### 9696 Federal Register / Vol. 76, No. 35 / Tuesday, February 22, 2011 / Proposed Rules

Pursuant to PRA, comments regarding the accuracy of the burden estimate, ways to minimize the burden, including the use of automated collection techniques or other forms of information technology, or any other aspect of this collection of information, should be sent to the above address. In addition, comments concerning the information collection should also be sent to the Desk Office for Agriculture, Office of Information and Regulatory Affairs, Office of Management and Budget, New Executive Office Building, 725 17th Street, NW., Room 725, Washington, DC

20503.

**FOR FURTHER INFORMATION CONTACT :**  Patricia A. Petrella, Marketing Specialist, Research and Promotion Branch, Fruit and Vegetable Programs, AMS, USDA, 1400 Independence Avenue, SW., Room 0632, Stop 0244, Washington, DC 20250–0244; telephone: (301) 334–2891; or facsimile: (301) 334– 2896; or e-mail: Patricia.Petrella@ams.usda.gov.

**SUPPLEMENTARY INFORMATION :**  A proposed rule was issued on November 2, 2010, and published in the Federal Register on November 8, 2010, (75 FR 68512). That rule proposed the establishment of an industry-funded promotion, research, and information program for fresh cut Christmas trees.

USDA was contacted by a congressman and received several letters from North Carolina growers requesting the comment period be reopened and extended to allow additional time to submit their comments. The growers also expressed that the comment period was open during their busiest time of the year.

USDA is reopening the comment period an additional 15 days to allow interested persons more time to review the proposed rule, perform a complete analysis, and submit written comments.

This notice is issued pursuant to the Commodity Promotion, Research, and Information Act of 1996 (1996 Act) (7 U.S.C. 7411–7425).

Dated: February 16, 2011. Rayne Pegg, Administrator, Agricultural Marketing
Service.
[FR Doc. 2011–3934 Filed 2–18–11; 8:45 am]

**BILLING CODE P DEPARTMENT OF ENERGY** 

**10 CFR Parts 430 and 431**

**[Docket No. EE–2008–BT–STD–0012]**

**Equipment Price Forecasting in Energy Conservation Standards Analysis** 

**AGENCY :**  Office of Energy Efficiency and Renewable Energy, Department of Energy.

**ACTION :**  Notice of data availability; request for comment.

**SUMMARY :**  The U.S. Department of Energy (DOE) seeks information related to potential technical improvements its energy conservation standards rulemaking analysis, and requests comment on corresponding revisions to the analysis for energy conservationstandards for refrigerators, refrigeratorfreezers and freezers.

**DATES :**  Written comments and information are requested on or before March 24, 2011.

**ADDRESSES :**  Interested persons are encouraged to submit comments using the Federal eRulemaking Portal at http://www.regulations.gov. Follow the instructions for submitting comments. Alternatively, interested persons may submit comments, identified by docket number EE–2008–BT–STD–0012, by any of the following methods:

• E-mail: to ResRefFreez–2008–STD– 0012@hq.doe.gov. Include EE–2008– BT–STD–0012 in the subject line of the
message.

• Mail: Ms. Brenda Edwards, U.S. Department of Energy, Building Technologies Program, Mailstop EE–2J, Equipment Price Forecasting in Energy Conservation Standards Analysis, EE– 2008–BT–STD–0012, 1000 Independence Avenue, SW., Washington, DC 20585–0121. Phone: (202) 586–2945. Please submit one signed paper original.

• Hand Delivery/Courier: Ms. Brenda Edwards, U.S. Department of Energy, Building Technologies Program, 6th Floor, 950 L’Enfant Plaza, SW., Washington, DC 20024. Phone: (202) 586–2945. Please submit one signed paper original.

Instructions: All submissions received must include the agency name and docket number for this rulemaking.

Docket: For access to the docket to read background documents, or comments received, go to the Federal eRulemaking Portal at http:// www.regulations.gov.

