Notices. Supplemental Notice of Proposed Rulemaking

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BILLING CODE 8320-01-M 72 88 Tuesday, May 8, 2007 Proposed Rules Part II Environmental Protection Agency 40 CFR Parts 51 and 52 Supplemental Notice of Proposed Rulemaking for Prevention of Significant Deterioration and Nonattainment New Source Review: Emission Increases for Electric Generating Units; Proposed Rule ENVIRONMENTAL PROTECTION AGENCY 40 CFR Parts 51 and 52 [Docket ID No. EPA-HQ-OAR-2005-0163; FRL-8307-7] RIN-2060-AN28 Supplemental Notice of Proposed Rulemaking for Prevention of Significant Deterioration and Nonattainment New Source Review:

Emission Increases for Electric Generating Units AGENCY: Environmental Protection Agency (EPA). ACTION: Supplemental Notice of Proposed Rulemaking. SUMMARY: This action is a supplemental notice of proposed rulemaking

(SNPR)to EPA's October 20, 2005 notice of proposed rulemaking (NPR). In the October 2005 NPR, EPA

(we)proposed to revise the emissions test for existing electric generating units

(EGUs)that are subject to the regulations governing the Prevention of Significant Deterioration

(PSD)and nonattainment major New Source Review

(NSR)programs (collectively “NSR”) mandated by parts C and D of title I of the Clean Air Act (CAA). We proposed three alternatives for the emissions test: a maximum achievable hourly emissions test, a maximum achieved hourly emissions test, and an output-based hourly emissions test. This action recasts the proposed options so that the output-based test becomes an alternative method to implement the maximum achieved or maximum achievable hourly tests, rather than a separate option. This SNPR also proposes a new option in which the hourly emissions increase test is added to the existing requirements for computing a significant increase and a significant net emissions increase on an annual basis. It also includes proposed rule language and supplemental information for the October 2005 proposal, including an examination of the impacts on emissions and air quality. These proposed regulations interpret the emissions increase component of the modification test under CAA 111(a)(4), in the context of NSR, for existing EGUs. The proposed regulations would promote the safety, reliability, and efficiency of EGUs. We are seeking comment on all aspects of this proposed rule. DATES: *Comments.* Comments must be received on or before July 9, 2007. Under the Paperwork Reduction Act, comments on the information collection provisions must be received by the Office of Management and Budget

(OMB)on or before June 7, 2007. *Public Hearing:* If anyone contacts us requesting to speak at a public hearing on or before May 29, 2007, we will hold a public hearing approximately 30 days after publication in the **Federal Register** . ADDRESSES: Submit your comments, identified by Docket ID No. EPA-HQ-OAR-2005-0163 by one of the following methods: • *http://www.regulations.gov:* Follow the on-line instructions for submitting comments. • *E-mail: a-and-r-docket@epa.gov.* • *Mail:* Attention Docket ID No. EPA-HQ-OAR-2005-0163, U.S. Environmental Protection Agency, EPA West (Air Docket), 1200 Pennsylvania Avenue, NW., Mail code: 6102T, Washington, DC 20460. Please include a total of 2 copies. In addition, please mail a copy of your comments on the information collection provisions to the Office of Information and Regulatory Affairs, Office of Management and Budget (OMB), Attn: Desk Officer for EPA, 725 17th Street, NW., Washington, DC 20503. • *Hand Delivery:* U.S. Environmental Protection Agency, EPA West (Air Docket), 1301 Constitution Avenue, Northwest, Room 3334, Washington, DC 20004, Attention Docket ID No. EPA-HQ-OAR-2005-0163. Such deliveries are only accepted during the Docket's normal hours of operation, and special arrangements should be made for deliveries of boxed information. *Instructions.* Direct your comments to Docket ID No. EPA-HQ-OAR-2005-0163. EPA's policy is that all comments received will be included in the public docket without change and may be made available online at *http://www.regulations.gov* including any personal information provided, unless the comment includes information claimed to be Confidential Business Information

(CBI)or other information whose disclosure is restricted by statute. Do not submit information that you consider to be CBI or otherwise protected through *http://www.regulations.gov* or e-mail. The *http://www.regulations.gov* website is an “anonymous access” system, which means EPA will not know your identity or contact information unless you provide it in the body of your comment. If you send an e-mail comment directly to EPA without going through *http://www.regulations.gov,* your e-mail address will be automatically captured and included as part of the comment that is placed in the public docket and made available on the Internet. If you submit an electronic comment, EPA recommends that you include your name and other contact information in the body of your comment and with any disk or CD-ROM you submit. If EPA cannot read your comment due to technical difficulties and cannot contact you for clarification, EPA may not be able to consider your comment. Electronic files should avoid the use of special characters, any form of encryption, and be free of any defects or viruses. For additional instructions on submitting comments, go to section B. of the SUPPLEMENTARY INFORMATION section of this document. *Docket.* All documents in the docket are listed in the *http://www.regulations.gov* index. Although listed in the index, some information is not publicly available, i.e., CBI or other information whose disclosure is restricted by statute. Certain other material, such as copyrighted material, is not placed on the Internet and will be publicly available only in hard copy form. Publicly available docket materials are available either electronically in *http://www.regulations.gov* or in hard copy at the U.S. Environmental Protection Agency, Air Docket, EPA/DC, EPA West Building, Room 3334, 1301 Constitution Ave., NW., Washington, DC. The Public Reading Room is open from 8:30 a.m. to 4:30 p.m., Monday through Friday, 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. FOR FURTHER INFORMATION CONTACT: Ms. Janet McDonald, Air Quality Policy Division (C504-03), U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, telephone number:

(919)541-1450; fax number:

(919)541-5509, or electronic mail e-mail address: *mcdonald.janet@epa.gov.* SUPPLEMENTARY INFORMATION: I. General Information A. Does this action apply to me? Entities potentially affected by the subject rule for this action are fossil-fuel fired boilers and turbines serving an electric generator with nameplate capacity greater than 25 megawatts

(MW)producing electricity for sale. Entities potentially affected by the subject rule for this action also include State, local, and tribal governments. Categories and entities potentially affected by this action are expected to include: Industry Group SIC a NAICS b Electric Services 491 221112. Federal government 1 22112 Fossil-fuel fired electric utility steam generating units owned by the Federal government. State/local/Tribal government 22112 Fossil-fuel fired electric utility steam generating units owned by municipalities. Fossil-fuel fired electric utility steam generating units in Indian country. a Standard Industrial Classification b North American Industry Classification System. B. Where can I get a copy of this document and other related information? 1 Establishments owned and operated by Federal, State, or local government are classified according to the activity in which they are engaged. In addition to being available in the docket, an electronic copy of this proposal will also be available on the World Wide Web. Following signature by the EPA Administrator, a copy of this notice will be posted in the regulations and standards section of our NSR home page located at *http://www.epa.gov/nsr.* C. What should I consider as I prepare my comments for EPA? 1. *Submitting CBI.* Do not submit this information to EPA through *http://www.regulations.gov* or e-mail. Clearly mark the part or all of the information that you claim to be CBI. For CBI information in a disk or CD ROM that you mail to EPA, mark the outside of the disk or CD ROM as CBI and then identify electronically within the disk or CD ROM the specific information 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 that does not contain the information claimed as CBI must be submitted for inclusion in the public docket. Information so marked will not be disclosed except in accordance with procedures set forth in 40 CFR part 2. Send or deliver information identified as CBI only to the following address: Roberto Morales, OAQPS Document Control Officer (C404-02), U.S. EPA, Research Triangle Park, NC 27711, Attention Docket ID No. EPA-HQ-OAR-2005-0163. 2. *Tips for Preparing Your Comments.* When submitting comments, remember to: • Identify the rulemaking by docket number and other identifying information (subject heading, **Federal Register** date and page number). • 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. D. How can I find information about a possible public hearing? People interested in presenting oral testimony or inquiring if a hearing is to be held should contact Ms. Pamela S. Long, New Source Review Group, Air Quality Policy Division (C504-03), U.S. EPA, Research Triangle Park, NC 27711, telephone number

(919)541-0641. If a hearing is to be held, persons interested in presenting oral testimony should notify Ms. Long at least 2 days in advance of the public hearing. Persons interested in attending the public hearing should also contact Ms. Long to verify the time, date, and location of the hearing. The public hearing will provide interested parties the opportunity to present data, views, or arguments concerning these proposed rules. E. How is the preamble organized? The information presented in this preamble is organized as follows: I. General Information A. Does this action apply to me? B. Where can I get a copy of this document and other related information? C. What should I consider as I prepare my comments for EPA? D. How can I find information about a possible public hearing? E. How is the preamble organized? II. Overview A. Option 1: Hourly Emissions Increase Test Followed by Annual Emissions Test B. Option 2: Hourly Emissions Increase Test III. Analyses Supporting Proposed Options A. The Integrated Planning Model B. NSR Availability Scenarios—Description of the Scenarios C. NSR Availability Scenarios-Discussion of SO 2 and NO X Results D. NSR Availability Scenarios-Discussion of PM 2.5 , VOC, and CO Results E. NSR Efficiency Scenario IV. Proposed Regulations for Option 1: Hourly Emissions Increase Test Followed by Annual Emissions Test A. Test for EGUs Based on Maximum Achieved Emissions Rates B. Test for EGUs Based on Maximum Achievable Emissions V. Proposed Regulations for Option 2: Hourly Emissions Increase Test VI. Legal Basis and Policy Rationale VII. Statutory and Executive Order Reviews A. Executive Order 12866: Regulatory Planning and Review B. Paperwork Reduction Act C. Regulatory Flexibility Act

(RFA)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 Risks 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 Low-Income Populations VIII. Statutory Authority II. Overview This action is a SNPR to EPA's October 20, 2005 (70 FR 61081) NPR. In the October 2005 NPR, we proposed to revise the emissions test for existing EGUs that are subject to the regulations governing the PSD and nonattainment major NSR programs (collectively “NSR”) mandated by parts C and D of title I of the CAA. We proposed three alternatives for the emissions test: a maximum achievable hourly emissions test, a maximum achieved hourly emissions test, and an output-based hourly emissions test. In the NPR, we did not propose to include, along with any of the revised NSR emissions tests, any provisions for computing a significant increase or a significant net emissions increase, although we solicited comment on retaining such provisions. In addition, we solicited comment on whether, if we revised the NSR test to be a maximum achieved emissions test or output-based emissions test, we should revise the NSPS regulations to include a maximum achieved emissions test or an output-based emissions test. This action recasts the proposed options so that the output test, instead of being an alternative to the maximum hourly achieved or maximum hourly achievable tests, becomes an alternative method for sources to implement those two tests. Specifically, we propose that each of the two tests would be implemented through

(i)an input method (as defined below),

(ii)the output method, or

(iii)at the source's choice, either the input or output method. This action includes proposed rule language and supplemental information for the October 2005 proposal as it relates to the major NSR regulations, including an examination of the impacts on emissions and air quality that would result were we to finalize one of the applicability tests proposed in the October 2005 proposal or in this SNPR, as described below. This action also proposes an additional option that was not included in the October 2005 rule. For convenience, this action characterizes the tests contained in the October 2005 NPR, described above, as Option 2 (with the maximum hourly achieved test characterized as Alternatives 1-4 and the maximum hourly achievable test characterized as Alternatives 5-6 within that Option 2, and with each of those tests including output-based alternatives). For the additional option proposed, which we characterize as Option 1, we are proposing that an hourly emissions increase test (either maximum achieved or maximum achievable, each with output-based alternatives) would include the significant net emissions increase test in the current major NSR rules, which is calculated on an actual-to-projected-actual annual emissions basis. We are also clarifying that Option 1 is our preferred option. When we proposed a revised emissions test for EGUs in October 2005, we referenced *United States* v. *Duke Energy Corp.,* 411 F.3d 539 (4th Cir.) rehearing den.__ F.3d__ (2005), cert. granted __ U.S.__ (2006). At the time of our proposal, the Fourth Circuit had denied the United States' petition for rehearing on the decision in Duke Energy, but the deadline for filing a petition for *certiorari* to the United States Supreme Court had not yet passed. Subsequently, on December 28, 2005, Intervenor plaintiffs Environmental Defense Fund, North Carolina Sierra Club, and North Carolina Public Interest Research Group filed a petition for *certiorari* asking the court to address several matters. On May 15, 2006 the United States Supreme Court granted the petition for a writ of *certiorari.* On April 2, 2007, the Supreme Court vacated and remanded the Fourth Circuit decision. [549 U.S.__ (2007)] , 75 U.S.L.W. 4167 (April 2, 2007). When we published the proposal in October 2005, it was in part in response to the Fourth Circuit's holding that EPA must read the 1980 PSD regulations to contain an hourly test, consistent with the NSPS regulations. The Supreme Court's vacatur was based on its finding that such a reading of the 1980 PSD regulations “was inconsistent with their terms.” The Supreme Court, however, indicated that EPA may be able to revise the regulations when, as here, it has a rational reason for doing so. While there is no longer a need to provide national consistency in light of the Fourth Circuit decision, we believe that the options for a maximum hourly test that we proposed in our October 2005 NPR and continue to propose in this SNPR are an appropriate exercise of our discretion, especially in light of the substantial EGU emission reductions from more efficient air quality programs promulgated after 1980. Accordingly, we continue to pursue the viability of imposing an hourly emissions test on EGUs for purposes of major NSR applicability. In May 2001, President Bush's National Energy Policy Development Group issued findings and key recommendations for a National Energy Policy. This document included numerous recommendations for action, including a recommendation that the EPA Administrator, in consultation with the Secretary of Energy and other relevant agencies, review NSR regulations, including administrative interpretation and implementation. The recommendation requested that we issue a report to the President on the impact of the regulations on investment in new utility and refinery generation capacity, energy efficiency, and environmental protection. Our report to the President and our recommendations in response to the National Energy Policy were issued on June 13, 2002. A copy of this information is available at *http://www.epa.gov/nsr/publications.html.* In that report we concluded: As applied to existing power plants and refineries, EPA concludes that the NSR program has impeded or resulted in the cancellation of projects which would maintain and improve reliability, efficiency and safety of existing energy capacity. Such discouragement results in lost capacity, as well as lost opportunities to improve energy efficiency and reduce air pollution. (New Source Review Report to the President at pg. 3.) On December 31, 2002, we promulgated final regulations that implemented several of the recommendations in the New Source Review Report to the President. However, that action left the NSR regulations as they related to utilities largely unchanged. This action continues to address the recommendations in the New Source Review Report to the President as they relate to electric utilities specifically and in light of the regulatory requirements for EGUs that have been promulgated since our 2002 regulations. The regulations proposed in the October 2005 NPR and on this action would promote the safety, reliability, and efficiency of EGUs. The proposed regulations are consistent with the primary purpose of the major NSR program, which is to balance the need for environmental protection and economic growth. The proposed regulations reasonably balance the economic need of sources to use existing physical and operating capacity with the environmental benefit of regulating those emissions increases related to a physical or operational change. This is particularly true in light of the substantial national EGU emissions reductions that other programs have achieved or are expected to achieve, which we described in detail at 70 FR 61083. Moreover, as the analyses included in this SNPR demonstrate, the proposed regulations would not have an undue adverse impact on local air quality. This section gives an overview of our proposed actions for major NSR applicability at existing EGUs, including the proposals in the NPR, as recast in this proposal, for the maximum hourly emissions tests and this additional proposal. Each of the options would promote the safety, reliability, and efficiency of EGUs. Each of the options would also balance the economic need of sources to use existing physical and operating capacity with the environmental benefit of regulating those emissions increases related to a change, considering the substantial national emissions reductions other programs have achieved or will achieve from EGUs. Our preferred Option is Option 1. We will select the final option after weighing the public comments on the Options. Table 1 summarizes our two Options. 2 For clarity, this table lists all of the steps in the applicability determinations under the various options and alternatives. These steps include, as Step 1, the determination of whether a physical change or change in the method of operation has occurred. This Step 1 is included in the table solely for purposes of clarity; neither the October 2005 NPR nor this action proposes any action of any type (or makes any re-proposal) concerning the regulations defining physical change or change in the method of operation. Similarly, the steps also include, as Steps 3 and 4, the current net significance test; and this SNPR does not propose any action of any type (or make any re-proposal) concerning the current net significance test. Finally, this action does not propose any action of any type (or make any re-proposal) concerning the current applicability test for EGUs. Table 1.—Proposed Options for Major NSR Applicability for Existing EGU 2 Option 1 Step 1: Physical Change or Change in the Method of Operation. Step 2: Hourly Emissions Increase Test. • Alternative 1—Maximum achieved hourly emissions; statistical approach; input basis. • Alternative 2—Maximum achieved hourly emissions; statistical approach; output basis. • Alternative 3—Maximum achieved hourly emissions; one-in-5-year baseline; input basis. • Alternative 4—Maximum achieved hourly emissions; one-in-5-year baseline; output basis. • Alternative 5—NSPS test—maximum achievable hourly emissions; input basis. • Alternative 6—NSPS test-maximum achievable hourly emissions; output basis. Step 3: Significant Emissions Increase Determined Using the Actual-to-Projected-Actual Emissions Test as in the Current Rules. 3 Step 4: Significant Net Emissions Increase as in the Current Rules. Option 2 Step 1: Physical Change or Change in the Method of Operation. Step 2: Hourly Emissions Increase Test. • Alternative 1—Maximum achieved hourly emissions; statistical approach; input basis. • Alternative 2—Maximum achieved hourly emissions; statistical approach; output basis. • Alternative 3—Maximum achieved hourly emissions; one-in-5-year baseline; input basis. • Alternative 4—Maximum achieved hourly emissions; one-in-5-year baseline; output basis. • Alternative 5—NSPS test—maximum achievable hourly emissions; input basis. • Alternative 6—NSPS test-maximum achievable hourly emissions; output basis. We request public comment on all aspects of this action. We intend to finalize either Option 1 or Option 2. We will also finalize either the maximum achieved or the maximum achievable alternative. We intend to respond to public comments on the October 20, 2005 NPR and this notice in a single **Federal Register** Notice and Response to Comments Document at the time that we take final action. 3 Steps 3 and 4 only apply when a unit fails Step 2. (That is, it is determined that an hourly emissions increase would occur.) A. Option 1: Hourly Emissions Increase Test Followed by Annual Emissions Test In the NPR, we did not propose to include, along with any of the revised NSR emissions tests, any provisions for computing a significant emissions increase or a significant net emissions increase, although we solicited comment on retaining such provisions. Many commenters believed netting is required under the Alabama Power Court decision, and supported options retaining netting. Therefore, we are proposing that major NSR applicability would include an hourly emissions increase test, followed by the current regulatory requirements for the actual-to-projected-actual emissions increase test to determine significance, and the significant net emissions increase test. We call this approach Option 1 and we are proposing it as our preferred option. Specifically, under Option 1, the major NSR program would include a four-step process as follows:

(1)Physical change or change in the method of operation;

(2)hourly emissions increase test ;

(3)significant emissions increase as in the current major NSR regulations; and

(4)significant net emissions increase as in the current major NSR regulations. Section IV of this preamble describes Option 1 in more detail. Our proposed regulatory language is for Option 1. Option 1 facilitates improvements for efficiency, safety, and reliability, without adverse air quality effects (as the discussion of the IPM and air quality analyses in Section III indicates). Specifically, changes that will not increase the hourly emissions rate—such as those to make repairs to reduce the number of forced outages—do not require further review under Option 1. That is, if there would be no hourly emissions increase following a physical change or change in the method of operation, the proposed rule does not require a determination of whether a significant increase or a significant net emissions increase would occur. Thus, Option 1 would simplify major NSR for changes where there is no increase in hourly emissions. However, many public commenters urged that we retain the significant emissions increase component of the emissions increase test. Therefore, we are proposing further review under Option 1 in instances where a physical or operational change at a given unit would increase the hourly emissions rate, such as would occur where there is an increase in existing capacity. In such cases, Option 1 requires further review using the significant increase and significant net emissions increase components of the current regulations. This approach retains an annual emissions test in determining NSR applicability. We are proposing both a maximum achieved hourly and a maximum achievable hourly emissions increase test under Step 2 of Option 1, which we discuss in detail in Section IV.A. of this preamble. Consistent with our policy goal of improving energy efficiency, we are proposing both an input 4 and output based format for both the maximum achievable and maximum achieved hourly emissions increase test options. Specifically, we are proposing the alternatives of

(i)use of input-based methodology for each test,

(ii)use of output-based methodology for each test, or

(iii)allowing the source to choose between input- or output-based methodology. Some commenters strongly opposed an output-based format, believing that it would encourage emissions increases. We believe these concerns are mitigated in a system where total annual emissions are capped nationally. Other commenters supported the output-based format, noting that it would encourage energy efficiency. 4 In this context, we use the term “input” as a convenient way to refer to the hourly emission rate test, and to distinguish it from the output test, which is calculated on the basis of hourly emissions per kilowatt hour of generation. We agree that an output-based test encourages efficient units, which has well-recognized benefits. The more efficient an EGU, the less it emits for a given period of operation. For example, a 50 MW combustion turbine that operates 500 hours a year, for 25,000 MWh per year at an emission rate of 75 ppm, would emit 46 tons per year at 25 percent efficiency, 41 tons per year at 28 percent efficiency, 37 tons per year at 31 percent efficiency, and 34 tons per year at 34 percent efficiency. Furthermore, we have established pollution prevention as one of our highest priorities. One of the opportunities for pollution prevention is maximizing the efficiency of energy generation. An output-based standard establishes emission limits in a format that incorporates the effects of unit efficiency by relating emissions to the amount of useful energy generated, not the amount of fuel burned. By relating emission limitations to the productive output of the process, output-based emission limits encourage energy efficiency because any increase in overall energy efficiency results in a lower emission rate. Allowing energy efficiency as a pollution control measure provides regulated sources with an additional compliance option that can lead to reduced compliance costs as well as lower emissions. The use of more efficient technologies reduces fossil fuel use and leads to multi-media reductions in environmental impacts both on-site and off-site. On-site benefits include lower emissions of all products of combustion, including hazardous air pollutants, as well as reducing any solid waste and wastewater discharges. Off-site benefits include the reduction of emissions and non-air environmental impacts from the production, processing, and transportation of fuels. While output-based emission limits have been used for regulating many industries, input-based emission limits have been the traditional method to regulate steam generating units. However, this trend is changing as we seek to promote pollution prevention and provide more compliance flexibility to combustion sources. For example, in 1998 we amended the NSPS for electric utility steam generating units (40 CFR part 60, subpart Da) to use output-based standards for nitrogen oxides (NO X ; 40 CFR 63.44a, 62 FR 36954, and 63 FR 49446). We recently promulgated new output-based emission limits for sulfur dioxide (SO 2 ) and NO X under subpart Da of 40 CFR part 60 (71 FR 9866) and for combustion turbines. (71 FR 38482.) B. Option 2: Hourly Emissions Increase Test For Option 2, we are proposing a maximum achieved emissions increase test alternative and a maximum achievable emissions increase test alternative. For both the maximum achieved and maximum achievable emissions increase test, we are also proposing the alternatives of

(i)the use of input-based methodology for each test;

(ii)the use of output-based methodology for each test, or

(iii)allowing the source to choose between input- or output-based methodology. We describe these alternatives in detail in Section V. of this preamble. Option 2 with the proposed maximum hourly achieved test would simplify NSR applicability determinations. Option 2 with the proposed maximum hourly achievable test provides even more simplicity by conforming NSR applicability determinations to NSPS applicability determinations. We also note the achieved and achievable tests eliminate the burden of projecting future emissions and distinguishing between emissions increases caused by the change from those due solely to demand growth, because any increase in the emissions under the hourly emissions tests would logically be attributed to the change. Both the achieved and achievable tests reduce recordkeeping and reporting burdens on sources because compliance will no longer rely on synthesizing emissions data into rolling average emissions. Option 2 would reduce the reviewing authorities' compliance and enforcement burden compared to the current regulations. In the October 2005 NPR, we also solicited comment on whether, if we revised the NSR test to be a maximum achieved emissions test or output-based emissions test, we should revise the NSPS regulations to include a maximum achieved emissions test or an output-based emissions test. This SNPR concerns the emissions test for existing EGUs in the major NSR programs. It does not address the emissions test for existing EGUs under the NSPS program. III. Analyses Supporting Proposed Options We examined how our proposed options for major NSR applicability for EGUs would affect control technology installation, emissions, and air quality. We conducted two separate analyses using the Integrated Planning Model (IPM). Our analyses show that none of the proposed options would have a detrimental impact on county-level emissions or local air quality. This section discusses our analyses and findings. More extensive information on our analyses is available in the Technical Support Document, which is available in Docket ID No. EPA-HQ-OAR-2005-0163. A. The Integrated Planning Model We use the IPM to analyze the projected impact of environmental policies on the electric power sector in the 48 contiguous States and the District of Columbia. The IPM is a multi-regional, dynamic, deterministic linear programming model of the entire electric power sector. It provides forecasts of least-cost capacity expansion, electricity dispatch, and emission control strategies for meeting energy demand and environmental, transmission, dispatch, and reliability constraints. We have used the IPM extensively to evaluate the cost and emissions impacts of proposed policies to limit emissions of sulfur dioxide and nitrogen oxides from the electric power sector. The IPM was a key analytical tool in developing the Clean Air Interstate Regulation (CAIR; see 70 FR 25162). However, the IPM capabilities and results are not limited to projections for CAIR States. It includes data for and projects emissions and controls for the electric sector in the contiguous United States. Each IPM model run is based on emissions controls on existing units, State regulations, cost and performance of generating technologies, SO 2 and NO X heat rates, natural gas supply and prices, and electricity demand growth assumptions. This input is updated on a regular basis. We used the IPM to project EGU SO 2 and NO X controls, emissions, and air quality in 2020 considering projected emission controls under the CAIR, Clean Air Mercury Rule (CAMR), and Clean Air Visibility Rule (CAVR). For convenience, we refer to this projection as the CAIR/CAMR/CAVR 2020 Base Case Scenario or, more simply, the Base Case Scenario. The IPM model used for this scenario is IPM v.2.1.9. 5 5 Complete documentation for IPM, including the Base Case Scenario, is available at *http://www.epa.gov/airmarkets/progsregs/epa-ipm/index.html.* See also Docket EPA-HQ-OAR-2005-0163, DCN 01. The IPM v 2.1.9 is based on 2,053 model plants, which represent 13,819 EGUs, including 1,242 coal-fired EGUs. 6 This represents all existing EGUs in the contiguous United States as of 2004, as well as new units that are already planned or committed, and new units that are projected to come online by 2007. The underlying data for these plants is contained in the National Electric Energy Data System (NEEDS), which contains geographic location, fuel use, emissions control, and other data on each existing EGU. NEEDS data for existing EGUs comes from a number of sources, including information submitted to EPA under the Title IV Acid Rain Program and the NO X Budget Program, as well as information submitted to the Department of Energy's (DOE's) Energy Information Agency, on Forms EIA 860 and 767. That is, the underlying data for each existing EGU in the IPM v.2.1.9 is information from an actual EGU in operation as of 2004 that has been submitted to the EPA or the DOE. 6 See the NEEDS 2004 documentation for IPM v.2.1.9 in Exhibit 4-6, which can be found at *http://www.epa.gov/airmarkets/progsregs/epa-ipm/past-modeling.html.* See also Docket EPA-HQ-OAR-2005-0163, DCN 02. The IPM v.2.1.9 model also accounts for growth in the EGU sector that is projected to occur through new builds, including both planned-committed units and potential units. Planned-committed EGUs are those that are likely to come online, because ground has been broken, financing obtained, or other demonstrable factors indicate a high probability that the EGU will come online. Planned-committed units in IPM v.2.1.9 were based on two information sources: RDI NewGen database

(RDI)distributed by Platts ( *http://www.platts.com* ) and the inventory of planned-committed units assembled by DOE, Energy Information Administration, for their Annual Energy Outlook. Potential EGUs are those units that may be built at a future date in response to electricity demand. In IPM v.2.1.9, potential new units are modeled as additional capacity and generation that may come online in each model region. IPM v.2.1.9 also accounts for emission limitations due to State regulations and enforcement actions. It includes State regulations that limit SO 2 and NO X emissions from EGUs. These are included in Appendix 3-2, available at *http://www.epa.gov/airmarkets/progsregs/epa-ipm/docs/bc3appendix.pdf.* 7 The IPM v.2.1.9 includes NSR settlement requirements for the following six utility companies: SIGECO, PSEG Fossil, TECO, We Energies (WEPCO), VEPCO and Santee Cooper. The settlements are included as they existed on March 19, 2004. A summary of the settlement agreements is included in Appendix 3-3 of the IPM documentation and is available *http://www.epa.gov/airmarkets/progsregs/epa-ipm/docs/bc3appendix.pdf.* 8 7 See also Docket EPA-HQ-OAR-2005-0163, DCN 03. 8 See also Docket EPA-HQ-OAR-2005-0163, DCN 03. In the IPM, EPA does not attempt to model unit-specific decisions to make equipment change or upgrades to non-environmental related equipment that could affect efficiency, availability or cost to operate the unit (and thus the amount of generation). Modeling such decisions would require either obtaining or making assumptions about the condition of equipment at units and would greatly increase model size, limiting its applicability in policy analysis. Specifically, IPM does not project that any particular existing EGU will make physical or operational changes that increase its efficiency, generation, or emissions. Therefore, IPM does not predict which particular EGUs will be subject to the major NSR applicability requirements. However, as discussed below, EPA has specially designed inputs to IPM that provide useful information directly related to major NSR applicability requirements. As we discuss below, these inputs are in the form of constraints to the IPM model rather than changes on a unit-by-unit basis. Reliability is a critical element of power plant operation. Reliability is generally defined as whether an EGU is able to operate over sustained periods at the level of output required by the utility. One measure of reliability is availability, the percentage of total time in a given period that an EGU is available to generate electricity. An EGU is available if it is capable of providing service, regardless of the capacity level that can be provided. Availability is generally measured using the number of hours that an EGU operates annually. For example, if an EGU operated 8,760 hours in a particular year, it was 100 percent available. Each year, EGUs are not available for some number of hours due to planned outages, maintenance outages, and forced outages. IPM v.2.1.9 uses information from the North American Electric Reliability Council (NERC)'s Generator Availability Data System

