1-i 

CHAPTER 1. INTRODUCTION

TABLE OF CONTENTS

1.1 PURPOSE OF THE DOCUMENT ................................................................................. 1-1

1.2 SUMMARY OF NATIONAL BENEFITS ..................................................................... 1-1

1.3 OVERVIEW OF APPLIANCE STANDARDS .............................................................. 1-4

1.4 OVERVIEW OF COMMERCIAL REFRIGERATION EQUIPMENT STANDARDS 1-5

1.4.1 Definitions............................................................................................................ 1-6

1.4.2 Rulemaking History ............................................................................................. 1-7

1.4.2.1 Standards Prescribed by Statute ............................................................... 1-7

1.4.2.2 Standards Established by Rulemaking ..................................................... 1-7

1.4.3 Current Energy Conservation Standards ............................................................ 1-10

1.4.4 Framework and Analysis Methodology ............................................................. 1-11

1.5 STRUCTURE OF THE DOCUMENT .......................................................................... 1-13

REFERENCES .......................................................................................................................... 1-16

LIST OF TABLES

Table 1.2.1 Annualized Benefits and Costs of Proposed Standards for Commercial 

Refrigeration Equipment ...................................................................................... 1-3

Table 1.4.1 CRE Standards Prescribed by EPCA, Effective January 1, 2010 ........................... 1-10

Table 1.4.2 CRE Standards Established in the 2009 Final Rule, Effective January 1, 2012 ..... 1-10

Table 1.4.3 CRE Analyses ......................................................................................................... 1-12
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CHAPTER 1. INTRODUCTION

1.1 PURPOSE OF THE DOCUMENT

This technical support document (TSD) is a stand-alone report that provides the technical 

analyses and results in support of the information presented in the notice of proposed rulemaking 

(NOPR) for commercial refrigeration equipment (CRE). This NOPR TSD also complements the 

life-cycle cost (LCC) and payback period (PBP), and national impact analysis (NIA)

spreadsheets that are posted on the U.S. Department of Energy’s (DOE’s) website 

at: www1.eere.energy.gov/buildings/appliance_standards/rulemaking.aspx/ruleid/27. 

1.2 SUMMARY OF NATIONAL BENEFITS

DOE’s analyses indicate that the proposed standards would save a significant amount of 

energy. The lifetime savings for commercial refrigeration equipment purchased in the 30-year 

period that begins in the year of the compliance with amended standards (2017–2046) amount to 

1.001 quadrillion British thermal units (quads). This is equivalent to 83 percent of total U.S. 

commercial sector energy (source energy) used for refrigeration in 2010.a

The cumulative national net present value (NPV) of total customer costs and savings of 

the proposed standards for commercial refrigeration equipment in 2012$ ranges from $1.606 

billion (at a 7 percent discount rate) to $4.067 billion (at a 3 percent discount rate). This NPV 

expresses the estimated total value of future operating cost savings minus the estimated increased 

installed costs for equipment purchased in 2017–2046, discounted to 2013. The industry net 

present value (INPV) is the sum of the discounted cash flows to the industry from the base year 

(2013) through the end of the analysis period (2046). Using a real discount rate of 10 percent,b

DOE estimates that the INPV for manufacturers of commercial refrigeration equipment is 

$1,162.0 million in 2012$. Under the proposed standards, DOE expects that manufacturers may 

lose up to 7.97 percent of their INPV, or approximately $92.6 million. 

The proposed standards are expected to have significant environmental benefits. The 

energy savings would result in cumulative greenhouse gas (GHG) emission reductions of 

54.88 million metric tons (MMt)c

 of carbon dioxide (CO2), 265.9 thousand tons of methane, 1.1 

thousand tons of nitrous oxide, 70.1 thousand tons of sulfur dioxide (SO2), 81.1 thousand tons of 

NOx, and 0.1 tons of mercury (Hg).d DOE estimates that the net present monetary value of the 

CO2 emissions reduction would be between $0.31 and $4.55 billion. DOE also estimates the 

 

a Total U.S. commercial sector energy (source energy) used for refrigeration in 2010 was 1.21 quads. Source: U.S. 

Department of Energy–Office of Energy Efficiency and Renewable Energy. Buildings Energy Data Book, 

Table 3.1.4, 2010 Commercial Energy End-Use Splits, by Fuel Type (Quadrillion Btu). 2012. (Last accessed April 

23, 2013.) 

http://buildingsdatabook.eren.doe.gov/TableView.aspx?table=3.1.4

b This is the rate used to discount future cash flows in the Manufacturer Impact Analysis. A discount rate of 10 

percent was calculated based on SEC filings and feedback from manufacturer interviews about the current cost of 

capital in the industry. For more information, refer to Chapter 12 of the NOPR TSD. c A metric ton is equivalent to 1.1 U.S. short tons. Results for NOx and Hg are presented in short tons.

d DOE calculated emissions reductions relative to the Annual Energy Outlook 2013 (AEO2013) Reference case, 

which generally represents current legislation and environmental regulations for which implementing regulations 

were available as of December 31, 2012. 
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present monetary value of the NOx emissions reduction would be between $8.8 and $90.7 

million at a 7 percent discount rate and between $19.1 and $196.2 million at a 3 percent discount 

rate.e

The benefits and costs of today’s proposed standards, for commercial refrigeration 

equipment sold in 2017–2046, can also be expressed in terms of annualized values. The 

annualized monetary values are the sum of 1) the annualized national economic value of the 

benefits from the customer operation of equipment that meets the proposed standards (consisting 

primarily of operating cost savings from using less energy, minus increases in equipment 

installed cost, which is another way of representing customer NPV) and 2) the annualized 

monetary value of the benefits of emission reductions, including CO2 emission reductions.f

The value of the CO2 reductions is calculated using a range of values per metric ton of CO2

(otherwise known as the Social Cost of Carbon [SCC]) developed by a recent Federal 

interagency process. The monetary costs and benefits of cumulative emissions reductions are 

reported in 2012$ to permit straightforward comparisons with the other costs and benefits. The 

derivation of the values of the SCC is discussed in appendices 14A and 14B. 

Although combining the values of operating savings and CO2 emission reductions 

provides a useful perspective, two issues should be considered. First, the national operating 

savings are domestic U.S. customer monetary savings that occur as a result of market 

transactions, while the value of CO2 reductions is based on a global value. Second, the 

assessments of operating cost savings and CO2 savings are performed with different methods 

that use different time frames for analysis. The national operating cost savings is measured over 

the lifetimes of commercial refrigeration equipment shipped in 2017–2046. The SCC values, on 

the other hand, reflect the present value of some future climate-related impacts resulting from the 

emission of 1 ton of CO2 in each year. These impacts continue well beyond 2100. 

Table 1.2.1 shows the annualized benefits and costs of the proposed standards. The 

results of the primary estimate are as follows. Table 1.2.1 shows the primary, low net benefits, 

and high net benefits scenarios. The primary estimate is the estimate in which the operating cost 

savings were calculated using the Annual Energy Outlook 2013 (AEO2013)

1 Reference Case 

forecast of future electricity prices. The other two estimates, low net benefits estimate and high 

net benefits estimate, are based on the low and high electricity price scenarios from the AEO2013

forecast. At a 7-percent discount rate for benefits and costs, the cost in the primary estimate of 

the standards proposed in today’s notice is $82 million per year in increased equipment costs. 

The annualized benefits are $203 million per year in reduced equipment operating costs, $75 

million in CO2 reductions (note that DOE used a 3-percent discount rate, along with the 

corresponding SCC series that uses a 3-percent discount rate, to calculate the monetized value of 

 

e DOE is currently investigating valuation of avoided Hg and SO2 emissions. 

f DOE used a two-step calculation process to convert the time-series of costs and benefits into annualized values. 

First, DOE calculated a present value in 2013, the year used for discounting the NPV of total consumer costs and 

savings, for the time-series of costs and benefits using discount rates of 3 and 7 percent for all costs and benefits 

except for the value of CO2 reductions. For the latter, DOE used a range of discount rates, as shown in Table 1.2.1. 

From the present value, DOE then calculated the fixed annual payment over a 30-year period (2017 through 2046) 

that yields the same present value. The fixed annual payment is the annualized value. Although DOE calculated 

annualized values, this does not imply that the time-series of cost and benefits from which the annualized values 

were determined is a steady stream of payments.
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CO2 emissions reductions), and $3.75 million in reduced NOx emissions. In this case, the 

annualized net benefit amounts to $199 million. At a 3-percent discount rate for all benefits and 

costs, the cost in the primary estimate of the amended standards proposed in today’s notice is 

$97 million per year in increased equipment costs. The benefits are $299 million per year in 

reduced operating costs, $75 million in CO2 reductions, and $5.33 million in reduced NOx

emissions. In this case, the net benefit amounts to $281 million per year. 

Table 1.2.1 Annualized Benefits and Costs of Proposed Standards for Commercial 

Refrigeration Equipment 

Discount 

Rate

Primary 

Estimate*

million 2012$

Low Net Benefits 

Estimate*

million 2012$

High Net Benefits 

Estimate*

million 2012$

Benefits

Operating Cost Savings 7% 203 197 212

3% 299 288 314

CO2 Reduction Monetized 

Value (at $12.9/Metric Ton)** 5% 19 19 19

CO2 Reduction Monetized 

Value (at $40.8/Metric Ton)** 3% 75 75 75

CO2 Reduction Monetized 

Value (at $62.2/Metric Ton)** 2.5% 114 114 114

CO2 Reduction Monetized 

Value (at $117.0/Metric Ton)** 3% 225 225 225

NOx Reduction Monetized 

Value (at $2,639/Ton)**

7% 3.75 3.75 3.75

3% 5.33 5.33 5.33

Total Benefits (Operating Cost 

Savings, CO2 Reduction and 

NOx Reduction)†

7% 281 275 290

3% 379 368 394

Costs

Total Incremental Installed 

Costs

7% 82 84 80

3% 97 100 95

Net Benefits Less Costs

Total Benefits Less Incremental 

Costs 

7% 199 191 210

3% 281 268 299

* This table presents the annualized costs and benefits associated with equipment shipped in 2017−2046. These results 

include benefits to consumers which accrue after 2046 from the products purchased in 2017−2046. The primary, low, 

and high estimates utilize forecasts of energy prices from the AEO2013 Reference Case, Low Economic Growth Case, 

and High Economic Growth Case, respectively. In addition, incremental equipment costs reflect a medium decline rate 

for projected product price trends in the Primary Estimate, a low decline rate for projected equipment price trends in 

the Low Benefits Estimate, and a high decline rate for projected equipment price trends in the High Benefits Estimate. 

The methods used to derive projected price trends are explained in Appendix 10B.

** The interagency group selected four sets of SCC values for use in regulatory analyses. Three sets of values are 

based on the average SCC from the three integrated assessment models at discount rates of 2.5, 3, and 5 percent. The 

fourth set, which represents the 95th percentile SCC estimate across all three models at a 3-percent discount rate, is 

included to represent higher-than-expected impacts from temperature change further out in the tails of the SCC 

distribution. The values in parentheses represent the SCC in 2015. The SCC time series incorporate an escalation 

factor. The value for NOX is the average of the low and high values used in DOE’s analysis.

† Total Benefits for both the 3- and 7-percent cases are derived using the series corresponding to average SCC with 3-

percent discount rate. In the rows labeled “7% plus CO2 range” and “3% plus CO2 range,” the operating cost and NOX

benefits are calculated using the labeled discount rate, and those values are added to the full range of CO2 values.

DOE also calculated the low net benefits and high net benefits estimates by calculating 

the operating cost savings and incremental installed costs at the AEO2013 low economic growth 

case and high economic growth case scenarios, respectively. These scenarios do not change the 
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monetized emissions reductions values. The net benefits and costs for low and high net benefits 

estimates were calculated in the same manner as the primary estimate by using the corresponding 

values of operating cost savings and incremental installed costs. 

1.3 OVERVIEW OF APPLIANCE STANDARDS

Part B of Title III of the Energy Policy and Conservation Act of 1975 (EPCA or the Act), 

Pub. L. 94-163, as amended by the National Energy Conservation Policy Act of 1978 (NECPA), 

Pub. L. 95-619; the National Appliance Energy Conservation Act of 1987 (NAECA), Pub. L. 

100-12; the National Appliance Energy Conservation Amendments of 1988 (NAECA 1988), 

Pub. L. 100-357; and the Energy Policy Act of 1992 (EPACT 1992), Pub. L. 102-486, 

established the Energy Conservation Program for Consumer Products other than Automobiles. 

(42 U.S.C. 6291–6309) Part 3 of Title IV of NECPA amended EPCA to add Part A-1 of Title III, 

which established an energy conservation program for certain industrial equipment.g

 (42 U.S.C. 

6311–6317) EPACT 1992 included amendments to EPCA that expanded Title III to include 

additional commercial equipment. The Energy Policy and Conservation Act of 2005 

(EPACT 2005), Pub. L. 109-58, updated several existing standards and test procedures; 

prescribed definitions, standards, and test procedures for certain new consumer products and 

commercial equipment; and mandated that the Secretary of Energy (the Secretary) commence 

rulemakings to develop test procedures and standards for certain new consumer products and 

commercial equipment.

DOE is required to design each standard for this equipment to 1) achieve the maximum 

improvement in energy efficiency that is technologically feasible and economically justified and 

2) result in significant conservation of energy. (42 U.S.C. 6295(o)(2)(A) and (o)(3)(B), 

42 U.S.C. 6316(e)(1)(A)) To determine whether a proposed standard is economically justified, 

DOE will, after receiving comments on the proposed standard, determine whether the benefits of 

the standard exceed its burdens to the greatest extent practicable, considering the following seven 

factors:

1. the economic impact of the standard on the manufacturers and on the consumers of the 

products subject to such standard;

2. the savings in operating costs throughout the estimated average life of the covered 

product in the type (or class) compared to any increase in the price of, or in the initial 

charges for maintenance expenses of, the covered products that are likely to result from 

the imposition of the standard; 

3. the total projected amount of energy savings likely to result directly from the imposition 

of the standard; 

4. any lessening of the utility or the performance of the covered products likely to result 

from the imposition of the standard; 

 

g This part was originally titled Part C. However, it was redesignated Part A-1 after Part B of Title III of EPCA was 

repealed by Pub. L. 109-58.
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5. the impact of any lessening of competition, as determined in writing by the Attorney 

General, that is likely to result from the imposition of the standard; 

6. the need for national energy conservation; and 

7. other factors the Secretary considers relevant.

(See 42 U.S.C. 6295(o)(2)(B)(i); 6316(e)(1)(A)) 

For commercial refrigeration equipment, DOE is applying those factors in a manner 

consistent with its other energy conservation standards rulemakings to ascertain the maximum 

improvement in energy efficiency that is technologically feasible and economically justified for 

this equipment.

1.4 OVERVIEW OF COMMERCIAL REFRIGERATION EQUIPMENT 

STANDARDS

EPACT 2005 included amendments to EPCA that update several existing standards and 

test procedures; prescribe definitions, standards, and test procedures for certain new consumer 

products and commercial equipment; and mandate that DOE commence rulemakings to develop 

test procedures and standards for certain new consumer products and commercial equipment. 

With respect to the standards for commercial refrigeration equipment, EPCA, as amended by 

EPACT 2005, also stated that:

(A) Not later than January 1, 2013, the Secretary shall issue a final rule to 

determine whether the standards established under this subsection should be 

amended. 

(B) Not later than 3 years after the effective date of any amended standards under 

subparagraph (A) or the publication of a final rule determining that the standards 

should not be amended, the Secretary shall issue a final rule to determine whether 

the standards established under this subsection or the amended standards, as 

applicable, should be amended. 

(C) If the Secretary issues a final rule under subparagraph (A) or (B) establishing 

amended standards, the final rule shall provide that the amended standards apply 

to products manufactured on or after the date that is – 

(i) 3 years after the date on which the final amended standard is published; or 

(ii) if the Secretary determines, by rule, that 3 years is inadequate, not later than 5 

years after the date on which the final rule is published. 

42 U.S.C. 6313(c)(6) 
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1.4.1 Definitions

Section 136(a)(3) of EPACT 2005 amended section 340 of EPCA by striking paragraph 9 

and inserting definitions for the following terms that describe commercial refrigeration 

equipment: 

(9)(A) The term “commercial refrigerator, freezer, and refrigerator-freezer” 

means refrigeration equipment that— 

(i) is not a consumer product (as defined in section 321 of EPCA);

(ii) is not designed and marketed exclusively for medical, scientific, or research 

purposes; 

(iii) operates at a chilled, frozen, combination chilled and frozen, or variable 

temperature;

(iv) displays or stores merchandise and other perishable materials horizontally, 

semi-vertically, or vertically;

(v) has transparent or solid doors, sliding or hinged doors, a combination of 

hinged, sliding, transparent, or solid doors, or no doors; 

(vi) is designed for pull-down temperature applications or holding temperature 

applications; and 

(vii) is connected to a self-contained condensing unit or to a remote condensing 

unit. 

(B) The term “holding temperature application” means a use of commercial 

refrigeration equipment other than a pull-down temperature application, except a 

blast chiller or freezer.

* * * 

(D) The term “pull-down temperature application” means a commercial 

refrigerator with doors that, when fully loaded with 12 ounce beverage cans at 

90 degrees F, can cool those beverages to an average stable temperature of 

38 degrees F in 12 hours or less. 

(E) The term “remote condensing unit” means a factory-made assembly of 

refrigerating components designed to compress and liquefy a specific refrigerant 

that is remotely located from the refrigerated equipment and consists of one or 

more refrigerant compressors, refrigerant condensers, condenser fans and motors, 

and factory supplied accessories.

(F) The term “self-contained condensing unit” means a factory-made assembly of 

refrigerating components designed to compress and liquefy a specific refrigerant 
1-7 

that is an integral part of the refrigerated equipment and consists of one or more 

refrigerant compressors, refrigerant condensers, condenser fans and motors, and 

factory supplied accessories.

42 U.S.C. 6311(9) 

1.4.2 Rulemaking History

The current standards for commercial refrigeration equipment are a result of two 

legislative actions and one rulemaking: standards prescribed by EPACT 2005 for certain 

equipment, standards for other equipment established by DOE through issuance of a final rule, 

and standard prescribed by American Energy Manufacturing Technical Corrections Act 

(AEMTCA), Pub. L. 112-210 (2012). 

1.4.2.1 Standards Prescribed by Statute

Section 136(c) of EPACT 2005 amended EPCA to prescribe energy conservation 

standards for self-contained equipment consisting of commercial refrigerators with solid doors, 

commercial refrigerators with transparent doors, commercial freezers with solid doors, 

commercial freezers with transparent doors, commercial refrigerator/freezers with solid doors 

designed for holding temperature applications, and commercial refrigerators with transparent 

doors designed for pull-down temperature applications. (42 U.S.C. 6313(c)(1–3)) These 

standards became effective on January 1, 2010. See Table 1.4.1 in section 1.4.3. 

Section 4 of AEMTCA established a new standard for self-contained service over counter 

commercial refrigerators for medium temperature applications (SOC.SC.M) by amending section 

342(c) of EPCA. (42 U.S.C. 6313(c)(4)) SOC.SC.M equipment had previously been 

inadvertently classified by EPACT 2005 under the category self-contained commercial 

refrigerators with transparent doors. (42 U.S.C. 6313(c)(2)) Section 4 of AEMTCA was aimed at 

addressing this discrepancy. 

1.4.2.2 Standards Established by Rulemaking 

Section 136(c) of EPACT 2005 also amended EPCA to mandate that DOE set standards 

for the following additional categories of equipment: ice-cream freezers; self-contained 

commercial refrigerators, freezers, and refrigerator-freezers without doors; and remote 

condensing commercial refrigerators, freezers, and refrigerator-freezers. (42 U.S.C. 

6313(c)(5)(A)) DOE undertook a rulemaking process beginning in April 2006, when it published 

the Rulemaking Framework for Commercial Refrigeration Equipment Including Ice-Cream 

Freezers; Self-Contained Commercial Refrigerators, Freezers, and Refrigerator-Freezers 

without doors; and Remote Condensing Commercial Refrigerators, Freezers, and RefrigeratorFreezers (April 2006 framework document). The April 2006 framework document described the 

procedural and analytical approaches DOE anticipated using to evaluate the establishment of 

energy conservation standards for these types of commercial refrigeration equipment. This 

document is available 

at www1.eere.energy.gov/buildings/appliance_standards/commercial/pdfs/comml_refrig_framew

ork.pdf
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DOE held a public meeting on May 16, 2006 to discuss procedural and analytical 

approaches to the rulemaking and to inform and facilitate the involvement of interested parties in 

the rulemaking process. The analytical framework presented at the public meeting described 

different analyses, such as the engineering analysis and the LCC and PBP analyses, the methods 

proposed for conducting them, and the relationships among the various analyses. 

After the public meeting associated with the April 2006 framework document, as part of 

the information gathering and sharing process for the preliminary manufacturer impact analysis 

(MIA), DOE conducted interviews with CRE manufacturers. DOE selected companies that 

represented production of all types of equipment covered by the rulemaking, ranging from small 

to large manufacturers, and included Air-Conditioning and Refrigeration Institute (ARI)h

member companies and non-ARI member companies. DOE had four objectives for these 

interviews: 1) solicit feedback on the draft engineering analysis (including methodology, 

production costs, manufacturing processes, and findings); 2) solicit feedback on topics related to 

the preliminary MIA; 3) provide an opportunity, early in the rulemaking process, for these 

manufacturers to express specific concerns to DOE; and 4) foster cooperation between the 

manufacturers and DOE. 

DOE developed a preliminary engineering analysis to estimate the cost of manufacturing 

equipment at efficiencies above the baseline levels. DOE also developed spreadsheets to conduct 

the LCC, PBP, and NIA. The LCC spreadsheet calculates national distributions of LCC savings 

at various energy efficiency levels above the baseline. It can also provide LCC savings based on 

typical input values for several business types that use commercial refrigeration equipment. The 

NIA spreadsheet calculates the national energy savings (NES) and national NPVs at various 

energy efficiency levels. It also includes a model that forecasts shipments for the various 

equipment classes of commercial refrigeration equipment at different efficiency levels.

In July 2007, DOE published an advance notice of proposed rulemaking (July 2007 

ANOPR) for commercial refrigeration equipment including ice-cream freezers; self-contained 

commercial refrigerators, freezers, and refrigerator-freezers without doors; and remote 

condensing commercial refrigerators, freezers, and refrigerator-freezers. 72 FR 41162 (July 26, 

2007). In the July 2007 ANOPR analysis, DOE considered establishing energy conservation 

standards for these types of commercial refrigeration equipment and announced a public meeting 

to receive comments on a variety of issues. This document is available at 

www1.eere.energy.gov/buildings/appliance_standards/commercial/pdfs/comml_refrig_anopr_07

2607.pdf. 

DOE held a public meeting on August 23, 2007 (August 2007 ANOPR public meeting) 

to provide interested parties the opportunity to comment on the equipment classes proposed by 

DOE in the July 2007 ANOPR; the analytical framework, models, and tools (e.g., LCC and NES 

spreadsheets) that DOE had developed to perform analyses of the impacts of potential energy 

conservation standards; the results of the preliminary analyses; and the candidate energy 

conservation standard levels. 

 

h On January 1, 2008, the Air-Conditioning and Refrigeration Institute (ARI) and the Gas Appliance Manufacturers 

Association (GAMA) merged to become the Air-Conditioning, Heating, and Refrigeration Institute (AHRI), to 

represent the interests of cooling, heating, and commercial refrigeration equipment manufacturers.
1-9 

After the publication of the July 2007 ANOPR and the presentation of the ANOPR to 

interested parties at the August 2007 ANOPR public meeting, DOE conducted additional 

interviews with CRE manufacturers as part of its development of the MIA for the NOPR. There 

were 13 general topics discussed during each of the interviews: 1) general key issues; 2) 

company overview and organizational characteristics; 3) company financial parameters; 4) 

production cost breakdown; 5) shipment projections and market shares; 6) equipment mixes; 

7) conversion costs; 8) markups and profitability; 9) cumulative regulatory burden; 10) exports, 

foreign competition, and outsourcing; 11) direct employment impact assessment; 12) market 

consolidation; and 13) baseline products and different design options. 

Based on findings from the preliminary engineering, LCC and NIA, and public comments 

provided in response to the July 2007 ANOPR, DOE updated these analyses. In updating these 

analyses, DOE reviewed the recommendations made on April 21, 1998 by the Advisory 

Committee on Appliance Energy Efficiency Standards. (Advisory Committee, No. 96)i

DOE’s 

analysis implemented recommendations related to 1) defining a range of energy price futures for 

each fuel used in the economic analyses; and 2) defining a range of primary energy conversion 

factors and associated emission reductions based on the generation of energy and emissions that 

would be displaced by energy efficiency standards for each rulemaking. In addition, DOE 

performed additional analyses assessing impacts on national employment, consumer subgroups, 

utilities, and the environment. DOE also developed analysis of alternatives to efficiency standard 

regulations. 

On August 25, 2008, DOE published a NOPR (August 2008 NOPR) for commercial 

refrigeration equipment including ice-cream freezers; self-contained commercial refrigerators, 

freezers, and refrigerator-freezers without doors; and remote condensing commercial 

refrigerators, freezers, and refrigerator-freezers, to propose energy conservation standards for 

these types of commercial refrigeration equipment, and to announce a public meeting to receive 

comments on a variety of issues. 73 FR at 50072. This document is available 

at www1.eere.energy.gov/buildings/appliance_standards/commercial/pdfs/cre_nopr_fr_final.pdf. 

DOE held a public meeting on September 23, 2008 (September 2008 public meeting) to 

provide interested parties the opportunity to comment on the proposed standards, results of the 

analyses, and the trial standard levels (TSLs). 

After the publication of the August 2008 NOPR and the September 2008 NOPR public 

meeting, DOE received more than 100 comments from a diverse set of interested parties, 

including manufacturers and their representatives, trade associations, wholesalers and distributors, 

energy conservation advocates, and electric utilities. Comments addressed DOE methodology, the 

information DOE used in its analyses, results of and inferences drawn from the analyses, impacts 

of standards, the merits of the different TSLs, standards options DOE considered, and other issues 

affecting adoption of standards for commercial refrigeration equipment.

 

i

Advisory Committee, No. 96 refers to the recommendations of the Advisory Committee on Appliance Energy 

Efficiency Standards and is available for inspection at the U.S. Department of Energy, 950 L’Enfant Plaza SW., 

Suite 600, Washington, DC, 20024 (Resource Room) in the file under “Energy Conservation Program for Consumer 

Products: Procedures for Consideration of New or Revised Energy Conservation Standards for Consumer Products,” 

RIN [1904–AA83], as document number 96.
1-10

DOE considered these comments in developing a final rule for commercial refrigeration 

equipment, published on January 9, 2009 (herein referred to as the “January 2009 final rule”). 

74 FR at 1092. The January 2009 final rule established standards for ice-cream freezers; selfcontained commercial refrigerators, freezers, and refrigerator-freezers without doors; and remote 

condensing commercial refrigerators, freezers, and refrigerator-freezers, which became effective 

on January 1, 2012. 

1.4.3 Current Energy Conservation Standards

Table 1.4.1 and Table 1.4.2 show the current standards for the two subsets of commercial 

refrigeration equipment. 