**FOR FURTHER INFORMATION CONTACT :**  Requests for additional information may be sent to Mr. John Cymbalsky, U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Building Technologies Program, EE–2J, 1000 Independence Avenue, SW., Washington, DC 20585–0121. Telephone: 202–586–4617. E-mail: Lucas.Adin@ee.doe.gov.

In the office of the General Counsel, contact Ms. Elizabeth Kohl, U.S. Department of Energy, Office of the General Counsel, GC–71,1000 Independence Ave., SW., Room 6A–179, Washington, DC 20585. Telephone: 202–586–7796; E-mail: Elizabeth.Kohl@hq.doe.gov.

**SUPPLEMENTARY INFORMATION :**  On January 18, 2011, the President issued Executive Order (the Order) 13563, meant to ensure that regulations seek more affordable, less intrusive means to achieve policy goals, and that agencies give careful consideration to the benefits and costs of those regulations. Among other things, the Order requires agencies propose or adopt a regulation only upon a reasoned determination that its benefits justify its costs, the regulation imposes the least burden on society consistent with obtaining the regulatory objectives, and that in choosing among alternative regulatory approaches, agencies choose those approaches that maximize net benefits.

The Order also contains provisions that bear on the analysis of benefits and costs. It provides that agencies must

‘‘use the best available techniques to quantify anticipated present and future benefits and costs as accurately as possible. ’’ In subsequent guidance on February 2, 2011, the Office of Information and Regulatory Affairs explained that such techniques include

‘‘ identifying changing future compliance costs that might result from technological innovation or anticipated behavioral changes. ’’

In light of the Order, DOE has examined its processes for establishing energy efficiency standards for consumer products and commercial equipment. In examining its analytical approaches for developing these regulations, DOE has developed a supplemental approach to help quantify the impacts flowing from the setting of efficiency levels for a given product or equipment. This approach is intended to improve accuracy in the assessment of future compliance costs. As part of this notice, DOE is soliciting comment on the potential inclusion of this approach for its future rulemaking activities. Additionally, DOE is seeking comment on the merits of adopting this approach within the context of its ongoing rulemaking to set standards for refrigerators, refrigerator-freezers, and


### 9697 Federal Register / Vol. 76, No. 35 / Tuesday, February 22, 2011 / Proposed Rules

1 See, for example, the review paper: Weiss, M., Junginger, H.M., Patel, M.K., Blok, K., (2010a). A Review of Experience Curve Analyses for Energy Demand Technologies. Technological Forecasting & Social Change. 77:411–428, which provides an extensive list of studies that have performed experience curve analyses. freezers (collectively, ‘‘refrigeration products ’’ ). Price Forecast Methodology

One of the key estimates that DOE currently makes during the analysis of energy conservation standards is the impact of efficiency regulations on equipment price. DOE uses its engineering analysis—which determines a given appliance’s cost as a function of its efficiency (through the development of cost-efficiency curves)—as the basis for estimating these equipment price impacts. The technology costs derived in the engineering analyses form the basis for product prices used in the national impact analysis that estimates regulatory impacts for products sold over the 30-year analysis period. Consequently, the price projections affect the economic impacts calculated for any potential energy conservation standard levels.

Currently, DOE’s analyses assume that the manufacturer costs and retail prices of products meeting various efficiency levels remain fixed, in real terms, after the compliance date and throughout the period of the analysis. This assumption is conservative. Examination of historical price data for certain appliances and equipment that have been subject to energy conservation standards indicates that the assumption of constant real prices and costs may, in many cases, over-estimate long-term appliance and equipment price trends. Economic literature and historical data suggest that the real costs of covered products and equipment may in fact trend downward over time according to

‘‘ learning ’’ or ‘‘ experience ’’ curves. A draft paper, ‘‘Using the Experience Curve Approach for Appliance Price Forecasting, ’’ posted on the DOE Web site along with this notice at http:// www.eere.energy.gov/buildings/ appliance

_standards, provides a summary of the data and literature currently available to DOE that is relevant to price forecasts for selected appliances and equipment.

