### Revised draft Federal Register notice and draft TSD for the rule titled " Regional Haze: Revisions to Provisions Governing Alternatives to Source-Specific Best Available Retrofit Technology (BART) Determinations, Limited SIP Disapprovals , and Federal Implementation Plans " RIN 2060-AR05 Phil Lorang to: Kymn, Christine J. 12/14/2011 05:14 PM
Cc: Martha Keating, Rhea Jones

From: Phil Lorang/RTP/USEPA/US

To: "Kymn, Christine J." <Christine

_ J.

_ Kymn@omb.eop.gov>

Cc: Martha Keating/RTP/USEPA/US@EPA, Rhea Jones/RTP/USEPA/US@EPA



### Christine,

Attached are revised draft versions of the FR notice and TSD, addressing comments conveyed in the recent inter agency phone call. We appreciate the assistance given by these reviewers.

These versions are redlined to the one version of each of these you received earlier. I am eager to answer any questions you have.

I will not be in the office or reachable on Friday December 16. If you are calling on that day, please call Rhea Jones at 919-541-2940 or Martha Keating at 919-541-9407.

EO12866_RegionalHazeRevisions_2060-AR05_NPRM_20111019_REDLINE_12_14_11_version3.docx

BtB Modeling 2011 TSD draft final_v2_REDLINE_12-14-11.docx



### Phil Lorang, Senior Policy Advisor Air Quality Policy Division, OAQPS, EPA 919-541-5463***E.O. 12866 Review

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Page 1 of 74 **6560**

**- 50** 

**- P** 

**ENVIRONMENTAL PROTECTION AGENCY**

**40 CFR Part 51**

**[EPA**

**- HQ** 

**- OAR** 

**- 2011** 

**- 0729; FRL** 

**– ]** 

**RIN 2060**

**- AR05** 

**Regional Haze: Revisions to Provisions Governing Alternative**  **s to** 

**Source**

**- Specific Best Available Retrofit Technology (BART)** 
**Determinations**
**, Limited SIP Disapprovals,**  **and Federal Implementation** 

**Plan s** 

**AGENCY:** Environmental Protection Agency (EPA).

**ACTION:** Proposed rule.

**SUMMARY:** The EPA is proposing revisions to our rules that pertain to

the regional haze program. In this action, the EPA is proposing that

the trading program in the recently promulgated Transport Rule, also

known as the Cross

- State Air Pollution Rule, achieves grea ter

reasonable progress towards the national goal of achieving natural

visibility conditions in Class I areas than source

- specific Best

Available Retrofit Technology (BART) in those states covered by the

Transport Rule . In this action, the EPA is also prop osing a limited

disapproval of the regional haze State Implementation Plans (SIPs)

that have been submitted by Alabama, Florida, Georgia, Kentucky,

Indiana, Iowa, Louisiana, Michigan, Mississippi, Missouri, North

Carolina, Ohio, Pennsylvania, South Carolina and Texas. These states

relied on requirements of the Clean Air Interstate Rule (CAIR) to

satisfy certain regional haze requirements

. To address deficiencies

in all of the CAIR

- dependent regional haze SIPs , in this action, the***E.O. 12866 Review

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Page 2 of 74 EPA is proposing Federal Implementation Plans (FIPs) to replace

reliance on the CAIR requirements in these SIPs with reliance on the

Transport Rule as an alternative to BART. S tates are encouraged, at

any time, to submit a revision to their regional haze SIP

incorporating the requirements of the Transport Rule at which time we

will withdraw the FIP we are proposing in this action.

**DATES:** Comments

. Comments must be received on or before **[INSERT DATE**

**30 45**  **DAYS AFTER PUBLICATION IN THE FEDERAL REGISTER]** 

.

Public Hearings

**ADDRESSES:** Submit your comments, identified by Docket ID No. EPA

- HQ

OAR

- 2011

- 0729, by one of the following methods: . If anyone contacts us requesting a public hearing on

or before **[INSERT DATE 1 0**  **DAYS AFTER DATE OF PUBLICATION IN THE**

**FEDERAL REGISTER]** a public hearing will be held in Research Triangle

Park, North Carolina on **[INSERT DATE 15 DAYS AFTER DATE OF** 

**PUBLICATION IN THE FEDERAL REGISTER]**

**.** , we will hold a public hearing.

Please refer to SUPPLEMENTARY INFORMATION for additional information

on the comment period and the public hearing.

**•** www.regulations.gov

**.** Follow the online instructions for

submitting comments. Attention Docket ID No. EPA

- HQ

- OAR

- 2011

-

0729

.

**•** Email: a

- and

- r

- docket@epa.gov

. Attention Docket ID No. EPA

- HQ

OAR

- 2011

- 0729

.

**•** Fax: (202) 566

- 9744. Attention Docket ID No. EPA

- HQ

- OAR

- 2011

-

0729

.***E.O. 12866 Review

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Page 3 of 74 **•** Mail:

**•** EPA Docket Center, EPA West (Air Docket), Attention Docket

ID No. EPA

- H Q

- OAR

- 2011

- 0729 , U.S. Environmenta l Protection

Agency, Mailcode: 2822T, 1200 Pennsylvania Ave nue, NW,

Washington, D

. C

. 20460. Please include a total of two copies.

Hand Delivery: U.S. Environmental Protection Agency, EPA West

(Air Docket), 1301 Constituti on Avenue, Northwest, Room 3334,

Washington, D

. C

. 20004, Attention Docket ID No. EPA

- HQ

- OAR

- 2011

-

0729

. Such deliveries are only accepted during the Docket's

normal hours of operation, and special arrangements should be

made for deliveries of boxed informat ion.

Instructions

. Direct your comments to Docket ID No. EPA

- HQ

- OAR

- 2011

-

0729

. The EPA's policy is that all comments received will be included

in the public docket without change and may be made available online

at www.regulations.gov , including any personal information provided,

unless the comment includes information claimed to be Confidential

Business Information (CBI) or other information whose disclo sure is

restricted by statute. Do not submit information that y ou consider to

be CBI or otherwise protected through www.regulations.gov or email.

The www.regulations.gov website is an “anonymous access” system,

which means the EPA will not know your identity or contact

information unless you provide i t in the body of your comment. If you

send an email comment directly to the EPA without going through

www.regulations.gov , your email address will be automatically

captured and included as part of the comment that is placed in the***E.O. 12866 Review

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Page 4 of 74 public docket and m ade available on the Internet. If you submit an

electronic comment, the EPA recommends that you include your name and

other contact information in t he body of your comment and with any

disk or CD

- ROM you submit. If the EPA cannot read your comment due to

technical difficulties and cannot contact you for clarification, the

EPA may not be able to consider your comment. Electronic files should

avoid the use of special characters, avoid any form of encryption,

and be f ree of any defects or viruses. For additional information

about the EPA 's public docket, visit the EPA Docket Center homepage

at www.epa.g ov/epahome/dockets.htm

**.**

Docket

. All documents in the docket are listed in the

www.regulations.gov index. Although listed in the index, some

information is not publicly available, e.g. , CBI or other information

who se disclo sure is restricted by statute. Certain other material,

such as copyrighted material, will be publicl y available only in hard

copy. Publicly available docket materials are available either

electronically in www.regulations.gov or in hard copy at the Air and

Radiation Docket and Information Center, EPA/DC, EPA West Building,

Room 3334, 1301 Constitution Ave., NW, Washington, D

. C. The Public

Reading Room is open from 8:30 a.m. to 4:30 p.m., Monday through

Fri d ay, excluding legal holidays. The telephone number for the Public

Reading Room is (202) 566

- 1744, and the telephone number for the Air

Docket is (202) 566

- 1742.***E.O. 12866 Review

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Page 5 of 74 **FOR FURTHER INFORMATION CONTACT:** Ms. Martha Keating , Office of Air

Quality Planning and Standards, Air Quality Policy Division, Mail

code C539

- 0 4 , Research Triangle Park, NC 27711, telephone (919) 541

-

9407; fax number: 919

- 541

- 0824; email address:

keating.martha@epa.gov

**SUPPLEMENTARY INFORMATION :**  .

**I. General Information**

This proposed action does not directly regulate emission

sources. It will affect state and local air pollution control

agencies located within the geographic areas covered by the T ransport

Rule A. Does this action apply to me?

1 and whose regional haze state implementation plan relied on

CAIR 2 as an alternative to BART for sulfur dioxide ( SO 2 ) and/or

Nitrogen Oxide ( NO X

These sources are in the following gro ups: ) for electric generating units ( EGU s ) subject to

BART requirements. Some of the EGUs located in such geographic areas

may also be affected by the FIPs that ma y result from final

rulemaking on this proposed action in that the final rule would allow

states the option of not requiring them to meet source

- specific BART

emission limits to which they otherwise could be subject

.

1 See Federal Implementation Plans to Reduce Interstate Transport of
Fine Particulate Matter and Ozone 76 FR 48208 (August 8, 2011)

.

2 See Rule to Reduce Interstate Transport of Fine Particulate Matter and Ozone (Clean Air Interstate Rule); Revisions to Acid Rain Program; Revisions to the NO
x SIP Call; Final Rule, 70 FR 25162 (May 12, 2005)

.***E.O. 12866 Review

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Page 6 of 74 Industry group SIC NAICS a b

Electric Services 492 221111, 221112, 221113, 221119,

221121, 221122

a Standard Industrial Classification.

b North American Industry Classification System.

B. What should I consider as I prepare my comments for the EPA ?

1. Submitting CBI. Do not submit this information to the EPA

through www.regulations.gov or email. Clearly mark the part or all of

the informa tion that you claim to be CBI. For CBI information in a

disk or CD ROM that you mail to the EPA , mark the outside of the disk

or CD ROM as CBI and then identify electronically within the disk or

CD ROM the specific infor mation that is claimed as CBI. In addition

to one complete version of the comment that includes information

claimed as CBI, a copy of the comment tha t does not contain the

information claimed to be CBI must be submitted for i nclusion in the

public docket. Information so marked will not be disclosed except in

accordance with procedures set forth in 40 CFR Part 2.

2. Tips for Preparing Your Comments

**•** Identify the rulemaking by docket number and other identifying

information (subject heading, . Whe n submitting comments,

remember to:

Federal Register date and page

number).***E.O. 12866 Review

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Page 7 of 74 **•** Follow directions

- The agency may ask you to respond to specific

questions or organize comments by referencing a Code of Federal

Regulations (CFR) part or section number.

**•** Explain why you agree or disagree; suggest alternatives and

substitute language for your requested changes.

**•** Describe any assumptions and provide any technical information

and/or data that you used.

**•** If you estimate potential costs or burdens, explain how you arrived

at your estimate in sufficient detail to allow for it to be

reproduced.

**•** Provide specific examples to illustrate your concerns, and suggest

alternatives.

**•** Explain your views as clearly as possible, avoiding the use of

profanity or personal threats.

**•** Make sure to submit your comments by the comment period deadline

identified.

In addition to bei ng available in the docket, an electronic copy

of this notice will be posted at C. Where can I get a copy of this document and other related

information?

http://www.epa.gov/ttn/oarpg/new.html under “Recent Actions **.”**

D. What information should I know about a possible public hearing?***E.O. 12866 Review

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Page 8 of 74 To request that a public hearing be held or t o register to speak

at the hearing on this document, contact Ms. Pamela Long at (919)

541

- 0641 before 5 p.m. on **[INSERT DATE 15**  **10 DAYS AFTER DATE OF** 

**PUBLICATION IN THE FEDERAL REGISTER].** For updates and additional

information on a public hearing, please check the EPA ’s website at

http://www.epa.gov/ttn/oarpg/new.html under “recent actions **.”**

The information presented in this notice is organized as

follows: E. How is this notice organized?

I. General Information A. Does this action apply to me? B. What should I consider as I prepare my comments for the EPA ? 1. Submitting CBI 2. Tips for Preparing Your Comments C. Where can I get a copy of this document and other related
information? D. What information should I know about a public hearing? E. How is this notice organized?

II. What a ction is the EPA proposing to t ake?

III. What is the b ackground for the EPA ’s proposed a ction? A. The Regional Haze Problem B. Clean Air Act Requirements for Addressing Regional Haze

C. A lternative Measures In Lieu of BART
1. Criteria for Comparing Visibility Progress of an Alternative
Program to BART
2. What is the Relationship between BART and CAIR ?
3. Remand of CAIR and Impli cations for State Regional Haze Implementation Plans

4. The T ransport R ule and Regional Haze State Implementation

Plans

IV. Proposed Determination that the Transport Rule is an Approvable
Alternative to BART

A. Application of the Two

- Pronged Test

B. Identification of Affected Class I Areas

C. Scenarios Examined

D. Emission Projections

E. Air Quality Modeling Results

F. Proposed Amendment to the Regional Haze Rule***E.O. 12866 Review

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Page 9 of 74 V. Proposed Limited Disapproval of Certain States’ Regional Haze

SIPs

VI. Proposed FIPs

VII. Statutory and Executive Order

A. Executive Order 12866: Regulatory Planning and Review and Review

Executive Order 13563: Improving Regulation and Regulatory
Review

B. Paperwork Reduction Act

C. Regulatory Flexibility Act

D. Unfunded Mandates Reform Act

E. Executive Order 13132: Federalism

F. Executive Order 13175: Consultation and Coordination with
Indian Tribal Governments
G. Executive Order 13045: Protection of Children from Environmental Health and Safety Risks
H. Executive Order 13211: Actions Concerning Regulations That Significantly Affect Energy Supply, Distribution, or Use

I. National Technology Transfer and Advancement Act

J. Executive Order 12898: Federal Actions to Address Environmental Justice in Minority Populations and

L ow

- Income Populations

**II. What ac**  **tion is the EPA**  **proposing to t ake?** 

In this action

, the EPA is proposing to find that the trading

program s in the Transport Rule 3

3 See Federal Imple mentation Plans to Reduce Interstate Transport of
Fine Particulate Matter and Ozone 76 FR 48208 (August 8, 2011) and Federal Implementation Plans for Iowa, Kansas, Michigan, Missouri, Oklahoma, and Wisconsin To Reduce Interstate Transport of Ozone 76 FR 40662(July 11, 2011) (finalized on December 15, 2011) for more details. For purposes of this proposed rule, the Transport Rule includes all of the states (28) included in the final Transport Rule and the supplemental. achieve greater reasonable progress

towards the national goal of achieving natural visibility conditions

in mandatory Class I federal areas than source

- specific BART in the

states in which the Transport Rule applies . Specifically, we are

proposing that the trading program s set out in the Transport Rule

Formatted: Indent: Left: 0", First line: 0"***E.O. 12866 Review

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Page 10 of 74 meet the requi rements of an alternative program as prescribed in the

regional haze rule (RHR) at 40 CFR 51.308(e)(3)and are proposing to

revise the regional haze regulations at 40 CFR 51.308(e)(4)

accordingly to allow states to substitute participation in the

trading pr ogram s under the Transport Rule for source

- specific BART.

In addition, we are also proposing to find that any approved SIPs

revising or adopting the Transport Rule trading program s , which must

control emissions at least as stringe ntly as the Transport Rule FIPs

,

will also meet the requirements for an alternative to BART for EGUs

for the pollutants which the Transport Rule limits in that state.

In this action we are also proposing a limited disapproval of

the regional haze SIPs that have been submitted by Alabama, Florida,

Georgia, Kentucky, Indiana, Iowa, Louisiana, Michigan, Mississippi,

Missouri, North Carolina, Ohio, Pennsylvania, South Carolina and

Texas. These states, fully consistent with the EPA ’s regulations at

the time, relied on CAIR requirements to satisfy the BART requirement

and the requirement for a long

- term strategy sufficient to achieve

the state

- adopted reasonable progress goals. 4

4 The states for which we are proposing limited disapproval in this
action are those that both relied on CAIR to satisfy BART requirements and are now covered by the requirements of the Transport
Rule , for which we have not already made such a proposal. CAIR and the CAIR FIP

requirements, however, will only remain in force to address emissions

through the 2011 c ontrol period and thus CAIR cannot be relied upon

in a SIP as a substitute for BART or as part of a long

- term control***E.O. 12866 Review

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Page 11 of 74 strategy. The EPA has already proposed limited disapproval of certain

other state regional haze SIPs that relied on CAIR

. 5

In this action we are also proposing FIPs for all the states for

which we have previously proposed limited disapproval and for all the

states for which we are proposing a limited disapproval of their

regional haze SIP in this action due to the change in status of CAIR.

Regional haze SIPs wer e due in December 2007. For a number of the

states identified above, we made a finding on January 15, 2009, that

the states had failed to timely submit a regional haze SIP. Most of

these states have subsequently submitted SIPs

, but we have not yet

acted on them. Under the CAA, the EPA is required to promulgate a FIP

within 2 years after finding that a state has failed to make a

required submission or after disapproving a SIP in whole or in part,

unless the state first adopts and we have fully approved a SIP. CAA §

110(c)(1 ). Given the se CAA requirements and the fact that the

Transport Rule has now replaced CAIR

, we consider it appropriate at

this time to issue FIPs to address the deficiencies in the regional

haze SIPs related to the termination of CAIR

. O ur adoption of these

FIPs at this time avoids the near

- term need for additional

administrative steps on the part of these states

. The proposed

regional haze FIPs also allow states the option of a less costly We plan to take

final action on both groups of SIPs when this action is finalized.

5 The states for which the EPA has previo usly proposed limited disapproval of regional haze SIPs are Kentucky, Tennessee, Virginia and West Virginia.***E.O. 12866 Review

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Page 12 of 74 approach to meeting the regional haze requirements of the CAA since

the proposed FIPs rely on the trading program already promulgated in

the Transport Rule

. We encourage s tates

, at a ny time , to submit a

revision to their regional haze SIP incorporating the requirements of

the Transport Rule at which time we will withdraw the FIP we are

proposing in this action . However, we anticipate that some states may

choose to remain subject to th e proposed FIP and not submit a SIP

revision. Our proposed finding that the Transport Rule makes greater

reasonable progress than BART for EGUs in these states will hold true

regardless of whether a state chooses to subm it a SIP revision under

subpart 52.3 8 and 52.39 or remai n subject to a FIP

.

The proposed FIP s also address the requirements for the affected

states’ long

- term strateg ies for R egional Haze

. The affected states

originally set the reasonable progress goals in their SIPs based on

the emission re ductions expected to be achieved by CAIR, along with

other emission reductions qualified for that purpose. Because overall

EGU emission reductions from the Transport Rule are larger than the

EGU reductions achieved by CAIR, we believe that the reasonable

p rogress goals in the SIPs for t he states addressed in this proposed

action do not need to be revised by the states at this time or

replaced by goals established by us via FIPs. The substitution of the

Transport Rule for CAIR does not w eaken any affected state’s long

term strategy. We intend to act on the rea sonable progress goals and

long

- ter m strategies (including the proposed FIP s ) and other***E.O. 12866 Review

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Page 13 of 74 requirements of the RHR (monitoring, consultation with federal land

managers, etc.) for each state in an individu al notice at or after

the time of the final rule for this action.

**II I** 

**. What is the b**  **ackground for**  **the EPA ’s proposed a**  **ction?**

Regional haze is visibility impairment that is produced by a

multitude of sources and activities which are located across a broad

geographic area and emit fine particles (PM A. The Regional Haze Problem

2.5 ) ( e.g. , sulfates,

nitrates, organic carbon, elemental carbon, and soil dust), and their

precursors ( e.g. , SO 2 , NO X , and in some cases, ammonia (NH 3 ) and

volatile organic compou nds (VOC)). Fine particle precursors react in

the atmosphere to form fine particulate matter

, which impairs

visibility by s cattering and absorbing light. Visibility impairment

reduces the clarity and alters the color of scenes , and reduces the

distance at which one can see a scene. PM 2.5

Data from the existing visibility monitoring network, the

“Interagency Mon itoring of Protected Visual Environments” (IMPROVE)

monitoring network, show that visibility impairment caused by air

pollution occurs virtually all the time at most national park and

wilderness areas

. The average visual range can also cause serious

health effects and mortality in humans and contributes to

environmental effects such as acid deposition and eutrophication.

6

6 Visual range is the greatest distance at which a dark object can be viewed against the sky. in many mandatory Class I***E.O. 12866 Review

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Page 14 of 74 fe deral areas 7 in the western United States is about 60

– 100 miles

, or

about one

- half to two

- thirds of the visual range that would exist

without anthropogenic air pollution. In most of the eastern Class I

areas of the United States, the average visual range is less than 20

miles , or about one

- fifth of the visual range that would exist under

estimated natural conditions. 64 FR 35715 (July 1, 1999).

In section 169A of the 1977 Amendments to the CAA, Congress

created a program for protecting visibility in the nation’s natio nal

parks and wilderness areas. This section of the CAA establishes as a

national goal the “prevention of any future, and the remedying of any

existing, impairment of visibility in m andatory Class I f ederal areas

which impairment results from manmade air pollution.” On December 2,

1980, the EPA promulgated regulations to address visibility

impairment in Class I areas that is “reasonably attributable” to a B. Clean Air Act Requirements for Addressing Regional Haze

7 Areas designated as mandatory Class I federal areas consist of national parks exceeding 6000 acres, wilderness areas and national memorial parks exceeding 5000 acres, and all international parks that
were in existen ce on August 7, 1977. 42 U.S.C. 7472(a). In accordance with section 169A of the CAA, EPA, in consultation with the Department of Interior, promulgated a list of 156 areas where visibility is identified as an important value. 44 FR 69122 (November 30, 1979). The extent of a mandatory Class I area includes subsequent changes in boundaries, such as park expansions. 42 U.S.C. 7472(a). Although states and tribes may designate as Class I additional areas which they consider to have visibility as an important value, the requirements of the visibility program set forth in section 169A of the CAA apply onl y to “ mandatory Class I Federal areas.” Each mandatory Class I Federal ar ea is the responsibility of a “Federal Land Manager.” 42 U.S.C. 7602(i). When we use the term “Class I area” in this action, we mean a “mandatory Class I Federal area.”***E.O. 12866 Review

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Page 15 of 74 single source or small group of sources, i.e.

Congress added section 169B to the CAA in 1990 to address

regional haze issues

. The EPA promulgated the RHR to address regional

ha ze on July 1, 1999 (64 FR 35713 ). T he RHR revised the existing

visibility regulations to integrate into the regulation provisions

addressing regional haze impairment and established a comprehensive

visibility protection program for Class I areas. The requi rements for

regional haze, found at 40 CFR 51.308 and 51.309, are included in the

EPA ’s visibility protection reg ulations at 40 CFR 51.300

- 309. The

requirement to submit a regional haze SIP applies to all 50 states,

the District of Columbia and the Virgin Islands. 40 CFR 51.308(b)

requires states to submit the first implementation plan addressing

regional haze visibility impairment no later than December 17, 2007. , “reasonably

attributable visibility impairment”. 45 FR 80084. These regulations

represented the first phase in addressing visibility impairment. The

EPA deferred action on regional haze that emanates from a variety of

sources until monito ring, modeling and scientific knowledge about the

relationships between pollutants and visibility impairment were

improved.

Section 169A of the CAA and the EPA ’s implementing regulations

require states to establish long

- term strategies for making

reasonable prog ress towards the national goal of achieving natural

visibility conditions in Class I areas. Implementation plans must

also give specific attention to certain stationary sources

.***E.O. 12866 Review

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Page 16 of 74 Specifically, section 169A(b)(2 )(A) of the CAA requires states to

revise their SIPs to contain such measures as may be necessary to

make reasonable progress towards the natural visibility goal,

including a requirement that certain categories of existing major

stationary sources 8 built b etween 1962 and 1977 procure, install, and

operate the “Best Available Retrofit Technology” as determined by the

state. Under the RHR, states are directed to conduct BART

determinations for such “BART

- eligible” sources that may be

anticipated to cause or c ontribute to any visibility impairment in a

Class I area

. Rather than requiring source

- specific BART controls,

states also have the flexibility to adopt an emissions trading

program or other alternative program as long as the alternative

provides greater r easonable progress towards improving visibility

than BART , as described below.

1. C. Alternative Measures In Lieu of BART

Criteria for determining if an alternative measure achieves

greater reasonable progress than source

- specific BART are set out in

the RHR at § 51.308(e)(3). The “better

- than

- BART” test may be

satisfied as follows: If the distribution of emissions is not

sub stantially different than under BART, and the alternative measure Criteria for Comp aring Visibility Progress of an

Alternative Program to BART

8 The set of “ major stationary sources” potentially subject to BART is listed in CAA section 169A(g)(7).***E.O. 12866 Review

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Page 17 of 74 results in greater emission reductions, then the alternative measure

may be deemed to achieve greater reasonable progress. If the

distribution of emissions is significantly different, then s tates are

directed to conduct an air quality modeling study to determine

differences in visibility between BART and the alternative program

for each impacted Class I area for the worst and best 20 percent of

days. 9

- Visibility does not decline in any Class I area The two

- pronged visibility test would dem onstrate “greater

reasonable progress” under the alternative program if both of the

following criteria are met:

10

- There is an overall improvement in visibility, determined by

comparing the average differe nces between BART and the

alternative over all affected Class I areas. , and

The EPA’s authority to establish non

- BART alternatives and the

specific methodology outlined above have has been judicially

challenged and upheld twice, firmly establishing that the CAA allows

states to substitute other programs for BART where the alternative

achieves greater progress. In the first case, the court affirmed our

interpretation of CAA 169A(b)(2) a s allowing for alternatives to BART

9 While the RHR directs the state to conduct the air quality modeling study, as described in section III.C.2

, EPA itself conducted such a study for CAIR and through a notice

- and

- comment rulemaking codified
the conclusion that the stated criteria were met by adding specific provisions allowing the use of CAIR in lieu of source

- specific BART.

10 As explained in section VI.1, the “decline” is relative to modeled

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Page 18 of 74 where those alternatives will result in greater reasonable progress

than BART

. Center for Energy and Economic Development v. EPA , 398

f.3d 653, 660 (D

. C

. Cir. 2005) (“CEED”) (finding reasonable the EPA ’s

interpretation o f CAA section 169(a)(2) as requiring BART only as

necessary to make reasonable progress ). In the second case, Utility

Air Regulatory Group v. EPA

2. , 471 F.3d 1333 (D

. C

. Cir. 2006), the

court found EPA’s two

- pronged visibility test to be a “reasonable

notion of reasonable progress” and specifically upheld our

determination that states could rely on CAIR, as discussed below, as

an alternative program to BART for EGUs in the CAIR

- affected states.

In May 2005, the EPA published CAIR, which required 28 states

and the District of Columbia to reduce emissions of SO What is the r elationship between BART and CAIR?

2 and NO X that

significantly contribute to , or interfere with maintenance of, the

1997 national ambient air quality standards (NAAQS) for fine

part iculates and/or ozone in any downwind state. The CAIR established

emission budgets for SO 2 and NO X for states that contribute

significantly to nonattainment in downwind states and required the

significantly contributing states to submit SIP revisions that

implement ed these budgets. Because such SIP revisions were already

overdue, CAIR also promulgated FIPs for the affected states

establishing a cap and trade program for EGUs with opt

- in provisions

for other sources. States ha d the flexibility to subsequentl y adopt

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Page 19 of 74 emission reductions sufficient to address interference with

attainment or maintenance of the NAAQS in other states. Many affected

states adopted CAIR

- mirroring SIPs, while others chos e to remain

under CAIR FIPs.

As noted in Section III.C.1 , the RHR allows states to implement

an alternative program in lieu of BART so long as the alternative

program has been demonstrated to achieve greater reasonable progress

toward the national vi sibi lity goal than would BART. The EPA made

just such a demonstration for CAIR in revisions to the regional haze

program made in 2005. 70 FR 39104 (July 6, 2005) . In those revisions,

we amended our regulations to provide that states participating in

the CAIR c ap

- and trade program under 40 CFR part 96 pursuant to an

EPA

- approved CAIR SIP or states that remain subject to the CA IR FIP

in 40 CFR part 97 need not require affected BART

- eligible EGUs to

install, operate, and maintain BART for emissions of SO 2 and NO X

As a result of our determination that CAIR was “better

- than

BART” a number of states in the CAIR region, fully consistent with

our regulations, designed their regional haze implementation plans to

rely on the CAIR cap

- and

- trade progr am as an alternative to BART for

EGU emissions of SO . 40

CFR 51.308(e) (4).

2 and NO X . These states also relied on CAIR as an

element of a long

- term strategy for achieving their reasonable

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Page 20 of 74 3.

Following our determination in 2005 that CAIR was “better

- than

BART” and the upholding of this determination by the court in 2006

,

the D

. C

. Circuit Court ruled on several petitions for r eview

challenging CAIR on various grounds. As a result of this litigation

the D

. C

. Circuit Court remanded CAIR to the EPA , but later decided

not to vacate the rule. Remand of CAIR and Implications for State Regional Haze

Implementation Pla ns

11 The court thereby left CAIR and CAIR SIPs

and FIPs in place in order to “temporarily preserve the environmental

values cov ered by CAIR” until the EPA rep laced it with a rule

consistent with the court's opinion. 550 F.3d at 1178. The EPA

replaced CAIR with the Transport Rule on August 8, 2011. 12

Many states relied on CAIR as an alternative to BART for SO The

Transport Rule will take effect on January 1, 2012 . The CAIR and the

CAIR F IPs will remain in place to address emissions through the end

of the 2011 control periods

.