Table 1.4.1 CRE Standards Prescribed by EPCA, Effective January 1, 2010 

Category Maximum Daily Energy Consumption

kWh/day*

Refrigerators with solid doors 0.10 V + 2.04

Refrigerators with transparent doors 0.12 V + 3.34

Freezers with solid doors 0.40 V + 1.38

Freezers with transparent doors 0.75 V + 4.10

Refrigerators/freezers with solid doors the greater of 0.27 AV - 0.71 or 0.70

Self-contained refrigerators with transparent doors 

designed for pull-down temperature applications 0.126 V + 3.51

* kilowatt-hours per day

Table 1.4.2 CRE Standards Established in the 2009 Final Rule, Effective January 1, 2012 

Equipment Class* Standard Level **,†

kWh/day Equipment Class Standard Level **,†kWh/day

VOP.RC.M 0.82 × TDA + 4.07 VCT.RC.I 0.66 × TDA + 3.05

SVO.RC.M 0.83 × TDA + 3.18 HCT.RC.M 0.16 × TDA + 0.13

HZO.RC.M 0.35 × TDA + 2.88 HCT.RC.L 0.34 × TDA + 0.26

VOP.RC.L 2.27 × TDA + 6.85 HCT.RC.I 0.4 × TDA + 0.31

HZO.RC.L 0.57 × TDA + 6.88 VCS.RC.M 0.11 × V + 0.26

VCT.RC.M 0.22 × TDA + 1.95 VCS.RC.L 0.23 × V + 0.54

VCT.RC.L 0.56 × TDA + 2.61 VCS.RC.I 0.27 × V + 0.63

SOC.RC.M 0.51 × TDA + 0.11 HCS.RC.M 0.11 × V + 0.26

VOP.SC.M 1.74 × TDA + 4.71 HCS.RC.L 0.23 × V + 0.54

SVO.SC.M 1.73 × TDA + 4.59 HCS.RC.I 0.27 × V + 0.63

HZO.SC.M 0.77 × TDA + 5.55 SOC.RC.L 1.08 × TDA + 0.22

HZO.SC.L 1.92 × TDA + 7.08 SOC.RC.I 1.26 × TDA + 0.26

VCT.SC.I 0.67 × TDA + 3.29 VOP.SC.L 4.37 × TDA + 11.82

VCS.SC.I 0.38 × V + 0.88 VOP.SC.I 5.55 × TDA + 15.02

HCT.SC.I 0.56 × TDA + 0.43 SVO.SC.L 4.34 × TDA + 11.51

SVO.RC.L 2.27 × TDA + 6.85 SVO.SC.I 5.52 × TDA + 14.63

VOP.RC.I 2.89 × TDA + 8.7 HZO.SC.I 2.44 × TDA + 9.

SVO.RC.I 2.89 × TDA + 8.7 SOC.SC.I 1.76 × TDA + 0.36

HZO.RC.I 0.72 × TDA + 8.74 HCS.SC.I 0.38 × V + 0.88 *

For this rulemaking, equipment class designations consist of a combination (in sequential order separated by periods) of (1) an 

equipment family code (VOP=vertical open, SVO=semivertical open, HZO=horizontal open, VCT=vertical transparent doors, 

VCS=vertical solid doors, HCT=horizontal transparent doors, HCS=horizontal solid doors, or SOC=service over counter); (2) an 

operating mode code (RC=remote condensing or SC=self-contained); and (3) a rating temperature code (M=medium temperature 

(38 °F)), L=low temperature (0 °F), or I=ice-cream temperature (-15 °F)). For example, “VOP.RC.M” refers to the “vertical 

open, remote condensing, medium temperature” equipment class.

** TDA is the total display area of the case, as measured in ARI Standard 1200-2006, appendix D. † V is the volume of the case, as measured in ARI Standard 1200-2006, appendix C.
1-11

In addition to the standards in Table 1.4.1 and Table 1.4.2, the standard for equipment 

class SOC.SC.M, established by AEMTCA, is given by the expression 0.6 × TDA + 1.0, and has 

an effective date of January 1, 2012 (42 U.S.C. 6313(c)(4)). 

1.4.4 Framework and Analysis Methodology 

DOE initiated this rulemaking to fulfill its statutory requirements set forth in 42 U.S.C. 

6313(c) with respect to establishing amended energy conservation standards for commercial 

refrigeration equipment. As the first step in April 2010, DOE published a Rulemaking 

Framework for Commercial Refrigeration Equipment (April 2010 framework document) 

describing the procedural and analytical approaches DOE anticipated using to evaluate the 

establishment of energy conservation standards for commercial refrigeration equipment. This 

document is available 

at www1.eere.energy.gov/buildings/appliance_standards/commercial/pdfs/cre_framework_04-

30-10.pdf

DOE held a public meeting on May 18, 2010 (May 2010 framework public meeting) to 

discuss procedural and analytical approaches to the rulemaking and to inform interested parties 

and facilitate their involvement in the rulemaking process. The analytical framework presented at 

the public meeting described different analyses, such as the engineering analysis and the LCC 

and PBP analyses, the methods proposed for conducting them, and the relationships among the 

various analyses.

After the analytical framework public meeting, as part of the information gathering and 

sharing process for the preliminary MIA, DOE organized and held interviews with CRE

manufacturers. DOE selected companies that represented production of all types of commercial 

refrigeration equipment, ranging from small to large manufacturers. DOE had four objectives for 

these interviews: 1) solicit feedback on the draft engineering analysis (including methodology, 

production costs, manufacturing processes, and findings); 2) solicit feedback on topics related to 

the preliminary MIA; 3) provide an opportunity, early in the rulemaking process, for 

manufacturers to express specific concerns to DOE; and 4) foster cooperation between the 

manufacturers and DOE.

In March 2011, DOE published a notice of public meeting and availability of the 

preliminary TSD (March 2011 preliminary analysis) for the ongoing rulemaking to potentially 

amend energy conservation standards for commercial refrigeration equipment. This document is 

available 

at www1.eere.energy.gov/buildings/appliance_standards/commercial/pdfs/fr_nopm_publication_

2011_03_30.pdf

DOE held a public meeting on April 19, 2011 (April 2011 preliminary analysis public 

meeting) to give stakeholders the opportunity to comment on the proposed equipment classes 

DOE is considering; the analytical framework, models, and tools (e.g., LCC and NES 

spreadsheets) that DOE has been using to perform analyses of the impacts of energy 

conservation standards; the results of the preliminary analyses; and the candidate energy 

conservation standard levels. See Table 1.4.3 for all the analyses discussed at the public meeting 

to be undertaken in each of the formal public rulemaking documents. 
1-12

Table 1.4.3 CRE Analyses 

Preliminary Analysis NOPR Final Rule*

Market and technology assessment Revised preliminary analyses Revised NOPR analyses

Screening analysis Customer subgroup analysis

Engineering analysis Manufacturer impact analysis

Energy use characterization Utility impact analysis

Markups to determine equipment price Employment impact analysis

LCC and PBP analyses Emissions analysis

Shipments analysis Emissions monetization

NIA Regulatory impact analysis

Preliminary MIA

* During the final rule phase, DOE considers the comments submitted by the U.S. Department of Justice in the NOPR phase 

concerning the impact of any lessening of competition that is likely to result from the imposition of the standard. (42 U.S.C. 

6295(o)(2)(B)(v))

After the posting of the March 2011 preliminary analysis TSD and the April 2011 

preliminary analysis public meeting, DOE conducted interviews with CRE manufacturers as part 

of the MIA for the NOPR. A number of general topics were discussed during each interview: 

1) general key issues; 2) company overview and organizational characteristics; 3) company 

financial parameters; 4) production cost breakdown; 5) shipment projections and market shares; 

6) equipment mixes; 7) conversion costs; 8) markups and profitability; 9) cumulative regulatory 

burden; 10) exports, foreign competition, and outsourcing; 11) direct employment impact 

assessment; 12) market consolidation; and 13) baseline products and different design options. 

DOE developed spreadsheets for the LCC and PBP analyses and for the NIA in an effort 

to meet the objectives of the Process Rule. The LCC spreadsheet calculates national distributions 

of LCC savings at all efficiency levels above the baseline. DOE also developed an NIA

spreadsheet that calculates the NES and national NPVs at all efficiency levels. This spreadsheet 

includes a model that forecasts shipments for the various equipment classes of commercial 

refrigeration equipment at different efficiency levels.

DOE reviewed the recommendations made on April 21, 1998, by the Advisory 

Committee on Appliance Energy Efficiency Standards. (Advisory Committee, No. 96) These 

recommendations related to: 1) using the full range of consumer marginal energy rates (CMERs) 

in the LCC analysis (replacing the use of national average energy prices); 2) defining a range of 

energy price futures for each fuel used in the economic analyses; and 3) defining a range of 

primary energy conversion factors and associated emission reductions based on the generation of 

energy and emissions that would be displaced by energy efficiency standards for each 

rulemaking. DOE’s analysis implemented 2) and 3) above; however, as discussed previously, 

DOE conducted the LCC analysis using regional average electricity prices for affected business 

types and did not develop CMERs in the LCC analysis. 
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1.5 STRUCTURE OF THE DOCUMENT

Listed below are the 17 TSD chapters and related appendices that collectively form the 

TSD. 

Chapter 1 Introduction: provides an overview of the appliance standards program and how 

it applies to the CRE rulemaking, provides a history of DOE’s actions to date, 

and outlines the structure of this document. 

Chapter 2 Analytical Framework: describes the rulemaking process.

Chapter 3 Market and Technology Assessment: provides DOE’s definition of commercial 

refrigeration equipment, discusses the proposed equipment classes, and names 

the major industry players. This chapter also provides an overview of 

commercial refrigeration technology, including techniques employed to 

improve equipment efficiency.

Chapter 4 Screening Analysis: identifies all the design options that improve CRE

efficiency, and determines which of these will be evaluated and which will be 

screened out.

Chapter 5 Engineering Analysis: presents detailed cost and efficiency information for the 

units of analysis. This chapter describes DOE’s approach for determining 

manufacturer costs, including the markups used for converting material costs to 

manufacturer sales prices.

Chapter 6 Markups Analysis: presents the methodology used to determine the distribution 

channel markups that are used to convert manufacturer selling prices into 

customer purchase price of the equipment. 

Chapter 7 Energy Use Analysis: DOE used the energy consumption model in the 

engineering analysis to estimate CRE energy use. DOE did not conduct a 

separate energy use analysis for this rulemaking. 

Chapter 8 Life-Cycle Cost and Payback Period Analysis: presents the methodology used 

to estimate the impact of potential new or amended standards on customers of 

commercial refrigeration equipment by calculating LCC and PBP values at all 

higher efficiency levels. 

Chapter 9 Shipments Analysis: presents the methodology used to estimate the historic and 

future shipments of commercial refrigeration equipment. The estimated 

shipments numbers are used as inputs to NIA and other downstream analyses.

Chapter 10 National Impact Analysis: presents the methodology used to estimate national 

impacts by calculating NES and NPV at all higher efficiency levels. 
1-14

Chapter 11 Customer Subgroup Analysis: evaluates impacts on identifiable customer 

subgroups that may be disproportionately disadvantaged by the proposed new or 

amended standards. 

Chapter 12 Manufacturer Impact Analysis: assesses the impacts on CRE manufacturers of 

any new or amended standards. In addition to financial impacts, a wide range of 

quantitative and qualitative effects may occur following adoption of a standard 

that may require changes to the manufacturing practices for this equipment. 

Chapter 13 Emissions Analysis: presents the assessment of the impacts of proposed CRE

standard levels on emissions of certain pollutants. 

Chapter 14 Monetization of Emissions Reductions Benefits: presents the methodology to 

estimate monetary benefits likely to result from the reduced emissions of certain 

pollutants. 

Chapter 15 Utility Impact Analysis: analyzes the effects of proposed new or amended CRE

standard levels on the electric utility industry.

Chapter 16 Employment Impact Analysis: estimates national job creation or elimination 

(indirect effects) resulting from possible amended standards due to reallocation 

of the associated commercial expenditures for purchasing and operating 

equipment. 

Chapter 17 Regulatory Impact Analysis: evaluates potential major alternatives to standards 

to achieve customer product energy efficiency. 

Appendix 5A Engineering Data: contains full engineering specifications for all equipment 

classes directly analyzed. 

Appendix 6A Data for Equipment Price Markups: presents detailed data used for markups 

analysis. 

Appendix 8A User Instructions For Life-Cycle Cost Spreadsheet: Presents user instructions 

for LCC spreadsheet.

Appendix 8B Detailed Life-Cycle Cost and Payback Period Analysis Results: Presents 

detailed results from the LCC analysis.

Appendix 8C Uncertainty and Variability in Life-Cycle Cost Analysis: Presents brief 

discussion on the uncertainty and variability analysis used in the LCC analysis. 

Appendix 8D: Estimation of Potential Equipment Price Trend for Commercial Refrigeration 

Equipment: Presents experiential learning analysis in the LCC analysis. 

Appendix 10A User Instructions for NIA Spreadsheet: Presents user instruction for the NIA 

spreadsheet.
1-15

Appendix 10B National Net Present Value Using Alternative Price Forecasts: Presents 

experiential learning sensitivity analysis results.

Appendix 10C Trial Standard Levels and Standards Equations: Presents the criteria for TSL 

selection and the proposed standards equation at each TSL.

Appendix 10D Full-Fuel-Cycle Multipliers: Presents the development of full-fuel-cycle 

coefficients

Appendix 10E RISC & OIRA Consolidated Information System (ROCIS) Tables: Presents the 

ROCISj

tables.

Appendix 12A Government Regulatory Impact Model (GRIM) Overview: Presents overview of 

the model used in the MIA. 

Appendix 14A Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 

12866: Presents the SCC analysis. 

Appendix 14B Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 

12866: technical model update: Presents updated SCC analysis. 

 

j

Regulatory Information Service Center (RISC) and Office of Information and Regulatory Affairs (OIRA) 

Combined Information System. 
1-16

REFERENCES

1. U.S. Department of Energy–Energy Information Administration. Annual Energy Outlook 

2013. 2013. Washington D.C. DOE/EIA-0383(2013). 
2-i 

CHAPTER 2. ANALYTICAL FRAMEWORK

TABLE OF CONTENTS

2.1 INTRODUCTION ........................................................................................................... 2-1

2.2 BACKGROUND ............................................................................................................. 2-4

2.3 MARKET AND TECHNOLOGY ASSESSMENT ........................................................ 2-4

2.3.1 Market Assessment .............................................................................................. 2-4

2.3.2 Technology Assessment ....................................................................................... 2-5

2.4 SCREENING ANALYSIS .............................................................................................. 2-5

2.5 ENGINEERING ANALYSIS .......................................................................................... 2-5

2.5.1 Baseline Models ................................................................................................... 2-6

2.5.2 Manufacturing Cost Analysis .............................................................................. 2-7

2.6 MARKUPS FOR EQUIPMENT PRICE DETERMINATION ....................................... 2-7

2.7 ENERGY USE ANALYSIS ............................................................................................ 2-7

2.8 LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS ..................................... 2-7

2.9 SHIPMENTS ANALYSIS............................................................................................. 2-10

2.10 NATIONAL IMPACT ANALYSIS .............................................................................. 2-10

2.11 CUSTOMER SUBGROUP ANALYSIS ....................................................................... 2-11

2.12 MANUFACTURER IMPACT ANALYSIS.................................................................. 2-12

2.13 EMISSIONS ANALYSIS .............................................................................................. 2-12

2.14 MONETIZATION OF EMISSIONS REDUCTIONS BENEFITS ............................... 2-14

2.15 UTILITY IMPACT ANALYSIS ................................................................................... 2-15

2.16 EMPLOYMENT IMPACT ANALYSIS ....................................................................... 2-15

2.17 REGULATORY IMPACT ANALYSIS ........................................................................ 2-16

2.18 DEPARTMENT OF JUSTICE REVIEW ..................................................................... 2-16

REFERENCES .......................................................................................................................... 2-17

LIST OF FIGURES

Figure 2.1.1 Analyses for Commercial Refrigeration Equipment Energy Conservation Standards

.............................................................................................................................. 2-3
2-1 

CHAPTER 2. ANALYTICAL FRAMEWORK

2.1 INTRODUCTION

This chapter provides a description of the general analytical framework used by the U.S. 

Department of Energy (DOE) in developing standards and assessing the impacts for commercial 

refrigeration equipment. The description addresses the methodology, the analytical tools, and the 

relationship between the various analyses conducted in the rulemaking. The objective of the 

rulemaking process is to determine minimum efficiency standards for commercial refrigeration 

equipment that are technologically feasible and economically justified. In this context, economic 

justification includes consideration of the economic impact on manufacturers and consumers, the 

national benefits, the impacts on utilities, and the impacts from any lessening of competition. 

Figure 2.1.1 summarizes the analytical components of the standards-setting process. The 

focus of this figure is the third column, identified as “Analysis.” The columns labeled “Key 

Inputs” and “Key Outputs” indicate how the analyses fit into the rulemaking process, and how 

the analyses relate to each other. Key outputs are analytical results that feed directly into the 

standards-setting process. Dotted lines connecting analyses indicate types of information that 

feed from one analysis to another. Key inputs are the types of data and information that the 

analyses require. Some key inputs exist in public databases and DOE will also collect inputs 

from stakeholders or others with special knowledge. Inputs developed by the project team for the 

standards-setting process are presented and open for stakeholder review.

The analyses that DOE performed for the notice of proposed rulemaking (NOPR) 

include: 

• a market and technology assessment to characterize the commercial refrigeration 

equipment market and review techniques and approaches used to produce more 

efficient commercial refrigeration equipment; 

• a screening analysis to identify design options that improve commercial refrigeration 

equipment efficiency and to determine which should be evaluated and which should 

be screened out;

• an engineering analysis to estimate the relationship between the manufacturing cost 

of a commercial refrigeration unit and its performance; 

• a markup analysis to convert manufacturer sales prices to customer purchase prices; 

• an energy use analysis to estimate the energy consumption of the equipment (for this 

NOPR, DOE used the energy consumption model from the engineering analysis and 

did not conduct a separate energy use analysis); 

• a life-cycle cost (LCC) and payback period (PBP) analysis to estimate the impact of 

potential new or amended standards on customers of commercial refrigeration 

equipment by calculating LCC and PBP values at all higher efficiency levels; 

• a shipments analysis to estimate shipments of commercial refrigeration equipment

over the time period examined in the analysis; 
2-2 

• a national impacts analysis to assess the aggregate impacts at the national level of net 

present value (NPV) of total customer savings and national energy savings (NES); 

• a customer subgroup LCC analysis to evaluate impacts on identifiable groups of 

customers who may be disproportionately affected by new or amended standards; 

• a manufacturer impact analysis (MIA) to estimate the financial impact of potential 

amended standards on commercial refrigeration equipment manufacturers and to 

calculate impacts on competition, employment at the manufacturing plant, and 

manufacturing capacity; 

• an emissions analysis to provide estimates of the effects of amended energy

conservation standards on emissions of carbon dioxide (CO2), sulfur dioxide (SO2), 

nitrogen oxides (NOX), and mercury (Hg); 

• a monetization of reduction of emission benefits from proposed standards; 

• a utility impact analysis to estimate the effects of proposed standards on the installed 

capacity and generating base of electric utilities; 

• an employment impact analysis to estimate the impacts of amended standards on net 

jobs eliminated or created in the general economy as a consequence of increased 

spending on the purchase price of commercial refrigeration equipment and reduced 

customer spending on energy; and 

• a regulatory impact analysis (RIA) to explore major alternatives to proposed 

standards that could achieve comparable energy savings. 

In response to comments it receives after publishing the NOPR, DOE may revise some of 

its analyses before publishing the final rule.
2-3 

Figure 2.1.1 Analyses for Commercial Refrigeration Equipment Energy Conservation 

Standards
2-4 

2.2 BACKGROUND

As described in chapter 1 of this technical support document (TSD), DOE announced a 

formal effort to consider further improvements to the process used to develop appliance 

efficiency standards. DOE called on energy efficiency groups, manufacturers, trade associations, 

state agencies utilities, and other interested parties to provide input to this effort. As a result of 

this combined effort, DOE published Procedures, Interpretations and Policies for Consideration 

of New or Revised Energy Conservation Standards for Consumer Products (the “Process Rule”), 

10 CFR part 430, subpart C, appendix A. The Process Rule outlined the procedural 

improvements identified by the interested parties, and included a review of the (1) economic 

models; (2) analytical tools; (3) methodologies; (4) non-regulatory approaches; and (5) 

prioritization of future rules. The Process Rule recommended that DOE take into account 

uncertainty and variability by carrying out scenario or probability analysis. The following 

sections provide a general description of the analytical components of the improved rulemaking 

framework. 

DOE developed the analytical framework pertaining to commercial refrigeration 

equipment in the Rulemaking Framework for Commercial Refrigeration Equipment

(April 30, 2010). DOE announced the availability of the Framework document in a notice of 

public meeting and availability of a Framework document published in the Federal Register on 

May 6, 2010. 75 FR at 24824. 

DOE presented the analytical approach to interested parties during a public meeting held 

on May 18, 2010.1

 DOE used comments gathered during the Framework public meeting as well 

as additional information for the preliminary analysis stage. DOE announced the notice of public 

meeting and the availability of the preliminary TSD2

 on March 30, 2011. 76 FR at 17573. 

The following sections provide a brief overview of the different analytical approaches of 

this rulemaking analysis plan. DOE has used the most reliable data available at the time of each 

analysis in this rulemaking. DOE has also considered the submissions of additional data from 

interested parties during the rulemaking process. 

2.3 MARKET AND TECHNOLOGY ASSESSMENT

The market and technology assessment characterizes the commercial refrigeration 

equipment market and existing technology options for making a unit of commercial refrigeration 

equipment more efficient. 

2.3.1 Market Assessment

DOE reviewed relevant literature and interviewed manufacturers to develop an overall 

picture of the commercial refrigeration equipment industry in the United States. Industry 

publications and trade journals, government agencies, and trade organizations provided the bulk 

of the information, including (1) manufacturers and their market shares; (2) shipments by 

product type and capacity; (3) product information; and (4) industry trends. 

When evaluating and establishing energy conservation standards, DOE generally divides 

covered equipment into equipment classes by the type of energy used, capacity, or other 
2-5 

performance-related features that affect efficiency. Different energy conservation standards may 

apply to different equipment classes. (42 U.S.C. 6295(q)) 

When initiating a standards rulemaking, DOE develops information on the present and 

past industry structure and market characteristics of the product(s) concerned. This activity 

consists of both quantitative and qualitative efforts to assess the industry and products based on 

publicly available information. 

2.3.2 Technology Assessment

The function of the technology assessment is to develop a preliminary list of technologies 

that could potentially be used to reduce the energy consumption of commercial refrigeration 

equipment, as well as to highlight the developments within those technology categories and their 

applicability to these equipment classes. The result is a list of technology options to be analyzed 

in the screening analysis. Chapter 3 of the TSD includes a detailed list of all technology options 

DOE identified for this rulemaking. 

2.4 SCREENING ANALYSIS

The purpose of the screening analysis is to evaluate the technologies identified in the 

technology assessment to determine which options to consider further in the analysis and which 

options to screen out. DOE consulted with industry, technical experts, and other interested 

parties in developing a list of energy-saving technologies for the technology assessment. DOE 

then applied the screening criteria to determine which technologies were unsuitable for further 

consideration in this rulemaking. Chapter 4 of the TSD, the screening analysis, contains details 

about DOE’s screening criteria. 

The screening analysis examines whether various technologies (1) are technologically 

feasible; (2) are practicable to manufacture, install, and service; (3) have an adverse impact on 

product utility or availability; and (4) have adverse impacts on health and safety. In consultation 

with interested parties, DOE reviewed the list of commercial refrigeration equipment 

technologies according to these criteria. In the engineering analysis, DOE further considers the 

efficiency-enhancement technologies that it did not eliminate in the screening analysis.

2.5 ENGINEERING ANALYSIS

The engineering analysis (chapter 5 of the TSD) develops cost-efficiency relationships

for commercial refrigeration equipment, estimating manufacturer costs of achieving increased 

efficiency levels. Manufacturing costs are used as the means of determining retail prices in the 

LCC analysis, and are needed for the MIA. The engineering analysis also determines the 

maximum technologically feasible energy efficiency level.

In general, the engineering analysis estimates the efficiency improvement potential of the 

individual or combinations of design options that passed the four criteria in the screening 

analysis. DOE, in consultation with stakeholders, uses the most appropriate method to determine 

the manufacturing cost-energy efficiency relationship. This cost-efficiency relationship 

developed in the engineering analysis is used in the LCC analysis.
2-6 

As described in TSD chapter 1, DOE will consider those commercial refrigeration 

equipment units that are designed to achieve the maximum improvement in energy efficiency 

that the Secretary of Energy determines are technologically feasible and economically justified. 

(42 U.S.C 6295(o)(2)(A)) Therefore, an important role of the engineering analysis is to identify 

the maximum technologically feasible level. The maximum technologically feasible level is one 

that is reached by the addition of efficiency improvements and/or design options, both 

commercially feasible and in prototypes, to the baseline units. DOE believes that the design 

options comprising the maximum technologically feasible level must have been physically 

demonstrated in at least a prototype form to be considered technologically feasible. 

DOE typically structures its engineering analysis around one of three methodologies: 

(1) the design-option approach, which calculates the incremental costs of adding specific design 

options to a baseline model; (2) the efficiency-level approach, which calculates the relative costs 

of achieving increases in energy efficiency levels without regard to design options used to 

achieve such increases; and/or (3) the reverse-engineering or cost-assessment approach, which 

involves a “bottom-up” manufacturing cost assessment based on a detailed bill of materials 

derived from tear-downs of the equipment being analyzed. 

In the Framework document, DOE stated its intention to use a design-option approach for 

the engineering analysis, as it was the methodology employed in the 2009 final rule analyses and 

was found to be the approach most appropriate for the equipment and technologies on the market 

because this equipment is designed and marketed based on the inclusion of specific features and 

components, rather than being sold as possessing a certain, standardized efficiency rating. In a 

design-option approach, analysis is performed in terms of incremental increases in efficiency due 

to the implementation of selected design options. For each equipment class, the engineering 

analysis estimates manufacturer production costs for each successive design option. Stakeholder 

comments did not refute this choice of a design-option approach, and thus this approach was 

employed in the preliminary analysis and NOPR engineering analysis. DOE also augmented this 

approach with some reverse-engineering analysis to develop base manufacturing costs for 

portions of the equipment analyzed. 

2.5.1 Baseline Models

In order to analyze design options for energy efficiency improvements, DOE defined a 

baseline model unit for each equipment class. DOE defined baseline models as units with the 

most popular and cost-effective features that are currently available on the market. It should be 

noted that this engineering baseline may, for some equipment classes, be comprised of lessefficient equipment than mandated by past standards, specifically the Energy Policy Act of 2005 

and 2009 DOE final rule standards. This is due to the fact that the rulemaking analyses were 

conducted in advance of the compliance date of some of these standards. In its selection process, 

DOE considered technical descriptions of the covered equipment, definitions of the equipment 

classes as described in the previous rulemaking documents, results of the market assessment, and 

suggestions from stakeholders.
2-7 

2.5.2 Manufacturing Cost Analysis 

There are several ways to develop the relationship between cost and performance. DOE 

chose to use a design-option approach in this rulemaking. This approach identifies potential 

technological paths manufacturers could use to achieve increased equipment energy efficiency. 