In light of these data and DOE’s aim to improve the accuracy and robustness of its analyses, DOE is considering assessing future costs by incorporating learning over time, consistent with the analysis in the currently available literature, in its analysis of regulatory options in the energy conservation standards for refrigeration products, in an attempt to create a more accurate and robust forecast of the pricing effects that accompany amended energy efficiency standards for these products. The consequences of this approach are outlined below. DOE is also considering applying this approach generally to its energy conservation standards-related analyses for appliance and commercial equipment.

DOE seeks comment on the merits of this approach, particularly with respect to its application to an analysis of potential energy efficiency standards for refrigeration products and the data presented in this notice.

In addition, DOE requests information regarding the potential for improving the methodology for projecting the cost of efficiency improvements over the analysis period in general. DOE provides additional background in the following paragraphs and seeks input on three broad categories: (1) Data sources; (2) potential methodologies; and (3) procedural issues. Background

Forecast Method. An extensive economic literature discusses the

‘‘ learning ’’ or ‘‘ experience ’’ curve phenomenon, typically based on observations in the manufacturing
sector. 1 In the experience curve method, the real cost of production is related to the cumulative production or

‘‘ experience ’’ with a product. To explain the empirical relationship, the theory of technology learning is used to substantiate a decline in the cost of producing a given product as firms accumulate experience with the technology. A common functional relationship used to model the evolution of production costs in this case is:
Y = aX

¥ b

, where a is an initial price (or cost), b is a positive constant known as the learning rate parameter, X is cumulative production, and Y is the price as a function of cumulative production. Thus, as experience (production) accumulates, the cost of producing the next unit decreases. The percentage reduction in cost that occurs with each doubling of cumulative production is known as the learning rate (LR), given by:

LR = 1

¥ 2

¥ b

DOE’s current price forecast methodology is a special case of the forecast equations specified above, but to date, DOE has assumed that the learning rate parameter is 0 in its energy conservation standards analysis. This notice describes an approach for improving this assumption and estimating non-zero learning rate parameters consistent with historical cost data.

Data. In typical learning curve formulations, the learning rate parameter is derived using two historical data series: Cumulative production and price (or cost). On the basis of previous rulemakings, DOE is aware of several relevant data sets. Annual shipments (for calculating cumulative production) of several appliances can be found in industry publications ( e.g., Appliance Magazine) and industry association ( e.g., the AirConditioning, Heating, and Refrigeration Institute (AHRI), the Association of Home Appliance Manufacturers (AHAM) Fact Book, etc. ) data sets. Historical shipment-weighted efficiency data could be gathered from these sources, as well as from the Energy Information Administration (EIA). Historical price or cost data for several products could be derived from the Bureau of Labor Statistics’ (BLS) Producer Price Index (PPI) and/or Consumer Price Index (CPI).

Table 1 provides these data for refrigerators, refrigerator-freezers, and freezers (including compacts). The inflation-adjusted price index is derived from CPI data for 1947 to 1997 and PPIdata from 1998 to 2009. The inflationadjusted price is derived from a current price estimate for refrigerator-freezers that is then scaled over time by the inflation-adjusted price index. DOE estimates that cumulative refrigerator, refrigerator-freezer, and freezer shipments are 22.22 million in 1946 and then they increase each year with the current year shipments.


### 9698 Federal Register / Vol. 76, No. 35 / Tuesday, February 22, 2011 / Proposed Rules

TABLE 

### 1—H ISTORICAL 

### D ATA 

### R EGARDING 

### R EFRIGERATOR 

### , R EFRIGERATOR 

### -F REEZER


### , AND 

### F REEZER 

### P RICES AND 

### S HIPMENTS

Year Inflation-adjusted price index Inflation-adjusted price (2009$) Shipments (millions) Cumulative Shipments (millions)

