Concentration in the George Neal, Iowa, Area of Ana lysis Based on PTE 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 219814.9 4693460.2 194.8 1 96.5*

*Equivalent to the 2010 SO 2 NAAQS set at 75 ppb17

The state’s modeling indicates that the highest pre dicted 3-year average 99 th percentile 1-hour average concentration within the chosen modeling do main is 194.8 μ g/m 3 , or 74.4 ppb. This
modeled concentration included the background concentration of SO 2 , and is based, in part, on
emission limits from a consent decree between MidAm erican Energy and the Sierra Club. Figure 5 below indicates that the predicted value occurred to the northwest of the George Neal facility. The state’s receptor grid is also shown in the figu re.

Figure 5: Maximum Predicted 99 th Percentile 1-Hour SO 2 Concentrations in the George Neal South Area of Analysis Based on PTE Emi ssion. The location of the George Neal emission units are shown by the red circles. T he maximum predicted 99 th percentile 1-
hour SO 2 concentration is 162.8 μg/m 3 located to the northwest of the George Neal North Facility. With the addition of the 32 μg/m 3 background concentration, the maximum

predicted concentration is 194.8 μg/m 3

.18

Jurisdictional Boundaries:

Once the geographic area of analysis associated wit h the George Neal South Generating Facility and background concentration is determined, existin g jurisdictional boundaries are considered for the purpose of informing our intended unclassif iable area, specifically with respect to clearly defined legal boundaries.

IDNR recommended an attainment area boundary consis ting of the entirety of Woodbury County. The EPA has confirmed that except for the G eorge Neal North and George Neal South
facilities which have been included in the state’s modeling analysis, there are no additional sources within Woodbury County that emit 100 tpy or more of SO 2. There are two other Title V 10 sources within the county. As previously mentioned, emissions from Sioux City Brick and Tile Company were analyzed and determined to be insignif icant due to the amount of SO 2 emissions (<100 tpy). Thus, Sioux City Brick and Tile Company was not included in the modeling analysis
and the SO 2 emissions from this facility are accounted for in the background concentration. The other source, not mentioned by the state, is Cargil l Inc. – Sioux City, which reported less than 1
ton of SO 2 in 2014. Based on available information, the EPA d oes not have reason to believe that either Sioux City Brick and Tile or Cargill Inc. – Sioux City are likely to cause or contribute to a violation of the NAAQS anywhere within Woodbury Cou nty.

The EPA believes that our intended unclassifiable a rea, consisting of all of Woodbury County in Iowa, are comprised of clearly defined legal bounda ries, and we find these boundaries to be a suitably clear basis for defining our intended uncl assifiable area.

Other Relevant Information

The EPA did not receive any additional information about the area in the immediate vicinity of George Neal South.

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 MidAmerican Energy George Neal South Generating Facility as unc lassifiable for the 2010 SO 2 NAAQS. Specifically, the area is comprised of the entirety of Woodbury County, Iowa.

The unclassifiable designation is based on the fact that although IDNR provided modeling to the EPA that demonstrated attainment for the area, some emission limits used by IDNR in this modeling analysis are not currently federally enfor ceable. 11 The emission limits assumed for George Neal North Unit 1 and 2 are based on a conse nt decree between MidAmerican and the Sierra Club. This agreement requires MidAmerican to cease burning coal in Unit 1 and 2 by April 16, 2016. The limits in this agreement are no t yet federally enforceable and therefore cannot be relied upon in the modeling analysis, or credited to inform a final designation. However, if these limits, which are adequately prot ective of the 1-hour NAAQS, become

10 Title V refers to the 40 CFR Part 70 and Part 71, Operating Permit programs.

11 See Attachment 2 of the March 20, 2015 document ti tled “Updated Guidance for Area Designations for th e 2010 Primary Sulfur Dioxide National Ambient Air Quality Standard” from Stephen D. Page, Director of the Of fice of Air Quality Planning and Standards.19

federally enforceable adequately in advance of the EPA’s promulgation of final designations, and if all other conditions are still representativ e of those contained in this document and the state adequately addresses the receptor grid distan ce, the EPA anticipates designating Woodbury County as unclassifiable/attainment. Notably, the s tate followed the Modeling TAD in its analysis indicating compliance with the NAAQS using the consent decree emission limits, and we do not have information leading us to believe th at any other sources in Woodbury County cause or contribute to a violation of the NAAQS.

For the reasons described above, EPA is unable at t his time, based on available information, to determine whether the area is meeting or not meetin g the NAAQS.