To develop a base cost for the core case of the commercial refrigeration units, DOE purchased 

units available on the market for specific equipment classes and dismantled them component-bycomponent to develop a bill of materials and cost model for the core of the refrigerated case. 

DOE then parameterized and expanded this information to apply to all equipment classes being 

modeled. Then, in the engineering cost model, DOE added these core costs to the costs of the 

energy-consuming components, developed using independent costing methods in conjunction 

with manufacturer data. The result was a cost for an entire production unit at each of the 

efficiency levels analyzed. 

2.6 MARKUPS FOR EQUIPMENT PRICE DETERMINATION 

DOE used the markup analysis to determine distribution channel markups that were used 

to convert the manufacturer selling price (MSP) of the equipment into customer purchase price. 

DOE identified three different major channels through which the customers purchase 

commercial refrigeration equipment. DOE then determined the market shares of each distribution 

channel. The markup values associated with each distribution channel were calculated from the 

industry profit data. Sales tax is an additional markup in addition to the markups associated with 

distribution channels. DOE calculated a weighted-average sales tax for the entire nation. Finally, 

the overall markups were calculated by weighted-averaging the distribution channel markups and 

adding the weighted-average sales tax. DOE calculated baseline markups that were applied to 

baseline MSPs and incremental markups that were applied to MSP increments at higher 

efficiency levels. See TSD chapter 6 for details on the markups analysis. 

2.7 ENERGY USE ANALYSIS

Based on the energy use analysis conducted as part of the 2009 final rule analysis, DOE 

concluded that the energy consumption model, which is part of the engineering analysis, was 

sufficiently accurate to calculate the energy use of commercial refrigeration equipment. 

Therefore, DOE did not conduct a separate energy use analysis as part of this rulemaking. 

2.8 LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS

DOE carried out the LCC and PBP analysis to evaluate the economic impacts of possible 

amended energy conservation standards developed for commercial refrigeration equipment on 

individual commercial customers. The effect of standards on customers includes a change in 

operating cost (usually decreased) and a change in purchase cost (usually increased). Two 

metrics were used to determine the effect of standards on customers:

• Life-cycle cost. LCC is the total customer cost over the life of the equipment–the sum 

of installed cost (purchase and installation costs) and operating costs (maintenance, 

repair, and energy costs). Future operating costs are discounted to the time of 

purchase and summed over the lifetime of equipment.
2-8 

• Payback period. PBP is the estimated amount of time it would take customers to 

recover the assumed higher purchase price of more-efficient equipment through lower 

operating costs.

An efficiency improvement to commercial refrigeration equipment that is financially 

attractive to a customer will typically have a low incremental PBP and a low incremental change 

in LCC associated with it.

As part of the engineering analysis (TSD chapter 5), design-option levels were ordered on 

the basis of increasing efficiency (decreased energy consumption) and increasing MSP values. 

The order was determined based on the cost-effectiveness of each design option; that is, the ratio 

of incremental cost increase to incremental energy savings. For the LCC and PBP analysis, DOE 

chose a maximum of eight levels, henceforth referred to as efficiency levels, from the list of 

engineering design-option levels. 

The first efficiency level or baseline efficiency level (Level 1) in each equipment class 

represents the least efficient and the least expensive equipment in that equipment class. The 

higher efficiency levels (Level 2 and up) have a progressive increase in efficiency and cost from 

Level 1. The highest efficiency level in each equipment class corresponds to the maximum 

technologically feasible (max-tech) level (see TSD chapter 5 for details). DOE treats each

efficiency level as a candidate standard level (CSL), as each efficiency level represents a 

potential standard level. The words “efficiency level” and “CSL” can be used interchangeably.

The installed cost of equipment to a customer is the sum of the equipment purchase price 

and installation costs. The purchase price includes manufacturer production cost, to which a 

manufacturer markup and outbound freight costs are applied to obtain the MSP. This value is 

calculated as part of the engineering analysis (TSD chapter 5). DOE then applies additional 

markups to the equipment to account for the markups associated with the distribution channels 

for this type of equipment (TSD chapter 6). Installation costs vary by state depending on the 

prevailing labor rates. 

Operating costs for commercial refrigeration equipment are a sum of maintenance costs, 

repair costs, and energy costs. These costs are incurred over the life of the equipment and 

therefore are discounted to the base year (2017, which is the compliance date of the amended 

standards that will be established as part of this rulemaking). The sum of the installed cost and 

the operating cost, discounted to reflect the present value, is termed the LCC. 

Generally, customers incur higher installed costs when they purchase higher efficiency 

equipment, and these cost increments will be offset partially or wholly by savings in the 

operating costs over the lifetime of the equipment. Usually, the savings in operating costs are due 

to savings in energy costs because higher efficiency equipment uses less energy over the lifetime 

of the equipment. LCC savings are calculated for each CSL of each equipment class.

The PBP of a CSL is obtained by dividing the increase in the installed cost (from the 

baseline efficiency level) by the decrease in annual operating cost (from the baseline efficiency 

level). For this calculation, DOE uses the first year operating cost changes as the estimate of the 
2-9 

decrease in operating cost, noting that some of the repair and replacement costs used herein are 

annualized estimates of costs. PBP is calculated for each CSL of each equipment class.

Apart from MSP, installation costs, and maintenance and repair costs, other important 

inputs for the LCC analysis are markups and sales tax, equipment energy consumption, 

electricity prices and future price trends, equipment lifetime, and discount rates.

Many inputs for the LCC analysis are estimated from the best available data in the 

market, and in some cases the inputs are generally accepted representative values within the 

commercial refrigeration equipment industry. However, in most cases each input has a range of 

values. For example, even though the average (and representative) lifetime of commercial 

refrigeration units in certain equipment classes may be 10 years, in general, equipment lifetimes 

of a typical refrigerator belonging to that equipment class may vary from 5 years to 15 years. 

While calculations based on the representative values yield average or representative values for 

the outputs (such as LCC or PBP), such values do not give an estimate of the ranges of values 

that these outputs could lie in. Therefore, DOE performed the LCC analysis in the form of Monte 

Carlo simulations in which certain inputs are provided a range of values and probability 

distributions. The results of the LCC analysis are presented in the form of mean and median LCC 

savings; percentages of customers experiencing net savings, net cost, and no impact in LCC; and 

median PBP. For each equipment class, 10,000 Monte Carlo simulations were carried out. The 

simulations were conducted using Microsoft Excel and Crystal Ball, a commercially available 

Excel add-in for carrying out Monte Carlo simulations. 

Usually, the equipment available in the market will have a distribution of efficiencies, 

that is, each CSL within an equipment class will have a corresponding market share associated 

with it. Usually, within an equipment class, the market share of the baseline efficiency level is 

the highest and the market share values decrease with an increase in CSL. LCC savings and PBP 

are calculated by comparing the installed costs and LCC values of the standards-case scenarios 

against those of the base-case scenario. The base-case scenario is the scenario in which 

equipment is assumed to be purchased by customers in the absence of the proposed amended 

energy conservation standards. Standards-case scenarios are scenarios in which equipment is 

assumed to be purchased by customers after the amended energy conservation standards go into 

effect. The number of standards-case scenarios for an equipment class is equal to one less than 

the total number of efficiency levels in that equipment class because each CSL above the 

baseline efficiency level represents a potential new standard. For the standards-case scenario at a 

particular CSL, the market share of the efficiency levels were obtained using a roll-up scenario, 

in which market shares of the efficiency levels (in the base-case scenario) below the 

corresponding CSL were rolled-up into the CSL. For the base-case scenario in the LCC analysis, 

DOE calculated the market shares of the efficiency levels using a method described in TSD 

chapter 10. 

Recognizing that each commercial building that uses the commercial refrigeration 

equipment is unique, DOE analyzed the LCC and PBP calculations for seven types of 

businesses: (1) supermarkets; (2) wholesaler/retailer multi-line stores, such as “big-box stores,” 

“warehouses,” and “supercenters”; (3) convenience and small specialty stores, such as meat 

markets, wine, beer, and liquor stores; (4) convenience stores associated with gasoline stations; 

(5) full-service restaurants; (6) limited service restaurants; and (7) other foodservice businesses, 
2-10

such as caterers and cafeterias. Different types of businesses face different energy prices and also 

exhibit differing discount rates that they apply to purchase decisions. 

Equipment lifetime is another input that does not justify usage of a single value for each 

equipment class. Therefore, DOE assumes a distribution of equipment lifetimes that are defined 

by Weibull survival functions. 

Another important factor influencing the LCC analysis is the state (location) in which the 

commercial refrigeration equipment is installed. Inputs that vary based on this factor include 

energy prices, installation costs, contractor markups, and sales tax. At the national level, the 

spreadsheets explicitly modeled variability in the model inputs for electricity price and markups 

using probability distributions based on the relative shipments of units to different states and 

business types. 

2.9 SHIPMENTS ANALYSIS

Commercial refrigeration equipment shipment numbers are key inputs to the NES

analysis, NPV calculations, and the MIA. Shipments analysis is used to estimate future 

commercial refrigeration equipment shipments over the national impact analysis period.

DOE calculated the historical shipments of commercial refrigeration equipment for the 

year 2009 based various shipments data sources. DOE then used the Annual Energy Outlook3

2013 (AEO2013) forecasts of commercial floor space additions, equipment lifetimes, and 

estimates of existing equipment stock to calculate the future shipments. 

TSD chapter 9 presents the mathematical formulation of the shipment analysis model and 

the methodology used to estimate historical and future shipments of commercial refrigeration 

equipment. 

2.10 NATIONAL IMPACT ANALYSIS

NES and NPV impacts are the cumulative energy and economic effects of an amended 

commercial refrigeration equipment energy conservation standard (TSD chapter 10). DOE 

projected the impacts from the year the standard would take effect through a selected number of 

years in the future. DOE analyzed energy savings, energy cost savings, equipment costs, and 

NPV of savings (or costs) for each CSL. The national energy and cost savings (or increases) that 

would result from amended energy conservation standards depend on the projected energy 

savings per unit and the anticipated amount of equipment sold. DOE created base-case shipment 

projections that include units at various efficiency levels. It based the projections on historical 

information plus forecasts of market influences, national economic growth, and electricity 

consumption. DOE then derived energy savings for various CSLs from the cost-efficiency 

schedules.

To make the analysis more accessible and transparent to all stakeholders, DOE used an 

Excel spreadsheet model to calculate the NES and the NPV (i.e., national economic costs and 

savings from new standards). Users can change input quantities within the spreadsheet to test the 

impact of alternative input assumptions. Unlike the LCC analysis, the NES spreadsheet does not 
2-11

use distributions for inputs or outputs. Users can demonstrate sensitivities by running different 

scenarios using the spreadsheet. 

As discussed in TSD chapter 10, the national impact analysis assesses the NPV of total 

consumer LCC and NES. DOE conducted an assessment of the aggregate impacts at the national 

level for the NOPR. Analyzing impacts of Federal energy conservation standards requires a 

comparison of projected U.S. energy consumption with and without amended standards. The 

base case, which is the projected U.S. energy consumption without standard, includes the mix of 

efficiencies being sold at the time the standard becomes effective.

DOE estimated national energy consumption for each year beginning with the expected 

effective date of the standard. DOE calculated national annual energy savings as the difference 

between two projections: a base case and a standards case. 

DOE has historically presented NES in terms of primary energy savings. DOE has begun to 

also estimate full-fuel-cycle energy savings. 76 FR 51282 (August 18, 2011), as amended at 77 FR 

49701 (August 17, 2012). The full-fuel-cycle (FFC) metric includes the energy consumed in 

extracting, processing, and transporting primary fuels, and thus presents a more complete picture of 

the impacts of energy efficiency standards. DOE’s approach is based on the calculation of an FFC 

multiplier for each of the energy types used by covered equipment. 

While DOE stated in that notice that it intended to use the Greenhouse Gases, Regulated 

Emissions, and Energy Use in Transportation (GREET) model to conduct the analysis, it also said it 

would review alternative methods, including the use of the DOE/Energy Information Administration 

(EIA)’s National Energy Modeling System (NEMS).a NEMS is a public domain, multi-sectored, 

partial equilibrium model of the U.S. energy sector. Each year, DOE/EIA uses NEMS to produce the 

Annual Energy Outlook (AEO). After evaluating both models and the approaches discussed in the 

August 18, 2011 notice, DOE has determined NEMS is a more appropriate tool for this application. 

77 FR 49701 (Aug. 17, 2012). Therefore, DOE is using the NEMS model to conduct FFC analyses. 

For the NOPR analysis, DOE calculated FFC energy savings using a methodology described in 

appendix 10D. Chapter 10 of this TSD presents both the primary NES and the FFC energy savings 

for the considered trial standard levels (TSLs).

2.11 CUSTOMER SUBGROUP ANALYSIS

The customer subgroup analysis evaluates impacts on identifiable groups of customers of 

commercial refrigeration equipment who may be disproportionately disadvantaged by amended 

energy conservation standards. The LCC and PBP analysis described in chapter 8 of this TSD is 

applied to seven major types of businesses belonging to the food-retail and foodservice sectors 

that use a majority of the commercial refrigeration equipment. Although the inputs for different 

types of businesses are different in the LCC and PBP analysis, the final results may not reflect 

the results experienced by certain customer subgroups. In other words, some of the adverse 

impacts on businesses that are disproportionately disadvantaged may be masked by the averaging

effect of the LCC and PBP analysis. Therefore, DOE carried out the customer subgroup analysis 

 

a For more information on NEMS, refer to DOE EIA documentation. A useful summary is National Energy 

Modeling System: An Overview 2003, DOE/EIA-0581(2003), March 2003.
2-12

by using the LCC and PBP analysis spreadsheet, but applying the inputs that are applicable only 

to the identified subgroups. 

In general, the subgroups that face higher cost of capital and lower electricity price rates 

are more disadvantaged than others. Higher cost of capital imposes burden on the businesses 

because they have to borrow additional capital to purchase equipment that meets new or 

amended standards, compared to the case of where there are no new or amended standards. 

Lower electricity price rates result in lower savings in energy costs and, consequently, lower 

LCC savings and higher PBPs. 

DOE carried out two customer subgroup analyses, one each for full-service restaurants 

and gasoline stations with convenience stores, by using the LCC spreadsheet described in TSD 

chapter 8, but with certain modifications. The input for business type was fixed to the identified 

subgroup, which ensured that the discount rates and electricity price rates associated with only 

that subgroup were selected in the Monte Carlo simulations (see TSD chapter 8). Additionally, a 

small business premium was added to the discount rate to reflect the higher discount rates faced 

by small businesses. Another major change from the LCC analysis was an added assumption that 

the subgroups do not have access to national accounts, which results in higher distribution 

channel markups for the subgroups, leading to higher equipment purchase prices. Apart from 

these changes, all other inputs for the customer subgroup analysis are same as those in the LCC 

analysis described in TSD chapter 8. 

2.12 MANUFACTURER IMPACT ANALYSIS

The MIA assesses the impacts of new energy conservation standards on manufacturers of 

the considered equipment. Potential impacts include financial effects, both quantitative and 

qualitative, that might lead to changes in the manufacturing practices for this equipment. DOE 

identified these potential impacts through interviews with manufacturers and other interested 

parties. 

DOE conducted the MIA in three phases, and further tailored the analytical framework 

based on interested parties’ comments. In Phase I, an industry profile was created to characterize 

the industry, and a preliminary MIA was conducted to identify important issues that required 

consideration. In Phase II, an industry cash flow model and an interview questionnaire were 

prepared to guide subsequent discussions. In Phase III, manufacturers were interviewed, and the 

impacts of standards were assessed both quantitatively and qualitatively. Industry and subgroup 

cash flow and NPV were assessed through use of the Government Regulatory Impact Model 

(GRIM). Then impacts on competition, manufacturing capacity, employment, and cumulative 

regulatory burden were assessed based on manufacturer interview feedback and discussions. 

DOE discusses its findings from the MIA in chapter 12 of the TSD.

2.13 EMISSIONS ANALYSIS

In the emissions analysis, DOE estimated the reduction in power sector emissions of 

carbon dioxide (CO2), nitrogen oxides (NOx), sulfur dioxide (SO2) and mercury (Hg) from 

potential energy conservation standards for commercial refrigeration equipment. In addition, 

DOE estimated emissions impacts in production activities (extracting, processing, and 
2-13

transporting fuels) that provide the energy inputs to power plants. These are referred to as 

“upstream” emissions. Together, these emissions account for the FFC. In accordance with 

DOE’s FFC Statement of Policy (76 FR 51282 (Aug. 18, 2011)), as amended at 77 FR 49701 

(August 17, 2012), the FFC analysis includes impacts on emissions of methane (CH4) and 

nitrous oxide (N2O), both of which are recognized as greenhouse gases. 

DOE conducted the emissions analysis using emissions factors derived from data in the 

latest version of EIA’s AEO2013, supplemented by data from other sources. DOE developed 

separate emissions factors for power sector emissions and upstream emissions. The method that 

DOE used to derive emissions factors is described in chapter 13 of the NOPR TSD.

EIA prepares the AEO using the NEMS. Each annual version of NEMS incorporates the 

projected impacts of existing air quality regulations on emissions. AEO2013 generally represents 

current legislation and environmental regulations, including recent government actions, for 

which implementing regulations were available as of December 31, 2012. 

SO2 emissions from affected electric generating units (EGUs) are subject to nationwide 

and regional emissions cap and trading programs. Title IV of the Clean Air Act sets an annual 

emissions cap on SO2 for affected EGUs in the 48 contiguous States and the District of 

Columbia (D.C.). SO2 emissions from 28 eastern States and D.C. were also limited under the 

Clean Air Interstate Rule (CAIR), which created an allowance-based trading program that 

operates along with the Title IV program in those States and D.C. 70 FR 25162 (May 12, 2005). 

CAIR was remanded to the U.S. Environmental Protection Agency (EPA) by the U.S. Court of 

Appeals for the District of Columbia Circuit (D.C. Circuit), but it remained in effect. See North 

Carolina v. EPA, 550 F.3d 1176 (D.C. Cir. 2008); North Carolina v. EPA, 531 F.3d 896 (D.C. 

Cir. 2008). On July 6, 2011, EPA issued a replacement for CAIR, the Cross-State Air Pollution 

Rule (CSAPR; also known as the Transport Rule). 76 FR 48208 (August 8, 2011). On August 

21, 2012, the D.C. Circuit issued a decision to vacate CSAPR. See EME Homer City 

Generation, LP v. EPA, 696 F.3d 7, 38 (D.C. Cir. 2012). The court ordered EPA to continue 

administering CAIR. The AEO2013 emissions factors used for today’s NOPR assume that CAIR 

remains a binding regulation through 2040. 

The attainment of emissions caps is typically flexible among EGUs and is enforced 

through the use of emissions allowances and tradable permits. Under existing EPA regulations, 

any excess SO2 emissions allowances resulting from the lower electricity demand caused by the 

adoption of an efficiency standard could be used to permit offsetting increases in SO2 emissions 

by any regulated EGU. In past rulemakings, DOE recognized that there was uncertainty about 

the effects of efficiency standards on SO2 emissions covered by the existing cap-and-trade 

system, but it concluded that no reductions in power sector emissions would occur for SO2 as a 

result of standards. 

Beginning in 2015, however, SO2 emissions will fall as a result of the Mercury and Air 

Toxics Standards (MATS) for power plants, which were announced by EPA on December 21, 

2011. 77 FR 9304 (Feb. 16, 2012). In the final MATS rule, EPA established a standard for HCl 

as a surrogate for acid gas hazardous air pollutants (HAP), and also established a standard for 

SO2 (a non-HAP acid gas) as an alternative equivalent surrogate standard for acid gas HAP. The 

same controls are used to reduce HAP and non-HAP acid gas; thus, SO2 emissions will be 
2-14

reduced as a result of the control technologies installed on coal-fired power plants to comply 

with the MATS requirements for acid gas. AEO2013 assumes that, in order to continue 

operating, coal plants must have either flue gas desulfurization or dry sorbent injection systems 

installed by 2015. Both technologies, which are used to reduce acid gas emissions, also reduce 

SO2 emissions. Under the MATS, NEMS shows a reduction in SO2 emissions when electricity 

demand decreases (e.g., as a result of energy efficiency standards). Emissions will be far below 

the cap established by CAIR, so it is unlikely that excess SO2 emissions allowances resulting 

from the lower electricity demand would be needed or used to permit offsetting increases in SO2 

emissions by any regulated EGU. Therefore, DOE believes that efficiency standards will reduce 

SO2 emissions in 2015 and beyond. 

CAIR established a cap on NOx emissions in eastern States and the District of Columbia. 

Energy conservation standards are expected to have little or no physical effect on these emissions 

in those States covered by CAIR because excess NOx emissions allowances resulting from the 

lower electricity demand could be used to permit offsetting increases in NOx emissions. 

However, standards would be expected to reduce NOx emissions in the States not affected by 

caps, so DOE estimated NOx emissions reductions from the standards considered in today’s 

NOPR for these States. 

The MATS limit mercury emissions from power plants, but they do not include emissions 

caps and, as such, DOE’s energy conservation standards would likely reduce Hg emissions. DOE 

will estimate mercury emissions reduction using emissions factors based on AEO2013, which 

incorporates the MATS. 

2.14 MONETIZATION OF EMISSIONS REDUCTIONS BENEFITS

DOE considered the estimated monetary benefits likely to result from the reduced 

emissions of CO2 and NOx that are expected to result from each of the standard levels 

considered. 

To estimate the monetary value of benefits resulting from reduced emissions of CO2, 

DOE used the most current Social Cost of Carbon (SCC) values developed and/or agreed to by 

an interagency process. The SCC is intended to be a monetary measure of the incremental 

damage resulting from greenhouse gas (GHG) emissions, including, but not limited to, net 

agricultural productivity loss, human health effects, property damage from sea level rise, and 

changes in ecosystem services. Any effort to quantify and to monetize the harms associated with 

climate change will raise serious questions of science, economics, and ethics. But with full 

regard for the limits of both quantification and monetization, the SCC can be used to provide 

estimates of the social benefits of reductions in GHG emissions. 

The Interagency Working Group on SCC released an update of its previous report in 

2013.b

 The most recent estimates of the SCC in 2015, expressed in 2012$, are $12.9, $40.8, 

$62.2, and $117 per metric ton of CO2 avoided. For emissions reductions that occur in later 

years, these values grow in real terms over time. Additionally, the interagency group determined 

 

b Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866. 

Interagency Working Group on Social Cost of Carbon, United States Government, May 2013. 

http://www.whitehouse.gov/sites/default/files/omb/inforeg/social_cost_of_carbon_for_ria_2013_update.pdf
2-15

that a range of values from 7 percent to 23 percent should be used to adjust the global SCC to 

calculate domestic effects, although DOE gives preference to consideration of the global benefits 

of reducing CO2 emissions. 

DOE multiplies the CO2 emissions reduction estimated for each year by the SCC value 

for that year in each of the four cases. To calculate a present value of the stream of monetary 

values, DOE discounts the values in each of the four cases using the discount rates that had been 

used to obtain the SCC values in each case.

DOE recognizes that scientific and economic knowledge continues to evolve rapidly as to 

the contribution of CO2 and other GHG to changes in the future global climate and the potential 

resulting damages to the world economy. Thus, these values are subject to change. 

DOE also estimates the potential monetary benefit of reduced NOx emissions resulting 

from the standard levels it considers. For NOx emissions, estimates suggest a very wide range of 

monetary values, ranging from 468 to $4,809 per ton in 2012$).c In accordance with OMB 

guidance, d DOE calculates a range of monetary benefits using each of the economic values for 

NOx and real discount rates of 3 percent and 7 percent. 

DOE is evaluating appropriate valuation of avoided SO2 and Hg emissions. Whether 

monetization of reduced Hg emissions will occur in this rulemaking is yet to be determined. 

2.15 UTILITY IMPACT ANALYSIS

DOE analyzed specific effects of its proposed standard levels on the electric utility 

industry as part of the NOPR analyses, using a variant of the DOE EIA NEMS. The version of 

NEMS used for appliance standards analysis is called NEMS-Building Technologies (NEMSBT)e

 and is based on the AEO2013 Reference Case with minor modifications. 

The utility impact analysis reports the changes in installed capacity and generation, by 

fuel type, that result from the adoption of new efficiency standards at each TSL, as well as 

changes in electricity consumption.

2.16 EMPLOYMENT IMPACT ANALYSIS

The imposition of standards can affect employment both directly and indirectly. Direct 

employment impacts are changes in the number of employees at the factories that produce the 

covered equipment, along with the affiliated distribution and service companies, resulting from 

the imposition of new standards. DOE evaluates direct employment impacts in the MIA. Indirect 

 

c For additional information, refer to U.S. Office of Management and Budget, Office of Information and Regulatory 

Affairs, 2006 Report to Congress on the Costs and Benefits of Federal Regulations and Unfunded Mandates on 

State, Local, and Tribal Entities, Washington, DC.

d OMB, Circular A-4: Regulatory Analysis (Sept. 17, 2003). e EIA approves use of the name NEMS to describe only an official version of the model without any modification to 

code or data. Because this analysis entails some minor code modifications and the model is run under various policy 

scenarios that are variations on EIA assumptions, DOE refers to it by the name NEMS-BT (BT is DOE’s Building 

Technologies Program, under whose aegis this work has been performed). NEMS-BT was previously called NEMSBRS.
2-16

employment impacts may result from expenditures shifting between goods (the substitution 

effect) and changes in income and overall expenditure levels (the income effect) that occur due 

to the imposition of standards. The combined direct and indirect employment effects are 

investigated in the employment impact analysis using the Pacific Northwest National 

Laboratory’s “Impact of Sector Energy Technologies” (ImSET) model. The ImSET model was 

developed for DOE’s Office of Planning, Budget, and Analysis, and estimates the employment 

and income effects of energy-saving technologies in buildings, industry, and transportation. In 

comparison with simple economic multiplier approaches, ImSET allows for more complete and 

automated analysis of the economic impacts of energy conservation investments. 

2.17 REGULATORY IMPACT ANALYSIS

In the NOPR stage, DOE prepared an RIA pursuant to Executive Order 12866, 

Regulatory Planning and Review, 58 FR 51735 (Oct. 4, 1993), which is subject to review under 

the Executive Order by the Office of Information and Regulatory Affairs at the Office of 

Management and Budget. The RIA addressed the potential for non-regulatory approaches to 

supplant or augment energy conservation standards to improve the energy efficiency or reduce 

the energy consumption of the commercial refrigeration equipment covered under this 

rulemaking. 