2 and

NO X

11 See North Carolina v. EPA , 531 F.3d 896; modified by 550 F.3d 1176 (D.C. Cir. 2008). for subject EGUs, as allowed under the BART prov isions at 40 CFR

51.308(e)(4). These state s also relied on the improvement in

visibility expected to result from controls planned or already

installed on sources in order t o meet CAIR provisions in developing

12 See Federal Implementation Plans to Reduce Interstate Transport of
Fine Particulat e Matter and Ozone 76 FR 48208 ( August 8, 2011 )

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Page 21 of 74 their long

- term visibility strategy. In addition, many state s relied

upon their own CAIR S IPs or the CAIR FIPs for their state s as legal

justification for these planned controls and consequently did not

include separate enforceable measures in the ir long

- term strategies

(a required element of a regional haze SIP submission ) to ensure

these EGU reductions. Thes e s tates also submitted demonstrations

showing that no additional controls on EGUs beyond CAIR would be

reasonable for the first 10

- year implementation period of the

regional haze program.

Since states in the CAIR

- affected region have based a number of

required elements of their regional haze programs on CAIR, which has

now been replaced by the Transport Rule , we cannot fully approve

regional haze SIP revisions that have rel ied on CAIR for e mission

reduction measures . To date, we have proposed limited disapprovals

for some states whose regional haze SIP revisions rely on CAIR (for

example for the S tate of Tennessee, 76 FR 33662 ( June 9, 2011 ) ). We

intend to t ake final action on those proposed limited disapprovals of

SIPs when this action is finalized. However, there are other state s

whose regional haze SIP relied on CAIR but for which the EPA has not

yet proposed to take action. In this action we are proposing a

limited disapprov al of the regional haze SIPs that have been

submitted by Alabama, Florida, Georgia, Kentucky, Indiana, Iowa,

Lo uisiana, Michigan, Mississippi, Missouri, North Carolina, Ohio,

Pennsylvania, South Carolina and Texas. These states relied on CAIR***E.O. 12866 Review

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Page 22 of 74 requirements to satisfy both the BART requirement and the requirement

for a long

- term strategy sufficient to achieve the state

- adopted

reasonable progress goals, and they are now covered by the Transport

Rule requirements.

4.

The Transport Rule sunsets CAIR and the CAIR FIPs for control

periods in 2012 and beyond

. The Transport Rule requires 2 8 states in

the eastern half of the United States to significantly improve air

quality by reducing EGU SO The Transport Rule and Reg ional Haze State Implementation

Plans

2 and NO X emissions that cross state lines

and contribute to ground

- level ozone and /or fine particle pollution

in other states. The rule allows air

- quality

- assured allowance

trading among covered sources, utilizing an allowance market

infrastructure modeled after existing allowance trading programs. The

Transport Rule allows sources to trade emissions allowances with

other sources within the same program ( e.g. , ozone season NO X

In developing the Transport Rule

, we did not conduct any

technical analysis to determine whether complianc e with the Transport

Rule would satisfy r egional h aze BART

- related requirements.

Accordingly, in the final Transport Rule

, the EPA did not make a

determination or establish any presumption that compliance with the ) in the

same or different states, while firmly constraining any emissions

shifting that may occur by establishing an emission ceiling for each

state

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Page 23 of 74 Transport Rule would satisfy BART

- related requirements for EGUs. We

have now completed such a technical analysis and it is the basis of

this action in which we are proposing to find that in affected

mandatory Class I f ederal areas

, the Transport Rule achieves greater

reasonable progress t owards the national goal of achieving natural

visibility conditions than source

- specific BART . Specifically, we are

proposing that participation by EGUs in the Transport Rule trading

program set out in 40 CFR part 97 subparts AAAAA

- DDDDD meets the

requirem ents of an alternative program as prescribed in the regional

haze rule (RHR) at § 51.308(e)(3)

, and we are proposing to revise the

regional haze regula tions at 40 CFR 51.308(e)(4) accordingly. The

proposed determination in this action that participation in the

Transport Rule trading program may substitute for BART applies only

to EGUs in the states in the Transport Rule region and only to the

pollutants subject to the requirements of the Transport Rule ( i.e.

,

SO 2 and/or NO X )

. BART for E e missions of other visibility impairing

pollutants ( e.g. , primary PM 2.5 , NH 3

Under the proposed revision to this section, a state in the

Transport Rule region whose EGUs are subject to the requirements of

the Transport Rule trading program only for annual NO or VOC) must still be evaluated

according to the RHR Guidelines. Non

- EGU sources also remain subject

to requirements of the RHR.

X or ozone season

NO X would be allowed to rely on our proposed determination that the

Transport Rule makes greater reasonable progress than source

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Page 24 of 74 BART for NO X . Such a state would still need to address BART for SO 2

In this action we are also proposing a FIP for those Transport

Rule state s for which we already have or now are proposing a limited

disapproval due to the termination of CAIR. For these states, the

proposed FIP would replace reliance on the CAIR requirements with

reliance on the Transport Rule as an alternative to BART for SO and other visibility impairing pollutants

.

2 and

NO X

We are proposing to leave unchanged the final sentence of

section 51.308(e)(4) in the regional haze regulations . This language

allows a state to address BART, when it is required based on

reasonable attribution of visibility impairment at a Class I area to

a particular source, by including a geographic enhancement in its

SIP. For example, a geographic enhancement in the form of adjusted

allocations at a BART

- sub ject source might take the place of sour ce

specific emission rate limits. Use of a geographic enhancement in the

context of reasonable attribution of visibility impairment at a Class

I area will be addressed in separate EPA or state actions on a case

by

- case basis in accordance with 40 CFR 51.30 6. emissio ns from EGUs and as a long

- term strategy measure.

We are proposing to leave unchanged the language in the regional

haze regulations at 40 CFR 51.308(e)(4) that allows states to retain

the discretion to include geographic enhancements in their SIP to***E.O. 12866 Review

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Page 25 of 74 accommodate the situation where BART is required base d on reasonable

attribution of visibility impairment at a Class I area. 13

**IV. Proposed D**  **etermination that the Transport Rule**  **is an Approvable** 

**Alternative to BART**

As described in section C.1., t he two

- pronged test for

determining if an alternative program achieves greater reasonable

progress than source

- specific BART is set out in the RHR at 40 CFR

51.308(e)(3 ). The underlying purpose of both prongs of the test is to

assess whether visibility conditions at Class I areas would be better

with the alternative program in place than they would without it. The

first prong ensures that the alternative program will not cause a

decline in visibility at any affected Class I area. It addresses the

possibility that the alternat ive program might cause local changes in

emissions that could result in localized visibility degradation. The

second prong ensures that the program results in improvements in

average visibility across all affected Class I area s as compared to

adopting source

- specific BART. Together, these tests ensure that the

alternative program provides for greater reasonable progress than

would source

- specific BART. A. Application of the Two

- Pronged Test

13 A geographic enhancement is a method, procedure, or process to allow a broad regional strategy, such as the Transport Rule cap and trade program, to accommodate BART for reasonable attributable impairment. For example, it could consist of a methodology for adjusting allowance allocations at a source which is required to
install BART controls.***E.O. 12866 Review

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Page 26 of 74 In the case of the Transport Rule as an alternative to source

specific BART, the logical reference po int for the first prong is

visibility conditions as they are expected to be at the time the

Transport Rule is implemented but in th e absence of BART. This

e nsures that the predicted visibility differences are due to the

Transport Rule alternative a nd not t o other extrinsic factors. For

example, if large increases in wild fires are expected, due to

accumulation of fuel from past forest management practices, a

degradation of visibility from curr ent conditions may be expected. It

would be irrational to disappro ve an alternative program as not

meeting the first prong of the test because of a modeled degradation

from current conditions, where that degradation is actually

anticipated because of smoke from wildfires

— sources which are not

subj ect to the CAA BART pr ovisions. By comparing the Transport Rule

alternative to future projected baseline conditions without any BART

program , such extrinsic variables are accounted for. The future

projected baseline also accounts for other non

- Transport Rule

constraints on EGU emissions including the Acid Rain Program, the NOx

SIP Call, New Source Performance Standards, Title V permits, any

state laws and consent order requiring emission reductions, and any

other permanent and enforceable binding reduction commitments

. We are

thus able to a scertain (to the extent possible where future

projections are concerned) whether visibility under the alternative

would decline at any affected Class I area, all other things being***E.O. 12866 Review

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Page 27 of 74 equal. Therefore, in applying the first prong of the t est to the

Transport Rule , we used a future (201 4 ) projected baseline

. 14

To satisfy each prong of the test we examined visibility

differences on both the worst and best 20 percent of days. Thus,

under the first prong, visibility must not decline at any affected

Class I area on either the best 20 percent or the worst 20 percent

days as a result of implementing the Transport Rule ; and, under the

second prong the 20 percent best and 20 percent worst days should be

considered in determining whether the Transport Rule produc es greate r

average improvement than source

- specific BART over all affected Class

I areas. Similarly, in applying the second prong of the test, we assumed

identical future conditions (the same as in the future 2014 baseline

case) for non

- EGU sources for both the source

- speci fic BART scenario

and the Transport Rule scenario.

B. Identification of Affected Class I Areas

In applying the two

- pronged test to the Transport Rule , we first

identified the Class I areas in the 48 contiguous states with

suf ficiently complete monitoring data available to support the

analysis. 15

14 The 2014 baseline modeling for this analysis is identic al to the Transport Rule 2014 baseline. The 2014 baseline does not include the Transport Rule, BART, or CAIR control programs

. There were 140 such Class I areas represented by 96

15 The modeling used a 2005 base case projected to a 2014 future year. The modeling days for the analysi s were based on the observed 20
percent best and 20 percent worst days f rom 2005 at each IMPROVE***E.O. 12866 Review

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Page 28 of 74 IMPROVE monitors ; nine Class I areas were excluded that did not have

sufficient historical ambient data from the IMPROVE monitoring

program to support the technical analysis. 16 After identifying these

areas we then considered two possible approaches we could use to

identify which of these areas are “affected” Class I areas in terms

of the potential effect of the Transport Rule as an alt ernative

control program to source

- specific BART. In the first approach, we

identified as affected Class I areas 60 mandatory Class I federal

areas represented by 46 IMPRO VE monitors located in 37 complete

states and four partial states that are contained in the eastern

portion of the Transport Rule modeling domain

. 17

In the Transport Rule , the determinati on of states that

contribute significantly to downwind nonattainment and/or maintenance The second approach

we considered was a national approach in which visibility impacts on

140 Class I areas across the 48 contiguous states were evaluated.

site. Therefore, the analysis could no t be completed for IMPROVE sites that did not have complete ambient data for 2005.

16 In the Reg ional Haze Program, there are 11 0 ambient monitoring sites which represent 155 Class I areas. Therefore, some monitors represent air quality at more than one Class I area. See Guidance for Tracking Progress under the Regional Haze Rule, U.S. EPA, EPA

- 454/B

03

- 004, September 2003, which i s found at: http://www.epa.gov/ttncaaa1/t1/memoranda/rh_tpurhr_gd.pdf . In our analysis we calculated visibility changes at each individual Class I area. Therefore, some IMPROVE monitor s are counted more than once in the averaging of the visibility data. This does not affect the proposed finding that the Transport Rule is better than source

specific BART.

17 The “eastern” Transport Rule modeling grid used a horizontal
resolution of 12 km.***E.O. 12866 Review

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Page 29 of 74 focused on the 37 states that are fully contained in this eastern

modeling domain. The eastern modeling domain a lso includes large

parts of Montana, Wyoming, Colorado, and New Mexico. In the Transport

Rule , EPA did not determine that Montana, Wyoming, Colorado, New

Mexico or the six New England states were contributing to violations

of the 1997 ozone NAAQS or the 1997 a nd 2006 PM 2.5 NAAQS, or

interfering with maintenance in downwind states and therefore they

are not included in the Transport Rule program. 18

The eastern Transport Rule modeling domain lies within a larger

modeling domain which covers the lower 48 states and adjacent However, we included

Class I areas located in these non

- Transport Rule states and partial

states in the first approa ch for identifying “affected areas”. It is

conceivable that because of proximity

, emissions from the Transport

Rule states could impact any of the Class I areas in the eastern

Transport Rule modeling domain. Specifically, in this first approach

for identif ying “affected areas” in the Transport Rule region we

examined impacts on 27 Class I areas located within the Transport

Rule states and 33 additional Class I areas located in non

- Transport

Rule states but within the eastern Transport Rule modeling domain

,

for a total of 60 Class I areas

.

18 The Transport Rule determined that the six New England states did
not contribute to nonattainment or interfere with maintenance in
downwind states . The Transport Rule did not make a determination whether Montana, Wyoming, Colorado, and New Mexico cont ribute to
nonattainment or interfere with maintenance in neighboring states

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Page 30 of 74 portions of Canada and Mexico. In the Transport Rule

, the results

obtained with this national domain were used to calculate boundary

conditions for the eastern Transport Rule region. The EPA did not use

the national domain to investigate interstate contributions to

nonattainment or interference with maintena nce, in part because the

air quality model structure for the national domain is less suitable

for that type of use. 19 In the second approach to identifying which

areas are “affected” Class I areas we used data from the larger

domain to estimate potential vi sibility impacts on Class I areas

located to the west of the Transport Rule modeling region boundary.

The additional 80 Class I areas under this national a pproach are in

states or part of states that were not part of the eastern modeling

domain for the Tra nsport Rule , but were part of the western modeling

domain. 20

19 The eastern modeling domain used a 12 km grid size, while the
national modeling domain used a 36 km grid size. See Air Quality Modeling Final Rule Technical Support Document, U.S. EPA, June 2011,
which is found at: http://www.epa.gov/airtransport/pdfs/AQModeling.pdf

. In this approach, the eastern domain 12 km modeling results

were used to calculate visib ility changes in the 60 eastern C lass I

areas and the national domain 36 km modeling results were used to

calculate visibility changes i n the 80 western Class I areas.

Consideration of this national region would encompass the possibility

20 See Air Quality Modeling Final Rule Technical Support Document, U.S. EPA, June 2011, which is found at: http://www.epa.gov/airtransport/pdfs/AQModeling.pdf

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Page 31 of 74 that the Transport Rule might have the effect of increasing EGU

emissions in the most western portion of the U nited States d ue to

shifts in electricity generation or other market effects. In total,

the national domain includes 140 Class I areas (including the 60

contained within the Transport Rule region ).

We request comment on whether the “affected Class I areas”

should be co nsidered to be the 60 Class I areas located in the

Transport Rule eastern modeling domain, the larger set of 140 Class I

areas in the larger national domain, or some other set. We note that

given the modeling results presented in section VI.5, the choice

b etween the 60 Class I areas or the 140 Class I areas does not affect

our proposed conclusion that both prongs of the two

- prong test are

met.

The Transport Rule requires 2 8 states in the eastern half of the

United States to reduc e EGU SO C. Scenarios Examined

2 and NO X emissions that cross state

lines and contribute to ground

- level ozone and fine particle

pollution in other states. BART, on the other hand, is app licable

nationwide and covers 26 industrial categories, including EGUs, of a

certain vintage. In our comparison, we sought to determine whether

the Transport Rule cap

- and

- trade program for EGUs will achieve

greater reasonable progress than would BART for EGUs only. Therefore,

we examined two relevant control scenarios. The first control

scenario exami ned SO 2 and NO X emissions from all EGUs nationwide after***E.O. 12866 Review

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Page 32 of 74 the application of BART controls to all BART

- eligible EGUs

( “N ationwide BART ” ) . In the second scenario

, EGU S O 2 and NO X

For the first prong of the test, t he “ Transport Rule + BART

elsewhere” scenario was compared to a 2014 future year b ase c ase

representing future emissions in the absence of either program (and

in the absence of CAIR) . The comparison to the 2014 future year “Base

C ase ” allows the EPA to ensure that the Transport Rule would not

cause degradation in visibility from conditions predicted for the

year 2014 in the absence of the Transport Rule , BART and CAIR

. emissions

reductions attributable to the Transport Rule were applied in the

Transport Rule region and BART controls were applied to all BART

eligible EGUS outside the Transport Rule region ( “ Transport Rule +

BART

- elsewhere”). The latter scenario reflects the fact that source

specific BART would remain a regional haze SIP element o utside the

Transport Rule region . I n order to more accurately project the

Transport Rule emissions, it is necessary to assume EGU BART controls

outside the Transport Rule region to account for potential load and

emission shifting among EGUs.

For both the “Nationwide BART” scenario and the “ Transport Rule

+ BART

- elsewhere” scenario, we modeled the presumptive EGU BART

limits for SO 2 and NO X emission rates as specified in the BART

Guidelines (Guidelines for BART Determinations Under the Regional

Haze Rule, 70 FR 39104, July 6, 2005), unless an actual emissi on rate

at a given unit with existing controls is lower. In the latter case,***E.O. 12866 Review

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Page 33 of 74 we modeled the lower emission rates. In addition, we modeled the

impacts of BART using stringent assumptions regarding the EGUs (or

specific units at EGUs) that would be subject t o BART. Specifically,

we assumed that all BART

- eligible EGUs were actually subject to BART

requirements. We also assumed that presumptive BART limits would be

applied to much smaller units. In this analysis we assumed the

threshold for BART

- eligibility was 100 MW for SO 2 and 25 MW for NO X

and did not eliminate any sources based on their annual total

emissions. (By comparison, the RHR BART Guidelines only apply

presumptive limits to EGUs having a total generating capacity of 750

MW and exempt BART

- eligible u nits with the potential to emit less

than 40 tons per year of either SO 2 or NO X

The RHR BART Guidelines specify presumptive SO .)

2 BART limits for

an EGU with an existing scrubber as 95 percent scrubber control

efficiency or 0.15 lbs/MMBtu. We used the Nat ional Electric Energy

Data System (NEEDS), an EPA database of existing and planned

committed EGUs, to identify which BART

- eligible units have existing

scrubbers. 21 The NEEDS also contains information on scrubber

efficiency and emission rates. For scrubbed BART

- eligible units we

based our BART emission rate on a comparison of the emission rate

listed for that unit in NEEDS to the presumptive SO 2

21 See The NEEDS User Guide: http://www.epa.gov/airmarkets/progsregs/epa

ipm/CSAPR/docs/Guide_to_NEEDSv410.pdf which is found at http://www.epa.gov/airmarkets/progsregs/epa

- ipm/transport.html

. emission rate.***E.O. 12866 Review

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Page 34 of 74 That i s, if the unit has at least a 95 percent efficient scrubber,

the emission rate being achieved at that control efficiency was

modeled for that unit even if the emission rate was higher than 0.15

lbs/MMBtu. Conversely, if an emission rate of 0.15 lbs/MMBtu o r lower

is being achieved

, we modeled that emission rate for the unit, even

if the scrubber is less than 95 percent efficient. For BART

- eligible

units without existing scrubbers, we modeled an emission rate that

reflected 95 percent control based on a new installation of a highly

efficient scrubber.

The RHR BART Guidelines specify presumptive limits for NO X based

on coal type and boiler configuration. The BART guidelines also

specify that existing NO X controls must be operated year round. For

t he source

- sp ecific “ Nationwide BART ” scenario and for the

“elsewhere” EGUs in the “ Transport Rule + BART

- elsewhere ” scenario,

we assumed that any BART

- subject unit with existing NO X controls in

the future baseline case would retain at least those controls and

would be required to operate them year round. If the existing NO X

controls in the future baseline case did not meet the presumptive

BART limits (with the modifications about applicability as described

above)

, we assumed installation of post

- combustion controls tha t

would meet the BART guidelines with year

- round operation. In the

“ Transport Rule + BART

- elsewhere” scenario, there are 5 states that

are subject to the Transport Rule requirements during the ozone***E.O. 12866 Review

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Page 35 of 74 season only. 22 For these states, NO X controls were assumed to operate

only during ozone season as required by the Transport Rule . The RHR

BART Guidelines also specify presumptive limits for NO X based on coal

type and boiler configuration. Table 1 summarizes the NO X emission

limits we applied to BART

- eligible unit s of 25 MW or greater. For

units firing a coal blend, which the BART Guidelines do not address,

we calculated a weighted presumptive NO X

**Table 1. BART Presumptive NO** limit based on the percentage

of each coal type fired.

**X Limits by Boiler Configuration and Coal**  **Type (lbs/MMBtu)**

**Bituminous Subbituminous**  **Lignite** Dry bottom wall

- fired 0.39 0.23 0.29 Tangential

- fired 0.28 0.15 0.17

Cell burners 0.40 0.45 Not applicable Dry turbo

- fired 0.32 0.23 Not applicable

Wet bottom tangential

- fired 0.62 Not applicable Not applicable Cyclone 0.10 0.10 0.10

Certain EGUs in the analysis were constrained by emission limits

other than presumptive limits due to a proposed or final regional

haze SIP, a proposed or final regional haze FIP, a final consent

decree, or state rules. These units and their emission limits are

detailed in the Technical Support Document ( TSD ) for this proposed

rule. ( See Technical Support Document for Demonstration of the

Transport Rule as a BART Alternative, Docket EPA

- HQ

- OAR

- 2011

- 0729 .)

22 States subject to the Transport Rule requirements during the ozone season only are Oklahoma, Arkansas, Louisiana, Mississippi and
Florida. D. Emission Projections***E.O. 12866 Review

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Page 36 of 74 To estimate emissions expected from the scenarios described in

section IV.3 , we used the Integrated Planning Model (IPM). The IPM is

a multi

- regional, dynamic, deterministic linear programming mode l of

the electric power sector. It is used extensively by the EPA t o

support regulatory activities. The IPM provides forecasts of least

cost capacity expansion, electricity dispatch, and emission control

strategies for meeting electricity demand subject to envi ronmental,

transmission, dispatch, and reliability constraints. The IPM was used

in this case to ev aluate the emissions impacts of the described

scenarios limiting the emissions of SO 2 and NO X from EGUs. This

analysis used the most recently updated IPM pla tform which is

documented at http://www.epa.gov/crossstaterule/

. 23 Table 2 presents

the annual emissions for each policy scenario as projected by the

IPM. As shown by the numbers in the far right column, “ Transport Rule

+ BART

- elsewhere” achieved greater emission reductions nationwide 24

**Table 2. EGU SO** for both pollutants than source

- specific “Nationwide BART” alone.

**2 and NO**  **X (In thousands of tons per year)**  **Annual Emissions as Projected by IPM**

2014 Base

Case EGU Emissions 2014

“ Nationwide

BART ” 2014

“ Transport
Rule + BART

elsewhere” Additional
reduction

from

“ Transport
Rule + BART

-

23 E xtensive documentation of the IPM platform may be found at http://www.epa.gov/airmarkets/progsregs/epa

- ipm/transport.html

.

24 In the context of this action, when we refer to nationwide emissions or a nationwide analysis, we are referring to the contiguous 48 states.***E.O. 12866 Review

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Page 37 of 74 elsewhere” ( “Nationwide

BART” minus

“ Transport
Rule + BART

elsewhere” )
Nationwide

SO 7,200 7,160

2 3,800 3,820 2,900 2,918 900 902

Nationwide

NO 2,100 1,946

X 1,900 1,798 1,800 1,756 100 42

The IPM projections of annual NO X and SO 2 emissions from EGUs for

the “ Transport Rule + BART

- elsewhere” control scenario summarized in

Table 2, which were used to arrive at the modeling results presented

in section VI.5, are based on the state budgets pre scribed in the

final Transport Rule published on August 8, 2011 and the supplemental

proposal published on July 11, 2011 f inalized on December 1 5 , 2011

. 25

On October 14, 2011 the EPA issued a proposed notice that would

increase NO X and SO 2 budgets for certain states in acc o rdance with

revisions to certain unit

- level input data. 76 FR 63860. Even if

these proposed increases to state budgets are finalized, emissions of

both NO X and SO 2

25 See Federal Implementation Plans to Reduce Interstate Transport of
Fine Particulate Matter and Ozone 76 FR 48208 ( August 8, 201 1). The ozone season state budgets for the states affected by the supplemental proposal published on July 11, 2001 (76 FR 40662) (and finalized on December 15, 2011) are included in the “ Transport Rule +

BART

- elsewhere” control scenario. in the Transport Rule states in the “ Transport Rule +

BART

- elsewhere” control scenario will still be substantially below

emissions in the “Base Case” scenario. Therefore, we believe that the

mod eling results in section VI.5 comparing these two scenarios based Formatted: Highlight Comment [MarthaK1]: Confirm date with
CAMD***E.O. 12866 Review

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Page 38 of 74 on the emissions from the final Transport Rule, showing that the

first prong of the better

- than

- BART test is satisfied, are also

sufficient for determining that the Transport Rule as modifie d by the

proposed increases in the state budgets also would meet the first

prong.

Also, even if the proposed state budget increases are finalized,

the “ Transport Rule + BART

- elsewhere” control scenario is still

projected to result in about 3,000 26,000 tons more NO X emission

reductions than “Nationwide BART” and about 845,000 821,000 tons more

SO 2 emission reductions than “Nationwide BART”. We believe the changes

in the emissions differences between these two scenarios that would

result if the proposed i ncreases in state budgets are finalized are

unlikely to affect the determination of whether “ Transport Rule +

BART

- elsewhere” provides greater visibility improvement than

“Nationwide BART” averaged across all affected Class I areas, as

assessed by the seco nd prong of two

- pronged test. A sensitivity

analysis that examines the impact of the proposed state budget

increases on visibility improvement is presented in Appendix C of the

TSD. We request comment on this aspect of our proposed determination.

To assess the air quality metrics that are part of the two

–

pronged test, we used the IPM emission projections summarized in

Table 2 as inputs to an air quality model to determine the impact of

“ Transport Rule + BART

- elsewhere” and “Nationwide BART” controls on E. Air Quality Modeling Results***E.O. 12866 Review

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Page 39 of 74 visibility in the affected Class I areas. To project air quality

impacts we used the Comprehensive Air Quality Model with Extension

(CAMx) version 5.3. The air quality modeling analysis and related

analy ses to project visibility improvement are described in more

detail in the TSD for the Transport Rule

. 26 The base year meteorology

used in the CAMx modeling was 2005. The base year IMPROVE ambient

monitoring data for the years 2003

- 2007 were used to project

visibility to 2014 and to compare the visibility improvements from

the two control scenarios. The 2003

- 2007 IMPROVE data were used

because these are the 5 years of data which straddle the base 2005

modeling year. The post

- processing calculations for visibi lity are

co nsistent with the RHR tracking progress guidance 27 and t he regional

haze air quality modeling guidance. 28 The visibility projections for

each Class I area are presented in the air quality modeling TSD. 29

The cornerstone of our modeling process was the 2014 “Base C ase ”

modeling scenario, which contains emissions for 2014 based on

26 See Air Quality Modeling Final Rule Technical Support Document, U.S. EPA, June 2011, which is found at: http://www.epa.gov/airtransport/pdfs/AQModeling.pdf

.

27 See Guidance for Tracking Progress Under the Regional Haze Rule,
U.S. EPA, EPA

- 454/B

- 03

- 004, September 2003, which is found at: http://www.epa.gov/ttncaaa1/t1/memoranda/rh_tpurhr_gd.pdf

.

28 See Guidan ce on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM 2.5 , and Regional Haze , U.S. EPA, EPA

- 454/B

- 07

- 002

, April 2007 , which is found

at: http://www.epa.gov/scram001/guidance/guide/final

- 03

- pm

- rh

guidance.pdf

.

29 See Technical Support Document for Demonstration of the Transport
Rule as a BART Alternative, Docket EPA

- HQ

- OAR

- 2011

- 0729.***E.O. 12866 Review

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Page 40 of 74 predicted growth and existing emissions controls. We used model

predicted changes in visibility impairment along with the observed

base year visibility values to estimate f uture visibility im pairment

at each Class I area. We applied the relative predicted change in

visibility (expressed as a percent) from the model, due to emissions

changes, to the base year visibility values to estimate future

visibility. The projected visi bility values were based on emissions

changes between the 2005 base year inventory and the 2014 inventory.

After we established the future year 2014 “Base C ase ” visibility

values, we calculated estimated visibility improvements at each Class

I area by mode ling the “Transport Rule + BART

- elsewhere” control

strategy as well as the “ N ationwide BART” strategy in 2014.

We did two separate analyses to assess the potential visibility

impacts of “ Transport Rule + BART

- elsewhere” and “Nationwide BART”

controls on 60 Class I areas in the Transport Rule region and on 140

Class I areas in the contiguous 48 states (referred to as the

national region ) . For both visibility scenarios w e quantified the

visibility impacts on the 20 percent best and 2 0 percent worst

visib ility days for the 2014 future

- year base case , the “ Transport

Rule + BART

- elsewhere” scenario, and the “Nationwide BART” control

scenario.

Under the first prong of the test, visibility cannot degrade at

any affected Class I area. To determine if “ Transpor t Rule + BART

elsewhere” resulted in degradation of visibility at any affected***E.O. 12866 Review

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Page 41 of 74 Class I area we compared the visibility impacts of “ Transport Rule +

BART

- elsewhere” to base case 2014 visibility conditions. As described

in detail in the TSD for this action

, the “ Transport Rule + BART

elsewhere” alternative passed this first prong in the Transport Rule

region by not causing visibility degradation at any of the 60

affected Class I area s in the eastern Transport Rule modeling domain

( i.e.