1947 ................................................. 3.95 $4,132 4.01 26.23 1948 ................................................. 4.03 4,218 5.46 31.68 1949 ................................................. 3.96 4,144 4.94 36.62 1950 ................................................. 3.83 4,001 7.09 43.71 1951 ................................................. 3.73 3,906 5.09 48.79 1952 ................................................. 3.52 3,686 4.60 53.39 1953 ................................................. 3.37 3,522 4.69 58.08 1954 ................................................. 3.12 3,258 4.65 62.73 1955 ................................................. 2.94 3,071 5.27 68.00 1956 ................................................. 2.50 2,611 4.78 72.78 1957 ................................................. 2.22 2,326 4.45 77.23 1958 ................................................. 2.09 2,186 4.23 81.45 1959 ................................................. 2.07 2,164 4.91 86.36 1960 ................................................. 1.99 2,081 4.61 90.98 1961 ................................................. 1.94 2,032 4.63 95.61 1962 ................................................. 1.88 1,967 4.94 100.56 1963 ................................................. 1.81 1,890 5.31 105.87 1964 ................................................. 1.75 1,829 5.75 111.61 1965 ................................................. 1.67 1,747 6.15 117.76 1966 ................................................. 1.56 1,633 6.21 123.97 1967 ................................................. 1.51 1,581 5.96 129.93 1968 ................................................. 1.47 1,536 6.42 136.35 1969 ................................................. 1.42 1,482 6.58 142.94 1970 ................................................. 1.38 1,439 6.59 149.53 1971 ................................................. 1.35 1,410 7.02 156.54 1972 ................................................. 1.31 1,366 7.66 164.21 1973 ................................................. 1.23 1,289 8.14 172.35 1974 ................................................. 1.17 1,226 7.38 179.73 1975 ................................................. 1.21 1,262 6.00 185.72 1976 ................................................. 1.20 1,250 6.27 192.00 1977 ................................................. 1.16 1,217 7.20 199.19 1978 ................................................. 1.15 1,200 7.43 206.62 1979 ................................................. 1.09 1,137 7.31 213.93 1980 ................................................. 1.02 1,062 6.80 220.73 1981 ................................................. 0.99 1,031 6.73 227.46 1982 ................................................. 1.01 1,055 6.29 233.75 1983 ................................................. 1.01 1,055 7.47 241.22 1984 ................................................. 0.98 1,028 7.99 249.20 1985 ................................................. 0.94 984 8.24 257.44 1986 ................................................. 0.92 957 8.68 266.12 1987 ................................................. 0.88 923 9.08 275.20 1988 ................................................. 0.86 895 9.34 284.53 1989 ................................................. 0.83 872 8.88 293.41 1990 ................................................. 0.79 823 8.97 302.37 1991 ................................................. 0.75 782 8.99 311.37 1992 ................................................. 0.72 758 9.52 320.88 1993 ................................................. 0.72 753 9.84 330.72 1994 ................................................. 0.73 766 10.39 341.11 1995 ................................................. 0.71 747 10.56 351.68 1996 ................................................. 0.70 736 10.93 362.60 1997 ................................................. 0.68 712 10.90 373.51 1998 ................................................. 0.63 659 11.98 385.49 1999 ................................................. 0.60 630 13.02 398.51 2000 ................................................. 0.57 596 13.18 411.69 2001 ................................................. 0.54 561 13.37 425.05 2002 ................................................. 0.52 539 14.84 439.89 2003 ................................................. 0.49 514 15.90 455.79 2004 ................................................. 0.48 499 16.69 472.48 2005 ................................................. 0.47 494 16.73 489.21 2006 ................................................. 0.46 482 15.39 504.60 2007 ................................................. 0.45 475 15.09 519.69 2008 ................................................. 0.45 475 14.37 534.06 2009 ................................................. 0.47 496 14.27 548.34

Application to Standards. Given the information currently available to DOE, DOE believes (and invites comments on the view that) the following methodology may provide the most accurate method for forecasting the incremental cost of efficiency given the potential impact of long-term product price trends or technological learning:


### 9699 Federal Register / Vol. 76, No. 35 / Tuesday, February 22, 2011 / Proposed Rules

2 A good review of the literature related to this issue can be found in Gillingham, K., R. Newell, K. Palmer. (2009). ‘‘Energy Efficiency Economics and Policy, ’’ Annual Review of Resource Economics , 1: 597–619; and Tietenberg, T. (2009). ‘‘Energy Efficiency Policy: Pipe Dream or Pipeline to the Future? ’’ Review of Environmental Economics and Policy. Vol. 3, No. 2: 304–320.