(GADS)to determine the annual availability for EGUs. The GADS database includes operating histories—some dating back to the early 1960's—for more than 6,500 EGUs. These units represent more than 75 percent of the installed generating capacity in the United States and Canada. Each utility provides reports, detailing its units' operation and performance. The reports include types and causes of outages and deratings, unit capacity ratings, energy production, fuel use, and design information. GADS provides a standard set of definitions for determining how to classify an outage on a unit, including planned outages, maintenance outages, and forced outages. The GADS data are reported and summarized annually. A planned outage is the removal of a unit from service to perform work on specific components that is scheduled well in advance and has a predetermined start date and duration (for example, annual overhaul, inspections, testing). Turbine and boiler overhauls or inspections, testing, and nuclear refueling are typical planned outages. A maintenance outage is the removal of a unit from service to perform work on specific components that can be deferred beyond the end of the next weekend, but requires the unit be removed from service before the next planned outage. Typically, maintenance outages may occur any time during the year, have flexible start dates, and may or may not have predetermined durations. For example, a maintenance outage would occur if an EGU experiences a sudden increase in fan vibration. The vibration is not severe enough to remove the unit from service immediately, but does require that the unit be removed from service soon to check the problem and make repairs. A forced outage is an unplanned component failure or other breakdown that requires the unit be removed from service immediately, that is, within 6 hours, or before the end of the next weekend. A common cause of forced outages is boiler tube failure. Each EGU must report the number of hours due to planned outages, maintenance outages, and forced outages to NERC annually. NERC summarized the data for all coal-fired EGUs over the period from 2000-2004 in its Annual Unit Performance Statistics Report. 9 For the years 2001-2004, the average annual planned outage hours for all coal-fired EGUs was 572.09 (about 23 days), the average annual maintenance outage hours for all coal-fired EGUs was 156.27 (about 6 days), and the average annual forced outage hours for all coal-fired EGUs was 348.75 (about 14 days). The total annual unavailable hours for all coal-fired EGUs were 1,087.57, which is 15.1 percent of the total annual hours of 8,760. Based on this data, the IPM v.2.1.9 assumed coal-fired EGUs were 85 percent available. As just noted, of the 1,087.57 total unavailable hours, 348.75 were forced outage hours, which means that coal-fired EGUs were unavailable due to forced outages approximately 4 percent of the hours in a year for the years 2000-2004. 9 The report is available at *http://www.nerc.com/~gads/* and in Docket EPA-HQ-OAR-2005-0163, DCN 04. We recently released a graphic presentation of electric power sector results under CAIR/CAMR/CAVR. Entitled “Contributions of CAIR/CAMR/CAVR to NAAQS Attainment: Focus on Control Technologies and Emission Reductions in the Electric Power Sector,” it is available at *http://www.epa.gov/cair/charts.html.* 10 As this presentation shows, under the CAIR/CAMR/CAVR 2020 Base Case Scenario, local SO 2 and NO X emissions generally decrease, average SO 2 and NO X emission rates decrease, and national SO 2 and NO X emissions decrease. As this document also shows, half of the coal-fired generation is expected to have scrubbers and either SCR or SNCR by 2020. These effects occur throughout the contiguous 48 States, not just in the CAIR States. 10 Also available in Docket EPA-HQ-OAR-2005-0163, DCN 05. We developed IPM scenarios to examine the effects of our proposed regulations, including the maximum hourly emissions increase tests (achievable and achieved, on an input and output basis), on EGU emissions and control technologies. These new IPM scenarios incorporate the parameters used in the IPM model v.2.1.9 that we describe above, including information for the electric sector in the contiguous United States. Thus, these new IPM scenarios revise the parameters in the CAIR/CAMR/CAVR 2020 Base Case Scenario consistent with the way EGUs might operate under the proposed major NSR applicability changes. We call these IPM scenarios the NSR Availability and the NSR Efficiency Scenarios, and discuss them in the following sections. B. NSR Availability Scenarios—Description of the Scenarios We developed two IPM scenarios, which we call the CAIR/CAMR/CAVR NSR Availability Scenarios, or, more simply, the NSR Availability Scenarios, to examine how changes to major NSR applicability under the proposed regulations could, by allowing sources to make repairs or improvements that increase hours of operation, affect emissions and control technology installation. The NSR Availability IPM scenarios are based on the CAIR/CAMR/CAVR 2020 Scenario. The primary difference between the current applicability test and the proposed tests is that under the proposed tests, sources could more readily make repairs or improvements that prevent forced outages, and thereby allow the source to operate more hours. These repairs allow the source to operate at the higher availability level that it achieved before its equipment degraded so much as to cause more forced outages. Some commenters emphasized this difference between the current applicability test and our proposals in the NPR. They explained that because, as we noted at 70 FR 61100, hours of operation are considered in determining annual emissions under the actual-to-projected-actual test in the current major NSR program but have no role in any of our proposed hourly emissions increase test options, an EGU could make a change that does not increase the maximum hourly emissions rate, but does allow the source to run more hours. This change would not trigger review under a maximum hourly emissions increase test in any case, but in some cases might trigger review under the current major NSR emissions increase test based on annual emissions with a 5-year baseline period. These commenters assert that the proposed applicability tests could allow substantial increases in annual emissions without triggering NSR. For several reasons, we believe commenters have overstated the likelihood that substantial increases in annual emissions and resulting deterioration in air quality would occur under the proposed maximum hourly emissions tests, as opposed to the current annual emissions, 5-year baseline test. First, an EGU can increase its hours of operation under the current regulations, as long as it does not make a physical change or change in the method of operation. Information from the RBLC confirms that most EGUs are already permitted to run 8760 hours annually. That is, increases in hours of operation at most EGUs are not a change in the method of operation. They are allowed and frequently occur at many EGUs under the current regulations without triggering major NSR. Second, increases in actual emissions stemming from increases in hours of operation that are unrelated to the change, are not considered in determining projected actual emissions. To the extent that changes resulting in increased hours would occur under the proposed regulatory scheme, any resulting increases in emissions will be diminished as the CAIR and BART programs are implemented and the SO 2 and NO X emissions for most EGUs are capped. As we described in detail in the NPR, 70 FR 61087, national and regional caps limit total actual annual EGU SO 2 and NO X emissions. These caps greatly reduce the significance of hours of operations on actual emissions from the sector nationally. Furthermore, as we indicated in our recent report of the CAIR/CAMR/CAVR, the more hours an EGU operates, the more likely it is to install controls. 11 Moreover, existing synthetic minor limits to avoid major NSR and enforceable limits on hours of operation on a particular EGU as a result of netting would remain in place under any revised emissions increase test. We thus believe the opportunities for many EGUs to significantly increase their emissions through higher hours of operation under a maximum hourly emissions increase test, as compared to the current annual emissions increase test with a 5-year baseline period, are generally limited. 11 See our presentation, “Contributions of CAIR/CAMR/CAVR to NAAQS Attainment: Focus on Control Technologies and Emission Reductions in the Electric Power Sector,” on pages 39 and 43. The presentation is available at *http://www.epa.gov/cair/charts.html.* Also available in Docket EPA-HQ-OAR-2005-0163, DCN 05. Nonetheless, we want to comprehensively examine the outcomes of a maximum hourly emissions increase test, using a robust methodology based on conservative (that is, protective of the environment) estimates. We therefore developed two IPM scenarios, which we call the CAIR/CAMR/CAVR NSR Availability Scenarios, or, more simply, the NSR Availability Scenarios, to examine how changes to major NSR applicability under the proposed regulations could, by allowing sources to make repairs or improvements that increase hours of operation, affect emissions and control technology installation. These IPM scenarios are based on the CAIR/CAMR/CAVR 2020 Scenario, which employs the IPM v.2.1.9 model that we describe in Section III. A. of this preamble, including information for the electric sector in the contiguous United States. Section III A. of this document also contains specific information on the assumptions about EGU assumptions in the IPM v.2.1.9. The NSR Availability Scenarios retain the heat input for each EGU from the CAIR/CAMR/CAVR 2020 Scenario. That is, we did not assume that any existing EGU would increase its capacity in the NSR Availability Scenario. The parameters in the IPM model are based on availability for 6,500 EGUs over the 5-year period from 2000-2004. In the NSR Availability scenarios, however, we changed the parameters in IPM v.2.1.9 consistent with the way EGUs might operate under the more flexible regulations that we are proposing. That is, we assumed that some owner/operators might make changes that increase the hours of operation of some EGUs. It is unlikely that an owner/operator would be able to make changes that reduce the hours that an EGU is unavailable due to a planned outage or a maintenance outage. However, EGUs would be able to make changes that increase their hours of operation as a result of a reduction in the number and length of forced outages. Specifically, with more flexibility concerning the number of hours EGUs operate annually, EGU owner/operators may replace broken-down equipment in an effort to reduce the number of forced outages. Such actions would increase the safety, reliability, and efficiency of EGUs, consistent with one of our primary policy goals for our proposed regulations. Therefore, in the NSR Availability Scenario, we assumed that coal-fired EGUs would be able to make changes that affect forced outage hours in two, alternative, ways:

(1)Coal-fired EGUs would reduce their forced outage hours by half (2 percent increase in availability); and

(2)coal-fired EGUs would have no forced outage hours (4 percent increase in availability). Therefore, in the first model run, we increased the coal-fired availability by 2 percent, from 85 percent to 87 percent annually. In the second NSR EGU run, we increased coal-fired availability by 4 percent, to 89 percent annually. We believe it is unlikely that an EGU would be able to make repairs that completely eliminate forced outage hours. However, we wanted a robust examination of changes that could impact emissions and air quality. 12 We therefore made the very conservative assumption to increase to EGU availability by 2 percent and 4 percent over the actual historical hours of operation for 6,500 EGUs over the years 2000-2004. All other information in the NSR Availability Scenarios is the same as that in IPM v.2.1.9 used for the CAIR/CAMR/CAVR Scenario. 12 While we believe it is most likely that an EGU would increase its hours of operation under these proposed regulations due to reducing the number of hours that the EGU is unavailable due to forced outage hurs, the analysis is applicable to increaes in hours of operation for other reasons. The NERC GADS calculates the average availability for an EGU by taking the actual total number of unavailable hours in a given year for all EGUs and dividing it evenly among the total number of EGUs. Based on the GADS data, the IPM assumes an upper bound of 85 percent availability for coal-fired EGUs. In GADS data for the years 2000-2004, some EGUs actually had more than 85 percent availability and some actually had less. The particular EGUs that had greater than 85 percent availability and less than 85 percent varied from year to year. Similarly, by eliminating forced outages, some EGUs could increase their availability by more than 2-4 percent and some EGUs could increase their availability by less than 2-4 percent. Likewise, the particular EGUs that were able to reduce their forced outage hours would also vary from year to year. For modeling purposes, it thus makes more sense to assume an average availability than to determine unit-by-unit availabilities for each and every EGU in a given year. Our approach based on average availability is also consistent with actual historical operations at particular EGUs and plantsites, which are most directly related to local emissions and air quality. Variation in actual annual hours of operation at a given EGU and at given plantsites do occur under current major NSR applicability. It is not uncommon for actual hours of operation for a particular EGU to vary by 348 hours (4 percent availability) or more from year to year. It is also not uncommon for the variation in actual hours of operation to occur among EGUs at a particular plantsite by 4 percent or more from year to year. For example, in one year Unit A might run 7,800 hours and Unit B might run 7,400 hours. In the next year Unit B might run 7,800 hours and Unit A 7,400 hours. This pattern further supports an approach based on average availability for estimating local emissions. Changes in average availability, rather than the absolute availability of any given EGU, thus is appropriate for analyzing the impact of proposed changes to major NSR applicability. C. NSR Availability Scenarios—Discussion of SO 2 and NO X Results This section discusses the SO 2 and NO X control device installation, national emissions, local emissions, and impact on air quality for EGUs under the NSR Availability Scenario. 1. *SO* 2 *and NO* X *Control Device Installation.* As Table 2 shows, the NSR Availability Scenarios project retrofitting of more control devices than under the CAIR/CAMR/CAVR 2020 Scenario. 13 This result occurs whether hours of operation increase by 2 percent or by 4 percent. Significantly, under the 4 percent scenario, more Gigawatts

(GW)of electric capacity are controlled than under the 2 percent scenario. For example, under NSR Availability 4%, there is 3.63 more GW of national EGU capacity with scrubbers than under CAIR/CAMR/CAVR 2020. These results are consistent with what IPM generally projects, as noted above; that is, the more hours an EGU operates, the more likely it is to install controls. 14 We thus conclude that the more hours an EGU operates, the more likely it is to install controls, regardless of whether the major NSR applicability test is on an hourly basis or an annual basis. 13 Available in Docket EPA-HQ-OAR-2005-0163, DCN 06. (System Summary Report for NSR Availability). 14 See our presentation, “Contributions of CAIR/CAMR/CAVR to NAAQS Attainment: Focus on Control Technologies and Emission Reductions in the Electri Power Sector,” on pages 39 and 43. The presentation is available at *http://www.epa.gov/cair/charts.html.* Also available in Docket EPA-HQ-OAR-2005-0163, DCN 05. Table 2.—2020 National EGUs With Emission Controls Under NSR Availability Scenarios Emission control type EGUs with additional controls compared to 2004 base case NSR availability 2% NSR availability 4% EGUs with additional controls compared to CAIR/CAMR/CAVR 2020 NSR availability 2% NSR availability 4% FGD 15 109.62 GW 111.53 GW 1.71 GW 3.63 GW SCR 16 73.47 GW 73.92 GW 0.62 GW 1.07 GW 2. *SO* 2 *and NO* X *National Emissions.* As Table 3 shows, the NSR Availability Scenarios project essentially no changes in SO 2 or NO X emissions nationally by 2020 as compared to emissions under the CAIR/CAMR/CAVR 2020 Scenario. 17 This result is consistent with the fact that under the NSR Availability Scenarios, the amount of controls increases, compared to CAIR/CAMR/CAVR 2020, and we find that these associated emissions decreases are offset by the emissions increases associated with the reduced forced outages and higher production levels. 15 15 FGD is flue gas desulfurization, also known as scrubbers, for control of SO 2 emissions. 16 SCR is selective catalytic reduction, used for control of NO X emissions. 17 CAIR/CAMR/CAVR SO 2 and NO X emissions available in Docket EPA-HQ-OAR-2005-0163, DCN 14. [EPA 219b_BART 13_2020_Pechan.xls]. NSR SO 2 and NO X Availability Emissions available in Docket EPA-HQ-OAR-2005-0163, DCN 14. [EPA 219b_NSR_OAQPS_5_Pechan_2020.xls] National totals for CAIR/CAMR/CAVR and NSR Availability include new units (IPM new units and planned-committed units). Table 3.—National EGU Emissions Under NSR Availability Scenarios Compared to CAIR/CAMR/CAVR 2020

(tpy)Pollutant CAIR/CAMR/CAVR NSR 4% NSR 2% Change-NSR 4% Change-NSR 2% SO 2 4,277,000 4,271,000 4,261,000 −6,000 <1% decrease −16,000 <1% decrease. NO X 1,989,000 2,016,000 2,003,000 28,000 1% increase 14,000 1% increase. As noted above, the NSR Availability Scenarios examine emissions changes based on very conservative estimates developed using actual historical hours of operation for 6,500 EGUs over the years 2000-2004. We conclude that to any extent that EGU hours of operation increase under a maximum hourly test, as opposed to the current average annual 5-year baseline test, such increased hours of operation would not increase national EGU SO 2 emissions. The increased availability would have very little effect on national NO X emissions, with approximately one percent increase nationally. This conclusion as to emissions in the contiguous 48 States supports extending the proposed rules nationwide, instead of limiting them to the States in the CAIR region. 3. *SO* 2 *and NO* X *Local Emissions Impact.* To examine the effect of the maximum hourly and 5-year baseline tests on local air quality, we compared 2020 county-level EGU SO 2 and NO X emissions under the CAIR/CAMR/CAVR 2020 and NSR Availability (4%) Scenario. 18 We describe these changes in detail in Chapter 4 of the Technical Support Document (TSD). As the TSD shows, the proposed revised NSR applicability tests would, under the very conservative assumptions described above, result in a somewhat different pattern of local emissions, with some counties experiencing reductions, some experiencing increases, and some remaining the same. This pattern is consistent with the fact that most coal-fired EGUs are in the CAIR region and therefore subject to regulations implementing the CAIR cap. According to the DOE's Energy Information Agency, for the years 2003-2004, approximately 80 percent of the coal steam electric generation and 75 percent of all electric generation occurred in CAIR States. 19 Furthermore, EGUs are subject to national SO 2 caps under the Acid Rain Program. 18 CAIR/CAMR/CAVR SO2 and NO X emissions available in Docket EPA-HQ-OAR-2005-0163, DCN 14. [EPA 219b_BART 13_2020_Pechan.xls]. NSR SO2 and NO X Availability Emissions available in Docket EPA-HQ-OAR-2005-0163, DCN 14. [EPA 219b_NSR_OAQPS_5_Pechan_2020.xls]. 19 Available in Docket EPA-HQ-OAR-2005-0163, DCN 08. (2000-2004 Electric Generation). For these reasons, an increase in emissions in one area results in a decrease elsewhere. This dynamic occurs regardless of the major NSR applicability test for existing EGUs. Nonetheless, the NSR Availability Scenario demonstrates that this pattern continues to occur when increased availability is assumed, such as we assume for present purposes would occur under the proposed maximum hourly and 5-year baseline tests. 4. *SO* 2 *and NO* X *Impact on Air Quality.* In Chapter 4 of the TSD, we compare projected county-level SO 2 and NO X emissions under NSR Availability 4% to those projected under CAIR/CAMR/CAVR 2020. Projected increases in emissions of these pollutants due to increased hours of operation at EGUs under the NSR Availability (4%) Scenario are small in magnitude and sparse across the continental U.S. Therefore, we would expect these increases to cause minimal local ambient effect, both directly on SO 2 and NO X emissions and as precursors to formation of PM 2.5 (SO 2 and NO X emissions) and ozone (NO X emissions). Because many counties experience decreases in emissions, we would further expect any local ambient effects from increased emissions to be somewhat diminished because of the emissions decreases elsewhere that yield regionwide improvements in air quality, including SO 2 , NO X , PM 2.5 , and ozone. We expect similar outcomes with respect to the NSR Availability (2%) Scenario where the emissions changes are smaller and constitute a pattern of increases and decreases that is similar to that of the NSR Availability (4%) Scenario. Based on the spatial distribution of SO 2 and NO X emissions changes as shown in the TSD, we would also expect patterns of air quality changes respectively under the NSR Availability (4%) Scenario to be consistent with projections under CAIR/CAMR/CAVR in 2020. We thus believe that the local air quality under this proposed regulations would be commensurate with that under the CMAQ modeling based on CAIR/CAMR/CAVR 2020 Scenario emissions projections. 20 That is, we believe local air quality under these proposed regulations would be commensurate with air quality we are projecting for 2020 absent a change to the existing major NSR emissions increase test. 20 As we describe in more detail in the TSD, the CAIR/CAMR/CAVR modeling is available on our website and in the docket for this rulemaking. The CMAQ modeling was conducted as part of EPA's multipollutant legislative assessment and the results are available in the Multipollutant Regulatory Analysis: The Clean Air Interstate Rule, The Clean Air Mercury Rule, and the Clean Air Visibility Rule (EPA promulgated rules, 2005) at *http://www.epa.gov/airmarkets/progsregs/cair/multi.html.* The specific technical support document on air quality modeling for CAIR/CAMR/CAVR, Technical Support Document for EPA's Multipollutant Analysis; Methods for Projecting Air Quality Concentrations for EPA's Multipollutant Analysis of 2005, is available at *http://www.epa.gov/airmarkets/progsregs/cair/multi.html* by clicking on the Technical Support Document—Air Quality Modeling Technique used for Multi-Pollutant Analysis link. It is also available in Docket EPA-HQ-OAR-2005-0163, DCN 09. Information on ozone modeling is available at *http://www.epa.gov/airmarkets/progsregs/cair/multi.html* through the Air quality Modeling Results Excel File link. It is also available in Docket EPA-HQ-OAR-2005-0163, DCN 16. D. NSR Availability Scenarios—Discussion of PM 2.5 , VOC, and CO Results We used the NSR Availability Scenarios that we describe in Section III.B of this preamble to examine the PM 2.5 , VOC, and CO emissions and air quality impacts of the proposed hourly emissions increase test. This Section provides the results of our analyses. 1. *PM* 2.5 *, VOC, and CO Control Device Installation.* As we discuss in the PM 2.5 NAAQS RIA, our NEEDS indicates that as of 2004, 84 percent of all coal-fired EGUS have an ESP in operation, about 14 percent of EGUs have a fabric filter, and roughly 2 percent have wet PM 2.5 scrubbers. 21 Gas-fired turbines are clean burning and BACT/LAER for these EGUs is no control. BACT/LAER for VOC and CO is good combustion control. Furthermore, EGU owner/operators have natural incentives to reduce VOC and CO emissions. VOC and CO emissions are products of incomplete combustion. These compounds are discharged into the atmosphere when fuel remains unburned or is burned only partially during the combustion process. Fuel is a significant portion of total costs for EGUs, particularly for older EGUs where capital costs are paid off. EGU owner/operators have in fact improved combustion practices to increase combustion efficiency, thereby limiting unburned fuel. Cost effective operation is especially desirable in areas where a cap and trade program increases the cost of operation by creating a cost to pollute, as is the case in the CAIR region where most ozone and PM 2.5 nonattainment areas are located. 21 *See* the Regulatory Impact Analysis for 2006 NAAQS for Particle Pollution Chapter 3—Controls, page 34. Available at *http://www.epa.gov/ttn/ecas/ria.html* and in Docket EPA-HQ-OAR-2005-0163, DCN 10. 2. *PM* 2.5 *, VOC, and CO National Emissions.* As Table 4 shows, EGUs contribute a small percentage of national PM 2.5 , CO, and VOC emissions. 22 22 CO emissions information from Clear Air Interstate Rule Emissions Inventory Technical Support Document, available at *http://www.epa.gov/interstateairquality/pdfs/finaltech01.pdf.* CO emissions rounded to nearest thousand ton level. Also available in Docket EPA-HQ-OAR-2005-0163, DCN 11. PM2.5 and VOC emissions information from PM2.5 NAAQS RIA, available at *http://www.epa.gov/ttn/ecas/ria.html.* Also available in Docket EPA-HQ-OAR-2005-0163, DCN 10. Table 4.—EGU Emissions As Percent of 2020 National Emissions

(tpy)Pollutant EGU National EGU as % National PM 2.5 533,000 6,206,000 8.6 VOC 45,000 12,414,000 0.4 CO 718,000 82,852,000 0.9 As Table 5 shows, the NSR Availability Scenarios project essentially no changes in PM 2.5 , VOC, or CO emissions nationally by 2020 as compared to emissions under the CAIR/CAMR/CAVR Scenario. 23 23 Emissions information available in Docket EPA-HQ-OAR-2005-0163, DCN 17. [NSR Availability PM 2.5 , VOC, and CO] National totals for CAIR/CAMR/CAVR and NSR Availability include new units (IPM new units and planned-committed units). Table 5.—National EGU Emissions Under NSR Availability Scenario Compared to CAIR/CAMR/CAVR 2020

(tpy)Pollutant CAIR/CAMR/CAVR NSR 4% Change-NSR 4% PM 2.5 526,642 524,245 (2,397) VOC 45,020 45,391 371 CO 716,184 711,254 (4,930) As described in Section III.B of this preamble, the NSR Availability Scenarios examine emissions changes based on very conservative estimates developed using actual historical hours of operation for 6,500 EGUs over the years 2000-2004. We conclude that to any extent that EGU hours of operation increase under a maximum hourly emissions increase test, as opposed to the current average annual 5-year baseline test, such increased hours of operation would not increase national EGU PM 2.5 and CO emissions. The increased availability would have very little effect on national VOC emissions, with less than half of a percent increase nationally. This conclusion as to emissions in the contiguous 48 States supports extending the proposed rules nationwide, instead of limiting them to the States in the CAIR region. 3. *PM* 2.5 , *VOC, and CO Local Emissions Impact.* To examine the effect of the maximum hourly emission increase tests on local air quality, we compared 2020 county-level EGU PM 2.5 , VOC, and CO emissions under the CAIR/CAMR/CAVR 2020 and NSR Availability (4%) Scenario. 24 We describe these changes in detail in Chapter 4 of the TSD. 24 Available in Docket EPA-HQ-OAR-2005-0163, DCN 17. [NSR Availability PM 2.5 , VOC, and CO]. As Chapter 4 of the TSD shows, projected PM 2.5 , VOC, and CO emissions changes under the proposed revised NSR applicability tests would result in a somewhat different pattern of local emissions, with some counties experiencing reductions, some experiencing increases, and some remaining the same compared to emissions changes under CAIR/CAMR/CAVR 2020. 4. *PM* 2.5 , *VOC, and CO Impact on Air Quality.* As Chapter 4 of the TSD shows, projected increases in EGU PM 2.5 , VOC, and CO emissions due to increased hours of operation at EGUs under the NSR Availability (4%) Scenario are small in magnitude and sparse across the continental U.S. Therefore, we would expect these increases to cause minimal changes in local ambient effect in comparison to that observed under CAIR/CAMR/CAVR for PM 2.5 and ozone (for which VOC is a precursor). Because many counties experience decreases in emissions, we would further expect any local ambient effects from increased emissions to be somewhat diminished because of the emissions decreases elsewhere that yield regionwide improvements in air quality. We have not modeled national or regional air quality improvements in CO concentrations. As noted in Table 4, however, EGU CO emissions are less than one percent of national CO emissions. According to our latest analysis, 2020 national CO emissions are projected to be 19,892,017 tons less than 2001 national CO emissions. 25 Local CO emissions are generally a function of traffic congestion from mobile sources. For these reasons, EGUs do not contribute significantly to national or local CO emissions. 25 See the Clean Air Interstate Rule Emissions Inventory Technical Support Document on pgs 7 and 38 at *http://www.epa.gov/cair/pdfs/finaltech01.pdf.* Also available in Docket EPA-HQ-OAR-2005-0163, DCN 11. The projected increases in CO emissions due to increased hours of operation at EGUs under the NSR Availability (4%) Scenario are small in magnitude and sparse across the continental U.S. We would expect these increases to cause minimal local ambient effect on CO. Therefore, based on the small increases and sparse distribution of CO emissions compared to CAIR/CAMR/CAVR 2020, and the small contribution of EGU emissions to national and local CO levels, we project no notable local impact on air quality from EGU CO emissions from NSR Availability 4%. E. NSR Efficiency Scenario. We designed another IPM model run to evaluate whether efficiency improvements that sources may make as a result of these proposed regulations would lead to local emissions increases and adverse effects on ambient air quality. Aside from independent factors such as climate and economy, efficiency is a primary determinant of the hours of operation of a given EGU. Neither the current annual emissions increase test nor any of the proposed EGU emission increase test alternatives directly measure an EGU's efficiency. However, the output-based alternatives (Alternatives 2, 4, and 6), which are expressed in a lb/KWh format that measures mass emissions per unit of electricity, are closely related to an EGU's efficiency. Thus, an output-based test encourages efficient units, which has well-recognized benefits. We anticipate that the output-based alternatives in particular, and the other alternatives to a lesser extent, could have the effect of encouraging EGUs to increase their efficiency. For these reasons, we focused on efficiency to examine whether an hourly test could result in emissions increases as compared to the annual emissions increase test. We call this run the NSR Efficiency Scenario. We assumed the least efficient EGUs (approximately 35% of all EGUs) would increase their efficiency by 4 percent. We ran the IPM with this scenario (4 percent efficiency increase for 371 coal-fired EGU, no increase in physical and operating existing capacity) and compared the results to the CAIR/CAVR/CAMR IPM model. We found approximately the same results from the NSR Efficiency Scenario as from the NSR Availability Scenarios. We describe the results of the NSR Efficiency analysis in detail in Chapter 5 of our TSD. 1. *Control Device Installation.* As Table 6 shows, the NSR Efficiency Scenario projects retrofitting of more control devices for SO 2 and NO X than under the CAIR/CAMR/CAVR 2020. 26 These results are consistent with what IPM generally projects. The more efficient an EGU is, the more cost effective it is to operate. The more cost effective it is to operate, the more hours it will operate. The more hours it operates, the more likely it is to install controls. 27 We thus conclude that the more efficiently an EGU operates, the more likely it is to install controls, regardless of whether the major NSR applicability test is on an hourly basis or an annual basis with a 5-year baseline. 26 Information from system summary report for the NSR Efficiency IPM Run. Available in Docket EPA-HQ-OAR-2005-0163, DCN 13 (System Summary Report for NSR Efficiency). CAIR/CAMR/CAVR emissions available in Docket EPA-HQ-OAR-2005-0163, DCN 14 [EPA 219b_BART 13_2020_Pechan]. 27 See our presentation, “Contributions of CAIR/CAMR/CAVR to NAAQS Attainment: Focus on Control Technologies and Emission Reductions in the Electric Power Sector,” on pages 39 and 43. The presentation is available at *http://www.epa.gov/cair/charts.html.* Also available in Docket EPA-HQ-OAR-2005-0163, DCN 05. Table 6.—2020 National EGUs with Emission Controls-NSR Efficiency Emissions control type EGUs with additional controls compared to 2004 controls case EGUs with additional controls compared to CAIR/CAMR/CAVR 2020 FGD 109 GW 1.5 GW. SCR 74 GW 1.0 GW. 2. *National Emissions.* As Table 7 shows, the NSR Efficiency Scenarios project reductions in SO 2 and NO X emissions nationally by 2020 as compared to emissions under the Base Case Scenario. 28 This result is consistent with the fact that under the NSR Efficiency Scenario, the amount of controls increases, compared to the Base Case. 28 CAIR/CAMR/CAVR SO 2 and NO X emissions available in Docket EPA-HQ-OAR-2005-0163, DCN 14 [EPA 219b_BART 13_2020_Pechan]. NSR Efficiency SO 2 and NO X Emissions available in Docket EPA-HQ-OAR-2005-0163, DCN 07 [EPA 219b_NSR_OAQPS_ 2a_Pechan_2020_(to EPA) 4-27-06]. NSR Efficiency PM 2.5 , VOC and CO Emissions available in Docket EPA-HQ-OAR-2005-0163, DCN 18. National totals for CAIR/CAMR/CAVR and NSR Efficiency include new units (IPM new units and planned-committed units). Table 7.—National EGU Emissions Under NSR Efficiency Scenario Compared to CAIR/CAMR/CAVR 2020

(tpy)Pollutant Total Emissions Under CAIR/CAMR/CAVR Total Emissions Under NSR efficiency Emissions Change Under NSR Efficiency Compared to CAIR/CAMR/CAVR SO 2 4,277,000 4,265,000 −12,000 NO X 1,989,000 1,984,000 −5,000 PM 2.5 526,642 529,647 3,005 VOC 45,019 44,835 −184 CO 716,184 711,314 −4,870 As noted above, the NSR Efficiency Scenarios examine emissions changes based on very conservative estimates of technically feasible improvements in efficiency. We conclude that to any extent that EGU efficiency increases under a maximum hourly emissions increase test, as opposed to the current average annual 5-year baseline test, such increased efficiency would not increase national EGU SO 2 , NO X , VOC, and CO emissions. The increased efficiency would have very little effect on national PM 2.5 emissions, with less than half of a percent increase nationally. This conclusion as to emissions in the contiguous 48 States supports extending the proposed rules nationwide, instead of limiting them to the States in the CAIR region. 3. *Local Emissions and Air Quality.* The NSR Efficiency Scenario projects a somewhat different pattern of local emissions compared to CAIR/CAMR/CAVR 2020. The NSR Efficiency Scenario projects decreases in many counties compared to CAIR/CAMR/CAVR 2020. Where there are projected increases in local SO 2 , NO X , PM 2.5 , VOC, and CO emissions, they are small in magnitude and sparse across the continental United States. Therefore, we would expect these increases to cause minimal local ambient impact effect. We describe the NSR Efficiency Scenario analysis and its results in detail in Chapters 5 and 6 our TSD. IV. Proposed Regulations for Option 1: Hourly Emissions Increase Test Followed By Annual Emissions Test In the NPR, we did not propose to include, along with any of the revised NSR emissions tests, any provisions for computing a significant increase or a significant net emissions increase, although we solicited comment on retaining such provisions. Many commenters preferred to retain an annual emissions increase test in addition to the hourly emissions increase test. We are proposing Option 1, in which the hourly emissions increase test would be followed by the actual-to-projected-actual emissions increase test and the significant net emissions increase test in the current regulations. Specifically, changes that will not increase the hourly emissions rate-such as those to make repairs to reduce the number of forced outages-do not require further review under Option 1. However, if there would be an hourly emissions increase following a physical change or change in the method of operation, the proposed rule requires a determination of whether a significant increase or a significant net emissions increase would occur. Thus, Option 1 retains the netting provisions in the current regulations. Option 1 also facilitates improvements for efficiency, safety, and reliability, without adverse air quality effects (as the above discussion of the IPM and air quality analyses indicates). We are proposing that Option 1 would apply to all EGUs. We are also requesting comment on whether Option 1 should be limited to the geographic area covered by CAIR, or to the geographic area covered by both CAIR and BART. We are also proposing that the Option 1 would apply to all regulated NSR pollutants. However, we also request comment on whether Option 1 should be limited to increases of SO 2 and NO X emissions. Under Option 1, the major NSR program would include a four-step process (with the second step revised as proposed, while retaining the other steps):

(1)Physical change or change in the method of operation as in the current major NSR regulations;

(2)hourly emissions increase test (maximum achieved hourly emissions rate or maximum achievable hourly emissions rate, each with output-based alternatives);

(3)significant emissions increase as in the current major NSR regulations; and

(4)significant net emissions increase as in the current major NSR regulations. For a modification to occur under Option 1, under Step 1, a physical change or change in the method of operation must occur, and, under Step 2, that change must result in an hourly emissions increase at the existing EGU. If a post-change hourly emissions increase is projected, Option 1 retains the requirements for a significant emissions increase and a significant net emissions increase. In such cases, under Step 3, the owner/operator would determine whether an emissions increase would occur using the actual-to-projected-actual annual emissions test in the current regulations. There would be no conversion from annual to hourly emissions. Finally, in Step 4, as in the current regulations, if a significant emissions increase is projected to occur, the source would still not be subject to major NSR unless there was a determination that a significant net emissions increase would occur. Table 8 summarizes these four steps. Table 8.—Major NSR Applicability for Existing EGUs Under Option 1 Option 1 Step 1: Physical Change or Change in the Method of Operation. Step 2: Hourly Emissions Increase Test. • Alternative 1—Maximum achieved hourly emissions; statistical approach; input basis. • Alternative 2—Maximum achieved hourly emissions; statistical approach; output basis. • Alternative 3—Maximum achieved hourly emissions; one-in-5-year baseline; input basis. • Alternative 4—Maximum achieved hourly emissions; one-in-5-year baseline; output basis. • Alternative 5—NSPS test—maximum achievable hourly emissions; input basis. • Alternative 6—NSPS test—maximum achievable hourly emissions; output basis. Step 3: Significant Emissions Increase Determined Using the Actual-to-Projected-Actual Emissions Test as in the Current Rules. 29 Step 4: Significant Net Emissions Increase as in the Current Rules. Option 1 would not alter the provisions in the current major NSR regulations pertaining to a significant emissions increase and a significant net emissions increase. Therefore, the regulations would retain the definitions of net emissions increase, significant, projected actual emissions, and baseline actual emissions. [See § 51.166(b)(3), § 51.166(b)(23), § 51.166(b)(40), § 51.166(b)(47), and analogous provisions in 40 CFR 51.165, 52.21, 52.24, and appendix S to 40 CFR part 51.] The regulations would also retain all provisions in the current regulations that refer to major modifications, including, but not limited to, those in § 51.166(a)(7)(i) through (iii), (b)(9), (b)(12), (b)(14)(ii), (b)(15), (b)(18), (i)(1) through (9), (j)(1) through (4), (m)(1) through (3), (p)(1) through (7), (r)(1) through (7), and (s)(1) through