, when using the first approach to identifying affected areas)

,

on either the 20 percent best or the 20 percent worst days

. In the

national region ( i.e. , when using the second approach to identifying

affected areas), the “ Transport Rule + BART

- elsewhere” alternative

was also pre dicted to not cause visibility degradation at any

affected Class I area on either the 20 percent best of the 20 percent

worst days, with a few exceptions. The exceptions were predicted

average degradations of 0.23, 0.23

, and 0.26 deciviews, respectively,

at Pine Mountain Wilderness, Arizona, Mazatzal Wilderness, Arizona,

and Saguaro National Park, Arizona, on the 20 percent worst days

. 30

There was also a predicted degradation of 0.05 deciviews on the 20

percent best days at Bryce Canyon National Park in Utah

. 31

30 The results for Pine Mountain and Mazatzal were the same because they are both represented by the same IMPROVE monitoring site (Ike ’s Backbone, IKBA). While not

part of the two

- pronged test, we also compared the baseline scenario

31 Changes in visibility were rounde d to the nearest 0.1 deciviews. Therefore, any changes that were less than 0 .05 were rounded down and
treated as zero. Any chan ges that were 0.05 or greater were rounded up and treated as potential degradation.***E.O. 12866 Review

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Page 42 of 74 to the “Nationwide BART” scenario. The analysis of the national

region under the “Nationwide BART” control scenario projected a

degradation of 0.23 deciviews on the 20 percent worst days at Pine

Mountain Wilderness and Mazatzal Wilderness (the same as the

“ Transport Rule + BART

- elsewhere” result just noted)

.

The fact that unexpected degradations at some western Class I

areas were predicted for the “Nationwide BART” scenario as well as

the “ Transport Rule + BART

- elsewhere” scenario led us to investigate

the CAMx modeling output in more detail. 32

In the CAMx output for 36 km grid cells in the vicinity of these

four Class I areas, we observed that modeled concentrations of

nitra te were very low on the 20 percent worst days (and 20 percent

best days at Bryce Canyon) in both the “ Transport Rule + BART

elsewhere” case and the “Nationwide BART” case

. The modeled nitrate

concentrations in these cases ranged from 0.001 to 0.004 μ g/m Based on that

investigation, we consider the visibility projections for the western

port ion of the national modeling domain that indicate potential

degradation in 4 western Class I areas under the “ Transport Rule +

BART

- elsewhere” scenario compared to the “Base Case” scenario to be

anomalous results that do not indicate the true effects that the

“ Transport Rule + BART

- elsewhere” scenario (or the “Nationwide BART”

scenario) will have on visibility in these areas.

3

32 Appendix B of the The TSD in the docket for this action provides more information on this aspect of the CAMx modeling results. ,***E.O. 12866 Review

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Page 43 of 74 averaged across the 20 percent worst or best days in 2005

. Notably,

the modeled concentrations were generally a small fraction of

monitored ambient nitrate concentrations at the IMPROVE sites for the

four Class I areas. In the cases where degradation was c alculated, a

very small increase in modeled nitrate was observed on several of the

worst or best modeled days. This lead to a relatively large modeled

percent increase in nitrate. As an example, on the worst day s at Pine

Mountain and Mazatzal the modeled nitrate concentration increased

from 0.001 μ g/m 3 in the 2 014 base case to 0.002 μ g/m 3

Further examination of the days when these nitrate increases

occur reveals a somewhat random pattern of very small increases and

decreases that appear unrelated to EGU emissions changes

. While IPM

predicts modestly higher NO in the

“ Transport Rule + BART

- elsewhere ” case.

X emissions in some nearby states under the

“ Transport Rule + BART

- elsewhere” scenario, the checkerboard pattern

of nitrate differences in A rizona and southern Utah show no logical

connection to these modestly higher emissions

. This nitrate modeling

issue appears similar to a previously noted nitrate chemistry

stability issue when modeled concentrations are very small and

relative humidity is very low. 33

33 T Appendix B of the he TSD in the docket for this action provides
more information on this issue

. Thus, we conclude that these positive

and negative differences between very low nitrate concentrations are

a modeling artifact attributable to the nitrate physics in CAMx for***E.O. 12866 Review

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Page 44 of 74 the conditions that apply in this geographic area on these days, and

a re not reasonable predictors of the true relative effects on

visibility of the emission control scenarios.

To illustrate how sensitive the predictions of degradation are

to highly variable results on particular days, if the one day of the

20 percent worst or best days with the largest increase in modeled

nitrate concentration at each site is removed from consideration for

that site, the apparent degradations no longer occur. We also note

that although the increases in modeled nitrate concentrations are

ver y small (ranging between 0.01 and 0.04 μg/m 3 for the one day at

each site just mentioned), the “relative response factor” method we

used to combine CAMx output ( representing future conditions ) with

IMPROVE monitoring data ( representing historical condition s ) greatly

magnified these small increases in nitrate concentrations. The small

increases in modeled nitrate are converted to relatively large

percent increases in nitrate and then multiplied by actual ambient

nitrate concentrations in the base period that are far higher than

the concentrations predicted by CAMx. Thus, very small differences in

concentrations of nitrate in the CAMx output that would have had no

effect on calculated deciview values if used directly, nevertheless

result in apparent degradatio ns on the order of 0.1 to 0.26 deciviews

after being combined with IMPROVE data. The EPA is investigating

possible modifications to the software used to post

- process CAMx

output . These possible revisions are aimed at avoiding potentially***E.O. 12866 Review

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Page 45 of 74 misleading results in situations such as the one observed near these

western Class I areas. W e seek comment on an alternate methodology

described in Appendix B of the TSD that attempts to address the

effects of very low nitrate concentrations on visibility results.

After considering the results of the first prong of the

visibility test and examining the CAMx output in more detail as

described above, w e are confident that no degradation in the four

western Class I areas will result from implementation of the

Transport Rule trading program s in the Eastern e astern U.S.

Consequently, we are proposing that the “ Transport Rule + BART

elsewhere” control scenario passes the first prong of the visibility

test considering affected Class I areas located in both the Transport

Rule region (first approach) and the national region (second

approach). Details on the individual Class I area calculations can be

found in the air quality modeling TSD.

The second prong of the test assesses whether the “ Transport

Rule + BART

- elsewhere” scena rio results in greater average visibility

improvement at affected Class I areas compared to the “Nationwide

BART” scenario. To determine if “ Transport Rule + BART

- elsewhere”

achieved greater average visibility improvement, we compared the

visibility impact s of “ Transport Rule + BART

- e lsewhere ” at the Class

I areas to visibility impacts predicted at these same areas after

implementation of “Nationwide BART”. In the Transport Rule region

(first approach) and the national region (second approach) , the***E.O. 12866 Review

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Page 46 of 74 average visibility improvement of the “ Transport Rule + BART

elsewhere” alternative was greater than “Nationwide BART” on both the

20 percent best and 20 percent worst days. Thus, the “ Transport Rule

+ BART

- elsewhere” alternative measure passed the second prong of the

test, regardless of which way affected Class I areas are identified.

A summary of the results of the second prong of the test for the

Transport Rule and national regions under each control scenario is

presented in Table 3.

**Table 3. Average Visibility Improvement in 2015 v. 2015 Base Case**  **(Deciviews)**

“ Transport Rule +

BART

- elsewhere” “ Nationwide BART ”

60 Class I Areas in the

Eastern Transport Rule Modeling Domain

20 percent Worst Days 1.6 0.7

20 percent Best Days 0.3 0. 1

140 Class I Areas in the
Western and Eastern Transport
Rule Modeling Domains

20 percent Worst Days 0.7 0.5

20 percent Best Days 0.1 0.1

Based on our finding that the “ Transport Rule + BART

- elsewhere”

control scenario passes the two

- pronged test, w e are proposing to

determine that the Transport Rule trading program s will provide

greater progress towards Regional Haze goals than source

- specific

BART

. This proposed determination applies only to EGUs in the F. Proposed Amendment to the Regional Haze Rule***E.O. 12866 Review

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Page 47 of 74 Transport Rule trading programs and only for the pollutants covered

by the programs in each state. Accordingly, we propose to revise 40

CFR 51.308(e ) (3)(ii)(4) by essentially replacing the name of CAIR

with the name of the Transport Ru le

.

We are also proposing that a state that chooses to meet the

emission reduction requirements of the Transport Rule by submitting a

complete SIP revision substantively identical to the provisions of

the EPA trading program that is approved as meeting th e requirements

of §52.38 and /or §52.39 also need not require BART

- eligible EGUs in

the s tate to install, operate, and maintain BART for the pollutants

covered by such a tradin g program in the s tate.

We are preserving the language in the regional haze regulations

at 40 CFR 51.308(e)(4)that allows states to include in their SIPs

geographic enhancements to the alternative program to accommodate a

situation where BART is required based on reasonable attr ibution of

visibili ty impairment at a Class I area.

A number of the states for which we are proposing a FIP had

previously failed to either submit a visibility SIP or had failed to

submit a SIP that could be fully approved under the visibility

regulations issued in 1980. See 45 FR 80084 (December 2, 1980). The

proposed regulatory text is drafted to take account of this and is

not intended to change the findings that have been made in the past

with respect to the relevant states’ compliance with the requirem ents

of visibility regulations found at 40 CFR 51.302

- 51.307.***E.O. 12866 Review

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Page 48 of 74 **V. Proposed**  **Limited Disapproval of Certain States’ Regional Haze** 

**SIPs**

In this action

, we are proposing a limited disapproval of the

regional haze SIPs that have been submitted by Alabama, Flor ida,

Georgia, Kentucky, Indiana, Iowa, Louisiana, Michigan, Mississippi,

Missouri, North Carolina, Ohio, Pennsylvania, South Carolina and

Texas. These states, fully consistent with the EPA ’s regulations at

the time, relied on CAIR requirements to satisfy the BART requirement

and the requirement for a long

- term strategy sufficient to achieve

the state

- adopted reasonable progress goals.

We are not proposing to disapprove the reasonable prog ress

targets for 2018 that are an element of the long

- term strategies for

these states. We made clear in the RHR that the reasonable progress

goals are not mandatory standards in the sense of there being

consequences if they are not met because there are i nherent

uncertainties in projecting future emissions and resulting visibility

conditions. See 64 FR 35733. However, to assess whether current

implementation strategies will be sufficient to meet the reasonable

progress goals, the RHR requires a midcourse r eview by each state

and, if necessary, a correction of the state’s regional haze plan.

See 40 CFR 52.308(g). We anticipate that since the Transport Rule

will result in greater emission reductions overall than CAIR, that

the need for such corrections will b e unlikely. Based on the

information currently before us, we believe that t he substitution of***E.O. 12866 Review

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Page 49 of 74 the Transport Rule for CAIR does not w eaken any affected state’s

long

- term strategy , but we will assess the midcourse review of each

state’s SIP to ensure that th is is so. We intend to act on the

reasonable progress goals and long

- term strategy (including the

proposed FIP) and other requirements of the RHR (BART determinations

for non

- EGU sources, monitoring, consultation with federal land

managers, etc.) for each state in an individual notice separately

from the final rule for this action. Those individual notices will

constitute the final action (approval or disapproval) on those other

elements of the SIP.

The EPA has already proposed limited disapproval of reg ional

haze SIPs that relied on CAIR that were submitted by Tennessee,

Virginia and West Virginia. The remedy for the limited disapprovals

previously proposed and those that are proposed in this action is

FIPs as described in section VI.

**VI. Proposed FIPs** 

In this action

, we are p roposing partial regional haze FIPs for

states for which we already have or are now proposing limited

disapprovals because of the termination of CAIR. These limited FIPs

would satisfy the BART requirement and be a part of satisfyi ng the

requirement for a long

- term strategy sufficient to achieve the state

adopted reasonable progress goals. The FIPs apply only to EGUs in the

affected states and only to pollutants covered by the Transport Rule

program s in those states. For the reasons discussed in section V.,***E.O. 12866 Review

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Page 50 of 74 t he proposed FIP s do not alter states’ reasonable progress goals or

replace these goals.

The proposed FIPs replace reliance on CAIR requirements with

reliance on the Transport Rule as an alternative to BART for SO 2 and

NO X emissions from EGUs in the following states’ regional haze SIPs:

Alabama, Georgia, Indiana, Iowa, Kentucky, Michigan, Missouri, North

Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, Texas,

Virginia and West Virginia . The proposed FIPs replace rel iance on

CAIR requirements with reliance on the Transport Rule as an

alternative to BART for NO X

Given the requirements of the CAA to promulgate a FIP afte r

disapproving a SIP in whole or in part ( CAA section 110(c)(1 ))

, we

consider it appropriate at this time to propose to issue FIPs to

address the noted deficiencies in the se states’ regional haze SIPs

related to the termination of CAIR and the replacement of CAIR with

the Transport Rule

. A state may choos e to submit a SIP or remain

subject to this FIP

. The proposed regional haze FIPs rely on the

trading program s set out in the FIPs promulgated by the EPA in August

2011 in the Transport Rule to limit the interstate transport of NO emissions from EGUs in the following

states’ regional haze SIPs: Florida , Louisiana and Mississippi.

X

and SO 2

**V II**  **. Statutory and Executive Order Reviews** .

A. Executive Order 12866: Regulatory Planning and Review and

Executive Order 13563: Improving Regulation and Regulatory Review***E.O. 12866 Review

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Page 51 of 74 Under Executive Order 12866 (58 FR 51735, October 4, 1993), this

action is a "significant regulatory action” because some may view it

as raising novel legal or policy issues arising out of legal

mandates, the President’s priorities, or the principles set f orth in

the Executive Order. Accordingly, the EPA submitted this action to

the Office of Management and Budget (OMB) for review under Executive

Orders 12866 and 13563 (76 FR 3821, January 21, 2011) and any changes

made in response to OMB recommendations ha ve been documented in the

docket for this action.

This action does not impose an information collection burden

under the provisions of the B. Paperwork Reduction Act

Paperwork Reduction Act , 44 U.S.C. 3501

et seq

. Burden is defined at 5 CFR 1320.3(b). This action does not

include or require any information collection.

The Regulatory Flexibility Act (RFA) generally requires an

agency to prepare a regulatory flexibility analysis of any rule

subject to notice and comment rulemak ing requirements under the

Administrative Procedure Act or any other statute unless the agency

certifies that the rule will not have a significant economic impact

on a substan tial number of small entities. Small entities include

small businesses, small org anizations, and small governmental

jurisdictions. C. Regulatory Flexibility Act

For purposes of assessing the impacts of this rule on small***E.O. 12866 Review

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Page 52 of 74 entitie s, small entity is defined as: (1) A small business that is a

small industrial entity as defined in the U.S. Small Business

Administration (SBA) size sta ndards. ( See

After considering the economic impacts of this proposed rule on

small entities, I certify that this action will not have a

significant economic impact on a substantial number of small

en tities. This rule will not impose any requirements on small

entities. Rather, this proposed rule would allow states to avoid

regulating EGUs in new ways based on the current requirements of the

Transport Rule and as such does not impose any new requirements on

small en tities. We continue to be interested in the potential impacts

of the proposed rule on small entities and welcome comments on issues

related to such impacts. 13 CFR 121.); (2) A

governmental jurisdiction that is a government of a city, county,

town, school district, or special district with a population of less

than 50,000; and (3) A small organization that is any not

- for

- profit

enterprise which is independent ly owned and operated and is not

dominant in its field.

This action contains no federal mandates under the provisions of

T itle II of the Unfunded Mandates Reform Act of 1995 (UMRA, 2 U.S.C.

1531

– 1538) for state, local, or tribal governments or the private

sector

. The action imposes no enforceable duty on any state, local , or D. Unfunded Mandates Reform Act***E.O. 12866 Review

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Page 53 of 74 tribal governments or the private sector

. Therefo re, this action is not

subject to the requirements of sections 202 or 205 of the UMRA

.

This action is also not subject to the requirements of section

203 of UMRA because it contains no regulatory requirements that might

significantly or uniq uely affect sma ll governments. This action

merely interprets the statutory requirements that apply to states in

preparing their SIPs and thus apply also to FIPs.

This action does not have federalism implications. It will not

have sub stantial direct effects on the states, on the relationship

between the national government and the states, or on the

distribution of power and responsibilities among the various levels

of government, as speci fied in Executive Order 13132. This action

does not impose any new mandates on state or local governments. E. Executive Order 13132: Federalism

Thus, Executive Order 13132 does not apply to this rule.

In the spirit of Executive Order 13132 and consistent with EPA

policy to promote communications between the EPA and state and local

governments, the EPA is specifically soliciting comments on this

proposed rule from state and local officials.

This rule does not have tribal implications, as specified in

Executive Order 13175 (6 5 FR 67249, November 9, 2000). The rule does

not have a substantial direct effect on one or more Indian tribes, F. Executive Order 13175: Consultation and Coordination with Indian

Tribal Governments***E.O. 12866 Review

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Page 54 of 74 since there are no BART

- eligible EGU sources on tribal lands in the

Transport Rule region

. In addition, the CAA does not provide f or the

inclusion of any tribal areas as mandatory Class I federal areas ;

thus

, tribal areas are not subject to the requirements of the RHR.

Furthermore, this proposed rule does not affect the relationship or

distribu tion of power and responsibilities between the federal

government and Indian tribes

. Thus, Executive Order 13175 does not

apply to this action. The EPA specifically solicits additional

comment on this proposed action from tribal officials.

The EPA interprets Executive Order 13045 (62 FR 19885, April 23,

1997) as applying to those regulatory actions that concern health or

safety risks, such that the ana lysis required under section G. Executive Order 13045: Protection of Children from Environmental

Health and Safety Risks

5

– 501 of the Order has the potential to influence the regulation.

This action is not subject to Executive Order 13045 because it does

not involve decisions on environmental health or safety risks that

may disproportionately aff ect children. The EPA believes that the

emissions reductions from the strategies in this rule will further

improve air quality and will further improve children’s health.

H. Executive Order 13211: Actions Concerning Regulations That

Significantly Affect En ergy Supply, Distribution, or Use

This action is not a “significant energy action” as defined in

Executive Order 13211 (66 FR 28355 (May 22, 2001)), because it is not***E.O. 12866 Review

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Page 55 of 74 likely to have a significant adverse effect on the supply,

distribution, or use of ener gy because it does not establish

requirements that directly affect the general public and the public

and private sectors . Rather, this proposed rule would allow states to

avoid regulating EGUs in new ways based on the current requirements

of the Transport Rule , and thus may avoid adverse effects that

conceivably might result from such additional regulation of EGUs by

states.

Section 12(d) of the National Technology Transfer and

Advancement Act of 1995 (" NTTAA"), Public Law 104

- 113, section 12(d),

(15 U.S.C. 272 note) directs the EPA to use voluntary consensus

standards in its regulatory activities unless to do so would be

inconsistent with applicable law or otherwise impractical. Voluntary

consensus stand ards are technical standards ( I. National Technology Transfer and Advancement Act

e.g. , materials

specifications, test methods, sampling procedures, and business

practices) that are developed or adopted by volunt ary consensus

standards bodies. The NTTAA directs the EPA to provide Congress,

through OMB, expl anations when the Agency decides not to use

available and applicable voluntary consensus standards. This

rulemaking does n ot involve technical standards. Therefore, the EPA

is not considering the use of any voluntary consensus standards.

J. Executive Order 12898: Federal Actions to Address Environmental

Justice in Minority Populations and Low

- Income Populations***E.O. 12866 Review

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Page 56 of 74 Executive Order 12898 (EO) (59 FR 7629, February 16, 1994)

establishes f ederal executive policy on environmental justi ce. Its

main provision direct s f ederal agencies, to the greatest extent

practicable and permitted by law, to make environmental justice part

of their mission by identifying and addressing, as appropriate,

disproportionately high and adverse human health or environmental

effects of the ir programs, policies, and activities on minority

populations and low

- income populations in the United States.

When considering the possible environmental justice impacts of

this proposed rule, it is important to distinguish the set of

scenarios on which the better

- than

- BART analysis described in this

notice is based from the set of possible future situations that could

come to pass based on the outcome of this rulemaking. The Transport

Rule is in place and will remain in place regardless of the outcome

o f this rulemaking. If we finalize the proposed rule, a regional haze

SIP or FIP for an affected state will be able to satisfy the BART

requirement for EGUs (for NO X only or for SO 2 and NO X , depending on

which Transport Rule program s appl y ies in that state) merely by

formally incorpo rating the Transport Rule into the long

- term strategy

of the SIP. 34

34 Such action by a state would not preclude it from also including in

the SIP source

- specific emission limits for EGUs of its choosing. If we do not adopt any rule establishing the Transport

Rule as an alternative to BART, the EGUs in each affected state will

still be required to pa rticipate in the cap

- and

- trade programs***E.O. 12866 Review

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Page 57 of 74 established by the Transport Rule . In this case the SIP or FIP would

also have to apply source

- specific BART to all BART

- eligible sources

except any that are found not to be subject to BART due to minimal

impacts on visibility or any that the state concludes should not be

further controlled based on its consideration of existing controls,

cost of additional controls, remaining lifetime of the unit, other

non

- air impacts and visibility impact s from controls . It is impo rtant

to recognize that because of the nature of cap

- and

- trade programs,

total state

- wide emissions will not be very different, if at all, if

the EPA were not to make a final determination that participation in

the Transport Rule trading program satisfied the BART requirements.

Any EGUs that would be required to comply with source

- specific BART

would generate tradable emission allowances that would find buyers

among the other EGUs in the state. Thus, we expect that the outcome

of this rule may change how a fixed amount of total emissions from

EGUs is divided among EGUs in a given affected state. Because of the

certainty of EGUs collectively m eeting the Transport Rule emission

caps, that fixed amount will generally be substantially less than

historical total EGU emissions in a given state.

We have concluded that it is not practicable to perform an

analysis which would attempt to predict exactly which EGUs would have

higher and lower emissions under the two possible outcomes. We have,

however, identified the locations of BART

- eligible sources in

Transport Rule

- affected state s to determine if there are high***E.O. 12866 Review

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Page 58 of 74 percentages of minority or low

- income populations living near such

sources. These are the sources that conceivably could have higher

emission s if we finalize the proposed rule than if we do not. An

analysis of demographic data shows that the average percentage of

African Americans living within a 3

- mile radius of BART

- eligible

sources in Transport Rule

- affected state s is somewhat higher ( six

pe rcent) than the corresponding national average percentage. All

other socio

- demographic parameters evaluated are within two percent

of the national average percentages, or below the national average

percentages. The results of the demographic analysis are p resented in

the memorandum entitled “Review of E nvironmental Justice Impacts,”

July 2011, a copy of which is available in the docket ( EPA

- HQ

- OAR

2011

- 0729 ). Strictly speaking, if we were not to finalize this rule

and the states (or we, through FIPs) were t o impose source

- specific

BART on these sources, other sources might increase their emissions

under the cap

- and

- trading programs. Since we do not know which other

sources might do so, we could not perform a similar demographic

analysis on such other sources

.

We do know that under the Transport Rule , ozone and PM 2.5 air

quality and health risks will be greatly reduced compared either to

current conditions or to future conditions if there were no Transport

Rule

. In the Transport Rule

, the EPA estimated the distribution of

PM 2.5 mortality risks according to race, income, and educational

attainment before and after implementation of the Transport Rule . In***E.O. 12866 Review

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Page 59 of 74 that analysis, we found that the Transport Rule market

- based regional

approach to reducing emissions of SO 2 and NO X from EGUs provided the

greatest PM 2.5 - related health benefits among populations: (1) most

susceptible to air pollution impacts, regardless of race; (2) with

lower levels of educational attainment; (3) living in counties with

among the highest number of individuals living below the poverty

lin e. The analysis also indicates that the Transport Rule , in

conjunction with the implementation of existing or proposed rules,

will reduce the disparity in risk between the highest

- risk counties

and the other 95 percent of counties for all races and educati onal

levels. This analysis is presented in more detail in the R egulatory

Impact Analysis f or the Transport Rule which is available in the

Transport Rule docket EPA

- HQ

- OAR

- 2009

- 0491 and from the main EPA

webpage for the Transport Rule www.epa.gov/airtranspo rt

The results of the Transport Rule analysis suggest that regional

reductions in PM .

2.5 levels can produce significant human health

benefits

— particularly among populations most susceptible and

vulnerable to PM 2.5 impacts. PM 2.5 air quality improvement s that would

be expected under implementation of source

- specific BART may differ

from the Transport Rule in terms of the emission reductions required

at any given source, especially since state s have the discretion to

determine which BART

- eligible sources to control and the level of

control that is feasible. However, the results of the Transport Rule

assessment suggest that the regional Transport Rule approach provides***E.O. 12866 Review

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Page 60 of 74 widespread health benefits especially among populations at greatest

risk.

**Li st of Subje**  **cts**

**40 CFR Part 51**

Administrative practice and procedure

, Air pollution control

,

Incorporation by reference, Intergovernmental relations, Nitrogen

oxides, Ozone, Particulate matter, Regional haze, Reporting and

recordkeeping requirements, Sulfur dioxide.***E.O. 12866 Review

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Page 61 of 74 **Page 59 of 7 2** 

**- Regional Haze:**  **Revisions to Provisions Governing**
**Alternative s**  **to Source**

**- Specific Best Available Retrofit Technology**  **(BART) Determinations , Limited SIP Disapprovals,**  **and Federal**  **Implementation Plan s** 

**40 CFR Part 52**

Administrative practice and procedure

, Air pollution control

,

Incorporation by reference, Intergovernmental relations, Nitrogen

oxides, Ozone, Particulate matter, Regional haze, Reporting and

recordkeeping requirements, Sulfur dioxide.

_________________________________ __ Dated:

___________________________________ Lisa P. Jackson,
Administrator

.***E.O. 12866 Review

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Page 62 of 74 For the reasons set forth in the preamble, part 51 of chapter I of

title 40 of the Code of Federal Regulations is proposed to be amended

as follows:

**PART 51**

**- [AMENDED]** 

1. The authority citation for part 51 continues to read as

follows:

**Authority:** 23 U.S.C. 101; 42 U.S.C. 7401

- 7671q

2. Section 51.308 is amended by revising paragraph (e)(3)(ii)(4)

to read as follows:

§ **51. 308**  **Regional haze program requirements**

********

(4) A State subject to a trading program established in accordance

with §52.38 or §52.39 under a Transport Rule Federal Implementation

Plan need not require BART

- eligible fossil fuel

- fired electric steam

generating plants in the State to install, op erate, and maintain BART

for the pollutant covered by such trading program in the State. A

State that chooses to meet the emission reduction requirements of the

Transport Rule by submitting a SIP revision that establishes a

trading program and is approved as meeting the requirements of §52.38

or §52.39 also need not require BART

- eligible fossil fuel

- fired

electric steam generating plants in the State to install, operate,

and ma intain BART for the pollutant covered by such trading program

in the State. A State may adopt provisions, consistent with the

requirements applicable to the State for a trading program***E.O. 12866 Review

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Page 63 of 74 established in accordance with §52.38 or §52.39 under the Transport

Rul e Federal Implementation Plan or established under a SIP revision

that is approved as meeting the requirements of §52.38 or §52.39, for

a geographic enhancement to the program to address the requirement

under §51.302(c) related to BART for reasonably attri butable

impairment from the pollutant covered by such trading program in that

State.

For the reasons set forth in the preamble, part 52 of chapter I of

title 40 of the Code of Federal Regulations is amended as follows:

**PART 52**

**- [AMENDED]** 

1. The authority citation for part 52 continues to read as follows:

**Authority:** 42 U.S.C. 7401, et seq

**Subpart B**

**- Alabama**  .

2. Section 52.61 is amended by revising paragraph (a) and adding new

paragraphs (c) and (d) to read as follows:

**§52.61 Visibility protection.**

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.302, 51.308(d)(3)

, and 51.308(e) for

protection of visibility in mandatory Class I Federal areas.

*****

(c) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X are satisfied by

§52.54 for the sources subject to those requirements.***E.O. 12866 Review

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Page 64 of 74 (d) Best Available Retrofit Technology for SO 2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart K**

**- Florida**  are satisfied by

§52.55 for the sources subject to those requirements.

3. Section 52.534 is amended by revising paragraph (a) and adding

new paragraph (c) as follows:

**§52.534 Visibility p rotection.** 

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.305, 51.307, 51.308(d)(3)

, and

51.308(e) for protection of visibility in mandatory Class I Federal

areas.

*****

(c) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emission s of NO X

**Subpart L** 

**- Georgia**  are satisfied by

§52.540 for the sources subject to those requirements.

4. Section 52.580 is added to read as follows:

**§52. 580 Visibility p**  **rotection.**

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.308(d)(3) and 51.308(e) for protection

of visibility in mandatory Class I Federal areas.***E.O. 12866 Review

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Page 65 of 74 (b) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X are satisfied by

§52.584 with respect to emission s of NO X

(c) Best Available Retrofit Technology for SO for the sources subject to

those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**S ubpart P** 

**- Indiana**  are satisfied by

§52.585 for the sources subject to those requirements.

5 . Section 52.791 is added to read as follows:

**§52. 791 Visibility p**  **rotection.**

a) The requirements of section 169A of the Clean Air Act are not met

because the plan does not include approvable measures for meeting the

requirements of 40 CFR 51.308(d)(3) and 51.308(e) for protection of

visibility in mandatory Class I Federal areas.

(b) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X

(c) Best Available Retrofit Technology for SO are satisfied by

§52.789 for the sources subject to those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart Q**

**- Iowa**  are satisfied by

§52.790 for the sources subject to those requirements.

6 . Section 52.8 42 is added to read as follows:

**§52. 8**  **42 Visibility p**  **rotection.*****E.O. 12866 Review

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Page 66 of 74 (a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for mee ting

the requirements of 40 CFR 51.308(d)(3) and 51.308(e) for protection

of visibility in mandatory Class I Federal areas.