3 A draft paper, ‘‘Notes on the Economics of Household Energy Consumption and Technology Choice, ’’ proposes a broad theoretical framework on which an empirical model might be based and is posted on the DOE Web site along with this notice

at http://www.eere.energy.gov/buildings/ appliance

_standards. • When sufficiently long-term data are available on the cost trends for equipment or technologies for particular efficiency design options, an empirical experience curve fit to the available data may be used to forecast future costs of such design option technologies. If a statistical evaluation indicates a low level of confidence in estimates of the design option cost trend, this method should not be used to forecast costs.

• When sufficiently long term data are not available for forecasting the cost of products or equipment using specific efficiency-improving components, the experience curve cost trend for the product or equipment as a whole should be applied to both the product or equipment price and the incremental product or equipment price.

• When sufficiently long term data are not available for a specific product or equipment, it may be appropriate to apply the experience curve cost trend for a similar product or equipment, or a product or equipment grouping that includes the product or equipment at issue, to both the product or equipment price and the incremental product or equipment price. Alternatively, DOE may use experience curve parameters from review studies that may indicate that certain parameter ranges apply to certain classes or groups of products or equipment that include the product or equipment under analysis. If data are not available for estimating a price trend, DOE may use a constant real price trend as in past rulemakings.

In other words, when data are available to help guide DOE in projecting potential cost reductions over time for a particular appliance or equipment, DOE plans to use these data as part of its analyses. In those instances where such data are unavailable, DOE will continue to employ the methods it currently uses, which is to hold costs at a fixed level for purposes of long-term impact projections.

For the energy conservation standardsanalysis for refrigerators, refrigeratorfreezers and freezers, long-term data are available on overall product costs. DOE is therefore considering use of the long term trend in product price to forecast the long term trend in the incremental cost of efficiency. DOE posts updated national impact analysis spreadsheets that incorporate price trend forecasting
at http://www.eere.energy.gov/ buildings/appliance

_standards for public review.

To improve the accuracy and reliability of price forecasts, DOE may periodically review the performance of equipment and incremental efficiency cost forecasts and may make further methodological improvements that improve forecast accuracy and reliability.

In the next section, DOE seeks information on all of the issues covered in this section, as well as additional topics.

General Discussion of Potential Consumer Welfare Impacts

DOE also notes that the economics literature provides a wide-ranging discussion of how consumers trade-off upfront costs and energy savings in the absence of government intervention. Much of this literature attempts to explain why consumers appear to undervalue energy efficiency improvements. This undervaluation suggests that regulation that promotes energy efficiency can produce significant net private gains (as well as producing social gains by, for example, reducing pollution). There is evidence that consumers undervalue future energy savings as a result of (1) a lack of information, (2) a lack of sufficient savings to warrant delaying or altering purchases ( e.g. an inefficient ventilation fan in a new building or the delayed replacement of a water pump), (3) inconsistent ( e.g. excessive short-term) weighting of future energy cost savings relative to available returns on other investments, (4) computational or other difficulties associated with the evaluation of relevant tradeoffs, and (5) a divergence in incentives ( e.g. renter versus owner; builder v. purchaser). In the abstract, it may be difficult to say how a welfare gain from correcting under-investment compares in magnitude to the potential welfare losses associated with no longer purchasing a machine or switching to an imperfect substitute, both of which still exist in this framework.