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 Iowa by either December 31, 2017, or December 31, 2 020.20 Technical Analysis for the IPL – Burlington Generat ing Station Area

(Des Moines County, Iowa)

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 IPL Burlington Generating Facility as unclassifiable for the 2010 SO 2 NAAQS. Specifically, the area is comprised of the entirety of Des Moines County, Iow a.

The unclassifiable designation is based on the unce rtain timing of proposed allowable emission limits on the IPL Burlington Generating Facility’s main boiler, specifically the lack of indication that the limits will be federally enforceable by th e July 2, 2016, court-ordered deadline to designate the area.

Introduction

The Des Moines County, Iowa, area contains a statio nary source that according to the EPA’s Air
Markets Database emitted in 2012 either more than 1 6,000 tons of SO 2 or more than 2,600 tons
of SO 2 and had an annual average emission rate of at leas t 0.45 pounds of SO 2 per one million British thermal units (lbs SO 2 /mmBTU). Specifically, in 2012, the Interstate Powe r & Light (IPL) Burlington electric generating facility emitt ed 4,697 tons of SO 2 and had an emissions rate
of 0.672 lb SO 2 /mmBTU. As of March 2, 2015, this stationary source had not met the specific requirements for being “announced for retirement.” Pursuant to the March 2, 2015 court-ordered schedule, the EPA must designate the area surroundi ng the facility by July 2, 2016.

In its submission, IDNR recommended that the area s urrounding IPL Burlington electric generating facility, specifically the entirety of D es Moines 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 ar ea of analysis where maximum
concentrations of SO 2 are expected. This assessment and characterization was performed using air dispersion modeling software, specifically AERM OD, analyzing allowable emissions. After careful review of the state’s assessment, supportin g documentation, and all available data, the EPA does not agree with the state’s recommendation for the area, and intends to designate the
area as unclassifiable based on the fact that emiss ion limits used in the IPL Burlington modeling analysis are not currently federally enforceable an d there is no indication in the IDNR submittal that the limits will be federally enforceable by Ju ly 2, 2016.

The IPL Burlington facility is located in southeast ern Iowa in the southeast portion of Des Moines County. As seen in Figure 6, the IPL Burling ton facility is located approximately 5 km south of the community of Burlington, Iowa (pop. ~25 ,000). The facility is along the Mississippi River, located on the Iowa side of the Iowa-Illinoi s state border. Figure 6 also shows nearby
emitters of SO 2 and the boundaries of Des Moines County, the area that the EPA intends to designate as unclassifiable.21

Figure 6: Location of the IPL Burlington Facility l abeled in red and the nearby Iowa Army Ammunition Plant labeled in blue. The EPA’s intende d unclassifiable designation is for the entirety of Des Moines County, Iowa.

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

Air Quality Data

This factor considers the SO 2 air quality monitoring data in the area surroundin g the IPL Burlington facility. Since no SO 2 ambient monitors were located in Des Moines County , no monitoring data was relied upon in EPA’s proposed d esignation for this area.

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:22

- 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 version available at the time of the modeling analysis. A discussion of the individual c omponents 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 with 3 km of 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. As previously mentioned, the facility is located in the Mississip pi River valley along the Iowa-Illinois border
and the rural determination was made based on the l and cover around the IPL Burlington facility.

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 IPL Burlington Facility is to deter mine the extent of the area of analysis, i.e., 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:

- 50 meters along the IPL Burlington Facility fenceli ne

- 50 meters from the fenceline to 0.5 km

- 100 meters extending from 0.5 km to 1.5 km

- 250 meters extending from 1.5 km to 3.0 km

- 500 meters extending from 3.0 km to 5.0 km

The receptor network contained 2,486 receptors and covered the eastern part of Des Moines County in Iowa and the western portion of Henderson County in Illinois.

Figure 7, included in the state’s recommendation, s hows the state’s chosen area of analysis surrounding the IPL Burlington facility, as well as the receptor grid for the area of analysis. Consistent with the Modeling TAD, receptors for the purposes of this designation effort were23

placed only in areas where it would also be feasibl e to place a monitor and record ambient air impacts. Therefore receptors were removed on the ad jacent Mississippi River. The impacts of the area’s geography and topography will be discussed l ater within this document.

Figure 7: Receptor Grid for the IPL Burlington Area of Analysis.