(b) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X

(c) Best Available Retrofit Technology for SO are satisfied by

§52.840 for the sources subject to those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart S**

**- Kentucky**  are satisfied by

§52.841 for the sources subject to those requirements.

7. Section 52.936 is amended by revising paragraph (a) and adding

new paragraphs (c) and (d) to read as follows:

**§52. 936 Visibility p**  **rotection.**

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.307(b)and (c), 51.308(d)(3)

, and

51.308(e) for protection of visibility in mandatory Class I Federal

areas.

*****

(c) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X are satisfied by

§52.940 for the sources subject to those requirements.***E.O. 12866 Review

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Page 67 of 74 (d) Best Available Retrofit Technology for SO 2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart T**

**- Louisiana**  are satisfied by

§52.941 for the sources subject to those requirements.

8 . Section 52.985 is added to read as follows:

**§52. 985 Visibility p**  **rotection.**

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.308(d)(3) and 51.308(e) for protection

of visibility in mandatory Class I Federal areas.

(b) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X

**Subpart X**

**- Michigan**  are satisfied by

§52.9 84 for the sources subject to those requirements.

9 . Section 52.1183 is amended by revising paragraph (a) and adding

new paragraphs (d) and (e) to read as follows:

**§52. 1183 Visibility p**  **rotection.**

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include appro vable measures for meeting

the requirements of 40 CFR 51.302, 51.305

, 51.307, 51.308(d)(3)

, and

51.308(e) for protection of visibility in mandatory Class I Federal

areas.

********E.O. 12866 Review

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Page 68 of 74 (d) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X

(e) Best Available Retrofit Technology for SO are satisfied by

§52.1186 for the sources subject to those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart Z**

**- Mississippi**  are satisfied by

§52.1187 for the sources subject to those requirements

.

1 0 . Section 52.1279 is added to read as follows:

**§52. 1279 Visibility p**  **rotection.**

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.308(d)(3) and 51.308(e) for protection

of visibility in mandatory Class I Federal areas.

(b) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respe ct to emissions of NO X

**Subpart AA**

**- Missouri**  are satisfied by

§52.1284 for the sources subject to those requirements.

11. Section 52.1339 is amended by revising paragraph (a) and adding

new paragraphs (c) and (d) to read as follows:

**§52. 1339 Visibility p**  **rotection.**

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.302

, 51.308(d)(3)

, and 51.308(e) for

protection of visibility in mandatory Cla ss I Federal areas.***E.O. 12866 Review

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Page 69 of 74 *****

(c ) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X

(d ) Best Available Retrofit Technology for SO are satisfied by

§52. 1236 for the sources subject to those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart II**

**- North Carolina**  are satisfied by

§52. 1327 for the sources subject to those requirements.

1 2 . Section 52.1779 is added to read as follows:

**§52. 1779**  **Visibility p rotection.** 

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.308(d)(3) and 51.308(e) for protection

of visibility in mandatory Class I Federal areas.

(b) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X

(c) Best Available Retrofit Technology for SO are satisfied by

§52.1784 for the sources subject to those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart KK**

**- Ohio**  are satisfied by

§52.1785 for the sources subject to those requirements.

1 3 . Section 52.1886 is added to read as follows:

**§52. 1886 Visibility p**  **rotection.*****E.O. 12866 Review

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Page 70 of 74 (a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.308(d)(3) and 51.308(e) for protection

of visibility in mandatory Class I Federal areas.

(b) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X

(c) Best Available Retrofit Technology for SO are satisfied by

§52.1882 for the sources subject to those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart NN**

**- Pennsylvania**  are satisfied by

§52.1883 for the sources subject to those requirements.

1 4 . Section 52.2042 is added to read as follows:

**§52. 2042 Visibility p**  **rotection.**

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.308(d)(3) and 51.308(e) for protection

of visibility in mandatory Class I Federal areas.

(b) Best Available Retro fit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X

(c) Best Available Retrofit Technology for SO are satisfied by

§52.2040 for the sources subject to those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart PP**

**- South Carolina**  are satisfied by

§52.2041 for the sources subject to those requirements.***E.O. 12866 Review

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Page 71 of 74 1 5 . Section 52.2132 is amended by revising paragraph (a) and adding

new paragraphs (d) and (e) to read as follows:

**§52. 213**  **2 Visibility p rotection.** 

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.302

, 51.305, 51.308(d)(3)

, and

51.308(e) for protection of visibility in mandatory Class I Federal

areas.

*****

(d) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X

(e) Best Available Retrofit Technology for SO are satisfied by

§52.2140 for the sources subject to those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart RR**

**- Tennessee**  are satisfied by

§52. 2141 for the sources subject to those requirements.

1 6 . Section 52.223 4 is added to read as follows:

**§52. 223**  **4 Visibility p**  **rotection.**

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.308(d)(3) and 51.308(e) for protection

of visibility in mandatory Class I Federal areas.***E.O. 12866 Review

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Page 72 of 74 (b) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X

(c) Best Available Retrofit Technology for SO are satisfied by

§52.2240 for the sources subject to those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart SS**

**- Texas**  are satisfied by

§52.2241 for the sources subject to those requirements.

1 7 . Section 52.2304 is amended by revising paragraph (a) and adding

new paragraphs (c) and (d) to read as follows:

**§52. 2304 Visibility p**  **rotection.**

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include appro vable measures for meeting

the requirements of 40 CFR 51.30 5, 51.308(d)(3)

, and 51.308(e) for

protection of visibility in mandatory Class I Federal areas.

*****

(c) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X

(d) Best Available Retrofit Technology for SO are satisfied by

§52.2283 for the sources subject to those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart VV**

**- Virginia**  are satisfied by

§52.2284 for the so urces subject to those requirements.

1 8 . Section 52.2452 is amended by revising paragraph (a) and adding

new paragraphs (d) and (e) to read as follows:***E.O. 12866 Review

– Draft

– Do Not Cite, Quote or Release During
Review*** EO12866_Regional Haze Revisions_2060

- AR05_Proposal FRN_ 20111019

Page 73 of 74 **§52. 2452 Visibility p**  **rotection.**

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include approvable measures for meeting

the requirements of 40 CFR 51.302, 51.305, 51.308(d)(3)

, and

51.308(e) for protection of visibility in mandatory Class I Fed eral

areas.

*****

(d) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51.308(e) with respect to emissions of NO X

(e) Best Available Retrofit Technology for SO are satisfied by

§52.2440) for the sources subject to those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2

**Subpart XX**

**- West Virginia**  are satisfied by

§52.2441 for the sources subject to those requirements.

1 9 . Section 52.2533 is amended by revising paragraph (a) and adding

new paragraphs (d) and (e) to read as follows:

**§52. 2533 Visibility p**  **rotection.**

(a) The requirements of section 169A of the Clean Air Act are not

met because the plan does not include appro vable measures for meeting

the requirements of 40 CFR 51.302, 51.305, 51.307, 51.308(d)(3)

, and

51.308(e) for protection of visibility in mandatory Class I Federal

areas.

********E.O. 12866 Review

– Draft

– Do Not Cite, Quote or Release During
Review*** EO12866_Regional Haze Revisions_2060

- AR05_Proposal FRN_ 20111019

Page 74 of 74 (d) Best Available Retrofit Technology for NO X . The requirements of

40 CFR 51. 308(e) with respect to emissions of NO X

(e) Best Available Retrofit Technology for SO are satisfied by

§52.2540 for the sources subject to those requirements.

2 . The requirements of

40 CFR 51.308(e) with respect to emissions of SO 2 are satisfied by

§52.2541 for the sources subject to those requirements.

### 1 

### Technical Support Document for Demonstration of the Transport Rule as a

BART Alternative

1.0 Introduction

This Technical Support Document (TSD) provides details on the air quality modeling analysis performed in support of EPA’s proposed determination that the trading programs in the Transport Rule 1 

### , also known as the Cross

- State Air Pollution Rule, achieve gre ater reasonable progress towards the national goal of achieving natural visibility conditions in Class I areas than

source

- specific Best Available Retrofit Technology (BART) in those states covered by the Transport Rule.

The Transport Rule requires 28 st ates in the eastern half of the United States to reduce electric generating unit (EGU) sulfur dioxide (SO 2 

### ) and nitrogen dioxide (NO X 

### ) emissions that cross state lines and contribute to ground

- level ozone and /or fine particle pollution in downwind

states. BART, on the other hand, is applicable nationwide and covers 26 industrial categories, including EGUs of a certain vintage. The analysis described in this TSD sought to determine whether the Transport Rule air quality assured allowance trading program fo r EGUs will achieve
greater visibility improvement than would BART for EGUs only.

Criteria for determining if a BART alternative (such as the Transport Rule trading program s ) achieves greater reasonable progress than source

- specific BART are set out in t he Regional Haze Rule at § 51.308(e)(3). The “better

- than

- BART” test may be satisfied as follows: If the distribution of emissions is not substantially different than under BART, and the alternative measure results in greater emission reductions, then the alternative measure may be deemed to achieve greater reasonable progress. If the distribution of emissions is significantly different under the alternative, then an air quality modeling study is conducted to determine differences in visibility between BA RT and the alternative program for each affected Class I area for the worst and best 20 percent of days. The two

- pronged visibility test would demonstrate “greater reasonable progress” under the alternative program if both of the following criteria are me t:

- Visibility does not decline in any Class I area 2

1 See Federal Implementation Plans to Reduce Interstate Transport of Fine Particulate Matter and Ozone, 76 FR 48208 (August 8, 2011) and Federal Implementation Plans for Iowa, Kansas, Michigan, Missouri, Oklahoma, and Wisconsin To Reduce In terstate Transport of Ozone, 76 FR 40662 (July 11, 2011) for more details. For the purposes of the proposed Transport Rule is Better

- than

- BART rule and for the analysis described in this TSD, the Transport Rule includes all of the states (28) included in t he final Transport Rule and the supplemental notice. 

### , and

2 The “decline” is relative to modeled future base case visibility conditions in the absence of any BART or alternative program control requirements (including CAIR and the Transport Rule).

### 2 - There is an overall improvement in visibility, determined by comparing the average

differences between BART and the alternative over all affected Class I areas.

The underlying purpose of both prongs of the test is to assess whether visibility conditions at Class I areas would be better with the alternative program in place than they would without it. The first prong ensures that the alternative program will not cause a decline in visibility at any affected Class I area. It addresses the possibility that the alternative program might cause local changes in emissions that could result in localized visibility degradation. The second prong ensures that the program results in improvements in averag e visibility across all affected Class I areas as compared to adopting source

- specific BART. Together, these tests ensure that the alternative program provides for greater visibility improvement than would source

- specific

BART.

Since the distribution o f emissions under the Transport Rule program s is substantially different than the distribution of emissions that might result from source

- specific BART

, an air quality modeling study was conducted to determine whether visibility improvement resulting

from implementation of the Transport Rule meets the two

- pronged visibility test for demonstrating “greater reasonable progress” than source

- specific BART.

Section 2.0 of this document describes the development of the emission projections that are the basis for the air quality and visibility modeling in the Transport Rule I s “Better

- than

– BART” analysis. Section 2.1 describes the underlying inventory of BART units and t he modeling criteria used to constrain each control scenario. National and state

- specific emission projections from the Integrated Planning Model (IPM) are described in section 2.2

. Section 3.0 of this TSD describes the air quality modeling performed for this analysis including the modeling process and methodology, and calculation of visibility impacts for each control scenario. Projected visibility impacts for each control scenario are shown for each mandatory Class I Federal area (for which there were su fficient data). Appendix A lists the inventory of BART

eligible units used in the “Nationwide BART” control scenario. Appendix B provides a detailed analysis of the effect of very low nitrate concentrations on visibility results at several Class I

areas, and Appendix C describes the potential visibility impacts of proposed revisions to the

NOx and SO 2 

### budgets for certain states subject to the Transport Rule

. .

2.0 Emission Projections Used for Transport Rule I s Better

- than

- BART Analysis

The air quality mode ling conducted for this analysis is based on emission projections for

two control scenarios. One scenario represents “Nationwide BART” and the other represents “Transport Rule + BART

- elsewhere”. The “Nationwide BART” scenario examined SO 2 

### and

NO X 

### emissio ns from all EGUs nationwide after the application of BART controls to all BART

eligible EGUs. In the “Transport Rule + BART

- elsewhere” scenario, EGU SO 2 

### and NO X

### 3 emissions reductions attributable to the Transport Rule were applied in the 28

- state Transport Rule region and BART controls were applied to all BART

- eligible EGUS outside the Transport Rule region that are not subject to Transport Rule requirements. The latter scenario reflects the

fact that source

- specific BART would remain a regional haze SIP e lement outside the Transport Rule region. In order to more accurately project the Transport Rule emissions, it is necessary to assume EGU BART controls outside the Transport Rule region to account for potential load and emission shifting among EGUs.

2.1 E lig ible BART Units and Modeling Criteria

The first step in developing the control scenarios was to identify EGUs in the contiguous 48 states that are eligible for BART controls and for which EPA has developed presumptive

emission limits. These criteria limi ted the analysis to coal

- fired EGUs for which construction commenced by August 7, 1977 and that were not in operation prior to August 7, 1962. The impacts of BART were modeled using stringent assumptions regarding the EGUs (or specific units at EGUs) that would be subject to BART. The Regional Haze rule (RHR) BART

Guidelines 3 

### specify that presumptive limits for NOx and SO 2 

### should be applied to EGUs having a total generating capacity of 750 MW. The Guidelines also exempt from controls BART

eligible units with the potential to emit less than 40 tons per year of either NOx or SO 2



### . In this analysis it was assumed that all BART

- eligible EGUs were subject to BART requirements to ensure that controls that states might choose to require on sources not subject to presumptive

BART were accounted for in this analysis. It was also assumed that presumptive BART limits would be applied to much smaller units. In this analysis it was assumed that the threshold for

BART

- eligibility was 100 MW for SO 2 

### and 25 MW for NO X 

### and no source was eliminated

based on their annual total emissions. Appendix A lists the EGUs that were assumed to be

BART

- subject for the purpose of this analysis.

For both the “Nationwide BART” scenario and the “Transport Rule + BART

- elsewhere”
scenario, t he modeled emission rates were the presumptive EGU BART limits for SO 2 

### and NO X 

### as specified in the BART Guidelines, unless an actual emission rate at a given unit w ith existing

controls is lower. In the latter case, the lower emission rates were modeled. Version 410 of the National Electric Energy Data System (NEEDS), an EPA database of existing and planned

committed EGUs, was used to identify emission rates for each EGU. 4



### For SO 2 

### , the RHR BART Guidelines specify presumptive BART limits for an EGU with

a n existing scrubber as 95 percent scrubber control efficiency or 0.15 lbs/MMBtu. The NEEDS

3 Guidelines for BART Determinations under the Regional Haze Rule, 70 FR 39104, July 6, 2005.

4 See The NEEDS User Guide: http://www.epa.gov/airmarkets/progsregs/epa

ipm/CSAPR/docs/Guide_to_NEEDSv410.pdf which is found at http://www.epa.gov/airmarkets/progsregs/epa

- ipm /transport.html

.

### 4 was used to identify which BART

- eligible units have existing scrubbers, the scrubber efficiency

at these units and the controlled SO 2 

### emission rate. For scrubbed BA RT

- eligible units the

modeled SO 2 

### emission rate was based on a comparison of the SO 2 

### emission rate listed for that unit in NEEDS to the presumptive SO 2 

### limits. For an EGU with a scrubber operating at 95 percent or higher efficiency, the emission rate being achieved at that control efficiency was modeled for that unit even if the emission rate was higher than 0.15 lbs/MMBtu. Conversely, if an emission rate of 0.15 lbs/MMBtu or lower is being achieved, that emission rate was modeled
for that unit, even if the scrubber is less than 95 percent efficient. For BART

- eligible units without existing scrubbers, an emission rate was modeled that reflected 95 percent control based on a new installation of a highly efficient scrubber.

For NOx, the RHR BART Guide lines specify presumptive limits based on coal type and boiler configuration. The BART guidelines also specify that existing NO X 

### controls must be operated year round. For the source

- specific “Nationwide BART” scenario and for the

“elsewhere” EGUs in the “Transport Rule + BART

- elsewhere” scenario, it was assumed that any

BART

- subject unit with existing NO X 

### controls in the future baseline case would retain at least those controls and would be required to operate them year round. If the existing NO X 

### control s in the future baseline case did not meet the presumptive BART limits, installation of post

combustion controls (i.e., selective catalytic reduction (SCR) or selective non

- catalytic reduction (SNCR)) that would meet the BART guidelines with year

- round ope ration was assumed. In the “Transport Rule + BART

- elsewhere” scenario, there are 5 states that are subject to the Transport Rule requirements during the ozone season only. 5 

### For these states, NO X 

### controls were assumed to operate only during ozone season a s required by the Transport Rule.

Table 2

- 1 summarizes the NO X 

### emission limits that were applied to BART

- eligible units of 25 MW or greater. For units firing a coal blend, which the BART Guidelines do not address, a weighted presumptive NO X 

### limit based o n the percentage of each coal type fired was calculated

and modeled.

Table 2

- 1. BART Presumptive NO X 

### Limits by Boiler Configuration and Coal Type (lbs/MMBtu)

Bituminous Subbituminous Lignite Dry bottom wall

- fired 0.39 0.23 0.29 Tangential

- fired 0.28 0.15 0.17
Cell burners 0.40 0.45 Not applicable Dry turbo

- fired 0.32 0.23 Not applicable Wet bottom tangential

- fired 0.62 Not applicable Not applicable Cyclone 0.10 0.10 0.10

5 States subject to the Transport Rule requirements during the ozone season only are Oklahoma, Arkansas, Louisiana, Mississippi and Florida.

### 5 BART emission limits modeled for certain EGUs were different from presumptive limits if the EGU has a configuration for which presumptive limits have not been established, or if the EGU has a different emission limit prescribed by a proposed or finalized State Implementation Plan, a Federal Implementation Plan, a final c onsent decree, or by state rule. These units and the

emission rates modeled for these units are detailed in Table 2

- 2

.

Note that all but a few of the EGUs listed in Table 2

- 2 are in states that are not covered by the Transport Rule. Hence, the assumptio ns about their BART emission rates cannot affect the outcome of the second prong of the “better than BART” test because the emission rates for these EGUs are the same in both the “nationwide BART” and Transport Rule + BART

elsewhere” air quality analyses t hat are compared in the second prong of the visibility test.

### 6 Table 2

- 2

. Modeled Emission Rates other than Presumptive Limits for Specific EGUs*

EGU Name State ORIS Plant Code/CAMD
UnitID Modeled NOx Emission Rate (lbs/MMBtu) Modeled SO 2 Emission Rate (lbs/MMBtu) Comment

R.M. Heskett B ND 2790/1875 0.20 FBC unit with no presumptive limits established. Used the “general” NOx limit used for this size boiler in the 2005
RHR BART Guidelines.
Marion IL 976/9173 0.20 FBC unit with no presumptive limits established. Used the “general” NOx limit used for this size boiler in the 2005
RHR BART Guidelines.
Monticello TX 6147/2809 0.14 Wall

- fired, wet bottom firing a 50/50 lignite/subbituminous blend. Emission rate per Memo from Rob LaCount re: New NOx requirements in the State of Texas (SB7) Big Bend FL 645/467
645/468
645/469 0.12 Consent decree

Bridgeport CT 568/373 0.14 (ozone season) 0.15 (non

- ozone season) 0.33 State alternative BART demonstration.

Navajo Tribal 4941/2662
4941/2663
4941/2664 0.24 NOx limit beginning 2009 per voluntary permit limit.

San Juan NM 2451/1596
2451/1597
2451/1598
2451/1599 0.05 0.15 Approved SIP (NOx)
Final FIP (SO 2 )

Muskogee OK 2952/2005
2952/2006 0.06 Proposed FIP

Sooner OK 6095/2773
6095/2774 0.06 Proposed FIP

Northeastern OK 2963/2019
2963/2020 0.06 Proposed FIP

Valmont CO 477/309

------ ------- Shutting down in 2017.
Howard Down NJ 50397/3655

------ ------- Converted to No. 6 fuel oil in 2010. Edge Moor DE 593/383 0.15 in 2009
0.125 in 2012 0.37 in 2009
0.26 in 2012 Delaware state regulation 1146

Indian River DE 594/388
594/389 0.15 in 2009
0.125 in 2012 0.37 in 2009
0.26 in 2012 Delaware state regulation 1146

Reid Gardner NV 2324/1401 0.20 0.15 Proposed SIP

### 7 2324/1402
Reid Gardner NV 2324/1403 0.28 0.15 Proposed SIP
Four Corners Tribal 2442/1581
2442/1582
2442/1583 ----- ----- Shutdown by 12/31/2014 (proposed FIP).

Four Corners Tribal 2442/1584
2442/1585 0.098 Unit 158 4 installing NOx controls by the end of 2017 and
Unit 158 5 installing NOx controls by end of 2018 (proposed FIP). KPC&L La Cygne KS 1241/819
1241/820 0.13 weighted

average of emissions
from both units 0.10 weighted

average of
emissions from
both units State consent decree.

Jeffrey Energy Center KS 6068/2734
6068/2735 0.15 0.15 State consent decree.

Boardman OR 6106/2778 0.23 beginning July 1, 2011 0.4 by 2014 Interim SO 2 limits must be met in 2014. NOx limit must be met beginning July 1, 2011. Facility s hutdown in 2020. 

### *Where an emission rate is not listed, the presumptive NOx or SO 2 

### emission rate for that EGU configuration was modeled.

### 8 2.2 Emission Pro jections

To estimate emissions expected from the control scenarios described in section 2.1

, the Integrated Planning Model 6 

### (IPM) was used. The IPM is a multi

- regional, dynamic, deterministic linear programming model of the electric power sector. It is used extensively by the EPA to support regulatory activities. The IPM provides forecasts of least

- cost capacity expansion, electricity dispatch, and emission control strategies for meeting electricity demand subject to environmental, transmission, dispat ch, and reliability constraints. The IPM was used in this case to evaluate the emissions impacts of the described scenarios limiting the emissions of

SO 2 

### and NO X 

### from EGUs. This analysis used the most recently updated IPM platform which is

documented at http://www.epa.gov/crossstaterule/

. Table 2

- 3 presents the annual emissions for each policy scenario as projected by the IPM. As shown by the numbers in the far right column, “Transport Rule + BART

- elsewhere” achieved greater emission reductions nationwide 7 

### for both pollutants than source

- specific “Nationwide BART” alone.

Table 2

- 3. National EGU SO 2 

### and NO X 

### Annual Emissions as Projected by IPM (i n thousands of tons per year)

2014 Base Case
EG U Emissions 2014
“Nationwide
BART” 2014 “Transport
Rule + BART

elsewhere” Additional reduction from “Transport Rule + BART

elsewhere” (“Nationwide BART” minus “Transport
Rule + BART

- elsewhere”)
National Annual
SO 2 7,160 3,820 2,918 902

National Annual
NO X 2,089 1,798 1,756 42



### The IPM projections of annual NO X 

### and SO 2 

### emissions from EGUs for the “Transport

Rule + BART

- elsewhere” control scenario summarized in Table 2

- 3, which were used to arrive at the modeling results presented in section 3 .5, are based on the state budgets prescribed in the final Transport Rule published on August 8, 201 1 and the supplemental proposal published on July 11, 2011. 8 

### State

- specific emission projections for the 2014 base case and each control

scenario are shown for SO 2 

### emissions in Table 2

- 4 and for NOx emissions in Table 2

- 5.

6 Extensive documentation of the IPM platform may be found at http://www.epa.gov/airmarkets/progsregs/epa

- ipm/transport.html

. 7 In the context of this analysis, when we refer to nationwide emissions or a nationwide analysis, we are referring t o the contiguous 48 states.

8 Federal Implementation Plans to Reduce Interstate Transport of Fine Particulate Matter and Ozone 76 FR 48208 (August 8, 2011). The ozone season state budgets for the states affected by the supplemental proposal published on Ju ly 11, 2001 (and finalized on December 15, 2011) are included in the “Transport
Rule + B ART

- elsewhere” control scenario (Federal Implementation Plans for Iowa, Kansas, Michigan, Missouri, Oklahoma, and Wisconsin To Reduce Interstate Transport of Ozone, 76 FR 40662)

.

### 9 Table 2

- 4. 2014 Annual SO 2 

### Emissions in the Transport Rule Region and Non

- Transport Rule Region States for the 2014 base case and each Control Scenario

.
Transport Region
States 2014
Base Case Nationwide
BART Transport
Rule +
BART

elsewhere Non

Transport Region
States 2014
Base Case Nationwide
BART Transport
Rule +
BART

elsewhere
Alabama 417.3 181.5 168.5 Arkansas 99.4 38.1 39.7 Georgia 170.3 151.4 93.6 Arizona 35.6 24.6 24.6

Illinois 141.6 116.1 133.7 California 7.3 7.4 7.3

Indiana 727.8 454.5 202.9 Colorado 62.1 22.4 26.6

Iowa 133.1 43.9 83.8 Connecticut 3.8 1.9 1.9

Kansas 69.8 19.8 49.1 Delaware 2.2 2.1 2.1 Kentucky 488.0 164.9 125.4 Florida 143.6 77.5 79.8 Maryland 42.9 36.5 28.6 Idaho 0.2 0.2 0.2 Michigan 269.4 141.4 174.3 Louisiana 118.2 81.2 92.6

Minnesota 70.9 56.5 50.1 Maine 2.4 2.6 2.4

Missouri 390.3 107.9 181.8 Massachusett

s 13.4 8.4 8.4

Nebraska 9 73.1 32.9 71.2 Mississippi 31.0 16.3 17.8 New Jersey 38.9 26.1 6.1 Montana 15.4 5.9 6.7

New York 42.9 42.1 18.8 Nevada 14.4 14.8 14.8
North
Carolina 126.0 130.9 74.0 New Hampshire 6.5 4.7 5.2

Ohio 851.2 546.7 190.0 New Mexico 11.9 10.8 11.7 Pennsylvania 509.6 222.6 134.5 North Dakota 103.6 37.7 37.0

South
Carolina 213.3 114.0 101.5 Oklahoma 138.0 41.4 41.4

Tennessee 284.5 321.3 66.7 Oregon 11.3 0.2 0.2

Texas 453.3 139.3 266.6 Rhode Island 0 0.0 0.0 Virginia 77.3 78.7 53.9 South Dakota 29.7 2.4 2.5 West Virginia 498.5 165.1 90.4 Utah 33.5 32.7 32.1

Wisconsin 130.5 52.1 51.4 Vermont 0.3 0.3 0.3 Washington 3.4 3.4 3.4

Total 6,220.50 3,346.20 2,416.90 Wyoming 51.8 37.2 42.9

Total 9 39.00 474.20 501.60

9 Gerald Gentleman Unit 2 was inadvertently omitted from the inventory of BART

- eligible units. SO 2 emission s for
Nebraska would be approximately 12,000 tons less under the Nationwide BART scenario if Gerald Gentleman Unit 2 had been properly included in the Nationwide BART control scenario; however we do not expect that this
difference in emissions would change the outcome of our analysis. Formatted: Superscript

Formatted: Superscript

Formatted: Subscript

### 10 Table 2

- 5. 2014 Annual NOx Emissions in the Transport Rule Region and Non

- Transport Rule Region States for the 2014 base case and each Control Scenario 10

Transport Region States 2014
Base Case Nationwide
BART Transport
Rule + BART

elsewhere Non

- Transport Region States 2014
Base Case Nationwide
BART Transport
Rule + BART

elsewhere
Alabama 76.0 74.1 70.3 Arkansas 36.3 26.2 36.9 Georgia 49.4 45.4 41.8 Arizona 35.6 26.0 26.0

Illinois 55.3 49.3 49.6 California 26.9 27.0 27.1

Indiana 117.8 107.8 111.5 Colorado 49.4 46.9 48.0

Iowa 48.4 41.8 42.4 Connecticut 2.9 2.7 2.5

Kansas 32.6 22.6 24.4 Delaware 1.7 1.8 1.7
Kentucky 83.5 75.4 78.0 Florida 100.6 81.0 75.7 Maryland 17.6 15.6 16.8 Idaho 0.6 0.6 0.6 Michigan 67.7 64.7 62.3 Louisiana 31.6 31.7 31.7

Minnesota 41.5 34.1 35.1 Maine 5.4 6.2 5.4

Missouri 57.3 50.3 51.2 Massachusetts 7.0 7.2 7.1

Nebraska 45.0 30.2 28.1 Mississippi 26.3 19.7 19.5 New Jersey 8.0 8.1 7.8 Montana 19.4 13.4 13.5

New York 21.7 21.8 20.5 Nevada 14.1 13.8 13.9

North Carolina 49.3 52.2 45.4 New Hampshire 5.1 3.1 3.0

Ohio 104.1 96.9 90.1 New Mexico 64.7 13.0 13.0 Pennsylvania 134.1 122.3 118.4 North Dakota 53.3 43.9 43.9

South Carolina 39.0 34.3 37.0 Oklahoma 67.0 44.6 44.3

Tennessee 29.3 34.7 20.5 Oregon 9.6 2.3 2.3

Texas 142.1 139.4 139.5 Rhode Island 0.4 0.4 0.5 Virginia 40.5 41.9 39.1 South Dakota 14.3 2.5 2.6 West Virginia 64.8 65.7 53.2 Utah 67.4 61.7 62.2
Wisconsin 40.7 36.5 34.5 Vermont 0.5 0.5 0.5 Washington 13.3 10.0 10.0

Total 1,365.70 1,265.10 1,217.50 Wyoming 70.2 46.5 46.5

Total 723.60 532.70 538.40

10 Due to limitations in the IPM model , NOx emissions from a small number of units were underestimated in the

“ National BART ” run. At the national level , the NOx emissions that were underestimated account for about 0.22%
of national emissions which is not significant for th e scope of this analysis.

