### 1 Technical Support Document (TSD)

for the Cross

- State Air Pollution Rule for the 2008 Ozone NAAQS

Docket ID No. EPA

- HQ

- OAR

- 201 5

- 0 5 0 0



# Ozone Transport Policy Analysis

Proposed Rule TSD

U.S. Environmental Protection Agency

Office of Air and Radiation

November 201 5

### 2

This Technical Support Document (TSD) provides information that supports EPA’s

proposal to update the Cross

- State Air Pollution Rule (CSAPR) to address the 2008 ozone

National Ambient Air Quality Standards (NAAQS). This TSD includes analysis to quantify

upwind state emissions that significantly contribute to nonattainment or interfe re with

maintenance of the NAAQS in downwind states ; quantification of emissions budgets (i.e., limits

on emissions); and illustrative analysis to evaluate compliance with the regulatory control

alternatives . The analysis is described in detail in the pre amble to the proposed rule. This TSD

is organized as follows:

A. Background on EPA’s Analysis to Quantify Emissions that Significantly Contribute to

Nonattainment or Interfere with Maintenance of the 2008 ozone NAAQS

B. Electric Generating Unit Signifi cant Contribution Cost Analysis

C. Analysis of Significant Contribution Using an Ozone Air Quality Assessment Tool

1. Introduction: Development of the assessment tool

2. Details on the construction of the assessment tool

3. Description of the results of the analysis using the assessment tool for the approach

A. Background on EPA’s Analysis to Quantify Emissions that Significantly Contribute to

Nonattainment or Interfere with Maintenanc e of the 2008 ozone NAAQS

In the preamble, we describe EPA’s multi

- step process to identify upwind states’

emissions that significantly contribute to nonattainment or interfere with maintenance with

respect to the 2008 ozone NAAQS. This approach is consistent with the approach used in

CSAPR. See section III of the preamble for an overview of this approach.

T he approach first uses air quality analysis to identify nonattainment and maintenance

receptors with respect to interstate transport for the 2008 ozone NAAQS. The approach then uses

further air quality analysis to identify upwind states whose ozone pollution contributions to these

monitoring sites meet or exceed a specified threshold amount of 1% of the NAAQS. See section

V of the preamble for details of applying these steps with respect to interstate emissions transport

for the 2008 ozone NAAQS.

The next step in the process identifies the EGU NO

x 

### reductions in each state in response

to ascending uniform NO X 

### cost thresholds. See section B in this TSD for discussion of this

analysis. Next, the process uses the ozone Air Quality Assessment Tool ( AQAT ) to estimate the

impact of the upwind state EGU NO

x 

### reductions on downwind ozone pollution levels for the

assessed EGU NO

x 

### cost

- per

- ton levels. See section C in this TSD for discussion of the

development and use of the ozone AQAT.

As described in the preamble, the EPA uses this air quality information in a multi

- factor

test, along with EGU NO

x 

### reductions and costs, to select a cost threshold to quantify each state’s

significant contribution to nonattainment and inte rference with maintenance. The cost threshold

assessment evaluates EGU NO

x 

### mitigation potential for all states in the contiguous U.S.

However, the EPA only evaluates EGU NO

x 

### reductions in the multi

- factor test from states that

### 3

were “linked” and which hav e EGU NO

x 

### reduction potential in at least one of the evaluated EGU

NO

x 

### cost thresholds. These states are listed in Table A

- 1 below. As described in preamble

section VII, Delaware is “linked” to downwind ozone problems but is not currently regulated

under CSAPR and does not have any EGU NO

x 

### reduction potential at any of the cost thresholds

evaluated. Therefore, the EPA is not proposing to include Delaware in the proposal and the EPA

did not include Delaware in applying the multi

- factor test.

Table A

- 1. States Evaluate d in the

Multi

- factor Test

Ozone Season NO

x



### Alabama New Jersey

Arkansas New York

Illinois North Carolina

Indiana Ohio

Iowa Oklahoma

Kansas Pennsylvania

Kentucky Tennessee

Louisiana Texas

Maryland Virginia

Michigan West Virginia

Mississippi Wisconsin

Missouri

A set of Excel spreadsheet files containing ozone AQAT data supporting the

determination of emissions that constitute significant contribution to nonattainment and

interference with maintenance of downwind air quality is available in the docket for this

rulemaking. Appendix B in this TSD describes these files.

B. Electric Generating Unit Significant Contribution Cost Analysis

EPA used the Integrated Planning Model (IPM) to analyze the ozone

- season NO

x 

### emissions reductions available from electric generating units (EGUs) at various uniform cost

levels in each upwind state. IPM was also used to evaluate illustrative compliance with the

proposal’s regulatory control alternatives (i.e., compliance with th e proposed emissions budgets

, with a more stringent alternative, and with a less stringent alternative).

IPM is a multiregional, dynamic, deterministic linear programming model of the U.S.

electric power sector that EPA uses to analyze cost and emissions impacts of environmental

policies. See “Documentation for EPA Base Case v.5.13 Using the Integrated Plann ing Model”,

“EPA Base Case v.5.14 Using IPM Incremental Documentation. March 25, 2015”, and “EPA

### 4

Base Case v.5.15 Using IPM Incremental Documentation. August, 2015” for further description

of the IPM model

. 1



### Using IPM, the EPA first modeled a base case EGU emissions scenario (i.e., a scenario

absent any emission reduction requirements related to this rule). The base case modeling

includes the Title IV SO 2 

### cap and trade program; NO

x 

### SIP Call regional ozone season cap and

trade program; the CSAPR regional ca p and trade programs; settlements; and state and federal

rules as listed in the IPM documentation referenced above.

The air quality modeling for this proposal, including identifying nonattainment and

maintenance receptors, performing contribution analysis, and modeling an illustrative control

case relied on IPM v5.14. After the modeling analyses were underway, the EPA released an

updated IPM base case, version 5.15, and the final Clean Power Plan (CPP). In order to reflect

all on

- the

- books policies as well as the most current power sector modeling data, the EPA

performed an assessment (described in this TSD) to reflect inclusion of IPM 5.15 with the CPP

for this proposal. 2



### EPA modeled the emissions reductions that would occur within each state first from

mov ing from the IPM v5.14 base case to the IPM v5.15 base case, and then from applying

ascending cost thresholds of emissions control based on IPM v5.15 cost threshold scenarios

. EPA designed a series of IPM runs that imposed increasing cost thresholds for o zone

- season

NO

x 

### emissions and tabulated those projected emissions for each state at each cost level. EPA

has referred to these tabulations as “cost curves”. 3 

### The cost curves report the remaining

emissions at each cost threshold after the state has made e mission reductions that are available

up to the particular cost threshold analyzed.

This part of the analysis applied ozone

- season cost thresholds to all fossil

- fuel

- fired

EGUs with a capacity greater than 25 MW in each state. Because of the time require d to build

advanced pollution controls, the model was prevented from building any new post

- combustion

controls, such as SCR or SNCR in 2017 in response to the cost thresholds. 4 

### The modeling does

allow the turning on of idled existing SCR and SNCR, the opt imization of existing SCR and

SNCR, shifting generation to lower

- NO X 

### emitting EGUs, and addition or upgrading of NO

x 

### combustion controls in 2017, such as low NO

x 

### burners (LNB).

In these scenarios, EPA imposed cost thresholds ranging from $500 per ton to $1 0,000

per ton of ozone

- season NO

x 

### . The IPM

- projected EGU emissions of ozone

- season NO

x 

### from the

1 http://www.epa.gov/airmarkets/powersectormodeling

2 C hanges between IPM v5.14 and v5.15 are documented in "EPA Base Case v. 5.15 Using IPM Incremental

Documentation. August, 2015" available in the docket for this rule.

3 These projected state level emissions for each “cost threshold” run are presented in several formats. The IPM

analysis outputs available in the docket contain a “state emissions” file for each analysis. The file contains two

worksheets. The first is tit led “all units” and shows aggregate emissions for all units in the state. The second is titled

“all fossil > 25MW” and shows emissions for a subset of these units that have a capacity greater than 25 MW. The

emissions in the “all fossil > 25 MW” workshee t are used to derive the budgets for each upwind state at the cost

thresholds determined to eliminate significant contribution to nonattainment or interference with maintenance in

linked downwind states, in an average year.

4 IPM results do include newly built 2017 post

- combustion pollution control retrofits in base case modeling, cost

curve runs, and remedy runs. These 2017 retrofits do not reflect any controls installed in response to the rule, but

instead represent those that are already announced and /or under construction and expected to be online by 2017, or

controls that were projected to be built in the base case in response to existing consent decree or state rule

requirements.

### 5

“Fossil > 25 MW” units and “All Units” are shown at each cost threshold for 2017 5 

### in Tables B

1 and B

- 2. 6 

### For more information about EPA’s adjustment of IPM outputs to reflect 2017,

please see Appendix C

. As described in Preamble section VI, the EPA limited generation shifting potential to

units within each state in IPM as an analytic proxy designed to respec t the feasibility of near

term generation shifting in light of these potential near

- term out

- of

- merit order dispatch

constraints. The EPA conducted a separate analysis similar to the $1,300 per ton cost threshold

scenario, except without limiting IPM’s abi lity to shift generation between states. That analysis,

described in detail Appendix F, showed a minimal impact on the overall tons of reductions

available at the $1,300 per ton cost threshold ( 1

, 686 tons in the proposed Transport Rule states )

and a minima l impact on state budgets (the largest percent change was a less than 3% decrease)

. As e xplained in preamble section VI, EPA determined that $500/ton was the appropriate

lowest cost threshold for ozone

- season NO

x 

### control for all potentially covered states in this

rulemaking. EPA then used the ozone AQAT to identify improvements in downwind air quality

at $500 per ton and, then, for the higher cost thresholds when that level did not completely

resolve all nonattainment and maintenance to which each state w as “linked”. EPA examined

cost levels of $500/ton, $1,300/ton, $3,400/ton, $5,000/ton, $6,400/ton, and $10,000/ton as a

representative sampling of points along the NO

x 

### cost curve. EPA selected these particular cost

levels because analysis suggested they were associated either with costs when particular

emission controls were widely available, reflected the costs examined for other EPA rules (e.g.,

$6,400/ton), or served as an upper

- bound of the cost curve analysis (e.g., $10,000/ton).

At each cost thresh old examined with the IPM model, the model outputs include state emission

totals from “All Units” as well as from “All fossil > 25 MW”. The “All Fossil > 25 MW” totals

represent an approximation of emissions from EGUs subject to this rule. The resulting state

ozone season NO

x 

### emissions levels from “All Units” at each cost threshold analyzed were

examined in the ozone AQAT to determine the impact on downwind air quality. The preamble

explains how EPA considered the results of the cost and air quality anal yses described in this

TSD to determine the appropriate set of cost thresholds for reducing significant contribution to

nonattainment and interference with maintenance. Because there are slight differences in the

units labeled as “EGUs” in the air quality modeling and the “All Units” from IPM, in the ozone

AQAT EPA used the difference in emissions between the base case emissions and the other cost

5 See section 2.3.3 “Documentation for EPA Base Case v.5.13 Using the Integrated Planning Model” for a

description about IPM model run years. Each year in the future is mapped to one of seven modeled years. While

2017 is mapped to the “2016” run year, for this analysis, EPA started with the 2018 run year and made small

mo difications to emissions to simulate 2017. Specifically, individual units that may be retiring, converting to gas, or

retrofitting NO

x controls in 2018 were adjusted to match their expected operation in 2017. This approach provided a

better estimate than using the “2016” run year because that run year would not capture similar fleet changes

expected to occur before 2017. Additionally, it provides a better projection of allowance banking behavior, as the

model would have two years to bank ozone

- season NO

x allowances in the CSAPR ozone

- season NO

x Phase 1

period, which matches the real world timeline.

6 EPA notes that, while ozone

- season emissions generally decline as the cost threshold increases, there are instances

where a state may see a small increase in emissions at a higher cost threshold compared to a lower cost threshold

analyzed. This is related to the interconnected, interstate nature of the grid, and the ability of generation to shift

from a less efficient/higher emitting source in one state to a more efficient/lower emitting source in another state at

higher cost levels. In other words, as multiple states experience the higher cost threshold on ozone

- season NO

x , a

region may minimize cost by dispatching more generation from lower

- emitting

- rate un its in a particular state that

counterintuitively raise that state’s total ozone

- season NO

x emissions, even as the regional ozone

- season NO

x emissions decline as a result.

### 6

thresholds from “All Units”. The emission differences are shown in Table B

- 3. To construct

total emissions f

or use in ozone AQAT , these differences were added to the total base case ozone

season anthropogenic NO

x 

### emissions used in the air quality modeling.

As described in the preamble, EPA developed state EGU NO

x 

### emissions budgets for each

of the three regulator y control alternatives. First, EPA calculated each covered state’s IPM

ozone

- season NO

x 

### emission rate (i.e. lbs NO

x 

### /MMBtu) from the $500, $1,300, and $3,400 per

ton uniform cost threshold assessment. The state

- level rate was calculated as the total emissions

from affected sources within the state, divided by the total heat input from these sources.

Second, the EPA multiplied this modeled state

- level emissions rate by 2014 reported

historic al state

- le vel heat input. Multiplying the projected state

- level emissions rate by historical

heat input yielded state

- specific ozone season EGU NO X 

### emissions. While the Energy

In formation Admini stration’s Annual Energy Outlook projects a slight increase in national

generation from 2014 to 2017, it projects generation from fossil sources to decrease slightly (

- 0.4%). As electricity generation from fossil sources is projected to be almost unchanged from

2014 to 2017, the EPA did not adjust the 2014 heat input to calcul ate state

- specific ozone season

EGU NO X 

### emissions.

Third, the EPA added an adjustment to account for differences in unit and SCR

availability and operation between the IPM run year of 2018 and the expected conditions

applicable to calendar year 2017 7



### . Ap pendix C explains the 2017 adjustments and shows the

adjustments made by model plant.

Fourth , the EPA select ed EGU emissions budgets as the lower of this calculated 2017

emission level and the 2014 historic monitored emissions. EPA conducted this analysis, and

estimated a resulting “budget” of emissions, for 37 states and the District of Columbia in the

Eastern U.S.

, whether or not this proposal would subject a given state to its emission budget

estimated here. The state

- level e mission rate from IPM, the 2014 historic heat input, and the

resulting ozone

- season NO

x 

### EGU emissions budgets are shown in Table B

- 4.

Finally, the EPA calculated the variability limits and assurance levels for each state based on the

calculated emissions budgets. Each state’s variability limit is 21% of its budget, and its assurance

level is the sum of its budget and variability limit , shown in Table B

- 5. Under the methodology

established in the final Transport Rule, the state

- specific portion of the NUSA (including the

Indian Country NUSA) is calculated as the percentage equal to the projected emissions from

“planned units” divided by the state budget plus a base two percent. The calculated existing unit

al location and new unit set aside (NUSA), including the Indian Country NUSA, for the proposed

budgets is shown in table B

- 6. 8



### As explained in the preamble, EPA proposes to promulgate EGU NO

x 

### ozone

- season

emissions budgets reflecting the uniform cost threshold of $1 ,300/ton to reduce significant

contribution to nonattainment and interference with maintenance.

The IPM runs performed for the cost analys es are listed in Table Appendix A

- 1 in of this

TSD. Table Appendix A

- 1 lists the name of each IPM run next to a description of the run. The

outpu t files of these model runs can be found in the rulemaking docket. In Tables B

- 1 through

7 In modeling the three regulatory control alternatives in IPM, EPA did not includ e the 2017 budget adjustments.

This allowed EPA to accurately understand the policy impacts of the regulatory alternatives for two reasons. First,

the 2017 adjustments account for emissions that IPM does not have included in the 2018 run year. Including th e

adjustments would artificially inflate the 2018 cap since it would be adding in allowances that the model did not

need. Second, using the 2018 model run year for analysis allowed units two years to use and bank allowances,

matching the time that these un its will have to use and bank allowances under CSAPR Phase 1.