(4)analogous provisions in 40 CFR 51.165, 52.21, 52.24, and appendix S to 40 CFR part 51. 29 Steps 3 and 4 only apply when a unit fails Step 2. (That is, it is determined that an hourly emissions increase would occur.) We are also proposing regulatory language containing the two-step modification provisions. (Steps 1 and 2 of Option 1, as outlined in Table 8.) As we noted at 70 FR 61088, you can find the regulatory text defining “modification” within the NSPS general provision regulations at 40 CFR 60.2 and 60.14. Substantially mirroring CAA 111(a)(4), § 60.2 contains a general description of the two components an activity must satisfy to qualify as a modification. § 60.14 elaborates on the general description contained in § 60.2 by more precisely defining how you measure the amount of pollution that results from an activity, and listing activities that do not qualify as physical changes or changes in the method of operation. (that is, the “increases” component of the modification definition, or Step 2.) As we proposed at 70 FR 61090, we have added a definition of modification in § 51.167, which mirrors the provisions in § 60.2. We are also proposing to add requirements defining the “increases” component of “modification” to the major NSR rules, analogous to the provisions in § 60.14. Specifically, the definition of modification in the proposed rules requires that an increase in the amount of regulated NSR pollutants must be determined according to the provisions in paragraph

(f)of § 51.167. Under Option 1, Alternatives 1-4, we are proposing to define the “increases” component to mean maximum hourly emissions rate achieved. That is, if a physical change or change in the method of operation (as defined under existing regulations, which we are not proposing to change) is projected to result in an increase in the maximum hourly emissions rate expected to be achieved over the maximum hourly emissions rate actually achieved at the EGU prior to the change, a modification would occur. The requirements for the maximum achieved alternatives are in proposed § 51.167(f)(1), Alternatives 1-4. Under Option 1, Alternatives 5 and 6, we are proposing to define the “increases” component to mean maximum achievable hourly emissions. For maximum achievable hourly emissions on an input basis, we are proposing to add a definition of the “increases” component of “modification” that substantially mirrors the definition of the “increases” component of “modification” in the NSPS provisions, which is found in 40 CFR 60.2. These requirements are in proposed § 51.167(f)(1), Alternative 5. For the maximum achievable alternative on an output basis (Alternative 6), the requirements are in proposed § 51.167(f)(1), Alternative 6. To incorporate the two-step modification provisions under Option 1, we are proposing to add two new sections to the major NSR program rules. The first, 40 CFR 51.167, would specify the requirements that State Implementation Plans must include for major NSR applicability at existing EGUs, including those for both attainment and nonattainment areas. (Proposed rule language for 40 CFR 51.167 accompanies this SNPR.) The second, 40 CFR 52.37, would contain the requirements for major NSR applicability for existing EGUs where we are the reviewing authority. Although the proposed amendatory language is for 40 CFR 51.167, we are proposing that the same requirements would apply under 40 CFR 52.37, differing only in that the Administrator is the reviewing authority, rather than the State, local, or tribal agency. Although this notice does not contain specific regulatory language, we are proposing that either 40 CFR 51.167 or 40 CFR 52.37, as appropriate, would contain the requirements for emissions increases at EGUs for all sections of the Code of Federal Regulations that contain the major NSR program, including 40 CFR 51.165, 51.166, 52.21, 52.24, and appendix S of 40 CFR part 51, as well as any regulations we finalize to implement major NSR in Indian Country. We are also proposing to make the same changes where necessary to conform the general provisions in parts 51 and 52 to the requirements of the major NSR program, such as in the definition of modification in 40 CFR 52.01. In addition, we are proposing to remove all applicability requirements for existing EUSGUs in all sections of the CFR that contain the major NSR program, as the EGU requirements would supersede these requirements. In the NPR, we proposed three alternatives for the hourly emissions increase test-the NSPS maximum achievable hourly emissions test, maximum achieved hourly emissions, and an output-based measure of hourly emissions. As some commenters noted, we did not give much detail about the output-based measure of hourly emissions. In this SNPR, we are recasting what we proposed in the NPR for the output-based methodology. In this SNPR, both the maximum achieved hourly emissions test and the maximum achievable hourly emissions test include output-based alternatives. Specifically, we are proposing two broad approaches under Option 1:

(1)A maximum achieved hourly emissions test; and

(2)a maximum achievable hourly emissions test. If we adopt the maximum achieved hourly emissions test, we may require that it be expressed in an input-based format (lb/hr) or an output-based format (lb/MWh). Alternatively, and as we did in our recently promulgated NSPS for combustion turbines (40 CFR part 60, subpart KKKK, July 6, 2006), we may also adopt both an input and output based format. If we adopt both formats, sources, at their choice, would be able to implement the hourly emissions test in either input-or output-based formats. Likewise, if we adopt the maximum achievable hourly emissions test, it may be expressed in an input-based format (lb/hr), an output-based format (lb/MWh), or both. We are also proposing two methods for computing maximum achieved emissions:

(1)Statistical approach; and

(2)one-in-5-year baseline. In terms of the regulatory language that accompanies this notice, we are proposing six alternatives for determining whether a physical or operational change at an EGU is a modification. These alternatives are summarized in Table 9 and can be found at proposed § 51.167(f)(1). In Sections IV.A and B below, we describe our two approaches for the hourly emissions increase test in more detail. The regulatory language proposed for these approaches (that is, maximum achieved and maximum achievable hourly emissions increase tests) would apply under both Option 1 and Option 2. Option 2, as described below in Section V, would eliminate the significance and netting steps that are included under current applicability regulations, whereas Option 1 would not eliminate the significance and netting steps. This action includes proposed rule language for Option 1. A. Test for EGUs Based on Maximum Achieved Emissions Rates As one approach, we are proposing that the hourly emissions increase test would be based on an EGU's historical maximum hourly emissions rate. We call this approach the maximum achieved hourly emissions test. Under this approach, an EGU owner/operator would determine whether an emissions increase would occur by comparing the pre-change maximum actual hourly emissions rate to a projection of the post-change maximum actual hourly emissions rate. We request comment on all alternatives for the maximum achieved hourly emissions increase test (see proposed Alternatives 1 through 4 for § 51.167(f)(1)), as well as on other possible approaches for determining maximum achieved hourly emissions. In particular, we request comments on whether the proposed maximum achieved methodologies would account for variability inherent in EGU operations and air pollution control devices. 1. *Determining the Pre-Change Emissions Rate.* The pre-change maximum actual hourly emissions rate would be determined using the highest rate at which the EGU actually emitted the pollutant within the 5-year period immediately before the physical or operational change. Thus, the maximum achieved emissions test is based on specific measures of actual historical emissions during a representative period. We are proposing four alternatives for determining the pre-change maximum hourly emissions rate actually achieved, which we denote here and in the proposed rule language as Alternatives 1 through 4. As shown above in Table 9, these alternatives consist of two different methods for determining the pre-change maximum emissions rate ( *i.e.* , the statistical approach and the one-in-5-year baseline approach), each of which can be applied on an input (lb/hr) basis or output (lb/MWh) basis. In addition to these four alternatives, which are included in the proposed rule language at § 51.167(f)(1), we are proposing that the source would have a choice of implementing the test on either an input-or output-basis. Proposed Alternatives 1 and 2 (input basis and output basis, respectively) utilize a statistical approach for you to use to analyze continuous emission monitoring system

(CEMS)or predictive emission monitoring system

(PEMS)data from the 5 years preceding the physical or operational change to determine the maximum actual pollutant emissions rate. The statistical approach utilizes actual recorded data from periods of representative operation to calculate the maximum actual emissions rate associated with the pre-change maximum actual operating capacity in the past 5 years. The maximum actual emissions rate is expressed as the upper tolerance limit (UTL). The UTL concept and equations are derived from work conducted by the National Bureau of Standards (now the National Institute of Standards and Technology (NIST)). 30 30 Mary Gibbons Natrella (1963). “Experimental Statistics,” NBS Handbook 91, U.S. Department of Commerce. This work is available on the Internet at *http://www.itl.nist.gov/div898/handbook/prc/section2/prc263.htm.* In conducting the analysis, you would select a period of 365 consecutive days from the 5 years preceding the change. Next, you would compile a data set (for example, in a spreadsheet) for the pollutant of interest with the hourly average CEMS or PEMS (as applicable) measured emissions rates (in lb/hr for Alternative 1, or lb/MWh for Alternative 2) and corresponding heat input data for all of the EGU operating hours in that period. From that data set, you would delete selected hourly data from this 365-day period in accordance with certain data limitations. Specifically, you would delete data from periods of startup, shutdown, and malfunction; periods when the CEMS or PEMS was out of control (as described below); and periods of noncompliance, according to proposed § 51.167(f)(2) as explained below in Section IV.A.3 on data limitations. The next step in the procedure is to sort the data set for the remaining operating hours by heat input rates. You would then extract the hourly data for the 10 percent of the data set corresponding to the highest heat input rates for the selected period. The next step is to apply basic statistical analyses to the extracted CEMS or PEMS hourly emissions rate data, calculating the average emissions rate, the standard deviation, and finally the UTL. See the proposed rule language for Alternatives 1 and 2 at § 51.167(f)(1) for the specifics of the calculations. As included in the proposed rule, Alternatives 1 and 2 calculate the UTL for the 99.9th percentile of the population (of hourly emissions rate readings) at the 99 percent confidence level. That is, under the proposed methodology we would expect, with a 99 percent confidence level, 99.9 percent of the hourly emissions rate data to be less than the UTL value. We are also proposing a 90 percentile of the population (of hourly emissions rate readings). We request comment on these proposed levels. In particular we request comment on whether a 99 or 90 percentile of the population (of hourly emissions rate readings) would be more appropriate. We also request comment on whether a 95 or 90 percent confidence level would be more appropriate. Alternatives 1 and 2 focus on EGU emissions during periods of representative operation at the greatest actual operating capacity of the unit, as demonstrated over the preceding 5 years (that is, the capacity that the unit actually utilized in the preceding 5 years). We believe that this is appropriate for a test with the purpose of, essentially, determining whether a physical or operational change increases the capacity of the unit, or the capacity utilization of the unit, over that achieved in the past 5 years. We further believe that the statistical approach properly accounts for the variability inherent in EGU operations and air pollution control technology. This approach helps to ensure that the emissions from an EGU will not exceed its pre-change maximum achieved hourly emissions rate simply through the random variability of the system, when a change has not expanded the capacity of the unit. Thus, the statistical approach utilizes actual recorded data from periods of representative operation to calculate the maximum actual hourly emissions rate in the past 5 years. We expect that for the most part, this rate will be associated with the pre-change maximum actual operating capacity during this period. Because Alternatives 1 and 2 can be used only if one has CEMS or PEMS data, we cannot adopt these alternatives alone. That is, if we elect to include either or both of these alternatives in the final rule, we will also finalize another alternative to be used for emissions of any regulated NSR pollutants that a source does not measure directly with a CEMS or PEMS. While we believe that the statistical approach would be best applied to hourly emissions data from the periods of highest heat input rates, we also propose and request comment on the option of sorting and extracting data based on the hourly emissions rate itself in lb/hr or lb/MWh, as applicable. In this alternative method for conducting the statistical approach, you would compile a data set in the same manner as in Alternatives 1 and 2. As in Alternatives 1 and 2, you would delete selected hourly data from this 365-day period in accordance with the same data limitations. Specifically, you would delete data from periods of startup, shutdown, and malfunction; periods when the CEMS or PEMS was out of control (as described below); and periods of noncompliance, as defined in proposed § 51.167(f)(2). However, the data would then be sorted by the recorded hourly average emissions rates, rather than by heat input rates. You would then extract the hourly data for the 10 percent of the data set corresponding to the highest hourly emissions rate readings for the selected period. You would next apply basic statistical analyses to the extracted CEMS or PEMS hourly emissions rate data, calculating the average emissions rate, the standard deviation, and finally the UTL. Under this alternate statistical method based on recorded hourly emissions rates, we are proposing a 99.9 percentile of the population (of hourly emissions rate readings) at a 99 percent confidence level. That is, under the proposed methodology we would expect, with a 99 percent confidence level, 99.9 percent of the hourly emissions rate data to be less than the UTL value. We are also proposing a 90 percentile of the population (of hourly emissions rate readings). We request comment on these proposed levels. In particular we request comment on whether a 99 or 90 percentile of the population (of hourly emissions rate readings) would be more appropriate. We also request comment on whether a 95 or 90 percent confidence level would be more appropriate. Proposed Alternatives 3 and 4 for determining the pre-change maximum actual emissions rate use the highest emissions rate (in lb/hr and lb/MWh, respectively) actually achieved for any hour within the 5-year period immediately before the physical or operational change. That is, the pre-change maximum emissions rate could be an emissions rate that was actually achieved for only 1 hour in the 5-year period. Under Alternatives 3 and 4, the highest hourly emissions rate would be determined based on historical actual emissions. You must determine the highest pre-change hourly emissions rate for each regulated NSR pollutant using the best data available to you. You must use the highest available source of data in the hierarchy presented below, unless your reviewing authority has determined that a data source lower in the hierarchy will provide better data for your EGU: • Continuous emissions monitoring system. • Approved PEMS. • Emission tests/emission factor specific to the EGU to be changed. • Material balance. • Published emission factor (such as AP-42). Under this hierarchy, most EGUs will use CEMS to measure the highest hourly SO 2 and NO X emissions. Some EGUs are currently equipped with CEMS to measure CO, and would thus use CEMS to measure historical hourly CO emissions. For other pollutants, we anticipate most EGUs would measure historical actual emissions using emission tests, site-specific emission factors, or mass balances (where applicable). We request comment on appropriate measures of historical actual emissions for all regulated NSR pollutants for all EGUs. In particular, we request comment on appropriate measures of historical actual emissions of CO, VOC, and lead, as turbines may not have significant emissions of these regulated NSR pollutants. We also request comment on whether emission factors that are not site-specific, such as those in AP-42, would be appropriate measures of historical actual emissions. As discussed above, proposed Alternatives 1 and 3 provide specific proposed rule language for the input-based (lb/hr) alternatives. Proposed Alternatives 2 and 4 provide specific proposed rule language for the output-based (lb/MWh) alternatives, largely repeating the proposed language for Alternatives 1 and 3, respectively. For purposes of the output-based alternatives, the proposed language for their input-based counterparts is adjusted in the following ways: • Emissions rates would be expressed in terms of lb/MWh, rather than lb/hr. • For EGUs that are cogeneration units, emissions rates would be determined based on gross energy output. For other EGUs, emissions rates would be determined based on gross electrical output. • Actual and projected emissions rates in lb/MWh would be determined over a 1-hour averaging period (that is, a period of one hour of continuous operation, rather than an instantaneous spike). We are proposing a gross output basis for this test, rather that net output, due to the difficulties involved in determining net output. This gross output basis is consistent with our recent revisions to the NSPS for EUSGUs (40 CFR part 60, subpart Da; 71 FR 9866) and stationary combustion turbines (40 CFR part 60, subpart KKKK; 71 FR 38487). For the output-based alternatives, we propose to cite the definitions in the CAIR rule at § 51.124(q) for the definitions of “cogeneration unit” and numerous other terms used in that definition. We propose to include definitions in § 51.167(h)(2) of this rule for “gross electrical output” and “gross energy output.” We propose to add definitions for “gross power output” and “useful thermal energy output,” which are terms used in the proposed definition of “gross energy output.” We invite comment on the output-based approach in general, the proposed output-based alternatives, and the related definitions we are proposing. 2. *Determining the Post-Change Emissions Rate* . We are proposing the same approach to post-change emissions for Alternatives 1 through 4. Specifically, for each regulated NSR pollutant, you must project the maximum emissions rate that your EGU will actually achieve in any 1 hour in the 5 years following the date the EGU resumes regular operation after the physical or operational change. An emissions increase results from the physical or operational change if this projected maximum actual hourly emissions rate exceeds the pre-change maximum actual hourly emissions rate. Regardless of any preconstruction projections, you must treat an emissions increase as occurring if the emissions rate actually achieved in any 1 hour during the 5 years after the change exceeds the pre-change maximum actual hourly emissions rate. 3. *Data Limitations in Determining Emissions Rates* . We are proposing four limitations on the data used to determine pre-change and post-change maximum emissions rates under the maximum achieved hourly emissions test (see proposed § 51.167(f)(2)(i)). The proposed limitations are identical for Alternatives 1 through 4. For purposes of determining maximum emissions rates under the maximum achieved test, we propose that you must not include the following types of data in your calculations: • Emissions rate data associated with startups, shutdowns, or malfunctions of your EGU, as defined by applicable regulation(s) or permit term(s), or malfunctions of an associated air pollution control device. A malfunction means any sudden, infrequent, and not reasonably preventable failure of the EGU or the air pollution control equipment to operate in a normal or usual manner. • CEMS or PEMS data recorded during monitoring system out-of-control periods. Out-of-control periods include those during which the monitoring system fails to meet quality assurance criteria (for example, periods of system breakdown, repair, calibration checks, or zero and span adjustments) established by regulation, by permit, or in an approved quality assurance plan. • Emissions rate data from periods of noncompliance when your EGU was operating above an emission limitation that was legally enforceable at the time the data were collected. • Data from any period for which the information is inadequate for determining emissions rates, including information related to the limitations listed above. The first two of these limitations are based on requirements of the NSPS General Provisions in subpart A of part 60. The prohibition of data from periods of startup, shutdown, and malfunction is found in the section on performance tests, specifically § 60.8(c), which states, in pertinent part: Operations during periods of startup, shutdown, and malfunction shall not constitute representative conditions for the purpose of a performance test nor shall emissions in excess of the level of the applicable emission limit during periods of startup, shutdown, and malfunction be considered a violation of the applicable emission limit unless otherwise specified in the applicable standard. The principle set out in this paragraph is that emissions during periods of startup, shutdown, and malfunction are not representative and typically should not figure into emission calculations. We propose to apply this principle to all data required to comply with the requirements in this action, and not limit it to performance test data. We do not believe that emissions during startup, shutdown, or malfunction are a reasonable basis for determining whether a physical or operational change at an EGU would result in an hourly emissions increase. It is more appropriate to focus on emissions during normal operations, which are expected to correlate more closely with the actual operating capacity of the EGU than would emissions during periods of startup, shutdown, or malfunction. The proposed rule language also expands slightly on the language of § 60.8(c) to clarify the meanings of startup, shutdown, and malfunction in the context of this action. The second data limitation reflects § 60.13(h), which states that “data recorded during periods of continuous system breakdown, repair, calibration checks, and zero and span adjustments shall not be included in data averages computed under this paragraph.” We do not believe that this type of unrepresentative CEMS or PEMS data, which may bear no relationship to actual emissions, should be included in calculations of maximum achieved emissions rates. The proposed rule language refers to and defines “monitoring system out-of-control periods,” in keeping with more current terminology for monitoring systems. The third proposed data limitation listed above would prohibit the use of emissions rate data from periods of noncompliance when your EGU was operating above an emission limitation that was legally enforceable at the time the data were collected. This reflects existing requirements under the major NSR program, specifically the definition of “baseline actual emissions” that is used in the actual-to-projected-actual applicability test. (See, for example, § 51.166(b)(47)(i)(b).) The fourth proposed data limitation reflects existing requirements under the major NSR program, again in the definition of “baseline actual emissions” that is used in the actual-to-projected-actual applicability test. (See, for example, § 51.166(b)(47)(i)(d).) This limitation would preclude the use of data from periods where there is inadequate information for determining emissions rates, including information related to the other three data limitations. This provision is simply intended to ensure that you generate reliable, defensible values for pre-change and post-change emissions rates. 4. *Recordkeeping and Reporting Requirements* . Under proposed Alternatives 1 through 4, an emissions increase has occurred if the emissions rate actually achieved in any one hour during the 5 years after the change exceeds the pre-change maximum actual hourly emissions rate (see, for example § 51.167(f)(1)(iii) under Alternative 1). Most EGUs are already reporting hourly SO 2 and NO X emissions through CEMS data to EPA as part of their requirements under the Acid Rain program and will continue to be required to do so under the CAIR. The Acid Rain and CAIR programs also require recordkeeping and reporting for EGUs not using CEMS, such that hourly emissions. PM 2.5 , VOC, and CO emissions can be computed from SO 2 and NO X emissions data. Therefore, emissions increases of regulated NSR pollutants will be transparent to the Agency and to the public. However, we request comment on whether additional recordkeeping and reporting requirements for post-change emissions should be required where EGUs are not using CEMS to measure emissions. B. Test for EGUs Based on Maximum Achievable Emissions Rates As we stated in our October 2005 NPR (70 FR 61090), we are proposing to allow existing EGUs to use the same maximum achievable hourly emissions test applied in the NSPS to determine whether a physical or operational change results in an emissions increase under the major NSR program. This test is based on a comparison of pre-change and post-change emissions rates in pounds per hour (lb/hr). 31 We are proposing an additional variation on the NSPS test, which would compare pre-change and post-change achievable emissions rates in pounds per megawatt-hour (lb/MWh). In the discussion that follows and in the proposed rule language, we refer to these two approaches as Alternatives 5 and 6, respectively. 31 In the NSPS regulations, emissions rates are compared in terms of kilograms per hour. We use English units in this proposed rulemaking in keeping with longstanding practice in the major NSR program, where annual emissions are generally computed using the lb/hr rate and hours of operation. 1. *Determining Pre-Change and Post-Change Emissions Rates* . Under Alternative 5, the major NSR regulations would apply at an EGU if a physical or operational change results in any increase above the maximum hourly emissions achievable at that unit during the 5 years prior to the change. Under this alternative, we are proposing to incorporate provisions similar to those in § 60.14(h) into the new § 51.167(f) (1). We propose that this regulatory language would substantially mirror, but would not be identical to, § 60.14(h). As with the definition of modification that we are proposing for § 51.167(h) (2), there are differences between the two programs that prevent a wholesale adoption of the NSPS modification provisions of § 60.14(h). Specifically, our proposed rule language addresses the full range of pollutants regulated under the major NSR program by referring to the “regulated NSR pollutants,” while the NSPS provisions limit the analysis to those pollutants regulated under an applicable NSPS. Also, as we previously explained at 70 FR 61090, we are proposing that the emissions increase test would apply to EGUs, rather than to EUSGUs. Under Alternative 5, § 51.167(f)

(1)would read as follows: *Emissions increase test.* For each regulated NSR pollutant, compare the maximum achievable hourly emissions rate before the physical or operational change to the maximum achievable hourly emissions rate after the change. Determine these maximum achievable hourly emissions rates according to § 60.14(b) of this chapter. No physical change, or change in the method of operation, at an existing EGU shall be treated as a modification for the purposes of this section provided that such change does not increase the maximum hourly emissions of any regulated NSR pollutant above the maximum hourly emissions achievable at that unit during the 5 years prior to the change. As stated in this proposed rule language, pre-change and post-change hourly emissions rates would be determined according to the NSPS provisions in § 60.14(b). That is, hourly emissions increases would be determined using emission factors, material balances, continuous monitor data, or manual emission tests. Alternative 6 is also based on the NSPS “maximum achievable” test, but is modified to an energy output (lb/MWh) basis. Under Alternative 6, § 51.167(f)

(1)would read as follows: *Emissions increase test* . For each regulated NSR pollutant, compare the maximum achievable emissions rate in pounds per megawatt-hour (lb/MWh) before the physical or operational change to the maximum achievable emissions rate in lb/MWh after the change. Determine these maximum achievable emissions rates according to § 60.14(b) of this chapter, using emissions rates in lb/MWh achievable over 1 hour of continuous operation in place of mass emissions rates. For EGUs that are cogeneration units, determine emissions rates based on gross energy output. For other EGUs, determine emissions rates based on gross electrical output. No physical change, or change in the method of operation, at an existing EGU shall be treated as a modification for the purposes of this section provided that such change does not increase the maximum emissions rate of any regulated NSR pollutant above the maximum emissions rate achievable at that unit during the 5 years prior to the change. To maintain an hourly basis for the emissions rate, the proposed language specifies that the maximum achievable emissions rate in lb/MWh is to be determined based on what is achievable over 1 hour of continuous operation (that is, a 1-hour averaging period rather than an instantaneous spike). In addition, as noted above in the discussion of the output-based alternatives under the maximum achieved hourly emissions test (Alternatives 2 and 4), we propose to cite the definition in the CAIR rule at § 51.124(q) for the definitions of “cogeneration unit” and related terms. We propose to include definitions in § 51.167(h)

(2)of this rule for “gross electrical output,” “gross energy output,” “gross power output,” and “useful thermal energy output.” 2. *Data Limitations in Determining Emissions Rates* . We are proposing three limitations on the data used to calculate the pre-change and post-change emissions rates under the maximum achievable hourly emissions test (see proposed § 51.167(f)

(2)(ii)). The proposed limitations are identical for Alternatives 5 and 6. For purposes of determining maximum emissions rates under the maximum achievable test, we propose that you must not use the following types of data in your calculations: • Emissions rate data associated with startups, shutdowns, or malfunctions of your EGU, as defined by applicable regulation(s) or permit term(s), or malfunctions of an associated air pollution control device. A malfunction means any sudden, infrequent, and not reasonably preventable failure of the EGU or the air pollution control equipment to operate in a normal or usual manner. • CEMS or PEMS data recorded during monitoring system out-of-control periods. Out-of-control periods include those during which the monitoring system fails to meet quality assurance criteria (for example, periods of system breakdown, repair, calibration checks, or zero and span adjustments) established by regulation, by permit, or in an approved quality assurance plan. • Data from any period for which there is inadequate information for determining emissions rates, including information related to the limitations listed above. These proposed data limitations are the same as three of the four data limitations that we are proposing for the maximum achieved tests (Alternatives 1 through 4). See Section IV.A.3. above for the discussion of these three data limitations. 3. *Recordkeeping and Reporting for Hourly Emissions* . We are proposing the same recordkeeping and reporting approach for the maximum achievable test (Alternatives 5 and 6) that we propose for the maximum achieved hourly emissions test (Alternatives 1 through 4). We describe our approach in Section IV.A.4 of this preamble. V. Proposed Regulations for Option 2: Hourly Emissions Increase Test This section contains details on the proposed regulatory language for Option 2, the hourly emissions increase test. We are proposing that Option 2 would apply to all existing EGUs. As we noted at 70 FR 61093, however, we are also requesting comment on whether Option 2 should be limited to the geographic area covered by CAIR, or to the geographic area covered by both CAIR and BART. We are also proposing that the Option 2 would apply to all regulated NSR pollutants. However, we also request comment on whether Option 2 should be limited to increases of SO 2 and NO X emissions. In this SNPR, for Option 2 we are proposing to exempt EGUs from the procedures in the current regulations for determining a significant emissions increase and a significant net emissions increase. Specifically, we are proposing to exempt EGUs from the applicability procedures based on a significant emissions increase and significant net emissions increase in the current regulations at 40 CFR 51.165, 51.166, 52.21, and 52.24 and in appendix S to 40 CFR part 51. That is, we are proposing to amend each of these sections to exempt EGUs from all provisions for significant emissions increases and significant net emission increases. For example, under Option 2 the provisions for determining a significant emissions increase and a significant net emissions increase in § 51.166(a)

(7)(iv)(a) would be amended to exempt EGUs as follows.

(a)Except for EGUs as defined in § 51.167(h)(1) of this Subpart, and except as otherwise provided in paragraphs (a)(7)(v) and

(vi)of this section, and consistent with the definition of major modification contained in paragraph (b)(2) of this section, a project is a major modification for a regulated NSR pollutant if it causes two types of emissions increases—a significant emissions increase (as defined in paragraph (b)(39) of this section), and a significant net emissions increase (as defined in paragraphs (b)(3) and (b)(23) of this section). The project is not a major modification if it dos not cause a significant emissions increase. If the project causes a significant emissions increase, then the project is a major modification only if it also results in a significant net emissions increase. We are proposing to amend all other provisions for significant emissions increase and significant net emissions increase in the current regulations at 40 CFR 51.165, 51.166, 52.21, and 52.24 and in appendix S to 40 CFR part 51 in an analogous manner to exempt EGUs. In place of the applicability procedures in the current regulations concerning significant emissions increase and significant net emissions increase, Option 2 applies an hourly emissions increase test to EGUs. We describe these as Steps 1 and 2, which comprise the two-step modification test and are the same as under Option 1, in Section IV of this preamble. As with Option 1, under Option 2, we are proposing to develop two new sections (40 CFR 51.167 and 52.37) to the major NSR program rules that would include the two-step provisions for modifications at EGUs. Thus, the amendatory language in this action applies to Option 2 as it relates to Steps 1 and 2. That is, under Option 2, EGUs would be subject to the new two-step requirements for modifications. They would not be subject to the requirements in the existing regulations for major modifications. Alternatives 1-6, comprising Step 2 of Option 2, are the same as under Option 1. We describe these alternatives in detail above in Section IV of this preamble. Table 10 shows Option 2, including Alternatives 1-6. Table 9.—Major NSR Applicability for Existing EGUs Under Option 2 Option 2 Step 1: Physical Change or Change in the Method of Operation. Step 2: Hourly Emissions Increase Test. • Alternative 1—Maximum achieved hourly emissions; statistical approach; input basis. • Alternative 2—Maximum achieved hourly emissions; statistical approach; output basis. • Alternative 3—Maximum achieved hourly emissions; one-in-5-year baseline; input basis. • Alternative 4—Maximum achieved hourly emissions; one-in-5-year baseline; output basis. • Alternative 5—NSPS test—maximum achievable hourly emissions; input basis. • Alternative 6—NSPS test—maximum achievable hourly emissions; output basis. Under Option 2, if a physical or operational change at an existing EGU is found to be a modification according to this hourly emissions test, the EGU would then be subject to all the substantive major NSR requirements of the existing regulations. Accordingly, we are also proposing to revise the substantive provisions in all the current major NSR regulations that apply to major modifications to apply also to modifications at EGUs. The amendatory language in this proposed rule does not include specific provisions for these changes. The substantive provisions to be amended would include, but not be limited to, the provisions in § 51.166(a)(7)(i) through (iii), (b)(9), (b)(12), (b)(14)(ii), (b)(15), (b)(18), (i)(1) through (9), (j)(1) through (4), (m)(1) through (3), (p)(1) through (7), (r)(1) through (7), and (s)(1) through (4). For example, we are proposing to amend § 51.166(a)(7)(iii) as follows.