### 11 3

. 0 Air Quality Modeling to Determine Future Visibility

In this section we describe the photochemical air quality modeling performed to support the finding that compliance with the Transport rule for EGUs w ill result in greater visibility improvement in Federal Class I areas than source

- specific BART.

This section also includes technical information on the air quality model applied in support of the proposed rule, and the procedures for projecting regional haze for future year

scenarios. The Transport Rule Air Quality Modeling

- Final Rule Technical Su pport Document ( TR

- AQMTSD) 11 

### contains more detailed information on the air quality modeling aspects of this rule. This technical support document provides additional information, including further details on the post

- processing of model results and calculation for visibility and visibility metrics.

3.1 Overview of the Modeling Process

We completed numerous modeling runs and post

- processing calculations to determine the impacts of emissions and emissions control strategies on visibility in Class I a reas. Determining such visibility impacts allows for the comparison of the effects of compliance with a

“N ationwide BART ” program (for EGUs) to the final Transport Rule, as represented by the “Transport rule + BART

- elsewhere ” scenario

. We detail these ca lculations and the modeling process in subsequent sections, following a brief description of the overall process.

The cornerstone of our modeling process was the 201 4 base case modeling scenario

, which contains emissions for 201 4 based on predicted growth and existing emissions controls. 12



### We used model

- predicted changes in visibility impairment along with the observed base year visibility values to estimate future visibility impairment at each Class I area. We applied the relative predicted change in vis ibility (expressed as a percent) from the model, due to emissions changes, to the base year visibility values to estimate future visibility. The projected visibility values were based on emissions changes between the 200 5 base year inventory and the 201 4 inventory.

After we established the future year 2014 base case visibility values, we calculated estimated visibility improvements at each Class I area by modeling the “ Transport Rule +
BART

- elsewhere ” 13

11 U.S. EPA, Air Quality Modeling

- Final Rule Technical Suppo rt Document (for the Cross State Air Pollution Rule). June 2011. Docket number EPA

- HQ

- OAR

- 2009

- 0491 available at 

### control strategy as well as the “ nationwide BART ” strategy in 201 4

.

http://www.epa.gov/airtransport/pdfs/AQModeling.pdf
12 This is the same 2014 base case model run used for the Transport Rule. It is a “no CAIR” scenario which assumes that CAIR is not in place in 2014. The basis for this assumption is explained in further detail in the Transport Rule final rule preamble.
13 The Transport Rule + BA RT elsewhere strategy is the Transport Rule applied in the region where it is in effect

### 12 3.2 Overview of the Future Year Visibility Projections

In general, we estimated base and future year visibility impairment using the same modeling approach that was used in the Ju ly 2011 Transport Rule final rule modeling to develop base and future year predictions of PM 2.5 

### concentrations and visibility impairment. In the f inal Transport Rule modeling we used the C AMx model (version 5.30) to predict PM 2.5 

### levels. We

used the C AMx predicted PM 2.5 

### components to estimate future year changes in visibility at Class I areas. Details of the application of C AMx for the final Transport Rule , including model performance, can be found in Section V of the Transport Rule NFR preamble and the TR

AQMTSD. Famil iarity with that detailed description is assumed for present purposes.

As described in the final TR

- AQMTSD , we performed a 200 5 Base Year model simulation to examine the ability of the modeling system to replicate observed concentrat ions of PM and its p recursors. We also model ed a future

- year base case scenario for 201 4

. The future

year base case scenario included emissions resulting from growth and emissions controls required under Federal and State law

. 14 

### We completed two additional model runs for this analysis; the “nationwide BART” run and the “Transpo rt Rule + BART

- elsewhere” run. We quantified the impacts of the Transport Rule and BART controls on visibility impairment by comparing the results of the future

- year 2014 base case model runs with the res ults of the

“ Transport Rule + BART

- elsewhere ” and the “ nationwide BART ” control strategy model runs.

T able 3

- 1 lists the four CAMx model runs that were used to post

- process the visibility results for this proposed rule.

Table 3

- 1

. CAMx model scenarios use d for the Better than BART analysis

Model Scenario Modeling Completed
and Documented in the Final Transport rule Modeling Completed
and Documented for the
Better than BART rule

2005 base case X

2014 base case X

2014 Nationwide BART X
2014 Transport Rule +
BART

- elsewhere X



### Figure 3

- 1 shows the CAMx modeling domain used for the Transport Rule Better

- than

BART model runs. As shown, there is a Continental U.S. 36km domain (the large black box)

with a nested Eastern U.S. 12km domain (outlined in red)

. V isibility results were calculated

and BART applied in the rest of the contiguous U.S., as previously defined.

14 For the Transport Rule base case modeling, we assumed that CAIR was not in place and only included EGU controls that were otherwise required by Federal or State law or regulations.

### 13 using the 12km modeling results for all Class I ar eas inside of the 12km domain. The 36km modeling results were used for all other Class I areas in the West, outside of the 12km domain.

Figure 3

- 1

. CAMx 12km and 36km resolution modeling domains

We quantified visibility impacts at the Class I areas which have complete IMPROVE

ambient data for 200 5 or are represented by IMPROVE monitors with complete data. Since the base year meteorology used in the C AMx modeling is from 200 5 , ambient data from 200 5 is

needed to be able to identify the best and worst observed visibility days . It is necessary to kno w which days make up the 20 percent best and worst days so that the model outputs can be calculated on the same days. For a Class I area without ambient data in 200 5 , there is no way to match up the model predicted changes in visibility with the ambient d ata from the 20 percent best and worst days. There are currently 110 IMPROVE monitoring sites (representing 15 5

Class I areas 15 

### ) collecting ambient PM 2.5 

### data at Class I areas. Of these 110 sites, 104 are in the

Continental U.S. Of the 104 sites in the Continental U.S., 96 h ave complete data for 200 5

. These 96 sites represent 1 40 Class I areas. 16



### The 1 40 Class I area sites are scattered throughout the country and represent all of the IMPROVE defined regional visibility areas

. 17

15 There are 156 Class I areas, but one area (Bering Sea) is not represented by an IMPROVE monitor. 

### Of the 140 Class I areas

, 60 are in the East ern 12km modeling domain and 8 0 are in the West, outside of the 12km domain, but inside the 36km

16 The matching of sites to monitors is taken from the Guidance f or Tracking Progress Under the Regional Haze Rule, EPA

- 454/B

- 03

- 004, September 2003.

17 IMPROVE: Spatial and Seasonal Patterns and Temporal Variability of Haze and its Constituents in the United States: Report III (May 2000)

.

### 14 modeling domain.

3.3 Calculation of Base Year (Current) Visibility Levels

Base year (current) visibility values at Class I areas were needed to determine the starting point for calculating future year visibility improvements. For the purpose of evaluating visibility for the “better than BART” analysis, visibility impairment was calculated for the 20% worst days

and the 20% be st days a t each Class I area. The calculation of baseline visibility values for each Class I area followed the procedures detailed in the Guidance for Tracking Progress. 18 

### The baseline visibility on the 20% worst days at each Class I area was calculated using the “n ew”

IMPROVE visibility equation (IMPROVE, 2006)

. The IMPROVE data was pre

- processed 19 

### for Regional Haze calculations and reformatted to MATS format (EPA, 2010). The daily deciview values were calculated and ranked for each Class I area for each of five year s for period 2003

- 200 7

. 20 

### The 20% highest deciview values were identified as the 20% worst days for the year. A similar procedure was followed to get the 20% best days in each Class I area. Table 3

- 2 shows

the base year ( 2003

- 200 7 ) estimated visibility impairment (in deciviews) at the 1 40 Class I areas on the 20% worst days and 20% best days at each area.

Table 3

- 2

. Base Year Visibility ( 2003

- 200 7 ) on the 20% B est Days and 20% Worst Days, at 1 40
IMPROVE Sites

Class I Area IMPROVE Representative
Site IMPROVE Site
Identifier State 2003

- 200 7
Baseline Visibility

(in dv)
20% Best

Days 2003

- 200 7 Baseline Visibility

(in dv)
20%
Worst Days

Acadia NP ACAD1 ACAD ME 8.3 22.8 Agua Tibia Wilderness AGTI1 AGTI CA 8.4 22.4 Alpine Lake Wilderness SNPA1 ALLA WA 5.1 17.0

Anaconda

- Pintler Wilderness SULA1 ANAC MT 2.4 17.1
Ansel Adams Wilderness (Minarets) KAIS1 ANAD CA 1.9 15.2

Arches NP CANY1 ARCH UT 3.0 10.8

Badlands NP BADL1 BADL SD 6.7 16.8 Mount Baldy Wilderness BALD1 BALD AZ 2.9 11.3

18 U.S. EPA, Guidance for Tracki ng Progress under the Regional Haze Rule (Tracking Progress Guidance) (September 2003).

19 The IMPROVE data are available at: http://views.cira.colostate.edu/web/DataWizard/

20 The base case modeling year for this analysis (and for the Transport Rule) was 2 005. Therefore, for this analysis, we used visibility data from the five year period centered about the 2005 base year (2003

- 2007).

### 15 Class I Area IMPROVE Representative Site IMPROVE
Site
Identifier State 2003

- 200 7 Baseline Visibility

(in dv)
20% Best

Days 2003

- 200 7
Baseline Visibility

(in dv)
20%
Worst Days

Bandelier NM BAND1 BAND NM 4.6 12.0 Big Bend NP BIBE1 BIBE TX 5.7 17.2 Black Canyon of the Gunnison
NM WEMI1 BLCA CO 2.8 10.0 Bosque del Apache BOAP1 BOAP NM 6.1 13.8

Bob Marshall Wilderness MONT1 BOMA MT 3.3 16.1 Boundary Waters Canoe Area BOWA1 BOWA MN 5.9 20.2 Bryce Canyon NP BRCA1 BRCA UT 2.4 11.6 Bridger Wilderness BRID1 BRID WY 1.7 10.7 Brigantine BRIG1 BRIG NJ 14.3 28.7

Cabinet Mountains Wilderness CABI1 CABI MT 3.3 14.3 Caney Creek Wilderness CACR1 CACR AR 11.8 26.7 Canyonlands NP CANY1 CANY UT 3.0 10.8 Capitol Reef NP CAPI1 CAPI UT 3.2 10.9

Caribou Wilderness LAVO1 CARI CA 2.5 13.7

Carlsbad Caverns NP GUMO1 CAVE TX 5.6 16.5

Chiricahua NM CHIR1 CHIR AZ 4.6 12.9

Chiricahua Wilderness CHIR1 CHIW AZ 4.6 12.9

Cohutta Wilderness COHU1 COHU GA 13.8 30.5

Crater Lake NP CRLA1 CRLA OR 1.6 13.2

Craters of the Moon NM CRMO1 CRMO ID 3.7 14.1 Cucamonga Wilderness SAGA1 CUCA CA 4.5 18.4

Desolation Wilderness BLIS1 DESO CA 2.3 12.9

Diamond Peak Wilderness CRLA1 DIPE OR 1.6 13.2 Dolly Sods Wilderness DOSO1 DOSO WV 11.2 29.9 Eagle Cap Wilderness STAR1 EACA OR 3.6 17.3 Eagles Nest Wilderness WHRI1 EANE CO 0.9 8.8 Emigrant Wilderness YOSE1 EMIG CA 3.4 16.9 Everglades NP EVER1 EVER FL 12.3 22.5 Fitzpatrick Wilderness BRID1 FITZ WY 1.7 10.7 Flat Tops Wilderness WHRI1 FLTO CO 0.9 8.8

Galiuro Wilderness CHIR1 GALI AZ 4.6 12.9
Gates of the Mountains
Wilderness GAMO1 GAMO MT 1.4 11.9

Gearhart Mountain Wilderness CRLA1 GEMO OR 1.6 13.2

Gila Wilderness GICL1 GICL NM 3.1 13.1

### 16 Class I Area IMPROVE Representative Site IMPROVE
Site
Identifier State 2003

- 200 7 Baseline Visibility

(in dv)
20% Best

Days 2003

- 200 7
Baseline Visibility

(in dv)
20%
Worst Days

Glacier NP GLAC1 GLAC MT 7.1 19.6

Glacier Peak Wilderness NOCA1 GLPE WA 3.0 13.3

Goat Rocks Wilderness WHPA1 GORO WA 1.6 12.7 Grand Canyon NP GRCA2 GRCA AZ 2.2 11.9

Great Gulf Wilderness GRGU1 GRGU NH 7.0 21.4

Great Sand Dunes NM GRSA1 GRSA CO 3.9 11.8 Great Smoky Mountains NP GRSM1 GRSM TN 13.2 30.6

Grand Teton NP YELL2 GRTE WY 2.2 11.2 Guadalupe Mountains NP GUMO1 GUMO TX 5.6 16.5 Hells Canyon Wilderness HECA1 HECA OR 5.0 19.0

Hercules

- Glades Wilderness HEGL1 HEGL MO 13.0 27.0

Hoover Wilderness HOOV1 HOOV CA 1.5 11.6 Isle Royale NP ISLE1 ISLE MI 6.6 21.3 Jarbidge Wilderness JARB1 JARB NV 2.4 12.3

James River Face Wilderness JARI1 JARI VA 14.0 28.9

John Muir Wilderness KAIS1 JOMU CA 1.9 15.2

Joshua Tree NM JOSH1 JOSH CA 5.7 18.9 Joyce

- Kilmer

- Slickrock
Wilderness GRSM1 JOYC TN 13.2 30.6

Kaiser Wilderness KAIS1 KAIS CA 1.9 15.2 Kalmiopsis Wilderness KALM1 KALM OR 6.4 16.4 Kings Canyon NP SEQU1 KICA CA 8.2 23.7

Lava Beds NM LABE1 LABE CA 3.0 14.1

La Garita Wilderness WEMI1 LAGA CO 2.8 10.0

Lassen Volcanic NP LAVO1 LAVO CA 2.5 13.7 Linville Gorge Wilderness LIGO1 LIGO NC 11.3 29.7

Lostwood LOST1 LOST ND 8.0 19.6 Lye Brook Wilderness LYBR1 LYBR VT 5.8 24.1
Maroon Bells

- Snowmass
Wilderness WHRI1 MABE CO 0.9 8.8

Mammoth Cave NP MACA1 MACA KY 16.5 32.0

Mazatzal Wilderness IKBA1 MAZA AZ 5.4 14.0

Medicine Lake MELA1 MELA MT 6.6 18.2

Mesa Verde NP MEVE1 MEVE CO 3.7 12.1

Mission Mountains Wilderness MONT1 MIMO MT 3.3 16.1

Mount Hood Wilderness MOHO1 MOHO OR 1.8 14.7

### 17 Class I Area IMPROVE Representative Site IMPROVE
Site
Identifier State 2003

- 200 7 Baseline Visibility

(in dv)
20% Best

Days 2003

- 200 7
Baseline Visibility

(in dv)
20%
Worst Days

Mount Jefferson Wilderness THSI1 MOJE OR 2.7 15.8

Mokelumne Wilderness BLIS1 MOKE CA 2.3 12.9

Mountain Lakes Wilderness CRLA1 MOLA OR 1.6 13.2

Moosehorn MOOS1 MOOS ME 8.6 21.2

Mount Rainier NP MORA1 MORA WA 5.1 17.1 Mount Washington Wilderness THSI1 MOWA OR 2.7 15.8

Mount Zirkel Wilderness MOZI1 MOZI CO 1.2 9.7

North Absaroka Wilderness NOAB1 NOAB WY 1.7 11.3

North Cascades NP NOCA1 NOCA WA 3.0 13.3

Okefenokee OKEF1 OKEF GA 14.9 27.2 Olympic NP OLYM1 OLYM WA 5.7 15.8

Otter Creek Wilderness DOSO1 OTCR WV 11.2 29.9 Pasayten Wilderness PASA1 PASA WA 2.6 15.4

Pecos Wilderness WHPE1 PECO NM 1.4 9.6

Petrified Forest NP PEFO1 PEFO AZ 5.0 13.6

Pine Mountain Wilderness IKBA1 PIMO AZ 5.4 14.0

Pinnacles NM PINN1 PINN CA 8.3 17.9 Point Reyes NS PORE1 PORE CA 9.7 22.4 Presidential Range

- Dry River
Wilderness GRGU1 PRRA NH 7.0 21.4

San Rafael Wilderness RAFA1 RAFA CA 5.9 19.4

Rawah Wilderness MOZI1 RAWA CO 1.2 9.7

Red Rock Lakes YELL2 REDR WY 2.2 11.2

Redwood NP REDW1 REDW CA 5.8 18.6 Roosevelt Campobello
International Park MOOS1 ROCA ME 8.6 21.2 Cape Romain ROMA1 ROMA SC 15.1 27.4 Rocky Mountain NP ROMO1 ROMO CO 2.3 12.9

Salt Creek SACR1 SACR NM 7.9 18.3

San Gabriel Wilderness SAGA1 SAGA CA 4.5 18.4 San Gorgonio Wilderness SAGO1 SAGO CA 5.0 21.4 Saguaro NM SAGU1 SAGU AZ 7.0 14.4

San Jacinto Wilderness SAGO1 SAJA CA 5.0 21.4

San Pedro Parks Wilderness SAPE1 SAPE NM 1.5 10.4

Sawtooth Wilderness SAWT1 SAWT ID 3.7 15.0 Scapegoat Wilderness MONT1 SCAP MT 3.3 16.1

### 18 Class I Area IMPROVE Representative Site IMPROVE
Site
Identifier State 2003

- 200 7 Baseline Visibility

(in dv)
20% Best

Days 2003

- 200 7
Baseline Visibility

(in dv)
20%
Worst Days

Selway

- Bitterroot Wilderness SULA1 SELW MT 2.4 17.1 Seney SENE1 SENE MI 7.1 25.1 Sequoia NP SEQU1 SEQU CA 8.2 23.7

Shenandoah NP SHEN1 SHEN VA 10.2 29.4 Shining Rock Wilderness SHRO1 SHRO NC 7.3 28.5

Sierra Ancha Wilderness SIAN1 SIAN AZ 5.7 14.5 Sipsey Wilderness SIPS1 SIPS AL 15.3 29.9

South Warner Wilderness LABE1 SOWA CA 3.0 14.1 Strawberry Mountain Wilderness STAR1 STMO OR 3.6 17.3 Superstition Wilderness TONT1 SUPE AZ 6.0 14.2 Sycamore Canyon Wilderness SYCA1 SYCA AZ 5.3 15.5

Teton Wilderness YELL2 TETO WY 2.2 11.2

Three Sisters Wilderness THSI1 THIS OR 2.7 15.8

Thousand Lakes Wilderness LAVO1 THLA CA 2.5 13.7

Theodore Roosevelt NP THRO1 THRO ND 7.1 17.9

UL Bend ULBE1 ULBE MT 4.4 15.5 Upper Buffalo Wilderness UPBU1 UPBU AR 12.0 27.0

Ventana Wilderness PINN1 VENT CA 8.3 17.9 Voyageurs NP VOYA2 VOYA MN 6.8 19.6

Washakie Wilderness NOAB1 WASH WY 1.7 11.3

West Elk Wilderness WHRI1 WEEL CO 0.9 8.8

Weminuche Wilderness WEMI1 WEMI CO 2.8 10.0

White Mountain Wilderness WHIT1 WHIT NM 3.4 13.0

Mount Adams Wilderness WHPA1 WHPA WA 1.6 12.7

Wheeler Peak Wilderness WHPE1 WHPE NM 1.4 9.6

Wind Cave NP WICA1 WICA SD 4.9 16.0

Wichita Mountains WIMO1 WIMO OK 9.9 23.6

Wolf Island OKEF1 WOLF GA 14.9 27.2

Yellowstone NP YELL2 YELL WY 2.2 11.2

Yosemite NP YOSE1 YOSE CA 3.4 16.9



### 3.4 Projection of Future Year Visibility Level

The visibility impacts of the T ransport R ule and nationwide BART SO 2 

### and NO X 

### emissions reductions were examined in terms of the projected improvements in visibility on the

### 19 20 percent best and worst visibility days at the Class I areas. We quantified visibility impacts for
the 140 Class I areas (listed in Table 3

- 2 ) in the Continental U.S. modeling domain which have complete IMPROVE ambient data for 2005 or are represented by IMPROVE monitors with complete data.

Visibility values for the 2014 base case and 2014 Transport Rule and nationwide BART

scenario s were calculated using the regional haze methodology outlined in section 6 of the photochemical modeling guidance

. 21 

### This photochemical modeling guidance recommends the calculation of future year changes in visibility in a similar manner to the calculation of changes

in PM 2.5 

### design values. The regional haze methodology for calculating future year visibility impairment is cod ified in EPA’s MATS software, which was used to post

- process the modeling runs for this analysis . This software can be found at: ( http://www.epa.gov/scram001/modelingapps_mats.htm )

.

In calc ulating visibility impairment, the extinction coefficient values 22 

### are made up of individual component species (sulfate, nitrate, organics, etc). The predicted change in visibility (on the 20 percent best and worst days) is calculated as the modeled percent change in the mass

for each of the PM 2.5 

### species and for coarse mass (on the 20% best and worst observed days) multiplied by the observed concentrations. The future mass of each component species is converted to extinction and then daily species extinctio n coefficients are summed to get a daily total extinction value (including Rayleigh scattering). The daily extinction coefficients are converted to deciviews and averaged across all 20 percent best or worst days. In this way, we calculate an average chan ge in deciviews from the base case to a future case at each IMPROVE site. Subtracting the 2014 “ Transport R ule + BART

- elsewhere ” scenario deciview values from the corresponding 2014 base case deciview values gives an estimate of the visibility benefits in Class I areas that are expected to occur from “Transport Rule + BART

- elsewhere”

. Likewise, subtracting the 2014 “ n ationwide BART ” scenario deciview values from the corresponding 2014 base case deciview values gives an estimate of the visibility benefits in Class I areas that are expected to occur from “ nationwide BART ”

.

The following options were chosen in MATS for calculating the future year visibility values for

the rule: New IMPROVE algorithm Use model grid cells at (IMPROVE) monitor Temporal adjust ment at monitor

- 3x3 for 12km grid, (1x1 for 36km grid)

21 Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM 2.5 , and Regional Haze, U.S. EPA, EPA

- 454/B

- 07

- 002, April 2007, which is found

at: http://www.epa.gov/scram001/guidance/guide/final

- 03

- pm

- rh

- guidance.pdf

. 22 Extinction coefficient is in units of inverse megameters (Mm
- 1 ).It is a measure of how much light is
absorbe d or scattered as it passes through a medium. Light extinction is commonly used as a measure of visibility impairment in the regional haze program.

### 20 Start monitor year

- 2003 End monitor year

- 2007 Base model year 2005 Minimum years required for a valid monitor

- 3

The “base model year” was chosen as 2005 because it is the base case meteorological year for the final Transport Rule modeling. The start and end years were chosen as 2003 and 2007 because that is the 5 year period which is centered on the base model year of 2005. These choices are consistent with using a 5 year base period for regional haze calculations.

3.5 Details of the Visibility Projection Methodology

The modeling guidance recommends that model predictions be used in a relative sense to estimate changes expected to occur in each major PM species that are used to estimate visibility impairment on the 20% best and worst days. These species are ammonium sulfate, ammonium nitrate, organic carbon mass, elemental carbon, crustal mass , sea salt, and coarse mass. Day

specific observations for mass associated with SO 4 

### , NO 3 

### , OC, E C, soil, and CM, are used to

calculate b ext 

### for each day. The appropriate month

- and area

- specific climatological relative humidity adjustment factor(s) ( f(rh) ) are used to calculate extinction values. Total b ext 

### for all components are converted to deciv iews for each day to get a daily deciview value.

The steps in the visibility impairment calculation are detailed below: Step 1

. Calculate the average baseline deciviews for the 20% of days with worst and the 20% days with best visibility.

For each of the 5 years in the base period, order all days from worst (highest deciview value) to best (lowest deciview value) visibility. For each year, note the 20% of days with worst and the 20% of days with best visibility. Calculate the arithmetic mean deciv iew value for the

identified 20% worst

- and best visibility days in each year. Average the resulting 5 yearly mean deciview values reflecting worst visibility. Average the 5 yearly mean deciview values reflecting mean visibility on the days with best vis ibility.

Step 2 . Estimate relative response factors (RRF) for each component of PM 2.5 

### and for coarse mass ( CM )

.

This is done using the modeled species concentrations on the measured best and worst days in 2005 at each IMPROVE site

. Take the arithmetic mean concentration for each PM 2.5 

### component (and coarse mass) computed at the Class I area monitoring site from the 2014 future

emissions case and divide this by the corresponding arithmetic mean concentration for each component obtained with base year (2 005) emissions. The resulting quotients are the

### 21 component

- specific RRF’s. A separate set of RRF values are calculated for the “worst” and

“best” visi bility days identified in step 1 . The RRFs are calculated using the identified 20% best

and 20% worst m onitored days at each Class I area.

Step 3

. Using the RRFs and ambient data, calculate future year daily concentration data for the best and worst days.

Multiply the relative response factors derived in Step 2 times measured daily

concentration data for each component of PM 2.5 

### and CM to get future daily estimates of species

concentrations for PM 2.5 

### components and CM on “worst visibility” and “best visibility” days. These multiplications produce future concentration estimates for SO 4 

### , NO 3 

### , OC, EC, Soil and CM for each of the previously selected “worst” and “best” visibility days. This calculation is performed for each best and worst day for the five year period using an RRF for each PM component (a separate set of RRFs for the best days and the worst d ays)

. Step 4

. Use the information developed in Step 3 to compute future year daily b ext 

### values for the best and worst days.

Use the future year concentration data calculated in step 3 to calculate future year daily

b ext 

### values for each PM component for each of the best and worst days for the five year period. This is accomplished by applying the “ new ” IMPROVE visibility algorithm shown below:

b ext 

### ≈ 2.2 x f s 

### (RH) x [Small Sulfate] + 4.8 x f L 

### (RH) x [Large Sulfate]

+ 2 .4 x f s 

### (RH) x [Small Nitrate] + 5.1 x f L 

### (RH) x [Large Nitrate] + 2.8 x {Small Organic Mass] + 6.1 x [Large Organic Mass] + 10 x [Elemental Carbon] + 1 x [Fine Soil]

+ 1.7 x f ss 

### (RH) x [Sea Salt] + 0.6 x [Coarse Mass] + Rayleigh Scattering (site specific)

The total sulfate, nitrate and organic carbon compound concentrations are each split into two fractions, representing small and large size distributions of those components. The organic mass concentration used in the new algorithm is 1.8 times the or ganic carbon mass concentration, changed from 1.4 times carbon mass concentration used for input into the old IMPROVE algorithm. Site

- specific Rayleigh scattering is calculated for the elevation and annual average temperature of each IMPROVE monitoring s ite.

The apportionment of the total concentration of sulfate compounds into the concentrations of the small and large size fractions is accomplished using the following

### 22 equations.

[Large Sulfate] = [Total Sulfate]/20 ug/m3 x [Total Sulfate], for [Total S ulfate] < 20 ug/m3

[Large Sulfate] = [Total Sulfate], for [Total Sulfate] 

### ≥ 20 ug/m3

[Small Sulfate] = [Total Sulfate]

- [Large Sulfate]

The same equations are used to apportion total nitrate and total organic mass concentrations into the small and larg e size fractions.

Sea salt is calculated as 1.8 x [Chloride] or 1.8 x [Chlorine] if the chloride measurement is below detection limits, missing or invalid. The algorithm also uses three new water growth adjustment terms. They are for use with the small size distribution and the large size distribution sulfate and nitrate compounds and for sea salt (f S 

### (RH), f L 

### (RH) and f SS 

### (RH) respectively)

. 23



### Step 5

. Use the daily total b ext 

### values from step 4 to calculate future mean deciview values for the best and worst days.

The total daily b ext 

### for each day is converted to deciviews. This gives a future year daily deciview value for each of the best and worst days at each site

.

Next, compute the arith metic mean future deciview value for the “worst” and “best” visibility days for each year. This leads to 5 future estimated mean deciview values for the “worst” and 5 future estimated mean deciview values for the “best” visibility days. Compute the

arith metic mean of the 5 mean values for deciviews on the “worst” days, and the arithmetic mean of the 5 mean deciview values estimated for the “best” visibility days.

3.6 Modeling Analysis of the Better than BART Two Pronged Test

The visibility improvements from the Transport Rule + BART

- elsewhere strategy were compared to the nationwide BART visibility improvements, in accordance with the two

- pronged

test for “better

- than

- BART” determinations set out in the Regional Haze Rule at § 51.308(e)(3).

The better

- than

- BART test is a two pronged test. Under the first prong, visibility must not decline at any Class I area, as determined by comparing the predicted visibility impacts at

each affected Class I area under the “ Transport Rule + BART

- elsewhere ” scenario with future

baseline (2014) visibility conditions. Under the second prong, overall visibility as measured by

23 Default values for site specific Rayleigh scattering and the f(rh ) terms were supplied in the IMPROVE data
available at on the VIEWS website.