8 See ‘ O3 NAAQS CSAPR Update

-- NUSA Calculations’ (Excel spreadsheet) in the docket for this proposal.

### 7

B

- 4

, the emissions are presented rounded to the nearest ton. A summary of the budgets and

assurance levels can be found in Appendix D and detailed calculations can be found in Appendix

E

. As noted above, EPA used the emissions shown in Table B

- 3 as input s to the air quality

assessment tool to estimate the impact that the combined reductions available from states

covered under the proposal to update CSAPR , at different cost

- per

- ton levels, would have on air

quality at downwind monitors that were identified as nonattainment and/or maintenance

receptors for this proposal. Section C in this TSD describes EPA’s development and use of the

assessment tool and the results fro m our analysis.

### 8

Table B

- 1 . 2017 Ozone Season NO

x 

### EGU Emissions* for Each State at Various

Pollution Control Cost Thresholds (CT) per Ton of Reduction (Tons) “Fossil >25 MW”.

*Source: Integrated Planning Model run by EPA, 2015. See Appendix A for list and description of these IPM runs. Emissions have been

rounded to the nearest ton. Emissio ns shown for all fossil

- fired units greater than 25 MW when only an ozone season cost constraint is applied.

Costs are in 201 1 $. 5.14 Base

Case 5.15 Base

Case $500/ton

CT $1300/ton

CT $3400/ton

CT $5000/ton

CT $6400/ton

CT $10000/ton

CT Less

Stringent

Control

Alternative Proposed

Emissions

Budgets More

Stringent

Control

Alternative

Alabama 11,821 13,289 11,560 9,708 9,620 8,509 7,871 7,450 11,792 10,182 10,221

Arizona 20,695 16,823 16,823 10,758 11,012 10,895 10,875 10,787 16,838 16,837 16,838

Arkansas 11,767 6,224 6,211 6,120 5,365 5,076 4,982 4,289 6,239 6,239 6,361

California 1,799 1,723 1,722 1,721 1,715 1,718 1,718 1,603 1,723 1,723 1,723

Colorado 14,369 13,000 12,999 12,964 12,316 12,051 11,619 10,888 13,000 13,000 13,000

Connecticut 382 409 408 408 381 362 362 336 408 408 408

Delaware 285 477 477 477 477 477 477 473 477 477 477

District of Columbia 0 0 0 0 0 0 0 0 0 0 0

Florida 28,786 25,345 24,138 18,812 18,200 18,052 17,626 17,410 25,584 25,733 25,769

Georgia 9,432 7,394 7,275 7,157 7,055 6,968 6,937 6,968 7,397 7,406 7,412

Idaho 0 42 36 36 35 35 35 35 43 39 41

Illinois 15,323 10,021 9,626 9,549 9,475 9,399 9,381 9,260 9,772 9,760 9,749

Indiana 43,122 41,748 35,137 29,575 28,759 27,978 28,310 24,639 35,095 30,285 30,270

Iowa 8,629 7,911 7,725 7,488 7,194 7,194 7,194 6,594 7,757 7,539 7,539

Kansas 11,434 11,332 10,904 10,894 10,867 10,654 10,494 10,182 10,904 10,904 10,904

Kentucky 38,933 27,141 23,533 15,245 14,759 14,668 13,685 12,638 24,143 15,916 15,966

Louisiana 13,662 10,897 10,833 10,780 10,497 10,436 10,430 10,191 10,900 10,812 10,807

Maine 222 261 261 261 261 253 249 248 261 261 261

Maryland 4,317 6,470 5,442 5,444 5,307 5,294 5,102 5,102 5,279 5,285 5,156

Massachusetts 652 863 912 874 860 825 754 699 866 866 863

Michigan 29,743 20,049 19,646 17,016 16,520 16,293 16,160 15,638 19,875 18,437 18,437

Minnesota 9,579 9,275 9,196 8,999 8,779 8,729 8,672 7,597 9,278 9,278 9,278

Mississippi 8,549 7,871 7,789 7,574 6,978 6,706 6,392 5,663 7,360 7,151 6,639

Missouri 18,495 17,050 16,116 16,054 15,897 15,752 15,120 14,275 16,144 16,180 16,218

Montana 8,498 7,756 7,743 7,743 7,743 7,719 7,719 7,719 7,756 7,756 7,756

Nebraska 14,164 14,173 14,173 13,770 10,921 10,742 10,284 9,248 14,173 14,173 14,173

Nevada 4,055 4,410 4,395 4,393 3,186 3,021 2,447 1,690 4,409 4,409 4,409

New Hampshire 140 140 140 140 140 139 139 138 140 140 140

New Jersey 3,980 3,302 2,932 2,931 2,924 2,921 2,918 2,837 2,439 2,438 2,433

New Mexico 17,248 17,356 17,356 16,848 16,850 16,721 16,272 15,989 17,356 17,356 17,356

New York 6,419 4,948 4,833 4,664 4,589 4,578 4,287 4,042 4,908 4,712 4,714

North Carolina 19,753 14,435 12,513 12,513 10,909 10,809 10,020 9,792 12,468 12,468 11,342

North Dakota 23,037 16,423 16,423 13,078 13,054 12,743 12,480 12,430 16,246 16,246 16,246

Ohio 27,785 27,795 22,049 18,149 18,129 18,022 17,718 17,564 22,050 18,369 18,369

Oklahoma 24,327 19,593 18,891 17,423 16,425 15,772 13,891 12,984 19,587 18,076 18,087

Oregon 212 0 0 0 0 0 0 0 0 0 0

Pennsylvania 50,517 41,661 39,451 14,902 14,870 14,748 14,729 14,657 40,466 15,152 15,150

Rhode Island 150 199 199 202 199 199 199 199 196 197 198

South Carolina 5,998 5,678 4,622 4,542 4,505 4,497 4,494 4,447 5,815 5,845 5,847

South Dakota 653 297 297 297 297 297 297 297 297 297 297

Tennessee 6,369 5,554 5,480 5,441 5,408 5,329 5,312 5,269 5,480 5,480 5,481

Texas 64,959 58,199 57,513 54,589 52,389 51,259 50,427 49,819 58,227 56,145 56,188

Utah 25,153 24,482 24,482 21,011 21,011 20,071 19,839 18,984 24,482 24,482 24,482

Vermont 3 3 3 3 3 3 3 3 3 3 3

Virginia 8,130 7,196 6,773 6,656 5,609 4,092 3,636 3,586 7,247 6,877 6,906

Washington 146 136 136 136 136 136 136 70 136 136 136

West Virginia 25,326 25,384 24,792 14,475 13,369 13,173 13,141 13,141 24,792 14,475 13,369

Wisconsin 8,214 5,257 5,252 5,221 5,150 5,126 4,981 4,639 5,251 5,251 5,251

Wyoming 14,281 10,796 10,724 10,167 9,258 9,244 8,810 8,334 10,796 10,796 10,796

Nationwide 661,514 570,787 539,942 457,206 439,404 397,120 386,293 367,409 511,907 486,000 451,848

### 9

Table B

- 2 . 2017 Ozone Season NO

x 

### EGU Emissions* for Each State at Various

Pollution Control Cost Thresholds (CT) per Ton of Reduction (Tons) “All Units”.

*Source: Integrated Planning Model run by EPA, 2015. See Appendix A for list and description of these IPM runs. Emissions have been

rounded to the nearest ton. Emissions shown for all fossil

- fired units greater than 25 MW when only an ozone season cost constraint is applied.

Costs are in 2011$. 5.14 Base

Case 5.15 Base

Case $500/ton

CT $1300/ton

CT $3400/ton

CT $5000/ton

CT $6400/ton

CT $10000/ton

CT Less

Stringent

Control

Alternative Proposed

Emissions

Budgets More

Stringent

Control

Alternative

Alabama 12,151 13,592 11,863 10,015 9,944 8,846 8,219 7,797 12,095 10,486 10,531

Arizona 20,835 16,960 16,961 10,895 11,150 11,032 11,012 10,924 16,975 16,975 16,975

Arkansas 11,890 6,399 6,386 6,295 5,624 5,335 5,254 4,560 6,414 6,414 6,536

California 4,122 3,789 3,789 3,788 3,781 3,786 3,785 3,670 3,789 3,789 3,789

Colorado 14,897 13,467 13,467 13,444 12,835 12,584 12,176 11,541 13,467 13,467 13,467

Connecticut 1,587 1,607 1,607 1,610 1,589 1,570 1,570 1,544 1,607 1,607 1,607

Delaware 388 580 580 580 580 580 580 576 580 580 580

District of Columbia 0 0 0 0 0 0 0 0 0 0 0

Florida 33,539 30,046 28,840 23,522 22,968 22,820 22,397 22,190 30,284 30,433 30,469

Georgia 9,535 7,498 7,378 7,260 7,159 7,072 7,041 7,072 7,501 7,510 7,516

Idaho 206 251 244 245 245 246 246 246 252 248 249

Illinois 15,810 11,002 10,627 10,564 10,493 10,427 10,415 10,295 10,773 10,761 10,750

Indiana 43,910 42,496 35,885 30,374 29,590 28,811 29,143 25,797 35,843 31,033 31,018

Iowa 9,364 8,307 8,190 7,951 7,913 7,913 7,940 7,342 8,153 7,935 7,935

Kansas 11,694 11,820 11,393 11,424 11,602 11,426 11,393 11,766 11,393 11,393 11,393

Kentucky 38,993 27,201 23,593 15,306 14,848 14,756 13,774 12,726 24,203 15,976 16,027

Louisiana 13,925 11,162 11,127 11,074 10,791 10,739 10,741 10,535 11,166 11,077 11,083

Maine 1,609 1,565 1,565 1,565 1,565 1,557 1,552 1,552 1,565 1,565 1,565

Maryland 5,107 7,324 6,295 6,297 6,160 6,147 5,955 5,955 6,132 6,138 6,009

Massachusetts 1,956 2,219 2,268 2,229 2,221 2,186 2,115 2,069 2,222 2,222 2,219

Michigan 32,421 22,233 21,858 19,340 18,862 18,713 18,717 18,677 22,073 20,635 20,635

Minnesota 11,501 11,223 11,145 10,947 10,743 10,691 10,650 9,576 11,226 11,226 11,226

Mississippi 8,951 8,299 8,217 8,002 7,416 7,208 6,895 6,258 7,788 7,579 7,067

Missouri 20,632 18,663 17,732 17,705 17,767 17,881 17,322 17,113 17,757 17,793 17,831

Montana 8,502 7,759 7,746 7,746 7,746 7,722 7,722 7,722 7,759 7,759 7,759

Nebraska 14,548 14,613 14,613 14,237 11,388 11,209 10,752 9,786 14,579 14,577 14,578

Nevada 4,192 4,547 4,532 4,530 3,323 3,158 2,584 1,840 4,546 4,546 4,546

New Hampshire 301 289 289 289 294 296 295 299 289 289 289

New Jersey 4,617 3,950 3,581 3,580 3,576 3,573 3,570 3,489 3,091 3,090 3,085

New Mexico 17,266 17,372 17,372 16,940 16,942 16,813 16,364 16,238 17,372 17,372 17,372

New York 9,123 7,911 7,807 7,638 7,578 7,579 7,305 7,072 7,870 7,675 7,676

North Carolina 22,048 17,307 15,385 15,389 13,784 13,685 12,895 12,774 15,341 15,341 14,215

North Dakota 23,037 16,423 16,423 13,078 13,054 12,743 12,480 12,430 16,246 16,246 16,246

Ohio 29,693 29,249 23,503 19,603 19,583 19,785 19,545 19,473 23,504 19,823 19,823

Oklahoma 24,335 19,620 18,918 17,450 16,452 15,799 13,930 13,023 19,614 18,103 18,114

Oregon 1,038 800 800 800 800 800 800 800 800 800 800

Pennsylvania 52,173 43,599 41,389 16,834 16,826 16,704 16,686 16,613 42,421 17,094 17,087

Rhode Island 208 257 257 260 257 257 257 257 254 255 256

South Carolina 6,183 5,875 4,819 4,739 4,701 4,693 4,690 4,721 6,016 6,046 6,047

South Dakota 653 297 297 297 297 297 297 297 297 297 297

Tennessee 6,382 5,566 5,492 5,454 5,446 5,367 5,350 5,307 5,493 5,493 5,494

Texas 66,651 59,199 58,570 56,391 54,406 53,283 52,529 52,707 59,228 57,146 57,223

Utah 25,160 24,489 24,489 21,018 21,018 20,078 19,846 19,209 24,489 24,489 24,489

Vermont 198 163 163 163 163 163 163 163 163 163 163

Virginia 11,254 9,201 8,778 8,662 7,809 6,292 6,182 6,339 9,252 8,882 8,911

Washington 1,002 747 747 747 747 747 747 926 747 747 747

West Virginia 25,606 25,664 25,071 14,755 13,649 13,453 13,421 13,421 25,071 14,755 13,649

Wisconsin 8,801 5,923 5,920 5,906 5,845 5,825 5,674 5,331 5,917 5,917 5,917

Wyoming 14,281 10,796 10,724 10,167 9,258 9,245 8,812 8,345 10,796 10,796 10,796

Nationwide 702,278 609,317 578,695 497,105 480,788 397,120 386,293 367,409 511,907 524,543 451,848

### 10 Table B

- 3 . Emission Differences between the 5.14 Base Case

and the Other Pollution Control Cost Thresholds (Tons) from “All Units”.

*Source: Integrated Planning Model run by EPA, 2015. See Appendix A for list and description of these IPM runs. Emissions have been

rounded to the nearest ton. Emissions shown for all fossil

- fired units greater than 25 MW when only an ozone season cost constraint is applied.