The state performed an analysis to locate any addit ional major sources of SO 2 within 20 km of IPL Burlington. For the area of analysis, the state did identify the Iowa Army Ammunition Plant (IAAP), with a maximum SO 2 emissions rate of 753.26 tpy during the 2012-2014 period, as a possible significant SO 2 contributor within 20 km of the IPL Burlington fac ility. The IAAP is located approximately 15 km to the northwest of the Burlington Facility. It has two coal-fired boilers that vent through a common stack. IDNR perf ormed a single point source modeling analysis for this facility to determine the plant’s impact within the IPL Burlington modeling analysis area. Although excluding IAAP as an intera ctive source for the IPL Burlington analysis and modeling the source separately does not follow the Modeling TAD and is not recommended, Region 7 believes the results likely give a conserv ative estimation for this analysis since the highest modeled impact from IAAP was added to the h ighest modeled impact from IPL Burlington. INDR modeling indicated that the highes t 4 th highest predicted concentration (corresponding to the 99 th percentile) averaged over three years attributed t o the emissions from the IAAP was 21.3 μg/m 3 . IDNR stated that this modeled concentration for t he IAAP, along with the inclusion of the modeled IPL Burlington results and background value, is below the 1-hr SO 2 NAAQS.24

As previously noted in this section, the state used a modeling grid extending out to 5.0 km, which is less than the 20 km area of analysis used to evaluate nearby sources. The impacts of the
one additional SO 2 source (IAAP) was model separately. EPA does have concerns with the relative small size of the 5 km receptor grid, alth ough modeling results for IPL Burlington shown in Figure 10 indicate that this 5 km grid likely co ntains the area of maximum concentrations. However, based on this uncertainty and other issues identified in this TSD, EPA is recommending an unclassifiable designation for Des Moines County, Iowa.

Modeling Parameter: Source Characterization

The state characterized the sources within the area of analysis in accordance with the practices outlined in the Modeling TAD as acceptable. Specifi cally, the state used actual stack heights in conjunction with allowable emissions limits. Actual stack heights were modeled with allowable
emission limits in this case since the actual stack heights were below the GEP stack height. The state also adequately characterized the IPL Burling ton 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 use d 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 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 may25

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 IPL Burling ton and one other emitter of SO 2 within 20 km in the area of analysis. This SO 2 source (IAAP) was evaluated individually in the st ate’s modeling analysis. The state determined that the em issions from this source would not lead to
exceedances of the 1-hr SO 2 NAAQS when added to the IPL Burlington modeled imp acts and the background value. The 20 km distance was select ed because the state believes that this distance adequately includes the sources which migh t contribute to concentrations in the area of analysis.

Table 7 lists the actual emissions from the IPL Bur lington Facility from 2012-2014. The
emissions data were obtained from EPA’s Clean Air M arkets Division for the purposes of this TSD. The state, however, has chosen to model the f acility based on PTE that will reflect the new allowable emission limit. The new proposed emission limit for the main IPL Burlington coal
utilization boiler is shown in Table 8. In addition , IDNR states that “Construction permit
modifications will be made to enforce the new emiss ion limits once EPA approves the modeling
results”. EPA Region 7 has discussed the timing of the issuan ce of this permit modification with IDNR but the permit modification has not yet been i ssued and it is not clear if the new emission limit will be effective by July 2, 2016.

Table 7: Actual SO 2 Emissions in 2012 – 2014 from the IPL Burlington F acility

Facility Name SO 2 Emissions (tons per year)

2012 2013 2014 Burlington Generating Station 4,697 3,941 3,657

Table 8: SO 2 Emissions based on proposed PTE from Facilities in the Des Moines County, Iowa, Area of Analysis.

Company ID Facility Name SO 2 Emissions (lb/hr), based on Proposed
emission limit

IPL Burlington

Generating Station (Main Boiler) 2,077

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 of26

meteorological data include NWS stations, site-spec ific or onsite data, and other sources such as universities, FAA, and military stations.

For the IPL Burlington area of analysis, surface me teorology from the NWS station in Burlington, Iowa, 5 km to the north, and coincident upper air observations from the NWS station in Davenport, Iowa, approximately 120 km to the nor theast were selected as best representative of meteorological conditions within the area of ana lysis (Figure 8).

The state used AERSURFACE version 13016 using data from the NWS station in Burlington, Iowa, located at 40.77N, 91.13W to estimate the sur face characteristics of the area of analysis. The state estimated values for 12 spatial sectors a t a monthly temporal resolution. AERSURFACE was processed three times, once each for dry, average, and wet surface moisture conditions. The output for the individual months fr om the three AERSURFACE runs were then manually combined into one output file. The state a lso 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 sub stance), and the surface roughness (sometimes referred to as “Zo”). In the figure below generated by the EPA, the locations of the Burlington, Iowa, NWS station and Davenport, Iowa, upper air st ation are shown relative to the IPL Burlington area of analysis.