### 23 the average improvement at all affected Class I areas must be better under the “ Transport Rule +

BART

- elsewhere ” scenari o than under “ Nationwide BART ” . The future year air quality modeling results were used to make this demonstration.

3.6.1 Better than BART Test

- 1 st 

### Prong

We did two separate analyses to assess the potential visibility impacts of “Transport Rule

+ BART

- elsewhere” and “Nationwide BART” controls . We analyzed one set of results (“first approach”) for the 60 Class I areas in the Transport Rule region (the Eastern 12km modeling domain) and a second set of results (“second approach”) for the 140 Class I areas in the contiguous 48 states (referred to as the national region). For both visibility scenarios we quantified the visibility impacts on the 20 percent best and 20 percent worst visibility days for

the 2014 future

- year base case, the “Transport Rule + BART

- elsewhere” scenario, and the

“Nationwide BART” control scenario. Under the first prong of the test, visibility cannot degrade at any affected Class I area. To determine if “Transport Rule + BART

- elsewhere” resulted in degradation of visibility at any aff ected Class I area we compared the visibility impacts of “Transport Rule + BART

- elsewhere” to base case 2014 visibility conditions.

Table 3

- 3 shows the projected visibility on the 20% best days and 20% worst days at each

Class I area in the 201 4 baseline and from the “ Transport Rule + BART

- elsewhere ” control
strateg y . Under the degradation test (1 st 

### prong), there should be no degradation from the Transport Rule scenario compared to the 201 4 baseline. The “ no degradation test” column shows

the results of subtracting the 201 4 baseline visibility values from the 201 4 Transport Rule +
BART

- elsewhere values. In order to pass this test, all values in the degradation test column should be zero or negative. 24

24 All differences that are < 0.05 dv were rounded down to 0.0 and are considered to be no degradation. In Tables 3

- 3
and 3

- 4, these sites are identified with an * next to the 0.0 in the no degradation

- test column. Calculating visibility changes to the nearest tenth of a deciview (rather than the nearest hundredth) is consistent with the practice for implementing the reasonable progress goals under the Regional Haze rule. (See, e.g ., Guidelines for Tracking Reasonable Progress, sample calculations in sections 1.8 and 1.11). Therefore, for purposes of the better

- than

- BART test, we have assumed that changes in visibility of less than 0.05 dv should not be considered degradation.

### 24 Table 3

- 3

. Projected visibility and visib ility change for the 201 4 baseline and the 201 4 Transport

+ BART

- elsewhere 20% best and worst days, at 1 40 Class I areas.

Class I Area (IMPROVE Site) State [A]

2014
Baseline Visibility

20% Best Days (dv) [B]

2014
Baseline Visibility

20%
Worst Days ( dv ) [C]

2014 TR +

BART

Elsewhere Case Visibility
20% Best Days (dv) [D]

2014 TR +

BART

Elsewhere Case Visibility
20% Worst Days (dv) No Degradati

on Test 20% Best

Days =[C]

– [A]* No Degradat
ion Test

20%
Worst Days =[D]

– [B]*

Eastern Class I areas (12km modeling domain)

Acadia NP ME 8.0 20.1 7.9 19.0 0.0

- 1.1
Badlands NP SD 6.3 16.0 6.2 15.4

- 0.1

- 0.6
Bandelier NM NM 4.2 11.1 4.1 10.8

- 0.1

- 0.3 Big Bend NP TX 5.4 16.3 5.2 15.2

- 0.2

- 1.1 Black Canyon of the
Gunnison NM CO 2.3 9.5 2.3 9.4

- 0.1

- 0.1 Bosque del Apache NM 5.6 13.0 5.5 12.5

- 0.1

- 0.6 Boundary Waters
Canoe Area MN 5.8 18.8 5.7 17.6

- 0.1

- 1.2 Brigantine NJ 13.2 25.4 12.9 22.8

- 0.4

- 2.5 Caney Creek
Wilderness AR 11.3 24.4 10.9 21.2

- 0.4

- 3.2
Carlsbad Caverns NP TX 5.2 15.5 5.1 14.7

- 0.1

- 0.9
Cohutta Wilderness GA 12.9 26.6 12.1 22.8

- 0.8

- 3.8 Dolly Sods
Wilderness WV 10.3 27.1 9.2 21.4

- 1.1

- 5.7 Eagles Nest
Wilderness CO 0.4 8.3 0.4 8.2 0.0

- 0.1 Everglades NP FL 11.5 20.4 11.1 19.3

- 0.3

- 1.0 Flat Tops Wilderness CO 0.4 8.3 0.4 8.2 0.0

- 0.1
Great Gulf
Wilderness NH 6.7 19.2 6.6 17.4

- 0.1

- 1.8
Great Sand Dunes
NM CO 3.5 11.3 3.5 11.1

- 0.1

- 0.2 Great Smoky
Mountains NP TN 12.2 27.0 11.4 23.3

- 0.8

- 3.7 Guadalupe
Mountains NP TX 5.2 15.5 5.1 14.7

- 0.1

- 0.9
Hercules

- Glades
Wilderness MO 12.2 25.2 11.6 22.7

- 0.6

- 2.5 Isle Royale NP MI 6.4 19.9 6.3 18.9

- 0.1

- 1.0
James River Face
Wilderness VA 12.9 25.8 12.1 21.6

- 0.9

- 4.2 Joyce

- Kilmer

Slickrock Wilderness TN 12.2 27.0 11.4 23.3

- 0.8

- 3.7
La Garita Wilderness CO 2.3 9.5 2.3 9.4

- 0.1

- 0.1

### 25 Class I Area (IMPROVE Site) State [A]

2014
Baseline Visibility

20% Best Days (dv) [B]

2014
Baseline Visibility

20%
Worst Days ( dv ) [C]

2014 TR +

BART

Elsewhere Case Visibility
20% Best Days (dv) [D]

2014 TR +

BART

Elsewhere Case Visibility
20% Worst Days (dv) No Degradati

on Test 20% Best

Days =[C]

– [A]* No Degradat
ion Test

20%
Worst Days =[D]

– [B]*

Linville Gorge
Wilderness NC 10.3 26.0 9.6 21.8

- 0.7

- 4.3
Lostwood ND 7.9 18.8 7.8 18.3

- 0.1

- 0.5 Lye Brook
Wilderness VT 5.5 20.7 5.4 18.2

- 0.1

- 2.6
Maroon Bells

Snowmass
Wilderness CO 0.4 8.3 0.4 8.2 0.0

- 0.1
Mammoth Cave NP KY 15.3 29.5 14.1 24.4

- 1.2

- 5.1
Medicine Lake MT 6.5 17.7 6.5 17.4 0.0

- 0.3
Mesa Verde NP CO 3.2 11.4 3.1 11.1

- 0.1

- 0.3
Moosehorn ME 8.4 19.0 8.4 18.0 0.0*

- 1.0
Mount Zirkel
Wilderness CO 1.0 9.2 1.0 9.2 0.0

- 0.1
North Absaroka
Wilderness WY 1.5 11.1 1.5 11.0 0.0 0.0
Okefenokee GA 13.9 24.1 13.0 21.6

- 0.9

- 2.5
Otter Creek
Wilderness WV 10.3 27.1 9.2 21.4

- 1.1

- 5.7
Pecos Wilderness NM 1.0 9.0 1.0 8.9

- 0.1

- 0.2 Presidential Range

Dry River
Wilderness NH 6.7 19.2 6.6 17.4

- 0.1

- 1.8
Rawah Wilderness CO 1.0 9.2 1.0 9.2 0.0

- 0.1
Roosevelt Campobello
International Park ME 8.4 19.0 8.4 18.0 0.0*

- 1.0 Cape Romain SC 13.6 24.0 12.9 21.2

- 0.7

- 2.9 Rocky Mountain NP CO 2.0 12.2 1.9 12.1 0.0

- 0.1
Salt Creek NM 7.3 17.1 7.2 16.4

- 0.1

- 0.7
San Pedro Parks
Wilderness NM 1.2 9.9 1.0 9.6

- 0.2

- 0.3 Seney MI 6.9 23.3 6.8 21.7

- 0.1

- 1.6
Shenandoah NP VA 9.0 26.2 8.2 21.2

- 0.8

- 5.0 Shining Rock
Wilderness NC 6.3 24.8 5.7 21.1

- 0.7

- 3.8 Sipsey Wilderness AL 14.5 26.5 13.6 22.8

- 0.9

- 3.7
Theodore Roosevelt
NP ND 6.8 17.0 6.8 16.7 0.0

- 0.3
UL Bend MT 4.2 15.2 4.2 15.2 0.0

- 0.1

### 26 Class I Area (IMPROVE Site) State [A]

2014
Baseline Visibility

20% Best Days (dv) [B]

2014
Baseline Visibility

20%
Worst Days ( dv ) [C]

2014 TR +

BART

Elsewhere Case Visibility
20% Best Days (dv) [D]

2014 TR +

BART

Elsewhere Case Visibility
20% Worst Days (dv) No Degradati

on Test 20% Best

Days =[C]

– [A]* No Degradat
ion Test

20%
Worst Days =[D]

– [B]*

Upper Buffalo
Wilderness AR 11.3 24.7 10.8 22.2

- 0.5

- 2.5 Voyageurs NP MN 6.6 18.4 6.5 17.4

- 0.1

- 1.0
Washakie Wilderness WY 1.5 11.1 1.5 11.0 0.0 0.0
West Elk Wilderness CO 0.4 8.3 0.4 8.2 0.0

- 0.1
Weminuche
Wilderness CO 2.3 9.5 2.3 9.4

- 0.1

- 0.1
White Mountain
Wilderness NM 3.1 12.3 3.0 11.7

- 0.1

- 0.6
Wheeler Peak
Wilderness NM 1.0 9.0 1.0 8.9

- 0.1

- 0.2
Wind Cave NP SD 4.6 15.1 4.6 14.8 0.0

- 0.3
Wichita Mountains OK 9.1 21.7 8.9 20.2

- 0.2

- 1.6
Wolf Island GA 13.9 24.1 13.0 21.6

- 0.9

- 2.5 Western Class I Areas (36km Modeling Domain)

Agua Tibia
Wilderness CA 7.9 20.2 7.8 20.2 0.0 0.0 Alpine Lake
Wilderness WA 4.6 15.8 4.6 15.7 0.0* 0.0
Anaconda

- Pintler
Wilderness MT 2.3 16.8 2.3 16.8 0.0 0.0
Ansel Adams
Wilderness (Minarets) CA 1.7 14.6 1.7 14.6 0.0 0.0
Arches NP UT 2.6 9.8 2.6 9.6

- 0.1

- 0.2 Mount Baldy
Wilderness AZ 2.5 10.9 2.4 10.9

- 0.1 0.0*
Bob Marshall
Wilderness MT 3.1 15.8 3.1 15.8 0.0

- 0.1 Bryce Canyon NP UT 2.4 10.8 2.4 10.7 0.1#

- 0.1 Bridger Wilderness WY 1.6 10.4 1.6 10.3 0.0

- 0.1
Cabinet Mountains
Wilderness MT 3.0 14.0 3.0 13.9 0.0*

- 0.1 Canyonlands NP UT 2.6 9.8 2.6 9.6

- 0.1

- 0.2 Capitol Reef NP UT 2.9 10.3 2.9 10.2 0.0

- 0.2
Caribou Wilderness CA 2.3 13.2 2.3 13.2 0.0 0.0
Chiricahua NM AZ 4.4 12.4 4.4 12.4

- 0.1

- 0.1
Chiricahua
Wilderness AZ 4.4 12.4 4.4 12.4

- 0.1

- 0.1

### 27 Class I Area (IMPROVE Site) State [A]

2014
Baseline Visibility

20% Best Days (dv) [B]

2014
Baseline Visibility

20%
Worst Days ( dv ) [C]

2014 TR +

BART

Elsewhere Case Visibility
20% Best Days (dv) [D]

2014 TR +

BART

Elsewhere Case Visibility
20% Worst Days (dv) No Degradati

on Test 20% Best

Days =[C]

– [A]* No Degradat
ion Test

20%
Worst Days =[D]

– [B]*

Crater Lake NP OR 1.5 12.7 1.5 12.7 0.0 0.0
Craters of the Moon
NM ID 3.5 13.7 3.5 13.6 0.0 0.0 Cucamonga
Wilderness CA 3.9 16.4 3.9 16.4 0.0 0.0
Desolation
Wilderness CA 2.1 12.4 2.1 12.4 0.0 0.0
Diamond Peak
Wilderness OR 1.5 12.7 1.5 12.7 0.0 0.0 Eagle Cap
Wilderness OR 3.5 16.9 3.4 16.9 0.0 0.0* Emigrant Wilderness CA 3.1 16.2 3.1 16.2 0.0 0.0 Fitzpatrick
Wilderness WY 1.6 10.4 1.6 10.3 0.0

- 0.1
Galiuro Wilderness AZ 4.4 12.4 4.4 12.4

- 0.1

- 0.1
Gates of the
Mountains
Wilderness MT 1.2 11.6 1.2 11.6 0.0

- 0.1
Gearhart Mountain
Wilderness OR 1.5 12.7 1.5 12.7 0.0 0.0
Gila Wilderness NM 2.9 13.0 2.9 12.9 0.0

- 0.2
Glacier NP MT 6.8 19.1 6.8 19.0 0.0 0.0
Glacier Peak
Wilderness WA 2.9 12.6 2.9 12.6 0.0 0.0
Goat Rocks
Wilderness WA 1.5 11.9 1.5 11.9 0.0*

- 0.1 Grand Canyon NP AZ 1.9 11.0 1.9 10.9 0.0*

- 0.1
Grand Teton NP WY 2.0 10.9 2.0 10.9 0.0 0.0 Hells Canyon
Wilderness OR 4.8 18.3 4.7 18.3 0.0 0.0
Hoover Wilderness CA 1.3 11.2 1.3 11.2 0.0 0.0 Jarbidge Wilderness NV 2.3 12.0 2.3 12.0 0.0 0.0
John Muir
Wilderness CA 1.7 14.6 1.7 14.6 0.0 0.0
Joshua Tree NM CA 5.5 17.3 5.5 17.3 0.0 0.0
Kaiser Wilderness CA 1.7 14.6 1.7 14.6 0.0 0.0 Kalmiopsis
Wilderness OR 6.1 16.1 6.1 16.1 0.0 0.0 Kings Canyon NP CA 7.6 21.5 7.6 21.5 0.0 0.0
Lava Beds NM CA 2.9 13.5 2.9 13.5 0.0 0.0

### 28 Class I Area (IMPROVE Site) State [A]

2014
Baseline Visibility

20% Best Days (dv) [B]

2014
Baseline Visibility

20%
Worst Days ( dv ) [C]

2014 TR +

BART

Elsewhere Case Visibility
20% Best Days (dv) [D]

2014 TR +

BART

Elsewhere Case Visibility
20% Worst Days (dv) No Degradati

on Test 20% Best

Days =[C]

– [A]* No Degradat
ion Test

20%
Worst Days =[D]

– [B]*

Lassen Volcanic NP CA 2.3 13.2 2.3 13.2 0.0 0.0
Mazatzal Wilderness AZ 5.0 12.9 5.0 13.2 0.0 0.2#
Mission Mountains
Wilderness MT 3.1 15.8 3.1 15.8 0.0

- 0.1
Mount Hood
Wilderness OR 1.6 13.9 1.6 13.8 0.0

- 0.1
Mount Jefferson
Wilderness OR 2.6 15.4 2.6 15.3 0.0 0.0
Mokelumne
Wilderness CA 2.1 12.4 2.1 12.4 0.0 0.0
Mountain Lakes
Wilderness OR 1.5 12.7 1.5 12.7 0.0 0.0
Mount Rainier NP WA 4.8 16.0 4.7 15.9 0.0

- 0.1 Mount Washington
Wilderness OR 2.6 15.4 2.6 15.3 0.0 0.0
North Cascades NP WA 2.9 12.6 2.9 12.6 0.0 0.0 Olympic NP WA 5.4 15.1 5.4 15.0 0.0 0.0 Pasayten Wilderness WA 2.4 14.8 2.4 14.7 0.0

- 0.1
Petrified Forest NP AZ 4.4 13.4 4.3 13.4 0.0 0.0
Pine Mountain
Wilderness AZ 5.0 12.9 5.0 13.2 0.0 0.2#
Pinnacles NM CA 7.8 16.5 7.8 16.5 0.0 0.0 Point Reyes NS CA 9.0 21.2 9.0 21.2 0.0 0.0
San Rafael
Wilderness CA 5.3 18.2 5.3 18.2 0.0 0.0
Red Rock Lakes WY 2.0 10.9 2.0 10.9 0.0 0.0
Redwood NP CA 5.8 18.0 5.8 18.0 0.0 0.0
San Gabriel
Wilderness CA 3.9 16.4 3.9 16.4 0.0 0.0 San Gorgonio
Wilderness CA 4.6 19.7 4.6 19.7 0.0 0.0 Saguaro NM AZ 6.5 13.4 6.3 13.7

- 0.2 0.3#
San Jacinto
Wilderness CA 4.6 19.7 4.6 19.7 0.0 0.0
Sawtooth Wilderness ID 3.6 14.8 3.6 14.8 0.0 0.0 Scapegoat
Wilderness MT 3.1 15.8 3.1 15.8 0.0

- 0.1 Selway

- Bitterroot
Wilderness MT 2.3 16.8 2.3 16.8 0.0 0.0 Sequoia NP CA 7.6 21.5 7.6 21.5 0.0 0.0

### 29 Class I Area (IMPROVE Site) State [A]

2014
Baseline Visibility

20% Best Days (dv) [B]

2014
Baseline Visibility

20%
Worst Days ( dv ) [C]

2014 TR +

BART

Elsewhere Case Visibility
20% Best Days (dv) [D]

2014 TR +

BART

Elsewhere Case Visibility
20% Worst Days (dv) No Degradati

on Test 20% Best

Days =[C]

– [A]* No Degradat
ion Test

20%
Worst Days =[D]

– [B]*

Sierra Ancha
Wilderness AZ 5.1 14.0 5.0 14.0

- 0.1 0.0
South Warner
Wilderness CA 2.9 13.5 2.9 13.5 0.0 0.0 Strawberry Mountain
Wilderness OR 3.5 16.9 3.4 16.9 0.0 0.0* Superstition
Wilderness AZ 5.5 13.5 5.5 13.4 0.0

- 0.1 Sycamore Canyon
Wilderness AZ 4.8 15.0 4.8 14.9 0.0

- 0.1
Teton Wilderness WY 2.0 10.9 2.0 10.9 0.0 0.0
Three Sisters
Wilderness OR 2.6 15.4 2.6 15.3 0.0 0.0
Thousand Lakes
Wilderness CA 2.3 13.2 2.3 13.2 0.0 0.0
Ventana Wilderness CA 7.8 16.5 7.8 16.5 0.0 0.0
Mount Adams
Wilderness WA 1.5 11.9 1.5 11.9 0.0*

- 0.1
Yellowstone NP WY 2.0 10.9 2.0 10.9 0.0 0.0
Yosemite NP CA 3.1 16.2 3.1 16.2 0.0 0.0

Note s : Values in the “ No Degradation T est” columns are derived by subtracting values in appropriate columns before those have been rounded to the nearest 0.1 dv, and then rounding the result. Thus apparent discrepancies are due to rounding. Negative numbers indicate visibility improvement.

* The result at these Class I areas was a degradation of less than 0.05 deciviews, which when rounded equals 0.0. # The default visibility test at these areas resulted in visibility degradation

. See discussion below and Appendix B for more information on why we do not believe that visibility degradation will actually occur in these areas

.



### The modeling results show that the “Transport Rule + BART

- elsewhere” alternative passed this first prong in the Transport Rule re gion by not causing visibility degradation at any of the 60 affected Class I areas in the eastern Transport Rule 12km modeling domain ( i.e.

, when using the first approach to identifying affected areas), on either the 20 percent best or the 20
percent worst days

. 25

25 Two Class I areas had degradation of < 0.05 dv on the 20% best days and are denoted in the table with a “*”. These values were rounded to zero and are considered to be no degradation. 

### In the national region ( i.e.

, when using the second approach to identifying affected areas), the “Transport Rule + BART

- elsewhere” alternative was also predicted to not cause visibility degradation at any affected Class I area on either the 20 perc ent best of the 20 percent worst days, with a few exceptions. The exceptions were predicted avera ge degradations

### 30 of 0.23, 0.23, and 0.26 deciviews, respectively, at Pine Mountain Wilderness, Arizona, Mazatzal
Wilderness, Arizona 26 

### , and Saguaro National Park , Arizona, on the 20 percent worst days 27 

### and a predicted degradation of 0.05 deciviews on the 20 percent best days at Bryce Canyon National

Park in Utah. 28 

### Table 3

- 4 shows the visibility results (with two significant digits) at these four

Class I areas for both the “Transport Rule + BART

- elsewhere” and the “Nationwide BART”

scenario.

Table 3

- 4. Class I areas with predicted visibility degradation using the default visibility

calculations

Class I Area
Name IMPROVE
ID Representative
Site State TR+BART

elsewhere 20% Best days TR+BART

elsewhere 20% Worst days Nationwide
BART 20% Best Days Nationwide
BART 20% Worst Days Bryce Canyon
NP BRCA BRCA1 UT 0.05

- 0.08 0.06

- 0.10
Mazatzal
Wilderness MAZA IKBA1 AZ

- 0.02 0.23

- 0.02 0.23
Pine Mountain
Wilderness PIMO IKBA1 AZ

- 0.02 0.23

- 0.02 0.23

Saguaro NM SAGU SAGU1 AZ

- 0.24 0.26

- 0.19

- 0.09



### The fact that unexpected degradations at some western Class I areas were predicted for the “Nationwide BART” scenario as well as the “Transport Rule + BART

- elsewhere” scenario led us to investigate the CAMx modeling output in more detail. Based on that in vestigation, we consider the visibility projections for the western portion of the national modeling domain that indicate potential degradation in four western Class I areas under the “Transport Rule + BART

elsewhere” scenario compared to the “Base Case” s cenario to be anomalous results that do not indicate the true effects that the “Transport Rule + BART

- elsewhere” scenario (or the “Nationwide BART” scenario) will have on visibility in these areas.

All four of the Class I areas are located in the western portion of the 36km modeling

domain (outside of the 12km modeling domain)

. In the CAMx output for the grid cells in the vicinity of these four Class I areas, we observed that modeled concentrations of nitrate were very

low on most of the 20 percent worst days (and 20 percent best days at Bryce Canyon) in all of

26 While not part of the two

- pronged test, we also compared the baseline sc enario to the “Nationwide BART” scenario. The analysis of the national region under the “Nationwide BART” control scenario also projected a degradation of 0.23 deciviews on the 20 percent worst days at Pine Mountain Wilderness and Mazatzal Wilderness

, the same as the “Transport Rule + BART

- elsewhere” result.

27 The results for Pine Mountain and Mazatzal were the same because they are both represented by the same IMPROVE monitoring site (Ike’s Backbone, IKBA).

28 Changes in visibility were rounded to the nearest 0.1 deciviews. Therefore, any changes that were less
than 0 .05 were rounded down and treated as zero. Any changes that were 0.05 or greater were rounded up and treated as potential degradation.

### 31 the modeling scenarios, including the 2005 and 2014 base cases as well as the “Transport Rule +

BART

- elsewhere” and “Nationwide BART” case s

. Notably, the 2005 base case modeled

concentrations were generally a small fraction of monitored ambient nitrate concentrations at the

IMPROVE sites for the four Class I areas. In the cases where degradation was calculated, a very

small increase in modeled nitrate was observed on several of the worst or best mo deled days. This lead to a relatively large modeled percent increase in nitrate. Since the modeled visibility test is based on relative changes in PM species, the very small increase in nitrate has a relatively large impact on the final results.

Furt her examination of the days when these nitrate increases occur reveals a seemingly random pattern of very small increases and decreases that appear unrelated to EGU emissions changes. This nitrate modeling issue appears similar to a previously noted nitra te chemistry stability issue when modeled concentrations are very small and relative humidity is very low. 29


### Thus, we conclude that these positive and negative differences between very low nitrate concentrations are a modeling artifact attributable to the ISORROPIA nitrate mechanism in CAMx for the conditions that apply in this geographic area on these days, and are not reasonable predictors of the true relative effects on visibility of the emission control scenarios.

To further analyze the cause of the v isibility degradation, we performed an analysis to illustrate how sensitive the predictions of degradation are to highly variable results on particular days . For each of these four Class I areas, we removed one day of the 20 percent worst or best days wit h the largest increase in modeled nitrate concentration at from the calculation of 2014 visibility in the “ Transport Rule + BART

- elsewhere” control case. When the single day is
removed, the predicted visibility degradations no longer occur.

Another poss ible method to address this modeling issue is to set a minimum concentration threshold for use in calculating RRFs for all PM species. Under this approach if the average concentration across all best or worst days at each site is below the minimum

threshol d, then the RRF would be set to 1.0. If a minimum threshold of 0.01 ug/m 3 

### is used, the degradation no long er occurs at any Class I area. Based on this information, t he EPA is considering whether to implement a minimum threshold concentration as part of the Regional

Haze c alculations. The minimum threshold would be built into the MATS software used to post

process photochemical output s

. These possible revisions are aimed at avoiding potentially misleading results in situations such as the one observed near these W estern Class I areas.

Based on these detailed analyses, w e are confident that no degradation in the four western

29 Tong 2005, Numerical instability in the Community Multiscale Air Quality Model and its impacts on aerosol and ozone simulations, available at: http://www.princeton.edu/~mauzer al/papers/CMAQ_instability%20submission.pdf and Bhave 2004, CMAQ Aerosol Module Development: Recent Enhancements and Future Plans, available at:
htt p://www.cmascenter.org/conference/2004/abstracts/Model%20Development/bhave_abstract.pdf

### 32 Class I areas will result from implementation of the Transport Rule trading program in the

Eastern U.S. (or from BART). Consequently, we are proposing that the “Transport Rule +

BART

- elsewhere” control scenario passes the first prong of the visibility test considering affected Class I areas located in both the Transport Rule region (first approach) and the national region (second approac h). Additional d etails on the analysis of this issue, including the sensitivity analyses where we removed individual days and set a minimum concentration threshold for the RRF calculation can be found in Appendix B.

3.6.2 Better than BART Test

- 2 nd 

### Pr ong

The second prong of the Better than BART test assesses whether the “Transport Rule +

BART

- elsewhere” scenario results in greater average visibility improvement at affected Class I areas compared to the “Nationwide BART” scenario. To determine if “Tran sport Rule + BART

elsewhere” achieved greater average visibility improvement, we compared the visibility impacts of “Transport Rule + BART

- elsewhere” at the Class I areas to visibility impacts predicted at these same areas after implementation of “Nationwi de BART”.

In the Transport Rule region (first approach) and the national region (second approach), the average visibility improvement should be larger under the “ Transport Rule + BART

elsewhere ” scenario compared to the “ nationwide BART ” scenario

. Table 3

- 5 shows the detailed

results of the 2 nd 

### prong analysis. In order to provide detailed information the modeled visibility change is shown individua lly for all 140 Class I areas. However, u nder the greater improvement test, it is acceptable if some Class I areas show greater improvement under the nationwide BART case, as long as the average improvement under the “ Transport+ BART

- elsewhere ” case is larger.

### 33 Table 3

- 5

- Projected v isibility for the 201 4 b ase case and the visibility change in 2014 for the

“ Transport Rule+ BART

- elsewhere ” and the “ nationwide BART ” scenarios on the 20% best and

w orst days at 1 40 I MPROVE Sites (including the average change for 60 and 140 area s)

.