Costs are in 2011$. 5.14 Base

Case 5.15 Base

Case $500/ton

CT $1300/ton

CT $3400/ton

CT $5000/ton

CT $6400/ton

CT $10000/ton

CT Less

Stringent

Control

Alternative Proposed

Emissions

Budgets More

Stringent

Control

Alternative

Alabama 0 1,441

- 288

- 2,136

- 2,207

- 3,305

- 3,932

- 4,354

- 56

- 1,665

- 1,620

Arizona 0

- 3,874

- 3,874

- 9,940

- 9,685

- 9,802

- 9,822

- 9,911

- 3,860

- 3,860

- 3,860

Arkansas 0

- 5,492

- 5,505

- 5,595

- 6,267

- 6,555

- 6,637

- 7,330

- 5,476

- 5,476

- 5,355

California 0

- 333

- 333

- 334

- 341

- 336

- 337

- 452

- 333

- 333

- 333

Colorado 0

- 1,430

- 1,430

- 1,453

- 2,062

- 2,313

- 2,721

- 3,356

- 1,430

- 1,430

- 1,430

Connecticut 0 20 19 22 2

- 17

- 17

- 44 20 20 20

Delaware 0 192 192 192 192 192 192 188 192 192 192

District of Columbia 0 0 0 0 0 0 0 0 0 0 0

Florida 0

- 3,493

- 4,700

- 10,017

- 10,571

- 10,719

- 11,142

- 11,350

- 3,255

- 3,106

- 3,070

Georgia 0

- 2,038

- 2,157

- 2,275

- 2,376

- 2,464

- 2,494

- 2,463

- 2,035

- 2,025

- 2,019

Idaho 0 44 38 38 39 39 39 39 45 42 43

Illinois 0

- 4,808

- 5,183

- 5,245

- 5,317

- 5,383

- 5,394

- 5,515

- 5,037

- 5,049

- 5,060

Indiana 0

- 1,414

- 8,025

- 13,536

- 14,320

- 15,099

- 14,767

- 18,113

- 8,067

- 12,877

- 12,892

Iowa 0

- 1,057

- 1,174

- 1,413

- 1,452

- 1,452

- 1,424

- 2,023

- 1,211

- 1,429

- 1,429

Kansas 0 126

- 301

- 271

- 93

- 269

- 301 71

- 301

- 301

- 301

Kentucky 0

- 11,792

- 15,400

- 23,687

- 24,146

- 24,237

- 25,220

- 26,267

- 14,790

- 23,017

- 22,967

Louisiana 0

- 2,764

- 2,798

- 2,851

- 3,134

- 3,187

- 3,185

- 3,391

- 2,760

- 2,849

- 2,843

Maine 0

- 44

- 44

- 44

- 44

- 52

- 57

- 57

- 44

- 44

- 44

Maryland 0 2,217 1,189 1,191 1,053 1,041 848 848 1,026 1,032 903

Massachusetts 0 262 312 273 264 230 158 113 265 265 262

Michigan 0

- 10,188

- 10,563

- 13,081

- 13,559

- 13,708

- 13,704

- 13,744

- 10,348

- 11,786

- 11,786

Minnesota 0

- 278

- 356

- 553

- 758

- 810

- 851

- 1,925

- 275

- 275

- 275

Mississippi 0

- 653

- 734

- 949

- 1,536

- 1,743

- 2,056

- 2,693

- 1,163

- 1,372

- 1,884

Missouri 0

- 1,969

- 2,900

- 2,927

- 2,865

- 2,751

- 3,310

- 3,519

- 2,875

- 2,839

- 2,801

Montana 0

- 743

- 756

- 756

- 756

- 780

- 780

- 780

- 743

- 743

- 743

Nebraska 0 65 65

- 311

- 3,160

- 3,339

- 3,796

- 4,762 31 29 30

Nevada 0 355 340 338

- 868

- 1,034

- 1,608

- 2,352 355 354 354

New Hampshire 0

- 12

- 12

- 12

- 7

- 5

- 6

- 2

- 12

- 12

- 12

New Jersey 0

- 667

- 1,036

- 1,037

- 1,041

- 1,044

- 1,047

- 1,128

- 1,526

- 1,528

- 1,532

New Mexico 0 106 106

- 326

- 324

- 452

- 902

- 1,027 106 106 106

New York 0

- 1,213

- 1,317

- 1,486

- 1,545

- 1,545

- 1,818

- 2,051

- 1,253

- 1,448

- 1,447

North Carolina 0

- 4,741

- 6,663

- 6,659

- 8,263

- 8,363

- 9,153

- 9,274

- 6,707

- 6,707

- 7,833

North Dakota 0

- 6,614

- 6,614

- 9,959

- 9,983

- 10,295

- 10,557

- 10,607

- 6,791

- 6,791

- 6,791

Ohio 0

- 444

- 6,190

- 10,090

- 10,110

- 9,908

- 10,147

- 10,220

- 6,189

- 9,870

- 9,870

Oklahoma 0

- 4,714

- 5,417

- 6,884

- 7,883

- 8,535

- 10,404

- 11,311

- 4,720

- 6,232

- 6,220

Oregon 0

- 238

- 238

- 238

- 238

- 238

- 238

- 238

- 238

- 238

- 238

Pennsylvania 0

- 8,575

- 10,785

- 35,339

- 35,347

- 35,469

- 35,488

- 35,560

- 9,752

- 35,079

- 35,086

Rhode Island 0 49 49 52 49 49 49 49 47 48 48

South Carolina 0

- 308

- 1,365

- 1,444

- 1,482

- 1,491

- 1,493

- 1,462

- 167

- 137

- 136

South Dakota 0

- 356

- 356

- 356

- 356

- 356

- 356

- 356

- 356

- 356

- 356

Tennessee 0

- 816

- 890

- 928

- 937

- 1,015

- 1,032

- 1,075

- 890

- 889

- 888

Texas 0

- 7,452

- 8,081

- 10,260

- 12,245

- 13,369

- 14,123

- 13,944

- 7,423

- 9,506

- 9,428

Utah 0

- 671

- 671

- 4,142

- 4,142

- 5,082

- 5,314

- 5,951

- 671

- 671

- 671

Vermont 0

- 36

- 36

- 36

- 36

- 36

- 36

- 36

- 36

- 36

- 36

Virginia 0

- 2,054

- 2,476

- 2,593

- 3,445

- 4,962

- 5,072

- 4,915

- 2,002

- 2,372

- 2,343

Washington 0

- 256

- 256

- 256

- 256

- 256

- 256

- 76

- 256

- 256

- 256

West Virginia 0 57

- 535

- 10,851

- 11,957

- 12,153

- 12,185

- 12,185

- 535

- 10,851

- 11,957

Wisconsin 0

- 2,878

- 2,881

- 2,894

- 2,955

- 2,976

- 3,127

- 3,469

- 2,884

- 2,884

- 2,884

Wyoming 0

- 3,486

- 3,558

- 4,115

- 5,023

- 5,037

- 5,470

- 5,937

- 3,486

- 3,486

- 3,486

Nationwide 0

- 92,961

- 123,583

- 205,173

- 221,490

- 230,390

- 240,492

- 253,916

- 117,865

- 177,736

- 180,222

### 11

Table B

- 4 . 2014 Heat Input, Emission Rates, and State Budgets

Less Stringent Control Alternative Proposed Alternative More Stringent Control Alternative

State 2014 Heat

Input

(MMBtu) 2018 IPM

Emission

Rate 2018 IPM

Emission

Rate *

2014 Heat

Input 2017 Budget

(w/2017

Adjustment

and 2014

Historic

Emission

Limiter) 2018 IPM

Emission

Rate 2018 IPM

Emission

Rate *

2014 Heat

Input

(Historic *

IPM Rate) 2017 Budget

(w/2017

Adjustment

and 2014

Historic

Emiss ion

Limiter) (w/

2017

Adjustment) 2018 IPM

Emission

Rate 2018 IPM

Emission

Rate *

2014 Heat

Input

(Historic *

IPM Rate) 2017 Budget

(w/2017

Adjustment

and 2014

Historic

Emission

Limiter) (w/

2017

Adjustment)

Alabama 410,477,094 0.058 11,886 11,886 0.049 9,979 9,979 0.048 9,931 9,931

Arkansas 185,511,093 0.076 6,987 7,038 0.075 6,898 6,949 0.066 6,051 6,101

Illinois 388,382,456 0.063 12,121 12,144 0.062 12,069 12,078 0.062 11,992 11,992

Indiana 447,417,615 0.150 33,483 33,483 0.126 28,284 28,284 0.123 27,585 27,585

Iowa 151,989,571 0.113 8,614 8,614 0.110 8,351 8,351 0.107 8,118 8,118

Kansas 154,921,650 0.120 9,278 9,278 0.120 9,272 9,272 0.120 9,259 9,259

Kentucky 380,694,315 0.184 28,320 32,783 0.119 19,350 21,519 0.116 18,776 20,945

Louisiana 326,662,000 0.097 15,844 15,861 0.097 15,790 15,807 0.094 15,360 15,378

Maryland 86,239,563 0.098 2,155 4,026 0.098 2,160 4,026 0.096 2,160 4,026

Michigan 307,723,171 0.145 20,186 22,022 0.126 17,279 19,115 0.123 16,646 18,624

Mississippi 172,406,970 0.071 6,083 6,083 0.069 5,910 5,910 0.064 5,487 5,487

Missouri 330,006,788 0.093 14,257 15,380 0.093 14,113 15,323 0.092 13,740 15,240

New Jersey 112,887,439 0.036 2,016 2,016 0.036 2,015 2,015 0.036 2,011 2,011

New York 235,619,397 0.039 4,607 4,607 0.038 4,450 4,450 0.037 4,391 4,391

North

Carolina 315,255,877 0.078 12,278 12,278 0.078 12,275 12,275 0.068 10,705 10,705

Ohio 457,251,027 0.088 20,194 20,194 0.073 16,660 16,660 0.073 16,637 16,637

Oklahoma 236,715,186 0.158 16,215 16,215 0.145 16,215 16,215 0.138 16,215 16,215

Pennsylvania 508,608,673 0.151 38,270 38,270 0.057 14,387 14,387 0.056 14,358 14,358

Tennessee 196,132,311 0.056 5,520 5,520 0.056 5,481 5,481 0.056 5,449 5,449

Texas 1,474,773,212 0.083 58,492 58,492 0.079 57,970 58,002 0.076 55,764 55,864

Virginia 179,324,728 0.078 6,955 6,955 0.076 6,818 6,818 0.065 5,834 5,834

West Virginia 317,087,558 0.145 22,932 22,932 0.084 13,390 13,390 0.078 12,367 12,367

Wisconsin 205,305,933 0.054 5,588 5,588 0.054 5,561 5,561 0.054 5,511 5,511

### 12

Table B

- 5. 2017 State Budgets, Variability Limits, and Assurance Levels

Less Stringent Alternative Proposed Budgets and Assurance Levels More Stringent Alternative

State 2017

Budgets 2017

Variability

Limit 2017

Assurance

Level 2017

Budgets 2017

Variability

Limit 2017

Assurance

Level 2017

Budgets 2017

Variability

Limit 2017

Assurance

Level

Alabama 11,886 2,496 14,382 9,979 2,096 12,075 9,931 2,086 12,017

Arkansas 7,038 1,478 8,516 6,949 1,459 8,408 6,101 1,281 7,382

Illinois 12,144 2,550 14,694 12,078 2,536 14,614 11,992 2,518 14,510

Indiana 33,483 7,031 40,514 28,284 5,940 34,224 27,585 5,793 33,378

Iowa 8,614 1,809 10,423 8,351 1,754 10,105 8,118 1,705 9,823

Kansas 9,278 1,948 11,226 9,272 1,947 11,219 9,259 1,944 11,203

Kentucky 32,783 6,884 39,667 21,519 4,519 26,038 20,945 4,398 25,343

Louisiana 15,861 3,331 19,192 15,807 3,319 19,126 15,378 3,229 18,607

Maryland 4,026 845 4,871 4,026 845 4,871 4,026 845 4,871

Michigan 22,022 4,625 26,647 19,115 4,014 23,129 18,624 3,911 22,535

Mississippi 6,083 1,277 7,360 5,910 1,241 7,151 5,487 1,152 6,639

Missouri 15,380 3,230 18,610 15,323 3,218 18,541 15,240 3,200 18,440

New Jersey 2,016 423 2,439 2,015 423 2,438 2,011 422 2,433

New York 4,607 967 5,574 4,450 935 5,385 4,391 922 5,313

North Carolina 12,278 2,578 14,856 12,275 2,578 14,853 10,705 2,248 12,953

Ohio 20,194 4,241 24,435 16,660 3,499 20,159 16,637 3,494 20,131

Oklahoma 16,215 3,405 19,620 16,215 3,405 19,620 16,215 3,405 19,620

Pennsylvania 38,270 8,037 46,307 14,387 3,021 17,408 14,358 3,015 17,373

Tennessee 5,520 1,159 6,679 5,481 1,151 6,632 5,449 1,144 6,593

Texas 58,492 12,283 70,775 58,002 12,180 70,182 55,864 11,731 67,595

Virginia 6,955 1,461 8,416 6,818 1,432 8,250 5,834 1,225 7,059

West Virginia 22,932 4,816 27,748 13,390 2,812 16,202 12,367 2,597 14,964

Wisconsin 5,588 1,173 6,761 5,561 1,168 6,729 5,511 1,157 6,668

### 13

Table B

- 6. Existing Unit Allocation and NUSA Calculations for Proposed Budgets.

Proposed

2017

Budgets Existing

Unit

Allocation NUSA Non

Indian

Country

NUSA

(tons) Indian

Country

NUSA

(tons)

Alabama 9,979 9,774 205 205

Arkansas 6,949 6,808 141 141

Illinois 12,078 11,487 591 591

Indiana 28,284 27,719 565 565

Iowa 8,351 7,932 419 411 8

Kansas 9,272 8,991 281 272 9

Kentucky 21,519 20,872 647 647

Louisiana 15,807 15,179 628 612 16

Maryland 4,026 3,541 485 485

Michigan 19,115 18,733 382 363 19

Mississippi 5,910 5,320 590 584 6

Missouri 15,323 15,009 314 314

New Jersey 2,015 864 1,151 1,151

New York 4,450 4,357 93 89 4

North

Carolina 12,275 12,027 248 236 12

Ohio 16,660 16,323 337 337

Oklahoma 16,215 15,890 325 309 16

Pennsylvania 14,387 13,370 1,017 1,017

Tennessee 5,481 5,372 109 109

Texas 58,002 55,092 2,910 2,852 58

Virginia 6,818 4,974 1,844 1,844

West

Virginia 13,390 13,122 268 268

Wisconsin 5,561 5,440 121 115 6

### 14

C. Analysis of Significant Contribution Using an Ozone Air Quality Assessment Tool

EPA has defined significant contribution to nonattainment and interference with

maintenance of downwind air quality using a multi

- factor test (described in the preamble) which

is based on cost , emissions, and air quality factors

. A key quantitative input for determining the

amount of significant contribution is the predicted downwind ambient air quality impacts of

upwind EGU emission reductions under the various NO

x 

### cost thresholds described in section B

of this TSD . Time and resource limitations (in particular the amoun t of time needed to set up,

run the CAMx model

, 9 

### and analyze the results for a single model run precluded the use of full air

quality modeling for all but a few emissions scenarios. Because EPA needed to evaluate

emission reductions under several different NO

x 

### cost thresholds, it was not possible to use

CAMx air quality modeling to evaluate all cases

. Consequently, EPA used a simplified assessment tool to estimate the downwind air

quality impacts from the NO

x 

### cost thresholds. For the NO

x 

### cost thresholds, the state

- by

- state

EGU emissions are projected using EPA’s IPM model under a given cost threshold of emission

reductions ( see section B of this TSD for details about the IPM model runs and for the emission

projections). The air quality impacts of these cost thresholds are then estimated using the ozone

AQAT

. The inputs and outputs of the tool can be found in the “ ozone_AQAT .xlsx” excel

workbook. The simplified tool allows the Agency to analyze many more NO

x 

### cost thresholds

than would otherwise be possible. The remainder of section C of this document will:

● 

### Present an introduction and overview of the ozone AQAT ;

● 

### Describe the construction of the ozone AQAT ;

● 

### Provide the results of the NO

x 

### cost threshold analyses;

1. Introduction: D evelopment of the ozone AQAT

The ozone AQAT was developed specifically for use in the rule’s significant contribution

analysis. EPA described and used a similar tool in CSAPR to evaluate fine particulate matter

(PM2.5) significant contribution

. For this rule, EPA refined both the construction and

application of the assessment tool for use in estimating change in ozone concentrations in

respons e to changes in NO

x 

### emissions

. One important change between CSAPR and this effort is

to use the ozone AQAT to examine changes in ozone

. We follow the methodology developed in

the final CSAPR where we calibrate the response of a pollutant 10 

### using two CAMx simulations

at different emission levels. In this rule , we used CAMx to calibrate the assessment tool’s

predicted change in ozone concentrations to changes in N O

x 

### emissions . This calibration is

9 See the Air Quality Modeling TSD, or “Updated Air Quality Modeling Technical Support Doc ument for the 2008

Ozone NAAQS Transport Assessment” for additional details.

www.epa.gov/airtransport/pdfs/Updated_2008_Ozone_NAAQS_Transport_AQModeling_TSD.pdf and the

Emission inventory information relevant to the 2011 and 2018 simulations , available at

www.epa.gov/ttn/chief/emch/index.html

10 In CSAPR, we estimated changes in sulfate using changes in SO 2 emissions.

### 15

receptor

- specific and is based on the changes in NO

x 

### emissio ns and resulting ozone

concentrations between the 201 7 base case and the modeled illustrative control ca s e 11 

### in 2017

. A critical factor in the assessment tool is the establish ment of a relationship between

ozone

- season N O

x 

### emission reductions and reductions in ozone . For the purposes of developing

and using an assessment tool to comp are the air quality impacts of N O

x 

### emission reductions

under various cost thresholds, we determine the relationship between changes in emissio ns and

changes in ozone contributions on a receptor

- by

- receptor basis. Specifically, EPA assumed that

, within the range of total N O

x 

### emissions being considered (as defined by the N O

x 

### cost

thresholds), a change in ozone

- season NO

x 

### emissions leads to a prop ortional change in

downwind ozone contributions 12



### . This proportional relationship was then modified using

calibration factors based on air quality modeling, as described below.