(iii)No new major stationary source, major modification, or modification at an EGU to which the requirements of paragraphs

(j)through (r)(5) of this section apply shall begin actual construction without a permit that states that the major stationary source, major modification, or modification at an EGU will meet those requirements. We are proposing to amend all other provisions in the current regulations at 40 CFR 51.165, 51.166, 52.21, and 52.24 and in appendix S to 40 CFR part 51 in an analogous manner to require that the substantive provisions in all the current major NSR regulations apply to modifications at EGUs. VI. Legal Basis and Policy Rationale This section supplements the legal arguments in our October 2005 proposal. (70 FR 70565.) In that action, we provided our legal basis and rationale for the proposed maximum achievable hourly emissions test and our alternative proposal, the maximum achieved hourly emissions test. We noted that the key statutory provisions provide, in relevant part, that a “modification” that triggers NSR occurs when a physical change or change in the method of operation “increases the amount of any air pollutant emitted” by the source. Although the Court in *New York* v. *EPA* held that the quoted provision refers to increases in actual emissions, the Court further indicated that the statute was silent as to the method for determining whether increases occur. When a statute is silent or ambiguous with respect to specific issues, the relevant inquiry for a reviewing court is whether the Agency's interpretation of the statutory provision is permissible. *Chevron U.S.A., Inc.* v. *NRDC, Inc* . 467 U.S. 837, 865 (1984). Accordingly, we have broad discretion to propose a reasonable method by which to calculate emissions increases for purposes of NSR applicability. This action continues to propose both the maximum achievable hourly emissions increase test and the maximum achieved hourly emissions increase test. We set forth legal basis and rationale in the NPR for these two tests. In this SNPR, however, we provide additional legal and policy basis for the hourly emissions increase tests, on both an input and output basis. We believe that a test based on maximum actual hourly emissions is a reasonable measure of actual emissions. It measures actual emissions at peak, or close to peak, physical and operational capacity. For reasons described elsewhere, and summarized below, we believe this approach implements sound policy objectives. As we noted at 70 FR 61091, we believe that a test based on maximum achievable hourly emissions remains a test based on actual emissions. The reason is that, as noted in the October 2005 proposal, as a practical matter, for most, if not all EGUs, the hourly rate at which the unit is actually able to emit is substantively equivalent to that unit's historical maximum hourly emissions. That is, most, if not all EGUs will operate at their maximum actual physical and operational capacity at some point in a 5-year period. In general, highest emissions occur during the period of highest utilization. As a result, both the maximum achievable and maximum achieved hourly emissions increase tests allow an EGU to utilize all of its existing capacity, and in this aspect the hourly rate at which the unit is actually able to emit is substantively equivalent under both tests. Some commenters took issue with this statement, arguing that maximum achievable emissions could differ from maximum achieved emissions for a given EGU for any given period as a result of factors independent of the physical or operational change, including variability of the sulfur content in the coal being burned. We have long recognized that the highest hourly emissions do not always occur at the point of highest capacity utilization, due to fluctuations in process and control equipment operation, as well as in fuel content and firing method. In fact, we justified an emission factor approach as our preferred approach when we proposed the NSPS regulations at § 60.14 in 1974. (See 39 FR 36947.) As we also noted in developing these NSPS provisions for modifications, “measurement techniques such as emission tests or continuous monitors are sensitive to routine fluctuations in emissions, and thus a method is needed to distinguish between significant increases in emissions and routine fluctuations in emissions.” (39 FR 36947.) At that time, we proposed a statistical method for use with stack tests and continuous monitors to measure actual emissions to address this issue. In light of these concerns, we developed a statistical approach for the maximum achieved hourly emissions increase test to assure that it identifies the maximum hourly pollutant emissions value (for example maximum lb/hr NO X during a specific one-year period). The statistical procedure would provide an estimate of the highest value (99.9 percentage level) in the period represented by the data set. We believe that this approach mitigates some of the uncertainty associated with trying to identify the highest hourly emissions rate at the highest capacity utilization. 32 We thus believe that, over a period that is representative of normal operations, in general the maximum achievable and maximum achieved hourly emissions test would lead to substantially equivalent results. 32 Commenters stated that the maximum achieved test is difficult to comply with due to fluctuations in equipment and control device performance that are beyond the control of the EGU owner/operator. Each of these proposed options would promote the safety, reliability, and efficiency of EGUs. Each of the options would balance the economic need of sources to use existing operating capacity with the environmental benefit of regulating those emission increases related to a change, considering the substantial national emissions reductions other programs have achieved or will achieve from EGUs. The proposed regulations are consistent with the primary purpose of the major NSR program, which is to balance the need for environmental protection and economic growth. As the analyses included in this SNPR demonstrate, the proposed regulations would not have an undue adverse impact on local air quality. Furthermore, as our analyses demonstrate, increases in hours of operation at EGUs, to the extent they may change under a maximum hourly rate test, do not increase national SO 2 , NO X , PM 2.5 , VOC, or CO emissions. Consistent with earlier analyses, our analyses demonstrate that in a system where most of the national emissions are capped, the more hours an EGU operates, the more likely it is to install controls. Moreover, each of the proposed options also offers additional benefits consistent with our overall policy goals. Option 1 would simplify major NSR for changes where there is no increase in hourly emissions. However, many public commenters urged that we retain the significant emissions increase component of the emissions increase test. Therefore, we propose Option 1, our preferred Option, for the purpose of maintaining the current significant net emissions increase component of the emissions increase test. Option 2 with the proposed maximum hourly tests would simplify major NSR by reducing applicability determinations complexity. Option 2 with the proposed maximum hourly achievable test provides more simplicity by conforming major NSR applicability determinations to NSPS applicability determinations. We also note that Option 2 (both achievable and achieved alternatives) eliminates the burden of projecting future emissions and distinguishing between emissions increases caused by the change from those due solely to demand growth, because any increase in the emissions under the maximum hourly achievable emissions test would logically be attributed to the change. In addition, Option 2 reduces recordkeeping and reporting burdens on sources because compliance will no longer rely on synthesizing emissions data into rolling average emissions. Option 2 would also reduce the reviewing authorities' compliance and enforcement burden. Consistent with our policy goal of encouraging efficient use of existing energy capacity, we are continuing to propose an output-based format for the hourly emissions increase tests. An output-based standard establishes emission limits in a format that incorporates the effects of unit efficiency by relating emissions to the amount of useful energy generated, not the amount of fuel burned. By relating emission limitations to the productive output of the process, output-based emission limits encourage energy efficiency because any increase in overall energy efficiency results in a lower emission rate. Allowing energy efficiency as a pollution control measure provides regulated sources with an additional compliance option that can lead to reduced compliance costs as well as lower emissions. The use of more efficient technologies reduces fossil fuel use and leads to multi-media reductions in environmental impacts both on-site and off-site. Option 2 does not include steps for determining whether significant net emissions increases have occurred. We recognize that the D.C. Circuit, in the seminal case, *Alabama Power* v. *EPA* , 636 F.2d 323 (D.C. Cir. 1980), which was handed down before Chevron, held that failure to interpret “increases” to allow netting would be “unreasonable and contrary to the expressed purposes of the PSD provisions. * * * ” *Id* . at 401. As we noted at 70 FR 61093, it is important to place this ruling in the context of the rules before the Court at that time. Our 1978 regulations required a source-wide accumulation of emissions increases without providing for an ability to offset these accumulated increases with any source-wide decreases. In finding that we must apply a bubble approach, the Court held that we could not require sources to accumulate increases without also accumulating decreases. It is unclear whether the Court would have reached the same conclusion if the emissions test before the Court only considered the increases from the project under review and not source-wide increases from multiple projects. We request comment on our observations related to the *Alabama Power* Court's decision related to netting and whether a major NSR program without netting can be supported under the Act. With respect to the significance levels, which, like netting, are not included under Option 2, we recognize that *Alabama Power* also upheld significance levels as a “permissible * * * exercise of agency power, inherent in most statutory schemes, to overlook circumstances that in context may fairly be considered *de minimis* .” *Id* . At 360. It is clear, however, that the Court considered the establishment of significance levels as discretionary. We believe that significance levels are not important to include in the rules proposed in Option 2 because under those rules, relatively minor changes for which the significance levels might come into play would not increase the maximum hourly rate. By comparison, the changes that do increase the maximum hourly rate are likely to be capacity increases that should not, by their nature, be considered *de minimis* . We request comment on all aspects of our legal and policy basis. VII. Statutory and Executive Order Reviews A. Executive Order 12866: Regulatory Planning and Review Under Executive Order

(EO)12866 (58 FR 51735, October 4, 1993), this action is a “significant regulatory action.” The action was identified as a “significant regulatory action” because it raises novel legal or policy issues. Accordingly, EPA submitted this action to the Office of Management and Budget

(OMB)for review under EO 12866 and any changes made in response to OMB recommendations have been documented in the docket for this action. In addition, EPA prepared an analysis of the potential costs and benefits associated with this action. This analysis is contained in the Information Collection Request

(ICR)document assigned EPA ICR number 1230.19. A copy of the analysis is available in the docket for this action and the analysis is briefly summarized in the Paperwork Reduction Act section. B. Paperwork Reduction Act The information collection requirements in this proposed rule have been submitted for approval to the Office of Management and Budget

(OMB)under the Paperwork Reduction Act, 44 U.S.C. 3501 *et seq.* The ICR document prepared by EPA has been assigned EPA ICR number 1230.19. Certain records and reports are necessary for the State or local agency (or the EPA Administrator in non-delegated areas), for example, to:

(1)Confirm the compliance status of stationary sources, identify any stationary sources not subject to the standards, and identify stationary sources subject to the rules; and

(2)ensure that the stationary source control requirements are being achieved. The information would be used by the EPA or State enforcement personnel to

(1)identify stationary sources subject to the rules,

(2)ensure that appropriate control technology is being properly applied, and

(3)ensure that the emission control devices are being properly operated and maintained on a continuous basis. Based on the reported information, the State, local or tribal agency can decide which plants, records, or processes should be inspected. The proposed rule would reduce burden for owners and operators of major stationary sources. We expect the proposed rule would simplify applicability determinations, eliminate the burden of projecting future emissions and distinguishing between emissions increases caused by the change from those due solely to demand growth, and reduce recordkeeping and reporting burdens. Over the 3-year period covered by the ICR, we estimate an average annual reduction in burden for all industry entities that would be affected by the proposed rule. For the same reasons, we also expect the proposed rule to reduce burden for State and local authorities reviewing permits when fully implemented. However, there would be a one-time, additional burden for State and local agencies to revise their SIPs to incorporate the proposed changes. Burden means the total time, effort, or financial resources expended by persons to generate, maintain, retain, or disclose or provide information to or for a Federal agency. This includes the time needed to review instructions; develop, acquire, install, and utilize technology and systems for the purpose of responding to the information collection; adjust existing ways to comply with any previously applicable instructions and requirements; train personnel to respond to a collection of information; search existing data sources; complete and review the collection of information; and transmit or otherwise disclose the information. An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB control number. The OMB control numbers for EPA's regulations are listed in 40 CFR parts 9. To comment on the Agency's need for this information, the accuracy of the provided burden estimates, and any suggested methods for minimizing respondent burden, including use of automated collection techniques, EPA has established a public docket for this rule, which includes this ICR, under Docket ID number EPA-HQ-OAR-2005-1063. Submit any comments related to the ICR for this proposed rule to EPA and OMB. See ADDRESSES section at the beginning of this notice for where to submit comments to EPA. Send comments to OMB at the Office of Information and Regulatory Affairs, Office of Management and Budget, 725 17th Street, Northwest, Washington, DC 20503, Attention: Desk Officer for EPA. Since OMB is required to make a decision concerning the ICR between 30 and 60 days after May 8, 2007, a comment to OMB is best assured of having its full effect if OMB receives it by June 7, 2007. The final rule will respond to any OMB or public comments on the information collection requirements contained in this proposal. C. Regulatory Flexibility Act

(RFA)The RFA generally requires an agency to prepare a regulatory flexibility analysis of any rule subject to notice and comment rulemaking 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 substantial number of small entities. Small entities include small businesses, small organizations, and small governmental jurisdictions. For purposes of assessing the impacts of this notice on small entities, 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 standards. ( *See* 13 CFR 121.201);

(2)a small governmental jurisdiction that is a government of a city, county, town, school district, or special district with a population of less than 50,000; or

(3)a small organization that is any not-for-profit enterprise that is independently owned and operated and is not dominant in its field. After considering the economic impacts of this notice on small entities, I certify that this action will not have a significant economic impact on a substantial number of small entities. In determining whether a rule has a significant economic impact on a substantial number of small entities, the impact of concern is any significant adverse economic impact on small entities, since the primary purpose of the regulatory flexibility analyses is to identify and address regulatory alternatives “which minimize any significant economic impact of the proposed rule on small entities.” 5 U.S.C. 603 and 604. Thus, an agency may certify that a rule will not have a significant economic impact on a substantial number of small entities if the rule relieves regulatory burden, or otherwise has a positive economic effect, on all of the small entities subject to the rule. We believe that these proposed rule changes will relieve the regulatory burden associated with the major NSR program for all EGUs, including any EGUs that are small businesses. This is because the proposed rule would simplify applicability determinations, eliminate the burden of projecting future emissions and distinguishing between emissions increases caused by the change from those due solely to demand growth, and by reducing recordkeeping and reporting burdens. As a result, the program changes provided in the proposed rule are not expected to result in any increases in expenditure by any small entity. We have therefore concluded that this proposed rule would relieve regulatory burden for all small entities. 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. D. Unfunded Mandates Reform Act Title II of the Unfunded Mandates Reform Act of 1995 (UMRA), Public Law 104-4, establishes requirements for Federal agencies to assess the effects of their regulatory actions on State, local, and tribal governments and the private sector. Under section 202 of the UMRA, EPA generally must prepare a written statement, including a cost-benefit analysis, for proposed and final rules with “Federal mandates” that may result in expenditures to State, local, and tribal governments, in the aggregate, or to the private sector, of $100 million or more in any one year. Before promulgating an EPA rule for which a written statement is needed, section 205 of the UMRA generally requires EPA to identify and consider a reasonable number of regulatory alternatives and adopt the least costly, most cost-effective or least burdensome alternative that achieves the objectives of the rule. The provisions of section 205 do not apply when they are inconsistent with applicable law. Moreover, section 205 allows EPA to adopt an alternative other than the least costly, most cost-effective or least burdensome alternative if the Administrator publishes with the final rule an explanation why that alternative was not adopted. Before EPA establishes any regulatory requirements that may significantly or uniquely affect small governments, including tribal governments, it must have developed under section 203 of the UMRA a small government agency plan. The plan must provide for notifying potentially affected small governments, enabling officials of affected small governments to have meaningful and timely input in the development of EPA regulatory proposals with significant Federal intergovernmental mandates, and informing, educating, and advising small governments on compliance with the regulatory requirements. We have determined that this rule would not contain a Federal mandate that would result in expenditures of $100 million or more by State, local, and tribal governments, in the aggregate, or the private sector in any 1 year. Although initially these changes are expected to result in a small increase in the burden imposed upon reviewing authorities in order for them to be included in the State's SIP, these revisions would ultimately simplify applicability determinations, eliminate the burden of reviewing projected future emissions and distinguishing between emissions increases caused by the change from those due solely to demand growth, and reduce the burden associated with making compliance determinations. Thus, this action is not subject to the requirements of sections 202 and 205 of the UMRA. For the same reasons stated above, we have determined that this notice contains no regulatory requirements that might significantly or uniquely affect small governments. Thus, this action is not subject to the requirements of section 203 of the UMRA. E. Executive Order 13132: Federalism Executive Order 13132, entitled “Federalism” (64 FR 43255, August 10, 1999), requires EPA to develop an accountable process to ensure “meaningful and timely input by State and local officials in the development of regulatory policies that have federalism implications.” “Policies that have federalism implications” is defined in the Executive Order to include regulations that have “substantial 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.” This proposed rule does not have federalism implications. It will not have substantial 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 specified in Executive Order 13132. We estimate a one-time burden of approximately 2,240 hours and $83,000 for State agencies to revise their SIPs to include the proposed regulations. However, these revisions would ultimately simplify applicability determinations, eliminate the burden of reviewing projected future emissions and distinguishing between emissions increases caused by the change from those due solely to demand growth, and reduce the burden associated with making compliance determinations. This will in turn reduce the overall burden of the program. 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 EPA and State and local governments, EPA specifically solicits comment on this proposed rule from State and local officials. F. Executive Order 13175: Consultation and Coordination With Indian Tribal Governments Executive Order 13175, entitled “Consultation and Coordination with Indian Tribal Governments” (65 FR 67249, November 9, 2000), requires EPA to develop an accountable process to ensure “meaningful and timely input by tribal officials in the development of regulatory policies that have tribal implications.” This proposed rule does not have tribal implications, as specified in Executive Order 13175. There are no Tribal authorities currently issuing major NSR permits. To the extent that this proposed rule may apply in the future to any EGU that may locate on tribal lands, tribal officials are afforded the opportunity to comment on tribal implications in this notice. Thus, Executive Order 13175 does not apply to this rule. Although Executive Order 13175 does not apply to this proposed rule, EPA specifically solicits comment on this proposed rule from tribal officials. We will also consult with tribal officials, including officials of the Navaho Nation lands on which Navajo Power Plant and Four Corners Generating Plant are located, before promulgating the final regulations. In the spirit of Executive Order 13132, and consistent with EPA policy to promote communications between EPA and State and local government, EPA specifically solicits comment on this proposed rule from State and local governments. G. Executive Order 13045: Protection of Children From Environmental Health Risks and Safety Risks Executive Order 13045: “Protection of Children from Environmental Health Risks and Safety Risks” (62 FR 19885, April 23, 1997) applies to any rule that:

(1)Is determined to be “economically significant” as defined under Executive Order 12866, and

(2)concerns an environmental health or safety risk that EPA has reason to believe may have a disproportionate effect on children. If the regulatory action meets both criteria, the Agency must evaluate the environmental health or safety effects of the planned rule on children, and explain why the planned regulation is preferable to other potentially effective and reasonably feasible alternatives considered by the Agency. This proposed rule is not subject to the Executive Order because it is not economically significant as defined in Executive Order 12866, and because the Agency does not have reason to believe the environmental health or safety risks addressed by this action present a disproportionate risk to children. We believe that, based on our analysis of electric utilities, this rule as a whole will result in equal environmental protection to that currently provided by the existing regulations, and do so in a more streamlined and effective manner. The public is invited to submit or identify peer-reviewed studies and data, of which the agency may not be aware, that assessed results of early life exposure to electric utilities. H. Executive Order 13211: Actions Concerning Regulations That Significantly Affect Energy Supply, Distribution, or Use This rule is not a “significant energy action” as defined in Executive Order 13211, “Actions Concerning Regulations That Significantly Affect Energy Supply, Distribution, or Use” [66 FR 28355 (May 22, 2001)] because it is not likely to have a significant adverse effect on the supply, distribution, or use of energy. In fact, this rule improves owner/operator flexibility concerning the supply, distribution, and use of energy. Specifically, the proposed rule would increase owner/operators' ability to utilize existing capacity at EGUs. I. National Technology Transfer and Advancement Act Section 12(d) of the National Technology Transfer and Advancement Act of 1995 (”NTTAA”), Public Law 104-113, 12(d) (15 U.S.C. 272 note) directs 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 standards are technical standards (for example, materials specifications, test methods, sampling procedures, and business practices) that are developed or adopted by voluntary consensus standards bodies. The NTTAA directs EPA to provide Congress, through OMB, explanations when the Agency decides not to use available and applicable voluntary consensus standards. This proposed rule does not involve technical standards. Therefore, EPA is not considering the use of any voluntary consensus standards. EPA welcomes comments on this aspect of the proposed rulemaking and, specifically, invites the public to identify potentially-applicable voluntary consensus standards and to explain why such standards should be used in this regulation. J. Executive Order 12898: Federal Actions To Address Environmental Justice in Minority Populations and Low-Income Populations Executive Order

(EO)12898 (59 FR 7629 (Feb. 16, 1994)) establishes federal executive policy on environmental justice. Its main provision directs Federal 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 their programs, policies, and activities on minority populations and low-income populations in the United States. EPA has determined that this proposed rule will not have disproportionately high and adverse human health or environmental effects on minority or low-income populations because it does not affect the level of protection provided to human health or the environment. This proposed rule amendment, in conjunction with other existing programs, would not relax the control measures on sources regulated by the rule and therefore would not cause emissions increases from these sources. VIII. Statutory Authority The statutory authority for this action is provided by sections 307(d)

(7)(B), 101, 111, 114, 116, and 301 of the CAA as amended (42 U.S.C. 7401, 7411, 7414, 7416, and 7601). This notice is also subject to section 307(d) of the CAA (42 U.S.C. 7407(d)). List of Subjects 40 CFR Part 51 Environmental protection, Administrative practice and procedure, Air pollution control, Nitrogen dioxide, Sulfur dioxide. 40 CFR Part 52 Environmental protection, Administrative practice and procedure, Air pollution control, Nitrogen dioxide, Sulfur dioxide. Dated: April 25, 2007. Stephen L. Johnson, Administrator. For the reasons set out in the preamble, title 40, chapter I 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. Subpart I—[Amended] 2. Add § 51.167 to read as follows: § 51.167 Preliminary major NSR applicability test for electric generating units (EGUs).

(a)*What is the purpose of this section?* State Implementation Plans and Tribal Implementation Plans must include the requirements in paragraphs

(b)through

(h)of this section for determining (prior to or after construction) whether a change to an EGU is a modification for purposes of major NSR applicability. Deviations from these provisions will be approved only if the State or Tribe demonstrates that the submitted provisions are at least as stringent in all respects as the corresponding provisions in paragraphs

(b)through

(h)of this section.

(b)*Am I subject to this section?* You must meet the requirements of this section if you own or operate an EGU that is located at a major stationary source, and you plan to make a change to the EGU.

(c)*What happens if a change to my EGU is determined to be a modification according to the procedures of this section?* If the change to your EGU is a modification according to the procedures of this section, you must determine whether the change is a major modification according to the procedures of the major NSR program that applies in the area in which your EGU is located. That is, you must evaluate your modification according to the requirements set out in the applicable regulations approved pursuant to § 51.165 and/or § 51.166, depending on the regulated NSR pollutants emitted and the attainment status of the area in which your EGU is located for those pollutants. Section 51.165 sets out the requirements for State nonattainment major NSR programs, while § 51.166 sets out the requirements for State PSD programs.

(d)*What is the process for determining if a change to an EGU is a modification?* The two-step process set out in paragraphs (d)(1) and

(2)of this section is used to determine (before beginning actual construction) whether a change to an EGU located at a major stationary source is a modification. Regardless of any preconstruction projections, a modification has occurred if a change satisfies both steps in the process.

(1)*Step 1.* Is the change a physical change in, or change in the method of operation of, the EGU? (See paragraph

(e)of this section for a list of actions that are not physical or operational changes.) If so, go on to Step 2 (paragraph (d)(2) of this section).

(2)*Step 2.* Will the physical or operational change to the EGU increase the amount of any regulated NSR pollutant emitted into the atmosphere by the source (as determined according to paragraph

(f)of this section) or result in the emissions of any regulated NSR pollutant(s) into the atmosphere that the source did not previously emit? If so, the change is a modification.

(e)*What types of actions are not physical changes or changes in the method of operation? (Step 1)* For purposes of this section, a physical change or change in the method of operation shall not include:

(1)Routine maintenance, repair, and replacement;

(2)Use of an alternative fuel or raw material by reason of an order under sections 2(a) and

(b)of the Energy Supply and Environmental Coordination Act of 1974 (or any superseding legislation) or by reason of a natural gas curtailment plan pursuant to the Federal Power Act;

(3)Use of an alternative fuel by reason of an order or rule under section 125 of the Act;

(4)Use of an alternative fuel at a steam generating unit to the extent that the fuel is generated from municipal solid waste;

(5)Use of an alternative fuel or raw material by a stationary source which the source is approved to use under any permit issued under 40 CFR 52.21 or under regulations approved pursuant to § 51.165 or § 51.166, or which:

(i)For purposes of evaluating attainment pollutants, the source was capable of accommodating before January 6, 1975, unless such change would be prohibited under any federally enforceable permit condition which was established after January 6, 1975 pursuant to 40 CFR 52.21 or under regulations approved pursuant to 40 CFR part 51 subpart I or § 51.166; or

(ii)For purposes of evaluating nonattainment pollutants, the source was capable of accommodating before December 21, 1976, unless such change would be prohibited under any federally enforceable permit condition which was established after December 21, 1976 pursuant to 40 CFR 52.21 or under regulations approved pursuant to 40 CFR part 51 subpart I or § 51.166;

(6)An increase in the hours of operation or in the production rate, unless such change is prohibited under any federally enforceable permit condition which was established after January 6, 1975 (for purposes of evaluating attainment pollutants) or after December 21, 1976 (for purposes of evaluating nonattainment pollutants) pursuant to 40 CFR 52.21 or regulations approved pursuant to 40 CFR part 51 subpart I or § 51.166;

(7)Any change in ownership at a stationary source;

(8)The installation, operation, cessation, or removal of a temporary clean coal technology demonstration project, provided that the project complies with:

(i)The State Implementation Plan for the State in which the project is located; and

(ii)Other requirements necessary to attain and maintain the national ambient air quality standard during the project and after it is terminated;

(9)For purposes of evaluating attainment pollutants, the installation or operation of a permanent clean coal technology demonstration project that constitutes repowering, provided that the project does not result in an increase in the potential to emit of any regulated pollutant emitted by the unit. This exemption shall apply on a pollutant-by-pollutant basis; or

(10)For purposes of evaluating attainment pollutants, the reactivation of a very clean coal-fired EGU.

(f)*How do I determine if there is an emissions increase? (Step 2)* You must determine if the physical or operational change to your EGU increases the amount of any regulated NSR pollutant emitted to the atmosphere using the method in paragraph (f)(1) of this section, subject to the limitations in paragraph (f)(2) of this section. If the physical or operational change to your EGU increases the amount of any regulated NSR pollutant emitted into the atmosphere or results in the emission of any regulated NSR pollutant(s) into the atmosphere that your EGU did not previously emit, the change is a modification as defined in paragraph (h)(2) of this section. Alternative 1 for paragraph (f)(1):

(1)*Emissions increase test.* For each regulated NSR pollutant for which you have hourly average CEMS or PEMS emissions data with corresponding fuel heat input data, compare the pre-change maximum actual hourly emissions rate in pounds per hour (lb/hr) to a projection of the post-change maximum actual hourly emissions rate in lb/hr, subject to the provisions in paragraphs (f)(1)(i) through

(iii)of this section.

(i)*Pre-change emissions.* Determine the pre-change maximum actual hourly emissions rate as follows:

(A)Select a period of 365 consecutive days within the 5-year period immediately preceding when you begin actual construction of the physical or operational change. Compile a data set (for example, in a spreadsheet) with the hourly average CEMS or PEMS (as applicable) measured emissions rates and corresponding heat input data for all of the hours of operation for that 365-day period for the pollutant of interest.

(B)Delete any unacceptable hourly data from this 365-day period in accordance with the data limitations in paragraph (f)(2) of this section.

(C)Extract the hourly data for the 10 percent of the remaining data set corresponding to the highest heat input rates for the selected period. This step may be facilitated by sorting the data set for the remaining operating hours from the lowest to the highest heat input rates.

(D)Calculate the average emissions rate from the extracted (i.e., highest 10 percent heat input rates) data set, using Equation 1: EP08MY07.000 Where: x = average emissions rate, lb/hr; n = number of emissions rate values; and x i = i th emissions rate value, lb/hr

(E)Calculate the standard deviation of the data set, s, using Equation 2: EP08MY07.001

(F)Calculate the Upper Tolerance Limit, UTL, of the data set using Equation 3: EP08MY07.002 Where: Z 1-p = 3.090, Z score for the 99.9 percentage of interval; and Z 1-q = 2.326, Z score for the 99 percent confidence level.

(G)Use the UTL calculated in paragraph (f)(1)(i)(F) of this section as the pre-change maximum actual hourly emissions rate.

(ii)*Post-change emissions—preconstruction projections.* For each regulated NSR pollutant, you must project the maximum emissions rate that your EGU will actually achieve in any 1 hour in the 5 years following the date the EGU resumes regular operation after the physical or operational change. An emissions increase results from the physical or operational change if this projected maximum actual hourly emissions rate exceeds the pre-change maximum actual hourly emissions rate.

(iii)*Post-change emissions-actually achieved.* Regardless of any preconstruction projections, an emissions increase has occurred if the hourly emissions rate actually achieved in the 5 years after the change exceeds the pre-change maximum actual hourly emissions rate. Alternative 2 for paragraph (f)(1):

(1)*Emissions increase test.* For each regulated NSR pollutant for which you have hourly average CEMS or PEMS emissions data with corresponding fuel heat input data, compare the pre-change maximum actual emissions rate in pounds per megawatt-hour (lb/MWh) to a projection of the post-change maximum actual emissions rate in lb/MWh, subject to the provisions in paragraphs (f)(1)(i) through

(iii)of this section. For EGUs that are cogeneration units, emissions rates are determined based on gross energy output. For other EGUs, emissions rates are determined based on gross electrical output.

(i)*Pre-change emissions.* Determine the pre-change maximum actual emissions rate as follows:

(A)Select a period of 365 consecutive days within the 5-year period immediately preceding when you begin actual construction of the physical or operational change. Compile a data set (for example, in a spreadsheet) with the hourly average CEMS or PEMS (as applicable) measured emissions rates in lb/MWh and corresponding heat input data for all of the hours of operation for that 365-day period for the pollutant of interest.

(B)Delete any unacceptable hourly data from this 365-day period in accordance with the data limitations in paragraph (f)(2) of this section.

(D)Calculate the average emissions rate from the extracted (i.e., highest 10 percent heat input rates) data set, using Equation 1: EP08MY07.003 Where: x = average emissions rate, lb/MWh; n = number of emissions rate values; and x i = i th emissions rate value, lb/MWh

(E)Calculate the standard deviation of the data set, s, using Equation 2: EP08MY07.004

(F)Calculate the Upper Tolerance Limit, UTL, of the data set using Equation 3: EP08MY07.005 Where: Z 1-p = 3.090, Z score for the 99.9 percentage of interval; and Z 1-q = 2.326, Z score for the 99 percent confidence level.

(G)Use the UTL calculated in paragraph (f)(1)(i)(F) of this section as the pre-change maximum actual hourly emissions rate.

(ii)*Post-change emissions—preconstruction projections.* For each regulated NSR pollutant, you must project the maximum emissions rate that your EGU will actually achieve over any period of 1 hour in the 5 years following the date the EGU resumes regular operation after the physical or operational change. An emissions increase results from the physical or operational change if this projected maximum actual emissions rate exceeds the pre-change maximum actual emissions rate.

(iii)*Post-change emissions—actually achieved.* Regardless of any preconstruction projections, an emissions increase has occurred if the emissions rate actually achieved over any period of 1 hour in the 5 years after the change exceeds the pre-change maximum actual emissions rate. Alternative 3 for paragraph (f)(1):

(1)*Emissions increase test.* For each regulated NSR pollutant, compare the pre-change maximum actual hourly emissions rate in pounds per hour (lb/hr) to a projection of the post-change maximum actual hourly emissions rate in lb/hr, subject to the provisions in paragraphs (f)(1)(i) through

(iv)of this section.

(i)*Pre-change emissions—general procedures.* The pre-change maximum actual hourly emissions rate for the pollutant is the highest emissions rate (lb/hr) actually achieved by the EGU for 1 hour at any time during the 5-year period immediately preceding when you begin actual construction of the physical or operational change.

(ii)*Pre-change emissions—data sources.* You must determine the highest pre-change hourly emissions rate for each regulated NSR pollutant using the best data available to you. Use the highest available source of data in the following hierarchy, unless your reviewing authority has determined that a data source lower in the hierarchy will provide better data for your EGU:

(A)Continuous emissions monitoring system (CEMS).

(B)Approved predictive emissions monitoring system (PEMS).

(C)Emission tests/emission factor specific to the EGU to be changed.

(D)Material balance calculations.

(E)Published emission factor.

(iii)*Post-change emissions—preconstruction projections.* For each regulated NSR pollutant, you must project the maximum emissions rate that your EGU will actually achieve in any 1 hour in the 5 years following the date the EGU resumes regular operation after the physical or operational change. An emissions increase results from the physical or operational change if this projected maximum actual hourly emissions rate exceeds the pre-change maximum actual hourly emissions rate.

(iv)*Post-change emissions—actually achieved.* Regardless of any preconstruction projections, an emissions increase has occurred if the hourly emissions rate actually achieved in the 5 years after the change exceeds the pre-change maximum actual hourly emissions rate. Alternative 4 for paragraph (f)(1):

(1)*Emissions increase test.* For each regulated NSR pollutant, compare the pre-change maximum actual emissions rate in pounds per megawatt-hour (lb/MWh) to a projection of the post-change maximum actual emissions rate in lb/MWh, subject to the provisions in paragraphs (f)(1)(i) through

(iv)of this section. For EGUs that are cogeneration units, emissions rates are determined based on gross energy output. For other EGUs, emissions rates are determined based on gross electrical output.

(i)*Pre-change emissions—general procedures.* The pre-change maximum actual emissions rate for the pollutant is the highest emissions rate (lb/MWh) actually achieved by the EGU over any period of 1 hour during the 5-year period immediately preceding when you begin actual construction of the physical or operational change.

(ii)*Pre-change emissions—data sources.* You must determine the highest pre-change emissions rate for each regulated NSR pollutant using the best data available to you. Use the highest available source of data in the following hierarchy, unless your reviewing authority has determined that a data source lower in the hierarchy will provide better data for your EGU:

(A)Continuous emissions monitoring system (CEMS).

(B)Approved predictive emissions monitoring system (PEMS).

(C)Emission tests/emission factor specific to the EGU to be changed.

(D)Material balance calculations.

(E)Published emission factor.