Class I Areas (IMPROVE Site) State 2014
Base Case Visibility

20% Best Days (dv) 2014 Base
Case Visibility

20%
Worst Days (dv) TR

– 2014
Base Case
20% Best

Days TR

– 2014
Base Case

20%
Worst Days BART

– 2014 Base

Case
20% Best

Days BART

– 2014
Base Case
20%
Worst Days

Acadia NP ME 8.0 20.1 0.0

- 1.1 0.0

- 0.8
Badlands NP SD 6.3 16.0

- 0.1

- 0.6

- 0.1

- 0.7
Bandelier NM NM 4.2 11.1

- 0.1

- 0.3

- 0.1

- 0.4 Big Bend NP TX 5.4 16.3

- 0.2

- 1.1

- 0.2

- 1.0 Black Canyon of the
Gunnison NM CO 2.3 9.5

- 0.1

- 0.1

- 0.1

- 0.1 Bosque del Apache NM 5.6 13.0

- 0.1

- 0.6

- 0.1

- 0.6 Boundary Waters
Canoe Area MN 5.8 18.8

- 0.1

- 1.2

- 0.1

- 1.0 Brigantine NJ 13.2 25.4

- 0.4

- 2.5

- 0.2

- 1.6 Caney Creek
Wilderness AR 11.3 24.4

- 0.4

- 3.2

- 0.6

- 2.2
Carlsbad Caverns NP TX 5.2 15.5

- 0.1

- 0.9

- 0.1

- 0.8
Cohutta Wilderness GA 12.9 26.6

- 0.8

- 3.8

- 0.5

- 2.3 Dolly Sods
Wilderness WV 10.3 27.1

- 1.1

- 5.7

- 0.8

- 3.2 Eagles Nest
Wilderness CO 0.4 8.3 0.0

- 0.1 0.0

- 0.1 Everglades NP FL 11.5 20.4

- 0.3

- 1.0

- 0.3

- 0.7 Flat Tops Wilderness CO 0.4 8.3 0.0

- 0.1 0.0

- 0.1
Great Gulf
Wilderness NH 6.7 19.2

- 0.1

- 1.8

- 0.1

- 1.3
Great Sand Dunes
NM CO 3.5 11.3

- 0.1

- 0.2

- 0.1

- 0.2 Great Smoky
Mountains NP TN 12.2 27.0

- 0.8

- 3.7

- 0.7

- 2.0 Guadalupe
Mountains NP TX 5.2 15.5

- 0.1

- 0.9

- 0.1

- 0.8
Hercules

- Glades
Wilderness MO 12.2 25.2

- 0.6

- 2.5

- 0.8

- 1.7 Isle Royale NP MI 6.4 19.9

- 0.1

- 1.0

- 0.2

- 0.9
James River Face
Wilderness VA 12.9 25.8

- 0.9

- 4.2

- 0.5

- 2.1 Joyce

- Kilmer

Slickrock Wilderness TN 12.2 27.0

- 0.8

- 3.7

- 0.7

- 2.0

### 34 Class I Areas (IMPROVE Site) State 2014
Base Case Visibility

20% Best Days (dv) 2014 Base
Case Visibility

20%
Worst Days (dv) TR

– 2014
Base Case
20% Best

Days TR

– 2014
Base Case

20%
Worst Days BART

– 2014 Base

Case
20% Best

Days BART

– 2014
Base Case
20%
Worst Days

La Garita Wilderness CO 2.3 9.5

- 0.1

- 0.1

- 0.1

- 0.1 Linville Gorge
Wilderness NC 10.3 26.0

- 0.7

- 4.3

- 0.5

- 2.3
Lostwood ND 7.9 18.8

- 0.1

- 0.5

- 0.1

- 0.5 Lye Brook
Wilderness VT 5.5 20.7

- 0.1

- 2.6

- 0.1

- 1.7
Maroon Bells

Snowmass
Wilderness CO 0.4 8.3 0.0

- 0.1 0.0

- 0.1
Mammoth Cave NP KY 15.3 29.5

- 1.2

- 5.1

- 0.9

- 2.8
Medicine Lake MT 6.5 17.7 0.0

- 0.3 0.0

- 0.3
Mesa Verde NP CO 3.2 11.4

- 0.1

- 0.3

- 0.1

- 0.3
Moosehorn ME 8.4 19.0 0.0*

- 1.0 0.0*

- 0.8
Mount Zirkel
Wilderness CO 1.0 9.2 0.0

- 0.1 0.0

- 0.1
North Absaroka
Wilderness WY 1.5 11.1 0.0 0.0 0.0 0.0
Okefenokee GA 13.9 24.1

- 0.9

- 2.5

- 0.7

- 1.7
Otter Creek
Wilderness WV 10.3 27.1

- 1.1

- 5.7

- 0.8

- 3.2
Pecos Wilderness NM 1.0 9.0

- 0.1

- 0.2

- 0.1

- 0.2 Presidential Range

Dry River
Wilderness NH 6.7 19.2

- 0.1

- 1.8

- 0.1

- 1.3
Rawah Wilderness CO 1.0 9.2 0.0

- 0.1 0.0

- 0.1
Roosevelt Campobello
International Park ME 8.4 19.0 0.0*

- 1.0 0.0*

- 0.8 Cape Romain SC 13.6 24.0

- 0.7

- 2.9

- 0.4

- 1.9 Rocky Mountain NP CO 2.0 12.2 0.0

- 0.1 0.0

- 0.1
Salt Creek NM 7.3 17.1

- 0.1

- 0.7

- 0.2

- 0.7
San Pedro Parks
Wilderness NM 1.2 9.9

- 0.2

- 0.3

- 0.2

- 0.4 Seney MI 6.9 23.3

- 0.1

- 1.6 0.0

- 1.5
Shenandoah NP VA 9.0 26.2

- 0.8

- 5.0

- 0.6

- 3.0 Shining Rock
Wilderness NC 6.3 24.8

- 0.7

- 3.8

- 0.5

- 2.1 Sipsey Wilderness AL 14.5 26.5

- 0.9

- 3.7

- 0.9

- 2.1
Theodore Roosevelt
NP ND 6.8 17.0 0.0

- 0.3 0.0

- 0.4

### 35 Class I Areas (IMPROVE Site) State 2014
Base Case Visibility

20% Best Days (dv) 2014 Base
Case Visibility

20%
Worst Days (dv) TR

– 2014
Base Case
20% Best

Days TR

– 2014
Base Case

20%
Worst Days BART

– 2014 Base

Case
20% Best

Days BART

– 2014
Base Case
20%
Worst Days

UL Bend MT 4.2 15.2 0.0

- 0.1 0.0

- 0.1 Upper Buffalo
Wilderness AR 11.3 24.7

- 0.5

- 2.5

- 0.6

- 1.4 Voyageurs NP MN 6.6 18.4

- 0.1

- 1.0

- 0.1

- 0.8
Washakie Wilderness WY 1.5 11.1 0.0 0.0 0.0 0.0
West Elk Wilderness CO 0.4 8.3 0.0

- 0.1 0.0

- 0.1
Weminuche
Wilderness CO 2.3 9.5

- 0.1

- 0.1

- 0.1

- 0.1
White Mountain
Wilderness NM 3.1 12.3

- 0.1

- 0.6

- 0.2

- 0.5
Wheeler Peak
Wilderness NM 1.0 9.0

- 0.1

- 0.2

- 0.1

- 0.2
Wind Cave NP SD 4.6 15.1 0.0

- 0.3

- 0.1

- 0.4
Wichita Mountains OK 9.1 21.7

- 0.2

- 1.6

- 0.2

- 1.2
Wolf Island GA 13.9 24.1

- 0.9

- 2.5

- 0.7

- 1.7

Eastern Class I Areas Average (60 Areas) - 0.3

- 1.6

- 0.2

- 1.0

Agua Tibia
Wilderness CA 7.9 20.2 0.0 0.0 0.0 0.0 Alpine Lake
Wilderness WA 4.6 15.8 0.0* 0.0 0.0* 0.0
Anaconda

- Pintler
Wilderness MT 2.3 16.8 0.0 0.0 0.0 0.0
Ansel Adams
Wilderness (Minarets) CA 1.7 14.6 0.0 0.0 0.0 0.0
Arches NP UT 2.6 9.8

- 0.1

- 0.2

- 0.1

- 0.2 Mount Baldy
Wilderness AZ 2.5 10.9

- 0.1 0.0*

- 0.1

- 0.2
Bob Marshall
Wilderness MT 3.1 15.8 0.0

- 0.1 0.0

- 0.1 Bryce Canyon NP UT 2.4 10.8 0.1#

- 0.1 0.1#

- 0.1 Bridger Wilderness WY 1.6 10.4 0.0

- 0.1 0.0

- 0.1
Cabinet Mountains
Wilderness MT 3.0 14.0 0.0*

- 0.1 0.0*

- 0.1 Canyonlands NP UT 2.6 9.8

- 0.1

- 0.2

- 0.1

- 0.2 Capitol Reef NP UT 2.9 10.3 0.0

- 0.2 0.0

- 0.2
Caribou Wilderness CA 2.3 13.2 0.0 0.0 0.0 0.0

### 36 Class I Areas (IMPROVE Site) State 2014
Base Case Visibility

20% Best Days (dv) 2014 Base
Case Visibility

20%
Worst Days (dv) TR

– 2014
Base Case
20% Best

Days TR

– 2014
Base Case

20%
Worst Days BART

– 2014 Base

Case
20% Best

Days BART

– 2014
Base Case
20%
Worst Days

Chiricahua NM AZ 4.4 12.4

- 0.1

- 0.1

- 0.1

- 0.2
Chiricahua
Wilderness AZ 4.4 12.4

- 0.1

- 0.1

- 0.1

- 0.2
Crater Lake NP OR 1.5 12.7 0.0 0.0 0.0 0.0
Craters of the Moon
NM ID 3.5 13.7 0.0 0.0 0.0 0.0 Cucamonga
Wilderness CA 3.9 16.4 0.0 0.0 0.0 0.0
Desolation
Wilderness CA 2.1 12.4 0.0 0.0 0.0 0.0
Diamond Peak
Wilderness OR 1.5 12.7 0.0 0.0 0.0 0.0 Eagle Cap
Wilderness OR 3.5 16.9 0.0 0.0* 0.0 0.0* Emigrant Wilderness CA 3.1 16.2 0.0 0.0 0.0 0.0 Fitzpatrick
Wilderness WY 1.6 10.4 0.0

- 0.1 0.0

- 0.1
Galiuro Wilderness AZ 4.4 12.4

- 0.1

- 0.1

- 0.1

- 0.2
Gates of the
Mountains
Wilderness MT 1.2 11.6 0.0

- 0.1 0.0* 0.0
Gearhart Mountain
Wilderness OR 1.5 12.7 0.0 0.0 0.0 0.0
Gila Wilderness NM 2.9 13.0 0.0

- 0.2 0.0

- 0.3
Glacier NP MT 6.8 19.1 0.0 0.0 0.0 0.0
Glacier Peak
Wilderness WA 2.9 12.6 0.0 0.0 0.0 0.0
Goat Rocks
Wilderness WA 1.5 11.9 0.0*

- 0.1 0.0*

- 0.1 Grand Canyon NP AZ 1.9 11.0 0.0*

- 0.1 0.0

- 0.1
Grand Teton NP WY 2.0 10.9 0.0 0.0 0.0 0.0 Hells Canyon
Wilderness OR 4.8 18.3 0.0 0.0 0.0 0.0
Hoover Wilderness CA 1.3 11.2 0.0 0.0 0.0 0.0 Jarbidge Wilderness NV 2.3 12.0 0.0 0.0 0.0 0.0
John Muir
Wilderness CA 1.7 14.6 0.0 0.0 0.0 0.0
Joshua Tree NM CA 5.5 17.3 0.0 0.0 0.1# 0.0
Kaiser Wilderness CA 1.7 14.6 0.0 0.0 0.0 0.0 Kalmiopsis OR 6.1 16.1 0.0 0.0 0.0

- 0.1

### 37 Class I Areas (IMPROVE Site) State 2014
Base Case Visibility

20% Best Days (dv) 2014 Base
Case Visibility

20%
Worst Days (dv) TR

– 2014
Base Case
20% Best

Days TR

– 2014
Base Case

20%
Worst Days BART

– 2014 Base

Case
20% Best

Days BART

– 2014
Base Case
20%
Worst Days

Wilderness Kings Canyon NP CA 7.6 21.5 0.0 0.0 0.0 0.0
Lava Beds NM CA 2.9 13.5 0.0 0.0 0.0 0.0
Lassen Volcanic NP CA 2.3 13.2 0.0 0.0 0.0 0.0
Mazatzal Wilderness AZ 5.0 12.9 0.0 0.2# 0.0 0.2#
Mission Mountains
Wilderness MT 3.1 15.8 0.0

- 0.1 0.0

- 0.1
Mount Hood
Wilderness OR 1.6 13.9 0.0

- 0.1 0.0

- 0.1
Mount Jefferson
Wilderness OR 2.6 15.4 0.0 0.0 0.0 0.0
Mokelumne
Wilderness CA 2.1 12.4 0.0 0.0 0.0 0.0
Mountain Lakes
Wilderness OR 1.5 12.7 0.0 0.0 0.0 0.0
Mount Rainier NP WA 4.8 16.0 0.0

- 0.1 0.0

- 0.1 Mount Washington
Wilderness OR 2.6 15.4 0.0 0.0 0.0 0.0
North Cascades NP WA 2.9 12.6 0.0 0.0 0.0 0.0 Olympic NP WA 5.4 15.1 0.0 0.0 0.0 0.0 Pasayten Wilderness WA 2.4 14.8 0.0

- 0.1 0.0

- 0.1
Petrified Forest NP AZ 4.4 13.4 0.0 0.0

- 0.1

- 0.2
Pine Mountain
Wilderness AZ 5.0 12.9 0.0 0.2# 0.0 0.2#
Pinnacles NM CA 7.8 16.5 0.0 0.0 0.0 0.0 Point Reyes NS CA 9.0 21.2 0.0 0.0 0.0 0.0
San Rafael
Wilderness CA 5.3 18.2 0.0 0.0 0.0 0.0
Red Rock Lakes WY 2.0 10.9 0.0 0.0 0.0 0.0
Redwood NP CA 5.8 18.0 0.0 0.0 0.0 0.0
San Gabriel
Wilderness CA 3.9 16.4 0.0 0.0 0.0 0.0 San Gorgonio
Wilderness CA 4.6 19.7 0.0 0.0 0.0 0.0 Saguaro NM AZ 6.5 13.4

- 0.2 0.3#

- 0.2

- 0.1
San Jacinto
Wilderness CA 4.6 19.7 0.0 0.0 0.0 0.0
Sawtooth Wilderness ID 3.6 14.8 0.0 0.0 0.0 0.0 Scapegoat
Wilderness MT 3.1 15.8 0.0

- 0.1 0.0

- 0.1

### 38 Class I Areas (IMPROVE Site) State 2014
Base Case Visibility

20% Best Days (dv) 2014 Base
Case Visibility

20%
Worst Days (dv) TR

– 2014
Base Case
20% Best

Days TR

– 2014
Base Case

20%
Worst Days BART

– 2014 Base

Case
20% Best

Days BART

– 2014
Base Case
20%
Worst Days

Selway

- Bitterroot
Wilderness MT 2.3 16.8 0.0 0.0 0.0 0.0 Sequoia NP CA 7.6 21.5 0.0 0.0 0.0 0.0
Sierra Ancha
Wilderness AZ 5.1 14.0

- 0.1 0.0 0.0 0.0
South Warner
Wilderness CA 2.9 13.5 0.0 0.0 0.0 0.0 Strawberry Mountain
Wilderness OR 3.5 16.9 0.0 0.0* 0.0 0.0* Superstition
Wilderness AZ 5.5 13.5 0.0

- 0.1 0.0

- 0.1 Sycamore Canyon
Wilderness AZ 4.8 15.0 0.0

- 0.1 0.0

- 0.1
Teton Wilderness WY 2.0 10.9 0.0 0.0 0.0 0.0
Three Sisters
Wilderness OR 2.6 15.4 0.0 0.0 0.0 0.0
Thousand Lakes
Wilderness CA 2.3 13.2 0.0 0.0 0.0 0.0
Ventana Wilderness CA 7.8 16.5 0.0 0.0 0.0 0.0
Mount Adams
Wilderness WA 1.5 11.9 0.0*

- 0.1 0.0*

- 0.1
Yellowstone NP WY 2.0 10.9 0.0 0.0 0.0 0.0
Yosemite NP CA 3.1 16.2 0.0 0.0 0.0 0.0 All Class I Areas Average (140 Areas) - 0.1

- 0.7

- 0.1

- 0.5

Note s : Negative numbers indicate visibility improvement.

* The result at these Class I areas was a degradation of less than 0.05 deciviews, which when rounded equals 0.0. # The default visibility test at these areas resulted in visibility degradation. See App endix B for more information on why we do not believe that visibility degradation will actually occur in these areas

. The values shown in this table

were used (before rounding) to calculate the eastern and national averages.



### A summary of the results of the second prong of the test for the Transport Rule and national regions under each control scenario is shown below in Table 3

- 6

.

### 39 Table 3

- 6

. Summary of average visibility results for Eastern and nationwide areas

. Transpor t Rule

– 2014
Base Case 20% Best Days Transport Rule

– 2014 Base
Case
20% Worst Days Nationwide
BART

– 2014

Base Case
20% Best

Days Nationwide
BART

– 2014

Base Case
20% Worst Days

Eastern Class I Areas Average (60 Areas) - 0.3

- 1.6

- 0.2

- 1.0

All Class I Areas Average (140 Areas) - 0.1

- 0.7

- 0.1

- 0.5



### For the 60 Eastern Class I areas analyzed, the average visibility improvement from 2014 baseline (on the 20 percent worst days) expected as a result of the Transport Rule + BART

elsewhere is 1.6 deciviews (dv), and the average degree of improvement from 2014 baseline predicted for nationwide BART is 1.0 dv. The average visibility improvement from 2014 baseline on the 20 percent best days expected as a result of the Transport Rule + BART

elsewhere is 0.3 deciviews (dv), and the average degree of improvement from 2014 baseline predicted for nationwide BART is 0.2 dv. Therefore, the Transport Rule makes substantially more improvement than nationwide BART in the East.

Similarly, for Class I Areas na tionwide, the visibility modeling shows that for the 140 class I areas evaluated, the average visibility improvement, on the 20 percent worst days in 2014 was 0.7 dv under the Transport Rule, and 0.5 dv under the nationwide BART approach. The average visi bility improvement, on the 20 percent best days in 2014 was 0.1 dv for “ Transport

Rule + BART

- elsewhere” and 0.1 dv under “ nationwide BART ” 30



### .

Based on these results, the Transport Rule scenario passes the second prong of the proposed better

- than

- BART test based on the fact that, on average, in both the Eastern Class I areas and nationally, visibility improvement is greater under the Transport Rule + BART

elsewhere scenario compared to nationwide BART on the 20% best and 20% worst visibility days.

3.6 .3 Summary of Better than BART Test

T he Transport Rule scenario passes the first prong of the two

- pronged better

- than

- BART test by not causing degradation of visibility at any Class I area on either the 20% best or 20%

30 B efore rounding to the tenths digit, “ Transport Rule +BART

- elsewhwere” has a visibility improvement of 0.13 dv compared to 0.11 dv for “ nationwide BART ”

.

### 40 worst visibility days. The Transpor t Rule also passes the second prong of the better

- than

- BART test based on the expectation that :(a) for the Eastern Class I areas visibility improvement is greater on average for the both the 20% best and 20% worst days under the Transport Rule compared to nationwide BART, and (b) for all Class I areas nationally, visibility improvement is essentially equal on the best 20% days, and greater on the worst 20% days. 31

31 Under the Regional Haze Rule, reasonable progress goals are defined in terms of improvement on the worst 20% days, and no degradation on the 20% best days. The proposed better

- than

- BART test does not specify whether each prong should apply on both best and worst days. For purposes of this analysis, as previously noted, we have considered both the best days and the worst days under both the no

- degradation prong and the overall

- improvement prong, without determining that all subsequent better

- than

- BART demonstratio ns must do so. Similarly, the fact that we have considered all Class I areas nationwide in part of our analysis does not imply that any future better

- than

BART demonstration must necessarily consider all Class I areas in the nation to be “impacted” by the particular
BART

- alternative under consideration.

### 41 

## Appendix A

EGUs that were assumed to BART

- subject for the purpose of this anal ysis

State Name Plant Name Unit ID Capacity (MW) On Line
Year

Alabama Barry 4 362 1969

Alabama Barry 5 750 1971

Alabama Charles R Lowman 1 86.0 1969

Alabama Charles R Lowman 2 238 1979

Alabama Charles R Lowman 3 238 1980

Alabama Colbert 5 459 1965

Alabama E C Gaston 4 256 1962

Alabama E C Gaston 5 861 1974

Alabama Gorgas 10 690 1972

Alabama Greene County 1 254 1965

Alabama Greene County 2 243 1966

Alabama James H Miller Jr 2 687 1985

Alabama James H Miller Jr 1 684 1978

Alabama Widows Creek 8 464 1965

Arizona Apache Station 2 175 1979

Arizona Apache Station 3 175 1979

Arizona Cholla 2 275 1978

Arizona Cholla 3 271 1980

Arizona Cholla 4 380 1981

Arizona Coronado U1B 395 1979

Arizona Coronado U2B 390 1980

Arizona H Wilson Sundt Generating Station 4 156 1967

Arizona Navajo 1 750 1974

Arizona Navajo 2 750 1975

Arizona Navajo 3 750 1976

Arkansas Flint Creek 1 528 1978

Arkansas White Bluff 1 815 1980

Arkansas White Bluff 2 825 1981

Colorado Cherokee 3 165 1962

Colorado Cherokee 4 388 1968

Colorado Comanche 1 366 1973

Colorado Comanche 2 370 1975

Colorado Craig C1 428 1980

Colorado Craig C2 428 1979

Colorado Hayden H1 205 1965

Colorado Hayden H2 300 1976

### 42 State Name Plant Name Unit ID Capacity (MW) On Line
Year

Colorado Martin Drake 5 46.0 1962

Colorado Martin Drake 6 77.0 1968

Colorado Martin Drake 7 131 1974

Colorado Pawnee 1 505 1981

Colorado Ray D Nixon 1 208 1980

Colorado Valmont 5 199 1964

Connecticut Bridgeport Station BHB3 372 1968

Delaware Edge Moor 4 174 1966

Delaware Indian River Generating Station 3 153 1970

Delaware Indian River Generating Station 4 405 1980

Florida Big Bend BB01 391 1970

Florida Big Bend BB02 391 1973

Florida Big Bend BB03 364 1976

Florida Crist 6 302 1970

Florida Crist 7 472 1973

Florida Crystal River 1 379 1966

Florida Crystal River 2 491 1969

Florida Crystal River 4 722 1982

Florida Crystal River 5 721 1984

Florida Deerhaven Generating Station B2 228 1981

Florida Lansing Smith 1 162 1965

Florida Lansing Smith 2 195 1967 Georgia Bowen 1BLR 713 1971 Georgia Bowen 2BLR 718 1972 Georgia Bowen 3BLR 902 1974 Georgia Bowen 4BLR 929 1975 Georgia Hammond 4 510 1970 Georgia Harllee Branch 1 266 1965 Georgia Harllee Branch 2 325 1967 Georgia Harllee Branch 3 509 1968 Georgia Harllee Branch 4 507 1969 Georgia Jack McDonough MB1 258 1963 Georgia Jack McDonough MB2 259 1964 Georgia Kraft 3 102 1965 Georgia McIntosh 1 157 1979 Georgia Scherer 1 837 1982 Georgia Scherer 2 843 1984 Georgia Wansley 1 891 1976 Georgia Wansley 2 892 1978 Georgia Yates Y6BR 352 1974

### 43 State Name Plant Name Unit ID Capacity (MW) On Line
Year Georgia Yates Y7BR 355 1974

Illinois Baldwin Energy Complex 1 624 1970

Illinois Baldwin Energy Complex 2 629 1973

Illinois Baldwin Energy Complex 3 629 1975

Illinois Coffeen 01 340 1965

Illinois Coffeen 02 560 1972

Illinois Dallman 31 86.0 1968

Illinois Dallman 32 87.0 1972

Illinois Dallman 33 199 1978

Illinois Duck Creek 1 335 1976

Illinois E D Edwards 2 273 1968

Illinois E D Edwards 3 364 1972

Illinois Havana 9 487 1978

Illinois Joliet 29 71 259 1965

Illinois Joliet 29 72 259 1965

Illinois Joliet 29 81 259 1965

Illinois Joliet 29 82 259 1965

Illinois Kincaid Generation LLC 1 584 1967

Illinois Kincaid Generation LLC 2 584 1968

Illinois Marion 4 170 1978

Illinois Marion 123 120 2003

Illinois Newton 1 557 1977

Illinois Newton 2 569 1982

Illinois Pearl Station 1A 22.0 1967

Illinois Powerton 51 385 1972

Illinois Powerton 52 385 1972

Illinois Powerton 61 385 1975

Illinois Powerton 62 385 1975

Illinois Waukegan 8 361 1962

Illinois Will County 4 510 1963

Illinois Wood River 5 383 1964

Indiana A B Brown 1 245 1979

Indiana Bailly 7 160 1962

Indiana Bailly 8 320 1968

Indiana Cayuga 1 479 1970

Indiana Cayuga 2 473 1972

Indiana Crawfordsville 6 12.6 1965

Indiana Dean H Mitchell 11 110 1970

Indiana F B Culley 2 90.0 1966

Indiana F B Culley 3 270 1973

### 44 State Name Plant Name Unit ID Capacity (MW) On Line
Year

Indiana Frank E Ratts 1SG1 122 1970

Indiana Frank E Ratts 2SG1 121 1970

Indiana Gibson 1 630 1975

Indiana Gibson 2 628 1975

Indiana Gibson 3 628 1978

Indiana Gibson 4 622 1979

Indiana Harding Street 70 435 1973

Indiana Jasper 2 1 14.0 1968

Indiana Logansport 6 22.0 1964

Indiana Merom 1SG1 507 1983

Indiana Merom 2SG1 493 1982

Indiana Michigan City 12 469 1974

Indiana Petersburg 1 232 1967

Indiana Petersburg 2 435 1969

Indiana Petersburg 3 540 1977

Indiana R M Schahfer 14 431 1976

Indiana R M Schahfer 15 472 1979

Indiana State Line 4 303 1962

Indiana Tanners Creek U4 500 1964

Indiana Wabash River 6 318 1968

Indiana Warrick 2 136 1964

Indiana Warrick 3 136 1965

Indiana Warrick 4 300 1970

Indiana Whitewater Valley 2 62.8 1973

Iowa Ames Electric Services Power Plant 7 33.0 1968

Iowa Burlington 1 209 1968

Iowa Fair Station 2 41.0 1967

Iowa George Neal North 1 135 1964

Iowa George Neal North 2 300 1972

Iowa George Neal North 3 515 1975

Iowa George Neal South 4 632 1979

Iowa Lansing 4 261 1977

Iowa Milton L Kapp 2 211 1967

Iowa Muscatine Plant #1 8 35.0 1969

Iowa Ottumwa 1 673 1981

Iowa Pella 6 15.0 1974

Iowa Pella 7 12.8 1964

Iowa Prairie Creek 4 125 1967

Iowa Streeter Station 6 18.9 1963

Iowa Streeter Station 7 35.8 1973

### 45 State Name Plant Name Unit ID Capacity (MW) On Line
Year

Iowa Walter Scott Jr. Energy Center 3 690 1978

Kansas Jeffrey Energy Center 1 730 1978

Kansas Jeffrey Energy Center 2 730 1980

Kansas La Cygne 1 724 1973

Kansas La Cygne 2 682 1977

Kansas Lawrence Energy Center 5 366 1971

Kansas Nearman Creek N1 229 1981

Kansas Quindaro 1 72.0 1965

Kansas Quindaro 2 111 1971

Kansas Tecumseh Energy Center 10 129 1962 Kentucky Big Sandy BSU1 260 1963 Kentucky Big Sandy BSU2 800 1969 Kentucky Cane Run 4 155 1962 Kentucky Cane Run 5 168 1966 Kentucky Cane Run 6 240 1969 Kentucky Cooper 1 116 1965 Kentucky Cooper 2 225 1969 Kentucky E W Brown 2 160 1963 Kentucky E W Brown 3 422 1971 Kentucky East Bend 2 600 1981 Kentucky Elmer Smith 1 132 1964 Kentucky Elmer Smith 2 261 1974 Kentucky Ghent 1 475 1973 Kentucky Ghent 2 469 1977 Kentucky Ghent 3 478 1981 Kentucky H L Spurlock 1 315 1977 Kentucky H L Spurlock 2 509 1981 Kentucky HMP&L Station Two Henderson H1 153 1973 Kentucky HMP&L Station Two Henderson H2 159 1974 Kentucky Kenneth C Coleman C1 150 1969 Kentucky Kenneth C Coleman C2 150 1970 Kentucky Kenneth C Coleman C3 155 1971 Kentucky Mill Creek 1 303 1972 Kentucky Mill Creek 2 301 1974 Kentucky Mill Creek 3 391 1978 Kentucky Mill Creek 4 477 1982 Kentucky Paradise 1 616 1963 Kentucky Paradise 2 602 1963 Kentucky Paradise 3 977 1970 Kentucky R D Green G1 231 1979

### 46 State Name Plant Name Unit ID Capacity (MW) On Line
Year Kentucky R D Green G2 233 1981 Kentucky Robert A Reid R1 65.0 1966

Louisiana Big Cajun 2 2B1 580 1981

Louisiana Big Cajun 2 2B1 580 1981

Louisiana R S Nelson 6 550 1982

Louisiana Rodemacher 2 523 1982 Maryland C P Crane 2 200 1963 Maryland Chalk Point LLC 1 341 1964 Maryland Chalk Point LLC 2 342 1965 Maryland Dickerson 3 182 1962 Maryland Herbert A Wagner 3 324 1966 Maryland Morgantown Generating Plant 1 624 1970 Maryland Morgantown Generating Plant 2 620 1971

Massachusetts Brayton Point 1 243 1963

Massachusetts Brayton Point 2 244 1964

Massachusetts Brayton Point 3 612 1969 Michigan Belle River 1 698 1984 Michigan Belle River 2 698 1985 Michigan Eckert Station 4 69.2 1964 Michigan Eckert Station 5 68.9 1968 Michigan Eckert Station 6 66.8 1970 Michigan Erickson Station 1 152 1973 Michigan Harbor Beach 1 103 1968 Michigan J H Campbell 1 260 1962 Michigan J H Campbell 2 355 1967 Michigan J H Campbell 3 825 1980 Michigan James De Young 4 20.5 1962 Michigan James De Young 5 27.0 1969 Michigan Monroe 1 770 1972 Michigan Monroe 2 785 1973 Michigan Monroe 3 795 1973 Michigan Monroe 4 775 1974 Michigan Presque Isle 5 88.0 1974 Michigan Presque Isle 6 88.0 1975 Michigan Presque Isle 7 85.0 1978 Michigan Presque Isle 8 85.0 1978 Michigan Presque Isle 9 85.0 1979 Michigan Shiras 2 19.5 1972 Michigan St Clair 7 440 1969 Michigan Trenton Channel 9A 536 1968