Within the assessment tool , t he relationships between upwind emissions and down wind

air quality are defined using the 201 7 base case contribution air quality modeling and a 201 7

illustrative control case . As described in the Air Quality Modeling TSD, CAMx state

- by

- state

source

- apportionment modeling was used to quantify the contributions to ozone at monitoring

sites due to NO

x 

### emissions from each upwind state for the 201 7 base case emission scenario. For

example, from the output of the CAMx source apportionment modeling, we know the ozone

contributio n at a downwind monitor resulting from the specific NO

x 

### emissions in the 2017 base

case from a particular upwind state

. In the ozone AQAT , we associate a change in emissions

from that upwind state with a particular change in its downwind contribution. In the

“uncalibrated” ozone AQAT

, for example, we assume that a 20% decrease in the upwind state’s

emissions leads to a 20% decrease in its downwind ozone contribution. This relationship is

calibrated using e mission reductions from the 2017 base case to the 2017 illustrative control

case 13 

### by calculating the relationship between the relative change in ozone at each receptor using

CAMx air quality modeling and the relative change in ozone at each receptor using the ozone

AQAT

. Using this relationship, i t was possible to calibrate the ozone AQAT ’s ozone response

for use in assessing ozone under various NO

x 

### cost thresholds. This is described further in section

C.2 of this document. For the example above, where a 20% reduction in emissions resulted in a

2 0% decrease in contribution, using “calibrated” ozone AQAT may yield , for example, a 10 %

reduction in concentration from the 20% reduction in emission s (a s derived directly from the

emission reduction and concentration change f rom the 2017 base case to the 2017 illustrative

control case ).

In the application of the uncalibrated ozone AQAT , we assume that the reduction of a ton

of emissions of NO

x 

### from the upwind state has an equivalent air quality effect downwind (on an

11 An integral input to the creation and use of the assessment tool was CAMx air quality modeling of the control

scenario used in calibration . This “illustrative control case” was created during the development of the assessment

tool for the proposed rule and its EGU emissions modeling reflects t he geography and cost threshold from the

control scenario at $1,300/ton for ozone

- season NO

x using IPM v. 5.14. Note that the emission reductions for this

scenario differ from the final values used in the proposed r ule

.

12 The relationship between NO

x emissions and ozone concentrations is known to be non

- linear when examined over

large ranges of NO

x e missions (e.g., Seinfeld and Pandis, pp 236

- 236). However, for some ranges of NO

x , VOC,

and meteorological conditions, the relationship may be reasonably linear. In this assessment tool, we are assuming a

linear relationship between NO

x emissions and ozo ne concentrations. This assumption is reasonable because the

changes in NO

x emissions and ozone concentrations are small (a few ppb), and the results are “bracketed” using two

modeled scenarios. Over this range, a majority of the nonlinearity in the rela tionship between emissions and

concentrations is directly accounted for by the air quality model.

13 The illustrative control case is an EGU NO

x ozone

- season emission budget sensitivity scenario, reflecting

emission reductions in the 23 eastern states that the EPA proposes to regulate under this rule.

### 16

air quality impact per ton basis), reg ardless of source sector or the location of the particular

emission source within the state where the ton was reduced. For example, reducing one ton of

NO

x 

### emissions from the power sector is assumed to have the same downwind ozone reduction as

reducing on e ton of NO

x 

### emissions of from the mobile source sector. For this rule, we are

examining all emission reductions within a 2017 time

- frame. Consequently, only reductions

from the power sector are anticipated. Because the calibration factor is based only on modeling

of 2017 with only emission reductions from the power sector, the calibration factor and thereby

calibrated ozone AQAT better represents changes in emissions in the power sector.

Because the tool is only being used over a fairly narrow range (f or which a calibration

factor has been developed), and because other options such as using CAMx to model all other

scenarios is cost and time

- prohibitive, EPA proposes to use ozone AQAT as a cost

- effective tool

for estimating the downwind ozone reductions due to upwind NO

x 

### emission reductions for the air

quality input to the multi

- factor test for this rule

. Other options, such as directly scaling the

results (i.e., an “uncalibrated ozone AQAT ”) will likely greatly overestimate the air quality

i mpacts of emission reductions.

Section C.2, below, is a technical explanation of the construction of the ozone AQAT

. Readers who prefer to access the results of the analysis using the ozone AQAT are directed to

section C.3.

2. Details on the construct ion of the ozone AQAT

(a) Overview of the ozone AQAT

This section describes the step

- by

- step development process for the ozone AQAT

. All of

the input and output data can be found in the Excel worksheets described in Appendix B. In the

ozone AQAT

, EPA link s state

- by

- state NO

x 

### emission reductions (from IPM) with CAMx

modeled ozone contributions in order to predict ozone concentrations at different cost thresholds

at monitoring sites with projected nonattainment and/or maintenance problems in the 2017 base

case . The reduction in ozone contributions and resulting air quality improvement were then

considered in a multi

- factor test for defining significant contribution to nonattainment and

interference with maintenance. In the analysis for a given recep tor, emissions were reduced in

only those upwind states that were “linked” to that receptor (i.e., contributed an air quality

impact at or above the 1 percent

-- of the NAAQS standard

-- air quality threshold) as well as the

state that contained that recep tor (regardless of that state’s contribution)

. For a discussion of the

1% threshold, see preamble section V

.

Specifically, the key estimates from the ozone AQAT for each receptor are:

● 

### The ozone contribution as a function of emissions at each cost thre shold, for each

upwind state that is contributing above the 1 percent air quality threshold and the state

containing the receptor.

● 

### The ozone contribution under base case NO

x 

### emissions (i.e., the IPM 5.14 base case)

, for each upwind state that is not above the 1 percent air quality threshold for that

receptor. These base level emissions may be different/reduced in other scenarios (i.e.,

the IPM 5.15 base case ) due to projected changes in the EGU sector (see section B

and references therein for additional de tails)

.

### 17

● 

### The non

- anthropogenic (i.e., background, boundary, biogenic, and wildfire) ozone

concentrations (these are assumed to be constant and equal to the contributions from

the 2017 source apportionment modeling (using IPM v. 5.14)

.

The results of the oz one AQAT analysis for each cost threshold can be found in section

C.3 of this document.

(b) Data used to construct the ozone AQAT for this rule

Several data sources were used to construct the calibrated ozone AQAT for this rule

. Three data sources provide the necessary initial information to construct the uncalibrated

versions of the ozone AQAT . The uncalibrated versions of the ozone AQAT were used to create

estimates of ozone response under NO

x 

### emissions defined by the illust rative control case . The

datasets required to construct the ozone AQAT included: the 2017 base case ozone

- season NO

x 

### emission inventories from all source sectors used in the source apportionment CAMx air quality

modeling (this includes all anthropogenic s ources and excludes biogenic sources and wildfires) ;

the CAMx 2017 ozone

- season contributions for each upwind state to each downwind receptor;

and the 2017 illustrative control case ozone

- season NO

x 

### emissions inventories from all source

secto rs. An additi onal dataset, 2017 ozone concentrations from CAMx for the illustrative control

case

, was used to compare the ozone AQAT

- estimated ozone concentrations for this scenario to

the corresponding air quality modeling results, and develop calibration factors to align the

response of ozone to changes in NO

x 

### emissions in the ozone AQAT with the response predicted

by CAMx . These calibration factors were then used to create a “calibrated” ozone AQAT

. Finally, EGU ozone

- season NO

x 

### emissions (from IPM) at each co st threshold were used to

generate ozone AQAT air quality results using the calibrated ozone AQAT . The base cas e

emissions inventories for the 2017 base case (using both versions 5.14 and 5.15 versions of IPM

for EGUs), as well as the CAMx 2017 base case s ource apportionment air quality modeling

results are discussed in preamble section V . The ozone

- season NO

x 

### EGU emissions for each

cost threshold (projected using IPM)

, including the base case

, are listed in Table B

- 2 and

described in section B of this TSD

. As described in the Air Quality Modeling TSD and the preamble, the air quality

contributions and emissions were modeled for all states 14 

### in the contiguous US . Thus, in the

ozone AQAT , these states had the possibility of making reductions in emissions leading to

changes in air quality contributions at the downwind receptors. Additionally, due to the

modeling domain, the ozone AQAT is only able to estimate changes in ozone concentratio ns

from monitors within these states 15



### .

(c) Detailed outline of the process for constructing and utilizing the ozone AQAT

The ozone AQAT was created and used in a multi

- step process. First, a version of the

ozone AQAT was created specifically for calib ration. As described in the following paragraphs,

t he ozone AQAT simulated the response of ozone to reductions in emissions of NO

x



### . Next, the

14 The District of Columbia was also modeled.

15 Because the illustrative control case does not include emission changes in some upwind states (e.g., states in the

western portion of the domain), calibration fact ors developed for these states, and the resulting changes in air

quality, may not be representative.

### 18

relative ozone response from the ozone AQAT was calibrated to the ozone response from CAMx

using the change in emissions from the 2017 base case to the illustrative control case . Next, the

calibrated ozone AQAT was used to evaluate the ozone response of emission reductions for each

NO

x 

### cost threshold assessed. A t each cost threshold, the state

- specific calibrated ozone estimates

were combined with other constituents from the base case resulting in estimated ozone design

values

. 16



### The illustrative control case played a key role in calibrat ing the assessment tool for use in

the rule

. One intent of this control scena rio was to create a calibration point within the range of

all emission reductions examined by EPA using the assessment tool . This calibration point was

used to create site

- specific calibration factors so that the response of ozone concentrations to

upwind NO

x 

### emission changes would more

- closely align with ozone estimates from CAMx. To

fill this role, EPA used the results of IPM modeling of a n illustrative control case 11 

### with similar

level and geog raphic distribution to the control remedy for this rule (except using IPM version

5.14 to estimate EGU emissions)

. Among other reasons, t his scenario served to develop the

calibration point s for the assessment tool which allowed EPA to reasonably assess the down wind

impacts of NO

x 

### reductions both more and less stringent than the illustrative control case

. In order to facilitate understanding of the calibration process, EPA is including an

example monitor for evaluation in this text: monitor number 240251001 in Harford County,

Maryland, with a 2017 base case predicted ozone average design value of 81.3 ppb and

maximum design value of 84 .0 ppb. Additional details for all monitors can be found in the

referenced tables in the docket.

(1) Create an uncalibrated version of the ozone AQAT for calibration

To create the version of the ozone AQAT for calibration, EPA used emissions and

contributions to estimate the change in predicted ozone due to NO

x 

### emission reductions under

the illustrative control case relative to the 2017 base case

. First, EPA calculated ozone

- season state

- level 2017 base case total NO

x 

### emissions from

all source sectors. These emissions estim ates were used for the CAMx 2017 source

apportionment modeling. This emissions data is divi ded into multiple source sectors for the

purposes of air quality modeling: power sector point (from v 5.14 IPM), non

- power sector point,

non

- point, onroad, nonroad, C3 marine, alm, and fires (see the Emissions Inventory TSD 17 

### for

additional details on the e missions inventories used in the CAMx air quality modeling). The

state

- level total NO

x 

### emissions are the sum of emissions from all these source sectors. Next,

EPA calculated the ozone

- season 2017 total NO

x 

### emissions across all source sectors for the

illu strative control case . EPA calculated the ratio of the emissions for the illustrative control

case to the total emissions for the base case for each state modeled in CAMx. More information

on the emissions inventories can be found in the preamble and in the Notice of Data Availability,

or NODA 18 

### . The total emissions data and resulting ratios can be found in Table C

- 1.

16 Details on procedures for calculating av era g e and max imum design values can be found in the Air Quality

Modeling TSD.

17 “Technical Support Document (TSD) Preparation of Emissions Inventories for the Version 6.2, 2011 Emissions

Modeling Platform”, available at

www.epa.gov/ttn/chief/emch/2011v6/2011v6_2_2017_2025_EmisMod_TSD_aug2015.pdf

18 “Notice of Availability of the Environmental Protection Agency’s Updated Ozone Transport Modeling Data for

the 2008 Ozone National Ambient Air Quality Standard (NAAQS)” (July 23, 2015 ) , available at

http://www.epa.gov/airtransport/pdfs/FR_Version_Transport_NODA.pdf

### 19

For each monitor, “uncalibrated” change in concentration is found by multiplying the

2017 base case ozone contribution by the difference in the ratio of emissions. The difference in

the ratio of emissions is calculated as the ratio of total ozone

- season NO

x 

### emissions in the

illustrative control case to the 2017 base case scenario minus 1

. Thus, if the illus trative control

case has smaller emissions, the net result is a negative number. When the change in

concentrations are summed across all states, the result is the total “uncalibrated” change in

concentration.

### 20

Table C

- 1. 201 7 Base Case and 201 7 Illust rative Control Case Ozone Contributions for Monitor

Number 240251001 in Harford County, Maryland , as well as Total N O

x 

### Emissions from all

Source

- Sectors for Each State

.

State/Source 2017 Base Case

Ozone

Contributions

(ppb) 2017 Base

Case NO

x Emissions

(tons) 2017 Illustrative

Control Case

NO

x Emissions

(tons) Ratio of

Illustrative

Control Case

Emissions to Base

Case Emissions Difference between the

Illustrative Control Case

Emissions and Base Case

Emissions as a Fraction of

Base Case Emission s Estimated 2017

Contribution of

Ozone (U ncalibrated

O zone AQAT ) (ppb)