Figure 8: IPL Burlington Area of Analysis and the B urlington, Iowa, NWS surface site and Davenport, Iowa, NWS upper air location27

As part of its recommendation, the state provided t he 3-year surface wind rose for Burlington, Iowa. In Figure 9, the frequency and magnitude of w ind speed and direction are defined in terms of from where the wind is blowing. Winds are predom inately from the northwest and south
southwest.

Figure 9: Burlington, Iowa, Cumulative 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 EPA’s Modeling TAD for area designations under the 2010 SO 2 NAAQS in the processing of the raw meteorological data into an AERMOD-ready format, an d 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 of28

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. In setting this threshold, no wind speeds lower than this value would be used for dete rmining concentrations. This approach is consistent with a March 2013 EPA memo titled, “Use of ASOS meteorological data in AERMOD dispersion Modeling.” This threshold was spe cifically applied to the one minute wind
data.

Modeling Parameter: Geography and Terrain

The terrain in the area of analysis is best describ ed as relatively flat as the IPL Burlington facilit y lies along the Mississippi River Valley. There are, however, rolling hills to the northwest of the facility. To account for these terrain changes, the AERMAP terrain program within AERMOD was used to specify terrain elevations for all the receptors. The source of the elevation data incorporated into the model is from the USGS Nation al 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 IPL Burlington area of analysis, IDNR chose the “first tier” approach but derived a statewide default background concentration using an average of the concentrations of four monitors using 2009-2011 data. The derived average background concentration was based on monitors from the following four cities in Iowa: Ce dar Rapids, Davenport, Des Moines, and Keosauqua. While the averaging of multiple monitors is not outlined in the Modeling TAD, EPA Region 7 believes that this methodology provides a conservative background concentration for the IPL Burlington area, which is located in rural southeast Iowa. In contrast, the four monitors used in the average background concentration are lo cated near higher populated areas and other
sources of SO 2 emissions. In fact, IDNR no longer uses this avera ging technique for sources in rural areas for this reason. IDNR is now using the Lake Sugema monitor for sources in rural
areas since this monitor is located in a rural area . The Lake Sugema monitor has a design value of 7 μg/m 3 , which is much lower than the background design va lue proposed in this analysis 12

. In summary, the background concentration for this a rea of analysis was determined by the state using the described “first tier” multiple monitor a veraging technique to be 32 micrograms per

12 http://www.iowadnr.gov/Portals/idnr/uploads/air/dis pmodel/background_concentrations_tsd.pdf29

cubic meter ( μ g/m 3 ), or 12.2 ppb, 13 and that value was incorporated into the final AER MOD
results.

Summary of Modeling Results

The AERMOD modeling parameters for the IPL Burlingt on area of analysis are summarized
below in Table 9.

Table 9: AERMOD Modeling Parameters for the IPL Bur lington, Iowa, Area of Analysis IPL Burlington, Iowa, Area of Analysis

AERMOD Version 14134 Dispersion Characteristics Rural

Modeled Sources 2

Modeled Stacks 1

Modeled Structures N/A

Modeled Fencelines 1 Total receptors 2,486

Emissions Type PTE based on proposed
emission limits

Emissions Years EPA inferred that new proposed limits on the IPL Burlington main boiler will likely take effect in 2016. However, in a December 23, 2015 updated
recommendation from the state, the emission limits will not be included in a permit. Meteorology Years 2012-2014 Surface Meteorology Station Burlington, Iowa Upper Air Meteorology Station Davenport, Iowa Methodology for Calculating Background SO 2 Concentration Statewide default from
monitors Calculated Background SO 2 Concentration 32 μ g/m 3

The results presented below in Table 10 show the ma gnitude and geographic location of the highest predicted modeled concentration based on pr oposed PTE emissions.

Table 10: Maximum Predicted 99 th Percentile 1-Hour SO 2

13 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

.30

Concentration in the IPL Burlington, Iowa, Area of Analysis Based on proposed PTE
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 657672.4 4514455.5 116.5 1 96.5* *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 116.5 μ g/m 3 , or 44.8 ppb. This modeled concentration
includes the background concentration of SO 2 and is based on proposed PTE emissions from the facility. When the modeled impact for the IAAP is combined wi th the separate modeling analysis for IPL Burlington, the results are below the 1-hr SO 2 NAAQS (maximum concentration of 137.79 μg/m 3 ). Figure 10 below was included as part of the state’s recommendation and indicates that the predicted value occurred to the northwest of the IPL Burlington facility. The state’s receptor grid is also shown in the figure.31

Figure 10: Maximum Predicted 99 th Percentile 1-Hour SO 2 Concentrations in the IPL Burlington Area of Analysis Based on Proposed P TE Emissions. Location of Burlington emission units are shown by red circles. The maximum Predicted 99 th Percentile 1-Hour is 84.5 μg/m 3 located just to the north of the IPL Burlington Fa cility. With the addition of the 32 μg/m 3 background concentration, the maximum predicted concentration is 116.5 μg/m 3

.