(iii)*Post-change emissions—preconstruction projections.* For each regulated NSR pollutant, you must project the maximum emissions rate that your EGU will actually achieve over any period of 1 hour in the 5 years following the date the EGU resumes regular operation after the physical or operational change. An emissions increase results from the physical or operational change if this projected maximum actual emissions rate exceeds the pre-change maximum actual emissions rate.

(iv)*Post-change emissions—actually achieved* . Regardless of any preconstruction projections, an emissions increase has occurred if the emissions rate actually achieved over any period of 1 hour in the 5 years after the change exceeds the pre-change maximum actual emissions rate. Alternative 5 for paragraph (f)(1):

(1)*Emissions increase test.* For each regulated NSR pollutant, compare the maximum achievable hourly emissions rate before the physical or operational change to the maximum achievable hourly emissions rate after the change. Determine these maximum achievable hourly emissions rates according to § 60.14(b) of this chapter. No physical change, or change in the method of operation, at an existing EGU shall be treated as a modification for the purposes of this section provided that such change does not increase the maximum hourly emissions of any regulated NSR pollutant above the maximum hourly emissions achievable at that unit during the 5 years prior to the change. Alternative 6 for paragraph (f)(1):

(1)*Emissions increase test.* For each regulated NSR pollutant, compare the maximum achievable emissions rate in pounds per megawatt-hour (lb/MWh) before the physical or operational change to the maximum achievable emissions rate in lb/MWh after the change. Determine these maximum achievable emissions rates according to § 60.14(b) of this chapter, using emissions rates in lb/MWh achievable over 1 hour of continuous operation in place of mass emissions rates. For EGUs that are cogeneration units, determine emissions rates based on gross energy output. For other EGUs, determine emissions rates based on gross electrical output. No physical change, or change in the method of operation, at an existing EGU shall be treated as a modification for the purposes of this section provided that such change does not increase the maximum emissions rate of any regulated NSR pollutant above the maximum emissions rate achievable at that unit during the 5 years prior to the change.

(2)*Data limitations for maximum emissions rates.* For purposes of determining pre-change and post-change maximum emissions rates under paragraph (f)(1) of this section, the following limitations apply to the types of data that you may use:

(i)*Data limitations for Alternatives 1-4.*

(A)You must not use emissions rate data associated with startups, shutdowns, or malfunctions of your EGU, as defined by applicable regulation(s) or permit term(s), or malfunctions of an associated air pollution control device. A malfunction means any sudden, infrequent, and not reasonably preventable failure of the EGU or the air pollution control equipment to operate in a normal or usual manner.

(B)You must not use continuous emissions monitoring system

(CEMS)or predictive emissions monitoring system

(PEMS)data recorded during monitoring system out-of-control periods. Out-of-control periods include those during which the monitoring system fails to meet quality assurance criteria (for example, periods of system breakdown, repair, calibration checks, or zero and span adjustments) established by regulation, by permit, or in an approved quality assurance plan.

(C)You must not use emissions rate data from periods of noncompliance when your EGU was operating above an emission limitation that was legally enforceable at the time the data were collected.

(D)You must not use data from any period for which the information is inadequate for determining emissions rates, including information related to the limitations in paragraphs (f)(2)(i)(A) through

(C)of this section.

(ii)*Data limitations for Alternatives 5 and 6.*

(B)You must not use continuous emissions monitoring system

(CEMS)or predictive emissions monitoring system

(C)You must not use data from any period for which the information is inadequate for determining emissions rates, including information related to the limitations in paragraphs (f)(2)(ii)(A) and

(B)of this section.

(g)*What are my requirements for recordkeeping?* You must maintain a file of all information related to determinations that you make under this section of whether a change to an EGU is a modification, subject to the following provisions:

(1)The file must include, but is not limited to, the following information recorded in permanent form suitable for inspection:

(i)Continuous monitoring system, monitoring device, and performance testing measurements;

(ii)All continuous monitoring system performance evaluations;

(iii)All continuous monitoring system or monitoring device calibration checks;

(iv)All adjustments and maintenance performed on these systems or devices; and

(v)All other information relevant to any determination made under this section of whether a change to an EGU is a modification.

(2)You must retain the file until the later of:

(i)The date 5 years following the date the EGU resumes regular operation after the physical or operational change; and

(ii)The date 5 years following the date of such measurements, maintenance, reports, and records.

(h)*What definitions apply under this section?* The definitions in paragraphs (h)(1) and

(2)of this section apply. Except as specifically provided in this paragraph (h), terms used in this section have the meaning accorded them under § 51.165(a)(1) or § 51.166(b), as appropriate to the situation (for example, the attainment status of the area where your source is located for a particular regulated NSR pollutant of interest). Terms not defined here or in § 51.165(a)(1) or § 51.166(b) (as appropriate) have the meaning accorded them under the applicable requirements of the Clean Air Act, 42 U.S.C. 7401, *et seq.*

(1)*Terms related to EGUs that are defined in § 51.124(q).* The following terms are as defined in § 51.124(q): *Boiler.* *Bottoming-cycle cogeneration unit.* *Cogeneration unit.* *Combustion turbine.* *Electric generating unit* or *EGU.* *Fossil fuel.* *Fossil-fuel-fired.* *Generator.* *Maximum design heat input.* *Nameplate capacity.* *Potential electrical output capacity.* *Sequential use of energy.* *Topping-cycle cogeneration unit.* *Total energy input.* *Total energy output.* *Useful power.* *Useful thermal energy.* *Utility power distribution system.*

(2)*Other terms defined for the purposes of this section.* *Attainment pollutant* means a regulated NSR pollutant for which your EGU may be subject to the PSD program that is applicable in the area where your EGU is located. In general, attainment pollutants are the regulated NSR pollutants listed in the PSD program for which there is no NAAQS or for which the area in which your EGU is located is designated as attainment or unclassifiable according to part 81 of this chapter. However, pollutant or precursor transport considerations may cause such regulated NSR pollutants to be treated as nonattainment pollutants as defined in this paragraph (h)(2) (for example, if your EGU is located in an ozone transport region). *Gross electrical output* means the electricity made available for use by the generator associated with the EGU. *Gross energy output* means, with regard to a cogeneration unit, the sum of the gross power output and the useful thermal energy output produced by the cogeneration unit. *Gross power output* means, with regard to a cogeneration unit, electricity or mechanical energy made available for use by the cogeneration unit. *Modification* , for an EGU, means any physical change in, or change in the method of operation of, an EGU which increases the amount of any regulated NSR pollutant emitted into the atmosphere by that source or which results in the emission of any regulated NSR pollutant(s) into the atmosphere that the source did not previously emit. An increase in the amount of regulated NSR pollutants must be determined according to the provisions in paragraph

(f)of this section. For purposes of this section, a physical change or change in the method of operation shall not include the types of actions listed in paragraph

(e)of this section. *Nonattainment pollutant* means a regulated NSR pollutant for which your EGU may be subject to the nonattainment major NSR program that is applicable in the area where your EGU is located. In general, nonattainment pollutants are the regulated NSR pollutants listed in the nonattainment major NSR program for which the area in which your EGU is located is designated as nonattainment according to part 81 of this chapter. However, pollutant or precursor transport considerations may cause such regulated NSR pollutants to be treated as attainment pollutants as defined in this paragraph (h)(2). *Useful thermal energy output* means, with regard to a cogeneration unit, the thermal energy made available for use in any industrial or commercial process, or used in any heating or cooling application, that is, total thermal energy made available for processes and applications other than electrical or mechanical generation. Thermal output for this section means the energy in recovered thermal output measured against the energy in the thermal output at 15 degrees Celsius and 101.325 kilopascals of pressure. [FR Doc. E7-8263 Filed 5-7-07; 8:45 am] BILLING CODE 6560-50-P 72 88 Tuesday, May 8, 2007 Proposed Rules Part III Department of Health and Human Services Centers for Medicare & Medicaid Services 42 CFR Part 412 Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for Federal Fiscal Year 2008; Proposed Rule DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Medicare & Medicaid Services 42 CFR Part 412 [CMS-1551-P] RIN 0938-AO63 Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for Federal Fiscal Year 2008 AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS. ACTION: Proposed rule. SUMMARY: This proposed rule would update the prospective payment rates for inpatient rehabilitation facilities

(IRFs)for Federal fiscal year

(FY)2008 (for discharges occurring on or after October 1, 2007 and on or before September 30, 2008) as required under section 1886(j)(3)(C) of the Social Security Act (the Act). Section 1886(j)(5) of the Act requires the Secretary to publish in the **Federal Register** on or before the August 1 that precedes the start of each fiscal year, the classification and weighting factors for the IRF prospective payment system's

(PPS)case-mix groups and a description of the methodology and data used in computing the prospective payment rates for that fiscal year. We are proposing to revise existing policies regarding the PPS within the authority granted under section 1886(j) of the Act. DATES: To be assured consideration, comments must be received at one of the addresses provided below, no later than 5 p.m. on July 2, 2007. ADDRESSES: In commenting, please refer to file code CMS-1551-P. Because of staff and resource limitations, we cannot accept comments by facsimile

(Fax)transmission. You may submit comments in one of four ways (no duplicates, please): 1. Electronically. You may submit electronic comments on specific issues in this regulation to *http://www.cms.hhs.gov/eRulemaking* . Click on the link “Submit electronic comments on CMS regulations with an open comment period.” (Attachments should be in Microsoft Word, WordPerfect, or Excel; however, we prefer Microsoft Word.) 2. *By regular mail* . You may mail written comments (one original and two copies) to the following address only: Centers for Medicare & Medicaid Services, Department of Health and Human Services, *Attention:* CMS-1551-P, P.O. Box 8012, Baltimore, MD 21244-8012. Please allow sufficient time for mailed comments to be received before the close of the comment period. 3. *By express or overnight mail.* You may send written comments (one original and two copies) to the following address only: Centers for Medicare & Medicaid Services, Department of Health and Human Services, *Attention:* CMS-1551-P, Mail Stop C4-26-05, 7500 Security Boulevard, Baltimore, MD 21244-8012. 4. *By hand or courier* . If you prefer, you may deliver (by hand or courier) your written comments (one original and two copies) before the close of the comment period to one of the following addresses. If you intend to deliver your comments to the Baltimore address, please call telephone number

(410)786-7195 in advance to schedule your arrival with one of our staff members. Room 445-G, Hubert H. Humphrey Building, 200 Independence Avenue, SW., Washington, DC 20201; or 7500 Security Boulevard, Baltimore, MD 21244-1850. (Because access to the interior of the HHH Building is not readily available to persons without Federal Government identification, commenters are encouraged to leave their comments in the CMS drop slots located in the main lobby of the building. A stamp-in clock is available for persons wishing to retain a proof of filing by stamping in and retaining an extra copy of the comments being filed.) Comments mailed to the addresses indicated as appropriate for hand or courier delivery may be delayed and received after the comment period. For information on viewing public comments, see the beginning of the SUPPLEMENTARY INFORMATION section. FOR FURTHER INFORMATION CONTACT: Pete Diaz,

(410)786-1235, for information regarding the 75 percent rule. Susanne Seagrave,

(410)786-0044, for information regarding the payment policies. Zinnia Ng,

(410)786-4587, for information regarding the wage index and prospective payment rate calculation. SUPPLEMENTARY INFORMATION: *Submitting Comments:* We welcome comments from the public on all issues set forth in this rule to assist us in fully considering issues and developing policies. You can assist us by referencing the file code CMS-1551-P and the specific “issue identifier” that precedes the section on which you choose to comment. *Inspection of Public Comments:* All comments received before the close of the comment period are available for viewing by the public, including any personally identifiable or confidential business information that is included in a comment. We post all comments received before the close of the comment period on the following Web site as soon as possible after they have been received: *http://www.cms.hhs.gov/eRulemaking* . Click on the link “Electronic Comments on CMS Regulations” on that Web site to view public comments. Comments received timely will also be available for public inspection as they are received, generally beginning approximately 3 weeks after publication of a document, at the headquarters of the Centers for Medicare & Medicaid Services, 7500 Security Boulevard, Baltimore, Maryland 21244, Monday through Friday of each week from 8:30 a.m. to 4 p.m. To schedule an appointment to view public comments, phone 1-800-743-3951. Table of Contents I. Background A. Historical Overview of the Inpatient Rehabilitation Facility Prospective Payment System (IRF PPS) for Fiscal Years

(FYs)2002 through 2007 B. Requirements for Updating the IRF PPS Rates C. Operational Overview of the Current IRF PPS D. Brief Summary of Proposed Revisions to the IRF PPS for FY 2008 II. 75 Percent Rule Policy III. Classification System for the Inpatient Rehabilitation Facility Prospective Payment System IV. Proposed FY 2008 IRF PPS Federal Prospective Payment Rates A. Proposed FY 2008 IRF Market Basket Increase Factor and Labor-Related Share B. Proposed Area Wage Adjustment C. Description of the Proposed IRF Standard Payment Conversion Factor and Proposed Payment Rates for FY 2008 D. Example of the Methodology for Adjusting the Proposed Federal Prospective Payment Rates V. Update to Payments for High-Cost Outliers Under the IRF PPS A. Proposed Update to the Outlier Threshold Amount for FY 2008 B. Update to the IRF Cost-to-Charge Ratio Ceilings VI. Clarification to the Regulations Text for Special Payment Provisions for Patients That Are Transferred VII. Provisions of a Proposed Regulation VIII. Collection of Information Requirement IX. Response to Public Comments X. Regulatory Impact Analysis A. Overall Impact B. Anticipated Effects of the Proposed Rule C. Anticipated Effects of the 75 Percent Rule Policy D. Alternatives Considered E. Accounting Statement F. Conclusion Regulation Text Addendum Acronyms Because of the many terms to which we refer by acronym in this proposed rule, we are listing the acronyms used and their corresponding terms in alphabetical order below. ASCA—Administrative Simplification Compliance Act of 2002, Pub. L. 107-105 BBA—Balanced Budget Act of 1997, Pub. L. 105-33 BBRA—Medicare, Medicaid, and SCHIP [State Children's Health Insurance Program] Balanced Budget Refinement Act of 1999, Pub. L. 106-113 BIPA—Medicare, Medicaid, and SCHIP [State Children's Health Insurance Program] Benefits Improvement and Protection Act of 2000, Pub. L. 106-554 CBSA—Core-Based Statistical Area CCR—Cost-to-Charge Ratio CFR—Code of Federal Regulations CMG—Case-Mix Group DRA—Deficit Reduction Act of 2005, Pub. L. 109-171 DSH—Disproportionate Share Hospital ECI—Employment Cost Indexes FI—Fiscal Intermediary FR—Federal Register FY—Federal Fiscal Year GDP—Gross Domestic Product HHH—Hubert H. Humphrey Building HIPAA—Health Insurance Portability and Accountability Act, Pub. L. 104-191 IFMC—Iowa Foundation for Medical Care IPPS—Inpatient Prospective Payment System IRF—Inpatient Rehabilitation Facility IRF-PAI—Inpatient Rehabilitation Facility-Patient Assessment Instrument IRF PPS—Inpatient Rehabilitation Facility Prospective Payment System IRVEN—Inpatient Rehabilitation Validation and Entry LIP—Low-Income Percentage MEDPAR—Medicare Provider Analysis and Review MMA—Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (Pub. L. 108-173) MSA—Metropolitan Statistical Area NAICS—North American Industrial Classification System OMB—Office of Management and Budget PAI—Patient Assessment Instrument PPS—Prospective Payment System RAND—RAND Corporation RFA—Regulatory Flexibility Act, Pub. L. 96-354 RIA—Regulation Impact Analysis RIC—Rehabilitation Impairment Category RPL—Rehabilitation, Psychiatric, and Long-Term Care Hospital Market Basket SCHIP—State Children's Health Insurance Program SIC—Standard Industrial Code TEFRA—Tax Equity and Fiscal Responsibility Act of 1982, Pub. L. 97-248 I. Background [If you choose to comment on issues in this section, please include the caption “Background” at the beginning of your comments.] A. Historical Overview of the Inpatient Rehabilitation Facility Prospective Payment System (IRF PPS) for Fiscal Years

(FYs)2002 through 2007 Section 4421 of the Balanced Budget Act of 1997 (BBA, Pub. L. 105-33), as amended by section 125 of the Medicare, Medicaid, and SCHIP [State Children's Health Insurance Program] Balanced Budget Refinement Act of 1999 (BBRA, Pub. L. 106-113), and by section 305 of the Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 (BIPA, Pub. L. 106-554), provides for the implementation of a per discharge prospective payment system (PPS), through section 1886(j) of the Social Security Act (the Act), for inpatient rehabilitation hospitals and inpatient rehabilitation units of a hospital (hereinafter referred to as IRFs). Payments under the IRF PPS encompass inpatient operating and capital costs of furnishing covered rehabilitation services (that is, routine, ancillary, and capital costs) but not costs of approved educational activities, bad debts, and other services or items outside the scope of the IRF PPS. Although a complete discussion of the IRF PPS provisions appears in the August 7, 2001 final rule (66 FR 41316) as revised in the FY 2006 IRF PPS final rule (70 FR 47880), we are providing below a general description of the IRF PPS for fiscal years

(FYs)2002 through 2005. Under the IRF PPS from FY 2002 through FY 2005, as described in the August 7, 2001 final rule, the Federal prospective payment rates were computed across 100 distinct case-mix groups (CMGs). We constructed 95 CMGs using rehabilitation impairment categories (RICs), functional status (both motor and cognitive), and age (in some cases, cognitive status and age may not be a factor in defining a CMG). In addition, we constructed five special CMGs to account for very short stays and for patients who expire in the IRF. For each of the CMGs, we developed relative weighting factors to account for a patient's clinical characteristics and expected resource needs. Thus, the weighting factors accounted for the relative difference in resource use across all CMGs. Within each CMG, we created tiers based on the estimated effects that certain comorbidities would have on resource use. We established the Federal PPS rates using a standardized payment conversion factor (formerly referred to as the budget neutral conversion factor). For a detailed discussion of the budget neutral conversion factor, please refer to our August 1, 2003 final rule (68 FR 45674, 45684 through 45685). In the FY 2006 IRF PPS final rule (70 FR 47880), we discussed in detail the methodology for determining the standard payment conversion factor. We applied the relative weighting factors to the standard payment conversion factor to compute the unadjusted Federal prospective payment rates. Under the IRF PPS from FYs 2002 through 2005, we then applied adjustments for geographic variations in wages (wage index), the percentage of low-income patients, and location in a rural area (if applicable) to the IRF's unadjusted Federal prospective payment rates. In addition, we made adjustments to account for short-stay transfer cases, interrupted stays, and high cost outliers. For cost reporting periods that began on or after January 1, 2002 and before October 1, 2002, we determined the final prospective payment amounts using the transition methodology prescribed in section 1886(j)(1) of the Act. Under this provision, IRFs transitioning into the PPS were paid a blend of the Federal IRF PPS rate and the payment that the IRF would have received had the IRF PPS not been implemented. This provision also allowed IRFs to elect to bypass this blended payment and immediately be paid 100 percent of the Federal IRF PPS rate. The transition methodology expired as of cost reporting periods beginning on or after October 1, 2002 (FY 2003), and payments for all IRFs now consist of 100 percent of the Federal IRF PPS rate. We established a CMS Web site as a primary information resource for the IRF PPS. The Web site URL is *http://www.cms.hhs.gov/InpatientRehabFacPPS/* and may be accessed to download or view publications, software, data specifications, educational materials, and other information pertinent to the IRF PPS. Section 1886(j) of the Act confers broad statutory authority to propose refinements to the IRF PPS. We finalized the refinements described in this section in the FY 2006 IRF PPS final rule (70 FR 47880). The provisions of the FY 2006 IRF PPS final rule became effective for discharges beginning on or after October 1, 2005. We published correcting amendments to the FY 2006 IRF PPS final rule in the **Federal Register** on September 30, 2005 (70 FR 57166). Any reference to the FY 2006 IRF PPS final rule in this proposed rule also includes the provisions effective in the correcting amendments. In the FY 2006 final rule (70 FR 47880 and 70 FR 57166), we finalized a number of refinements to the IRF PPS case-mix classification system (the CMGs and the corresponding relative weights) and the case-level and facility-level adjustments. These refinements were based on analyses by the RAND Corporation (RAND), a non-partisan economic and social policy research group, using calendar year 2002 and FY 2003 data. These were the first significant refinements to the IRF PPS since its implementation. In conducting the analysis, RAND used claims and clinical data for services furnished after the IRF PPS implementation. These newer data sets were more complete, and reflected improved coding of comorbidities and patient severity by IRFs. The researchers were able to use new data sources for imputing missing values and more advanced statistical approaches to complete their analyses. The RAND reports supporting the refinements made to the IRF PPS are available on the CMS Web site at: *http://www.cms.hhs.gov/InpatientRehabFacPPS/09_Research.asp* . The final key policy changes, effective for discharges occurring on or after October 1, 2005, are discussed in detail in the FY 2006 IRF PPS final rule (70 FR 47880 and 70 FR 57166). The following is a brief summary of the key policy changes: • Adopted the Office of Management and Budget's (OMB's) Core-Based Statistical Area

(CBSA)market area definitions in a budget neutral manner. • Implemented a budget-neutral three-year hold harmless policy for IRFs that had been classified as rural in FY 2005, but became urban in FY 2006. • Implemented a payment adjustment to account for changes in coding that did not reflect real changes in case mix. We reduced the standard payment amount by 1.9 percent to account for such changes in coding following implementation of the IRF PPS. • Modified the CMGs, tier comorbidities, and relative weights in a budget-neutral manner. The five special CMGs remained the same as they had been before FY 2006 and continued to account for very short stays and for patients who expire in the IRF. • Implemented a teaching status adjustment in a budget neutral manner for IRFs, similar to the one adopted for inpatient psychiatric facilities. • Revised and rebased the market basket and labor-related share to reflect the operating and capital cost structures for rehabilitation, psychiatric, and long-term care

(RPL)hospitals to update IRF payment rates. • Updated the rural adjustment from 19.14 percent to 21.3 percent in a budget neutral manner. • Updated the low-income percentage

(LIP)adjustment from an exponent of 0.484 to an exponent of 0.6229 in a budget neutral manner. • Updated the outlier threshold amount from $11,211 to $5,129. As noted above, a detailed discussion of the final key policy changes for FY 2006 appears in the FY 2006 IRF PPS final rule (70 FR 47880 and 70 FR 57166). In the FY 2007 final rule (71 FR 48354) we made the following revisions and updates: • Updated the relative weight and average length of stay tables based on re-analysis of the data by CMS and our contractor, the RAND Corporation. • Reduced the standard payment amount by 2.6 percent to account more fully for coding changes that do not reflect real changes in case mix. • Updated the IRF PPS payment rates by the FY 2007 estimates of the market basket and the labor-related share. • Updated the IRF PPS payment rates by the FY 2007 wage indexes. • Applied the second year of the hold harmless policy in a budget neutral manner. • Updated the outlier threshold from $5,129 to $5,534. • Updated the urban and rural national cost-to-charge ratio ceilings for the purposes of determining outlier payments under the IRF PPS and clarified the methodology described in the regulations text. • Revised the regulation text in § 412.23(b)(2)(i) and § 412.23(b)(2)(ii) to reflect the statutory changes in section 5005 of the Deficit Reduction Act of 2005 (DRA, Pub. L. 109-171). The regulation text change prolongs the overall duration of the phased transition to the full 75 percent threshold established in § 412.23(b)(2)(i) and § 412.23(b)(2)(ii), by extending the transition's 60 percent phase for an additional 12 months. In addition to the above DRA requirements pertaining to the applicable compliance percentage requirements under § 412.23(b)(2), we also permitted a comorbidity that meets the criteria as specified in (b)(2)(i) to continue to be used before the 75 percent compliance threshold must be met. B. Requirements for Updating the IRF PPS Rates On August 7, 2001, we published a final rule titled “Medicare Program; Prospective Payment System for Inpatient Rehabilitation Facilities” in the **Federal Register** (66 FR 41316) that established a PPS for IRFs as authorized under section 1886(j) of the Act and codified at subpart P of part 412 of the Medicare regulations. In the August 7, 2001 final rule, we set forth the per discharge Federal prospective payment rates for FY 2002, which provided payment for inpatient operating and capital costs of furnishing covered rehabilitation services (that is, routine, ancillary, and capital costs) but not costs of approved educational activities, bad debts, and other services or items that are outside the scope of the IRF PPS. The provisions of the August 7, 2001 final rule were effective for cost reporting periods beginning on or after January 1, 2002. On July 1, 2002, we published a correcting amendment to the August 7, 2001 final rule in the **Federal Register** (67 FR 44073). Any references to the August 7, 2001 final rule in this proposed rule include the provisions effective in the correcting amendment. Section 1886(j)(5) of the Act and § 412.628 of the regulations require the Secretary to publish in the **Federal Register** , on or before the August 1 that precedes the start of each new FY, the classifications and weighting factors for the IRF CMGs and a description of the methodology and data used in computing the prospective payment rates for the upcoming FY. On August 1, 2002, we published a notice in the **Federal Register** (67 FR at 49928) to update the IRF Federal prospective payment rates from FY 2002 to FY 2003 using the methodology as described in § 412.624. As stated in the August 1, 2002 notice, we used the same classifications and weighting factors for the IRF CMGs that were set forth in the August 7, 2001 final rule to update the IRF Federal prospective payment rates from FY 2002 to FY 2003. We continued to update the prospective payment rates in accordance with the methodology set forth in the August 7, 2001 final rule for each succeeding FY up to and including FY 2005. For FY 2006, however, we published a final rule that revised several IRF PPS policies (70 FR 47880). The provisions of the FY 2006 IRF PPS final rule became effective for discharges occurring on or after October 1, 2005. We published correcting amendments to the FY 2006 IRF PPS final rule in the **Federal Register** (70 FR 57166). Any reference to the FY 2006 IRF PPS final rule in this proposed rule includes the provisions effective in the correcting amendments. In the final rule for FY 2007, we updated the IRF Federal prospective payment rates. In addition, we updated the cost-to-charge ratio ceilings and the outlier threshold. We implemented a 2.6 percent reduction to the FY 2007 standard payment amount to account more fully for changes in coding practices that do not reflect real changes in case mix. We revised the tier comorbidities and the relative weights to ensure that IRF PPS payments reflect, as closely as possible, the costs of caring for patients in IRFs. The final FY 2007 Federal prospective payment rates were effective for discharges occurring on or after October 1, 2006 and on or before September 30, 2007. C. Operational Overview of the Current IRF PPS As described in the August 7, 2001 final rule, upon the admission and discharge of a Medicare Part A fee-for-service patient, the IRF is required to complete the appropriate sections of a patient assessment instrument, the Inpatient Rehabilitation Facility-Patient Assessment Instrument (IRF-PAI). All required data must be electronically encoded into the IRF-PAI software product. Generally, the software product includes patient grouping programming called the GROUPER software. The GROUPER software uses specific Patient Assessment Instrument

(PAI)data elements to classify (or group) patients into distinct CMGs and account for the existence of any relevant comorbidities. The GROUPER software produces a five-digit CMG number. The first digit is an alpha-character that indicates the comorbidity tier. The last four digits represent the distinct CMG number. (Free downloads of the Inpatient Rehabilitation Validation and Entry (IRVEN) software product, including the GROUPER software, are available on the CMS Web site at *http://www.cms.hhs.gov/InpatientRehabFacPPS/06_Software.asp* ). Once a patient is discharged, the IRF completes the Medicare claim (UB-92 or its equivalent) using the five-digit CMG number and sends it to the appropriate Medicare fiscal intermediary (FI). Claims submitted to Medicare must comply with both the Administrative Simplification Compliance Act (ASCA, Pub. L. 107-105), and the Health Insurance Portability and Accountability Act of 1996 (HIPAA, Pub. L. 104-191). Section 3 of the ASCA amends section 1862(a) of the Act by adding paragraph

(22)which requires the Medicare program, subject to section 1862(h) of the Act, to deny payment under Part A or Part B for any expenses for items or services “for which a claim is submitted other than in an electronic form specified by the Secretary.” Section 1862(h) of the Act, in turn, provides that the Secretary shall waive such denial in two types of cases and may also waive such denial “in such unusual cases as the Secretary finds appropriate.” See also the final rule on Electronic Submission of Medicare Claims (70 FR 71008, November 25, 2005). Section 3 of the ASCA operates in the context of the administrative simplification provisions of HIPAA, which include, among others, the requirements for transaction standards and code sets codified as 45 CFR parts 160 and 162, subparts A and I through R (generally known as the Transactions Rule). The Transactions Rule requires covered entities, including covered providers, to conduct covered electronic transactions according to the applicable transaction standards. (See the program claim memoranda issued and published by CMS at: *http://www.cms.hhs.gov/ElectronicBillingEDITrans/* and listed in the addenda to the Medicare Intermediary Manual, Part 3, section 3600. Instructions for the limited number of claims submitted to Medicare on paper are published by CMS at: *http://www.cms.hhs.gov/manuals/downloads/clm104c25.pdf* . The Medicare FI processes the claim through its software system. This software system includes pricing programming called the PRICER software. The PRICER software uses the CMG number, along with other specific claim data elements and provider-specific data, to adjust the IRF's prospective payment for interrupted stays, transfers, short stays, and deaths, and then applies the applicable adjustments to account for the IRF's wage index, percentage of low-income patients, rural location, and outlier payments. For discharges occurring on or after October 1, 2005, the IRF PPS payment also reflects the new teaching status adjustment that became effective as of FY 2006, as discussed in the FY 2006 IRF PPS final rule (70 FR 47880). D. Brief Summary of Proposed Revisions to the IRF PPS for FY 2008 In this proposed rule, we are proposing to make the following revisions, updates, and clarifications: • Update the FY 2008 IRF PPS payment rates by the proposed market basket, as discussed in section IV.A. • Update the FY 2008 IRF PPS payment rates by the proposed wage index and the labor related share in a budget neutral manner, as discussed in section IV.A and B. • Update the pre-reclassified and pre-floor wage indexes based on the applicable Office of Management and Budget

(OMB)bulletins that add or delete Core-Based Statistical Areas (CBSAs) numbers and title changes, as discussed in section IV.B. • Implement the final year of the 3-year hold harmless policy adopted in the FY 2006 IRF PPS final rule (70 FR 47880, 47923 through 47926) in a budget neutral manner, as discussed in section IV.B. • Update the outlier threshold amount for FY 2008 to $7,522, as discussed in section V.A. • Update the cost-to-charge ratio ceiling and the national average urban and rural cost-to-charge ratios for purposes of determining outlier payments under the IRF PPS, as discussed in section V.B. • Clarify the regulations text for the special payment provisions for patients that are transferred, as discussed in section VI. II. 75 Percent Rule Policy [If you choose to comment on issues in this section, please include the caption “75 Percent Rule Policy” at the beginning of your comments.] In order to be excluded from the acute care inpatient hospital PPS specified in § 412.1(a)(1) and instead be paid under the IRF PPS, a hospital or rehabilitation unit of an acute care hospital must meet the requirements for classification as an IRF stipulated in subpart B of part 412. As discussed in previous **Federal Register** publications (68 FR 26786 (May 16, 2003), 68 FR 53266 (September 9, 2003), 69 FR 25752 (May 7, 2004), 70 FR 36640 (June 24, 2005), and 71 FR 48354 (August 18, 2006)), § 412.23(b)(2) specifies one criterion which Medicare uses for classifying a hospital or unit of a hospital as an IRF. The criterion is that a minimum percentage of a facility's total inpatient population must require intensive rehabilitative services for the treatment of at least one of 13 medical conditions listed in § 412.23(b)(2)(iii) in order for the facility to be classified as an IRF. In addition, for cost reporting periods beginning on or after July 1, 2004, and before July 1, 2008, a patient with a comorbidity as defined at § 412.602 may be included in the inpatient population that counts toward the required applicable percentage if certain requirements are met. The minimum percentage is known as the “compliance threshold.” Prior to the May 7, 2004 final rule (69 FR 25752), § 412.23(b)(2) stipulated that the compliance threshold was 75 percent. Therefore, the compliance threshold was commonly referred to as the “75 percent rule.” In addition, prior to the May 7, 2004 final rule the regulation only specified 10 medical conditions. However, in the May 7, 2004 final rule we revised § 412.23(b)(2), and that revision increased the number of medical conditions to 13, as well as temporarily lowered the compliance threshold while at the same time specified a transition period at the end of which IRFs would once again have to meet a compliance threshold of 75 percent. Also, the revised regulation specified that during the compliance threshold transition period a patient's comorbidity may be used to determine if a provider met the compliance threshold provided certain applicable requirements were met. In § 412.602 a comorbidity is defined as a specific patient condition that is secondary to the patient's principal diagnosis. A patient's principal diagnosis is the primary reason for the patient being admitted to an IRF, and this diagnosis is used to determine if the patient had a medical condition that can be counted towards meeting the compliance threshold. As specified in the May 7, 2004 final rule, in order for an inpatient with a certain comorbidity to be included in the inpatient population that counts toward the applicable percentage the following criteria must be met: • The patient is admitted for inpatient rehabilitation for a condition that is not one of the conditions listed in § 412.23(b)(2)(iii). • The patient also has a comorbidity that falls in one of the conditions listed in § 412.23(b)(2)(iii). • The comorbidity has caused significant decline in functional ability in the individual such that, even in the absence of the admitting condition, the individual would require the intensive rehabilitation treatment that is unique to inpatient rehabilitation facilities paid under the IRF PPS and that cannot be appropriately performed in another care setting covered under this Title. In accordance with the May 7, 2004 final rule, IRFs would have to meet a compliance threshold of 75 percent for cost reporting periods starting on or after July 1, 2007. However, Section 5005 of the Deficit Reduction Act of 2005