AL 0.4053 

### 88,805 85,721 0.97

- 0.03

- 0.01

AZ 0.0958 

### 71,906 71,906 1.00 0.00 0.00

AR 0.2264 

### 69,737 69,039 0.99

- 0.01 0.00

CA 0.1106 

### 236,322 236,322 1.00 0.00 0.00

CO 0.1942 

### 90,756 90,756 1.00 0.00 0.00

CT 0.011 

### 17,672 17,672 1.00 0.00 0.00

DE 0.1559 

### 7,786 7,786 1.00 0.00 0.00

DC 0.7334 

### 2,252 2,252 1.00 0.00 0.00

FL 0.1141 

### 177,514 177,513 1.00 0.00 0.00

GA 0.3035 

### 103,536 103,526 1.00 0.00 0.00

ID 0.0349 

### 27,893 27,893 1.00 0.00 0.00

IL 0.672 

### 148,178 147,770 1.00 0.00 0.00

IN 1.8904 

### 139,133 127,487 0.92

- 0.08

- 0.16

IA 0.1933 

### 70,467 70,045 0.99

- 0.01 0.00

KS 0.285 

### 79,939 79,513 0.99

- 0.01 0.00

KY 1.973 

### 106,830 97,311 0.91

- 0.09

- 0.18

LA 0.2597 

### 173,330 172,886 1.00 0.00 0.00

ME 0.0005 

### 17,576 17,576 1.00 0.00 0.00

MD 24.619 

### 46,029 45,312 0.98

- 0.02

- 0.38

MA 0.0037 

### 35,369 35,369 1.00 0.00 0.00

MI 0.8339 

### 131,486 124,374 0.95

- 0.05

- 0.05

MN 0.1142 

### 89,328 89,332 1.00 0.00 0.00

MS 0.1596 

### 54,832 54,706 1.00 0.00 0.00

MO 0.5299 

### 101,035 99,736 0.99

- 0.01

- 0.01

MT 0.0688 

### 38,504 38,504 1.00 0.00 0.00

NE 0.1569 

### 70,005 70,005 1.00 0.00 0.00

NV 0.0279 

### 28,192 28,192 1.00 0.00 0.00

NH 0.0009 

### 8,932 8,932 1.00 0.00 0.00

NJ 0.4374 

### 52,743 52,031 0.99

- 0.01

- 0.01

NM 0.1688 

### 65,263 65,263 1.00 0.00 0.00

NY 0.4009 

### 109,910 107,416 0.98

- 0.02

- 0.01

NC 0.4684 

### 98,064 91,850 0.94

- 0.06

- 0.03

ND 0.0848 

### 74,118 74,118 1.00 0.00 0.00

OH 4.0022 

### 160,110 150,516 0.94

- 0.06

- 0.24

OK 0.4683 

### 131,763 129,215 0.98

- 0.02

- 0.01

OR 0.0232 

### 40,507 40,507 1.00 0.00 0.00

PA 6.0769 

### 174,664 147,166 0.84

- 0.16

- 0.96

RI 0.0006 

### 5,845 5,844 1.00 0.00 0.00

SC 0.1097 

### 55,897 55,846 1.00 0.00 0.00

SD 0.0587 

### 22,192 22,192 1.00 0.00 0.00

### 21

TN 0.7044 

### 85,759 85,693 1.00 0.00 0.00

TX 1.0563 

### 467,245 465,179 1.00 0.00 0.00

UT 0.0942 

### 66,486 66,486 1.00 0.00 0.00

VT 0.0015 

### 5,473 5,473 1.00 0.00 0.00

VA 5.3016 

### 87,754 87,514 1.00 0.00

- 0.01

WA 0.0327 

### 75,833 75,833 1.00 0.00 0.00

WV 2.9988 

### 64,839 53,954 0.83

- 0.17

- 0.50

WI 0.2178 

### 75,047 75,035 1.00 0.00 0.00

WY 0.2063 

### 68,864 68,864 1.00 0.00 0.00

TRIBAL 0.0436 

### 26,717 26,717 1.00 0.00 0.00

CNMX 0.7368 1.00 0.00 0.00

OFFSHORE 0.4494 1.00 0.00 0.00

FIRE 0.3074 1.00 0.00 0.00

ICBC 16.652 1.00 0.00 0.00

BIOG 6.0915 1.00 0.00 0.00



### (2) Calibrate the ozone response in the ozone AQAT using CAMx modeling of the 2017 base

and 2017 illustrative control case

Next, the estimate of the monitor specific ozone responses under the illustrative control

case was used to calibrate the ozone AQAT to CAMx. First, the changes in ozone predicted by

the ozone AQAT and CAMx for the average design values were calculated for each monitor for

the illustrative control case relative to the 2017 base case concentrations. The difference from

CAMx was then divided by the difference from the ozon e AQAT , resulting in a monitor

- specific

calibration factor (see Table C

- 2 for an example calculation). The calculation of these monitor

specific calibration factors provided EPA with the ability to align the ozone response predicted

by the ozone AQAT to t he ozone response p redicted by CAMx at a level of N O

x 

### reductions that

EPA expected to be close to the range of all emission reductions examined by EPA

. The ozone AQAT and CAMx concentration differences can be found in the

“ o zone_AQAT .xlsx ” excel workbook o n worksheet “ 2017 contributions uncalibrated ” in

columns BN and BO , respectively. The calibration factor can be found in column BP of the

aforementioned excel worksheet.

### 22

Table C

- 2. Ozone Contributions in the 2017 Base Case and 2017 Illustrative Control Case

Calibration Scenario from CAMx and Uncalibrated Ozone AQAT for Monitor Number

240251001 in Harford County, Maryland ( See Table C

- 1). These Values are then Used to

Create a Calibration Factor

.

2017 Base Case

Ozone

Concentration

( ppb) Estimated 201 7

Illustrative Control

Case Calibration

Scenario Ozone

Concentration (ppb) Estimated

Change in

Concentration

CAMx 81.369 80.469

- 0.900

Ozone AQAT 81.369 78.803

- 2.56 6

Calibration Factor

– Change in

Concentration f

rom CAMx Divided

b y Change in Concentration f rom t he

O zone AQAT 0.3508



### (3) Create a calibrated version of the ozone AQAT for cost threshold analysis

Next, EPA created the calibrated version of the ozone AQAT for the cost threshold

analysis. EPA used emissions, air quality ozone contributions , and calibration factors to estimate

the change in predicted ozone due to N O

x 

### emission reductions under each cost threshold

evaluated. First, as described in step 2, EPA calculated ozone

- season state

- level 2017 base case

total N O

x 

### emissions. EPA calculated the state

- level total emissions using both IPM v5.14 as

well as v 5.15. Th us, in all cost threshold simulations, the contributions for all states were

adjusted (either to the base level or to a cost level using IPM v5.15). Next, b ecause the

emissions from all other sectors are constant, EPA focused on the differences in EGU emi ssions

between each cost threshold and the 2017 base case using IPM v 5.14 (see Table B

- 3 for the

emission differences ) 19



### . Finally, EPA calculated the ratio of the emission differences to the

total 20 

### NO

x 

### emissions for the 2017 base case (using IPM v. 5

. 14) for each state modeled in

CAMx (see Table C

- 1) . More information on the emissions inventories can be found in

preamble and in the NODA

. For each cost threshold level analyzed, on a receptor

- by

- receptor basis, the emissions

change for each upwind state is associated with one of two cost threshold levels (either the IPM

v5.15 base case emissions level or the particular threshold cost level) depending on whether the

upwind state is “linked” to that receptor or if the receptor is located within the state . St ates that

are contributing above the air quality threshold (i.e., greater than or equal to 1 percent

19 We note that the total ozone

- season NO

x emissions from the IPM “all units” outputs used in the assessment tool

air quality analysis and the EGU emissions used in the CAMx air quality modeling were slightly different (i.e., some

“all units” emissions are apportioned to different sectors in the emission in ventory used in CAMx). However,

within ozone AQAT, because the difference in emissions were consistently calculated using IPM’s “all units”, the

resulting air quality estimates are not affected.

20 The total emissions from all anthropogenic sources (exclud ing Biogenics and Fires), coinciding with the emissions

that were “tagged” in the source

- apportionment modeling

.

### 23

contribution of ozone ) to the monitor, as well as the stat e containing the monitor, make N O

x 

### emissions reductions available at the particular threshold lev el. The emissions for all other states

are adjusted to the IPM v 5.15 base case level (from the IPM v. 5.14 base case level)

. For the three regulatory control alternatives , all states were adjusted to the emission

levels in the case, regardless of whether the state was “linked”. These scenarios examine the

emission results when budgets have been applied to the 23

- state geography.

For each monitor, the predicted 2017 change in contribution of ozone from each state is

calculated by mul tiplying the state s pecific 2017 IPM v5.14 base case ozone contribution b y the

calibration factor as well as by the ratio of the change in emissions ( T able B

- 3 , for either the cost

threshold level or the IPM v. 5.15 base case level depending on whether the state is linked and

divided by the total 2017 IPM v. 5.14 base case emissions for all sectors (Table C

- 1) ) . This

calibrated change in ozone is then added to the ozone contribution from the 2017 IPM v5.14 base

case modeling. The result is the “calibrated” total ozone contribution

. For each monitor, these state

- level “calibrated” contributions are then summed to

estimate total ozone contribution from the states in the CAMx modeling domain. Finally,

“other” modeled ozone contributions (“TRIBAL”, “CNMX”, “OFFSHORE”, ” FIRE”, “ICBC”,

and “BIOG”) are added from the 2017 IPM v. 5.14 base case modeling to the state contributions

to account for other sources of ozone affecting the modeling domain. The total ozone from all

the states and “other” contributions equals the aver age design values estimated in the assessment

tool

. The maximum design values were estimated by multiplying the estimated average design

values by the ratio of the modeled 2017 IPM v5.14 base case maximum to average design values.

Generally, a s the cost t hreshold value increased, the estimated average and maximum

design values at each receptor decreased. In the assessment tool , the estimated value of the

average design value was used to estimate whether the location will be out of attainment, while

the es timated maximum design value was used to estimate whether the location w ill be out of

maintenance. The area was noted as having a nonattainment or maintenance issue if its

estimated air quality level was greater than or equal to 76 ppb

.

3. Description of the results of the analysis using the assessment tool for the approach.

This section describes the results of the IPM v5.15 base case and cost threshold analysis

using the ozone AQAT . In section C.2 of this TSD, we described the construction of the oz one

AQAT to estimate the air quality im pacts of various levels of EGU N O

x 

### emissions.

As described in section B, EPA examined a number of different emission scenarios: the

IPM 5.15 base case; the illustrative control case; cost threshold levels of $500/ton , $1,300/ton,

$3,400/ton, $5,000/ton, $6,400/ton, and $10,000/ton; and three regulatory control alternatives

( i.e., proposed EGU NO

x 

### emissions budgets, and more and less stringent alternatives )

. The average and maximum design values (ppb) estimated using the assessment tool for

each identified receptor for each cost threshold level can be found in Table s C

- 3 and C

- 4,

respectively. The monitors are in alphabetical order by state . No monitors are estimated to have

resolved their average design value proble ms (i.e., estimated nonattainment) at any of the N O

x 

### cost threshold s examined when examined across the IPM v. 5.15 scenarios . However, the

average design value for two monitors dropped below 76 ppb in the transition from the IPM v.

5.14 to IPM v. 5.15 bas e cases 21



### .

21 Monitors 360850067 in Richmond , New York and 390610006 in Hamilton , Ohio.

### 24

Many monitors are projected to have maintenance issues at all cost levels. However,

some monitors have their maintenance issues solved at various cost levels. In the IPM 5.15 base

case, Monitors 261630019 in Wayne County, Michigan, 340230011 in Middlesex, New Jersey,

420031005 in Allegheny, Pennsylvania, and 480850005 in Colin, Texas are estimated to not

have maintenance issues

. No states appear to be solely linked to these receptors.

Examining the incremental difference in receptors at the $500/ton cost threshold (where

non

- linked states are kept at IPM v5.15 emission levels), we estimate that maintenance problems

for monitor s 340290006 in New Jersey and 211850004 in Kentucky would be resolved.

However, no states are linked solely to these receptor s

. At the $1,300/ton cost threshold, five additional monitors are projected to be clean.

These are monitors 211110067 in Kentucky, 240053001 in Maryland, 340150002 in New Jersey,

390610006 i n Ohio, and 482010026 in Texas. North Carolina is linked solely to monitor

240053001 in Baltimore Maryland.

At the $3,400/ton cost threshold, one additional monitor 481211032 in Texas is estimated

to have a clean maintenance value. No states are solely l inked to this monitor.

No additional monitors are projected to be clean until the $10,000/ton level, where one

monitor, 421010024 in Pennsylvania, is projected to have a clean maintenance value. At the

$6,400/ton cost level, Tennessee was linked solely to this monitor.

In the assessment of air quality using the calibrated assessment tool

, we are able to

estimate the relative contributions of particular upwind states contributing to a particular

estimated design value s

. As noted, at ea ch of the cost levels up to $10,0 00/ton, we also

compared each state ’ s adjusted ozone concentration against the 1% air quality threshold

. Aside

from North Carolina at $1,300/ton and Tennessee at $10,000/ton

, where their final monitor is

clean, w e did not see instances where a state’s contributions dropped below 1% of the NAAQS

for all of its linkages.

Lastly, once the budgets for the rule were established (based on the results of the multi

factor test) and IPM was used to model compliance with the rule, it was possible to est imate air

quality concentrations at each downwind receptor using the ozone AQAT for each of the three

regulatory control alternatives . Average and maximum design value estimates for the “ less

stringent alternative ”

, the “ proposed emissions budgets ”, and the “ more stringent alter na tive ”

can be found in Tables C

- 5 and C

- 6

. The design value results (i.e., which receptors are estimated

to have nonattainment and/or maintenance problems) for the proposed emissions budgets

scenario are similar to that of the $1, 300/ton cost threshold.

### 25

Table C

- 3. Average O zone DVs ( ppb) for N O

x 

### Cost Thresholds ($/ton) Assessed Using the

Ozone AQAT

.

Monitor

Identification

Number State County CAMx

2017 5.14

Base

Case

(ppb) Assessment Tool Average Ozone Design Values (ppb).

5.15

Base

Case $500 $1,300 $3,400 $5,000 $6,400 $10,000

90010017 Connecticut Fairfield 75.8 75.6 75.6 75.3 75.3 75.3 75.3 75.3

90013007 Connecticut Fairfield 77.1 76.9 76.8 76.5 76.5 76.5 76.5 76.4

90019003 Connecticut Fairfield 78.0 77.9 77.8 77.5 77.5 77.5 77.5 77.5

90099002 Connecticut New Haven 77.2 77.1 77.1 76.9 76.9 76.9 76.9 76.9

211110067 Kentucky Jefferson 75.8 74.6 73.9 72.9 72.8 72.8 72.7 72.5

211850004 Kentucky Oldham 73.7 72.5 71.8 70.7 70.7 70.6 70.5 70.3

240053001 Maryland Baltimore 73.2 73.3 73.0 72.5 72.4 72.4 72.3 72.3

240251001 Maryland Harford 81.3 81.4 81.1 80.5 80.4 80.4 80.3 80.3

260050003 Michigan Allegan 75.5 75.1 75.0 74.9 74.9 74.9 74.8 74.8

261630019 Michigan Wayne 74.0 73.5 73.4 73.3 73.2 73.2 73.2 73.2

340071001 New Jersey Camden 74.2 73.8 73.6 72.6 72.6 72.6 72.6 72.6

340150002 New Jersey Gloucester 75.1 74.7 74.5 73.4 73.3 73.3 73.3 73.3

340230011 New Jersey Middlesex 73 72.5 72.3 71.2 71.2 71.1 71.1 71.1

340290006 New Jersey Ocean 73.9 73.4 73.2 72.1 72.1 72.1 72.0 72.0

360810124 New York Queens 75.7 75.4 75.3 74.8 74.8 74.8 74.8 74.8

360850067 New York Richmond 76.3 75.9 75.7 74.9 74.9 74.8 74.8 74.8

361030002 New York Suffolk 79.2 79.0 79.0 78.7 78.7 78.7 78.7 78.7

390610006 Ohio Hamilton 76.3 74.7 73.4 71.7 71.6 71.6 71.5 71.2

420031005 Pennsylvania Allegheny 75.3 74.5 74.2 72.2 72.2 72.2 72.2 72.1

421010024 Pennsylvania Philadelphia 75.1 74.6 74.3 72.8 72.8 72.8 72.7 72.7

480391004 Texas Brazoria 81.4 81.2 81.1 81.1 81.1 81.0 81.0 81.0

480850005 Texas Collin 74.9 74.6 74.6 74.5 74.5 74.4 74.4 74.4

481130069 Texas Dallas 74.0 73.7 73.7 73.6 73.6 73.5 73.5 73.5

481130075 Texas Dallas 75.8 75.5 75.5 75.5 75.4 75.4 75.4 75.4

481210034 Texas Denton 76.9 76.7 76.7 76.6 76.6 76.6 76.5 76.5

481211032 Texas Denton 75.1 74.9 74.9 74.8 74.7 74.7 74.7 74.7

482010024 Texas Harris 75.9 75.8 75.8 75.8 75.8 75.7 75.7 75.7

482010026 Texas Harris 73.5 73.4 73.4 73.4 73.3 73.3 73.3 73.3

482010055 Texas Harris 75.4 75.3 75.3 75.2 75.2 75.2 75.2 75.2

482011034 Texas Harris 76.8 76.7 76.7 76.6 76.6 76.6 76.6 76.6

482011039 Texas Harris 78.2 78.1 78.1 78.0 78.0 78.0 78.0 78.0

482011050 Texas Harris 74.6 74.5 74.5 74.4 74.4 74.4 74.4 74.4

484390075 Texas Tarrant 75.5 75.3 75.2 75.2 75.1 75.1 75.1 75.1

484392003 Texas Tarrant 79.6 79.4 79.3 79.3 79.2 79.2 79.2 79.2

484393009 Texas Tarrant 78.6 78.4 78.4 78.3 78.3 78.2 78.2 78.2

484393011 Texas Tarrant 74.5 74.2 74.2 74.1 74.0 74.0 74.0 74.0

551170006 Wisconsin Sheboygan 77.0 76.7 76.6 76.6 76.6 76.5 76.5 76.5

### 26

Table C

- 4 . Maximum O zone DVs (ppb) for NO

x 

### Cost Thresholds ($/ton) Assessed Using the

Ozone AQAT

.