Jurisdictional Boundaries

Once the geographic area of analysis associated wit h the IPL Burlington Facility is determined, existing jurisdictional boundaries are considered f or the purpose of informing our intended unclassifiable area, specifically with respect to c learly defined legal boundaries.

IDNR recommended an attainment area boundary consis ting of the entirety of Des Moines County. The IAAP is located in Des Moines County an d is the only source within 20 km. As previously discussed, the EPA believes that it is u nlikely for the emissions from this facility, if controlled to the proposed PTE levels, to cause or contribute to a violation of the NAAQS within Des Moines County.32

There are two additional Title V sources within the county. Big River Resources West Burlington reported 68 tpy of SO 2 emissions in 2014. Natural Gas Pipeline Co. of Ame rica – Station 204 reported less than 1 ton of SO 2 in 2014. All non-Title V sources in this rural cou nty are believed to be adequately represented by the ba ckground concentration used in the modeling. There are no other sources within Des Moines County or within 20 km of its borders that emit at or above 100 tpy of SO 2 , according to the 2011 NEI.

The EPA believes that our intended designated area, consisting of all of Des Moines County in Iowa, has clearly defined legal boundaries, and we find these boundaries to be a suitably clear basis for defining our intended designated area.

Other Relevant Information

The EPA did not receive any additional information about the area in the immediate vicinity of IPL Burlington.

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 IPL Burlington Generating Facility as unclassifiable for the 2010 SO 2 NAAQS. Specifically, the area is comprised of entirety of Des Moines County, Iowa.

The unclassifiable designation is based on the unce rtain timing of proposed allowable emission limits on the IPL Burlington Generating Facility’s main boiler, specifically the lack of indication that the emission limits will be federally enforcea ble by the July 2, 2016, court-ordered deadline to designate the area. The modeling provided by IDN R using the proposed emission limits shows attainment. The modeling performed by IDNR followed the recommended EPA modeling TAD for designation purposes. However, since the propos ed emission rates that were used in IDNR’s modeling analysis are not federally enforceable, IP L Burlington could emit at a rate that was higher than the rate that was modeled and that coul d affect the resulting modeled concentrations. Therefore, EPA is proposing an unclassifiable desig nation. Should IDNR submit additional information documenting that the limits used in the modeling represent federally enforceable limits and adequately address the receptor grid dis tance, EPA believes the modeling would support an unclassifiable/attainment designation.

For the reasons described above, EPA is unable at t his time, based on available information, to determine whether the area is meeting or not meetin g the NAAQS.

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 Iowa by either December 31, 2017, or December 31, 2 020.33 Technical Analysis for the IPL – Ottumwa Generating Station Area

(Wapello County, Iowa)

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 IPL Ottumwa Generating Facility as unclassifiable for the 2010 SO 2 NAAQS. Specifically, the area is comprised of the entirety of Wapello County, Iowa.

The unclassifiable designation is based on the unce rtain timing of proposed allowable emission limits on the IPL Ottumwa Generating Facility’s mai n boiler, specifically the lack of indication that the limits will be federally enforceable by th e July 2, 2016, court-ordered deadline to designate the area.

Introduction

The Wapello County, Iowa, area contains a stationar y source that according to the EPA’s Air
Markets Database emitted in 2012 either more than 1 6,000 tons of SO 2 or more than 2,600 tons
of SO 2 and had an annual average emission rate of at leas t 0.45 pounds of SO 2 per one million British thermal units (lbs SO 2 /mmBTU). Specifically, in 2012, the IPL Ottumwa ele ctric generating facility emitted 11,985 tons of SO 2 and had an emissions rate of 0.666 lb
SO 2 /mmBTU. As of March 2, 2015, this stationary source had not met the specific requirements for being “announced for retirement.” Pursuant to t he March 2, 2015, court-ordered schedule, the EPA must designate the area surrounding the facilit y by July 2, 2016.

In its submission, IDNR recommended that the area s urrounding the IPL Ottumwa Electric Generating Facility, specifically the entirety of W apello 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 ar ea of analysis where maximum
concentrations of SO 2 are expected. This assessment and characterization was performed using air dispersion modeling software, specifically AERM OD, analyzing allowable emissions. After careful review of the state’s assessment, supportin g documentation, and all available data, the EPA does not agree with the state’s recommendation for the area and intends to designate the area as unclassifiable, based on the timing of new proposed emission limits used in IDNR’s IPL Ottumwa modeling analysis.