2.18 DEPARTMENT OF JUSTICE REVIEW

Section 325(o)(2)(B)(i)(V) of the Energy Policy and Conservation Act states that before 

the Secretary of Energy may prescribe a new or amended energy conservation standard, the 

Secretary shall ask the Attorney General to make a determination of “the impact of any lessening 

of competition...that is likely to result from the imposition of the standard.” (42 U.S.C. 6295) 

Pursuant to this requirement, DOE will solicit the views of the Department of Justice (DOJ) on 

any lessening of competition that is likely to result from the imposition of a proposed standard 

and will give the views provided full consideration in assessing the economic justification of a 

proposed standard. DOE may consult with DOJ at earlier stages in the standards development 

process to seek to obtain preliminary views on competitive impacts. 
2-17

REFERENCES

1. U.S. Department of Energy-Office of Energy Efficiency and Renewable Energy Building 

Technologies Program. Rulemaking Framework for Commercial Refrigeration Equipment. 

2010. Washington, D.C. < http://www1.eere.energy.gov/buildings/appliance_standards/

product.aspx/productid/52> 

2. U.S. Department of Energy–Office of Energy Efficiency and Renewable Energy. 

Preliminary Technical Support Document: Energy Conservation Program for Certain 

Commercial and Industrial Equipment: Commercial Refrigeration Equipment. April 2011. 

Washington, D.C. <http://www.regulations.gov/#!documentDetail;D=EERE-2010-BTSTD-0003-0030> 

3. U.S. Department of Energy-Energy Information Administration. Annual Energy Outlook 

2013, 2013. Washington, DC. DOE/EIA-0383(2013). <http://www.eia.gov/forecasts/aeo/> 
CHAPTER 3. MARKET AND TECHNOLOGY ASSESSMENT

TABLE OF CONTENTS 

3.1 INTRODUCTION ........................................................................................................... 3-1

3.2 MARKET ASSESSMENT .............................................................................................. 3-4

3.2.1 Trade Association ................................................................................................ 3-4

3.2.2 Manufacturers and Market Share ......................................................................... 3-5

3.2.2.1 Small Businesses ................................................................................. 3-7

3.2.3 Regulatory Programs ........................................................................................... 3-8

3.2.3.1 Natural Resources Canada ................................................................... 3-8

3.2.3.2 Canadian Standards Association ......................................................... 3-9

3.2.3.3 Australia ............................................................................................ 3-10

3.2.4 Non-Regulatory Initiatives................................................................................. 3-10

3.2.4.1 ENERGY STAR ................................................................................ 3-10

3.2.4.2 Consortium for Energy Efficiency .................................................... 3-11

3.2.4.3 Federal Energy Management Program .............................................. 3-11

3.2.4.4 Rebate Programs ................................................................................ 3-12

3.2.5 Equipment Classes ............................................................................................. 3-12

3.2.6 Shipments ........................................................................................................... 3-17

3.2.6.1 ARI Data ............................................................................................ 3-17

3.2.6.2 NAFEM Data .................................................................................... 3-19

3.2.6.3 Freedonia Market Reports ................................................................. 3-19

3.2.6.4 Appliance Magazine Data ................................................................. 3-20

3.2.6.5 Census Bureau Data .......................................................................... 3-21

3.2.7 Equipment Lifetimes .......................................................................................... 3-23

3.2.8 Market Performance Data .................................................................................. 3-24

3.2.8.1 Remote Condensing Equipment ........................................................ 3-24

3.2.8.2 Self-Contained Equipment ................................................................ 3-25

3.3 TECHNOLOGY ASSESSMENT .................................................................................. 3-29

3.3.1 Technologies and Designs Relevant to All Equipment Classes ........................ 3-29

3.3.1.1 Higher Efficiency Lighting ............................................................... 3-29

3.3.1.2 Higher Efficiency Lighting Ballasts .................................................. 3-30

3.3.1.3 Remote Lighting Ballast Location .................................................... 3-30

3.3.1.4 Higher Efficiency Expansion Valves ................................................ 3-30

3.3.1.5 Higher Efficiency Evaporator Fan Motors ........................................ 3-31

3.3.1.6 Variable-Speed Evaporator Fan Motors and Evaporator Fan Motor 

Controllers.......................................................................................................... 3-32

3.3.1.7 Higher Efficiency Evaporator Fan Blades ......................................... 3-32

3.3.1.8 Improved Evaporator Coil Design .................................................... 3-33

3.3.1.9 Low-Pressure Differential Evaporators ............................................. 3-34

3.3.1.10 Case Insulation Increases or Improvements ...................................... 3-34

3.3.1.11 Defrost Mechanisms .......................................................................... 3-34

3.3.1.12 Defrost Cycle Control ....................................................................... 3-35

3.3.1.13 Vacuum Insulated Panels .................................................................. 3-35

3.3.1.14 Occupancy Sensors for Lighting Controls ........................................ 3-35

3-i 
3.3.2 Designs Relevant Only to Equipment with Doors ............................................. 3-36

3.3.2.1 Improved Transparent Doors ............................................................. 3-36

3.3.2.2 Anti-Fog Films on Transparent Doors .............................................. 3-36

3.3.2.3 Anti-Sweat Heater Controllers .......................................................... 3-37

3.3.3 Designs Relevant Only to Equipment Without Doors ....................................... 3-37

3.3.3.1 Air Curtain Design ............................................................................ 3-37

3.3.3.2 Night Curtains ................................................................................... 3-37

3.3.4 Technologies and Designs Relevant Only to Self-Contained Equipment ......... 3-38

3.3.4.1 Higher Efficiency Compressors ........................................................ 3-38

3.3.4.2 Liquid Suction Heat Exchangers ....................................................... 3-39

3.3.4.3 Improved Condenser Coil Design ..................................................... 3-39

3.3.4.4 Higher Efficiency Condenser Fan Motors ......................................... 3-40

3.3.4.5 Variable-Speed Condenser Fan Motors and Condenser Fan Motor 

Controllers.......................................................................................................... 3-40

3.3.4.6 Higher Efficiency Condenser Fan Blades ......................................... 3-40

REFERENCES .......................................................................................................................... 3-41

LIST OF TABLES

Table 3.2.1 Canadian Standards Association Equipment Classes and Efficiency Ratings ......... 3-9

Table 3.2.2 ENERGY STAR Commercial Refrigerator and Freezer Key Criteria ................... 3-11

Table 3.2.3 Commercial Refrigeration Equipment Families ..................................................... 3-14

Table 3.2.4 Commercial Refrigeration Equipment Classes ....................................................... 3-16

Table 3.2.5 ARI 2005 Shipments of Commercial Refrigerators and Freezers by Equipment Class

............................................................................................................................ 3-18

Table 3.2.6 NAFEM Shipments Categories and Corresponding DOE Equipment Classes ...... 3-19

Table 3.2.7 Freedonia Shipments Categories and Corresponding DOE Equipment Classes .... 3-20

Table 3.2.8 Historical Shipments of Refrigerated Display Cases .............................................. 3-20

Table 3.2.9 Statistical Forecasts of Refrigerated Display Case Shipments ............................... 3-20

Table 3.2.10 Historical Shipments of Commercial Refrigerators.............................................. 3-21

Table 3.2.11 Statistical Forecasts of Commercial Refrigerator Shipments ............................... 3-21

Table 3.2.12 Shipments of Open Refrigerated Display Cases (Remote Condensing and SelfContained) .......................................................................................................... 3-22

Table 3.2.13 Shipments of Closed Refrigerated Display Cases (Remote Condensing and SelfContained) .......................................................................................................... 3-22

Table 3.2.14 Shipments of Commercial Reach-In Cabinets (Remote Condensing and SelfContained) .......................................................................................................... 3-23

Table 3.2.15 Estimates for Commercial Refrigeration Equipment Lifetimes ........................... 3-24

LIST OF FIGURES

Figure 3.2.1 Domestic Refrigerated Display Case Market Shares as of 2005 ............................. 3-6

Figure 3.2.2 Domestic Commercial Refrigerator Market Share as of 2008 ................................ 3-7

Figure 3.2.3 Market Performance Data for the VOP.SC.M Equipment Class .......................... 3-25

Figure 3.2.4 Market Performance Data for the VCT.SC.M Equipment Class .......................... 3-26

Figure 3.2.5 Market Performance Data for the VCT.SC.L Equipment Class ........................... 3-26

Figure 3.2.6 Market Performance Data for the VCS.SC.M Equipment Class........................... 3-27

3-ii
Figure 3.2.7 Market Performance Data for the VCS.SC.L Equipment Class ............................ 3-27

Figure 3.2.8 Market Performance Data for the HCT.SC.M Equipment Class .......................... 3-28

Figure 3.2.9 Market Performance Data for the HCT.SC.L Equipment Class ........................... 3-28

Figure 3.2.10 Market Performance Data for the HCS.SC.M Equipment Class ......................... 3-29

3-iii
CHAPTER 3. MARKET AND TECHNOLOGY ASSESSMENT

3.1 INTRODUCTION

This chapter details the market and technology assessment that the U.S. Department of 

Energy (DOE) has conducted in support of the ongoing energy conservation standards 

rulemaking for commercial refrigeration equipment, including self-contained and remote 

condensing commercial refrigerators, freezers, refrigerator-freezers, and ice-cream freezers; and 

self-contained commercial refrigerators with transparent doors designed for pull-down 

temperature applications. 

The purpose of the market assessment is to develop a qualitative and quantitative 

characterization of the commercial refrigeration equipment industry and market structure based 

on publicly available information and information submitted by manufacturers and other 

stakeholders. Manufacturer characteristics and market shares, existing regulatory and nonregulatory efficiency improvement initiatives, equipment classes, and trends in markets and 

equipment characteristics are addressed. The purpose of the technology assessment is to develop 

a preliminary list of technologies that could improve the efficiency of commercial refrigeration 

equipment. 

Commercial refrigeration equipment is primarily used in the food retail industry (e.g.,

supermarkets, grocery stores, and convenience stores) and in the foodservice industry (e.g., 

restaurants and cafeterias) to store, display, and merchandize perishable food products. 

Definitions

Section 136(a)(3) of the Energy Policy Act of 2005 (EPACT 2005) amended section 340 

of the Energy Policy and Conservation Act (EPCA), in part by adding subsection 340(9) (42 

U.S.C 6311(9)) with definitions for the following terms that describe commercial refrigeration 

equipment: 

 

(9)(A) The term “commercial refrigerator, freezer, and refrigerator-freezer” 

means refrigeration equipment that— 

(i) is not a consumer product (as defined in section 321); 

(ii) is not designed and marketed exclusively for medical, scientific, or research 

purposes; 

(iii) operates at a chilled, frozen, combination chilled and frozen, or variable 

temperature;

(iv) displays or stores merchandise and other perishable materials horizontally, 

semivertically, or vertically; 

(v) has transparent or solid doors, sliding or hinged doors, a combination of 

hinged, sliding, transparent, or solid doors, or no doors; 

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(vi) is designed for pull-down temperature applications or holding temperature 

applications; and 

(vii) is connected to a self-contained condensing unit or to a remote condensing 

unit. 

(B) The term “holding temperature application” means a use of commercial 

refrigeration equipment other than a pull-down temperature application, except a 

blast chiller or freezer.

* * * 

(D) The term “pull-down temperature application” means a commercial 

refrigerator with doors that, when fully loaded with 12 ounce beverage cans at 90 

degrees F, can cool those beverages to an average stable temperature of 38 

degrees F in 12 hours or less.

(E) The term “remote condensing unit” means a factory-made assembly of 

refrigerating components designed to compress and liquefy a specific refrigerant 

that is remotely located from the refrigerated equipment and consists of one or 

more refrigerant compressors, refrigerant condensers, condenser fans and motors, 

and factory supplied accessories.

(F) The term “self-contained condensing unit” means a factory-made assembly of 

refrigerating components designed to compress and liquefy a specific refrigerant 

that is an integral part of the refrigerated equipment and consists of one or more 

refrigerant compressors, refrigerant condensers, condenser fans and motors, and 

factory supplied accessories. 

(42 U.S.C. 6311(9)) 

EPACT 2005 does not explicitly define the terms “self-contained commercial 

refrigerator, freezer, or refrigerator-freezer” or “remote condensing commercial refrigerator, 

freezer, or refrigerator-freezer.” DOE interpreted these two terms to mean “commercial 

refrigerator, freezer, or refrigerator-freezer that is connected to a self-contained condensing unit” 

and “commercial refrigerator, freezer, or refrigerator-freezer that is connected to a remote 

condensing unit,” respectively. 

Accordingly, the four categories of equipment covered under this rulemaking are as 

follows. 

1. Self-contained refrigerators, freezers, and refrigerator-freezers: EPCA defines a 

“self-contained condensing unit,” in part, as “an integral part of the refrigerated 

equipment.” (42 U.S.C. 6311(9)(F)) Under the definitions quoted above, a selfcontained commercial refrigerator, freezer, or refrigerator-freezer is a category of 

commercial refrigeration equipment in which the refrigerated cabinet and the 

condensing unit are integrated into one unit. Self-contained commercial refrigeration 

equipment is primarily used for storing, displaying, and/or merchandising food 

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products in small to medium-sized grocery and other food retail stores, restaurants 

and hotels, and in cafeteria-style foodservice venues. EPACT 2005 prescribed energy 

conservation standards for self-contained commercial refrigerators, freezers, and 

refrigerator-freezers with doors. For self-contained commercial refrigerators, freezers, 

and refrigerator-freezers without doors, DOE established energy conservation 

standards in DOE’s 2009 commercial refrigeration equipment final rule. 74 FR 1092 

(Jan. 9, 2009). 

2. Remote condensing commercial refrigerators, freezers, and refrigeratorfreezers: Under the definitions presented above, a remote condensing refrigerator, 

freezer, or refrigerator-freezer is a type of commercial refrigeration equipment that is 

connected to a remote condensing unit. Remote condensing commercial refrigeration 

equipment is generally used to display and merchandise food products in large retail

installations like supermarkets and grocery stores. EPCA defines a “remote 

condensing unit,” in part, as being “remotely-located from the refrigerated 

equipment.” (42 U.S.C. 6311(9)(F)) DOE concluded during the 2009 rulemaking that 

the difference in language from the definition of “self-contained condensing unit” 

described above means that a remote condensing unit is not a part of the refrigerated 

equipment. 74 FR at 1104–1105 (Jan. 9, 2009). Therefore, in the 2009 final rule DOE 

adopted energy conservation standards for remote condensing commercial 

refrigerators, freezers, and refrigerator-freezers that apply to the refrigerated 

equipment, but not the remote condensing units. 

3. Self-contained commercial refrigerators designed for pull-down temperature 

applications: EPCA defines “pull-down temperature application” to mean “a 

commercial refrigerator with doors that, when fully loaded with 12 ounce beverage 

cans at 90 degrees F, can cool those beverages to an average stable temperature of 38 

degrees F in 12 hours or less.” (42 U.S.C. 6311(9)(D)) Units fitting this description 

are typically known as beverage merchandisers or beverage coolers because of their 

use in displaying individually packaged beverages for sale. Even though this 

equipment has a similar configuration to self-contained refrigerators with transparent 

doors, EPCA prescribed separate standards for pull-down refrigerators with 

transparent doors. (42 U.S.C. 6313(c)(3)) Correspondingly, DOE intends to keep this 

equipment as a separate class in this rulemaking. Additionally, DOE notes that EPCA 

does not currently contain a standard for self-contained commercial refrigerators for 

pull-down temperature applications with solid doors or for equipment operating at 

other temperatures. 

 

4. Commercial ice-cream freezers: On December 8, 2006, DOE published a final rule 

in which it adopted test procedures for commercial refrigeration equipment. In this 

final rule, DOE adopted the following definition for “ice-cream freezer”: “a 

commercial freezer that is designed to operate at or below -5 °F (-21 °C) and that the 

manufacturer designs, markets, or intends for the storing, displaying, or dispensing of 

ice cream.” 10 CFR 431.62, 71 FR at 71340, 71369. In addition, this final rule 

prescribed a rating temperature of -15°F for ice-cream freezers. 10 CFR 431.64, 71 

FR at 71370 (Dec. 8, 2006). Under this definition, unless equipment is designed, 

3-3 
marketed, or intended specifically for the storage, display, or dispensing of ice cream, 

it would not be considered an “ice-cream freezer.” Multi-purpose commercial 

freezers, manufactured for storage and display, for example, of frozen foods as well 

as ice cream would not meet this definition, and DOE would not treat them as 

commercial ice-cream freezers in this rulemaking. This is in accordance with the 

comments DOE received during the 2009 rulemaking that indicated that DOE should 

not classify such freezers as ice-cream freezers. 74 FR at 1103 (Jan. 9, 2009). On the 

other hand, any commercial freezer that is specifically manufactured for storing, 

displaying, or dispensing ice cream, and that is designed so that in normal operation it 

can operate at or below -5 °F (-21 °C), would meet the definition. This includes 

equipment that some interested parties referred to as true ice-cream cabinets—

freezers that are designed to operate considerably below -5 °F (sometimes referred to 

as “hardening” cabinets) and are specifically designed for ice cream storage, for 

example—as well as those ice-cream dipping cabinets that are designed to operate 

below -5 °F. 

3.2 MARKET ASSESSMENT

The following market assessment identifies the manufacturer trade association, domestic 

manufacturers of commercial refrigeration equipment, manufacturer market share, regulatory 

programs, and non-regulatory initiatives; defines equipment classes; provides historical shipment 

data, shipment projections, and equipment lifetime estimates; and summarizes market 

performance data.

3.2.1 Trade Association 

The Air-Conditioning, Heating, and Refrigeration Institute (AHRI, formerly the AirConditioning and Refrigeration Institute, or ARI, before merging with the Gas Appliance 

Manufacturers Association, or GAMA, to form AHRI) is the most prominent trade association 

for commercial refrigeration equipment manufacturers. On January 12, 2005, ARI developed an 

agreement with member manufacturers to establish the Commercial Refrigerator Manufacturers 

Division (CRMD) within ARI and to develop and implement a certification program for 

commercial refrigerators, commercial freezers, and commercial refrigerator-freezers.

The CRMD was originally a separate trade organization founded in 1933. It serves 

supermarkets, food stores, convenience stores, restaurants, hotels, motels, food processing 

establishments, and hospitals. The technical activities of CRMD include: 

• harmonization of international equipment standards; 

• development of industry performance standards for commercial refrigeration 

equipment; 

• updating of industry guidelines for retail store fixture installation, design, energy 

conservation, electronic case controls, and specifications for equipment installation;

• communicating with refrigerant suppliers and government agencies about 

environmentally acceptable refrigerants; and

• providing input to government agencies concerning regulations affecting the industry. 

3-4 
3.2.2 Manufacturers and Market Share

Current AHRI CRMD members are listed below; parent companies are shown in 

parentheses if applicable.

1

• Continental 

Refrigerator

• Hussmann (Ingersoll 

Rand)

• Southern Store 

Fixtures

• CSC Worldwide

(formerly Columbus 

Showcase)

• Killion Industries • Structural Concepts 

Corp. 

• Hill Phoenix (Dover 

Corp.)

• Kysor/Warren (Enodis) • Zero Zone

• Hoshizaki America, 

Inc.

• Master-Bilt Products 

(Standex)

Other commercial refrigeration equipment manufacturers are listed below; parent 

companies are shown in parentheses if applicable.

• Amtekco • Howard/McCray • Tor Rey Refrigeration

• Arctic Air • Kelvinator (Electrolux) • Traulsen

• Arctic Star • McCall Refrigeration

(Manitowoc Food 

Service)*

• True Manufacturing

• Arneg USA • Northland Refrigeration • Turbo Air

• Beverage-Air* • Regal-Pinnacle • Victory Refrigeration

• Custom Deli • Royal Store Fixtures 

(Parisi)

• Vogel

• Custom Fabricators • Spartan Showcase

• Delfield (Manitowoc 

Food Service)*

• Silver King

*Current AHRI member

According to Appliance Magazine, which most recently published market share data for 

refrigerated display cases in 2005, four companies represented approximately 85 percent of the 

U.S. refrigerated display case market, with about 185,000 units shipped in 2004.2 However, 

Appliance Magazine provides no precise definition of a refrigerated display case and it is 

therefore unclear what specific types of equipment the data covers—whether it is equipment that 

is self-contained or remote condensing, or equipment with doors or without doors. 

As of 2004, Hussmann Corporation, a division of Ingersoll Rand, was the largest 

domestic manufacturer of refrigerated display cases according to the Appliance Magazine data, 

holding approximately 48 percent of the U.S. market (Figure 3.2.1). 

3-5 
Source: Appliance Magazine, “28th Annual Portrait of the U.S. Appliance Industry,” September 2005.

Figure 3.2.1 Domestic Refrigerated Display Case Market Shares as of 2005 

Manufacturers in the “Other” category (in Figure 3.2.1) are listed below; parent 

companies are listed in parenthesis if applicable. 

• Arneg USA • Master-Bilt Products 

(Standex)

• Structural 

Concepts Corp.

• CSC Worldwide • Regal-Pinnacle • True 

Manufacturing

• Federal Industries 

(Standex)

• Royal Store Fixture (Parisi) • Turbo Air

• Howard/McCray • Southern Store Fixtures • Zero Zone

• Killion Industries • Spartan Showcase

The landscape of the commercial refrigeration equipment market has changed since this 

data was collected in 2005. For example, Tyler Refrigeration no longer exists independently, and 

consolidation has occurred with large-market share companies having made acquisitions in the 

time since this data was collected. DOE has additional information regarding the commercial 

refrigeration equipment market share by company, but since that data was obtained from 

purchased reports that are not publicly available, DOE is not presenting that information in this 

technical support document (TSD). 

Appliance Magazine also publishes data regarding market share for “commercial 

refrigerators.” As is the case with refrigerated display cases, Appliance Magazine does not 

provide a precise definition of what a commercial refrigerator is. It is therefore unclear what 

specific types of equipment that data covers—whether it is equipment that is self-contained or 

remote condensing, or equipment with doors or without doors. 

According to Appliance Magazine, which most recently published new data on the 

market share of commercial refrigerators in September 2009, seven companies comprised 78 

Tyler Refrigeration

16%

Hill Phoenix

15%

Kysor/Warren

6%

Other

15%

Hussmann

48%

3-6 
percent of the U.S. commercial refrigerator market as of 2008. Of these, True Manufacturing 

represented the largest market share, with 41 percent. The additional six named companies 

comprised 37 percent of the market, and other manufacturers comprised the remaining 22 

percent of the market (Figure 3.2.2). 

Source: Appliance Magazine, “32nd Annual Portrait of the U.S. Appliance Industry,” September 2009. 

Figure 3.2.2 Domestic Commercial Refrigerator Market Share as of 2008 

Manufacturers in the “Other” category (in Figure 3.2.2) are listed below; parent 

companies are listed in parentheses if applicable. 

• Arctic Air • Hoshizaki America, Inc. • Silver King

• Arctic Star • Hussmann (Ingersoll 

Rand)

• Structural Concepts 

Corp.

• CSC Worldwide • Kelvinator • Tor Rey 

Refrigeration

• Custom Deli • Kysor/Warren (Enodis) • Turbo Air

• Custom Fabricators • Master-Bilt Products 

(Standex)

• Victory Refrigeration

• Hill Phoenix (Dover 

Corp.)

• McCall Refrigeration • Zero Zone

3.2.2.1 Small Businesses

DOE is considering the possibility that energy conservation standards for commercial 

refrigeration equipment would adversely affect small businesses. The Small Business 

Administration (SBA) defines small business manufacturing enterprises for commercial 

refrigeration equipment as those having 750 employees or fewer.3 SBA lists small business size 

standards for industries as they are described in the North American Industry Classification 

System (NAICS). The size standard for an industry is the largest size that a for-profit company

can have in that industry and still qualify as a small business for Federal Government programs.

These size standards are generally expressed in terms of the average annual receipts or the 

True

41%

Traulsen

Victory 9%

10%

Beverage 

Air

6%

Delfield

7%

Continental

4%

Northland

1%

Other

22%

3-7 
average employment of a firm. For commercial refrigeration equipment, the size standard is 

matched to NAICS code 333415, Air-Conditioning and Warm Air Heating Equipment and 

Commercial and Industrial Refrigeration Equipment Manufacturing. 

DOE studied the potential impacts on these small businesses in detail during the 

manufacturer impact analysis, which was conducted as a part of the notice of proposed 

rulemaking (NOPR) analysis. DOE identified a number of commercial refrigeration equipment 

manufacturers that qualify as small businesses, which are listed below; parent companies are 

listed in parentheses if applicable.

• Admiral Craft • Killion Industries

• Amtekco • MaxxCold

• Arctic Air • Northland Refrigeration

• Arctic Star • Regal-Pinnacle

• Ascend Mfg. • Royal Store Fixture (Parisi)

• Beverage Air • Saturn Equipment

• Blue Air Commercial Refrigeration • Silver King

• ColdTech USA • Southern Store Fixtures

• Continental Refrigerator • Spartan Showcase

• CSC Worldwide • Structural Concepts Corp.

• Everest Refrigeration • Summit Commercial

• Fagor Refrigeration • Tor Rey Refrigeration

• Fogel USA • Utility Refrigerator

• Global Refrigeration • Victory Refrigeration

• Howard/McCray • Zero Zone

3.2.3 Regulatory Programs

Outside of the United States, Canada and Australia have efficiency standards for 

commercial refrigeration equipment. Additionally, the following states have established 

appliance efficiency regulations in the past: Arizona, California, Connecticut, Maryland, 

Massachusetts, Minnesota, New Jersey, New York, Oregon, Rhode Island, Vermont, and 

Washington. Of these, California is the only state that explicitly regulated all types of 

commercial refrigerators, freezers, and refrigerator-freezers with past state standards. Arizona, 

Oregon, Rhode Island, Connecticut, Maryland, New Jersey, New York, and Washington 

regulated certain types of commercial refrigeration equipment. Many of these standards have 

since been pre-empted by the Federal standards for self-contained equipment with doors set forth 

in EPACT 2005 and effective January 1, 2010. The documents that set forth individual state 

appliance efficiency standards can be accessed via the Database of State Incentives for 

Renewables & Efficiency (DSIRE), a DOE-funded online database.4

 

3.2.3.1 Natural Resources Canada 

The Natural Resources Canada (NRCan) Office of Energy Efficiency has energy

efficiency standards for commercial refrigerators, freezers, and refrigerator-freezers. A May 

2010 NRCan bulletin proposed standards for self-contained equipment without doors, equipment 

3-8 
with remote condensing units, and commercial ice cream freezers. These changes also serve to 

align the standards with those in the United States.

5 The test method for determining compliance 

is AHRI Standard 1200-2008, Performance Rating of Commercial Refrigerated Display 

Merchandisers and Storage Cabinets, with the following specifications for the integrated 

average temperature (IAT): 

• Refrigerator compartment: 38°F ± 2°F (3.3oC ± 1.1oC) 

• Freezer compartment: 0°F ± 2°F (-17.8oC ± 1.1oC) 

• Wine chiller: 45°F ± 2°F (7.2oC ± 1.1oC) 

• Ice-cream cabinet: -5°F ± 2°F (-20.6oC ± 1.1oC) 

3.2.3.2 Canadian Standards Association

The Canadian Standards Association (CSA) is an independent standards-setting agency 

that establishes test procedures and efficiency standards that the Canadian government typically 

adopts. The Canadian standard CAN/CSA C657-04, Energy Performance Standard for 

Refrigerated Display Cabinets (Merchandisers), applies to remote condensing commercial 

equipment with and without doors, and self-contained commercial equipment with and without 

doors, except as covered by CSA C827-10. Commercial refrigerators and commercial freezers 

with doors (including commercial ice-cream freezers) are covered in a separate test procedure 

and standard, CSA C827-10, Energy Performance Standard for Food Service Refrigerators and 

Freezers. This standard is a revision of the original CSA standard published in 1995. Among the 

changes are redefined equipment categories and new minimum energy performance standards 

(MEPS).

a

 

The CSA C657-04 standard divides commercial refrigeration equipment into seven 

classes and several sub-classes. Table 3.2.1 summarizes classes and MEPS levels from CSA 

C657-04. For equipment with a remote condensing unit, the MEPS use a pre-determined remote 

condensing unit efficiency to calculate daily energy use. 