(DRA)(Pub. L. 109-171 modified the applicable time periods when the various compliance thresholds, as originally specified in the May 7, 2004 final rule, must be met.) The net effect of the DRA was extension of the compliance threshold transition period. Due to the DRA, the transition period was extended to include cost reporting periods starting on or after July 1, 2004, and before July 1, 2008. Therefore, in order to conform the regulations to the DRA, we revised § 412.23(b)(2) and stipulated that an IRF with a cost reporting period starting on or after July 1, 2008, instead of July 1, 2007, must meet the 75 percent compliance threshold. In addition, we also permitted a comorbidity that meets the criteria as specified in (b)(2)(i) to continue to be used to determine the compliance threshold for cost reporting periods beginning before July 1, 2008 instead of July 1, 2007. (For a complete description of all the changes made, see the FY 2007 IRF PPS final rule (71 FR 48354)). For cost reporting periods beginning on or after July 1, 2008, comorbidities will not be eligible for inclusion in the calculations used to determine if the provider meets the 75 percent compliance threshold specified in § 412.23(b)(2)(ii). As the 75 percent rule is only partially phased in at this time and there are limitations to the policy conclusions that can be drawn from currently available claim and patient assessment data, this rule maintains existing policy. However, in the May 7, 2004 final rule (69 FR 25762), we encouraged research evaluating the continued use of comorbidities in determining compliance with the 75 percent rule. Therefore, we are soliciting comments supporting current policy or other options, including use of some or all of the existing comorbidities in calculating the compliance percentage for an additional fixed period of one or more years or to integrate the inclusion of some or all of the existing comorbidities on a permanent basis. In addition, we are soliciting comments that include clinical data based on scientifically sound research that provide evidence on these and other options. III. Classification System for the Inpatient Rehabilitation Facility Prospective Payment System [If you choose to comment on issues in this section, please include the caption “Classification System for the Inpatient Rehabilitation Facility Prospective Payment System” at the beginning of your comments.] For the FY 2008 IRF PPS, we will use the same case-mix classification system that we used for FY 2007, as set forth in the FY 2007 IRF PPS final rule (71 FR 48354). Table 1 below, “Relative Weights and Average Lengths of Stay for Case-Mix Groups”, presents the CMGs, the comorbidity tiers, the corresponding relative weights, and the average length of stay value for each CMG and tier. The average length of stay for each CMG is used to determine when an IRF discharge meets the definition of a short-stay transfer, which results in a per diem case level adjustment. Because these data elements are not changing, Table 1 shown below is identical to Table 4 that was published in the FY 2007 IRF PPS final rule (71 FR 48354, 48364 through 48370). The methodology we used to construct the data elements in Table 1 is described in detail in the FY 2007 IRF PPS final rule (71 FR 48354). BILLING CODE 4120-07-P EP08MY07.006 EP08MY07.007 EP08MY07.008 EP08MY07.009 EP08MY07.010 EP08MY07.011 EP08MY07.012 EP08MY07.013 BILLING CODE 4120-07-C IV. Proposed FY 2008 IRF PPS Federal Prospective Payment Rates [If you choose to comment on issues in this section, please include the caption “Proposed FY 2008 IRF PPS Federal Prospective Payment Rates” at the beginning of your comments.] A. Proposed FY 2008 IRF PPS Market Basket Increase Factor and Labor-Related Share Section 1886(j)(3)(C) of the Act requires the Secretary to establish an increase factor that reflects changes over time in the prices of an appropriate mix of goods and services included in the covered IRF services, which is referred to as a market basket index. In updating the FY 2008 payment rates outlined in this proposed rule, CMS applied an appropriate increase factor to the FY 2007 IRF PPS payment rates that is based on the rehabilitation, psychiatric, and long-term care hospital

(RPL)market basket. In constructing the RPL market basket, we used the methodology set forth in the FY 2006 IRF PPS final rule (70 FR 47880, 47908 through 47915). As discussed in that final rule, the RPL market basket primarily uses the Bureau of Labor Statistics'

(BLS)data as price proxies, which are grouped in one of the three BLS categories: Producer Price Indexes (PPI), Consumer Price Indexes (CPI), and Employment Cost Indexes (ECI). We evaluated and selected these particular price proxies using the criteria of reliability, timeliness, availability, and relevance, and believe they continue to be the best measures of price changes for the cost categories. As discussed in the FY 2007 IRF PPS proposed rule, beginning April 2006 with the publication of March 2006 data, the BLS” ECI has used a different classification system, the North American Industrial Classification System (NAICS), instead of the Standard Industrial Codes (SIC). We have consistently used the ECI as the data source for our wages and salaries and other price proxies in the RPL market basket and did not make any changes. This proposed rule's estimated FY 2008 IRF market basket increase factor and labor-related share will be updated for the final rule based on the most recent data available from the BLS. We will use the same methodology described in the FY 2006 IRF PPS final rule to compute the FY 2008 IRF market basket increase factor and labor-related share. For this proposed rule, the FY 2008 IRF market basket increase factor is 3.3 percent. This is based on Global Insight, Inc.’s forecast for the first quarter of 2007 (2007q1) with historical data through the fourth quarter of 2006 (2006q4). We propose to update the market basket with more recent data for the final rule to the extent it is available. However, we note that the President's budget includes a proposal for a zero percent update in the IRF market basket for FY 2008, and that the provisions outlined in this proposed rule would need to reflect any legislation that the Congress enacts to adopt this proposal. In addition, we have used the methodology described in the FY 2006 IRF PPS final rule to update the labor-related share for FY 2008. In FY 2004, we updated the 1992 market basket data to 1997 based on the methodology described in the August 1, 2003 final rule (68 FR 45688 through 45689). As discussed in the FY 2006 IRF PPS final rule (70 FR 47880, 47915 through 47917), we rebased and revised the market basket for FY 2006 using the 2002-based cost structures for IRFs, IPFs, and LTCHs to determine the FY 2006 labor-related share. For FY 2007, we used the same methodology discussed in the FY 2006 IRF PPS final rule (70 FR 47880, 47908 through 47917) to determine the FY 2007 IRF labor-related share. For FY 2008, we continue to use the same methodology discussed in the FY 2006 IRF PPS final rule. As shown in Table 2, the total FY 2008 RPL labor-related share is 75.846 percent in this proposed rule. We propose to update the labor-related share with more recent data for the final rule to the extent it is available. Table 2.—Proposed FY 2008 IRF Labor-Related Share Relative Importance Cost category Proposed FY 2008 IRF labor-related relative importance Wages and salaries 52.640 Employee benefits 14.149 Professional fees 2.907 All other labor intensive services 2.147 Subtotal 71.843 Labor-related share of capital costs 4.003 Total 75.846 SOURCE: Global Insight, Inc, 1st Qtr, 2007; @USMACRO/CONTROL0307 @CISSIM/TL0207.SIM Historical Data through 4th QTR, 2006 B. Proposed Area Wage Adjustment Section 1886(j)(6) of the Act requires the Secretary to adjust the proportion (as estimated by the Secretary from time to time) of rehabilitation facilities' costs attributable to wages and wage-related costs by a factor (established by the Secretary) reflecting the relative hospital wage level in the geographic area of the rehabilitation facility compared to the national average wage level for those facilities. The Secretary is required to update the wage index on the basis of information available to the Secretary on the wages and wage-related costs to furnish rehabilitation services. Any adjustments or updates made under section 1886(j)(6) of the Act for a FY are made in a budget neutral manner. In the FY 2007 IRF PPS final rule, we maintained the methodology described in the FY 2006 IRF PPS final rule to determine the wage index, labor market area definitions, and hold harmless policy consistent with the rationale outlined in that final rule (70 FR 47880, 47917 through 47933). In the FY 2006 IRF PPS final rule, we adopted a 3-year hold harmless policy specifically for rural IRFs whose labor market designations changed from rural to urban under the CBSA-based labor market area designations. This policy specifically applied to IRFs that had been previously designated rural and which, effective for discharges on or after October 1, 2005, would otherwise have become ineligible for the 19.14 percent rural adjustment. For FY 2008, the third and final year of the 3-year phase-out of the budget-neutral hold harmless policy, we will no longer apply an adjustment for IRFs that meet the criteria described in the FY 2006 final rule (70 FR 47880, 47923 through 47926). For FY 2008, we propose to maintain the policies and methodologies described in the FY 2007 IRF PPS final rule relating to the labor market area definitions, the wage index methodology for areas with wage data, and hold harmless policy consistent with the rationale outlined in the FY 2006 IRF PPS final rule (70 FR 47880, 47917 through 47933). Therefore, this proposed rule continues to use the Core-Based Statistical Area

(CBSA)labor market area definitions and the pre-reclassification and pre-floor hospital wage index based on 2003 cost report data. In addition, the budget neutral hold harmless policy established in the FY 2006 final rule will expire for discharges occurring on or after October 1, 2007. In adopting the CBSA geographic designations in FY 2006, we provided a one-year transition with a blended wage index for all providers. For FY 2006, the wage index for each provider consisted of a blend of 50 percent of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index (both using FY 2001 hospital data). We referred to the blended wage index as the FY 2006 IRF PPS transition wage index. As discussed in the FY 2006 IRF PPS final rule (70 FR 47880, 47926), subsequent to the expiration of this one-year transition on September 30, 2006, we used the full CBSA-based wage index values as published in the Addendum of the FY 2007 IRF PPS final rule (71 FR 48354) and in the Addendum of this proposed rule. When adopting OMB's new labor market designations, we identified some geographic areas where there were no hospitals and, thus, no hospital wage index data on which to base the calculation of the IRF PPS wage index (70 FR 47880). In this proposed rule, we are proposing to revise our methodology to determine a proxy for rural areas without hospital wage data. Under the CBSA labor market areas, there are no rural hospitals in rural Massachusetts and rural Puerto Rico. Because there was no rural proxy for more recent rural data within those areas, we used the FY 2006 wage index value in both FY 2006 and FY 2007 for rural Massachusetts and rural Puerto Rico. Due to the use of the same wage index value (from FY 2006) for these areas for two fiscal years, we believe it is appropriate at this point to consider alternatives in our methodology to update the wage index for rural areas without rural hospital wage index data. We believe that the best imputed proxy would 1) use pre-floor, pre-reclassified hospital data, 2) be easy to evaluate, 3) use the most local data, and 4) be easily updateable from year-to-year. Since the implementation of the IRF PPS, we have used the pre-floor, pre-reclassified hospital wage data that is easy to evaluate and is updateable from year-to-year. In addition, the IRF PPS wage index is based on hospitals' cost report data, which reflects local available data. Therefore, we believe the imputed proxy for a rural area without hospital wage data is consistent with our past methodology and other post-acute PPS wage index policy. Although our current methodology uses rural pre-floor, pre-reclassified hospital wage data, this method is not updateable from year-to-year. Therefore, in cases where there is a rural area without rural hospital wage data, we propose using the average wage index from all contiguous CBSAs to represent a reasonable proxy for the rural area within a State. While this approach does not use rural data, it does use pre-floor, pre-reclassified hospital wage data, it is easy to evaluate, it is updateable from year-to-year, and it uses the most local data available. In determining an imputed rural wage index, we interpret the term “contiguous” to mean sharing a border. For example, in the case of Massachusetts, the entire rural area consists of Dukes and Nantucket counties. We have determined that the borders of Dukes and Nantucket counties are local and contiguous with Barnstable and Bristol counties. Under the proposed methodology, the wage indexes for the counties of Barnstable (CBSA 12700: 1.2539) and Bristol (CBSA 39300: 1.0783) are averaged, resulting in an imputed rural wage index of 1.1661 for rural Massachusetts for FY 2008. While we believe that this policy could be readily applied to other rural areas that lack hospital wage data (possibly due to hospitals converting to a different provider type, such as a CAH, that does not submit the appropriate wage data), we may re-examine this policy should a similar situation arise in the future. However, we do not believe that this policy is appropriate for Puerto Rico. There are sufficient economic differences between hospitals in the United States and those in Puerto Rico (including the payment of hospitals in Puerto Rico using blended Federal/Commonwealth-specific rates) that a separate and distinct policy for Puerto Rico is necessary. Consequently, any alternative methodology for imputing a wage index for rural Puerto Rico would need to take into account these economic differences and the payment rates hospitals receive in Puerto Rico. Our policy of imputing a rural wage index based on the wage index(es) of CBSAs contiguous to the rural area in question does not recognize the unique circumstances of Puerto Rico. While we have not yet identified an alternative methodology for imputing a wage index for rural Puerto Rico, we will continue to evaluate the feasibility of using existing hospital wage data and, possibly, wage data from other sources. By maintaining our current policy for Puerto Rico, we will maintain consistency with other post-acute care PPS wage index policies. Accordingly, we propose to continue using the most recent wage index previously available for Puerto Rico; that is, a wage index of 0.4047. We solicit comments on our proposal to maintain the current wage index policy for rural Puerto Rico. In the FY 2006 IRF PPS final rule (70 FR 47880, 47920), we notified the public that the Office of Management and Budget

(OMB)published a bulletin that changed the titles to certain CBSAs after the publication of our FY 2006 IRF PPS proposed rule (70 FR 30186). Since the publication of the FY 2006 IRF PPS final rule, OMB published additional bulletins that updated the CBSAs. Specifically, OMB added or deleted certain CBSA numbers and revised certain titles. Accordingly, in this proposed rule, we are proposing to clarify that this and all subsequent IRF PPS rules and notices are considered to incorporate the CBSA changes published in the most recent OMB bulletin that applies to the hospital wage data used to determine the current IRF PPS wage index. The OMB bulletins may be accessed online at *http://www.whitehouse.gov/omb/bulletins/index.html* . To calculate the wage-adjusted facility payment for the payment rates set forth in this proposed rule, we multiply the unadjusted Federal prospective payment by the proposed FY 2008 RPL labor-related share (75.846 percent) to determine the labor-related portion of the Federal prospective payments. We then multiply this labor-related portion by the applicable proposed IRF wage index shown in Table 1 for urban areas and Table 2 for rural areas in the Addendum. Adjustments or updates to the IRF wage index made under section 1886(j)(6) of the Act must be made in a budget neutral manner; therefore, we calculated a budget neutral wage adjustment factor as established in the August 1, 2003 final rule and codified at § 412.624(e)(1), and described in the steps below. We propose to use the following steps to ensure that the FY 2008 IRF standard payment conversion factor reflects the update to the proposed wage indexes (based on the FY 2003 pre-reclassified and pre-floor hospital wage data) and the proposed labor-related share in a budget neutral manner: *Step 1* Determine the total amount of the estimated FY 2007 IRF PPS rates, using the FY 2007 standard payment conversion factor and the labor-related share and the wage indexes from FY 2007 (as published in the FY 2007 IRF PPS final rule). *Step 2* Calculate the total amount of estimated IRF PPS payments, using the FY 2007 standard payment conversion factor and the proposed FY 2008 labor-related share and proposed CBSA urban and rural wage indexes. *Step 3* Divide the amount calculated in step 1 by the amount calculated in step 2, which equals the FY 2008 budget neutral wage adjustment factor of 1.0026. *Step 4* Apply the FY 2008 budget neutral wage adjustment factor from step 3 to the FY 2007 IRF PPS standard payment conversion factor after the application of the estimated market basket update to determine the FY 2008 standard payment conversion factor. C. Description of the Proposed IRF Standard Payment Conversion Factor and Proposed Payment Rates for FY 2008 To calculate the proposed standard payment conversion factor for FY 2008 and as illustrated in Table 3 below, we begin by applying the estimated market basket increase factor (3.3 percent) to the standard payment conversion factor for FY 2007 ($12,981), which equals $13,409. We then apply the proposed combined budget neutrality factor for the wage index and labor related share and final year of the hold harmless policy of 1.0040 (1.0026 * 1.0014 = 1.0040), which would result in a proposed standard payment conversion factor of $13,463. Table 3.—Calculations To Determine the Proposed FY 2008 Standard Payment Conversion Factor Explanation for adjustment Calculations FY 2007 Standard Payment Conversion Factor 12,981 Proposed FY 2008 Market Basket Increase Factor × 1.033 Subtotal = 13,409 Proposed Budget Neutrality Factor for the Wage Index, Labor-Related Share, and the Hold Harmless Provision × 1.0040 Proposed FY 2008 Standard Payment Conversion Factor = $13,463 After the application of the relative weights, the resulting proposed unadjusted IRF prospective payment rates for FY 2008 are shown below in Table 4, “Proposed FY 2008 Payment Rates.” BILLING CODE 4120-07-P EP08MY07.014 EP08MY07.015 EP08MY07.016 EP08MY07.017 BILLING CODE 4120-07-C D. Example of the Methodology for Adjusting the Proposed Federal Prospective Payment Rates Table 5 illustrates the proposed methodology for adjusting the Federal prospective payments (as described in sections IV.A through C of this proposed rule). The examples below are based on two hypothetical Medicare beneficiaries, both classified into CMG 0110 (without comorbidities). The unadjusted Federal prospective payment rate for CMG 0110 (without comorbidities) can be found in Table 4 above. One beneficiary is in Facility A, an IRF located in rural Spencer County, Indiana, and another beneficiary is in Facility B, an IRF located in urban Harrison County, Indiana. Facility A, a non-teaching hospital, has a disproportionate share hospital

(DSH)percentage of 5 percent (which results in a LIP adjustment of 1.0309), a wage index of 0.8538, and an applicable rural adjustment of 21.3 percent. Facility B, a teaching hospital, has a DSH percentage of 15 percent (which results in a LIP adjustment of 1.0910), a wage index of 0.9118, and an applicable teaching status adjustment of 0.109. To calculate each IRF's labor and non-labor portion of the Federal prospective payment, we begin by taking the unadjusted Federal prospective payment rate for CMG 0110 (without comorbidities) from Table 4 above. Then, we multiply the estimated labor-related share (75.846) described in section IV.A by the unadjusted Federal prospective payment rate. To determine the non-labor portion of the Federal prospective payment rate, we subtract the labor portion of the Federal payment from the unadjusted Federal prospective payment. To compute the wage-adjusted Federal prospective payment, we multiply the result of the labor portion of the Federal payment by the appropriate wage index found in the Addendum in Tables 1 and 2, which will result in the wage-adjusted amount. Next, we compute the wage-adjusted Federal payment by adding the wage-adjusted amount to the non-labor portion. To adjust the Federal prospective payment by the facility-level adjustments, there are several steps. First, we take the wage-adjusted Federal prospective payment and multiply it by the appropriate rural and LIP adjustments (if applicable). Then, to determine the appropriate amount of additional payment for the teaching status adjustment (if applicable), we multiply the teaching status adjustment (0.109, in this example) by the wage-adjusted and rural-adjusted amount (if applicable). Finally, we add the additional teaching status payments (if applicable) to the wage, rural, and LIP-adjusted Federal prospective payment rate. Table 5 illustrates the components of the proposed adjusted payment calculation. BILLING CODE 4120-07-P EP08MY07.018 BILLING CODE 4120-07-C Thus, the proposed adjusted payment for Facility A would be $32,405.16 and the proposed adjusted payment for Facility B would be $32,635.56. V. Update to Payments for High-Cost Outliers Under the IRF PPS [If you choose to comment on issues in this section, please include the caption “High-Cost Outliers Under the IRF PPS” at the beginning of your comments.] A. Proposed Update to the Outlier Threshold Amount for FY 2008 Section 1886(j)(4) of the Act provides the Secretary with the authority to make payments in addition to the basic IRF prospective payments for cases incurring extraordinarily high costs. A case qualifies for an outlier payment if the estimated cost of the case exceeds the adjusted outlier threshold. We calculate the adjusted outlier threshold by adding the IRF PPS payment for the case (that is, the CMG payment adjusted by all of the relevant facility-level adjustments) and the adjusted threshold amount (also adjusted by all of the relevant facility-level adjustments). Then, we calculate the estimated cost of a case by multiplying the IRF's overall cost-to-charge ratio

(CCR)by the Medicare allowable covered charge. If the estimated cost of the case is higher than the adjusted outlier threshold, we make an outlier payment for the case equal to 80 percent of the difference between the estimated cost of the case and the outlier threshold. In the August 7, 2001 final rule (66 FR 41316, 41362 through 41363), we discussed our rationale for setting the outlier threshold amount for the IRF PPS so that estimated outlier payments would equal 3 percent of total estimated payments. Subsequently, we updated the IRF outlier threshold amount in the FYs 2006 and 2007 IRF PPS final rules (70 FR 47880 and 71 FR 48354) to maintain estimated outlier payments at 3 percent of total estimated payments, and we also stated that we would continue to analyze the estimated outlier payments for subsequent years and adjust the outlier threshold amount as appropriate to maintain the 3 percent target. For this proposed rule, we performed an updated analysis of FY 2005 claims and IRF-PAI data using the same methodology we used to set the initial outlier threshold amount when we first implemented the IRF PPS in the August 7, 2001 final rule (66 FR 41316), which is also the same methodology we used to update the outlier threshold amounts for FYs 2006 and 2007. Using the updated FY 2005 claims and IRF-PAI data, we estimate that IRF outlier payments as a percentage of total estimated payments for FY 2007 increased from 3 percent using the FY 2004 data to approximately 3.8 percent using the updated FY 2005 data. We are still investigating the reasons for the change in estimated outlier payments between FY 2004 and FY 2005, and will carefully evaluate all possible reasons for this change. Based on the updated analysis using FY 2005 data, and consistent with the broad statutory authority conferred upon the Secretary in sections 1886(j)(4)(A)(i) and 1886(j)(4)(A)(ii) of the Act, we propose to update the outlier threshold amount to $7,522 to decrease estimated outlier payments from approximately 3.8 to 3 percent of total estimated aggregate IRF payments for FY 2008. The outlier threshold amount for FY 2008 is subject to change in the final rule based on analysis of updated data. B. Update to the IRF Cost-to-Charge Ratio Ceilings In accordance with the methodology stated in the August 1, 2003 final rule (68 FR 45692 through 45694), we apply a ceiling to IRFs' cost-to-charge ratios (CCRs). Using the methodology described in that final rule, we propose to update the national urban and rural CCRs for IRFs. We apply the national urban and rural CCRs in the following situations: • New IRFs that have not yet submitted their first Medicare cost report. • IRFs whose overall CCR is in excess of 3 standard deviations above the corresponding national geometric mean, which we propose to set at 1.55 (based on the current estimate) for FY 2008. • Other IRFs for whom accurate data with which to calculate an overall CCR are not available. Specifically, for FY 2008, we estimate a proposed national CCR of 0.589 for rural IRFs and 0.475 for urban IRFs. For new facilities, we use these national ratios until the data become available for us to compute the facility's actual CCR using the first tentative settled or final settled cost report data, which we will then use for the subsequent cost reporting period. We note that the proposed national average rural and urban CCRs and our estimate of 3 standard deviations above the corresponding national geometric mean in this section are subject to change in the final rule based on updated analysis and data. C. Adjustment of IRF Outlier Payments In the August 1, 2003 final rule (68 FR 45674, 45693 through 45694), we finalized a proposal to make IRF outlier payments subject to reconciliation when IRFs' cost reports are settled, consistent with the policy adopted for IPPS hospitals in the June 9, 2003 IPPS final rule (68 FR 34494, 34501). The revised methodology provides for retroactive adjustments to IRF outlier payments to account for differences between the CCRs from the latest settled cost report and the actual CCRs computed at the time the cost report that coincides with the date of discharge is settled using the cost and charge data from that cost report. This revised methodology addresses vulnerabilities found in the IPPS and the IRF outlier payment policies, which may have resulted in outlier payments that were too high or too low. Along these lines, we are analyzing IRF outlier payments from the beginning of the IRF PPS through FY 2005, obtained from IRFs' cost report filings, to identify specific payment vulnerabilities in the IRF outlier payment policy. Under this policy, which is outlined in § 412.624(e)(5), which in turn references § 412.84(i) and § 412.84(m) of the IPPS regulations, outlier payments will be processed on an interim basis throughout the year using IRFs' CCRs based on the best information available at the time. When an IRF's cost report is settled, any reconciliation of outlier payments by fiscal intermediaries will be based on the relationship between an IRF's costs and charges at the time a particular discharge actually occurred. This revised methodology ensures that the final outlier payments reflect an accurate assessment of the actual costs the IRF incurred for treating the case. We have not yet issued instructions to the fiscal intermediaries regarding IRF outlier reconciliation because we have been analyzing the data and assessing the systems changes necessary to conduct the reconciliation. Thus, we will soon issue instructions to fiscal intermediaries to begin reconciling IRF outlier payments upon settlement of IRF cost reports. VI. Clarification to the Regulation Text for Special Payment Provisions for Patients That Are Transferred [If you choose to comment on issues in this section, please include the caption “Clarification to the Regulation Text for Special Payment Provisions for Patients that are Transferred” at the beginning of your comments.] Section 125(a)(3) of the BBRA amended Section 1886(j)(1) of the Act by adding a paragraph

(E)that states “Construction relating to transfer authority—Nothing in this subsection shall be construed as preventing the Secretary from providing for an adjustment to payments to take into account the early transfer of a patient from a rehabilitation facility to another site of care.” In the FY 2002 proposed and final IRF PPS rules, we proposed and adopted the transfer payment policy under § 412.624(f). The transfer policy provides payments that more accurately reflect facility resources used and services delivered for patients that transfer to another site of care as discussed in the FY 2002 IRF PPS final rule (66 FR 41316, 41353 through 41355). We are proposing to revise our regulations text to clarify our existing policy under § 412.624(f). In the FY 2002 IRF PPS final rule (66 FR 41316, 41353 through 41355), we discuss our rationale, criteria for defining a transfer case, and the methodology to determine the unadjusted Federal prospective payment for the transfer case. In addition, we discuss several adjustments that we apply to the unadjusted Federal prospective payment rate. The final adjustments described in the FY 2002 IRF PPS final rule (65 FR 66304, 66347 through 66357) include the area wage adjustment, rural adjustment, the LIP adjustment, and the high-cost outlier adjustment. In our FY 2006 IRF PPS final rule (70 FR 47880), we refined the facility level adjustments and also adopted a teaching status adjustment. We define a transfer under § 412.602 to mean the release of a Medicare inpatient from an IRF to another IRF, a short-term, acute-care prospective payment hospital, a long-term care hospital as described in § 412.23(e), or a nursing home that qualifies to receive Medicare or Medicaid payment. In order to receive a transfer payment under § 412.624(f), a patient must be transferred to another site of care as defined in § 412.602 and had to have stayed in the IRF for less than the average length of stay for the case-mix group (CMG). Table 1 in this proposed rule presents the CMGs, the comorbidity tiers, the corresponding relative weights, and the average length of stay value for each CMG and tier. We use the average length of stay for each CMG to determine when an IRF discharge meets the definition of a transfer, which results in a per diem case level adjustment. Since the implementation of the IRF PPS, we determine whether a claim meets the high-cost outlier policy under § 412.624(e)(5), as revised in the FY 2007 IRF PPS final rule (71 FR 48354, 48382 through 48383). A case qualifies for an outlier payment if the estimated cost of the case exceeds the adjusted outlier threshold, in which case we make an outlier payment equal to 80 percent of the difference between the estimated cost of the case and the outlier threshold. Since the implementation of the IRF PPS, we have provided an additional high-cost outlier payment to both transfer cases and full CMG cases when applicable. We propose to clarify the regulations text to articulate the transfer policy more clearly. Specifically, we propose to add the phrase “subject to paragraph (e)(5)” at the end of the paragraph under § 412.624(f)(2)(v). The proposed revised § 412.624(f)(2)(v) will read, “By applying the adjustment described in paragraphs (e)(1), (e)(2), (e)(3), (e)(4), and (e)(7) of this section to the unadjusted payment amount determined in paragraph (f)(2)(iv) of this section to equal the adjusted transfer payment amount, subject to paragraph (e)(5).” VII. Provisions of the Proposed Regulation [If you choose to comment on issues in this section, please include the caption “Provisions of the Proposed Regulations” at the beginning of your comments.] We are proposing to make revisions to the regulation text in order to implement the proposed policy changes for IRFs for FY 2007 and subsequent fiscal years. Specifically, we are proposing to make conforming changes in 42 CFR part 412. We discuss these proposed revisions and others in detail below. A. Section 412.624 Methodology for Calculating the Federal Prospective Payment Rates In this section, we are proposing to revise the current regulations text in paragraph (f)(2)(v) to clarify that we determine whether a high-cost outlier payment would be applicable for transfer cases. We emphasize that this is not a change to our current methodology for determining whether a high-cost outlier payment applies to transfer cases. B. Additional Proposed Changes • Update the FY 2008 IRF PPS payment rates by the proposed market basket, as discussed in section IV.A. • Update the FY 2008 IRF PPS payment rates by the proposed wage index and the labor related share in a budget neutral manner, as discussed in section IV.A and B. • Update the pre-reclassified and pre-floor wage indexes based on the CBSA changes published in the most recent OMB bulletins that apply to the hospital wage data used to determine the current IRF PPS wage index, as discussed in section IV.B. • Implement the final year of the three-year hold harmless policy adopted in the FY 2006 IRF PPS final rule (70 FR 47880, 447923 through 47926) in a budget neutral manner, as discussed in section IV.B. • Update the outlier threshold amount for FY 2008 to $7,522, as discussed in section V.A. • Update the cost-to-charge ratio ceiling and the national average urban and rural cost-to-charge ratios for purposes of determining outlier payments under the IRF PPS, as discussed in section V.B. VIII. Collection of Information Requirements This document does not impose information collection and recordkeeping requirements. Consequently, it need not be reviewed by the Office of Management and Budget under the authority of the Paperwork Reduction Act of 1995. IX. Response to Public Comments Because of the large number of public comments we normally receive on **Federal Register** documents, we are not able to acknowledge or respond to them individually. We will consider all comments we receive by the date and time specified in the DATES section of this preamble and, when we proceed with a subsequent document, we will respond to the comments in the preamble to that document. X. Regulatory Impact Analysis [If you choose to comment on issues in this section, please include the caption “Regulatory Impact Analysis” at the beginning of your comments.] A. Overall Impact We have examined the impacts of this proposed rule as required by Executive Order 12866 (September 1993, Regulatory Planning and Review), the Regulatory Flexibility Act (RFA, September 16, 1980, Pub. L. 96-354), section 1102(b) of the Social Security Act, the Unfunded Mandates Reform Act of 1995 (Pub. L. 104-4), and Executive Order 13132. Executive Order 12866 (as amended by Executive Order 13258, which merely reassigns responsibility of duties) directs agencies to assess all costs and benefits of available regulatory alternatives and, if regulation is necessary, to select regulatory approaches that maximize net benefits (including potential economic, environmental, public health and safety effects, distributive impacts, and equity). A regulatory impact analysis