The IPL Ottumwa Facility is located in southeastern Iowa in the northwest portion of Wapello County. As seen in Figure 11, the IPL Ottumwa facil ity is located along the Des Moines River approximately 8 km northwest of the community of Ot tumwa, Iowa (pop. ~25,000). Also, Figure
11 shows the state’s recommended area for the attai nment designation and the EPA’s intended unclassifiable designation for the area.34

Figure 11: Location of the IPL Ottumwa Facility lab eled in red and the nearby CargillEddyville Facility labeled in blue.

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

Air Quality Data

This factor considers the SO 2 air quality monitoring data in the area surroundin g the IPL Ottumwa facility. Since no SO 2 ambient monitors were located in Wapello County, n o monitoring data was relied upon in EPA’s proposed d esignation for this area.

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 the35

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 version available at the time of modeling analysis. A discussion of the individual c omponents 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 with 3 km of 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. As previously mentioned, the facility is located along the Des Mo ines River and the rural determination was
made based on the land cover around the IPL Ottumwa Facility.

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 IPL Ottumwa Facility is to determin e the extent of the area of analysis, i.e., 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 state performed an analysis to locate any addit ional major sources of SO 2 within 20 km of IPL Ottumwa. For the IPL Ottumwa area, the state ev aluated one additional emitter of SO 2 that is within 20 km of IPL Ottumwa Facility in any directi on (Cargill - Eddyville). The state did not include Cargill – Eddyville in its modeling analysi s of IPL Ottumwa, and further discussion of this source is provided in the Modeling Parameter: Emissions Section of this TSD.

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

- 50 meters along the IPL Ottumwa Facility fenceline

- 50 meters from the fenceline to 0.5 km

- 100 meters extending from 0.5 km to 1.5 km

- 250 meters extending from 1.5 km to 3.0 km36

- 500 meters extending from 3.0 km to 5.0 km

The receptor network contained 3,955 receptors and covered the western portion of Wapello County in Iowa.

Figure 12, included in the state’s recommendation, shows the state’s chosen area of analysis surrounding the IPL Ottumwa Facility, as well as th e receptor grid for the area of analysis. Consistent with the Modeling TAD, receptors for the purposes of this designation effort were placed only in areas where it would also be feasibl e to place a monitor and record ambient air impacts. The impacts of the area’s geography and to pography will be discussed within this
document.

As previously noted in this Section, the state used a modeling grid extending out to 5.0 km, which is less than the 20 km area of analysis used to evaluate nearby sources. No other significant SO 2 sources were modeled. EPA does have concerns with the relative small size of the 5 km receptor grid, although modeling results f or IPL Ottumwa shown in Figure 15 indicate that this 5 km grid likely contains the area of max imum concentrations. However, based on this uncertainty and other issues identified in this TSD , EPA is recommending an unclassifiable designation for Wapello County, Iowa.

Figure 12: Receptor Grid for the IPL Ottumwa Facili ty Area of Analysis37

Modeling Parameter: Source Characterization

The state characterized the sources within the area of analysis in accordance with the practices outlined in the Modeling TAD as acceptable. Specifi cally, the state used actual stack heights in conjunction with allowable emissions limits. Actual stack heights were modeled with allowable
emission limits in this case since the actual stack heights were below the GEP stack height. The state also adequately characterized the IPL Ottumwa Facility building layout and location, as well as the stack parameters, e.g., exit temperatur e, exit velocity, location, and diameter. Where appropriate, the AERMOD component BPIPPRIME was use d 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 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 IPL Ottumwa and one other significant emitter of SO 2 within 20 km in the area of analysis. The state dee med this 20 km distance appropriate because the state believes that the area of analysis descri bed above adequately includes the sources which might contribute to those concentrations.

The other nearby SO 2 source, Cargill – Eddyville, is approximately 15 k m to the northeast of IPL Ottumwa. Cargill – Eddyville had SO 2 emissions greater than 1,500 tons each year from 2 012-38

2014. IDNR states that the Cargill – Eddyville faci lity replaced its coal-fired boilers with natural gas boilers in 2015, thus reducing SO 2 emissions from this facility by over 99%. Therefor e, IDNR did not include Cargill – Eddyville in it mode ling analysis.

Table 11 lists the actual emissions from the IPL Ot tumwa Facility from 2012-2014. The
emissions data were obtained from EPA’s Clean Air M arkets Division for the purposes of this TSD. The state, however, has chosen to model the fa cility based on PTE that reflect new allowable emission limits that are not currently fe derally enforceable. The proposed emission
limit for the main IPL Ottumwa coal utilization boi ler is listed in Table 12. In addition, IDNR
states that “Construction permit modifications will be made to enforce the new emission limits once EPA approves the modeling results”. EPA Region 7 has discussed the timing of the issuance of this permit modification with IDNR but the permit modification has not yet been
issued and it is not clear if the new emission limi t will be effective by July 2, 2016.