Table 3.2.1 Canadian Standards Association Equipment Classes and Efficiency Ratings 

Class IAT*

°F Temperature Open/Closed Deck

Number of 

Air 

Curtains

Angle of Air 

Curtain 

from 

Vertical

MEPS

2004

kWh/ft

per day

1 41.0 Medium Open Single/Multi 1 0-30° 4.0

2 41.0 Medium Open Single/Multi 1 30-60° 2.9

3 41.0 Medium Open Single/Multi 1 60-90° 1.6

4 0.0 Low Open Multi 2 or 3 0-30° 9.4

5 0.0 Low Open Single 1 60-90° 4.6

6a 41.0 Low/Medium Closed Multi Single Vent with Glass 2.3

6b 0.0 Same as 6a 6.1

7a 41.0 Medium Closed Single/Multi Glass N/A 2.6

7b 41.0 Same as 7a, except with only a gravity coil (no fan coil) 1.0

Source: CSA C657-04, Energy Performance Standard for Refrigerated Display Cabinets (Merchandisers).

* IAT = the average temperature of all test packages recorded during testing.

a Changes to the standard make it extremely difficult to compare levels between the 1995 and updated standards. 

3-9 

 
3.2.3.3 Australia

Australia has required efficiency standards for commercial refrigeration equipment since

October 1, 2004.6

 The standards apply to both remote condensing and self-contained commercial 

equipment used to store chilled and frozen food. The MEPS are established in Australian 

Standard (AS) 1731.14-2003 as total energy consumption per total display area (TEC/TDA) in 

kilowatt-hours per day per square meter for various equipment types. The Australian standards 

categorize equipment by the following criteria:

• remote or self-contained condensing unit 

• lit shelves or unlit shelves 

• number of shelves 

• solid door or glass door 

• fan coil or gravity coil 

• high, medium, or low temperature 

The standards also specify minimum energy performance by M-package temperatures 

(temperature of a load package) for self-contained cabinets. AS 1731-2003 specifies the test 

procedures used to measure energy consumption. 

3.2.4 Non-Regulatory Initiatives

DOE reviewed several voluntary programs promoting energy efficient commercial 

refrigeration equipment in the United States, including the ENERGY STAR® program for 

commercial refrigerators and commercial freezers, the Consortium for Energy Efficiency (CEE) 

initiative for commercial refrigeration equipment, and the Federal Energy Management Program 

(FEMP) procurement program for energy efficient commercial refrigerators and commercial 

freezers. DOE also reviewed various rebate programs offered by utilities.

3.2.4.1 ENERGY STAR

The ENERGY STAR labeling program has a specification, in version 2.0 as of April 

2009, for self-contained solid and glass door commercial refrigerators and commercial freezers.

7

This program does not apply to remote condensing commercial equipment or self-contained 

commercial equipment without doors. The ENERGY STAR version 2.0 specification criteria for 

commercial equipment list the maximum energy consumption as follows. 

3-10
Table 3.2.2 ENERGY STAR Commercial Refrigerator and Freezer Key Criteria

Product Volume (in cubic feet)* Refrigerator Freezer

Vertical Configuration

Solid Door Cabinets

0 < V < 15 <= 0.089V + 1.411 <= 0.250V + 1.250

15 <= V < 30 <= 0.037V + 2.200 <= 0.400V - 1.000

30 <= V < 50 <= 0.056V + 1.635 <= 0.163V + 6.125

50 <= V <= 0.060V + 1.416 <= 0.158V + 6.333

Glass Door Cabinets

0 < V < 15 <= 0.118V + 1.382 <= 0.607V + 0.893

15 <= V < 30 <= 0.140V + 1.050 <= 0.733V - 1.000

30 <= V < 50 <= 0.088V + 2.625 <= 0.250V + 13.500

50 <= V <= 0.110V + 1.500 <= 0.450V + 3.500

Chest Configuration

Solid or Glass Door Cabinets <= 0.125V + 0.475 <=0.270V + 0.130

*V = Association of Home Manufacturers (AHAM) volume in cubic feet

In addition to the scope of coverage, there are several notable differences between the 

ENERGY STAR criteria and those currently used by DOE. For one, ENERGY STAR uses the 

American National Standards Institute/American Society of Heating, Refrigerating and AirConditioning Engineers (ANSI/ASHRAE) Standard 72-2005, Method of Testing Commercial

Refrigerators and Freezers, as the sole method of test. As ASHRAE Standard 72-2005 

incorporates the same rating temperatures as DOE for refrigerators and freezers and is the same 

test method referenced in AHRI Standard 1200 for self-contained refrigerators and freezers, this 

difference is nominal and does not impact the test result. The ENERGY STAR criteria also

specify ANSI/AHAM HRF-1-2004 for measuring internal volume. The ENERGY STAR criteria 

also differ from DOE’s existing standards in the treatment of energy management devices and in 

the definition of door type (solid or transparent) based on percentage of transparent area. 

3.2.4.2 Consortium for Energy Efficiency

The CEE has a Commercial Kitchen Initiative, which encourages equipment purchasers 

to buy more efficient commercial refrigeration equipment and directs them toward other rebate 

programs for which these purchases may qualify them. The CEE program applies to solid door 

and glass-door reach-in commercial refrigerators and commercial freezers.8

 This program is 

based on ENERGY STAR version 2.0 standard levels, as listed in Table 3.2.2, and applies to 

self-contained commercial equipment with doors. The program specifies standard levels in terms 

of maximum daily energy use in kilowatt-hours per day for various door types for both vertical 

and horizontal equipment. 

3.2.4.3 Federal Energy Management Program

FEMP is a program administered by DOE that oversees the Federal Government’s energy 

management and investment initiatives. FEMP has established purchasing specifications for 

energy efficient equipment, including commercial refrigeration equipment, which Federal 

agencies must follow when buying new equipment for their facilities.

9 Federal purchasers are 

required by EPACT 2005 to purchase equipment that is either ENERGY STAR qualified or 

FEMP designated. The FEMP designated equipment consists of equipment that is in the upper 25 

percent of energy efficiency in its class.

3-11
3.2.4.4 Rebate Programs

Numerous organizations and entities throughout the United States offer rebate programs 

for customers who purchase and install qualified commercial refrigeration equipment. Most of 

these incentive programs are accessible through the DSIRE online database. DSIRE lists all 

available incentives, including those offered by states, municipalities, utility companies, and the 

Federal government. This includes numerous incentives for purchasers of commercial 

refrigeration equipment units that meet specific criteria. While many entities offer rebates for 

commercial refrigeration equipment, most of which can be found on the DSIRE website, some 

are listed below as examples. 

Efficiency Vermont, an organization offering technical assistance and financial incentives 

to encourage energy efficiency in Vermont, offers rebates for the installation of commercial 

refrigeration equipment that exhibits certain performance or design characteristics. These rebates 

include $100 for zero-energy transparent doors, $150 for light-emitting diode (LED) refrigerated 

display case light fixtures, and $6 per linear foot of display case strip curtains and continuous 

covers.10

The EnergySmart Grocer Program is funded by California utility ratepayers under the 

auspices of the California Public Utilities Commission. Eligible participants include grocery and 

convenience stores, food processors, and refrigerated warehouses operating in the Pacific Gas 

and Electric Company (PG&E) electric service territory. The program offers rebates for use of 

specific technologies on commercial equipment such as night covers on equipment without 

doors, upgrades to more efficient case lighting, anti-sweat heater controls, improved reach-in 

door gaskets, and electronically commutated permanent magnet (ECM) motors. Additionally, the 

program provides rebates to end users who replace older equipment with new high-efficiency 

equipment.11

NV Energy offers incentives promoting the installation of energy efficient commercial 

refrigeration equipment through the Nevada Sure Bet Program. These rebates are available to the 

utility’s commercial, industrial, and institutional customers and are based on qualifying 

equipment from the ENERGY STAR program. Additionally, the program offers rebates for the 

installation of specific technologies, such as $4 per linear foot for the installation of night covers 

on commercial refrigeration equipment without doors and $30 per motor for the installation of 

ECM motors in refrigerated cases.

12

Otter Tail Power Company offers rebates to Minnesota commercial customers under the 

Conservation Improvement Program. Under this program, customers are eligible to receive 

between $20 and $40 per linear foot of, or upgrade to, high-efficiency commercial refrigeration 

equipment, among other rebate offers.

13

3.2.5 Equipment Classes

Commercial refrigeration equipment can be divided into various equipment classes 

categorized by physical characteristics that affect equipment efficiency. Most of these 

characteristics affect the kind of merchandise that the equipment can be used to display and 

determine how the customer can access that merchandise. Key physical characteristics are the 

3-12
operating temperature, the presence or absence of doors (closed cases or open cases), the type of 

doors used (transparent or solid), the angle of the door or air curtain (horizontal, semivertical, or 

vertical), and the type of condensing unit (remote condensing or self-contained). The following 

list shows the key characteristics of commercial refrigeration equipment that DOE developed as 

part of the 2009 final rule and identified in the Framework document and preliminary analysis 

for this rulemaking: 

1. Operating temperature

• Medium temperature (38 °F rating temperature, refrigerators)

• Low temperature (0 °F rating temperature, freezers)

• Ice-cream temperature (-15 °F rating temperature, ice-cream freezers)

2. Door type

• Equipment with transparent doors 

• Equipment with solid doors 

• Equipment without doors 

3. Orientation (air-curtain or door angle) 

• Horizontal 

• Semivertical

• Vertical 

4. Type of condensing unit 

• Remote condensing 

• Self-contained

Additionally, because this rulemaking covers equipment for which standards were set in 

the EPACT 2005 legislation, DOE has included a separate class for commercial refrigerators 

with transparent doors for pull-down temperature applications. The inclusion of this equipment 

as a separate class reflects the distinction that was made in the EPACT 2005 standards, which set 

specific standards for this type of equipment separate from the standards for other commercial 

refrigerators with transparent doors. DOE expressed its plans to include this equipment in the 

form of a separate family with a single class, and this was included in the May 2010 Framework 

document and March 2011 preliminary analysis. In response to stakeholder feedback, DOE has 

retained this designation in the NOPR. 

Table 3.2.3 shows the nine commercial refrigeration equipment families DOE has 

considered within the scope of this rulemaking. 

3-13
Table 3.2.3 Commercial Refrigeration Equipment Families

Equipment Family Designation Description

Vertical Open VOP Equipment without doors and an air-curtain angle ≥ 0° and < 10°

Semivertical Open SVO Equipment without doors and an air-curtain angle ≥ 10° and 

< 80°

Horizontal Open HZO Equipment without doors and an air-curtain angle ≥ 80°

Vertical Closed Transparent VCT Equipment with hinged or sliding transparent doors and a door 

angle < 45°

Vertical Closed Solid VCS Equipment with hinged or sliding solid (opaque) doors and a 

door angle ≥ 45°

Horizontal Closed Transparent HCT Equipment with hinged or sliding transparent doors and a door 

angle < 45°

Horizontal Closed Solid HCS Equipment with hinged or sliding solid (opaque) doors and a 

door angle ≥ 45°

Service Over Counter SOC Equipment with sliding or hinged doors intended for use by sales 

personnel and fixed or hinged glass for displaying merchandise

Pull-Down* PD* Commercial refrigerators with transparent doors for pull-down

temperature applications

*This equipment family is only applicable to PD.SC.M

The first eight equipment families contain equipment that can have one of two 

condensing unit types and one of three operating temperatures. The ninth family, pull-down 

equipment, contains only a single class as defined by EPACT 2005. The condensing unit type 

has a significant impact on utility and energy use, and can be either remote condensing (RC) or 

self-contained (SC). Remote condensing equipment is typically more efficient on a normalized 

basis than self-contained equipment because of economies of scale incurred in the use of large, 

multiplex compressor rack systems that feed multiple units. Remote condensing equipment 

cannot be easily relocated, due to the refrigerant piping attachments, whereas self-contained 

equipment is more mobile, generally requiring only an electrical outlet for operation. 

The operating temperature of the equipment also has a significant impact on utility and 

energy use. DOE has specified operating temperature classes of medium (M), low (L) or icecream (I), representing rating temperatures (or IAT) of 38 °F, 0 °F, or -15 °F, respectively 

(± 2 °F). Because different types of merchandise require different temperatures (e.g., chilled 

versus frozen), operating temperature is a necessary distinction. Also, the larger temperature 

differences and thermodynamic behavior of refrigerants means that equipment with lower 

operating temperatures runs less efficiently than equipment with higher operating temperatures.

For open cases, “vertical” represents an air-curtain angle of < 10° from the vertical, 

“semivertical” represents an air-curtain angle of ≥ 10° and < 80° from the vertical, and 

“horizontal” represents an air-curtain angle of ≥ 80° from the vertical. DOE developed a 

definition for air-curtain angle as part of the January 2009 final rule analysis: 

(1) For equipment without doors and without a discharge air grille or discharge air 

honeycomb, the angle between a vertical line extended down from the highest 

point on the manufacturer’s recommended load limit line and the load limit line 

3-14
itself, when the equipment is viewed in cross- section; and (2) For all other 

equipment without doors, the angle formed between a vertical line and the straight 

line drawn by connecting the point at the inside edge of the discharge air opening 

with the point at the inside edge of the return air opening, when the equipment is 

viewed in cross-section. 

Using all combinations of equipment family, operating mode, and temperature for the 

first eight families, plus the self-contained medium-temperature pull-down class, 49 equipment 

classes are possible, as illustrated in Table 3.2.4. DOE developed a lettering system in the 2009 

rulemaking to simplify discussion of equipment classes, and has retained that system in this 

rulemaking. The lettering designation for a particular equipment class consists of the 

abbreviations for the equipment family, operating mode, and temperature, separated by periods.

Table 3.2.4 shows a complete list of equipment classes with lettering designations organized by 

family, operating mode, and temperature.

3-15
Table 3.2.4 Commercial Refrigeration Equipment Classes

Equipment Family

Equipment

Family

Designation

Sample 

Equipment

Family Image

Operating 

Mode

Designation

Temperature

Designation

Equipment Class 

Designation

Vertical Open VOP

RC 

M (38 °F) VOP.RC.M

L (0 °F) VOP.RC.L

I (-15 °F) VOP.RC.I

SC

M (38 °F) VOP.SC.M

L (0 °F) VOP.SC.L

I (-15 °F) VOP.SC.I

Semivertical Open SVO

RC 

M (38 °F) SVO.RC.M

L (0 °F) SVO.RC.L

I (-15 °F) SVO.RC.I

SC

M (38 °F) SVO.SC.M

L (0 °F) SVO.SC.L

I (-15 °F) SVO.SC.I

Horizontal Open HZO

RC 

M (38 °F) HZO.RC.M

L (0 °F) HZO.RC.L

I (-15 °F) HZO.RC.I

SC

M (38 °F) HZO.SC.M

L (0 °F) HZO.SC.L

I (-15 °F) HZO.SC.I

Vertical Closed 

Transparent VCT 

RC 

M (38 °F) VCT.RC.M

L (0 °F) VCT.RC.L

I (-15 °F) VCT.RC.I

SC

M (38 °F) VCT.SC.M

L (0 °F) VCT.SC.L

I (-15 °F) VCT.SC.I

Vertical Closed Solid VCS 

RC 

M (38 °F) VCS.RC.M

L (0 °F) VCS.RC.L

I (-15 °F) VCS.RC.I

SC

M (38 °F) VCS.SC.M

L (0 °F) VCS.SC.L

I (-15 °F) VCS.SC.I

Horizontal Closed 

Transparent HCT

RC 

M (38 °F) HCT.RC.M

L (0 °F) HCT.RC.L

I (-15 °F) HCT.RC.I

SC

M (38 °F) HCT.SC.M

L (0 °F) HCT.SC.L

I (-15 °F) HCT.SC.I

Horizontal Closed 

Solid HCS

RC 

M (38 °F) HCS.RC.M

L (0 °F) HCS.RC.L

I (-15 °F) HCS.RC.I

SC

M (38 °F) HCS.SC.M

L (0 °F) HCS.SC.L

I (-15 °F) HCS.SC.I

Service Over Counter SOC

RC 

M (38 °F) SOC.RC.M

L (0 °F) SOC.RC.L

I (-15 °F) SOC.RC.I

SC

M (38 °F) SOC.SC.M

L (0 °F) SOC.SC.L

I (-15 °F) SOC.SC.I

Pull-Down PD SC M (38 °F) PD.SC.M

3-16
3.2.6 Shipments

This section presents the shipments data DOE obtained to conduct the NOPR analyses. 

DOE gathered data from ARI (submitted as part of the 2009 DOE rulemaking process), 

Freedonia Group, the North American Association of Food Equipment Manufacturers 

(NAFEM), Appliance Magazine, and the U.S. Census Bureau. 

3.2.6.1 ARI Data

As part of its comments on the Framework document for the 2009 rulemaking (Docket

No. EE-2006-STD-0126, ARI, No. 7, Exhibit B at p. 1), ARI submitted annual shipment data by 

equipment class for its member companies for the year 2005. DOE used this shipments data as 

part of the basis for this analysis, as newer shipments data were not available. DOE understands 

that this data does not include the entire industry because ARI did not represent all 

manufacturers at that time.

b However, because this data covered a significant portion of the 

commercial refrigeration equipment sold, and because no other detailed data was available at that 

time, the 2005 ARI shipments data was used as the total commercial refrigeration equipment 

shipments for the 2009 final rule, and has been incorporated as an input into the analyses for the 

current rulemaking. 

Table 3.2.5 shows 2005 annual shipments for each category of commercial refrigeration 

equipment by equipment class. The ARI data included shipments for equipment that operates at 

an “application” temperature (e.g., wine chillers that operate at 45 °F and freezers that operate at 

-30 °F). However, DOE only considered in its analyses shipments of equipment at the three 

temperatures used in this rulemaking (38 °F, 0 °F, and -15 °F; see section 3.2.5). The shipments 

of equipment that operate at one of these three temperatures constitute approximately 98 percent 

of the shipments that ARI reported. 

b Most notably, True Manufacturing, which DOE understands to have a large market share of self-contained 

equipment.

3-17

 
Table 3.2.5 ARI 2005 Shipments of Commercial Refrigerators and Freezers by Equipment

Class

Equipment

Family

Equipment

Family

Designation

Operating 

Mode

Designation

Temperature

Designation

Equipment Class 

Designation ARI Shipments*

Vertical Open VOP RC M (38 °F) VOP.RC.M 38,743

L (0 °F) VOP.RC.L 0

I (-15 °F) VOP.RC.I 0

SC M (38 °F) VOP.SC.M 6,512

L (0 °F) VOP.SC.L 0

I (-15 °F) VOP.SC.I 0

Semivertical Open SVO RC M (38 °F) SVO.RC.M 29,552

L (0 °F) SVO.RC.L 0

I (-15 °F) SVO.RC.I 0

SC M (38 °F) SVO.SC.M 9,750

L (0 °F) SVO.SC.L 0

I (-15 °F) SVO.SC.I 0

Horizontal Open HZO RC M (38 °F) HZO.RC.M 4,541

L (0 °F) HZO.RC.L 14,278

I (-15 °F) HZO.RC.I 0

SC M (38 °F) HZO.SC.M 838

L (0 °F) HZO.SC.L 1,738

I (-15 °F) HZO.SC.I 0

Vertical Closed 

Transparent

VCT RC M (38 °F) VCT.RC.M 2,767

L (0 °F) VCT.RC.L 38,483

I (-15 °F) VCT.RC.I 0

SC M (38 °F) VCT.SC.M 43,374

L (0 °F) VCT.SC.L 2,472

I (-15 °F) VCT.SC.I 1,898

Vertical Closed 

Solid

VCS RC M (38 °F) VCS.RC.M 49

L (0 °F) VCS.RC.L 2

I (-15 °F) VCS.RC.I 43

SC M (38 °F) VCS.SC.M 4

L (0 °F) VCS.SC.L 4,202

I (-15 °F) VCS.SC.I 470

Horizontal Closed 

Transparent

HCT RC M (38 °F) HCT.RC.M 0

L (0 °F) HCT.RC.L 15

I (-15 °F) HCT.RC.I 0

SC M (38 °F) HCT.SC.M 724

L (0 °F) HCT.SC.L 0

I (-15 °F) HCT.SC.I 9,056

Horizontal Closed 

Solid

HCS RC M (38 °F) HCS.RC.M 37

L (0 °F) HCS.RC.L 0

I (-15 °F) HCS.RC.I 0

SC M (38 °F) HCS.SC.M 39,761

L (0 °F) HCS.SC.L 4,109

I (-15 °F) HCS.SC.I 0

Service Over 

Counter

SOC RC M (38 °F) SOC.RC.M 9,312

L (0 °F) SOC.RC.L 9

I (-15 °F) SOC.RC.I 0

SC M (38 °F) SOC.SC.M 1,108

L (0 °F) SOC.SC.L 0

I (-15 °F) SOC.SC.I 0

Pull-Down PD SC M (38 °F) PD.SC.M N.A.**

* Source: Docket No. EE-2006-STD-0126, ARI, No. 7, Exhibit B at p. 1.

** Self-contained pull-down refrigerators with transparent doors were not explicitly addressed in the 2005 shipments data from ARI.

3-18
3.2.6.2 NAFEM Data

NAFEM publishes a biennial study of the foodservice equipment and supplies market. 

The latest available report is titled 2008 Size and Shape of the Industry Study.

14 It contains 

survey data from NAFEM members (not all members provided data for the report) including 

shipments numbers and the value of sales in dollars. Based on the numbers reported by the 

respondents to the survey, NAFEM developed a total market estimate of shipments (units 

shipped and dollar sales) for the year 2007. NAFEM also estimated the projected shipments for 

2008. NAFEM published similar study reports for shipments in 2006,15 2004,16 and 2002.17 

The “refrigeration and ice machine study” is part of the NAFEM reports and includes 

shipments data for under-counter, reach-in, pass-through, roll-in/roll-through refrigerators and 

freezers; air curtain refrigerators; milk coolers; and ice-cream cabinets, freezers, and dispensers 

(gelato equipment, dipping freezer/cabinets). Table 3.2.6 shows the DOE equipment classes to 

which the NAFEM equipment was assigned. Shipments numbers have been withheld from 

publication because the NAFEM reports are not publicly available documents. 

Table 3.2.6 NAFEM Shipments Categories and Corresponding DOE Equipment Classes

NAFEM Category Assigned DOE 

Equipment Class

Air curtains or air curtain refrigerators VOP.SC.M

Milk coolers VCS.SC.M

Under-counter refrigerators VCS.SC.M

Under-counter freezers VCS.SC.L

Reach-in/pass-through refrigerators VCS.SC.M,VCT.SC.M

Reach-in/pass-through freezers VCS.SC.L,VCT.SC.L

Roll-in/roll-through refrigerators VCS.SC.M

Roll-in/roll-through freezers VCS.SC.L

Ice-cream cabinets, freezers & dispensers

(gelato equipment, dipping freezers/cabinets)

HCT.SC.I,HCT.SC.L, 

HCS.SC.I

3.2.6.3 Freedonia Market Reports

The Freedonia Group published a study on the United States commercial refrigeration 

industry titled Commercial Refrigeration Equipment to 2014.

18 This report contains dollar values 

of commercial refrigeration equipment sales and in some cases shipments data in number of 

units. Shipments data are reported by market type (food and beverage retail, foodservice), 

equipment type (open and closed display case, reach-ins), and operating temperature (normal, 

low, and ice-cream temperatures). The report also presents the year-on-year percentage changes 

in total commercial refrigeration market from 1999 to 2009, which includes commercial 

refrigeration equipment used in food production and food distribution market sectors, and other 

equipment categories like beverage vending machines, walk-ins, liquid chillers, transportation 

systems, and refrigeration parts. Table 3.2.7 shows the classification of the Freedonia equipment 

categories into DOE product classes. Shipments numbers have been withheld from publication 

because Freedonia reports are not publicly available.

3-19
Table 3.2.7 Freedonia Shipments Categories and Corresponding DOE Equipment Classes

Freedonia Equipment Type 

Designation

Freedonia 

Operating 

Temperature

Designation

DOE Equipment Class(es)

Open self-service display 

cases

Normal VOP.RC.M,HZO.RC.M,SVO.RC.M

VOP.SC.M,SVO.SC.M,HZO.SC.M

Closed display cases Normal VCT.RC.M,VCT.SC.M

Open display cases Low VOP.RC.L,HZO.RC.L,SVO.RC.L

VOP.SC.L,HZO.SC.L,SVO.SC.L

Closed display cases Low VCT.RC.L,VCT.SC.L, 

SOC.RC.L,SOC.SC.L

Ice-cream freezer & other Ice-cream VCT.RC.I,VCT.SC.I,HCT.SC.I, 

HCT.SC.L

Reach-in refrigerators Normal VCS.SC.M

Reach-ins freezers Low VCS.SC.L

3.2.6.4 Appliance Magazine Data

Appliance Magazine publishes historical and forecasted shipments of refrigerated display 

cases, shown in Table 3.2.8 and Table 3.2.9.

c

 

Table 3.2.8 Historical Shipments of Refrigerated Display Cases

Year Unit Shipments

1999 340,453

2000 347,262

2001 175,000

2002 183,300

2003 191,549

2004 185,000

2005 177,000

2006 180,540

2007 184,000

2008 172,129

Source: Appliance Magazine, “56th Annual Statistical Review,” May 2009.

Table 3.2.9 Statistical Forecasts of Refrigerated Display Case Shipments

Year Unit Shipments

2009 152,000

2010 156,000

2011 162,000

2012 166,000

Source: Appliance Magazine, “58th Annual Appliance Industry Forecasts,” 

February 2010.

It is unclear what is responsible for the sharp decline in display case shipments between 

2000 and 2001 reported by Appliance Magazine. A similar decline is reported in other market 

literature.

19 DOE believes that some of the observed decline in shipments is the result of a 

general slowdown in the U.S. economy in the second and third quarters of 2001. Financial 

c As mentioned earlier, Appliance Magazine describes the data as representing refrigerated display cases but does 

not provide a precise definition of the equipment. It is unclear what types of equipment this term covers—whether it 

is equipment that is self-contained or remote condensing, or equipment with doors or without doors.

3-20

 
reports by commercial refrigeration equipment manufacturers discuss depressed investment and 

uncertainty in the retail food industry between 2000 and 2005 as contributing to low sales of 

commercial refrigeration equipment. There may be other explanations, including possible 

changes in what equipment Appliance Magazine included in its categorization of “refrigerated 

display cases.” 