Other literature indicates that with less than perfect foresight and uncertainty about the future, consumers may trade off these types of investments at a higher than expected rate between current consumption and uncertain future energy cost savings. Some studies suggest that this seeming undervaluation may be explained in certain circumstances by differences between tested and actual energy savings, or by uncertainty and irreversibility of energy investments.

The mix of evidence in the empirical literature suggests that if feasible, analysis of regulations mandating energy efficiency improvements should explore the potential for both welfare gains and losses and move toward fuller economic framework where all relevant changes can be quantified. 2 While DOE is not prepared at present to provide a fuller quantifiable framework for this discussion, DOE seeks comments on how to assess these issues. 3

Issues on Which DOE Seeks Comment and Information

Data Sources

1. DOE seeks data related to observed trends in historical costs, retail prices, and shipment efficiencies of products and equipment covered by the Energy Conservation Standards program.

2. DOE seeks data related to observed trends in historical costs, retail prices, and shipment efficiencies of products and equipment that, while not covered by the Energy Conservation Standards program, may be of use to DOE with respect to its treatment of technology learning curves and consumer welfare impacts.

3. DOE seeks data related to historical costs and prices of covered products and equipment delineated by efficiency level.

4. DOE seeks information on the appropriate range of values for learning parameters found in the relevant literature, either in the aggregate or associated with specific appliances, equipment, technologies, or production
processes. Potential Methodologies

1. DOE specifically seeks comment on the methodology described in the

‘‘ Background’’ section above.

2. DOE seeks information on alternative methodologies for forecasting equipment price trends in its analyses.

3. DOE seeks comment on how changes in other product attributes, including efficiency, could be

‘‘normalized’’ or ‘‘ corrected’’ based on historical data.

4. DOE seeks comment on methods for calculating changes in historical costs or prices, including the use of the PPI and CPI.

5. DOE seeks comment on methods of deriving historical production volumes.

6. DOE seeks comment on the details of the method, data and references


### 9700 Federal Register / Vol. 76, No. 35 / Tuesday, February 22, 2011 / Proposed Rules

described in the draft paper ‘‘Using the Experience Curve Approach for Appliance Price Forecasting ’’ posted on the DOE Web site at http:// www.eere.energy.gov/buildings/ appliance

_standards.

7. DOE seeks comment on data sources and analytical methods for estimating potential consumer welfare impacts from energy conservation standards, including information on specific consumer subgroups of products regulated under the energy conservation program.

Procedural Issues

1. DOE seeks comment on the details of how equipment price forecasts and consumer welfare impacts may be incorporated into specific downstream analyses that rely on the engineering analysis outputs and what other methodological changes to those analyses might be merited.

2. DOE seeks comment on products or equipment, or groups of products or equipment, that are likely to have the greatest and least improvement in price forecast accuracy from the application of experience curve methodology.

3. DOE seeks information on alternative methods for modeling persistent price trends for regulated products or equipment. General Analysis Methodology

1. DOE seeks comments and information regarding additional ways of improving the accounting of costs and benefits in its energy conservation standards analysis, including comment on benefits and costs that may not have been included in energy conservation standards analyses to date.

2. DOE seeks information on how standards can affect the dynamics of innovation and investment in U.S. appliance and equipment industries.

3. DOE seeks comment on ways in which standards-induced innovation and investment might impact the competitiveness of U.S. products and companies in the global marketplace.

4. DOE seeks comment on the additional global benefits that may arise from standards that may encourage U.S. appliances and equipment to have efficiency performance levels exceeding the efficiency performance levels of appliances and equipment in other countries.

The purpose of this NODA is to solicit feedback from industry, manufacturers, academia, consumer groups, efficiency advocates, government agencies, and other stakeholders on issues related price forecasts in DOE’s engineering analyses for Energy Conservation Standards rulemakings. DOE is specifically interested in information and sources of data related to covered products and equipment that could be used in formulating a methodology regarding long term equipment price forecasts, and a methodology regarding consumer welfare impacts. Respondents are advised that DOE is under no obligation to acknowledge receipt of the information received or provide feedback to respondents with respect to any information submitted under this NODA. Responses to this NODA do not bind DOE to any further actions related to this topic.