Table 11: Actual SO 2 Emissions in 2012 – 2014 from Facilities in the IP L Ottumwa Facility Area of Analysis

Facility Name SO 2 Emissions (tons per year)

2012 2013 2014 IPL Ottumwa Generating Station 11,985 13,126 9,227 Cargill – Eddyville 1,627 1,772 1,577
Total Emissions 13,612 14,898 10,804

Table 12: SO 2 Emissions based on proposed PTE for IPL Ottumwa Ge nerating Station in the Wapello County, Iowa, Area of Analysis

Company ID Facility Name SO 2 Emissions (lb/hr), based on PTEs

IPL Ottumwa Facility

(Main Boiler) 1,734

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 if actual emissions are used) should be used in designations efforts. As noted in the Modeling TAD, the selection of data should be b ased on spatial and climatological (temporal) representativeness. The representativene ss of the data are based on: 1) the proximity of the meteorological monitoring site to the area u nder 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 inclu de NWS stations, site-specific or onsite data, and other sources such as universities, FAA, and mi litary stations.

For the IPL Ottumwa area of analysis, surface meteo rology from the NWS station in Ottumwa, Iowa, approximately 8 km to the southeast, and coin cident upper air observations from the NWS39

station in Davenport, Iowa, approximately 120 km to the northeast were selected as best representative of meteorological conditions within the area of analysis (Figure 13).

The state used AERSURFACE version 13016 using data from the NWS station in Ottumwa, Iowa, located at 41.11N, 92.45W to estimate the sur face characteristics of the area of analysis. The state estimated values for 12 spatial sectors a t a monthly temporal resolution. AERSURFACE was processed three times, once each for dry, average, and wet surface moisture conditions. The output for the individual months fr om the three AERSURFACE runs were then manually combined into one output file. The state a lso 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 sub stance), and the surface roughness (sometimes referred to as “Zo”). In the figure below, generate d by the EPA, the location of the Ottumwa, Iowa, NWS station and Davenport, Iowa, upper air st ation is shown relative to the IPL Ottumwa area of analysis.

Figure 13: IPL Ottumwa Area of Analysis and the Ott umwa, Iowa, surface site and

Davenport, Iowa, NWS upper air location

As part of its recommendation, the state provided t he 3-year surface wind rose for Ottumwa, Iowa. In Figure 14, the frequency and magnitude of wind speed and direction are defined in40

terms of from where the wind is blowing. Winds at t he Ottumwa NWS site are predominately
from the northwest and south.

Figure 14: Ottumwa, Iowa, Cumulative Annual Wind Ro se 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 EPA’s Modeling TAD for area designations under the 2010 SO 2 NAAQS in the processing of the raw meteorological data into an AERMOD-ready format, an d 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 produce a more complete set of concentration estimates. As a guard against excessively high conc entrations that could be produced by41

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 2013 EPA memo titled, “Use of ASOS meteorol ogical 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 relatively flat as the IPL Ottumwa facility lies along the Des Moines River in southeast Iowa. To account for these terrain changes, the AERMAP terrain program within AERMOD was used to sp ecify terrain elevations for all the receptors. The source of the elevation data incorpo rated into the model is 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 IPL Ottumwa area of analysis, IDNR chose th e “first tier” approach but derived a statewide default background concentration using an average of the concentrations of four monitors using 2009-2011 data. The derived average background concentration was based on monitors from the following four cities in Iowa: Ce dar Rapids, Davenport, Des Moines, and Keosauqua. While the averaging of multiple monitors is not outlined in the Modeling TAD, EPA Region 7 believes that this methodology provides a conservative background concentration for the IPL Ottumwa area, which is located in rural sou th central Iowa. In contrast, the four monitors used in the average background concentration are lo cated near higher populated areas and other
sources of SO 2 emissions. In fact, IDNR no longer uses this avera ging technique for sources in rural areas for this reason. IDNR is now using the Lake Sugema monitor for sources in rural
areas since this monitor is located in a rural area . The Lake Sugema monitor has a design value of 7 μg/m 3 , which is much lower than the background design va lue proposed in this analysis 14

. In summary, the background concentration for this a rea of analysis was determined by the state using the described “first tier” multiple monitor a veraging technique to be 32 micrograms per cubic meter ( μ g/m 3 ), or 12.2 ppb, 15 and that value was incorporated into the final AER MOD
results.