Appliance Magazine also published historical and forecasted shipments of commercial 

refrigerators, shown in Table 3.2.10 and Table 3.2.11.

d

 

Table 3.2.10 Historical Shipments of Commercial Refrigerators

Year Unit Shipments

1999 233,750

2000 245,437

2001 260,000

2002 263,000

2003 268,000

2004 275,000

2005 289,000

2006 307,000

2007 309,375

Source: Appliance Magazine, “54th Annual Statistical Review,” May 2007, “31st

Annual Portrait of the U.S. Appliance Industry,” September 2008.

Table 3.2.11 Statistical Forecasts of Commercial Refrigerator Shipments

Year Unit Shipments

2009 270,455

2010 275,323

2011 280,830

Source: Appliance Magazine, “57th Annual Appliance Industry Forecasts,” 

January 2009.

Appliance Magazine appears to have stopped offering historical and forecast information 

on shipments of commercial refrigerators and display cases after 2010. Thus the information 

presented here reflects the latest available data from that source.

3.2.6.5 Census Bureau Data

The U.S. Census Bureau’s Economic Census of Manufacturing Industry Series publishes 

statistics on the quantity and value of shipments for those companies with shipments over 

$100,000 in value.20, 21, 22 There are eight categories for display cabinets and display cases, 

including reach-ins. These are sub-divided into reach-in, closed display, and open display. 

Table 3.2.12 shows shipment data for open refrigerated display cases, which include both 

self-contained units without doors and remote condensing units without doors. It is not possible 

d Similar to its treatment of refrigerated display cases, Appliance Magazine describes the data as representing 

commercial refrigerators, but does not provide a precise definition of the equipment. It is unclear what types of 

equipment this term covers—whether it is equipment that is self-contained or remote condensing, or equipment with 

doors or without doors.

3-21

 
to determine from Table 3.2.12 which shipments are for self-contained units and which are for 

remote condensing units since the census data reports these together. 

Table 3.2.12 Shipments of Open Refrigerated Display Cases (Remote Condensing and SelfContained)

Type Open or 

Closed Temperature Survey Year

Number of 

Companies with 

Sales Over 

$100,000

Shipment

Quantity

1,000s

Shipment 

Value

$1,000

Display Case

One Level

Open Normal 2007 15 (q)47.7 237,791

2002 6 - 89,622

1997 13 - 140,259

Display Case

Multi Level

Open Normal 2007 10 S 170,628

2002 9 - 341,472

1997 11 58.6 258,310

Display Case Open Frozen Food 2007 7 S 29,366

2002 6 - 11,538

1997 7 20.4 90,213

Source: U.S. Census, Economic Census, Manufacturing Industry Series 2007, 

http://factfinder.census.gov/servlet/DatasetMainPageServlet?_program=ECN&_tabId=ECN1&_submenuId=datasets_4&_lang=en; 

U.S. Census, Economic Census, Manufacturing Industry Series 1997, EC97M-3334D, www.census.gov/epcd/www/97EC31.HTM; 

U.S. Census, Economic Census, Manufacturing Industry Series 2002, EC02-31I-333415 (RV), www.census.gov/econ/census02. 

* S - Withheld because estimate did not meet publication standards

**(q) - 20–29 percent estimated

Table 3.2.13 shows shipment data for closed refrigerated display cases, which include 

both self-contained units with doors and remote condensing units with doors. It is not possible to 

determine from Table 3.2.13 which shipments are for remote condensing units and which are for 

self-contained condensing units. 

Table 3.2.13 Shipments of Closed Refrigerated Display Cases (Remote Condensing and 

Self-Contained)

Type Open or 

Closed Temperature Survey Year

Number of 

Companies with 

Sales Over 

$100,000

Shipment 

Quantity

1,000s

Shipment 

Value

$1,000

Display Case Closed Normal 2007 8 S 108,627

2002 11 - 50,601

1997 15 - 91,892

Cabinet Closed Frozen Food 2007 7 S 25,100

2002 8 - 20,618

1997 9 - 112,873

Other 

Display 

Cases

Not stated Low Temp. 2007 6 S D

2002 7 - 58,549

1997 6 - 43,150

Source: U.S. Census, Economic Census, Manufacturing Industry Series 2007, 

http://factfinder.census.gov/servlet/DatasetMainPageServlet?_program=ECN&_tabId=ECN1&_submenuId=datasets_4&_lang=en; 

U.S. Census, Economic Census, Manufacturing Industry Series 1997, EC97M-3334D, http://www.census.gov/epcd/www/97EC31.HTM; 

U.S. Census, Economic Census, Manufacturing Industry Series 2002, EC02-31I-333415 (RV), http://www.census.gov/econ/census02. 

* S - Withheld because estimate did not meet publication standards

** D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals

3-22
Table 3.2.14 shows shipment data for commercial reach-in (vertical) cabinets. These 

cabinets can have either solid or glazed doors. It is not possible to determine from Table 3.2.14

which shipments are for remote condensing units and which shipments are for self-contained 

units. 

Table 3.2.14 Shipments of Commercial Reach-In Cabinets (Remote Condensing and SelfContained)

Type Open or 

Closed Temperature Survey Year

Number of 

Companies with 

Sales Over 

$100,000

Shipment

Quantity

1,000s

Shipment 

Value

$1,000

Display 

Cabinets - Not 

for Frozen 

Foods

Not 

Specified

Normal 2007 21 S 655,800

2002 21 381.7 465,553

1997 29 - 439,081

Display 

Cabinet

Not 

Specified

Low 

Temperature

2007 11 S 341,136

2002 16 - 259,105

1997 24 - 307,605

Source: U.S. Census, Economic Census, Manufacturing Industry Series 2007, 

http://factfinder.census.gov/servlet/DatasetMainPageServlet?_program=ECN&_tabId=ECN1&_submenuId=datasets_4&_lang=en; 

U.S. Census, Economic Census, Manufacturing Industry Series 1997, EC97M-3334D, http://www.census.gov/epcd/www/97EC31.HTM; 

U.S. Census, Economic Census, Manufacturing Industry Series 2002, EC02-31I-333415 (RV), http://www.census.gov/econ/census02. 

*S - Withheld because estimate did not meet publication standards

In summary, although the U.S. Census Bureau data contain some limited shipments data 

that would be useful for conducting technical analyses, not enough detail is available to provide 

specific assessments for shipments within each of the primary categories covered in this 

rulemaking. 

3.2.7 Equipment Lifetimes

DOE reviewed available literature and consulted with experts on commercial 

refrigeration equipment to establish typical equipment lifetimes. The literature and individuals 

consulted estimated a wide range of typical equipment lifetimes, shown in Table 3.2.15. 

Individuals with experience in the manufacturing or distribution of commercial 

refrigeration equipment suggested a typical case life of 5 to 15 years. Experts in the field 

suggested that while the equipment is typically robust in design, much of the equipment is 

replaced for cosmetic reasons during store remodeling (typically every 10 years or so). One 

distributor suggested that U.S. tax depreciation schedules, which allow depreciation over a 5-

year period for retail fixtures, including commercial refrigerators and commercial freezers,23 are 

one driver for regular replacement of commercial refrigeration equipment in the United States.

Some literature suggested lifetimes of up to 20 years or more for commercial 

refrigeration equipment. Many of the studies cited here related to examination of environmental 

impacts of refrigerant emissions and therefore may not always clearly distinguish between the 

lifetime of the case and the lifetime of the compressor racks.24 However, available literature and 

consultation with experts in the field suggested that smaller, independently owned grocery stores 

were more likely to keep equipment longer than larger chain stores.

3-23
Several industry experts and stakeholders suggested during interviews and in public 

meetings that there is a significant used and refurbished equipment market. However, DOE did 

not determine the size of the used market relative to the new market. Those consulted generally 

agreed that the salvage value of used equipment was very low compared to the initial purchase 

price. This is due to both cosmetic concerns and the custom nature of much of the equipment. 

The difficulty in collecting used equipment of the same “look” for planned display case line-ups 

in retail stores was cited as another reason for the low price of used equipment. A survey in the 

Pacific Northwest reported that for small, independent grocery stores (< 20,000 square feet) and 

independently owned convenience stores, the fraction of owners who would consider purchase of 

refurbished equipment was 25 and 16 percent, respectively. For larger regional chains, this 

fraction was approximately 11 percent. None of the large grocery chains surveyed had plans to 

purchase refurbished equipment. See TSD chapter 8 and chapter 9 for the equipment lifetime 

values used in the LCC and shipments analyses.

Table 3.2.15 Estimates for Commercial Refrigeration Equipment Lifetimes

Life Reference

15 years Heshong Mahone Group 200425

5-7 years (large chains) Verisae 200626

15 years (smaller chains and independent grocers

may go up to 20 years)

Verisae 200627

7-15 years Mark Ellis & Associates 200328

15 years Foster-Miller 200129

15-20 years U.S. Environmental Protection Agency 200130

15 years Arthur D. Little 200231

9-10 years (9 years with doors, 10 years without 

doors)

CEC 200432

5-15 years (typically 10 years) Hansen 200633

10 years PG&E 20043

7-10 years (remote condensing)

8-12 years (self-contained)

Intergovernmental Panel on Climate Change 200134

7 years Fisher 199135

10-15 years Navigant Consulting, Inc. 200936

3.2.8 Market Performance Data

3.2.8.1 Remote Condensing Equipment

During the 2009 rulemaking, DOE conducted a survey of existing remote condensing

refrigerated equipment from major manufacturers and compiled a performance database based 

on available information. Information such as total refrigeration load, evaporator temperature, 

lighting power draw, defrost power draw, and motor power draw were used to analytically 

determine calculated daily energy consumption (CDEC) according to the methodology of AHRI

Standard 1200, Performance Rating of Commercial Refrigerated Display Merchandisers and 

Storage Cabinets.

This data was used to develop figures included in the market and technology assessment 

chapter of the 2009 final rule TSD showing the relationship between CDEC and TDA for the 

VOP.RC.M, SVO.RC.M, and HZO.RC.M classes, as well as a plot showing the relationship 

between air curtain angle and performance. Because the market baseline did not change between 

3-24
the 2009 final rule and the publication of the preliminary analysis TSD for the current 

rulemaking, DOE retained those figures in the preliminary analysis TSD chapter 3.

Since the publication of the preliminary analysis for the current rulemaking, the 

compliance date of the 2009 standards (January 1, 2012) has passed, altering the market baseline. 

DOE does not have sufficiently detailed information for specific equipment models to allow it to 

show similar plots representative of the current market. Based on discussions with 

manufacturers, DOE believes that many remote condensing equipment lines offer models at or 

near the baseline, with options to add higher-efficiency features upon customer request. 

3.2.8.2 Self-Contained Equipment

For self-contained equipment, market performance plots were developed for selected 

equipment classes based on rated test data for this equipment from publicly accessible sources. 

These included the California Energy Commission (CEC), and ENERGY STAR directories. The 

rated energy consumption values, capacities, and equipment types were used to produce market 

performance plots for self-contained equipment classes. However, because these directories are 

produced by different parties independent from DOE and are in some cases voluntary, the data 

contained within them does not always align exactly with the DOE equipment classes, nor does it 

necessarily reflect the entire range of efficiencies on the market within a given equipment class. 

For example, for some classes currently covered under a TDA-based standard, only volume 

information was available in these directories. Figure 3.2.3 through Figure 3.2.10 show energy 

use as a function of size for select self-contained equipment classes. 

Figure 3.2.3 Market Performance Data for the VOP.SC.M Equipment Class

3-25
Figure 3.2.4 Market Performance Data for the VCT.SC.M Equipment Class

Figure 3.2.5 Market Performance Data for the VCT.SC.L Equipment Class

3-26
Figure 3.2.6 Market Performance Data for the VCS.SC.M Equipment Class

Figure 3.2.7 Market Performance Data for the VCS.SC.L Equipment Class

3-27
Figure 3.2.8 Market Performance Data for the HCT.SC.M Equipment Class

Figure 3.2.9 Market Performance Data for the HCT.SC.L Equipment Class

3-28
Figure 3.2.10 Market Performance Data for the HCS.SC.M Equipment Class

3.3 TECHNOLOGY ASSESSMENT 

The purpose of the technology assessment is to develop a preliminary list of technologies 

that could potentially be used to improve the efficiency of commercial refrigeration equipment.

The following assessment provides descriptions of technologies and designs that apply to all 

equipment classes; designs that apply to equipment without doors only; and technologies and 

designs that apply to self-contained equipment only. 

3.3.1 Technologies and Designs Relevant to All Equipment Classes

The following technologies and designs are relevant to all equipment classes: higher 

efficiency lighting, higher efficiency lighting ballasts, remote ballast location, higher efficiency 

expansion valves, higher efficiency evaporator fan motors, variable-speed evaporator fan motors 

and evaporator fan motor controllers, higher efficiency evaporator fan blades, improved 

evaporator coil design, low-pressure differential evaporators, insulation increases or 

improvements, defrost mechanisms, defrost cycle control, vacuum insulated panels (VIPs), and 

occupancy sensors for lighting controls. 

3.3.1.1 Higher Efficiency Lighting 

Commercial refrigeration equipment often includes lighting to illuminate the contents.

Some commercial refrigeration equipment also includes an illuminated sign on the exterior of the 

unit. Higher efficiency lighting leads to energy savings in two ways: less energy is used directly 

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for lighting, and less heat energy is dissipated into the refrigerated case by the lamp. Efficiency 

in lighting is commonly measured as efficacy (lumens/watt), or the quantity of light output 

(lumens) per electrical energy input (watts, W).

During the time frame of the 2009 rulemaking, DOE found that the commercial 

refrigeration industry had begun using T8 fluorescent lighting in most cases. T8 lighting is 

substantially more efficacious than T12 lighting and is predominantly used with electronic 

ballasts, which are more efficient than the magnetic ballasts commonly used in T12 lighting. 

A significant trend in recent years has been the use of LED technology. Although LEDs 

currently on the market consume more energy per lumen of light output than fluorescents, they 

provide better directionality than linear fluorescent bulbs, allowing for greater control of the light 

output. The result is comparable product illumination with less total wattage. There have been 

recent advancements in LED efficacy and numerous large retailers have adopted LED 

technology. Research by the Lighting Resource Center indicates that consumers found lighting in 

display cases using LEDs desirable. 37 Every major display door manufacturer offers LED 

lighting as design option, and some are moving to make LEDs a standard feature on their doors. 

3.3.1.2 Higher Efficiency Lighting Ballasts 

Higher efficiency lighting ballasts reduce energy consumption by requiring less electrical 

power to operate and by reducing waste heat generation, which contributes to case heat load. 

Many illuminated display cases currently installed in supermarkets use fluorescent 

lighting with magnetic ballasts, which use inductance to modulate power flow to fluorescent 

lamps. Magnetic ballasts have significant electrical resistance losses. More recently, the market 

has moved toward the use of electronic ballasts, which use solid state electronics to modulate the 

power provided to fluorescent lamps. Electronic ballasts, which convert power at high frequency, 

have lower electrical resistance losses compared to magnetic ballasts, which operate at line 

frequency. Fluorescent lamps also operate more efficiently at the higher frequency provided by 

electronic ballasts. In addition to the direct reductions in electrical power consumption, heat 

generated by the lighting and the lighting ballast contribute to the case heat load, as both the 

lighting and ballasts are often located inside the refrigerated space. Increasing ballast efficiency

also reduces the case heat load, and thus the compressor load. DOE notes that LED lighting does 

not require independent lighting ballasts, as the LED emitters generally are powered by onboard 

drivers built into each fixture. 

3.3.1.3 Remote Lighting Ballast Location 

Because ballasts may be located apart from the fluorescent lamps they power, 

manufacturers could choose to place them within the display case cabinet but outside of the 

refrigerated space, reducing heat load and case energy consumption.

3.3.1.4 Higher Efficiency Expansion Valves 

Expansion valves are refrigerant metering devices that control the amount of refrigerant 

flowing to the evaporator coil. In doing so, they simultaneously decrease the temperature and 

pressure of the refrigerant, creating a cold liquid-vapor mixture. The low temperature of the 

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refrigerant leaving the expansion valve creates the driving force to move heat out of the 

refrigerated space and into the evaporator. 

The most basic type of expansion device is a capillary tube, which may be found in small 

self-contained commercial refrigeration equipment. The capillary tube is a long, thin piece of 

pipe that creates a pressure drop in the refrigerant through frictional losses. Capillary tubes must 

be sized to the particular application and cannot adjust for variations in load or ambient operating 

conditions. They are often oversized for worst-case conditions, and therefore may operate at 

reduced efficiency during normal operation. 

The thermostatic expansion valve (TXV) is common in remote condensing commercial 

refrigeration equipment. This device uses an orifice to reduce the pressure of the entering 

refrigerant and a sensing bulb to monitor and maintain the temperature of the superheated vapor 

leaving the evaporator. Because the TXV allows for some degree of adjustment of refrigerant 

expansion, it may be somewhat more efficient than the capillary tube device under varying 

conditions. 

The electronic expansion valve (EEV) is similar to the TXV, but uses an electronic 

control system to optimize refrigeration-system performance under all operating conditions. 

Because it does this with greater flexibility than a TXV allows, an EEV theoretically allows for 

increases in energy efficiency under varying conditions. However, as with the TXV, an EEV will 

likely not provide significant energy savings over a properly sized capillary tube or a TXV under 

fixed ambient conditions such as those used in the DOE test procedure. 

3.3.1.5 Higher Efficiency Evaporator Fan Motors 

Evaporator fan motors are fractional horsepower in size (generally on the order of 6-12 

watts), are responsible for moving air across the evaporator coil, and typically run at one speed. 

The manufacturer will match the motor size and blade design to the evaporator coil to meet the 

expected load on the case under most conditions. Higher efficiency evaporator fan motors reduce 

energy consumption by requiring less electrical power to generate motor shaft output power. 

Electric motors operate based on the interaction between a field magnet and a magnetic 

rotor. In a brushed motor, the field magnets are permanent magnets and the rotor is an 

electromagnet; the situation is reversed in a brushless motor. The electromagnetic interactions 

between these two magnets cause the rotor to rotate.

Single-phase motors, the simplest type of electric motor, suffer from a serious 

shortcoming. Single-phase motors only produce a rotating magnetic field when the rotor is 

rotating, and simply powering the electromagnet is therefore not sufficient to start such a motor. 

One of the most significant differences between different types of single-phase motors is the way 

in which they handle this start-up problem. 

Nearly all inexpensive fan motors are either shaded-pole or permanent split capacitor 

(PSC), and the same is true for baseline commercial refrigeration equipment fan motors (fan 

motors not marketed as “high efficiency”). In both cases, the electromagnet consists of windings 

of electrical wire through which current is driven. In a shaded-pole motor, a portion of these 

windings is “shaded” by a copper loop. The interactions between the magnetic field generated by 

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the shaded portion and that generated by the unshaded portion induce rotation when the motor is 

powered. Because the imbalance between the shaded and un-shaded portions of the magnet 

remains throughout operation, however, shaded-pole motors are inefficient, with typical motor 

efficiencies less than 20 percent.38 Shaded-pole motors are, however, electrically simple and 

inexpensive. 

In a PSC motor, a smaller, start-up winding is present in addition to the main winding. 

The start-up winding is electrically connected in parallel with the main winding and in series 

with a capacitor. At start up, the interactions between the magnetic field generated by the start-up 

winding and that generated by the main winding induce rotation. Because of the capacitor, 

however, the current to the start-up winding is cut off as the motor reaches steady state. Due to

this design, PSC motors are more energy efficient than their shaded-pole counterparts, with 

motor efficiencies ranging from 25 to 40 percent, according to DOE’s research, depending on 

motor size, design, and manufacturer. The energy efficiency of commercial refrigeration 

equipment fans that use shaded-pole motors can be substantially improved by replacing them 

with PSC motors.

A third type of electric motor, the ECM motor (also known as the brushless permanent 

magnet motor), is more energy efficient than both shaded-pole and PSC motors. ECM motors, 

which are sold in high volumes, are three-phase electric motors with efficiencies even greater 

than PSC motors. These motors are actually DC motors, often with a built-in inverter allowing 

them to run off of AC current. They also feature a permanent magnet rotor. An electronic 

controller pulses power to the motor, and these signals drive different groups of windings inside 

the motor. The controller modulates these pulses of power in order to maintain a desired speed 

and torque output. The result is a motor that is capable of maintaining constant torque and of 

varying its speed as needed, resulting in high operating efficiencies, on the order of 60–70 

percent at the sizes used in commercial refrigeration equipment. However, ECM motors can 

weigh about twice as much and are more expensive than equivalent PSC motors. 

3.3.1.6 Variable-Speed Evaporator Fan Motors and Evaporator Fan Motor 

Controllers

Evaporator fan motor controllers allow fan motors to run at variable speed to match 

changing conditions in the case. During periods of frost build-up, fan motor power requirements 

increase; during the post-defrost period, power requirements decrease. Evaporator fan speeds 

could also be modulated to account for increased or decreased refrigeration load due to product 

loading, ambient conditions, or other factors. Varying the fan speed to suit the conditions could 

ensure more stable discharge air temperatures (and thus more stable product temperatures) and 

improve coil performance. Evaporator fan motor controllers could also allow the case to run 

more efficiently at different ambient humidity and temperature levels.

3.3.1.7 Higher Efficiency Evaporator Fan Blades

High-efficiency evaporator fan blades, or tangential evaporator fans, move air more 

efficiently, yielding energy consumption savings by reducing the required fan shaft power. The 

evaporator fans typically used in commercial refrigeration equipment have sheet metal blades.

Usually, the fan blade manufacturer supplies the blades and the equipment manufacturer mounts 

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them. These fan blades are not optimized for commercial refrigeration equipment. Evaporator 

fans may have lower efficiencies due to the higher required pressure drops, for which sheet metal 

fans are not well suited. Required fan shaft power could be reduced if the fan blades were 

optimized for each application.

Tangential fans are one technology that provide an opportunity to decrease equipment 

energy consumption.39 Tangential fans use a vortex builder to generate a uniform airflow over a 

large surface. This makes them better suited to evaporator and condenser fans, which need to 

distribute airflow over a large coil surface area. A single long tangential fan can meet the airflow 

requirements for an entire refrigerated cabinet, and would require only one high-efficiency fan 

motor. 

3.3.1.8 Improved Evaporator Coil Design 

The evaporator is a refrigerant-to-air heat exchanger composed of metals with high 

thermal conductivity such as aluminum and copper. It is responsible for evaporating and 

superheating the entering refrigerant liquid-vapor mixture while extracting heat from the air in 

the refrigerated space. The internal heat-exchanging surfaces in contact with refrigerant are 

commonly referred to as “refrigerant-side,” while the external heat-exchanging surfaces in 

contact with the air are referred to as “air-side.” 

Depending on the requirements of the equipment, the evaporator can be designed to have 

a discharge air temperature (DAT) that can be up to 10 °F colder than the desired temperature of 

the refrigerated space. Because a temperature difference is necessary to drive heat into the 

refrigerant from the air passing over the coil, the saturated evaporator temperature (SET) must be 

considerably colder than the DAT. The magnitude of this driving force is directly related to the 

total refrigeration load and the thermal characteristics of the evaporator, as shown in Eq. 3.1. 

UA

Q DAT TSET =∆=−

Eq. 3.1

Where: 

Q = the total refrigeration load (Btu/h), 

U = the heat transfer coefficient of the evaporator (Btu/°F/ft2), 

A = the area of the evaporator (ft2), and 

ΔT = the temperature difference between the discharge air temperature and evaporator 

temperature (°F). 

Increasing the effective heat transfer surface area of the coil or improving other thermal 

characteristics of the coil will decrease the necessary ΔT and therefore decrease the SET. This 

results in an increased compressor energy efficiency ratio (EER) and lower compressor energy 

consumption. 

Enhancements to the refrigerant-side surface area of the evaporator typically include 

rifled or diamond-pattern tubing and an increase in the number of tube passes. Enhancements to 

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the air-side surface area can include increased fin pitch (decreased fin spacing), fin patterns 

(wavy or zig-zag), and increased numbers of tube passes. 

Increasing the overall size of the coil in one or more dimensions without changing other 

aspects of the coil is another way to increase the area. However, many applications place limits 

on the feasible increase in the size of the coil. 

3.3.1.9 Low-Pressure Differential Evaporators

Decreasing the air-side pressure drop of an evaporator coil allows for the use of lower 

power evaporator fan motors. This can be enabled through utilization of designs that reduce 

restrictions to the flow of air across the coil, such as reducing the fin pitch and decreasing the 

number of tube passes. Large spaces between fins and tubes also reduce “bridging” due to frost 

buildup, which can completely block airflow through portions of the coil. 

3.3.1.10 Case Insulation Increases or Improvements

Either increasing the insulation thickness or reducing insulation conductivity will reduce 

the energy consumption of commercial refrigeration equipment. Typical baseline insulation 

thickness for refrigerated display cases ranges from 1.5 inches for medium-temperature units to 

2.5 inches for ice-cream temperature units. This thickness also varies by manufacturer and 

model. Foamed-in-place polyurethane foam is used for most cases. Improved technology 

polyurethane foam insulation can reduce conductivity, and thus case heat load. The improvement 

is due mainly to the formation of smaller air cells within the foam insulation structure and better 

cell-size consistency. Additionally, a variety of blowing agents are available for use on the 

market, with different blowing agents resulting in different thermal properties for the foam 

produced. The impact of an increase in insulation thickness or insulation quality is generally 

limited for open cases because a large portion of the cooling load is due to infiltration. Cases 

with doors stand to gain more significant energy savings due to increased insulation thickness 

and/or quality. 

3.3.1.11 Defrost Mechanisms 

As the air in the refrigerated space is cooled, water vapor condenses on the surface of the 

evaporator coil. In refrigerators and freezers, where the evaporator coil is below 32 °F, this water 

freezes as it collects, forming a growing layer of frost. The frost reduces cooling performance by 

increasing the thermal resistance to heat transfer from the coil to the air, and by obstructing 

airflow. Both the method in which defrost is performed and control of the defrost cycle can lead 

to increased energy savings.

There are several methods available for defrosting the evaporator coil: off-cycle defrost, 

electric defrost, and hot-gas defrost. Off-cycle defrost involves shutting off refrigerant flow to 

the coil while leaving the evaporator fan running. This method is used where case air is above 

the freezing point of water and can be used to melt the frost. Electric defrost is used when the air 

temperature is not high enough to defrost the coil, and when defrost must occur quickly to 

prevent any significant rise in product temperature. Electric defrost involves melting frost by 

briefly turning on an electric resistance heater that is in contact with or near the evaporator coil. 

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Hot-gas defrost involves the use of the hot compressor discharge gas to warm the 

evaporator from the refrigerant side. Electricity usage is reduced in comparison to the electric 

defrost method because available heat, which would otherwise be rejected in the condenser, is 

used. The hot gas defrost system requires more complicated piping and control than electric 

defrost. An additional drawback is the thermal stress inflicted upon the refrigerant piping by the 

alternating flow of hot gas and cold refrigerant. 

3.3.1.12 Defrost Cycle Control 

Management of frost buildup on coils is essential in ensuring continued efficient 

operation of the unit. Traditionally, defrosting systems have been run on regular intervals 

utilizing a simple timer. However, such systems have two possible negative consequences in that 

the defroster may be run too often, resulting in wasted energy, or not often enough, resulting in 

decreased system performance. Some systems have been developed that allow for control of the 

termination of defrosting based on temperature; when the coils reach a specified temperature, the 

defroster is turned off. However, initiation of the cycle still occurs on a periodic basis using a 

timer. 