Monitor

Identification

Number State County CAMx

2017 5.14

Base

Case

(ppb) Assessment Tool Maximum Ozone Design Values (ppb).

5.15

Base

Case $500 $1,300 $3,400 $5,000 $6,400 $10,000

90010017 Connecticut Fairfield 78.4 78.2 78.1 77.8 77.8 77.8 77.8 77.8

90013007 Connecticut Fairfield 81.4 81.2 81.1 80.8 80.8 80.7 80.7 80.7

90019003 Connecticut Fairfield 81.1 80.9 80.9 80.6 80.5 80.5 80.5 80.5

90099002 Connecticut New Haven 80.2 80.1 80.0 79.9 79.9 79.9 79.9 79.9

211110067 Kentucky Jefferson 78.6 77.3 76.6 75.6 75.5 75.4 75.4 75.1

211850004 Kentucky Oldham 77.3 76.0 75.3 74.2 74.1 74.1 74.0 73.7

240053001 Maryland Baltimore 76.2 76.3 76.0 75.4 75.4 75.3 75.3 75.2

240251001 Maryland Harford 84.0 84.1 83.8 83.2 83.1 83.0 83.0 83.0

260050003 Michigan Allegan 78.5 78.1 78.0 77.9 77.9 77.8 77.8 77.8

261630019 Michigan Wayne 76.2 75.7 75.6 75.4 75.4 75.4 75.4 75.4

340071001 New Jersey Camden 78.1 77.6 77.4 76.4 76.4 76.4 76.4 76.3

340150002 New Jersey Gloucester 77.5 77.1 76.8 75.7 75.7 75.6 75.6 75.6

340230011 New Jersey Middlesex 76.3 75.8 75.6 74.4 74.4 74.4 74.4 74.3

340290006 New Jersey Ocean 76.6 76.1 75.8 74.7 74.7 74.7 74.7 74.6

360810124 New York Queens 77.6 77.3 77.2 76.7 76.7 76.7 76.7 76.7

360850067 New York Richmond 77.8 77.4 77.3 76.5 76.4 76.4 76.4 76.4

361030002 New York Suffolk 80.8 80.6 80.6 80.3 80.3 80.3 80.3 80.3

390610006 Ohio Hamilton 79.1 77.4 76.1 74.4 74.3 74.2 74.1 73.8

420031005 Pennsylvania Allegheny 76.5 75.7 75.4 73.4 73.3 73.3 73.3 73.3

421010024 Pennsylvania Philadelphia 78.4 77.9 77.6 76.1 76.0 76.0 76.0 75.9

480391004 Texas Brazoria 82.3 82.1 82.1 82.0 82.0 82.0 81.9 81.9

480850005 Texas Collin 76.0 75.8 75.8 75.7 75.6 75.6 75.6 75.6

481130069 Texas Dallas 78.0 77.7 77.7 77.6 77.5 77.5 77.5 77.5

481130075 Texas Dallas 76.7 76.5 76.4 76.4 76.3 76.3 76.3 76.3

481210034 Texas Denton 79.4 79.2 79.2 79.1 79.0 79.0 79.0 79.0

481211032 Texas Denton 76.3 76.0 76.0 76.0 75.9 75.9 75.8 75.8

482010024 Texas Harris 78.5 78.4 78.4 78.3 78.3 78.3 78.3 78.3

482010026 Texas Harris 76.1 76.0 76.0 75.9 75.9 75.9 75.9 75.9

482010055 Texas Harris 77.0 76.9 76.9 76.8 76.8 76.8 76.7 76.7

482011034 Texas Harris 77.8 77.6 77.6 77.6 77.5 77.5 77.5 77.5

482011039 Texas Harris 80.2 80.0 80.0 80.0 79.9 79.9 79.9 79.9

482011050 Texas Harris 76.2 76.1 76.1 76.0 76.0 76.0 76.0 76.0

484390075 Texas Tarrant 76.4 76.2 76.2 76.1 76.1 76.0 76.0 76.0

484392003 Texas Tarrant 82.1 81.8 81.8 81.7 81.7 81.6 81.6 81.6

484393009 Texas Tarrant 78.6 78.4 78.4 78.3 78.3 78.2 78.2 78.2

484393011 Texas Tarrant 76.6 76.3 76.3 76.2 76.2 76.1 76.1 76.1

551170006 Wisconsin Sheboygan 79.4 79.2 79.1 79.0 79.0 79.0 79.0 79.0

### 27

Table C

- 5

. Average O zone DVs (ppb) Three Remedy Control Alternatives Assessed Using the

Assessment Tool.

Monitor

Identification

Number State County CAMx

2017 5.14

Base Case

(ppb) Assessment Tool Average Ozone Design

Values (ppb).

Less

Stringent

Alternative Proposed

Emissions

Budgets More

Stringent

Alternative

90010017 Connecticut Fairfield 75.8 75.5 75.2 75.2

90013007 Connecticut Fairfield 77.1 76.8 76.5 76.5

90019003 Connecticut Fairfield 78.0 77.8 77.5 77.5

90099002 Connecticut New Haven 77.2 77.1 76.9 76.9

211110067 Kentucky Jefferson 75.8 74.0 72.9 72.9

211850004 Kentucky Oldham 73.7 71.8 70.8 70.8

240053001 Maryland Baltimore 73.2 73.0 72.4 72.4

240251001 Maryland Harford 81.3 81.1 80.5 80.4

260050003 Michigan Allegan 75.5 75.0 74.9 74.9

261630019 Michigan Wayne 74.0 73.4 73.3 73.3

340071001 New Jersey Camden 74.2 73.6 72.6 72.6

340150002 New Jersey Gloucester 75.1 74.5 73.4 73.3

340230011 New Jersey Middlesex 73.0 72.3 71.1 71.1

340290006 New Jersey Ocean 73.9 73.1 72.1 72.0

360810124 New York Queens 75.7 75.3 74.8 74.8

360850067 New York Richmond 76.3 75.7 74.9 74.8

361030002 New York Suffolk 79.2 79.0 78.7 78.7

390610006 Ohio Hamilton 76.3 73.4 71.8 71.8

420031005 Pennsylvania Allegheny 75.3 74.2 72.2 72.2

421010024 Pennsylvania Philadelphia 75.1 74.3 72.8 72.8

480391004 Texas Brazoria 81.4 81.2 81.1 81.1

480850005 Texas Collin 74.9 74.6 74.5 74.5

481130069 Texas Dallas 74.0 73.7 73.6 73.6

481130075 Texas Dallas 75.8 75.5 75.5 75.5

481210034 Texas Denton 76.9 76.7 76.6 76.6

481211032 Texas Denton 75.1 74.9 74.8 74.8

482010024 Texas Harris 75.9 75.8 75.8 75.8

482010026 Texas Harris 73.5 73.4 73.4 73.4

482010055 Texas Harris 75.4 75.3 75.2 75.2

482011034 Texas Harris 76.8 76.7 76.6 76.6

482011039 Texas Harris 78.2 78.1 78.0 78.0

482011050 Texas Harris 74.6 74.5 74.4 74.4

484390075 Texas Tarrant 75.5 75.2 75.2 75.2

484392003 Texas Tarrant 79.6 79.3 79.3 79.3

484393009 Texas Tarrant 78.6 78.4 78.3 78.3

484393011 Texas Tarrant 74.5 74.2 74.1 74.1

551170006 Wisconsin Sheboygan 77.0 76.6 76.6 76.6

### 28

Table C

- 6. Maximum Ozone DVs (ppb) Three Remedy Control Scenarios Assessed Using the

Assessment Tool.

Monitor

Identification

Number State County CAMx 2017

5.14 Base

Case (ppb) Assessment Tool Maximum Ozone Design

Values (ppb).

Less

Stringent

Alternative Proposed

Emissions

Budgets More

Stringent

Alternative

90010017 Connecticut Fairfield 78.4 78.1 77.8 77.8

90013007 Connecticut Fairfield 81.4 81.1 80.7 80.7

90019003 Connecticut Fairfield 81.1 80.9 80.5 80.5

90099002 Connecticut New Haven 80.2 80.0 79.8 79.8

211110067 Kentucky Jefferson 78.6 76.7 75.6 75.6

211850004 Kentucky Oldham 77.3 75.3 74.2 74.2

240053001 Maryland Baltimore 76.2 76.0 75.4 75.4

240251001 Maryland Harford 84.0 83.8 83.1 83.1

260050003 Michigan Allegan 78.5 78.0 77.9 77.9

261630019 Michigan Wayne 76.2 75.6 75.4 75.4

340071001 New Jersey Camden 78.1 77.4 76.4 76.4

340150002 New Jersey Gloucester 77.5 76.9 75.7 75.7

340230011 New Jersey Middlesex 76.3 75.6 74.4 74.4

340290006 New Jersey Ocean 76.6 75.8 74.7 74.7

360810124 New York Queens 77.6 77.2 76.7 76.7

360850067 New York Richmond 77.8 77.3 76.4 76.4

361030002 New York Suffolk 80.8 80.6 80.3 80.3

390610006 Ohio Hamilton 79.1 76.1 74.4 74.4

420031005 Pennsylvania Allegheny 76.5 75.4 73.4 73.4

421010024 Pennsylvania Philadelphia 78.4 77.6 76.1 76.0

480391004 Texas Brazoria 82.3 82.1 82.0 82.0

480850005 Texas Collin 76.0 75.8 75.7 75.7

481130069 Texas Dallas 78.0 77.7 77.6 77.6

481130075 Texas Dallas 76.7 76.5 76.4 76.4

481210034 Texas Denton 79.4 79.2 79.1 79.1

481211032 Texas Denton 76.3 76.0 76.0 76.0

482010024 Texas Harris 78.5 78.4 78.3 78.3

482010026 Texas Harris 76.1 76.0 75.9 75.9

482010055 Texas Harris 77.0 76.9 76.8 76.8

482011034 Texas Harris 77.8 77.6 77.6 77.6

482011039 Texas Harris 80.2 80.0 80.0 80.0

482011050 Texas Harris 76.2 76.1 76.0 76.0

484390075 Texas Tarrant 76.4 76.2 76.1 76.1

484392003 Texas Tarrant 82.1 81.8 81.7 81.7

484393009 Texas Tarrant 78.6 78.4 78.3 78.3

484393011 Texas Tarrant 76.6 76.3 76.2 76.2

551170006 Wisconsin Sheboygan 79.4 79.1 79.0 79.0

### 29



# Appendix A: IPM Runs Used in Transport Rule Significant

Contribution Analysis

### 30

Table A

- 1 lists IPM runs used in the significant contribution analysis. The IPM runs can

be found in the docket for this rulemaking.

Table Appendix A

- 1. IPM Runs Used in Transport Rule Significant Contribution Analysis

Run Name Run Description

5.14_ Base_Case Base Case model run, which includes the national Title IV SO 2 cap

- and

- trade

program; NO

x SIP Call regional ozone season cap

- and

- trade program; the Cross

State Air Pollution trading programs, and set tlements and state rules

. This is

based on AEO estimates from 2014.

5.14_ OS_NOx_ 500_CT Imposes a marginal cost of $500 per ton of ozone season NO

x in all states

starting in 2017. Also forces all extant and currently operating SCR to operate

at “full operation”. Created using IPM v5.14.

5.14_ OS_NOx_ 1300_CT Imposes a marginal cost of $1,300 per ton of ozone season NO

x in all states

starting in 2017. Also forces all extant and currently operating SCR to operate

at “full operation” and all non

- operating SCR are returned to “full operation”.

Units without SOA combustion controls upgraded to SOA combustion controls.

Created using IPM v5.14.

5.14_ OS_NOx_ 3400_CT Imposes a marginal cost of $3,400 per ton of ozone season NO

x in all states

starting in 2017. Also forces all extant and currently operating SCR to op erate

at “full operation” and all non

- operating SCR are returned to “full operation”.

Units without SOA combustion controls upgraded to SOA combustion controls.

Units with SNCR “fully operate” those controls. Created using IPM v5.14.

5.14_ OS_NOx_ 5000_C T Imposes a marginal cost of $5,000 per ton of ozone season NO

x in all states

starting in 2017. Also forces all extant and currently operating SCR to operate

at “full operation” and all non

- operating SCR are returned to “full operation”.

Units without SOA combustion controls upgraded to SOA combustion controls.

Units with SNCR “fully operate” those controls. Created using IPM v5.14.

5.14_ OS_NOx_ 6200_CT Imposes a marginal cost of $6,200 per ton of ozone season NO

x in all states

starting in 20 17. Also forces all extant and currently operating SCR to operate

at “full operation” and all non

- operating SCR are returned to “full operation”.

Units without SOA combustion controls upgraded to SOA combustion controls.

Units with SNCR “fully operate” those controls. Created using IPM v5.14.

5.14_ OS_NOx_ 10000_CT Imposes a marginal cost of $10,000 per ton of ozone season NO

x in all states

starting in 2017. Also forces all extant and currently operating SCR to operate

at “full operation” and all non

- operating SCR are returned to “full operation”.

Units without SOA combustion controls upgraded to SOA combustion controls.

Unit s with SNCR “fully operate” those controls. Created using IPM v5.14.

5.14_OS_NO x

_ Illustrative_Control_Case Imposes the state emission limits with variability limits derived from the $1,300

per ton of NO

x case were applied to states covered by this proposa l. Units with

SCRs operate them at “full operation” and units with SCRs that are not

operating return them to “full operation”. Units without SOA combustion

controls upgraded to SOA combustion controls. Created using IPM v 5.14. This

run is also called the “Illustrative Control Case”

5.15_ Base_Case Base Case model run, which includes the national Title IV SO 2 cap

- and

- trade

program; NO

x SIP Call regional ozone season cap

- and

- trade program; the Cross

State Air Pollution trading programs, and settlements and state rules. This is

based on AEO estimates from 2015 and includes the final Clean Power Plan.

5.15_ OS_NOx _500_ CT Imposes a marginal cost of $500 per ton of ozone season NO

x in all states

starting in 2017. Also forces all extant and currently operating SCR to operate

at “full operation”. Created using IPM v5.15.

5.15_ OS_NOx_1300_CT Imposes a marginal cost of $1,300 per ton of ozone season NO

x in all states

starting in 2017. Also forces all extant and currently operating SCR to operate

at “full operation” and all non

- operating SCR are returned to “full operation”.

### 31 Units without SOA combustion controls upgraded to SOA combustion controls.

Created using IPM v5.15.

5.15_ OS_NOx_3400_CT Imposes a marginal cost of $3,400 per ton of ozone season NO

x in all states

starting in 2017. Also forces all extant and currently operating SCR to operate

at “full operation” and all non

- operating SCR are returned to “full operation”.

Units without SOA combustion controls upgraded to SOA combustion controls.

Uni ts with SNCR “fully operate” those controls. Created using IPM v5.15.

5.15_ OS_NOx_5000_CT Imposes a marginal cost of $5,000 per ton of ozone season NO

x in all states

starting in 2017. Also forces all extant and currently operating SCR to operate

at “ full operation” and all non

- operating SCR are returned to “full operation”.

Units without SOA combustion controls upgraded to SOA combustion controls.

Units with SNCR “fully operate” those controls. Created using IPM v5.15.

5.15_ OS_NOx_6400_CT Imposes a marginal cost of $6,400 per ton of ozone season NO

x in all states

starting in 2017. Also forces all extant and currently operating SCR to operate

at “full operation” and all non

- operating SCR are returned to “full operation”.