Summary of Modeling Results

14 http://www.iowadnr.gov/Portals/idnr/uploads/air/dis pmodel/background_concentrations_tsd.pdf

15 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

.42

The AERMOD modeling parameters for the Ottumwa area of analysis are summarized below in
Table 13.

Table 13: AERMOD Modeling Parameters for the IPL Ot tumwa, Iowa, Area of Analysis

Ottumwa, Iowa, Area of Analysis

AERMOD Version 14134 Dispersion Characteristics Rural

Modeled Sources 2

Modeled Stacks 1

Modeled Structures N/A

Modeled Fencelines 1 Total receptors 3,955

Emissions Type PTE based on proposed
emission limits

Emissions Years EPA inferred that new proposed limits on the IPL
Ottumwa main boiler will likely take effect in 2016. However, in a December 23, 2015 updated
recommendation from the state, the emission limits will not be included in a permit. Meteorology Years 2012-2014 Surface Meteorology Station Ottumwa, Iowa Upper Air Meteorology Station Davenport, Iowa Methodology for Calculating Background SO 2 Concentration Statewide default from
monitors Calculated Background SO 2 Concentration 32 μ g/m 3

The results presented below in Table 14 show the ma gnitude and geographic location of the highest predicted modeled concentration based on pr oposed PTE emissions.

Table 14: Maximum Predicted 99 th Percentile 1-Hour SO 2 Concentration in the IPL Ottumwa, Iowa, Area of Ana lysis Based on PTE 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 537343.2 4549206.1 89.7 19 6.5* *Equivalent to the 2010 SO 2 NAAQS set at 75 ppb43

The state’s modeling indicates that the predicted 9 9 th percentile 1-hour average concentration within the chosen modeling domain is 89.7 μ g/m 3 , or 34.5 ppb. This modeled concentration
includes the background concentration of SO 2 , includes the emissions from Cargill – Eddyville combusting natural gas, and is based on the propose d PTE emissions from the facility. Figure 15 below was included as part of the state’s recommend ation and indicates that the predicted value occurred to the south of the IPL Ottumwa facility. The state’s receptor grid is also shown in the figure.

Figure 15: Maximum Predicted 99 th Percentile 1-Hour SO 2 Concentrations in the IPL Ottumwa Area of Analysis Based on proposed PTE Emission. Location of the Ottumwa emission units are shown by the red circles . The maximum Predicted 99 th Percentile 1-Hour is 89.7 μg/m 3 located just to the west of the IPL Ottumwa Facili ty.

Jurisdictional Boundaries:44

Once the geographic area of analysis associated wit h the IPL Ottumwa Facility is determined, existing jurisdictional boundaries are considered f or the purpose of informing our intended unclassifiable area, specifically with respect to c learly defined legal boundaries.

IDNR recommended an attainment area boundary consis ting of the entirety of Wapello County. There are only three additional Title V sources wit hin the county, none of which emit more than 12 tpy of SO 2 . All minor sources in this rural county are believ ed to be adequately represented by the background concentration used in the modeling.

The EPA believes that our intended unclassifiable a rea, consisting of all of Wapello County in Iowa, has clearly defined legal boundaries and we f ind these boundaries to be a suitably clear basis for defining our intended unclassifiable area

.

Other Relevant Information

The EPA did not receive any additional information for the area in the immediate vicinity of IPL
Ottumwa.

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 IPL Ottumwa Generating Facility as unclassifiable for the 2010 SO 2 NAAQS. Specifically, the boundaries are comprised of entirety of Wapello County, Iowa.

The unclassifiable designation is based on the unce rtain timing of proposed allowable emission limits on the IPL Ottumwa Generating Facility’s mai n boiler, specifically the lack of indication that the emission limits will be federally enforcea ble by the July 2, 2016, court-ordered deadline to designate the area. The modeling provided by IDN R using the proposed emission limits shows attainment. The modeling performed by IDNR followed the recommended EPA modeling TAD for designation purposes. However, since the propos ed emission rates that were used in IDNR’s modeling analysis are not federally enforceable, IP L Ottumwa could emit at a rate that was higher than the rate that was modeled and that coul d affect the resulting modeled concentrations. Therefore, EPA is proposing an unclassifiable desig nation. Should IDNR submit additional information documenting that the limits used in the modeling represent federally enforceable limits and adequately address the receptor grid dis tance, EPA believes the modeling would support an unclassifiable/attainment designation.

For the reasons described above, EPA is unable at t his time, based on available information, to determine whether the area is meeting or not meetin g the NAAQS.

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 Iowa by either December 31, 2017, or December 31, 2 020.