Control of the defrost cycle requires the use of sensors to determine whether a defrost 

cycle is needed. The data collected can consist of either the temperature drop across the coil or 

detection of the physical thickness of frost buildup using photocells. The first of these two 

methods is based on the idea that decreased airflow across the coil is a result of frost buildup, 

meaning that the temperature differential across the coil will increase. However, there are issues 

in that external factors aside from frost buildup on the coil may be the reason for decreased 

airflow. The second method is more accurate but requires more sophisticated sensors. There has 

been significant research performed regarding the topic of defrost cycle control, and several 

manufacturers have introduced controllers that are now commercially available. However, due 

largely to concerns about reliability and accuracy, these technologies have not achieved largescale acceptance in the commercial refrigeration equipment market. 

3.3.1.13 Vacuum Insulated Panels

The importance of the amount of refrigerated volume that a unit offers and the desire to 

reduce unit energy consumption suggest that technologies that would allow an increase in 

insulation thermal resistivity (R-value) while maintaining insulation thickness would be of 

interest. VIPs could provide such performance. VIPs consist of an outer airtight membrane 

surrounding a core material to form a cavity, which is then evacuated to remove the air from the 

panel. The result is a product that performs in a manner similar to a traditional vacuum flask, 

resulting in greatly reduced thermal conduction per unit of thickness as compared to traditional 

foam insulations. VIP technology has existed for many years, but has only recently begun to see 

widespread application, most notably in residential refrigerators, due to decreasing production 

costs. 

3.3.1.14 Occupancy Sensors for Lighting Controls 

Lighting is one of the major sources of energy consumption in commercial refrigeration 

equipment. While higher efficiency lighting reduces the total lighting energy consumption, it 

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could be decreased further by employing occupancy sensors to switch off or dim the display case 

lighting when not necessary, such as during periods of low customer traffic and when the store is 

closed. Occupancy sensors turn off or dim the case lighting when no motion is sensed near the 

case for a preset period of time.

Occupancy sensors are not used with fluorescent lighting due to restarting issues at low 

temperatures. However, LED lighting does not have such problems. Therefore, occupancy 

sensors can be used only in conjunction with LED lighting. 

3.3.2 Designs Relevant Only to Equipment with Doors

The following technologies and designs are relevant only to equipment classes with 

doors: improved transparent doors, anti-fog films on transparent doors, and anti-sweat heater 

controllers. 

3.3.2.1 Improved Transparent Doors

Transparent doors allow refrigerated products to be displayed to consumers while 

keeping cold air inside the display case. Transparent doors also generally have a lower thermal 

resistance than solid insulated walls, thus allowing heat transfer into the refrigerated space at a 

higher rate. In cases with transparent doors, these surfaces are responsible for a significant 

portion of the case heat load. On freezers and some refrigerators, glass doors must also be heated 

to prevent frost or condensation from forming on the outside. These “anti-sweat” heaters often 

run continuously and consume significant amounts of energy, and also contribute to the case heat 

load. Total case energy consumption can be reduced both by improving the overall insulation 

value (U-factor) of the door and by reducing the required anti-sweat heater power. Improvements 

to heat transfer performance could include the use of additional panes of glass and expanded use 

of inert gas filled panes using argon, krypton, or xenon. The treatment of the window glass with 

advanced low emissivity coatings and increasing the number of coated surfaces could also 

reduce losses due to radiation heat transfer. Additionally, improvements to door frame insulation 

and gasketing would reduce conduction and infiltration losses. Reductions in the anti-sweat 

heater power needed can often be achieved as a function of improved conductive performance of 

the door, as well as in improvements to the gasketing and other door features. This is because the 

exterior surface of a better-insulated door will have a higher temperature than one with poor 

insulating properties, thus making condensation on the exterior of the door less likely. 

3.3.2.2 Anti-Fog Films on Transparent Doors 

Most commercial refrigeration equipment with transparent doors for merchandising and 

product access currently utilizes anti-sweat heaters to prevent fogging and condensation buildup. However, there are anti-fog treatments composed of advanced hydrophobic materials that 

prevent condensate from attaching or lingering on a glass surface and therefore prevent the 

formation of water droplets that may obscure a customer’s view of the product. Such anti-fog 

films could potentially be used on transparent doors as a static means of preventing fogging, 

eliminating the need for active energy-consuming systems. 

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3.3.2.3 Anti-Sweat Heater Controllers

Anti-sweat heater controllers match the run time of anti-sweat heaters to the anti-sweat 

heating requirements imposed by the ambient humidity, reducing energy consumption when 

ambient humidity is low. Anti-sweat heaters are used to prevent moisture condensation on 

surfaces of display cases, the temperatures of which can be below the ambient dew point. 

Freezer-door gaskets are a typical example of such a surface. Anti-sweat heaters on 

freezer-door gaskets are typically always on, but the installation of controls that sense ambient 

conditions can turn off the heaters when anti-sweat heating is not required, reducing electricity 

consumption. Such control requires measuring the local dew point or relative humidity, and 

measuring external surface temperatures. A particular heater can be turned on when the 

temperature of a particular surface falls below the dew point, or the heaters can be cycled with 

on-times increasing with dew point. Reducing anti-sweat heater on-time will also yield 

additional energy savings in display-case heat load reductions, since anti-sweat heaters 

contribute to case heat load.

It is possible that electric anti-sweat heaters could be replaced by a hot gas line running 

around the door frame. Although manufacturers have claimed that this is a difficult technology to 

implement, it has seen widespread and successful use in residential freezers.

3.3.3 Designs Relevant Only to Equipment Without Doors 

The following technologies and designs are relevant only to equipment classes without 

doors: air curtain design and night curtains. 

3.3.3.1 Air Curtain Design

Refrigerated display cases without doors allow consumers easy access to products while 

maintaining temperatures that ensure food safety. In the absence of doors, a circulated air curtain 

is used to prevent infiltration and keep cold air inside the case. The refrigeration load for these 

cases is dominated by infiltration, or the entrainment of warm and moist air into the curtain. This 

infiltration adds both sensible and latent heat to the case, and deposits additional moisture on the 

evaporator coil, which must be removed through defrosting. 

Improved air curtain design is aimed at lessening the impact of infiltration by reducing 

the entrainment of warm ambient air. Making the air curtain flow as laminar as possible reduces 

entrainment. This involves configuring the plenum before the air curtain discharge grill to shape 

the velocity profile using a honeycomb grill to align the airstreams and encourage laminar flow. 

Improvements to the velocity profile and discharge air grill may enhance the performance of the 

air curtain and reduce the infiltration load. 

3.3.3.2 Night Curtains

Open display cases have a high rate of infiltration of warm external air into the 

refrigerated cases. During store operating hours, when the refrigerated products are being taken 

out by customers and restocked by staff, such infiltration losses are inevitable. However, 

infiltration could be substantially reduced during the hours when the store is closed by using 

3-37
infiltration reduction mechanisms called night curtains. Night curtains typically take the form of 

a flexible barrier, often composed of plastic or metalized fabric, which can be pulled down over 

the open case and fastened to provide a temporary cover over the opening. These devices reduce 

the heat and moisture entry into the refrigerated space through various heat transfer mechanisms.

By fully or partially covering the case opening, night curtains reduce the convective heat transfer 

into the case through reduced air infiltration. Additionally, they provide a measure of insulation, 

reducing conduction into the case, and also decrease radiation into the case by blocking radiated 

heat from entering the refrigerated space. 

3.3.4 Technologies and Designs Relevant Only to Self-Contained Equipment

The following technologies and designs are relevant only to self-contained equipment:

higher efficiency compressors, liquid suction heat exchangers, improved condenser coil design, 

higher efficiency condenser fan motors, variable-speed condenser fan motors and condenser fan 

motor controllers, and higher efficiency condenser fan blades. 

3.3.4.1 Higher Efficiency Compressors 

Several technologies exist to increase the efficiency of commercial refrigeration 

equipment compressors. High-efficiency reciprocating and scroll compressors, sometimes 

incorporating variable-speed motors, all have the potential to reduce energy consumption 

compared to the traditional reciprocating compressors commonly used in commercial 

refrigeration equipment. 

Scroll compressors compress gas between two spirals, one fixed and one rotating. This 

method is fundamentally different from that of traditional compressors. High-efficiency 

reciprocating compressors are as efficient, or more efficient, than scroll compressors. However, 

when compared to scroll compressors, some drawbacks exist to the use of high-efficiency 

reciprocating compressors, including noise, cost, and reliability.

Variable-speed compressors are implemented through an electronic control on the 

compressor motor, which allows the motor to operate at different speeds. Variable-speed 

compressors reduce energy consumption in three ways:e

1. When refrigerant flow is reduced during part-load operation, the condenser and 

evaporator (designed for full flow conditions) are more effective and thus more 

efficient. Temperature drops decrease, resulting in reduced pressure rise across the 

compressor, which also improves efficiency. 

2. Close matching of load eliminates the cycling that occurs with single-stage 

compressors. Maintaining a constant pressure is more efficient because losses at 

higher pressure rise are greater than gains at lower pressure rise.

3. During the off cycle, the pressure in the system equilibrates. At intermediate pressure, 

refrigerant vapor will condense in the cold evaporator rather than the condenser. 

e Variable-speed compressors typically increase efficiency over a broad operating range but do not inherently 

increase maximum efficiency at the compressor rating point

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Essentially, some of the heat rejection load is rejected to the evaporator during this 

time, reducing overall system performance. Variable-speed operation would eliminate 

or significantly reduce compressor off-time and the related inefficiencies.

However, scroll and variable-speed compressor technologies have not become present in the 

domestic commercial refrigeration equipment market on a significant scale, and DOE’s research 

has indicated that a significant amount of research and development work would be required 

before these technologies could reach the market. Instead, commercial refrigeration equipment 

manufacturers often rely on compressor manufacturers to continuously update their designs for 

traditional reciprocating compressors. As updated models of reciprocating compressors, usually 

featuring higher efficiencies than the models they replace, appear on the market, these models 

are generally incorporated into the equipment offerings of the commercial refrigeration unit 

manufacturers. 

3.3.4.2 Liquid Suction Heat Exchangers

The goal of a liquid suction heat exchanger is to further cool the flow of liquid refrigerant 

entering the expansion valve using the flow of gaseous refrigerant leaving the evaporator. The 

exchanger provides sub-cooling for the entering liquid by super-heating the exiting suction 

vapor. Hotter suction vapor is less susceptible to heat gains in the return piping to the compressor 

rack. The compressor work is increased, however, because the suction vapor has greater 

enthalpy. In addition, the possibility of compressor overheating problems brought on by the 

combination of increased compressor work and hotter vapor limits the use of this method in 

some situations. The possibility for these problems and the potential efficiency gains from liquid 

suction heat exchangers depend on several factors, including evaporator temperature, type of 

refrigerant used, and system pressures. Additionally, some parties have expressed concern 

regarding the reliability of liquid suction heat exchangers. 

3.3.4.3 Improved Condenser Coil Design

Like the evaporator, the condenser is a refrigerant-to-air heat exchanger composed of 

metals with high thermal conductivity, such as aluminum and copper. It is responsible for 

condensing and sub-cooling the entering refrigerant vapor while rejecting heat from the 

refrigerant into the ambient air.

The condenser’s saturated condenser temperature (SCT) is markedly warmer than the 

ambient air, with the exact temperature differential being a function of the equipment design and 

operating conditions. As with evaporator coils, increasing the area of the condenser coil or 

otherwise improving its heat transfer capability will decrease the necessary ΔT across the coil

and therefore decrease the SCT, resulting in increased compressor efficiency (and thus increased 

EER).

Enhancements to the refrigerant-side surface area of the condenser typically include 

rifled or diamond-pattern tubing and an increase in the number of tube passes. Enhancements to 

the air-side surface area can include increased fin pitch (decreased fin spacing), fin patterns 

(wavy or zig-zag), and increased numbers of tube passes. 

3-39
Increasing the overall size of the coil in one or more dimensions without changing other 

aspects of the coil is another way to increase the area. However, many applications place limits 

on the feasible increase in the size of the coil. 

3.3.4.4 Higher Efficiency Condenser Fan Motors 

Condenser fan motors are responsible for moving air across the condenser coil and 

typically run at one speed. The manufacturer matches the motor size and blade to the condenser 

coil to meet the expected load on the case under most conditions. Higher efficiency condenser 

fan motors reduce energy consumption by requiring less electrical power to generate motor shaft 

output power. Condenser fan motors are generally of the same size and type as evaporator fan 

motors. See section 3.3.1.5 for a discussion of higher efficiency fan motor technology. 

3.3.4.5 Variable-Speed Condenser Fan Motors and Condenser Fan Motor 

Controllers

Condenser fan motor controllers could allow fan motors to run at variable speed to match 

changing conditions in the case. Matching the fan speed to varying conditions and heat loads 

could then improve system performance, allowing the refrigeration system to run more 

efficiently at different ambient humidity and temperature levels. However, under constant 

ambient conditions, the energy savings benefit with condenser fan motor controllers would likely 

be small. 

3.3.4.6 Higher Efficiency Condenser Fan Blades

Conventional fans have sheet metal blades mounted to a central hub, and are generally 

not optimized for the specific application in which they will be used. Instead, they are designed 

for mass production and scalability in order to minimize production cost and waste. Optimization 

of fan design for specific applications could significantly reduce input energy needed in order to 

perform the necessary work. Higher efficiency fan blades could be capable of moving more air at 

a given rotational speed when compared to traditional fan blades. This means that a smaller 

motor could be used, or the existing motor could be run at a lower speed, resulting in direct 

energy savings. 

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REFERENCES

1. Air Conditioning, Heating and Refrigeration Institute. Personal communication. 

August 26, 2010. 

2. The Share-of-Market Picture for 2004. Appliance Magazine. September 2005. 

3. U.S. Small Business Administration. Small Business Size Standards Matched to 

North American Industry Classification System. 2006. (Last accessed June 25, 

2007.) <http://www.sba.gov/gopher/Financial-Assistance/SizeStandards/sizetablestandards.txt> The June 25, 2007 material from this website is 

available in Docket EE-2006-STD-0126. For more information, contact Brenda 

Edwards-Jones at (202) 586-2945. 

4. U.S. Department of Energy−Office of Energy Efficiency and Renewable Energy. 

DSIRETM: Database of State Incentives for Renewables & Efficiency. 2011. (Last 

accessed March 9, 2011). <http://www.dsireusa.org/> 

5 Natural Resources Canada – Office of Energy Efficiency. Energy Efficiency 

Regulations – Self-Contained, Commercial Refrigerators, Freezers, and 

Refrigerator-Freezers without Doors; Commercial Refrigerators, Freezers, and 

Refrigerator-Freezers with a Remote Condensing Unit; Commercial Ice-Cream 

Freezers – Bulletin on Developing and Amending Standards. May 2010. Last 

accessed March 16, 2011). <http://oee.nrcan.gc.ca/regulations/bulletin/refrigeratorfreezers-may-2010.cfm?attr=0> 

6. Australian Government−Department of Environment and Water Resources, 

Australian Greenhouse Office. Requirements for Commercial Refrigeration. 2004. 

(Last accessed June 27, 2007.) 

<http://www.energyrating.gov.au/commrefrig1.html> The June 27, 2007 material 

from this website is available in Docket EE-2006-STD-0126. For more information, 

contact Brenda Edwards-Jones at (202) 586-2945. 

7. U.S. Environmental Protection Agency, ENERGY STAR. Commercial Refrigerator 

and Freezers Key Product Criteria. 2010. (Last accessed March 9, 2011.) 

<http://www.energystar.gov/index.cfm?c=commer_refrig.pr_crit_commercial_refri

gerators> 

8. Consortium for Energy Efficiency, Commercial Kitchens Initiative. High Efficiency 

Specifications for Commercial Refrigerators and Freezers. 2010. (Last accessed 

August 30, 2010.) <http://www.cee1.org/com/comkit/files/RefrigerationSpecification.pdf> 

9. U.S. Department of Energy – Office of Energy Efficiency and Renewable Energy, 

Federal Energy Management Program. Procuring Energy-Efficient Products. 2010. 

(Last accessed August 30, 2010.) 

<http://www1.eere.energy.gov/femp/technologies/procuring_eeproducts.html> 

3-41
10. Efficiency Vermont. Refrigeration and Controls Rebates. 2011. (Last accessed 

March 9, 2011.) <http://www.efficiencyvermont.com/for_my_business/ways-tosave-and-rebates/Refrigeration/rebates.aspx> 

11. Energy Smart Grocer. EnergySmart Grocer Incentive Worksheet. 2011. (Last 

accessed March 9, 2011.) 

<http://www.energysmartgrocer.org/pdfs/PGE/2010_12%20EnergySmartGrocer%2

0IncentiveWorksheet_v2.pdf> 

12. NV Energy. Nevada Sure Bet Commercial Incentives. 2011. (Last accessed March 

9, 2011.) 

<http://www.nvenergy.com/saveenergy/business/incentives/surebet/commercial.cf

m> 

13. Otter Trail Power Company. Rebates. 2011. (Last accessed March 9, 2011.) 

<http://www.otpco.com/SaveEnergyMoney/Rebates.asp> 

14. North American Association of Food Equipment Manufacturers. 2008 Size and 

Shape of the Industry. 2008. Chicago, IL. 

15. North American Association of Food Equipment Manufacturers. 2006 Size and 

Shape of the Industry. 2006. Chicago, IL.

16. North American Association of Food Equipment Manufacturers. 2004 Size and 

Shape of the Industry. 2004. Chicago, IL

17. North American Association of Food Equipment Manufacturers. 2002 Size and 

Shape of the Industry. 2002. Chicago, IL

18. Freedonia Group, Incorporated. Commercial Refrigeration Equipment to 2014. 

2010. Cleveland, OH. Study 2661. 

19. Freedonia Group, Incorporated. Commercial Refrigeration Equipment to 2008. 

2004. Cleveland, OH. Study 1849. 

20. U.S. Census Bureau. 2007 Economic Census, Manufacturing, Industry Series, AirConditioning and Warm Air Heating Equipment and Commercial and Industrial 

Refrigeration Equipment Manufacturing: 2007. October 2009. EC07-31I1-333415. 

Washington, D.C. 

21. U.S Census Bureau. 2002 Economic Census, Manufacturing, Industry Series, AirConditioning and Warm Air Heating Equipment and Commercial and Industrial 

Refrigeration Equipment Manufacturing: 2002. December 2004. EC02-31I-333415 

(RV). Washington, D.C. 

3-42
22. U.S. Census Bureau. 1997 Economic Census, Manufacturing, Industry Series, AirConditioning and Warm Air Heating Equipment and Commercial and Industrial 

Refrigeration Equipment Manufacturing: 1997. September 1999. EC97M-3334D. 

Washington, D.C. 

23. U.S. Internal Revenue Service. Field Directive on the Planning and Examination of 

Cost Segregation Issues in the Retail Industry. 2004. (Last accessed June 25, 2007.) 

<http://www.irs.gov/businesses/article/0,,id=151273,00.html> The June 25, 2007 

material from this website is available in Docket EE-2006-STD-0126. For more 

information, contact Brenda Edwards-Jones at (202) 586-2945. 

24. Sand, J.R., S.K. Fisher, and V.D. Baxter. Energy and Global Warming Impacts of 

HFC Refrigerants and Emerging Technologies. 1997. Oak Ridge National 

Laboratory: Oak Ridge, TN. (Last accessed June 25, 2007.) 

<http://www.afeas.org/tewi/tewi-iii.pdf> The June 25, 2007 material from this 

website is available in Docket EE-2006-STD-0126. For more information, contact 

Brenda Edwards-Jones at (202) 586-2945. 

25. Heshong Mahone Group, Inc. New York Energy Smart Program Cost-Effectiveness 

Assessment December 2004. Prepared for the New York State Energy Research and 

Development Authority. 2004. (Last accessed June 26, 2007.) 

<http://www.nyserda.org/Energy_Information/SBC/cost_effectiveness.pdf> The 

June 26, 2007 material from this website is available in Docket EE-2006-STD0126. For more information, contact Brenda Edwards-Jones at (202) 586-2945. 

26. Glasch, V. Personal communication. Verisae. Communication with Keith Glasch.

2006. 

27. Hepperla, P. Personal communication. Verisae. Communications with Paul 

Hepperla. 2006. 

28. Mark Ellis & Associates. New Zealand Minimum Energy Performance Standards 

for Commercial Refrigeration Cabinets, Prepared for the Energy Efficiency and 

Conservation Authority. 2003. (Last accessed June 26, 2007.) 

<http://www.eeca.govt.nz/eeca-library/products/standards/report/meps-forcommercial-refridgeration-cabinets-03.pdf> The June 26, 2007, material from this 

website is available in Docket EE-2006-STD-0126. For more information, contact 

Brenda Edwards-Jones at (202) 586-2945. 

29. Foster-Miller. Development and Demonstration of an Advanced Supermarket 

Refrigeration/HVAC System. 2001. Oak Ridge National Laboratory: Oak Ridge, 

TN. Report No. ORL-970163.

3-43
30. U.S. Environmental Protection Agency−Office of Air and Radiation. U.S. High 

GWP Gas Emissions 1990–2010: Inventories, Projections, and Opportunities for 

Reductions, June 2001. 2001. (Last accessed June 26, 2007.) 

<http://www.epa.gov/highgwp/projections.html> The June 26, 2007, material from 

this website is available in Docket EE-2006-STD-0126. For more information, 

contact Brenda Edwards-Jones at (202) 586-2945. 

31. Arthur D. Little, Inc. Final Report to the Alliance for Responsible Atmospheric 

Policy, March 21, 2002. 2002. (Last accessed March 16, 2011.) 

<http://www.arap.org/adlittle/toc.html> The June 26, 2007 material from this 

website is available in Docket EE-2006-STD-0126. For more information, contact 

Brenda Edwards-Jones at (202) 586-2945. 

32. California Energy Commission. Update of Appliance Efficiency Regulations: 

California Energy Commission Staff Report, November 2004. 2004. California 

Energy Commission: Sacramento, CA. Report No. 400-04-007F. 

33. Hansen, M. Personal communication. Key Mechanical, Kent, WA. Communication 

with Mary Hansen. 2006. 

34. Intergovernmental Panel on Climate Change, World Meteorological 

Organization/United Nations Environment Programme. Good Practice Guidance 

and Uncertainty Management in National Greenhouse Gas Inventories. Chapter 3, 

Good Practices. 2001. (Last accessed June 26, 2007.) <http://www.ipccnggip.iges.or.jp/public/gp/english/3_Industry.pdf> The June 26, 2007 material from 

this website is available in Docket EE-2006-STD-0126. For more information, 

contact Brenda Edwards-Jones at (202) 586-2945. 

35. Fischer, S., et al. Energy and Global Warming Impacts of CFC Alternative 

Technologies. 1991. Prepared by Oak Ridge National Laboratory and Arthur D. 

Little, Inc. Sponsored by Alternative Fluorocarbons Environmental Acceptability 

Study (AFEAS) and the U.S. Department of Energy. 

36. Navigant Consulting, Inc. Energy Savings Potential and R&D Opportunities for 

Commercial Refrigeration. Final Report. 2009. Submitted to the U.S. Department 

of Energy’s Energy Efficiency and Renewable Energy Building Technologies 

Program. Washington, D.C. 

<http://apps1.eere.energy.gov/buildings/publications/pdfs/corporate/commercial_ref

rig_report_10-09.pdf> 

37. Raghavan R., and N. Narendran. 2002 Solid State Lighting II: Proceeding of the 

Society of Photo-Optical Instrumentation Engineer - Refrigerated Display Case 

Lighting with LEDs. 2002. Lighting Research Center, Rensselaer Polytechnic 

Institute: Rensselaer, NY.

3-44
38. Leeson. Single-phase Electric Motors. 2006. (Last accessed on June 26, 2007.) 

<http://www.iprocessmart.com/leeson/leeson_singlephase_article.htm> The June 

26, 2007 material from this website is available in Docket EE-2006-STD-0126. For 

more information, contact Brenda Edwards-Jones at (202) 586-2945. 

39. Walker, D.H. Investigation of Energy-Efficient Supermarket Display Cases. 2004. 

Oak Ridge National Laboratory: Oak Ridge, TN. Report No. ORNL/TM-2004/292. 

3-45
CHAPTER 4. SCREENING ANALYSIS

TABLE OF CONTENTS

4.1 INTRODUCTION .............................................................................................................. 4-1

4.2 TECHNOLOGIES THAT DO NOT CONSISTENTLY AFFECT CALCULATED DAILY

ENERGY CONSUMPTION .............................................................................................. 4-2

4.2.1 Higher Efficiency Expansion Valves ...................................................................... 4-2

4.2.2 Variable-Speed Condenser Fans and Condenser Fan Motor Controllers ............... 4-3

4.2.3 Anti-Sweat Heater Controllers ................................................................................ 4-3

4.2.4 Liquid-Suction Heat Exchangers ............................................................................ 4-3

4.3 SCREENED-OUT TECHNOLOGY – AIR CURTAIN DESIGN ..................................... 4-4

4.4 REMAINING TECHNOLOGIES ...................................................................................... 4-4

 

4-i 
CHAPTER 4. SCREENING ANALYSIS

4.1 INTRODUCTION

This chapter describes the screening analysis that the U.S. Department of Energy (DOE) 

has performed in support of the energy conservation standards rulemaking for commercial 

refrigeration equipment. 

In the market and technology assessment (chapter 3 of this technical support document 

(TSD)), DOE presented an initial list of technologies that have the potential to reduce the energy 

consumption of commercial refrigeration equipment. The goal of the screening analysis is to 

screen out technologies that will not be considered further in the rulemaking analyses. DOE 

evaluated the list of remaining technologies using the screening criteria set forth in the Energy 

Policy and Conservation Act (EPCA). (42 U.S.C. 6311–6317) 

Section 325(o) of EPCA establishes criteria for prescribing new or amended standards 

that are designed to achieve the maximum improvement in energy efficiency. Further, EPCA 

directs the Secretary of Energy to determine whether a standard is technologically feasible and 

economically justified. (42 U.S.C. 6295(o)(2)(A), as directed by 42 U.S.C. 6316(a)(1)−(3)) In 

addition, EPCA establishes guidelines for determining whether a standard is economically 

justified. (42 U.S.C. 6295(o)(2)(B)) In view of the EPCA requirements for determining whether 

a standard is technologically feasible and economically justified, Appendix A to subpart C of 10 

CFR part 430, “Procedures, Interpretations, and Policies for Consideration of New or Revised 

Energy Conservation Standards for Consumer Products” (the Process Rule), sets forth 

procedures to guide DOE in its consideration and promulgation of new or revised efficiency 

standards. These procedures elaborate on the statutory criteria provided in 42 U.S.C. 6295(o) 

and, in part, eliminate inapplicable technologies early in the process of prescribing or amending 

an energy efficiency standard. In particular, sections 4(b)(4) and 5(b) of the Process Rule provide 

guidance to DOE in determining whether to eliminate from consideration any technology that 

presents unacceptable problems with respect to the following criteria. 

Technological feasibility. Technologies incorporated in commercial equipment or in 

working prototypes will be considered technologically feasible. 