Units without SOA combustion controls upgraded to SOA combustion controls.

Units with SNCR “fully operate” those controls. Created using IPM v5.15.

5.15_ OS_NOx_10000_CT Imposes a marginal cost of $10,000 per ton of ozone season NO

x in all states

starting in 2017. Also forces all extant and currently operating SCR to operate

at “full operation” and all non

- operating SCR are returned to “full operation”.

Units without SOA combustion controls upgraded to SOA combustion controls.

Units with SNCR “fully operate” those controls. Created using IPM v5.15.

5.15_ OS_NOx_ Less_Stringent Imposes the budgets with variability limits derived from the $500 per ton of NO

x case were applied to states covered by this proposal. Units with SCRs operate

them at “full operation”. Created using IPM v5.15.

5.15_ OS_NOx_ Proposed Imposes the budgets with variability limits derived from the $1,300 per ton of

NO

x case were applied to states covered by this proposal. Units with SCRs

operate them at “full operation” and units with SCRs that are not operating

return them to “full operation”. Units without SOA combustion controls

upgraded to SOA combustion controls. Created using IPM v5.15.

5.15_ OS_NOx_ More_Stringent Im poses the budgets with variability limits derived from the $3,400 per ton of

NO

x case were applied to states covered by this proposal . Units with SCRs

operate them at “full operation” and units with SCRs and SNCRs that are not

operating return them to “fu ll operation”. Units without SOA combustion

controls upgraded to SOA combustion controls. Created using IPM v5.15.

### 32



# Appendix B : Description of Excel Spreadsheet Data Files for the

Significant Contribution Analysis

### 33

EPA placed the following Excel workbook file in the Transport Rule docket

.

The annual and quarterly emissions for all AQAT simulations can be found in this file.

sensitivity_tool .xlsx

. This workbook contains a number of worksheets.

State

- level emissi on totals used in the modeling

 “2017eh (base)” contains state and source

- sector specific ozone

- season NO

x 

### emission

totals for the 5.14 base case. Column D, “TOTAL w/o beis, fires” is an input in the tool.

 “2017eh (illustrative control)” contains state an d source

- sector specific ozone

- season

NO

x 

### emission totals for the illustrative control case. Column D, “TOTAL w/o beis,

fires” is an input in the tool for use in development of the calibration factor.

 “State Level Emissions” are the total ozone

- season NO

x 

### emissions from IPM for the

various base, cost thresholds (CT), and regulatory control alternatives

. The results

include totals for “all units” and for all fossil units greater than 25 MW for 2018. Results

also include totals for “all units” for 2017 (t he sum of the results for 2018 plus the values

from “2017 additions”).

 “2017 additions” includes emissions from units that are projected to remain in operation

in 2017, but are retired in 2018.

 “IPM Summary” contains the emission difference (in tons) betwe en the 5.14 base case

for all units and each of the other scenarios.

 “emission fractions” contains the emission difference as a fraction of the 2017 5.14 base

case total emissions without beis and fires. These fractions are directly used in the tool.

Column E contains the emission fraction for the illustrative control case (used in

calibration of the tool).

Air quality modeling design values from CAMx

 “CAMx O3 DVs” contains design values for three scenarios (the 2011 case, the 2017

IPM v. 5.14 base ca se, and the 2017 illustrative control case”. The average and

maximum design values are shown using one decimal place and to four decimal places”.

State

- level ozone contributions

 “2017 contributions (orig)” includes the original contributions with five decimal places of

resolution. The truncated shortened version of these contributions equal the truncated

base case average design value. See the Air Quality Modeling TSD and the preamble for

details about the contributions.

 “2017 contributions (scaled)” adjusts the “2017 contributions (orig)” using the ratio of

the four decimal place base case design value to the one decimal place base case design

value.

 “2017 contributions” contains a copy of the “2017 contributions (scaled)” contributions.

These contri butions are used throughout the rest of the assessment tool.

Air quality estimates

 “Summary DVs” contains the average and maximum design value estimates (truncated to

one decimal place) for receptors that were nonattainment or maintenance in the 2017 base

case air quality modeling. Monitors that are at or above 76.0 ppb are shaded.

### 34

 “2017 contributions uncalibrated”. Contains the unadjusted estimated change in

concentration resulting from the difference in emissions between the 2017 5.14 base case

and the illustrative control case. The calibration factor is calculated in column BP. The

ratio of the maximum to average design value for the base case is found in column BU.

This fraction is used in the other air quality worksheets to adjust the average desi gn value

to a maximum value.

 “515 base” contains the estimated state

- by

- state and receptor

- by

- receptor air quality

contributions and design values for the 2017 IPM v. 5.15 base case emissions. All states

are adjusted to the 5.15 base case emission level r egardless of whether they are “linked”

to a specific monitor.

 “500 CT” contains the contributions and design values for the $500/ton cost threshold

analysis (where non

- linked states were adjusted to the IPM v. 5.15 base case emission

level).

 “1300 CT” con tains the contributions and design values for the $1,300/ton cost threshold

analysis (where non

- linked states were adjusted to the IPM v. 5.15 base case emission

level).

 “3400 CT” contains the contributions and design values for the $3,400/ton cost thresho ld

analysis (where non

- linked states were adjusted to the IPM v. 5.15 base case emission

level).

 “5000 CT” contains the contributions and design values for the $5,000/ton cost threshold

analysis (where non

- linked states were adjusted to the IPM v. 5.15 bas e case emission

level).

 “6400 CT” contains the contributions and design values for the $6,400/ton cost threshold

analysis (where non

- linked states were adjusted to the IPM v. 5.15 base case emission

level).

 “10000 CT” contains the contributions and design values for the $10,000/ton cost

threshold analysis (where non

- linked states were adjusted to the IPM v. 5.15 base case

emission level).

 “ Less stringent ” contains the estimated state

- by

- state and receptor

- by

- receptor air quality

contributions and design val ues for the $500/ton policy case emissions. All states are

adjusted to this emission level regardless of whether they are “linked” to a specific

monitor.

 “ Proposed budgets ” contains the estimated state

- by

- state and receptor

- by

- receptor air

quality contri butions and design values for the $1,300/ton policy case emissions. All

states are adjusted to this emission level regardless of whether they are “linked” to a

specific monitor.

 “ More stringent ” contains the estimated state

- by

- state and receptor

- by

- recep tor air

quality contributions and design values for the $3,400/ton policy case emissions. All

states are adjusted to this emission level regardless of whether they are “linked” to a

specific monitor.

 The “10000 CT (links)”, “6400 CT (links)”, “5000 CT (l inks)”, “ 3400 CT (links) ”

, “ 1300

CT (links) ”

, “ 500 CT (links) ”

, “ 515 Base (links) ”

, “ More stringent (links)”, “ Proposed

budgets (links) ” , “ Less stringent (links)” worksheets assess the linkages for the 1%

threshold. A contribution is set to zero if the maximum design value is less than 76.0 ppb

or if it is a contribution from the state containing the monitor (i.e., “home” state).

Compare rows 4 and 5 to look for linkages that affect whether a state is no longer linked

### 35

to a monitor that continues to have air quality issues. A value of 1 indicates that the state

is “linked”. Note that we are particularly interested in states where there is a value of 1 in

row 4 an d no value in row 5.

### 36



# Appendix C : Description of 2017 Adjustments to 2018 IPM EGU

Ozone

- Season NO X 

# Emissions Data

### 37

To calculate the 2017 emissions for the base case, uniform NO X 

### cost threshold cases, proposed

remedy and alternative cases, and produce a flat files for air quality modeling, EPA started with

the 2018 Base Case results and made modifications to emissions of units in three categories as

described in the table below.

Table Appendix C

- 1 . Description of 201 7 ozone

- season NO X 

### Adjustment Calculation

2017 ozone

- season NO X 

### Adjustment Case How 2017 Adjustments Were Calculated

SCR Operation/Installation For units that had an SCR in 2018 but were assumed to not operate

(or be installed) in 2017, EPA recalculated the NO X 

### emissions for

the unit with the 2018 heat input and the 2016 emissions rate

Retirement For units projected to retire in 2018, emissions from the 2016 run

year were included in the 2017 emissions

For uniform NO X 

### cost threshold cases and policy alt ernative cases,

emissions from units with SCRs were determined by multiplying

their heat input in the 2016 run year by their optimized NO X



### removal rate.

Coal

- To

- Gas For units that had implemented coal

- to

- gas retrofit options in 2018

and had not dispatche d, emissions from the 2016 run year were

incorporated. However, if the coal

- to

- gas retrofit options had

dispatched in 2018, then the NO X 

### emissions were calculated based

on the 2018 fuel use and 2016 NO X 

### rate.

The tables below lists the units that were a ffected by these changes and for each case the number

of tons of ozone season NO X 

### added to the 2018 results to calculate the 2017 ozone season NO X 

### emissions. Units may not have added emissions in every case. Separate tables are provided to

show adjustments for IPM v5.14 and IPM v5.15 cases. These adjustments are summarized at the

state level in Appendix E.

Table Appendix C

- 2. Incremental ozone season NO X 

### emissions added to 2018 IPM v5.14

cases to calculate 2017 ozone season NO X 

### emissions.

NEEDS ID Reason for

Adjustment

( Ozone

Transport Base

Case) Base Case

Incremental

Ozone Season

NOx (tons) Reason for

Adjustment

( Illustrative Control

Case) Proposed

Remedy Case

Incremental

Ozone Season

NOx (tons)

113_B_2 

### SCR Retrofit 922 SCR Retrofit 590

113_B_3 

### SCR Retrofit 918 SCR Retrofit 864

113_B_4 

### SCR Retrofit 1344 SCR Retrofit 1265

### 38

160_B_2 

### SCR Retrofit 829 SCR Retrofit 639

160_B_3 

### SCR Retrofit 1205 SCR Retrofit 1140

1710_B_3 

### 0 SCR Retrofit 0

1893_B_1 

### 0 SCR Retrofit 1

1893_B_2 

### 0 SCR Retrofit 1

1893_B_4 

### SCR Retrofit 509 SCR Retrofit 509

2442_B_4 

### SCR Retrofit 4734 SCR Retrofit 4734

2442_B_5 

### SCR Retrofit 4850 SCR Retrofit 4850

2817_B_1 

### SCR Retrofit 240 SCR Retrofit 240

2963_B_3313 

### SCR Retrofit 1176 SCR Retrofit 153

6030_B_1 

### SCR Retrofit 593 SCR Retrofit 467

6030_B_2 

### SCR Retrofit 461 SCR Retrofit 310

6076_B_1 

### SCR Retrofit 961 SCR Retrofit 595

6076_B_2 

### SCR Retrofit 935 SCR Retrofit 573

6101_B_BW91 

### SCR Retrofit 905 SCR Retrofit 905

6204_B_1 

### SCR Retrofit 1085 SCR Retrofit 1085

6204_B_2 

### SCR Retrofit 1062 SCR Retrofit 1062

6204_B_3 

### SCR Retrofit 1390 SCR Retrofit 1390

879_B_52 

### 0 SCR Retrofit 528

1378_B_1 

### Retirement 1257 Coal

- To

- Gas 1257

1378_B_2 

### Retirement 1163 Coal

- To

- Gas 1163

1378_B_3 

### Retirement 5390 Coal

- To

- Gas 5390

469_B_4 

### Coal

- To

- Gas 1666 Coal

- To

- Gas 1666

10676_B_5 

### Retirement 185 Retirement 129

667_B_1 

### Coal

- To

- Gas 166 Retirement 165

667_B_2 

### Coal

- To

- Gas 195 Retirement 194

1077_G_3 

### Retirement 24 Retirement 24

1394_B_1 

### Retirement 3 Retirement 3

1394_B_2 

### Retirement 4 Retirement 4

1394_B_5 

### Retirement 10 Retirement 10

1507_B_1 

### Retirement 4 Retirement 4

1507_B_2 

### Retirement 3 Retirement 3

1507_B_3 

### Retirement 3 Retirement 3

1507_B_4 

### Retirement 22 Retirement 22

1571_B_1 

### Retirement 710 Retirement 710

1619_B_3 

### Retirement 0 Retirement 0

1619_B_4 

### Retirement 8 Retirement 8

170_B_4 

### Retirement 51 Retirement 51

### 39

1769_B_7 

### Retirement 618 Retirement 618

1769_B_8 

### Retirement 604 Retirement 604

1769_B_9 

### Retirement 613 Retirement 613

2324_B_4 

### Retirement 975 Retirement 975

271_B_5 

### Retirement 1 Retirement 1

271_B_6 

### Retirement 1 Retirement 1

477_B_5 

### Retirement 1020 Retirement 1020

6181_B_1 

### Retirement 544 Retirement 544

6181_B_2 

### Retirement 252 Retirement 252

6183_B_SM

- 1 

### Retirement 332 Retirement 332

170_B_1* 

### 0 Adjustment for state

assurance level

specification error

- 170

170_B_2* 

### 0 Adjustment for state

assurance level

specification error

- 394

2408_B_1* 

### 0 Adjustment for state

assurance level

specification error

- 230

56963_G_E101* 

### 0 Adjustment for state

assurance level

specification error

- 53

56963_G_E102* 

### 0 Adjustment for state

assurance level

specification error

- 53

6641_B_1* 

### 0 Adjustment for state

assurance level

specification error

- 69

6641_B_2* 

### 0 Adjustment for state

assurance level

specification error

- 66

*Seven units had emissions revised downward for air quality modeling purposes because of mis

specified state assurance levels in the modeling. These adjustments were determined by a

subsequent model run , “ 5.14_OS_NOX_Proposal_AQ2 ” 

### that can be found in the docket.

### 40

Table Appendix C

- 3. Incremental ozone season NO X 

### emissions added to 2018 IPM v5.15 results to calculate 2017 ozone season

NO X 

### emissions. 22

Reason for 2017 Adjustment

Retirement

SCR Retrofit

C2G

NEEDS ID Base

Case $500/ton

Cost

Threshold $1300/ton

Cost

Threshold $3400/ton

Cost

Threshold $5000/ton

Cost

Threshold $64000/ton

Cost

Threshold $10,000/ton

Cost

Threshold Less

Stringent

Alternative Proposed

Remedy

Case More

Stringent

Alternative

10676_B_3 86

10676_B_5 129 129 129 129 129 129 129 129 129 129

113_B_2 580 580 592 876 835 825 846 594 594 594

113_B_3 874 874 874 874 874 874 874 874 874 874

113_B_4 1,280 1,280 1,280 1,280 1,280 1,280 1,280 1,280 1,280 1,280

1378_B_1 2,420 1,499 1,499 1,499 1,499 1,499 1,499 2,420 1,499 1,499

1378_B_3 2,964 2,964 670 670 670 670 670 2,964 670 670

1394_B_1 17 17 17 17 17 17 17 17 17 17

141_B_1 20 20 20 20 20 20 20 20 20 20

141_B_3 39 39 39 39 39 39 39 39 39 39

1507_B_1 4 4 4 4 4 4 4 4 4 4

1507_B_2 3 3 3 3 3 3 3 3 3 3

1507_B_3 3 3 3 3 3 3 3 3 3 3

1507_B_4 17 17 17 17 9 5 4 17 17 17

1571_B_1 587 296 293 293 293 293 293 296 296 296

1571_B_2 955 955 955 955 955 955 955 955 955 955

1572_B_1 1,180 1,180 1,180 1,058 1,058 1,058 1,058 1,180 1,180 1,071

1572_B_3 240 240 240 218 218 218 218 240 240 220

1599_B_1 0.89 0.19 0.20

1619_B_ 3 0.60 0.96 0.68 0.98 0.92 0.53 0.14 0.62 0.62 0.60

1619_B_4 82 131 94 134 126 73 20 85 85 82

22 This table shows adjustments at the NEEDS unit level. The calcu lated adjustments at the IPM model plant level can be found in the file “IPM v5.15 2017

Emissions Adjustments” in the docket for this rule.