(RIA)must be prepared for major rules with economically significant effects ($100 million or more in any one year). This proposed rule is a major rule, as defined in Title 5, United States Code, section 804(2), because we estimate the impact to the Medicare program, and the annual effects to the overall economy, would be more than $100 million. We estimate that the total impact of these proposed changes for estimated FY 2008 payments compared to estimated FY 2007 payments would be an increase of approximately $150 million (this reflects a $200 million increase from the update to the payment rates and a $50 million decrease due to the proposed update to the outlier threshold amount to decrease estimated outlier payments from approximately 3.8 percent in FY 2007 to 3 percent in FY 2008). The RFA requires agencies to analyze options for regulatory relief of small entities. For purposes of the RFA, small entities include small businesses, nonprofit organizations, and government jurisdictions. Most IRFs and most other providers and suppliers are considered small entities, either by nonprofit status or by having revenues of $6 million to $29 million in any one year. (For details, see the Small Business Administration's final rule that set forth size standards for health care industries, at 65 FR 69432, November 17, 2000.) Because we lack data on individual hospital receipts, we cannot determine the number of small proprietary IRFs or the proportion of IRFs' revenue that is derived from Medicare payments. Therefore, we assume that all IRFs (an approximate total of 1,200 IRFs, of which approximately 60 percent are nonprofit facilities) are considered small entities and that Medicare payment constitutes the majority of their revenues. The Department of Health and Human Services generally uses a revenue impact of 3 to 5 percent as a significance threshold under the RFA. As shown in Table 6, we estimate that the net revenue impact of this proposed rule on all IRFs is to increase estimated payments by about 2.4 percent, with an estimated increase in payments of 3 percent or higher for some categories of IRFs (such as rural freestanding IRFs, urban IRFs in the East North Central and Mountain regions, and rural IRFs in the Middle Atlantic and East South Central regions). Thus, we anticipate that this proposed rule may have a significant impact on a substantial number of small entities. However, the estimated impact of this proposed rule is a net increase in revenues across all categories of IRFs, so we believe that this proposed rule would not impose a significant burden on small entities. Medicare fiscal intermediaries and carriers are not considered to be small entities. Individuals and States are not included in the definition of a small entity. In addition, section 1102(b) of the Act requires us to prepare a regulatory impact analysis if a rule may have a significant impact on the operations of a substantial number of small rural hospitals. This analysis must conform to the provisions of section 603 of the RFA. For purposes of section 1102(b) of the Act, we define a small rural hospital as a hospital that is located outside of a Metropolitan Statistical Area and has fewer than 100 beds. As discussed in detail below, the rates and policies set forth in this proposed rule would not have an adverse impact on rural hospitals based on the data of the 199 rural units and 20 rural hospitals in our database of 1,234 IRFs for which data were available. Section 202 of the Unfunded Mandates Reform Act of 1995 (Pub. L. 104-4) also requires that agencies assess anticipated costs and benefits before issuing any rule whose mandates require spending in any one year of $100 million in 1995, updated annually for inflation. That threshold level is currently approximately $120 million. This proposed rule would not mandate any requirements for State, local, or tribal governments, nor would it affect private sector costs. Executive Order 13132 establishes certain requirements that an agency must meet when it promulgates a proposed rule (and subsequent final rule) that imposes substantial direct requirement costs on State and local governments, preempts State law, or otherwise has Federalism implications. As stated above, this proposed rule would not have a substantial effect on State and local governments. B. Anticipated Effects of the Proposed Rule We discuss below the impacts of this proposed rule on the budget and on IRFs. 1. Basis and Methodology of Estimates This proposed rule sets forth updates of the IRF PPS rates contained in the FY 2007 final rule, proposes an update to the outlier threshold for high-cost cases, and proposes an adjustment to the wage index methodology. Based on the above, we estimate that the FY 2008 impact would be a net increase of $150 million in payments to IRF providers (this reflects a $200 million estimated increase from the proposed update to the payment rates and a $50 million estimated decrease due to the proposed update to the outlier threshold amount to decrease the estimated outlier payments from approximately 3.8 percent in FY 2007 to 3 percent in FY 2008). The impact analysis in Table 6 of this proposed rule represents the projected effects of the proposed policy changes in the IRF PPS for FY 2008 compared with estimated IRF PPS payments in FY 2007 without the proposed policy changes. We estimate the effects by estimating payments while holding all other payment variables constant. We use the best data available, but we do not attempt to predict behavioral responses to these proposed changes, except where noted, and we do not make adjustments for future changes in such variables as number of discharges or case-mix, except where noted. We note that certain events may combine to limit the scope or accuracy of our impact analysis, because such an analysis is future-oriented and, thus, susceptible to forecasting errors because of other changes in the forecasted impact time period. Some examples could be legislative changes made by the Congress to the Medicare program that would impact program funding, or changes specifically related to IRFs. In addition, changes to the Medicare program may continue to be made as a result of the BBA, the BBRA, the BIPA, the MMA, the DRA, or new statutory provisions. Although these changes may not be specific to the IRF PPS, the nature of the Medicare program is such that the changes may interact, and the complexity of the interaction of these changes could make it difficult to predict accurately the full scope of the impact upon IRFs. In updating the rates for FY 2008, we proposed a number of standard annual revisions and clarifications mentioned elsewhere in this proposed rule (for example, the update to the wage and market basket indexes used to adjust the Federal rates). We estimate that these proposed revisions would increase payments to IRFs by approximately $200 million. The aggregate change in estimated payments associated with this proposed rule is estimated to be an increase in payments to IRFs of $150 million for FY 2008. The market basket increase of $200 million and the $50 million decrease due to the proposed update to the outlier threshold amount to decrease estimated outlier payments from approximately 3.8 percent in FY 2007 to 3.0 percent in FY 2008 would result in a net change in estimated payments from FY 2007 to FY 2008 of $150 million. The effects of the proposed changes that affect IRF PPS payment rates are shown in Table 6. The following proposed changes that affect the IRF PPS payment rates are discussed separately below: • The effects of the proposed update to the outlier threshold amount to decrease total estimated outlier payments from approximately 3.8 to 3 percent of total estimated payments for FY 2008, consistent with section 1886(j)(4) of the Act. • The effects of the annual market basket update (using the RPL market basket) to IRF PPS payment rates, as required by sections 1886(j)(3)(A)(i) and 1886(j)(3)(C) of the Act. • The effects of applying the budget-neutral labor-related share and wage index adjustment, including a proposal to revise our methodology to determine a proxy for rural areas without hospital wage data (as described in section IV of this proposed rule), as required under section 1886(j)(6) of the Act. • The effects of the final year of the 3-year budget-neutral hold-harmless policy for IRFs that were rural under § 412.602 during FY 2005, but are urban under § 412.602 beginning FY 2006 and lose the rural adjustment, resulting in a decrease in the estimated IRF PPS payments if not for the hold harmless policy. • The total proposed change in estimated payments based on the FY 2008 proposed policies relative to estimated FY 2007 payments without the proposed policies. 2. Description of Table 6 The table below categorizes IRFs by geographic location, including urban or rural location and location with respect to CMS's nine census divisions (as defined on the cost report) of the country. In addition, the table divides IRFs into those that are separate rehabilitation hospitals (otherwise called freestanding hospitals in this section), those that are rehabilitation units of a hospital (otherwise called hospital units in this section), rural or urban facilities, ownership (otherwise called for-profit, non-profit, and government), and by teaching status. The top row of the table shows the overall impact on the 1,234 IRFs included in the analysis. The next 12 rows of Table 6 contain IRFs categorized according to their geographic location, designation as either a freestanding hospital or a unit of a hospital, and by type of ownership; all urban, which is further divided into urban units of a hospital, urban freestanding hospitals, and by type of ownership; and all rural, which is further divided into rural units of a hospital, rural freestanding hospitals, and by type of ownership. There are 1,015 IRFs located in urban areas included in our analysis. Among these, there are 816 IRF units of hospitals located in urban areas and 199 freestanding IRF hospitals located in urban areas. There are 219 IRFs located in rural areas included in our analysis. Among these, there are 199 IRF units of hospitals located in rural areas and 20 freestanding IRF hospitals located in rural areas. There are 419 for-profit IRFs. Among these, there are 340 IRFs in urban areas and 79 IRFs in rural areas. There are 748 non-profit IRFs. Among these, there are 624 urban IRFs and 124 rural IRFs. There are 67 government-owned IRFs. Among these, there are 51 urban IRFs and 16 rural IRFs. The remaining three parts of Table 6 show IRFs grouped by their geographic location within a region, and the last part groups IRFs by teaching status. First, IRFs located in urban areas are categorized with respect to their location within a particular one of the nine CMS geographic regions. Second, IRFs located in rural areas are categorized with respect to their location within a particular one of the nine CMS geographic regions. In some cases, especially for rural IRFs located in the New England, Mountain, and Pacific regions, the number of IRFs represented is small. Finally, IRFs are grouped by teaching status, including non-teaching IRFs, IRFs with an intern and resident to average daily census

(ADC)ratio less than 10 percent, IRFs with an intern and resident to ADC ratio greater than or equal to 10 percent and less than or equal to 19 percent, and IRFs with an intern and resident to ADC ratio greater than 19 percent. The estimated impacts of each proposed change to the facility categories listed above are shown in the columns of Table 6. The description of each column is as follows: Column

(1)shows the facility classification categories described above. Column

(2)shows the number of IRFs in each category. Column

(3)shows the number of cases in each category. Column

(4)shows the estimated effect of the proposed adjustment to the outlier threshold amount so that estimated outlier payments decrease from approximately 3.8 percent in FY 2007 to 3 percent of total estimated payments for FY 2008. Column

(5)shows the estimated effect of the market basket update to the IRF PPS payment rates. Column

(6)shows the estimated effect of the update to the IRF labor-related share, wage index, and the final year of the hold harmless policy, in a budget neutral manner. Column

(7)compares our estimates of the payments per discharge, incorporating all of the proposed changes reflected in this proposed rule for FY 2008, to our estimates of payments per discharge in FY 2007 (without these proposed changes). The average estimated increase for all IRFs is approximately 2.4 percent. This estimated increase includes the effects of the 3.3 percent market basket update. It also includes the 0.9 percent overall estimated decrease in estimated IRF outlier payments from the proposed update to the outlier threshold amount. Because we are making the remainder of the proposed changes outlined in this proposed rule in a budget-neutral manner, they would not affect total estimated IRF payments in the aggregate. However, as described in more detail in each section, they would affect the estimated distribution of payments among providers. BILLING CODE 4120-07-P EP08MY07.019 BILLING CODE 4120-07-C 3. Impact of the Proposed Update to the Outlier Threshold Amount (Column 4, Table 6) In the FY 2007 IRF PPS final rule (71 FR 48354), we used FY 2004 patient-level claims data (the best, most complete data available at that time) to set the outlier threshold amount for FY 2007 so that estimated outlier payments would equal 3 percent of total estimated payments for FY 2007. For this proposed rule, we are proposing to update our analysis using FY 2005 data. Using the updated FY 2005 data, we now estimate that IRF outlier payments as a percentage of total estimated payments for FY 2007 increased from 3 percent using the FY 2004 data to approximately 3.8 percent using the updated FY 2005 data. Thus, we are proposing to adjust the outlier threshold amount for FY 2008 to $7,522 to set total estimated outlier payments equal to 3 percent of total estimated payments in FY 2008. The proposed estimated change in total payments between FY 2007 and FY 2008, therefore, includes a 0.9 percent (rounded from 0.85 percent) overall estimated decrease in payments because the estimated outlier portion of total payments is estimated to decrease from approximately 3.8 percent to 3 percent. The impact of this proposed update (as shown in column 4 of Table 6) is to decrease estimated overall payments to IRFs by 0.9 percent. We do not estimate that any group of IRFs would experience an increase in payments from this proposed update. We estimate the largest decrease in payments to be a 1.7 percent decrease in estimated payments to rural IRFs in the Mountain region. 4. Impact of the Proposed Market Basket Update to the IRF PPS Payment Rates (Column 5, Table 6) In column 5 of Table 6, we present the estimated effects of the proposed market basket update to the IRF PPS payment rates. In the aggregate, and across all hospital groups, the proposed update would result in a 3.3 percent increase in overall estimated payments to IRFs. 5. Impact of the Proposed CBSA Wage Index, Labor-Related Share, and the Hold Harmless Policy for FY 2008 (Column 6, Table 6). In column 6 of Table 6, we present the effects of the proposed budget neutral update of the wage index, labor-related share, and the final year of the hold harmless policy. In FY 2006, we provided a 1-year blended wage index and a 3-year phase out of the rural adjustment for IRFs that changed designation because of the change from MSAs to CBSAs (referenced as the hold harmless policy). We applied the blended wage index to all IRFs and the hold harmless policy to those IRFs that qualify, as described in § 412.624(e)(7), in order to mitigate the impact of the change from the MSA-based labor area definitions to the CBSA-based labor area definitions for IRFs. As discussed in the FY 2007 IRF PPS final rule (71 FR 48345), the blended wage index expired in FY 2007 and will not be applied for discharges occurring on or after October 1, 2006. In addition, FY 2008 is the third and final year of the hold harmless policy, and we are continuing to apply this policy as described in the FY 2006 final rule in a budget neutral manner. As discussed in this proposed rule, we are proposing to revise our methodology to impute a rural wage index value for rural areas without hospital wage data and update the wage index based on the CBSA-based labor market area definitions in a budget neutral manner. We are also applying the third and final year of the hold harmless policy in a budget neutral manner. Thus, in the aggregate, the estimated impact of the proposed update to the wage index and labor-related share is zero percent. In the aggregate and for all urban IRFs, we do not estimate that these proposed changes would affect overall estimated payments to IRFs. However, we estimate that these proposed changes would have small distributional effects. We estimate a 0.2 percent increase in estimated payments to rural IRFs. We estimate the largest increase in payments to be a 0.7 percent increase for urban IRFs in the Mountain region and for rural IRFs in the Middle Atlantic region. We estimate the largest decrease in payments to be a 0.9 percent decrease for rural IRFs in the New England region. C. Anticipated Effects of the 75 Percent Rule Policy The existing policy for classifying a facility as an IRF, which is described in § 412.23(b)(2), allows the inclusion of comorbidities meeting certain requirements in the calculations used to determine the compliance percentage for cost reporting periods beginning on or after July 1, 2004, and before July 1, 2008. However, for cost reporting periods beginning on or after July 1, 2008, comorbidities will not be eligible for inclusion in the calculations used to determine if the provider meets the 75 percent compliance threshold. As discussed in section II of this proposed rule, we are not proposing to change existing policy. On or after July 1, 2008, we anticipate that IRFs would make adjustments to their admission and coding practices to continue to meet the compliance threshold. Data limitations and two important sources of uncertainty prevent a precise estimate of the effect of this policy at this time. One source of uncertainty is what proportion of patients who would no longer be treated in IRFs would instead be treated by other, lower-cost post-acute care settings such as skilled nursing facilities or home health agencies. Another source of uncertainty is determining how providers will make adjustments on or after July 1, 2008. While we cannot make a precise estimate at this time, we anticipate modest decreases in Medicare payments beginning on or after July 1, 2008. D. Alternatives Considered Because we have determined that this proposed rule would have a significant economic impact on IRFs and on a substantial number of small entities, we will discuss the alternative changes to the IRF PPS that we considered. Section 1886(j)(3)(C) of the Act requires the Secretary to update the IRF PPS payment rates by an increase factor that reflects changes over time in the prices of an appropriate mix of goods and services included in the covered IRF services. As discussed above, we estimate the RPL market basket increase factor for FY 2008 to be 3.3 percent. This increase factor represents the majority of the impact on IRF providers shown in Table 6. Thus, we believe this estimated net increase in payments across all categories of IRFs represents a benefit to IRF providers and, thus, to IRFs that are small entities. We considered maintaining the existing outlier threshold amount for FY 2008 because this proposed update would have a negative impact on IRF providers and, therefore, on small entities. If we maintain the FY 2007 outlier threshold amount, more outlier cases would have qualified for the additional outlier payments in FY 2008. However, analysis of updated FY 2005 data indicates that estimated outlier payments would not equal 3 percent of estimated total payments for FY 2008 unless we proposed to update the outlier threshold amount. Also, we estimate that the effect of this proposal on estimated payments to IRFs is small (less than 1 percent). E. Accounting Statement As required by OMB Circular A-4 (available at *http://www.whitehouse.gov/omb/circulars/a004/a-4.pdf* ), in Table 8 below, we have prepared an accounting statement showing the classification of the expenditures associated with the provisions of this proposed rule. This table provides our best estimate of the increase in Medicare payments under the IRF PPS as a result of the proposed changes presented in this proposed rule based on the data for 1,234 IRFs in our database. All estimated expenditures are classified as transfers to Medicare providers (that is, IRFs). Table 8.—Accounting Statement: Classification of Estimated Expenditures, from the 2007 IRF PPS Rate Year to the 2008 IRF PPS Rate Year (in Millions) Category Transfers Annualized Monetized Transfers $150 million. From Whom To Whom? Federal Government to IRF Medicare Providers. F. Conclusion (Column 7, Table 6) Overall, the estimated payments per discharge for IRFs in FY 2008 are projected to increase by 2.4 percent, compared with those in FY 2007, as reflected in column 7 of Table 6. We estimate that IRFs in urban areas would experience a 2.4 percent increase in estimated payments per discharge compared with FY 2007. We estimate that IRFs in rural areas would experience a 2.7 percent increase in estimated payments per discharge compared with FY 2007. We estimate that rehabilitation units and freestanding rehabilitation hospitals in urban areas would both experience a 2.4 percent increase in estimated payments per discharge. We estimate that rehabilitation units in rural areas would experience a 2.6 percent increase in estimated payments per discharge, while freestanding rehabilitation hospitals in rural areas would experience a 3.1 percent increase in estimated payments per discharge. Overall, we estimate that the largest payment increase would be 3.4 percent among rural IRFs in the Middle Atlantic region. We do not estimate that any group of IRFs would experience an overall decrease in payments from the proposed changes in this proposed rule. In accordance with the provisions of Executive Order 12866, this regulation was reviewed by the Office of Management and Budget. List of Subjects in 42 CFR Part 412 Administrative practice and procedure, Health facilities, Medicare, Puerto Rico, Reporting and recordkeeping requirements. For the reasons set forth in the preamble, the Centers for Medicare & Medicaid Services proposes to amend 42 CFR chapter IV as follows: PART 412—PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL SERVICES 1. The authority citation for part 412 continues to read as follows: Authority: Secs. 1102 and 1871 of the Social Security Act (42 U.S.C. 1302 and 1395hh). Subpart P—Prospective Payment for Inpatient Rehabilitation Hospitals and Rehabilitation Units 2. Section 412.624 is amended by revising paragraph (f)(2)(v) to read as follows: § 412.624 Methodology for calculating the Federal prospective payment rates.