Issued in Washington, DC, on February 15,
2011. Cathy Zoi, Assistant Secretary, Energy Efficiency and Renewable Energy.
[FR Doc. 2011–3873 Filed 2–18–11; 8:45 am]

**BILLING CODE 6450–01–P**

**DEPARTMENT OF THE INTERIOR**

**Office of Surface Mining Reclamation and Enforcement** 

**30 CFR Part 901**

**[SATS No. AL–076–FOR; Docket ID: OSM– 2010–0020]** 

**Alabama Regulatory Program**

**AGENCY :**  Office of Surface Mining Reclamation and Enforcement, Interior.

**ACTION :**  Proposed rule; public comment period and opportunity for public hearing on proposed amendment.

**SUMMARY :**  We, the Office of Surface Mining Reclamation and Enforcement (OSM), are announcing receipt of a proposed amendment to the Alabama regulatory program (Alabama program) under the Surface Mining Control and Reclamation Act of 1977 (SMCRA or the Act). Alabama proposes revisions to its Program regarding their license fees, annual license updates, and blaster certification fees. Alabama intends to revise its program to improve operational efficiency. The fees will be used to recover Alabama’s anticipated costs of reviewing, administering, and enforcing Alabama’s licensing and blaster certification requirements.

This document gives the times and locations that the Alabama program and proposed amendment to that program are available for your inspection, the comment period during which you may submit written comments on the amendment, and the procedures that we will follow for the public hearing, if one is requested.

**DATES :**  We will accept written comments on this amendment until 4 p.m., c.s.t., March 24, 2011. If requested, we will hold a public hearing on the amendment on March 21, 2011. We will accept requests to speak at a hearing until 4 p.m., c.s.t. on March 9,
2011.

**ADDRESSES :**  You may submit comments, identified by SATS No. AL–076–FOR by any of the following methods:

• E-mail: swilson@osmre.gov. Include

‘‘ SATS No. AL–076–FOR’’ in the subject line of the message.

• Mail/Hand Delivery: Sherry Wilson, Director, Birmingham Field Office, Office of Surface Mining Reclamation and Enforcement, 135 Gemini Circle, Suite 215, Homewood, Alabama 35209.

• Fax: (205) 290–7280.

• Federal eRulemaking Portal: http:// www.regulations.gov. Follow the instructions for submitting comments.

Instructions: All submissions received must include the agency name and docket number for this rulemaking. For detailed instructions on submitting comments and additional information on the rulemaking process, see the

‘‘Public Comment Procedures ’’ heading of the **SUPPLEMENTARY INFORMATION** section of this document.

Docket: For access to the docket to review copies of the Alabama program, this amendment, a listing of any scheduled public hearings, and all written comments received in response to this document, you must go to the address listed below during normal business hours, Monday through Friday, excluding holidays. You may receive one free copy of the amendment by contacting OSM’s Birmingham Field Office or going to http:// www.regulations.gov.

Sherry Wilson, Director, Birmingham Field Office, Office of Surface Mining Reclamation and Enforcement, 135 Gemini Circle, Suite 215, Homewood, Alabama 35209, Telephone: (205) 290– 7282, E-mail: swilson@osmre.gov.

In addition, you may review a copy of the amendment during regular business hours at the following location:

Alabama Surface Mining Commission, 1811 Second Ave., P.O. Box 2390, Jasper, Alabama 35502–2390, Telephone: (205) 221–4130.

**FOR FURTHER INFORMATION CONTACT :**  Sherry Wilson, Director, Birmingham Field Office. Telephone: (205) 290–
7282. E-mail: swilson@osmre.gov.

**SUPPLEMENTARY INFORMATION :**  I. Background on the Alabama Program II. Description of the Proposed Amendment III. Public Comment Procedures IV. Procedural Determinations I. Background on the Alabama Program

Section 503(a) of the Act permits a State to assume primacy for the