### 41

170_B_4 51 51 51 51 51 51 51 51 51 51

1710_B_3 4 0.24 0.27 0.15 0.17 0.17 0.18 4 4 0.24

1743_B_1 142 381 366 158

1769_B_7 1,836 1,836 1,836 1,836 1,836 1,836 1,836 1,836 1,836 1,836

2104_B_3 510 560 508 506 506 597 742 619 629 665

2104_B_4 521 563 702 995 995 995 995 521 521 498

2107_B_1 158

2324_B_4 975 975 975 975 975 975 975 975 975 975

2442_B_4 4,734 4,734 4,734 4,734 4,734 4,662 4,615 4,734 4,734 4,734

2442_B_5 4,850 4,850 4,850 4,850 4,850 4,778 4,719 4,850 4,850 4,850

2454_G_1 80 80 80 80 80 80 80 80 80 80

271_B_5 1 1 1 1 1 1 1 1 1 1

2817_B_1 240 240 240 240 240 240 240 240 240 240

2963_B_3313 154 154 154 146 146 136 136 154 154 154

315_B_2 32 32 32 32 32 32 32 32 32 32

350_B_1 6 6 6 6 6 6 6 6 6 6

356_B_8 9 9 9 9 9 9 9 9 9 9

469_B_4 1,666 1,666 1,666 1,666 1,666 1,666 1,666 1,666 1,666 1,666

470_B_2 3 3 3 7 3 3 1 3 3 3

50976_B_AAB01 82 62 77 175 308 269

562_B_4 0.47 0.47 0.47 0.47 0.47 0.47 0.47

564_B_1 271

6021_B_C2 8 5 0 .26

6030_B_1 2,031 2,031 2,031 2,031 1,956 1,893 2,031 2,031 2,031 2,031

6030_B_2 218 218

6076_B_1 595 595 595 595 587 587 587 595 595 595

6076_B_2 573 573 573 573 573 573 573 573 573 573

6101_B_BW91 905 905 905 905 905 905 881 905 905 905

6165_B_1 815

6181_B_2 33 100 100 100 101

6204_B_1 851 856 874 1,084 1,079 1,063 974 851 852 852

6204_B_2 1,062 1,062 1,062 1,062 1,062 1,057 1,026 1,062 1,062 1,062

6204_B_3 1,390 1,390 1,390 1,390 1,390 1,390 1,368 1,390 1,390 1,390

667_B_1 361 361 361 361 361 361 361 361 361 361

676_B_2 6 6 6 6 6 6 6 6 6 6

### 42

861_B_01 21 21 8 17 13

879_B_62 2 2 1 2 2 2

Total 35,161 34,075 31,680 32,472 32,566 32,331 33,430 34,869 31,793 31,619



### Table Appendix C

- 4. Reason for each 2017 adjustment by unit and case (text version)

Reason for 2017 Adjustment

Retirement R

SCR Retrofit SCR

C2G C2G

NEEDS ID Base

Case $500/ton

Cost

Threshold $1300/ton

Cost

Threshold $3400/ton

Cost

Threshold $5000/ton

Cost

Threshold $64000/ton

Cost

Threshold $10,000/ton

Cost

Threshold Less

Stringent

Alternative Proposed

Remedy

Case More

Stringent

Alternative

10676_B_3 R

10676_B_5 R R R R R R R R R R

113_B_2 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

113_B_3 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

113_B_4 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

1378_B_1 R R R R R R R R R R

1378_B_3 R R R R R R R R R R

1394_B_1 R R R R R R R R R R

141_B_1 R R R R R R R R R R

141_B_3 R R R R R R R R R R

1507_B_1 R R R R R R R R R R

1507_B_2 R R R R R R R R R R

1507_B_3 R R R R R R R R R R

1507_B_4 R R R R R R R R R R

1571_B_1 R R R R R R R R R R

1571_B_2 R R R R R R R R R R

1572_B_1 R R R R R R R R R R

1572_B_3 R R R R R R R R R R

1599_B_1 R R R

1619_B_3 R R R R R R R R R R

1619_B_4 R R R R R R R R R R

### 43

170_B_4 R R R R R R R R R R

1710_B_3 R SCR SCR C2G C2G C2G C2G R R SCR

1743_B_1 R R R R

1769_B_7 R R R R R R R R R R

2104_B_3 R R R R R R R R R R

2104_B_4 R R R R R R R R R R

2107_B_1 SCR

2324_B_4 R R R R R R R R R R

2442_B_4 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

2442_B_5 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

2454_G_1 R R R R R R R R R R

271_B_5 R R R R R R R R R R

2817_B_1 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

2963_B_3313 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

315_B_2 R R R R R R R R R R

350_B_1 R R R R R R R R R R

356_B_8 R R R R R R R R R R

469_B_4 R R R R C2G R R R R R

470_B_2 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

50976_B_AAB01 R R R R R R

562_B_4 R R R R R R R

564_B_1 R

6021_B_C2 SCR SCR SCR

6030_B_1 R R R R C2G C2G R R R R

6030_B_2 C2G C2G

6076_B_1 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

6076_B_2 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

6101_B_BW91 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

6165_B_1 R

6181_B_2 R R R R R

6204_B_1 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

6204_B_2 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

6204_B_3 SCR SCR SCR SCR SCR SCR SCR SCR SCR SCR

667_B_1 R R R R R R R R R R

676_B_2 R R R R R R R R R R

### 44

861_B_01 R R R R R

879_B_62 SCR SCR SCR SCR SCR SCR

### 45



# Appendix D: Ozone

- Season NO

x 

# Emissions Budgets for IPM

Modeling

### 46

To best model the three regulatory control alternatives in IPM, EPA did not include the 2017 budget adjust ments in the state budgets.

Table Appendix D

- 1 shows the proposed 2017 state budgets and the equivalent 2018 transport region and state emission constraints

used for IPM a nalysis in the IPM v5.15 model platfor m. Data for the state budgets and assurance levels that were developed for the air

quality modeling using the IPM v5.14 platform appear in table appendix D

- 2.

Table Appendix D

- 1 . Ozone

- Season NO X 

### Emissions Budgets For IPM v5.15 Modeling

Budgets in GREY indicate states where budgets were limited based on 2014 emissions. Less Stringen t Alternative Budgets Proposed Budgets More Stringent Alternative Budgets

2016

-

2017

Budgets

(CSAPR

Phase 1) 2017

Budgets 2017

Assurance

Level 2018

Emission

Allowances

For IPM 2018 IPM

Emissions

Constraint

(Assurance

Level) for

IPM 2017

Budgets 2017

Assurance

Level 2018

Emission

Allowances

For IPM 2018 IPM

Emissions

Constraint

(Assurance

Level) for

IPM 2017

Budgets 2017

Assurance

Level 2018

Emission

Allowances

For IPM 2018 IPM

Emissions

Constraint

(Assurance

Level) for

IPM

Alabama 31,623 11,886 14,382 11,886 14,382 9,979 12,075 9,979 12,075 9,931 12,017 9,931 12,017

Arkansas 15,110 7,038 8,516 6,987 8,454 6,949 8,408 6,898 8,347 6,101 7,382 6,051 7,322

Illinois 21,208 12,144 14,694 12,121 14,667 12,078 14,614 12,069 14,604 11,992 14,510 11,992 14,511

Indiana 46,526 33,483 40,514 33,483 40,515 28,284 34,224 28,284 34,224 27,585 33,378 27,585 33,378

Iowa 16,370 8,614 10,423 8,614 10,423 8,351 10,105 8,351 10,105 8,118 9,823 8,118 9,823

Kansas 9,278 11,226 9,278 11,226 9,272 11,219 9,272 11,219 9,259 11,203 9,259 11,203

Kentucky 34,421 32,783 39,667 28,320 34,268 21,519 26,037 19,350 23,413 20,945 25,343 18,776 22,719

Louisiana 18,115 15,861 19,192 15,844 19,171 15,807 19,127 15,790 19,106 15,378 18,607 15,360 18,586

Maryland 7,179 4,026 4,871 2,155 2,607 4,026 4,871 2,160 2,613 4,026 4,871 2,160 2,614

Michigan 27,529 22,022 26,647 20,186 24,425 19,115 23,129 17,279 20,907 18,624 22,535 16,646 20,142

Mississippi 12,429 6,083 7,360 6,083 7,360 5,910 7,151 5,910 7,151 5,487 6,639 5,487 6,639

Missouri 21,944 15,380 18,610 14,257 17,251 15,323 18,541 14,113 17,077 15,240 18,440 13,740 16,625

New Jersey 3,930 2,016 2,439 2,016 2,439 2,015 2,438 2,015 2,438 2,011 2,433 2,011 2,433

New York 10,369 4,607 5,574 4,607 5,575 4,450 5,385 4,450 5,385 4,391 5,313 4,391 5,313

North

Carolina 20,312 12,278 14,856 12,278 14,856 12,275 14,853 12,275 14,853 10,705 12,953 10,705 12,953

Ohio 40,149 20,194 24,435 20,194 24,435 16,660 20,159 16,660 20,159 16,637 20,131 16,637 20,131

Oklahoma 22,694 16,215 19,620 16,215 19,620 16,215 19,620 16,215 19,620 16,215 19,620 16,215 19,620

Pennsylvania 52,057 38,270 46,306 38,270 46,306 14,387 17,408 14,387 17,408 14,358 17,373 14,358 17,373

Tennessee 11,462 5,520 6,679 5,520 6,679 5,481 6,632 5,481 6,632 5,449 6,593 5,449 6,593

Texas 65,560 58,492 70,775 58,492 73,819 58,002 70,183 57,970 70,143 55,864 67,595 55,764 67,475

Virginia 14,452 6,955 8,416 6,955 8,416 6,818 8,250 6,818 8,250 5,834 7,059 5,834 7,059

West Virginia 24,287 22,932 27,748 22,932 27,748 13,390 16,202 13,390 16,202 12,367 14,964 12,367 14,964

Wisconsin 14,540 5,588 6,761 5,588 6,761 5,561 6,729 5,561 6,729 5,511 6,668 5,511 6,669

Region cap 532,266 371,665 362,281 311,867 304,677 302,028 294,34 7

### 47

Table Appendix D

- 2. Ozone

- Season NO X 

### Emissions Budgets For IPM v5.14 M odeling

Budgets For IPM v5.14 Modeling

2016

- 2017 Budgets

(CSAPR Phase 1) 2018 Emission

Allowances s

for IPM 2018 IPM Assurance

Level for IPM

Alabama 31,623 10,474 12,673

Arkansas 15,110 9,105 11,017

Delaware 683 827

Illinois 21,208 14,109 17,072

Indiana 46,526 28,460 34,437

Iowa 16,370 9,234 11,174

Kansas 9,558 11,565

Kentucky 34,421 25,918 31,361

Louisiana 18,115 17,425 21,085

Maryland 7,179 2,389 2,891

Michigan 27,529 22,152 26,804

Mississippi 12,429 7,369 8,917

Missouri 21,944 15,215 18,410

New Jersey 3,930 2,676 3,238

New York 10,369 4,313 5,218

North Carolina 20,312 12,435 15,047

Ohio 40,149 17,951 21,720

Oklahoma 22,694 18,899 22,868

Pennsylvania 52,057 21,664 26,213

Tennessee 11,462 5,988 7,246

Texas 65,560 64,020 77,464

Virginia 14,452 7,261 8,786

West Virginia 24,287 13,687 16,562

Wisconsin 14,540 7,676 9,288

Region cap 532,266 348,663

### 48



# Appendix E: Detailed Budget Calculations

### 49

See the spreadsheet “ Ozone Transport Policy Analysis TSD Appendix E ” for detailed

calculations of state budgets and assurance levels.

### 50



# Appendix F: State Generation Constraint Analysis

### 51

As described in Preamble section VI, the EPA limited generation shifting potential to units

within e ach state in IPM as an analytic proxy designed to respect the feasibility of near

- term

generation shifting in light of these potential near

- term out

- of

- merit order dispatch constraints.

The EPA conducted a separate analysis similar to the $1,300 per ton co st threshold scenario,

except without limiting IPM’s ability to shift generation between states. 23



### The resulting state level emissions and calculated budgets from this scenario are compared to

those of the $1,300 per ton cost threshold run and proposed budgets in Table F

- 1.

Overall, removing the state generation limit constraints in IPM achieve only an additional 1686

tons of ozone season NO X 

### emissions reductions. The resulting state budgets were minimally

affected, at most seeing a 2.7% decrease in any individual state budget. The transport regional

cap decreased by only 636 tons, or 0.2%. 24



### Table F

- 1

. Comparison of state level ozone season NO X 

### emission reductions from affected

sources and resulting state budgets between the $1300 per ton cost threshold cases with and

without state level generation constraints.

2018 IPM $1,300 per ton Cost

Threshold Scenario Emissions from

Affect Units (tons) Resulting 2017 Budgets of Two

Scenarios

Proposal

States State As Proposed

With State

Generation

Limits No State

Generation

Limits Delta Proposed

Budgets Budgets Based

On No State

Generation

Limit

Scenario Delta

Y Alabama 9,708 9,709 1 9,979 9,974

- 5

Y Arkansas 6,069 5,955

- 115 6,949 6,863

- 86

Connecticut 407 407 0 325 325 0

Delaware 477 477 0 610 610 0

District of

Columbia 0 0 0 0 0 0

Florida 18,369 18,511 142 18,414 18,455 41

Georgia 7,157 7,299 142 7,307 7,358 51

Y Illinois 9,541 9,732 191 12,078 11,957

- 121

Y Indiana 29,575 29,732 158 28,284 28,626 342

Y Iowa 7,488 7,487

- 1 8,351 8,353 2

Y Kansas 10,894 10,818

- 76 9,272 9,247

- 25

Y Kentucky 13,076 13,081 5 21,519 21,528 9

Y Louisiana 10,762 10,671

- 91 15,807 15,926 119

Maine 234 234 0 150 150 0

Y Maryland 2,775 2,766

- 10 4,026 4,026 0

Massachusetts 778 672

- 107 720 684

- 36

Y Michigan 15,180 14,743

- 437 19,115 18,978

- 136

23 IPM Output files for this scenario can be found in the docket as “5.15_OS_NOx_1300_CT_NoGenLimit”

24 Details of th e budget calculations for 5.15_OS_NOx_1300_CT_NoGenLimit can be found in the docket as

“Budget Calculations For 1300CT No State Gen Limit Scenario.xlsx”

### 52

Minnesota 8,999 9,014 14 7,884 7,795

- 90

Y Mississippi 7,574 7,328

- 246 5,910 5,766

- 144

Y Missouri 14,843 14,649

- 194 15,323 15,406 82

Nebraska 13,770 13,766

- 4 10,284 10,284 0

New

Hampshire 140 140 0 106 106 0

Y New Jersey 2,931 2,930 0 2,015 2,014

- 1

Y New York 4,664 4,556

- 108 4,450 4,394

- 57

Y North

Carolina 12,513 11,951

- 563 12,275 12,041

- 234

North Dakota 10,808 10,270

- 538 15,063 14,964

- 99

Y Ohio 18,149 18,131

- 18 16,660 16,733 73

Y Oklahoma 17,269 17,279 10 16,215 16,215 0

Y Pennsylvania 14,773 14,905 132 14,387 14,412 25

Rhode Island 202 218 17 190 197 7

South

Carolina 4,542 4,668 125 5,082 5,067

- 14

South Dakota 297 297 0 386 386 0

Y Tennessee 5,441 5,441 0 5,481 5,481 0

Y Texas 54,557 54,583 26 58,002 57,913

- 89

Vermont 3 3 0 61 61 0

Y Virginia 6,656 6,793 136 6,818 6,810

- 8

Y West Virginia 14,475 13,916

- 560 13,390 13,028

- 362

Y Wisconsin 5,221 5,295 74 5,561 5,540

- 21

Total of 23

Proposed

States 294,135 292,450

- 1,686 311,867 311,231

- 636