(f)* * *

(2)* * *

(v)By applying the adjustment described in paragraphs (e)(1), (e)(2), (e)(3), (e)(4), and (e)(7) of this section to the unadjusted payment amount determined in paragraph (f)(2)(iv) of this section to equal the adjusted transfer payment amount, subject to paragraph (e)(5) of this section. (Catalog of Federal Domestic Assistance Program No. 93.773, Medicare—Hospital Insurance; and Program No. 93.774, Medicare—Supplemental Medical Insurance Program). Dated: March 22, 2007. Leslie V. Norwalk, Acting Administrator, Centers for Medicare & Medicaid Services. Approved: April 3, 2007. Michael O. Leavitt, Secretary. The following addendum will not appear in the Code of Federal Regulations. Addendum This addendum contains the tables referred to throughout the preamble of this proposed rule. The tables presented below are as follows: Table 1.—Proposed Inpatient Rehabilitation Facility Wage Index for Urban Areas for Discharges Occurring from October 1, 2007 through September 30, 2008 Table 2.—Proposed Inpatient Rehabilitation Facility Wage Index for Rural Areas for Discharges Occurring from October 1, 2007 through September 30, 2008 Table 1.—Proposed Inpatient Rehabilitation Facility Wage Index for Urban Areas for Discharges Occurring From October 1, 2007 Through September 30, 2008 CBSA code Urban area (constituent counties) Wage index 10180 Abilene, TX 0.8000 Callahan County, TX Jones County, TX Taylor County, TX 10380 Aguadilla-Isabela-San Sebastián, PR 0.3915 Aguada Municipio, PR Aguadilla Municipio, PR Añasco Municipio, PR Isabela Municipio, PR Lares Municipio, PR Moca Municipio, PR Rincón Municipio, PR San Sebastián Municipio, PR 10420 Akron, OH 0.8654 Portage County, OH Summit County, OH 10500 Albany, GA 0.8991 Baker County, GA Dougherty County, GA Lee County, GA Terrell County, GA Worth County, GA 10580 Albany-Schenectady-Troy, NY 0.8720 Albany County, NY Rensselaer County, NY Saratoga County, NY Schenectady County, NY Schoharie County, NY 10740 Albuquerque, NM 0.9458 Bernalillo County, NM Sandoval County, NM Torrance County, NM Valencia County, NM 10780 Alexandria, LA 0.8006 Grant Parish, LA Rapides Parish, LA 10900 Allentown-Bethlehem-Easton, PA-NJ 0.9947 Warren County, NJ Carbon County, PA Lehigh County, PA Northampton County, PA 11020 Altoona, PA 0.8812 Blair County, PA 11100 Amarillo, TX 0.9169 Armstrong County, TX Carson County, TX Potter County, TX Randall County, TX 11180 Ames, IA 0.9760 Story County, IA 11260 Anchorage, AK 1.2023 Anchorage Municipality, AK Matanuska-Susitna Borough, AK 11300 Anderson, IN 0.8681 Madison County, IN 11340 Anderson, SC 0.9017 Anderson County, SC 11460 Ann Arbor, MI 1.0826 Washtenaw County, MI 11500 Anniston-Oxford, AL 0.7770 Calhoun County, AL 11540 Appleton, WI 0.9455 Calumet County, WI Outagamie County, WI 11700 Asheville, NC 0.9216 Buncombe County, NC Haywood County, NC Henderson County, NC Madison County, NC 12020 Athens-Clarke County, GA 0.9856 Clarke County, GA Madison County, GA Oconee County, GA Oglethorpe County, GA 12060 Atlanta-Sandy Springs-Marietta, GA 0.9762 Barrow County, GA Bartow County, GA Butts County, GA Carroll County, GA Cherokee County, GA Clayton County, GA Cobb County, GA Coweta County, GA Dawson County, GA DeKalb County, GA Douglas County, GA Fayette County, GA Forsyth County, GA Fulton County, GA Gwinnett County, GA Haralson County, GA Heard County, GA Henry County, GA Jasper County, GA Lamar County, GA Meriwether County, GA Newton County, GA Paulding County, GA Pickens County, GA Pike County, GA Rockdale County, GA Spalding County, GA Walton County, GA 12100 Atlantic City, NJ 1.1831 Atlantic County, NJ 12220 Auburn-Opelika, AL 0.8096 Lee County, AL 12260 Augusta-Richmond County, GA-SC 0.9667 Burke County, GA Columbia County, GA McDuffie County, GA Richmond County, GA Aiken County, SC Edgefield County, SC 12420 Austin-Round Rock, TX 0.9344 Bastrop County, TX Caldwell County, TX Hays County, TX Travis County, TX Williamson County, TX 12540 Bakersfield, CA 1.0725 Kern County, CA 12580 Baltimore-Towson, MD 1.0088 Anne Arundel County, MD Baltimore County, MD Carroll County, MD Harford County, MD Howard County, MD Queen Anne's County, MD Baltimore City, MD 12620 Bangor, ME 0.9711 Penobscot County, ME 12700 Barnstable Town, MA 1.2539 Barnstable County, MA 12940 Baton Rouge, LA 0.8084 Ascension Parish, LA East Baton Rouge Parish, LA East Feliciana Parish, LA Iberville Parish, LA Livingston Parish, LA Pointe Coupee Parish, LA St. Helena Parish, LA West Baton Rouge Parish, LA West Feliciana Parish, LA 12980 Battle Creek, MI 0.9762 Calhoun County, MI 13020 Bay City, MI 0.9251 Bay County, MI 13140 Beaumont-Port Arthur, TX 0.8595 Hardin County, TX Jefferson County, TX Orange County, TX 13380 Bellingham, WA 1.1104 Whatcom County, WA 13460 Bend, OR 1.0743 Deschutes County, OR 13644 Bethesda-Frederick-Gaithersburg, MD 1.0903 Frederick County, MD Montgomery County, MD 13740 Billings, MT 0.8712 Carbon County, MT Yellowstone County, MT 13780 Binghamton, NY 0.8786 Broome County, NY Tioga County, NY 13820 Birmingham-Hoover, AL 0.8894 Bibb County, AL Blount County, AL Chilton County, AL Jefferson County, AL St. Clair County, AL Shelby County, AL Walker County, AL 13900 Bismarck, ND 0.7240 Burleigh County, ND Morton County, ND 13980 Blacksburg-Christiansburg-Radford, VA 0.8213 Giles County, VA Montgomery County, VA Pulaski County, VA Radford City, VA 14020 Bloomington, IN 0.8533 Greene County, IN Monroe County, IN Owen County, IN 14060 Bloomington-Normal, IL 0.8944 McLean County, IL 14260 Boise City-Nampa, ID 0.9401 Ada County, ID Boise County, ID Canyon County, ID Gem County, ID Owyhee County, ID 14484 Boston-Quincy, MA 1.1679 Norfolk County, MA Plymouth County, MA Suffolk County, MA 14500 Boulder, CO 1.0350 Boulder County, CO 14540 Bowling Green, KY 0.8148 Edmonson County, KY Warren County, KY 14740 Bremerton-Silverdale, WA 1.0913 Kitsap County, WA 14860 Bridgeport-Stamford-Norwalk, CT 1.2659 Fairfield County, CT 15180 Brownsville-Harlingen, TX 0.9430 Cameron County, TX 15260 Brunswick, GA 1.0164 Brantley County, GA Glynn County, GA McIntosh County, GA 15380 Buffalo-Niagara Falls, NY 0.9424 Erie County, NY Niagara County, NY 15500 Burlington, NC 0.8674 Alamance County, NC 15540 Burlington-South Burlington, VT 0.9474 Chittenden County, VT Franklin County, VT Grand Isle County, VT 15764 Cambridge-Newton-Framingham, MA 1.0970 Middlesex County, MA 15804 Camden, NJ 1.0392 Burlington County, NJ Camden County, NJ Gloucester County, NJ 15940 Canton-Massillon, OH 0.9031 Carroll County, OH Stark County, OH 15980 Cape Coral-Fort Myers, FL 0.9342 Lee County, FL 16180 Carson City, NV 1.0025 Carson City, NV 16220 Casper, WY 0.9145 Natrona County, WY 16300 Cedar Rapids, IA 0.8888 Benton County, IA Jones County, IA Linn County, IA 16580 Champaign-Urbana, IL 0.9644 Champaign County, IL Ford County, IL Piatt County, IL 16620 Charleston, WV 0.8542 Boone County, WV Clay County, WV Kanawha County, WV Lincoln County, WV Putnam County, WV 16700 Charleston-North Charleston, SC 0.9145 Berkeley County, SC Charleston County, SC Dorchester County, SC 16740 Charlotte-Gastonia-Concord, NC-SC 0.9554 Anson County, NC Cabarrus County, NC Gaston County, NC Mecklenburg County, NC Union County, NC York County, SC 16820 Charlottesville, VA 1.0125 Albemarle County, VA Fluvanna County, VA Greene County, VA Nelson County, VA Charlottesville City, VA 16860 Chattanooga, TN-GA 0.8948 Catoosa County, GA Dade County, GA Walker County, GA Hamilton County, TN Marion County, TN Sequatchie County, TN 16940 Cheyenne, WY 0.9060 Laramie County, WY 16974 Chicago-Naperville-Joliet, IL 1.0751 Cook County, IL DeKalb County, IL DuPage County, IL Grundy County, IL Kane County, IL Kendall County, IL McHenry County, IL Will County, IL 17020 Chico, CA 1.1053 Butte County, CA 17140 Cincinnati-Middletown, OH-KY-IN 0.9601 Dearborn County, IN Franklin County, IN Ohio County, IN Boone County, KY Bracken County, KY Campbell County, KY Gallatin County, KY Grant County, KY Kenton County, KY Pendleton County, KY Brown County, OH Butler County, OH Clermont County, OH Hamilton County, OH Warren County, OH 17300 Clarksville, TN-KY 0.8436 Christian County, KY Trigg County, KY Montgomery County, TN Stewart County, TN 17420 Cleveland, TN 0.8109 Bradley County, TN Polk County, TN 17460 Cleveland-Elyria-Mentor, OH 0.9400 Cuyahoga County, OH Geauga County, OH Lake County, OH Lorain County, OH Medina County, OH 17660 Coeur d'Alene, ID 0.9344 Kootenai County, ID 17780 College Station-Bryan, TX 0.9045 Brazos County, TX Burleson County, TX Robertson County, TX 17820 Colorado Springs, CO 0.9701 El Paso County, CO Teller County, CO 17860 Columbia, MO 0.8542 Boone County, MO Howard County, MO 17900 Columbia, SC 0.8933 Calhoun County, SC Fairfield County, SC Kershaw County, SC Lexington County, SC Richland County, SC Saluda County, SC 17980 Columbus, GA-AL 0.8239 Russell County, AL Chattahoochee County, GA Harris County, GA Marion County, GA Muscogee County, GA 18020 Columbus, IN 0.9318 Bartholomew County, IN 18140 Columbus, OH 1.0107 Delaware County, OH Fairfield County, OH Franklin County, OH Licking County, OH Madison County, OH Morrow County, OH Pickaway County, OH Union County, OH 18580 Corpus Christi, TX 0.8564 Aransas County, TX Nueces County, TX San Patricio County, TX 18700 Corvallis, OR 1.1546 Benton County, OR 19060 Cumberland, MD-WV 0.8446 Allegany County, MD Mineral County, WV 19124 Dallas-Plano-Irving, TX 1.0075 Collin County, TX Dallas County, TX Delta County, TX Denton County, TX Ellis County, TX Hunt County, TX Kaufman County, TX Rockwall County, TX 19140 Dalton, GA 0.9093 Murray County, GA Whitfield County, GA 19180 Danville, IL 0.9266 Vermilion County, IL 19260 Danville, VA 0.8451 Pittsylvania County, VA Danville City, VA 19340 Davenport-Moline-Rock Island, IA-IL 0.8846 Henry County, IL Mercer County, IL Rock Island County, IL Scott County, IA 19380 Dayton, OH 0.9037 Greene County, OH Miami County, OH Montgomery County, OH Preble County, OH 19460 Decatur, AL 0.8159 Lawrence County, AL Morgan County, AL 19500 Decatur, IL 0.8172 Macon County, IL 19660 Deltona-Daytona Beach-Ormond Beach, FL 0.9263 Volusia County, FL 19740 Denver-Aurora, CO 1.0930 Adams County, CO Arapahoe County, CO Broomfield County, CO Clear Creek County, CO Denver County, CO Douglas County, CO Elbert County, CO Gilpin County, CO Jefferson County, CO Park County, CO 19780 Des Moines-West Des Moines, IA 0.9214 Dallas County, IA Guthrie County, IA Madison County, IA Polk County, IA Warren County, IA 19804 Detroit-Livonia-Dearborn, MI 1.0281 Wayne County, MI 20020 Dothan, AL 0.7381 Geneva County, AL Henry County, AL Houston County, AL 20100 Dover, DE 0.9847 Kent County, DE 20220 Dubuque, IA 0.9133 Dubuque County, IA 20260 Duluth, MN-WI 1.0042 Carlton County, MN St. Louis County, MN Douglas County, WI 20500 Durham, NC 0.9826 Chatham County, NC Durham County, NC Orange County, NC Person County, NC 20740 Eau Claire, WI 0.9630 Chippewa County, WI Eau Claire County, WI 20764 Edison, NJ 1.1190 Middlesex County, NJ Monmouth County, NJ Ocean County, NJ Somerset County, NJ 20940 El Centro, CA 0.9076 Imperial County, CA 21060 Elizabethtown, KY 0.8697 Hardin County, KY Larue County, KY 21140 Elkhart-Goshen, IN 0.9426 Elkhart County, IN 21300 Elmira, NY 0.8240 Chemung County, NY 21340 El Paso, TX 0.9053 El Paso County, TX 21500 Erie, PA 0.8827 Erie County, PA 21604 Essex County, MA 1.0418 Essex County, MA 21660 Eugene-Springfield, OR 1.0876 Lane County, OR 21780 Evansville, IN-KY 0.9071 Gibson County, IN Posey County, IN Vanderburgh County, IN Warrick County, IN Henderson County, KY Webster County, KY 21820 Fairbanks, AK 1.1059 Fairbanks North Star Borough, AK 21940 Fajardo, PR 0.4036 Ceiba Municipio, PR Fajardo Municipio, PR Luquillo Municipio, PR 22020 Fargo, ND-MN 0.8250 Cass County, ND Clay County, MN 22140 Farmington, NM 0.8589 San Juan County, NM 22180 Fayetteville, NC 0.8945 Cumberland County, NC Hoke County, NC 22220 Fayetteville-Springdale-Rogers, AR-MO 0.8865 Benton County, AR Madison County, AR Washington County, AR McDonald County, MO 22380 Flagstaff, AZ 1.1601 Coconino County, AZ 22420 Flint, MI 1.0969 Genesee County, MI 22500 Florence, SC 0.8388 Darlington County, SC Florence County, SC 22520 Florence-Muscle Shoals, AL 0.7843 Colbert County, AL Lauderdale County, AL 22540 Fond du Lac, WI 1.0063 Fond du Lac County, WI 22660 Fort Collins-Loveland, CO 0.9544 Larimer County, CO 22744 Fort Lauderdale-Pompano Beach-Deerfield Beach, FL 1.0133 Broward County, FL 22900 Fort Smith, AR-OK 0.7731 Crawford County, AR Franklin County, AR Sebastian County, AR Le Flore County, OK Sequoyah County, OK 23020 Fort Walton Beach-Crestview-Destin, FL 0.8643 Okaloosa County, FL 23060 Fort Wayne, IN 0.9517 Allen County, IN Wells County, IN Whitley County, IN 23104 Fort Worth-Arlington, TX 0.9569 Johnson County, TX Parker County, TX Tarrant County, TX Wise County, TX 23420 Fresno, CA 1.0943 Fresno County, CA 23460 Gadsden, AL 0.8066 Etowah County, AL 23540 Gainesville, FL 0.9277 Alachua County, FL Gilchrist County, FL 23580 Gainesville, GA 0.8958 Hall County, GA 23844 Gary, IN 0.9334 Jasper County, IN Lake County, IN Newton County, IN Porter County, IN 24020 Glens Falls, NY 0.8324 Warren County, NY Washington County, NY 24140 Goldsboro, NC 0.9171 Wayne County, NC 24220 Grand Forks, ND-MN 0.7949 Polk County, MN Grand Forks County, ND 24300 Grand Junction, CO 0.9668 Mesa County, CO 24340 Grand Rapids-Wyoming, MI 0.9455 Barry County, MI Ionia County, MI Kent County, MI Newaygo County, MI 24500 Great Falls, MT 0.8598 Cascade County, MT 24540 Greeley, CO 0.9602 Weld County, CO 24580 Green Bay, WI 0.9787 Brown County, WI Kewaunee County, WI Oconto County, WI 24660 Greensboro-High Point, NC 0.8866 Guilford County, NC Randolph County, NC Rockingham County, NC 24780 Greenville, NC 0.9432 Greene County, NC Pitt County, NC 24860 Greenville, SC 0.9804 Greenville County, SC Laurens County, SC Pickens County, SC 25020 Guayama, PR 0.3235 Arroyo Municipio, PR Guayama Municipio, PR Patillas Municipio, PR 25060 Gulfport-Biloxi, MS 0.8915 Hancock County, MS Harrison County, MS Stone County, MS 25180 Hagerstown-Martinsburg, MD-WV 0.9038 Washington County, MD Berkeley County, WV Morgan County, WV 25260 Hanford-Corcoran, CA 1.0282 Kings County, CA 25420 Harrisburg-Carlisle, PA 0.9402 Cumberland County, PA Dauphin County, PA Perry County, PA 25500 Harrisonburg, VA 0.9073 Rockingham County, VA Harrisonburg City, VA 25540 Hartford-West Hartford-East Hartford, CT 1.0894 Hartford County, CT Litchfield County, CT Middlesex County, CT Tolland County, CT 25620 Hattiesburg, MS 0.7430 Forrest County, MS Lamar County, MS Perry County, MS 25860 Hickory-Lenoir-Morganton, NC 0.9010 Alexander County, NC Burke County, NC Caldwell County, NC Catawba County, NC 25980 Hinesville-Fort Stewart, GA 1 0.9178 Liberty County, GA Long County, GA 26100 Holland-Grand Haven, MI 0.9163 Ottawa County, MI 26180 Honolulu, HI 1.1096 Honolulu County, HI 26300 Hot Springs, AR 0.8782 Garland County, AR 26380 Houma-Bayou Cane-Thibodaux, LA 0.8082 Lafourche Parish, LA Terrebonne Parish, LA 26420 Houston-Sugar Land-Baytown, TX 1.0008 Austin County, TX Brazoria County, TX Chambers County, TX Fort Bend County, TX Galveston County, TX Harris County, TX Liberty County, TX Montgomery County, TX San Jacinto County, TX Waller County, TX 26580 Huntington-Ashland, WV-KY-OH 0.8997 Boyd County, KY Greenup County, KY Lawrence County, OH Cabell County, WV Wayne County, WV 26620 Huntsville, AL 0.9007 Limestone County, AL Madison County, AL 26820 Idaho Falls, ID 0.9088 Bonneville County, ID Jefferson County, ID 26900 Indianapolis-Carmel, IN 0.9895 Boone County, IN Brown County, IN Hamilton County, IN Hancock County, IN Hendricks County, IN Johnson County, IN Marion County, IN Morgan County, IN Putnam County, IN Shelby County, IN 26980 Iowa City, IA 0.9714 Johnson County, IA Washington County, IA 27060 Ithaca, NY 0.9928 Tompkins County, NY 27100 Jackson, MI 0.9560 Jackson County, MI 27140 Jackson, MS 0.8271 Copiah County, MS Hinds County, MS Madison County, MS Rankin County, MS Simpson County, MS 27180 Jackson, TN 0.8853 Chester County, TN Madison County, TN 27260 Jacksonville, FL 0.9165 Baker County, FL Clay County, FL Duval County, FL Nassau County, FL St. Johns County, FL 27340 Jacksonville, NC 0.8231 Onslow County, NC 27500 Janesville, WI 0.9655 Rock County, WI 27620 Jefferson City, MO 0.8332 Callaway County, MO Cole County, MO Moniteau County, MO Osage County, MO 27740 Johnson City, TN 0.8043 Carter County, TN Unicoi County, TN Washington County, TN 27780 Johnstown, PA 0.8620 Cambria County, PA 27860 Jonesboro, AR 0.7662 Craighead County, AR Poinsett County, AR 27900 Joplin, MO 0.8605 Jasper County, MO Newton County, MO 28020 Kalamazoo-Portage, MI 1.0704 Kalamazoo County, MI Van Buren County, MI 28100 Kankakee-Bradley, IL 1.0083 Kankakee County, IL 28140 Kansas City, MO-KS 0.9495 Franklin County, KS Johnson County, KS Leavenworth County, KS Linn County, KS Miami County, KS Wyandotte County, KS Bates County, MO Caldwell County, MO Cass County, MO Clay County, MO Clinton County, MO Jackson County, MO Lafayette County, MO Platte County, MO Ray County, MO 28420 Kennewick-Richland-Pasco, WA 1.0343 Benton County, WA Franklin County, WA 28660 Killeen-Temple-Fort Hood, TX 0.8901 Bell County, TX Coryell County, TX Lampasas County, TX 28700 Kingsport-Bristol-Bristol, TN-VA 0.7985 Hawkins County, TN Sullivan County, TN Bristol City, VA Scott County, VA Washington County, VA 28740 Kingston, NY 0.9367 Ulster County, NY 28940 Knoxville, TN 0.8249 Anderson County, TN Blount County, TN Knox County, TN Loudon County, TN Union County, TN 29020 Kokomo, IN 0.9669 Howard County, IN Tipton County, IN 29100 La Crosse, WI-MN 0.9426 Houston County, MN La Crosse County, WI 29140 Lafayette, IN 0.8931 Benton County, IN Carroll County, IN Tippecanoe County, IN 29180 Lafayette, LA 0.8289 Lafayette Parish, LA St. Martin Parish, LA 29340 Lake Charles, LA 0.7914 Calcasieu Parish, LA Cameron Parish, LA 29404 Lake County-Kenosha County, IL-WI 1.0570 Lake County, IL Kenosha County, WI 29460 Lakeland, FL 0.8879 Polk County, FL 29540 Lancaster, PA 0.9589 Lancaster County, PA 29620 Lansing-East Lansing, MI 1.0088 Clinton County, MI Eaton County, MI Ingham County, MI 29700 Laredo, TX 0.7811 Webb County, TX 29740 Las Cruces, NM 0.9273 Dona Ana County, NM 29820 Las Vegas-Paradise, NV 1.1430 Clark County, NV 29940 Lawrence, KS 0.8365 Douglas County, KS 30020 Lawton, OK 0.8065 Comanche County, OK 30140 Lebanon, PA 0.8679 Lebanon County, PA 30300 Lewiston, ID-WA 0.9853 Nez Perce County, ID Asotin County, WA 30340 Lewiston-Auburn, ME 0.9126 Androscoggin County, ME 30460 Lexington-Fayette, KY 0.9181 Bourbon County, KY Clark County, KY Fayette County, KY Jessamine County, KY Scott County, KY Woodford County, KY 30620 Lima, OH 0.9042 Allen County, OH 30700 Lincoln, NE 1.0092 Lancaster County, NE Seward County, NE 30780 Little Rock-North Little Rock, AR 0.8890 Faulkner County, AR Grant County, AR Lonoke County, AR Perry County, AR Pulaski County, AR Saline County, AR 30860 Logan, UT-ID 0.9022 Franklin County, ID Cache County, UT 30980 Longview, TX 0.8788 Gregg County, TX Rusk County, TX Upshur County, TX 31020 Longview, WA 1.0011 Cowlitz County, WA 31084 Los Angeles-Long Beach-Glendale, CA 1.1760 Los Angeles County, CA 31140 Louisville, KY-IN 0.9118 Clark County, IN Floyd County, IN Harrison County, IN Washington County, IN Bullitt County, KY Henry County, KY Jefferson County, KY Meade County, KY Nelson County, KY Oldham County, KY Shelby County, KY Spencer County, KY Trimble County, KY 31180 Lubbock, TX 0.8613 Crosby County, TX Lubbock County, TX 31340 Lynchburg, VA 0.8694 Amherst County, VA Appomattox County, VA Bedford County, VA Campbell County, VA Bedford City, VA Lynchburg City, VA 31420 Macon, GA 0.9519 Bibb County, GA Crawford County, GA Jones County, GA Monroe County, GA Twiggs County, GA 31460 Madera, CA 0.8154 Madera County, CA 31540 Madison, WI 1.0840 Columbia County, WI Dane County, WI Iowa County, WI 31700 Manchester-Nashua, NH 1.0243 Hillsborough County, NH Merrimack County, NH 31900 Mansfield, OH 0.9271 Richland County, OH 32420 Mayagüez, PR 0.3848 Hormigueros Municipio, PR Mayagüez Municipio, PR 32580 McAllen-Edinburg-Pharr, TX 0.8773 Hidalgo County, TX 32780 Medford, OR 1.0818 Jackson County, OR 32820 Memphis, TN-MS-AR 0.9373 Crittenden County, AR DeSoto County, MS Marshall County, MS Tate County, MS Tunica County, MS Fayette County, TN Shelby County, TN Tipton County, TN 32900 Merced, CA 1.1471 Merced County, CA 33124 Miami-Miami Beach-Kendall, FL 0.9812 Miami-Dade County, FL 33140 Michigan City-La Porte, IN 0.9118 LaPorte County, IN 33260 Midland, TX 0.9786 Midland County, TX 33340 Milwaukee-Waukesha-West Allis, WI 1.0218 Milwaukee County, WI Ozaukee County, WI Washington County, WI Waukesha County, WI 33460 Minneapolis-St. Paul-Bloomington, MN-WI 1.0946 Anoka County, MN Carver County, MN Chisago County, MN Dakota County, MN Hennepin County, MN Isanti County, MN Ramsey County, MN Scott County, MN Sherburne County, MN Washington County, MN Wright County, MN Pierce County, WI St. Croix County, WI 33540 Missoula, MT 0.8928 Missoula County, MT 33660 Mobile, AL 0.7913 Mobile County, AL 33700 Modesto, CA 1.1729 Stanislaus County, CA 33740 Monroe, LA 0.7997 Ouachita Parish, LA Union Parish, LA 33780 Monroe, MI 0.9707 Monroe County, MI 33860 Montgomery, AL 0.8009 Autauga County, AL Elmore County, AL Lowndes County, AL Montgomery County, AL 34060 Morgantown, WV 0.8423 Monongalia County, WV Preston County, WV 34100 Morristown, TN 0.7933 Grainger County, TN Hamblen County, TN Jefferson County, TN 34580 Mount Vernon-Anacortes, WA 1.0517 Skagit County, WA 34620 Muncie, IN 0.8562 Delaware County, IN 34740 Muskegon-Norton Shores, MI 0.9941 Muskegon County, MI 34820 Myrtle Beach-Conway-North Myrtle Beach, SC 0.8810 Horry County, SC 34900 Napa, CA 1.3374 Napa County, CA 34940 Naples-Marco Island, FL 0.9941 Collier County, FL 34980 Nashville-Davidson—Murfreesboro, TN 0.9847 Cannon County, TN Cheatham County, TN Davidson County, TN Dickson County, TN Hickman County, TN Macon County, TN Robertson County, TN Rutherford County, TN Smith County, TN Sumner County, TN Trousdale County, TN Williamson County, TN Wilson County, TN 35004 Nassau-Suffolk, NY 1.2662 Nassau County, NY Suffolk County, NY 35084 Newark-Union, NJ-PA 1.1892 Essex County, NJ Hunterdon County, NJ Morris County, NJ Sussex County, NJ Union County, NJ Pike County, PA 35300 New Haven-Milford, CT 1.1953 New Haven County, CT 35380 New Orleans-Metairie-Kenner, LA 0.8831 Jefferson Parish, LA Orleans Parish, LA Plaquemines Parish, LA St. Bernard Parish, LA St. Charles Parish, LA St. John the Baptist Parish, LA St. Tammany Parish, LA 35644 New York-Wayne-White Plains, NY-NJ 1.3177 Bergen County, NJ Hudson County, NJ Passaic County, NJ Bronx County, NY Kings County, NY New York County, NY Putnam County, NY Queens County, NY Richmond County, NY Rockland County, NY Westchester County, NY 35660 Niles-Benton Harbor, MI 0.8915 Berrien County, MI 35980 Norwich-New London, CT 1.1932 New London County, CT 36084 Oakland-Fremont-Hayward, CA 1.5819 Alameda County, CA Contra Costa County, CA 36100 Ocala, FL 0.8867 Marion County, FL 36140 Ocean City, NJ 1.0472 Cape May County, NJ 36220 Odessa, TX 1.0073 Ector County, TX 36260 Ogden-Clearfield, UT 0.8995 Davis County, UT Morgan County, UT Weber County, UT 36420 Oklahoma City, OK 0.8843 Canadian County, OK Cleveland County, OK Grady County, OK Lincoln County, OK Logan County, OK McClain County, OK Oklahoma County, OK 36500 Olympia, WA 1.1081 Thurston County, WA 36540 Omaha-Council Bluffs, NE-IA 0.9450 Harrison County, IA Mills County, IA Pottawattamie County, IA Cass County, NE Douglas County, NE Sarpy County, NE Saunders County, NE Washington County, NE 36740 Orlando, FL 0.9452 Lake County, FL Orange County, FL Osceola County, FL Seminole County, FL 36780 Oshkosh-Neenah, WI 0.9315 Winnebago County, WI 36980 Owensboro, KY 0.8748 Daviess County, KY Hancock County, KY McLean County, KY 37100 Oxnard-Thousand Oaks-Ventura, CA 1.1546 Ventura County, CA 37340 Palm Bay-Melbourne-Titusville, FL 0.9443 Brevard County, FL 37460 Panama City-Lynn Haven, FL 0.8027 Bay County, FL 37620 Parkersburg-Marietta, WV-OH 0.7977 Washington County, OH Pleasants County, WV Wirt County, WV Wood County, WV 37700 Pascagoula, MS 0.8215 George County, MS Jackson County, MS 37860 Pensacola-Ferry Pass-Brent, FL 0.8000 Escambia County, FL Santa Rosa County, FL 37900 Peoria, IL 0.8982 Marshall County, IL Peoria County, IL Stark County, IL Tazewell County, IL Woodford County, IL 37964 Philadelphia, PA 1.0996 Bucks County, PA Chester County, PA Delaware County, PA Montgomery County, PA Philadelphia County, PA 38060 Phoenix-Mesa-Scottsdale, AZ 1.0287 Maricopa County, AZ Pinal County, AZ 38220 Pine Bluff, AR 0.8383 Cleveland County, AR Jefferson County, AR Lincoln County, AR 38300 Pittsburgh, PA 0.8674 Allegheny County, PA Armstrong County, PA Beaver County, PA Butler County, PA Fayette County, PA Washington County, PA Westmoreland County, PA 38340 Pittsfield, MA 1.0266 Berkshire County, MA 38540 Pocatello, ID 0.9400 Bannock County, ID Power County, ID 38660 Ponce, PR 0.4842 Juana Díaz Municipio, PR Ponce Municipio, PR Villalba Municipio, PR 38860 Portland-South Portland-Biddeford, ME 0.9908 Cumberland County, ME Sagadahoc County, ME York County, ME 38900 Portland-Vancouver-Beaverton, OR-WA 1.1416 Clackamas County, OR Columbia County, OR Multnomah County, OR Washington County, OR Yamhill County, OR Clark County, WA Skamania County, WA 38940 Port St. Lucie-Fort Pierce, FL 0.9833 Martin County, FL St. Lucie County, FL 39100 Poughkeepsie-Newburgh-Middletown, NY 1.0911 Dutchess County, NY Orange County, NY 39140 Prescott, AZ 0.9836 Yavapai County, AZ 39300 Providence-New Bedford-Fall River, RI-MA 1.0783 Bristol County, MA Bristol County, RI Kent County, RI Newport County, RI Providence County, RI Washington County, RI 39340 Provo-Orem, UT 0.9537 Juab County, UT Utah County, UT 39380 Pueblo, CO 0.8753 Pueblo County, CO 39460 Punta Gorda, FL 0.9405 Charlotte County, FL 39540 Racine, WI 0.9356 Racine County, WI 39580 Raleigh-Cary, NC 0.9864 Franklin County, NC Johnston County, NC Wake County, NC 39660 Rapid City, SD 0.8833 Meade County, SD Pennington County, SD 39740 Reading, PA 0.9622 Berks County, PA 39820 Redding, CA 1.3198 Shasta County, CA 39900 Reno-Sparks, NV 1.1963 Storey County, NV Washoe County, NV 40060 Richmond, VA 0.9177 Amelia County, VA Caroline County, VA Charles City County, VA Chesterfield County, VA Cumberland County, VA Dinwiddie County, VA Goochland County, VA Hanover County, VA Henrico County, VA King and Queen County, VA King William County, VA Louisa County, VA New Kent County, VA Powhatan County, VA Prince George County, VA Sussex County, VA Colonial Heights City, VA Hopewell City, VA Petersburg City, VA Richmond City, VA 40140 Riverside-San Bernardino-Ontario, CA 1.0904 Riverside County, CA San Bernardino County, CA 40220 Roanoke, VA 0.8647 Botetourt County, VA Craig County, VA Franklin County, VA Roanoke County, VA Roanoke City, VA Salem City, VA 40340 Rochester, MN 1.1408 Dodge County, MN Olmsted County, MN Wabasha County, MN 40380 Rochester, NY 0.8994 Livingston County, NY Monroe County, NY Ontario County, NY Orleans County, NY Wayne County, NY 40420 Rockford, IL 0.9989 Boone County, IL Winnebago County, IL 40484 Rockingham County-Strafford County, NH 1.0159 Rockingham County, NH Strafford County, NH 40580 Rocky Mount, NC 0.8854 Edgecombe County, NC Nash County, NC 40660 Rome, GA 0.9193 Floyd County, GA 40900 Sacramento—Arden-Arcade—Roseville, CA 1.3372 El Dorado County, CA Placer County, CA Sacramento County, CA Yolo County, CA 40980 Saginaw-Saginaw Township North, MI 0.8874 Saginaw County, MI 41060 St. Cloud, MN 1.0362 Benton County, MN Stearns County, MN 41100 St. George, UT 0.9265 Washington County, UT 41140 St. Joseph, MO-KS 1.0118 Doniphan County, KS Andrew County, MO Buchanan County, MO DeKalb County, MO 41180 St. Louis, MO-IL 0.9005 Bond County, IL Calhoun County, IL Clinton County, IL Jersey County, IL Macoupin County, IL Madison County, IL Monroe County, IL St. Clair County, IL Crawford County, MO Franklin County, MO Jefferson County, MO Lincoln County, MO St. Charles County, MO St. Louis County, MO Warren County, MO Washington County, MO St. Louis City, MO 41420 Salem, OR 1.0438 Marion County, OR Polk County, OR 41500 Salinas, CA 1.4337 Monterey County, CA 41540 Salisbury, MD 0.8953 Somerset County, MD Wicomico County, MD 41620 Salt Lake City, UT 0.9402 Salt Lake County, UT Summit County, UT Tooele County, UT 41660 San Angelo, TX 0.8362 Irion County, TX Tom Green County, TX 41700 San Antonio, TX 0.8844 Atascosa County, TX Bandera County, TX Bexar County, TX Comal County, TX Guadalupe County, TX Kendall County, TX Medina County, TX Wilson County, TX 41740 San Diego-Carlsbad-San Marcos, CA 1.1354 San Diego County, CA 41780 Sandusky, OH 0.9302 Erie County, OH 41884 San Francisco-San Mateo-Redwood City, CA 1.5165 Marin County, CA San Francisco County, CA San Mateo County, CA 41900 San Germán-Cabo Rojo, PR 0.4885 Cabo Rojo Municipio, PR Lajas Municipio, PR Sabana Grande Municipio, PR San Germán Municipio, PR 41940 San Jose-Sunnyvale-Santa Clara, CA 1.5543 San Benito County, CA Santa Clara County, CA 41980 San Juan-Caguas-Guaynabo, PR 0.4452 Aguas Buenas Municipio, PR Aibonito Municipio, PR Arecibo Municipio, PR Barceloneta Municipio, PR Barranquitas Municipio, PR Bayamón Municipio, PR Caguas Municipio, PR Camuy Municipio, PR Canóvanas Municipio, PR Carolina Municipio, PR Cataño Municipio, PR Cayey Municipio, PR Ciales Municipio, PR Cidra Municipio, PR Comerío Municipio, PR Corozal Municipio, PR Dorado Municipio, PR Florida Municipio, PR Guaynabo Municipio, PR Gurabo Municipio, PR Hatillo Municipio, PR Humacao Municipio, PR Juncos Municipio, PR Las Piedras Municipio, PR Loíza Municipio, PR Manatí Municipio, PR Maunabo Municipio, PR Morovis Municipio, PR Naguabo Municipio, PR Naranjito Municipio, PR Orocovis Municipio, PR Quebradillas Municipio, PR Río Grande Municipio, PR San Juan Municipio, PR San Lorenzo Municipio, PR Toa Alta Municipio, PR Toa Baja Municipio, PR Trujillo Alto Municipio, PR Vega Alta Municipio, PR Vega Baja Municipio, PR Yabucoa Municipio, PR 42020 San Luis Obispo-Paso Robles, CA 1.1598 San Luis Obispo County, CA 42044 Santa Ana-Anaheim-Irvine, CA 1.1473 Orange County, CA 42060 Santa Barbara-Santa Maria-Goleta, CA 1.1091 Santa Barbara County, CA 42100 Santa Cruz-Watsonville, CA 1.5457 Santa Cruz County, CA 42140 Santa Fe, NM 1.0824 Santa Fe County, NM 42220 Santa Rosa-Petaluma, CA 1.4464 Sonoma County, CA 42260 Sarasota-Bradenton-Venice, FL 0.9868 Manatee County, FL Sarasota County, FL 42340 Savannah, GA 0.9351 Bryan County, GA Chatham County, GA Effingham County, GA 42540 Scranton—Wilkes-Barre, PA 0.8347 Lackawanna County, PA Luzerne County, PA Wyoming County, PA 42644 Seattle-Bellevue-Everett, WA 1.1434 King County, WA Snohomish County, WA 42680 Sebastian-Vero Beach, FL 0.9573 Indian River County, FL 43100 Sheboygan, WI 0.9026 Sheboygan County, WI 43300 Sherman-Denison, TX 0.8502 Grayson County, TX 43340 Shreveport-Bossier City, LA 0.8865 Bossier Parish, LA Caddo Parish, LA De Soto Parish, LA 43580 Sioux City, IA-NE-SD 0.9200 Woodbury County, IA Dakota County, NE Dixon County, NE Union County, SD 43620 Sioux Falls, SD 0.9559 Lincoln County, SD McCook County, SD Minnehaha County, SD Turner County, SD 43780 South Bend-Mishawaka, IN-MI 0.9842 St. Joseph County, IN Cass County, MI 43900 Spartanburg, SC 0.9174 Spartanburg County, SC 44060 Spokane, WA 1.0447 Spokane County, WA 44100 Springfield, IL 0.8890 Menard County, IL Sangamon County, IL 44140 Springfield, MA 1.0079 Franklin County, MA Hampden County, MA Hampshire County, MA 44180 Springfield, MO 0.8469 Christian County, MO Dallas County, MO Greene County, MO Polk County, MO Webster County, MO 44220 Springfield, OH 0.8593 Clark County, OH 44300 State College, PA 0.8784 Centre County, PA 44700 Stockton, CA 1.1442 San Joaquin County, CA 44940 Sumter, SC 0.8083 Sumter County, SC 45060 Syracuse, NY 0.9691 Madison County, NY Onondaga County, NY Oswego County, NY 45104 Tacoma, WA 1.0789 Pierce County, WA 45220 Tallahassee, FL 0.8942 Gadsden County, FL Jefferson County, FL Leon County, FL Wakulla County, FL 45300 Tampa-St. Petersburg-Clearwater, FL 0.9144 Hernando County, FL Hillsborough County, FL Pasco County, FL Pinellas County, FL 45460 Terre Haute, IN 0.8765 Clay County, IN Sullivan County, IN Vermillion County, IN Vigo County, IN 45500 Texarkana, TX-Texarkana, AR 0.8104 Miller County, AR Bowie County, TX 45780 Toledo, OH 0.9586 Fulton County, OH Lucas County, OH Ottawa County, OH Wood County, OH 45820 Topeka, KS 0.8730 Jackson County, KS Jefferson County, KS Osage County, KS Shawnee County, KS Wabaunsee County, KS 45940 Trenton-Ewing, NJ 1.0835 Mercer County, NJ 46060 Tucson, AZ 0.9202 Pima County, AZ 46140 Tulsa, OK 0.8103 Creek County, OK Okmulgee County, OK Osage County, OK Pawnee County, OK Rogers County, OK Tulsa County, OK Wagoner County, OK 46220 Tuscaloosa, AL 0.8542 Greene County, AL Hale County, AL Tuscaloosa County, AL 46340 Tyler, TX 0.8811 Smith County, TX 46540 Utica-Rome, NY 0.8396 Herkimer County, NY Oneida County, NY 46660 Valdosta, GA 0.8369 Brooks County, GA Echols County, GA Lanier County, GA Lowndes County, GA 46700 Vallejo-Fairfield, CA 1.5137 Solano County, CA 47020 Victoria, TX 0.8560 Calhoun County, TX Goliad County, TX Victoria County, TX 47220 Vineland-Millville-Bridgeton, NJ 0.9832 Cumberland County, NJ 47260 Virginia Beach-Norfolk-Newport News, VA-NC 0.8790 Currituck County, NC Gloucester County, VA Isle of Wight County, VA James City County, VA Mathews County, VA Surry County, VA York County, VA Chesapeake City, VA Hampton City, VA Newport News City, VA Norfolk City, VA Poquoson City, VA Portsmouth City, VA Suffolk City, VA Virginia Beach City, VA Williamsburg City, VA 47300 Visalia-Porterville, CA 0.9968 Tulare County, CA 47380 Waco, TX 0.8633 McLennan County, TX 47580 Warner Robins, GA 0.8380 Houston County, GA 47644 Warren-Troy-Farmington Hills, MI 1.0054 Lapeer County, MI Livingston County, MI Macomb County, MI Oakland County, MI St. Clair County, MI 47894 Washington-Arlington-Alexandria, DC-VA-MD-WV 1.1054 District of Columbia, DC Calvert County, MD Charles County, MD Prince George's County, MD Arlington County, VA Clarke County, VA Fairfax County, VA Fauquier County, VA Loudoun County, VA Prince William County, VA Spotsylvania County, VA Stafford County, VA Warren County, VA Alexandria City, VA Fairfax City, VA Falls Church City, VA Fredericksburg City, VA Manassas City, VA Manassas Park City, VA Jefferson County, WV 47940 Waterloo-Cedar Falls, IA 0.8408 Black Hawk County, IA Bremer County, IA Grundy County, IA 48140 Wausau, WI 0.9722 Marathon County, WI 48260 Weirton-Steubenville, WV-OH 0.8063 Jefferson County, OH Brooke County, WV Hancock County, WV 48300 Wenatchee, WA 1.0346 Chelan County, WA Douglas County, WA 48424 West Palm Beach-Boca Raton-Boynton Beach, FL 0.9649 Palm Beach County, FL 48540 Wheeling, WV-OH 0.7010 Belmont County, OH Marshall County, WV Ohio County, WV 48620 Wichita, KS 0.9063 Butler County, KS Harvey County, KS Sedgwick County, KS Sumner County, KS 48660 Wichita Falls, TX 0.8311 Archer County, TX Clay County, TX Wichita County, TX 48700 Williamsport, PA 0.8139 Lycoming County, PA 48864 Wilmington, DE-MD-NJ 1.0684 New Castle County, DE Cecil County, MD Salem County, NJ 48900 Wilmington, NC 0.9835 Brunswick County, NC New Hanover County, NC Pender County, NC 49020 Winchester, VA-WV 1.0091 Frederick County, VA Winchester City, VA Hampshire County, WV 49180 Winston-Salem, NC 0.9276 Davie County, NC Forsyth County, NC Stokes County, NC Yadkin County, NC 49340 Worcester, MA 1.0722 Worcester County, MA 49420 Yakima, WA 0.9847 Yakima County, WA 49500 Yauco, PR 0.3854 Guánica Municipio, PR Guayanilla Municipio, PR Peñuelas Municipio, PR Yauco Municipio, PR 49620 York-Hanover, PA 0.9397 York County, PA 49660 Youngstown-Warren-Boardman, OH-PA 0.8802 Mahoning County, OH Trumbull County, OH Mercer County, PA 49700 Yuba City, CA 1.0730 Sutter County, CA Yuba County, CA 49740 Yuma, AZ 0.9109 Yuma County, AZ 1 At this time, there are no hospitals located in this CBSA-based urban area on which to base a wage index. Therefore, the wage index value is based on the methodology described in the August 15, 2005 final rule (70 FR 47880). The wage index value for this area is the average wage index for all urban areas within the state. Table 2.—Proposed Inpatient Rehabilitation Facility Wage Index for Rural Areas for Discharges Occurring From October 1, 2007 Through September 30, 2008 CBSA code Nonurban area Wage index 01 Alabama 0.7591 02 Alaska 1.0661 03 Arizona 0.8908 04 Arkansas 0.7307 05 California 1.1454 06 Colorado 0.9325 07 Connecticut 1.1709 08 Delaware 0.9705 10 Florida 0.8594 11 Georgia 0.7593 12 Hawaii 1.0448 13 Idaho 0.8120 14 Illinois 0.8320 15 Indiana 0.8538 16 Iowa 0.8681 17 Kansas 0.7998 18 Kentucky 0.7768 19 Louisiana 0.7438 20 Maine 0.8443 21 Maryland 0.8926 22 Massachusetts 2 1.1661 23 Michigan 0.9062 24 Minnesota 0.9153 25 Mississippi 0.7738 26 Missouri 0.7927 27 Montana 0.8590 28 Nebraska 0.8677 29 Nevada 0.8944 30 New Hampshire 1.0853 31 New Jersey 1 32 New Mexico 0.8332 33 New York 0.8232 34 North Carolina 0.8588 35 North Dakota 0.7215 36 Ohio 0.8658 37 Oklahoma 0.7629 38 Oregon 0.9753 39 Pennsylvania 0.8320 40 Puerto Rico 3 0.4047 41 Rhode Island 1 42 South Carolina 0.8566 43 South Dakota 0.8480 44 Tennessee 0.7827 45 Texas 0.7965 46 Utah 0.8140 47 Vermont 0.9744 48 Virgin Islands 0.8467 49 Virginia 0.7940 50 Washington 1.0263 51 West Virginia 0.7607 52 Wisconsin 0.9553 53 Wyoming 0.9295 65 Guam 0.9611 1 All counties within the State are classified as urban. 2 Massachusetts has areas designated as rural; however, no short-term, acute care hospitals are located in the area(s) for FY 2008. As discussed in the preamble in Section IV.B, we are proposing to impute a wage index value for rural Massachusettes based on the average wage index from all contiguous CBSAs. 3 Puerto Rico has areas designated as rural; however, no short-term, acute care hospitals are located in the area(s) for FY 2008. As discussed in the preamble in Section IV.B, we are proposing to continue to use the most recent wage index previously available for Puerto Rico as discussed in the FY 2006 IRF PPS final rule (70 FR 47880). [FR Doc. 07-2241 Filed 5-2-07; 8:45 am]

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