### 47 State Name Plant Name Unit ID Capacity (MW) On Line
Year

Minnesota Allen S King 1 610 1968

Minnesota Austin Northeast NEPP 29.3 1971

Minnesota Clay Boswell 3 351 1973

Minnesota Clay Boswell 4 525 1980

Minnesota Hibbing 1 10.2 1965

Minnesota Hibbing 2 10.2 1965

Minnesota Hibbing 3 10.2 1965

Minnesota Hoot Lake 3 84.0 1964

Minnesota Sherburne County 1 762 1976

Minnesota Sherburne County 2 752 1977

Minnesota Silver Bay Power BLR2 69.0 1963

Minnesota Silver Lake 3 24.3 1962

Minnesota Silver Lake 4 59.2 1969

Minnesota Taconite Harbor Energy Center 3 68.0 1967 Mississippi Henderson H3 17.9 1967 Mississippi Jack Watson 4 230 1968 Mississippi Jack Watson 5 476 1973 Mississippi R D Morrow 1 180 1978 Mississippi R D Morrow 2 180 1978 Mississippi Victor J Daniel Jr 1 514 1977 Mississippi Victor J Daniel Jr 2 514 1981

Missouri Asbury 1 213 1970

Missouri Blue Valley 3 51.0 1965

Missouri Iatan 1 651 1980

Missouri James River Power Station 4 56.0 1964

Missouri James River Power Station 5 97.0 1970

Missouri Labadie 1 597 1970

Missouri Labadie 2 594 1971

Missouri Labadie 3 612 1972

Missouri Labadie 4 612 1973

Missouri Lake Road 6 97.4 1967

Missouri Marshall 5 16.0 1967

Missouri Montrose 3 176 1964

Missouri New Madrid 1 580 1972

Missouri New Madrid 2 580 1977

Missouri Rush Island 1 604 1976

Missouri Rush Island 2 604 1977

Missouri Sibley 2 53.9 1962

Missouri Sibley 3 401 1969

Missouri Sikeston Power Station 1 233 1981

### 48 State Name Plant Name Unit ID Capacity (MW) On Line
Year

Missouri Sioux 1 497 1967

Missouri Sioux 2 497 1968

Missouri Southwest Power Station 1 178 1976

Missouri Thomas Hill MB1 175 1966

Missouri Thomas Hill MB2 275 1969

Montana Colstrip 1 307 1975

Montana Colstrip 2 307 1976

Montana J E Corette Plant 2 158 1968

Nebraska Gerald Gentleman 32 1 665 1979

Nebraska Lon Wright 7 20.0 1963

Nebraska Lon Wright 8 85.0 1976

Nebraska Nebraska City 1 646 1979

Nebraska North Omaha 4 138 1963

Nebraska North Omaha 5 224 1968

Nebraska Sheldon 1 105 1968

Nebraska Whelan Energy Center 1 77.0 1981

Nevada Reid Gardner 1 110 1965

Nevada Reid Gardner 2 110 1968

Nevada Reid Gardner 3 110 1976 New Hampshire Merrimack 2 320 1968
New Jersey PSEG Hudson Generating Station 2 608 1967

New Mexico Four Corners 1 170 1963

New Mexico Four Corners 2 170 1963

New Mexico Four Corners 3 220 1964

New Mexico Four Corners 4 760 1969

New Mexico Four Corners 5 760 1970

New Mexico San Juan 1 322 1976

New Mexico San Juan 2 320 1973

New Mexico San Juan 3 495 1979

New Mexico San Juan 4 506 1982

North Carolina Asheville 1 191 1964

North Carolina Asheville 2 185 1971

North Carolina Belews Creek 1 1115 1974

North Carolina Belews Creek 2 1115 1975

North Carolina Cliffside 5 550 1972

North Carolina L V Sutton 3 403 1972

32 Gerald Gentleman Unit 2 was inadvertently omitted from the BART inv entory. See Table 2

- 4 for information on
how this omission potentially affected total SO 2 emissions the “Nationwide BART” control scen ario

. Total NOx emissions would not have been impacted. Formatted: Superscript

Formatted: Superscript

Formatted: Subscript

Formatted: Superscript

### 49 State Name Plant Name Unit ID Capacity (MW) On Line
Year

North Carolina Lee 3 248 1962

North Carolina Marshall 1 378 1965

North Carolina Marshall 2 378 1966

North Carolina Marshall 3 657 1969

North Carolina Marshall 4 657 1970

North Carolina Roxboro 1 369 1966

North Carolina Roxboro 2 671 1968

North Carolina Roxboro 3A 353 1973

North Carolina Roxboro 3B 353 1973

North Carolina Roxboro 4A 349 1980

North Carolina Roxboro 4B 349 1980

North Dakota Coal Creek 1 554 1979

North Dakota Coal Creek 2 560 1981

North Dakota Leland Olds 1 221 1966

North Dakota Leland Olds 2 448 1975

North Dakota Milton R Young B1 250 1970

North Dakota Milton R Young B2 455 1977

North Dakota R M Heskett B2 75.5 1963

North Dakota Stanton 1 130 1967

Ohio Avon Lake 12 616 1970

Ohio Bay Shore 3 142 1963

Ohio Bay Shore 4 215 1968

Ohio Cardinal 1 600 1967

Ohio Cardinal 2 600 1967

Ohio Cardinal 3 630 1977

Ohio Conesville 3 165 1962

Ohio Conesville 4 780 1973

Ohio Conesville 5 375 1976

Ohio Conesville 6 375 1978

Ohio Dover 4 15.2 1968

Ohio Eastlake 5 597 1972

Ohio General James M Gavin 1 1310 1974

Ohio General James M Gavin 2 1300 1975

Ohio Hamilton 8 32.8 1964

Ohio Hamilton 9 51.0 1974

Ohio J M Stuart 1 597 1971

Ohio J M Stuart 2 597 1970

Ohio J M Stuart 3 597 1972

Ohio J M Stuart 4 597 1974

Ohio Lake Road 11 20.0 1967

### 50 State Name Plant Name Unit ID Capacity (MW) On Line
Year

Ohio Lake Shore 18 245 1962

Ohio Miami Fort 7 500 1975

Ohio Miami Fort 8 500 1978

Ohio Muskingum River 5 585 1968

Ohio Orrville 13 23.0 1971

Ohio Shelby Municipal Light Plant 1 12.0 1968

Ohio Shelby Municipal Light Plant 2 12.0 1968

Ohio St Marys 6 9.00 1967

Ohio W H Sammis 4 180 1962

Ohio W H Sammis 5 300 1967

Ohio W H Sammis 6 600 1969

Ohio W H Sammis 7 600 1971

Ohio Walter C Beckjord 5 238 1962

Ohio Walter C Beckjord 6 414 1969

Oklahoma Muskogee 4 511 1977

Oklahoma Muskogee 5 522 1978

Oklahoma Northeastern 3313 450 1979

Oklahoma Northeastern 3314 450 1980

Oklahoma Sooner 1 535 1979

Oklahoma Sooner 2 540 1980 Oregon Boardman 1SG 585 1980 Pennsylvania Bruce Mansfield 1 830 1976 Pennsylvania Bruce Mansfield 2 830 1977 Pennsylvania Bruce Mansfield 3 830 1979 Pennsylvania Cheswick 1 580 1970 Pennsylvania Conemaugh 1 850 1970 Pennsylvania Conemaugh 2 850 1971 Pennsylvania Hatfields Ferry Power Station 1 530 1969 Pennsylvania Hatfields Ferry Power Station 2 530 1970 Pennsylvania Hatfields Ferry Power Station 3 530 1971 Pennsylvania Homer City Station 1 620 1969 Pennsylvania Homer City Station 2 614 1970 Pennsylvania Homer City Station 3 650 1977 Pennsylvania Keystone 1 850 1967 Pennsylvania Keystone 2 850 1968 Pennsylvania Mitchell Power Station 33 277 1963 Pennsylvania New Castle 5 138 1964 Pennsylvania Portland 2 243 1962 Pennsylvania PPL Brunner Island 2 387 1965 Pennsylvania PPL Brunner Island 3 754 1981

### 51 State Name Plant Name Unit ID Capacity (MW) On Line
Year Pennsylvania PPL Montour 1 761 1971 Pennsylvania PPL Montour 2 757 1973

South Carolina Canadys Steam CAN1 105 1962

South Carolina Canadys Steam CAN2 116 1964

South Carolina Canadys Steam CAN3 175 1967

South Carolina Dolphus M Grainger 1 85.0 1966

South Carolina Dolphus M Grainger 2 85.0 1966

South Carolina Jefferies 3 153 1970

South Carolina Jefferies 4 153 1970

South Carolina Wateree WAT1 350 1970

South Carolina Wateree WAT2 350 1971

South Carolina Williams WIL1 615 1973

South Carolina Winyah 1 295 1975

South Carolina Winyah 2 295 1977

South Dakota Big Stone 1 470 1975

Tennessee Bull Run 1 881 1967

Tennessee Cumberland 1 1232 1973

Tennessee Cumberland 2 1233 1973

Texas Big Brown 1 575 1971

Texas Big Brown 2 575 1972

Texas Coleto Creek 1 632 1980

Texas Fayette Power Project 1 598 1979

Texas Fayette Power Project 2 598 1980

Texas Harrington 061B 347 1976

Texas Harrington 062B 347 1978

Texas Harrington 063B 347 1980

Texas J T Deely 1 385 1977

Texas J T Deely 2 385 1978

Texas Martin Lake 1 750 1977

Texas Martin Lake 2 750 1978

Texas Martin Lake 3 750 1979

Texas Monticello 1 565 1974

Texas Monticello 2 565 1975

Texas Monticello 3 750 1978

Texas Sandow 4 545 1981

Texas W A Parish WAP5 645 1977

Texas W A Parish WAP6 650 1978

Texas W A Parish WAP7 565 1980

Texas Welsh 1 528 1977

Texas Welsh 2 528 1980

### 52 State Name Plant Name Unit ID Capacity (MW) On Line
Year

Utah Hunter 1 430 1978

Utah Hunter 2 430 1980

Utah Huntington 1 445 1977

Utah Huntington 2 450 1974 Virginia Chesapeake 4 217 1962 Virginia Chesterfield 5 310 1964 Virginia Chesterfield 6 658 1969 Washington Transalta Centralia Generation BW21 703 1972 Washington Transalta Centralia Generation BW22 703 1973 West Virginia Fort Martin Power Station 1 552 1967 West Virginia Fort Martin Power Station 2 555 1968 West Virginia Harrison Power Station 1 652 1972 West Virginia Harrison Power Station 2 642 1973 West Virginia Harrison Power Station 3 651 1974

West Virginia John E Amos 1 800 1971 West Virginia John E Amos 2 800 1972 West Virginia John E Amos 3 1300 1973 West Virginia Mitchell 1 800 1971 West Virginia Mitchell 2 800 1971 West Virginia Mountaineer 1 1300 1980 West Virginia Mt Storm 1 524 1965 West Virginia Mt Storm 2 524 1966 West Virginia Mt Storm 3 521 1973 West Virginia Pleasants Power Station 1 639 1979 West Virginia Pleasants Power Station 2 639 1980

Wisconsin Capitol Heat and Power 1 0.9 1963

Wisconsin Capitol Heat and Power 2 1 1964

Wisconsin Columbia 1 555 1975

Wisconsin Columbia 2 559 1978

Wisconsin Edgewater 4 321 1969

Wisconsin Genoa 1 356 1969

Wisconsin John P Madgett B1 398 1978

Wisconsin Manitowoc 7 18.0 1964

Wisconsin Menasha B24 14.5 1964

Wisconsin Nelson Dewey 2 111 1962

Wisconsin Pleasant Prairie 1 617 1980

Wisconsin Pulliam 8 133 1964

Wisconsin South Oak Creek 7 298 1965

Wisconsin South Oak Creek 8 312 1967

Wisconsin Valley 1 70.0 1968

### 53 State Name Plant Name Unit ID Capacity (MW) On Line
Year

Wisconsin Valley 2 70.0 1968

Wisconsin Valley 3 70.0 1969

Wisconsin Valley 4 70.0 1969

Wisconsin Weston 3 338 1981 Wyoming Dave Johnston BW43 220 1964 Wyoming Dave Johnston BW44 330 1972 Wyoming Jim Bridger BW71 530 1974 Wyoming Jim Bridger BW72 530 1975 Wyoming Jim Bridger BW73 530 1976 Wyoming Jim Bridger BW74 530 1979 Wyoming Laramie River Station 1 565 1980 Wyoming Laramie River Station 2 570 1981 Wyoming Naughton 1 160 1963 Wyoming Naughton 2 210 1968 Wyoming Naughton 3 330 1971 Wyoming Neil Simpson 5 14.6 1969 Wyoming Wyodak BW91 335 1978

### 54 

## A ppendix B

Analysis of Visibility Degradation at Four Class I Areas

The default post

- processing to calculate changes in visibility from the Transport Rule and nationwide BART (compared to the 2014 base case) showed apparent visibility degradation at
four Class I areas, as shown in table B

- 1 below.

Table B

- 1

. Visibility ch ange for the 2014 “ Transport Rule + BART

- elsewhere ” case compared to the 2014 base case (positive numbers represent degradation)

.

Class I Area Name IMPROVE
ID Representative IMPROVE
Site State Visibility Change
TR+BART

elsewhere 20% Best days Visibility Change
TR+BART

elsewhere 20% Worst days Bryce Canyon NP BRCA BRCA1 UT 0.05

- 0.08

Mazatzal Wilderness MAZA IKBA1 AZ

- 0.02 0.23
Pine Mountain
Wilderness PIMO IKBA1 AZ

- 0.02 0.23 Saguaro NM SAGU SAGU1 AZ

- 0.24 0.26



### All four of the Class I areas are located in the western portion of the 36km modeling domain (outside of the 12km modeling domain). In the CAMx output for the grid cells in the vicinity of these four Class I areas, we observed that in most cases, modeled concentrations of

nitrat e were very low on the 20 percent worst days (and 20 percent best days at Bryce Canyon) in both the “Transport Rule + BART

- elsewhere” case and the “Nationwide BART” case. The modeled nitrate concentrations in these cases ranged from 0.001 to 0.004 μg/m 3



### , averaged across the 20 percent worst or best days in 2005. As an example, F igure B

- 1 shows the daily average nitrate concentration for September 4 (the figure shows the model ed concentration for September

4 th 

### in 2014)

, which is one of the measured 20% wors t days at Saguaro National Monument. It can be seen that the modeled nitrate concentration in much of Arizona and large parts of the West are very small (the gray color is concentrations of < 0 .0001 ug/m3).

### 55 Figure B

- 1

. Modeled daily average particulate nitrate concentration in the 2014 base case

scenario.

Notably, the modeled concentrations were generally a small fraction of monitored

ambient nitrate concentrations at the IMPROVE sites for the four Class I areas. In the cases where degradation was calculated, a very small increase in modeled nitrate was observed on several of the worst or best modeled days. This led to a relatively large modeled percent increase

in nitrate. Table B

- 2 shows the modeled daily average nitrate concentration on a single best or worst day at each of the four Class 1 areas. Among the 20% best or worst days at each of these Class I areas, these particular days had the largest percentage increase in n itrate. At each class I
area, there were between 22 and 25 days that went into the best or worst days calculations.

### 56 Table B

- 2

. Modeled nitrate concentrations on the single best or worst day with the largest modeled nitrate increase between the 2014 base case and the 2014 Transport R ule scenario.

Class I Area State Date Best

or Worst Day? Modeled
Nitrate
Concentration
2014 Base Case (ug/m3) Modeled Nitrate
Concentration 2014 Transport
Rule + BART

Elsewhere (ug/m3) %
Nitrate
Increase

Mazatzal Wilderness AZ 9/10/2005 Worst 0.0003 0.0196 6533%

Pine Mountain Wilderness AZ 9/10/2005 Worst 0.0003 0.0196 6533%

Bryce Canyon NP UT 12/09/2005 Best 0.0047 0.015 319%

Saguaro NM AZ 9/04/2005 Worst 0.0096 0.0497 518%



### The large percentage increase in nitrate on a single day at Matzatzal and Pine Mountain has a large influence on the average nitrate RRF that is used in the visibility calculation. The average nitrate concentration (averaged over 23 days) on the worst days at Pine Mountain and

Mazatzal increased from 0.001 μg/m 3 

### in the 2014 base case to 0.002 μg/m 3 

### in the “Transport

Rule + BART

- elsewhere” case. This is a very small increase that would not lead to noticeable changes in visibility; however it is a large percentage increase (100%). Since the modeled visibility test is based on relative changes in PM species, the very small increase in nitrate has a large impact on the final results.

Further examination of the days when these nitrate increases occur reveals a somewhat random pattern of very small increases and decreases that appear unrelated to EGU emissions changes. Figure B

- 2 shows the relative change in nitrate on September 4 th 

### between the 2014 base case and 2014 Transport Rule +BART

- elsewhere case.

### 57 Figure B

- 2

. Nitrate relative response factor on September 4 th 

### between the 2014 base case and the 2014 Transport Rule scenario (values > 1 are increases in nitrate in the control scenario)

.

W

hile IPM predicts modestly higher NO X 

### emissions in some nearby states under the “Transport Rule + BART

- elsewhere” scenario, the checkerboard pattern of nitrate increases and

decreases in the desert Southwest (among other areas) show no logical connection to these modestly higher emissions. Th is nitrate modeling issue appears similar to a previously noted nitrate chemistry stability issue when modeled concentrations are very small and relative humidity is very low. 33 

### T he instability is related to the ISORROPIA nitrate partitioning

mechanism tha t is used in CAMx to solve the partitioning of nitrate between the gas and particle phase. The same partitioning mechanism is used in both the CAMx and CMAQ models. An updated version of ISORROPIA (ISOROPPIA II) has been developed and reportedly has solv ed most of the instability issues encountered with the current version

. 34

33 Tong 2005, Numerical instability in the Community Multiscale Air Quality Model and its impacts on aerosol and ozone simulations, available at: http://www.princeton.edu/~mauzeral/papers/CMAQ_instability%20submission.pdf

. And Bhave 2004, CMAQ Aerosol Module Development: Recent Enhancements and Future Plans, av ailable at: http://www.cmascenter.org/conference/2004/abstracts/Model%20Development/bhave_abstract.pdf

34 Fountoukis 2007, ISORROPIA II: a computationa lly efficient thermodynamic equilibrium model for K +

– Ca 2+

– Mg 2+

– NH 4 +

– Na +

– SO 4 2

−

– NO 3 −

– Cl −

– H 2 O aerosols, available at: http://www.atmos

- chem

phys.org/7/4639/2007/acp

- 7

- 4639

- 2007.pdf

### 58 T hus, we conclude that these positive and negative differences between very low nitrate concentrations are a modeling artifact attributable to the ISORROPIA nitrate mechanism in

C AMx for the conditions that apply in this geographic area on these days, and are not reasonable predictors of the true relative effects on visibility of the emission control scenarios.

As a comparison, we also examined the sulfate relative concentration on September 4 th 

### . Figure

B

- 3 shows the relative change in sulfate on September 4 th 

### between the 2014 base case and 2014 Transpo rt Rule +BART

- elsewhere case. Note the smooth spatial pattern of sulfate relative changes.

Figure B

- 3

. Sulfate relative response factor on September 4 th 

### between the 2014 base case and the 2014 Transport Rule scenario (value s < 1 are decreases in sulfate in the control scenario)

.

To further analyze the cause of the visibility degradation, we performed an analysis to

illustrate how sensitive the predictions of degradation are to highly variable results on particular days

. For each of these four Class I areas, we removed the one day (the day at each site listed in

table B

- 2) of the 20 percent worst or best days with the largest incre ase in modeled nitrate

concentration . When the single day is removed, the apparent visibility degradations no longer

occur. Table B

- 3 shows the default results with all days and the results when the single day is removed from the analysis.

### 59 Table B

- 3

. V isibility results with all days and with one day removed from the calculations

.

Class I area IMPROVE
site Visibility change
default Visibility change with one day
removed Number of modeled days in
the best or worst days
calculation Bryce Canyon NP BRCA 0.05 (best)

- 0.01 22

Mazatzal Wilderness MAZA 0.23 (worst)

- 0.01 23
Pine Mountain
Wilderness PIMO 0.23 (worst)

- 0.01 23 Saguaro NM SAGU 0.26 (worst)

- 0.06 25



### Th e large percentage increase in nitrate can also be accounted for in the post

- processing of the model results by setting a minimum concentration RRF threshold when calculating RRFs for all PM spe cies. If the average species concentration across all best or worst days at each site

is below the mi nimum threshold, then the RRF for that particular species would be set to 1.0. To test this, the regional haze post

- processing software (MATS) was run again with a minimum average concentration threshold of 0.01 ug/m3. Table B

- 4 shows the results of this analysis.

Table B

- 4

. Change in visibility between the 2014 base case and the 2014 Transport Rule

scenario when a minimum RRF threshold (0.01 ug/m3) is set in the post

- processing software

.

Class I area IMPROVE
site Visibility Change
TR1+BART best days Visiblity Change
TR1+BART worst days Bryce Canyon NP BRCA

- 0.01

- 0.08

Mazatzal Wilderness MAZA

- 0.02

- 0.01
Pine Mountain
Wilderness PIMO

- 0.02

- 0.01 Saguaro NM SAGU

- 0.24

- 0.06



### As can be seen from Table B

- 4, if a minimum RRF threshold of 0.01 ug/m3 is used, the degradation no longer occurs at any Class I area. Based on this information, t he EPA is considering whether to implement a minimum threshold concentration as part of the default Regional Haze calculations. The minimum threshold would be buil t into the MATS software used to post

- process photochemical output s

. These possible revisions are aimed at avoiding potentially misleading results in situations such as the one observed near these particular

W estern Class I areas.

Based on these additi onal analyses of the visibility modeling results, w e are confident that no degradation in the four western Class I areas will result from implementation of the Transport Rule trading program in the Eastern U.S.

### 60 

## A ppendix C

Sensitivity Analysis Accounting f or Proposed Increase s in Certain Transport
Rule State Budgets

The Better than BART modeling analysis for this proposed rule was completed using the emissions totals from the final Transport Rule, and also assuming that the July 11, 2011 proposal regarding ozone

- season NOx emissions in five states will be finalized. 35 

### Recently, EPA proposed 36 

### to make adjustments to the EGU SO2 and NOx budgets in several states. In all cases,
the budgets are proposed to be increased. Table C

- 1 summarizes the propos ed budget increases.

Table C

- 1

. Proposed increases in Transport Rule 2014 SO2 and NOx Budgets
State 2014 SO 2 Budget Increase (tons) 2014 N O x Budget Increase (tons)

Louisiana N/A 4231 Mississippi N/A 2136
Michigan N/A 5228

Nebraska N/A 3559

New Jersey N/A 112

New York 3527 3485

Texas 70067 1375

Wisconsin 7757 2473

Total Increase 81351 22599



### The proposed SO 2 

### and NOx budget increases are relatively modest compared to the total
modeled reduc tions from the Transport Rule. The modeled SO 2 

### reductions from the Transport Rule are ~3.8 million tons per year and NOx reductio ns are ~125,000 tons per year. In addition, considering the proposed budget increases, the “Transport Rule +BART

- elsewhere” control
scenario is still projected to result in about 26,000 tons more NOx emission reductions than “nationwide BART” and about 821,000 tons more SO 2 

### emission reductions than “nationwide
BART”. The only increase in emissions that is large enough to potentially affect the Better than BART analysis is the SO 2 

### budget increase in Texas. This is due to the relatively large increase in
Texas SO 2 

### compared to other states, and the fact that SO 2 

### emissions account for the majority of
the PM 2.5 

### and visibility im pacts from the Transport Rule. Therefore, we completed a more detailed sensitivity analysis of the potential impact from the Texas SO 2 

### budget increase.

35 The air quality modeling conducted for this analysis included in the CSAPR scenario the states addressed in the July 11 proposal. These states are Iowa, Kansas, Michigan, Nebraska, Minnesota , and
Oklahoma.
36 Revisions to the Federal Implementation Plans to Reduce Interstate Transport of Fine Particulate Matter and Ozone, 76 FR 63860 (October 14, 2011)

### 61 Table C

- 2 shows the Texas SO 2 

### emissions as modeled in the Better than BART analysis
and the emissions that would occur if the state budget is increased as proposed.

Table C

- 2

. Texas 2014 SO2 emissions and decreases compared to the 2014 modeled base

case

2014 Base Case
SO 2 Emissions 2014 TR+
BART

elsewhere SO 2 Emissions (estimate from
IPM used in air quality modeling) 2014 Proposed Budget Increase SO 2 Emissions
Decrease from TR (as modeled) SO 2 Emissions
Decrease from
TR with
Increased Budget 453,332 266,627 70,067

- 186,705

- 116,638



### Table C

- 2 shows that the modeled SO 2 

### reduction in Te xas is ~186,000 tons per year. After accounting for the proposed increase in the SO 2 

### budget for Texas, the SO 2 

### emissions
reduction is still ~116,000 tons per year. This would reduce the total SO 2 

### reduction from the Transport Rule from ~3.8 million tons per year to ~3.7 million tons per year.

It can be seen from Table C

- 2 that even with the increase in the SO 2 

### budget for Texas, there is still a large SO 2 

### reduction in Texas, compared to the 2014 base case and the impact on
the total net SO 2 

### reduction from the Transport Rule is minimal ( < 2% decrease in SO 2 

### reductions).

Given this information, we would still expect major visibility improvements at Class I areas in and around Texas from the Transport Rule. However, in order to better inform the process, we performed a very conservative s ensitivity analysis to provide a limiting upper estimate of the worst case impact of increases in Texas SO 2 

### allowances.

Sensitivity Analysis of Better than BART with Increased Texas SO 2 

### Allowances

We identified the most likely “affected” Class I areas for Texas and then assumed that these areas would get zero benefit from the Transport Rule. Table C

- 3 shows the 9 Class I areas
in and near Texas that were identified as the affected areas

. 37 

### We identified these areas by looking at the regional haze analy sis conducted by the CENRAP regional planning organization in support of the development of regional haze SIPs in Texas and surrounding states.

37 Affected Class I areas were identified by examining consultation letters from states surro unding Texas which were included in the Texas regional haze SIP submissions. The letters are included in Appendix 4

- 3 available here: http://www.tceq.texas.gov/airquality/s ip/bart/haze_appendices.html . We included 6 areas which had a > 2 Mm
- 1 impact from Texas. These areas had much higher visibility impacts from Texas compared to other analyzed Class I
areas. We also included the 3 Class I areas that are in Texas or are r epresented by an IMPROVE monitor that is
located in Texas.

### 62 Table C

- 3

. Class I areas most affected by Texas emissions and the modeled visibility improvement from the Transport Rule + BART

- elsewhere case

.

Class I Area Name State TR+BART

elsewhere
20% Best days TR+BART

elsewhere 20% Worst days Big Bend NP TX

- 0.2

- 1.1 Caney Creek Wilderness AR

- 0.4

- 3.2

Carlsbad Caverns NP TX

- 0.1

- 0.9 Guadalupe Mountains NP TX

- 0.1

- 0.9

Hercules

- Glades Wilderness MO

- 0.6

- 2.5

Salt Creek NM

- 0.1

- 0.7 Upper Buffalo Wilderness AR

- 0.5

- 2.5

White Mountain Wilderness NM

- 0.1

- 0.6

Wichita Mountains OK

- 0.2

- 1.6



### For this analysis, we assumed that the visibility benefits shown in Table C

- 3 would
become zero as a result of the allowanc e adjustment for SO2 in Texas. This is a very conservative assumption because there would still be 116,000 tons per year of SO 2 

### reductions in Texas and this also assumes that there would be no visibility benefits in these 9 Class I areas
from the ~3.6 million tons of SO 2 

### reductions from the other Transport Rule states. This is not a realistic assumption, but one that we use here i n order to be conservative.

Sensitivity Analysis Results

We recalculated the average visibility changes at the 60 Eastern and 140 nationwide Class I areas in the Better than BART analysis, assuming that the visibility change at the 9 Class
I are as in Ta ble C

- 3 would be zero. The first prong of the Better than BART test would still be passed because there will be no degradation in visibility at any Class I areas on either t he 20% best or 20% worst days. Table C

- 4 below shows the average visibility results and the re

calculated average visibility results for the Texas sensitivity case.

### 63 Table C

- 4

. Average visibility improvement on the 20% best and 20% worst days in the Better than BART analysis and the Texas sensitivity analysis

. “Transport Rule +
BART

elsewhere” “Transport Rule +
BART

- elsewhere” Texas Sensitivity Case “Nationwide BART”

60 Class I Areas in the Eastern Transport Rule Modeling
Domain
20 percent Worst Days 1. 6 1.3 1.0

20 percent Best Days 0. 3 0. 3 0. 2

140 Class I Areas in the Western and Eastern Transport Rule Modeling Domains
20 percent Worst Days 0. 7 0. 6 0. 5

20 percent Best Days 0. 1 0.1 0.1



### Table C

- 4 shows that the even with the very conservative assumptions in this analysis, the Transport Rule+ BART

- elsewhere case is still, on average, better than (or equal to) nationwide BART on both the 20% best and 20% worst days at the 60 Eastern Class I areas and
at the 140 nationwide Class I areas.