Practicability to manufacture, install, and service. If mass production of a technology 

in commercial equipment and reliable installation and servicing of the technology could be 

achieved on the scale necessary to serve the relevant market at the time of the effective date of 

the standard, then that technology will be considered practicable to manufacture, install, and 

service.

Impacts on equipment utility or equipment availability. If DOE determines that a 

technology will have significant adverse impact on the utility of the equipment to significant 

subgroups of consumers, or result in the unavailability of any covered equipment type with 

performance characteristics (including reliability), features, sizes, capacities, and volumes that 

are substantially the same as equipment generally available in the United States at the time, DOE 

will not consider it further.

4-1 
Adverse impacts on health or safety. If DOE determines that a technology will have 

significant adverse impacts on health or safety, DOE will not consider it further. 

In summary, if DOE determines that a technology, or a combination of technologies, has 

unacceptable effects on the policies stated in section 5(b) of the Process Rule, it will be 

eliminated from consideration. If a particular technology fails to meet one or more of the four 

criteria, it will be screened out. The reasons for eliminating any technology are documented in 

section 4.3. 

4.2 TECHNOLOGIES THAT DO NOT CONSISTENTLY AFFECT CALCULATED 

DAILY ENERGY CONSUMPTION 

DOE understands that some of the technologies presented in chapter 3 of this TSD may

potentially reduce annual energy consumption for specific pieces of equipment under certain 

field operating conditions, but may not consistently reduce calculated daily energy consumption 

(CDEC), as measured by the DOE test procedure, utilizing the American National Standards 

Institute/American Society of Heating, Refrigerating and Air-Conditioning Engineers 

(ANSI/ASHRAE) Standard 72, Method of Testing Commercial Refrigerators and Freezers, for 

all units of a given class. In some cases, while a technology may benefit a specific individual 

model or unit produced by a given manufacturer, it may not necessarily be considered to have 

similar effects across all units of that same equipment class, depending on the design of each 

unit. Moreover, certain technologies may provide benefits within specific operating conditions 

that they may encounter in some field applications, but would not produce benefits within the 

scope of the ASHRAE method of test. Therefore, DOE removed from consideration those 

technologies that cannot be considered to consistently affect or reduce CDEC during the tests

across the range of equipment analyzed. These technologies include higher efficiency expansion 

valves, variable-speed condenser fans and condenser fan motor controllers, anti-sweat heater 

controllers, and liquid-suction heat exchangers (LSHXs). 

4.2.1 Higher Efficiency Expansion Valves

Higher efficiency expansion valves can reduce the annual energy consumption in some 

commercial refrigeration units by controlling refrigerant flow to adapt to varying loads and

ambient conditions. However, this is largely a function of the design of a specific unit. While 

some models may benefit from the use of a higher efficiency expansion valve, others may not 

see the same efficiency increase due to a refrigeration system being configured differently. 

Moreover, while there are small thermodynamic fluctuations during the ASHRAE 72 test, the 

test as a whole is conducted under ambient and internal conditions that are held as close to 

constant as possible. Much of the advantage in the field performance of improved expansion 

valves arises from their ability to adapt to extreme variations in conditions, which are not likely 

to be experienced during the ASHRAE 72 test. Therefore, since this technology could not be 

found to have a consistent efficiency improvement effect across entire equipment classes, DOE 

did not consider higher efficiency expansion valves in the engineering analysis. 

4-2 
4.2.2 Variable-Speed Condenser Fans and Condenser Fan Motor Controllers 

Variable-speed condenser fan motors and controllers driving the condenser fan motors 

can adapt condenser operation to changing ambient temperatures (effectively by creating floating 

head pressure), and thereby could reduce the energy consumption of self-contained commercial 

refrigeration equipment operating in areas with varying ambient conditions. However, because 

testing under the ANSI/ASHRAE Standard 72 test procedure is conducted at a constant ambient 

temperature, there is little opportunity to account for the adaptive technology of varying 

condenser fan motor speed to reduce CDEC. Moreover, DOE understands that condenser fan 

motor controllers would function best when paired with a variable-speed modulating compressor, 

a technology that DOE understands to be only in the early research and development stages of 

implementation in this industry. Therefore, DOE did not consider variable-speed condenser fan 

motors or condenser fan motor controllers in the engineering analysis. 

4.2.3 Anti-Sweat Heater Controllers

A commercial refrigeration equipment manufacturer typically sizes anti-sweat heaters 

according to the ambient temperature and humidity of a particular operating environment. The 

end-user must maintain that environment to prevent condensation (i.e., fog) from forming on 

surfaces such as display case glass. Anti-sweat heater controllers modulate the operation of antisweat heaters by reducing anti-sweat heater power when humidity is low. Anti-sweat heater 

controllers operate most effectively when a constant ambient dew point cannot be maintained. 

However, in the context of the test procedure, anti-sweat heater controllers will solely serve to 

keep the power to the anti-sweat heaters at the levels necessary for the test conditions. These 

fixed conditions of 75 °F and 55 percent relative humidity are the conditions that ASHRAE has 

determined to be generally representative of commercial refrigeration equipment operating 

environments and which DOE has adopted in its test procedure. While anti-sweat heater 

controllers could modulate the anti-sweat power to a further extent in the field so as to account 

for more or less extreme ambient conditions, a system equipped with anti-sweat heater 

controllers will not likely exhibit significantly different performance at test procedure conditions 

than a unit with anti-sweat heaters tuned for constant 75/55 conditions. Therefore, DOE did not 

consider anti-sweat heater controllers in the engineering analysis.

4.2.4 Liquid-Suction Heat Exchangers

An LSHX is an indirect liquid-to-vapor heat transfer device that evaporates any residual 

liquid refrigerant that remains in the evaporator discharge line, and thereby minimizes the risk of 

liquid refrigerant carrying over into the compressor. Generally, LSHXs are installed in 

refrigeration systems to ensure proper system operation and increase system performance.

However, the performance of an LSHX is dependent on the specific design used in a given piece 

of equipment, as well as other properties of the system and the operating conditions. A 

combination of refrigerant type, operating temperature, ambient conditions, and other factors 

determines whether an LSHX will increase or decrease the CDEC as measured by the 

ANSI/ASHRAE Standard 72 test procedure. In some cases, an LSHX can produce enough of a 

pressure differential across the device, which requires additional compressor energy to 

overcome, that the result is a net increase in energy consumption. Manufacturers have stated that, 

while an LSHX can reduce energy consumption in a lower efficiency or baseline system, these 

4-3 
devices often produce negative energy impacts in more advanced equipment designs. DOE has 

also heard from stakeholders that LSHXs may have issues with unreliability, resulting in 

refrigerant leakage and increased system energy consumption. Because LSHXs do not 

consistently reduce CDEC in the equipment classes analyzed, DOE did not consider this 

technology in the engineering analysis. 

4.3 SCREENED-OUT TECHNOLOGY – AIR CURTAIN DESIGN

An air curtain is a fan-powered device that creates a moving wall (curtain) of air, which 

separates two spaces of different temperatures. Air curtains are used in commercial refrigeration 

equipment to minimize the infiltration of warmer external air into the refrigerated space. In its 

market and technology assessment (TSD chapter 3), DOE noted that its research had presented 

the possibility of advanced air curtain designs with levels of performance beyond the traditional 

air curtains generally employed in open display cases being used in the commercial refrigeration 

equipment industry. However, DOE has determined that advanced air curtain designs are only in 

the research stage and, therefore, it would be impracticable to manufacture, install, and service 

this technology on the scale necessary to serve the relevant market at the time the standard

becomes effective. Sections 4(a) and 5(b) of the Process Rule specifically set “practicability to 

manufacture, install, and service” as a criterion that should be satisfied for technology to be 

considered as a design option. Therefore, DOE screened out improved air curtains as a design 

option for improving the energy efficiency of commercial refrigeration equipment. 

4.4 REMAINING TECHNOLOGIES

After eliminating those technologies that do not reduce CDEC and screening out 

technologies that do not meet the requirements of sections 4(a)(4) and 5(b) of the Process Rule, 

DOE is considering the following technologies: 

• higher efficiency lighting 

• higher efficiency lighting ballasts

• remote lighting ballast location

• higher efficiency evaporator fan motors 

• variable-speed evaporator fan motors and evaporator fan motor controllers 

• improved evaporator coil design 

• higher efficiency evaporator fan blades 

• low-pressure differential evaporators

• case insulation increases or improvements 

• defrost mechanisms

• defrost cycle controls 

• vacuum insulated panels 

• occupancy sensors for lighting controls 

• improved transparent doors (equipment with doors only) 

• anti-fog films on transparent doors (equipment with doors only) 

• night curtains (equipment without doors only) 

• higher efficiency compressors (self-contained equipment only) 

• improved condenser coil design (self-contained equipment only) 

4-4 
• higher efficiency condenser fan motors (self-contained equipment only) 

• higher efficiency condenser fan blades (self-contained equipment only) 

4-5 
CHAPTER 5. ENGINEERING ANALYSIS

TABLE OF CONTENTS

5.1 INTRODUCTION ........................................................................................................... 5-1

5.2 METHODOLOGY OVERVIEW .................................................................................... 5-1

5.3 EQUIPMENT CLASSES ANALYZED.......................................................................... 5-3

5.3.1 Classes Chosen for Analysis ................................................................................ 5-3

5.3.2 Baseline Equipment ............................................................................................. 5-4

5.3.3 Service over Counter Equipment ......................................................................... 5-5

5.4 COST MODEL ................................................................................................................ 5-6

5.4.1 Development of Core Case Costs ........................................................................ 5-6

5.4.1.1 Selection of Units for Teardown Analysis ............................................ 5-7

5.4.1.2 Manufacturer Production Cost Estimates and Assumptions ................. 5-7

5.4.1.3 Structure of the Cost Model .................................................................. 5-8

5.4.1.4 Material Prices ...................................................................................... 5-9

5.4.1.5 Results ................................................................................................. 5-10

5.4.2 Design Option Costs .......................................................................................... 5-10

5.4.2.1 Light-Emitting Diode Price Forecasting ............................................. 5-11

5.4.3 Representative Unit Manufacturer Production Cost Values .............................. 5-11

5.5 MANUFACTURER SELLING PRICE ........................................................................ 5-12

5.5.1 Manufacturer Markup ........................................................................................ 5-12

5.5.2 Representative Units .......................................................................................... 5-13

5.5.3 Shipping Costs ................................................................................................... 5-14

5.6 ENERGY CONSUMPTION MODEL .......................................................................... 5-14

5.6.1 Non-Numerical Assumptions............................................................................. 5-15

5.6.2 Numerical Constants and Assumptions ............................................................. 5-16

5.6.3 Screened-In Technologies .................................................................................. 5-16

5.6.4 Screened-In Technologies Not Considered in the Engineering Analysis .......... 5-17

5.6.4.1 Remote Lighting Ballast Location ...................................................... 5-17

5.6.4.2 Variable-Speed Evaporator Fan Motors and Evaporator Fan Motor 

Controllers.......................................................................................................... 5-18

5.6.4.3 Higher Efficiency Evaporator and Condenser Fan Blades ................. 5-18

5.6.4.4 Low-Pressure Differential Evaporators .............................................. 5-18

5.6.4.5 Defrost Cycle Control ......................................................................... 5-19

5.6.4.6 Defrost Mechanisms ........................................................................... 5-19

5.6.4.7 Anti-Fog Films on Transparent Doors ................................................ 5-19

5.6.5 Design Options................................................................................................... 5-20

5.6.5.1 Higher Efficiency Lighting and Occupancy Sensors .......................... 5-20

5.6.5.2 Higher Efficiency Evaporator Fan Motors ......................................... 5-23

5.6.5.3 Improved Evaporator Coil Design ...................................................... 5-23

5.6.5.4 Improved Insulation and Vacuum Insulated Panels ............................ 5-24

5.6.5.5 Improved Transparent Doors .............................................................. 5-26

5.6.5.6 Higher Efficiency Condenser Fan Motors .......................................... 5-29

5.6.5.7 Improved Condenser Coil Design ....................................................... 5-29

5.6.5.8 Higher Efficiency Compressors .......................................................... 5-30

5-i 
5.6.5.9 Night Curtains ..................................................................................... 5-31

5.6.6 Model Components ............................................................................................ 5-31

5.6.6.1 Component Energy Consumption ....................................................... 5-32

5.6.6.2 Compressor Energy Consumption ...................................................... 5-33

5.6.6.3 Component Load Model ..................................................................... 5-34

5.6.6.4 Radiation Load Model ........................................................................ 5-35

5.6.6.5 Conduction Load Model ..................................................................... 5-36

5.6.6.6 Infiltration Load Model....................................................................... 5-36

5.7 COST-EFFICIENCY CURVES .................................................................................... 5-37

5.8 OFFSET FACTORS ...................................................................................................... 5-63

5.9 EXTENSION OF ANALYSIS TO SECONDARY EQUIPMENT CLASSES ............ 5-65

5.9.1 Development of Extension Multiplier Approach in 2009 Rulemaking ............. 5-66

5.9.2 Current Use of Extension Multiplier Methodology ........................................... 5-68

REFERENCES .......................................................................................................................... 5-70

LIST OF TABLES

Table 5.4.1 Cost Model Output Classifications ........................................................................... 5-7

Table 5.4.2 Examples of Major Manufacturing Processes .......................................................... 5-8

Table 5.5.1 Representative Unit Specifications ......................................................................... 5-13

Table 5.6.1 Energy Consumption Model Numerical Constants and Assumptions .................... 5-16

Table 5.6.2 Details for Lighting for VOP, SVO, HZO, and SOC Equipment Families 

Design Option .................................................................................................... 5-22

Table 5.6.3 Details for Lighting for VCT and PD Equipment Families Design Option ........... 5-22

Table 5.6.4 Details for Evaporator Fan Motor Design Option .................................................. 5-23

Table 5.6.5 Details for Evaporator Coil Design Option ............................................................ 5-24

Table 5.6.6 Properties of Standard and Enhanced Evaporator Coil Designs ............................. 5-24

Table 5.6.7 Assumptions in Cost Calculation Methodology for Insulation Thickness 

Increase .............................................................................................................. 5-25

Table 5.6.8 Assumptions in Cost Calculation Methodology for Vacuum Insulated Panels ...... 5-26

Table 5.6.9 Details for Insulation Design Options .................................................................... 5-26

Table 5.6.10 Details for Doors for VCT Equipment Family, Low and Ice-Cream 

Temperature Design Option ............................................................................... 5-27

Table 5.6.11 Details for Doors for VCT and PD Equipment Families, Medium 

Temperature Design Option ............................................................................... 5-27

Table 5.6.12 Details for HCT Equipment Family, Medium Temperature Design Option ........ 5-28

Table 5.6.13 Details for Doors for HCT Equipment Family, Low, and Ice-Cream 

Temperature Design Option ............................................................................... 5-28

Table 5.6.14 Details for Doors for SOC Equipment Family, Medium Temperature 

Design Option .................................................................................................... 5-29

Table 5.6.15 Details for “Increased Condenser Surface Area” Design Option ......................... 5-29

Table 5.6.16 Properties of Standard and Enhanced Condenser Coil ......................................... 5-30

Table 5.6.17 Details for “Night Curtains” Design Option ......................................................... 5-31

Table 5.7.1 Figure, Table, and Page Numbers for Cost-Efficiency Results .............................. 5-38

Table 5.7.2 Cost-Efficiency Data for the VOP.RC.M Equipment Class ................................... 5-39

Table 5.7.3 Cost-Efficiency Data for the VOP.RC.L Equipment Class .................................... 5-40

Table 5.7.4 Cost-Efficiency Data for the VOP.SC.M Equipment Class ................................... 5-41

5-ii
Table 5.7.5 Cost-Efficiency Data for the SVO.RC.M Equipment Class ................................... 5-42

Table 5.7.6 Cost-Efficiency Data for the SVO.SC.M Equipment Class ................................... 5-43

Table 5.7.7 Cost-Efficiency Data for the HZO.RC.M Equipment Class ................................... 5-44

Table 5.7.8 Cost-Efficiency Data for the HZO.RC.L Equipment Class .................................... 5-45

Table 5.7.9 Cost-Efficiency Data for the HZO.SC.M Equipment Class ................................... 5-46

Table 5.7.10 Cost-Efficiency Data for the HZO.SC.L Equipment Class .................................. 5-47

Table 5.7.11 Cost-Efficiency Data for the VCT.RC.M Equipment Class ................................. 5-48

Table 5.7.12 Cost-Efficiency Data for the VCT.RC.L Equipment Class .................................. 5-49

Table 5.7.13 Cost-Efficiency Data for the VCT.SC.M Equipment Class ................................. 5-50

Table 5.7.14 Cost-Efficiency Data for the VCT.SC.L Equipment Class .................................. 5-51

Table 5.7.15 Cost-Efficiency Data for the VCT.SC.I Equipment Class .................................... 5-52

Table 5.7.16 Cost-Efficiency Data for the VCS.SC.M Equipment Class .................................. 5-53

Table 5.7.17 Cost-Efficiency Data for the VCS.SC.L Equipment Class ................................... 5-54

Table 5.7.18 Cost-Efficiency Data for the VCS.SC.I Equipment Class .................................... 5-55

Table 5.7.19 Cost-Efficiency Data for the HCT.SC.M Equipment Class ................................. 5-56

Table 5.7.20 Cost-Efficiency Data for the HCT.SC.L Equipment Class .................................. 5-57

Table 5.7.21 Cost-Efficiency Data for the HCT.SC.I Equipment Class .................................... 5-58

Table 5.7.22 Cost-Efficiency Data for the HCS.SC.M Equipment Class .................................. 5-59

Table 5.7.23 Cost-Efficiency Data for the HCS.SC.L Equipment Class ................................... 5-60

Table 5.7.24 Cost-Efficiency Data for the SOC.RC.M Equipment Class ................................. 5-61

Table 5.7.25 Cost-Efficiency Data for the SOC.SC.M Equipment Class .................................. 5-62

Table 5.7.26 Cost-Efficiency Data for the PD.SC.M Equipment Class .................................... 5-63

Table 5.9.1 Extension Multipliers for Remote and Self-Contained Equipment 

Without Doors .................................................................................................... 5-66

Table 5.9.2 Extension Multipliers .............................................................................................. 5-68

Table 5.9.3 Extension Multipliers by Equipment Class ............................................................ 5-69

LIST OF FIGURES

Figure 5.4.1 Copper and Stainless Steel Price Trends ............................................................... 5-10

Figure 5.5.1 Components of Manufacturer Selling Price .......................................................... 5-12

Figure 5.6.1 Composition of the Energy Consumption Model .................................................. 5-32

Figure 5.7.1 Cost-Efficiency Curve for the VOP.RC.M Equipment Class ............................... 5-39

Figure 5.7.2 Cost-Efficiency Curve for the VOP.RC.L Equipment Class ................................ 5-40

Figure 5.7.3 Cost-Efficiency Curve for the VOP.SC.M Equipment Class ................................ 5-41

Figure 5.7.4 Cost-Efficiency Curve for the SVO.RC.M Equipment Class ............................... 5-42

Figure 5.7.5 Cost-Efficiency Curve for the SVO.SC.M Equipment Class ................................ 5-43

Figure 5.7.6 Cost-Efficiency Curve for the HZO.RC.M Equipment Class ............................... 5-44

Figure 5.7.7 Cost-Efficiency Curve for the HZO.RC.L Equipment Class ................................ 5-45

Figure 5.7.8 Cost-Efficiency Curve for the HZO.SC.M Equipment Class................................ 5-46

Figure 5.7.9 Cost-Efficiency Curve for the HZO.SC.L Equipment Class ................................. 5-47

Figure 5.7.10 Cost-Efficiency Curve for the VCT.RC.M Equipment Class ............................. 5-48

Figure 5.7.11 Cost-Efficiency Curve for the VCT.RC.L Equipment Class .............................. 5-49

Figure 5.7.12 Cost-Efficiency Curve for the VCT.SC.M Equipment Class .............................. 5-50

Figure 5.7.13 Cost-Efficiency Curve for the VCT.SC.L Equipment Class ............................... 5-51

Figure 5.7.14 Cost-Efficiency Curve for the VCT.SC.I Equipment Class ................................ 5-52

Figure 5.7.15 Cost-Efficiency Curve for the VCS.SC.M Equipment Class .............................. 5-53

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Figure 5.7.16 Cost-Efficiency Curve for the VCS.SC.L Equipment Class ............................... 5-54

Figure 5.7.17 Cost-Efficiency Curve for the VCS.SC.I Equipment Class ................................ 5-55

Figure 5.7.18 Cost-Efficiency Curve for the HCT.SC.M Equipment Class .............................. 5-56

Figure 5.7.19 Cost-Efficiency Curve for the HCT.SC.L Equipment Class ............................... 5-57

Figure 5.7.20 Cost-Efficiency Curve for the HCT.SC.I Equipment Class ................................ 5-58

Figure 5.7.21 Cost-Efficiency Curve for the HCS.SC.M Equipment Class .............................. 5-59

Figure 5.7.22 Cost-Efficiency Curve for the HCS.SC.L Equipment Class ............................... 5-60

Figure 5.7.23 Cost-Efficiency Curve for the SOC.RC.M Equipment Class.............................. 5-61

Figure 5.7.24 Cost-Efficiency Curve for the SOC.SC.M Equipment Class .............................. 5-62

Figure 5.7.25 Cost-Efficiency Curve for the PD.SC.M Equipment Class ................................. 5-63

Figure 5.8.1 Illustration of Offset Factor using TDA as the Normalization Metric .................. 5-64

5-iv
CHAPTER 5. ENGINEERING ANALYSIS

5.1 INTRODUCTION

The engineering analysis establishes the relationship between manufacturer selling price

(MSP) and energy consumption for the commercial refrigeration equipment directly examined in 

this rulemaking. This equipment includes self-contained and remote condensing commercial 

refrigerators, freezers, refrigerator-freezers, and ice cream freezers, as well as self-contained 

commercial refrigerators with transparent doors designed for pull-down temperature 

applications. The “cost-efficiency” relationship, which depicts a manufacturer’s cost of 

achieving increased equipment efficiency for a given equipment class, serves as the basis for 

downstream cost-benefit calculations with respect to individual customers, manufacturers, and 

the nation. 

5.2 METHODOLOGY OVERVIEW

This section describes the analytical methodology that the U.S. Department of Energy 

(DOE) used for the engineering analysis. In this rulemaking, DOE adopted a design option 

approach to produce analytically derived curves depicting the cost-efficiency relationship for 

each equipment class analyzed. In a design option approach, the goal of the analysis is to 

calculate the incremental cost and energy consumption impacts of implementing specific energysaving technologies, known as “design options,” in a representative baseline design for a given 

equipment type. 

To implement the design option analysis in this rulemaking, DOE first selected specific 

classes of covered equipment for which to quantitatively calculate the manufacturing cost and

daily energy consumption directly (section 5.3.1). DOE analytically developed cost-efficiency 

relationships only for equipment classes with high shipment volumes, henceforth referred to as 

“primary” equipment classes. Some equipment classes were not included in the direct 

engineering analysis because they had low shipments volumes. These are referred to as 

“secondary” equipment classes. For each primary equipment class, a “representative” unit, 

intended to physically approximate a typical high-shipment-volume design currently on the 

market, was defined using sets of baseline parameters and specifications gathered from market 

research, industry publications, and manufacturer interviews (sections 5.3.2 and 5.5.2). This 

representative unit served as the point of analysis for the modeling of the equipment class that it 

represented. Baseline parameters were selected to represent the typical suite of technologies with 

which entry-level commercial refrigeration units available on the market at the time of this 

analysis were equipped. These parameters included specific physical attributes such as case 

volume, number of fans, and standard wall thickness. 

In order to explore the efficiency improvements available for use with the equipment 

analyzed, DOE conducted research into energy-saving technologies applicable for 

implementation into commercial refrigeration equipment. This research, performed using sources 

including manufacturer interviews and reviews of trade literature, is summarized in chapter 3 of 

this technical support document (TSD), Market and Technology Assessment. The results of that

analysis, a set of technology options, were compared against a set of screening criteria as 

described in TSD chapter 4, Screening Analysis. The outputs of the screening analysis were 

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considered in the engineering analysis, and it was from these technologies that design options 

were selected for quantitative modeling (sections 5.6.3–5.6.5). 

For each equipment class analyzed, DOE developed estimates of the cost to manufacture 

the representative unit at the baseline and higher efficiencies. In order to facilitate this, DOE 

developed estimates of the manufacturer production cost (MPC) of the unit at each design option 

level. DOE estimated two separate sets of costs in the analysis. The first of these was the cost to 

manufacture the refrigerated case of each representative unit. This “core case” consisted of 

components, such as structural members, shelving, wiring, air curtain grilles, and trim, that did 

not change at higher design option levels. Core case costs were developed through physical 

teardowns and cost modeling of equipment purchased on the market during the analysis period 

(section 5.4.1). The second set of cost data estimated the costs to manufacture and install the 

components that make up each design option. These were elements of the equipment, including 

heat exchangers, fans, glass doors, and lighting, that directly affected daily energy consumption 

and thus were manipulated in the engineering analysis. The costs for the design options were 

developed from a number of sources and corroborated with feedback from industry 

(section 5.4.2). Core case and design option costs were coupled to yield system MPCs for each 

representative unit at each level of efficiency modeled (section 5.4.3). 

In order to calculate estimates of daily energy consumption for each representative unit at 

each design option level examined, DOE developed an analytical model to simulate the 

performance of each unit, as configured, when tested under the DOE test procedure. This model 

used the representative unit specifications, design option data (section 5.6.5), test procedure 

provisions, and a set of assumptions (sections 5.6.1 and 5.6.2) to produce estimates of daily 

energy consumption for each equipment configuration studied. To produce these estimates, the 

model calculated the heat load placed on the given piece of equipment by the ambient conditions 

and heat-producing internal components. The model selected an appropriately-sized remote 

condensing or self-contained compressor and then calculated the electrical input energy into the 

compressor required to remove the heat load during the simulated test period. The additional 

energy consumption during the test period of energy-consuming components such as fans, 

defrost heaters, and lighting was also calculated, summed, and added to the compressor energy 

consumption as applicable to yield estimates of daily electrical energy consumption for each 

equipment configuration modeled (section 5.6.6).

DOE organized the results of the energy consumption and cost models in the form of 

cost-efficiency curves for each equipment class analyzed, depicting MPC versus daily energy 

consumption. To form the curves, DOE ordered the design options and their associated cost and 

energy consumption data based on cost effectiveness, ranging from the baseline to the maximum 

technologically feasible (“max-tech”) equipment configuration for each class. DOE then applied 

manufacturer markups and added outbound freight costs to the MPC estimates to express the 

relationship between MPC and MSP (section 5.5). The final result was a set of cost-efficiency 

curves comparing MSP and daily energy consumption at all modeled design option levels for 

each primary equipment class (section 5.7). 

Energy conservation standards for the covered equipment classes take the form of linear 

equations expressed as a function of refrigerated volume or total display area and defined by a 

slope and y-intercept. These equations were developed using the outputs of the engineering 

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analysis, with specific analysis points corresponding to calculated daily energy consumption 

(CDEC) values for each class. The engineering analysis contained an ancillary calculation 

necessary in developing standard-level equations for the covered equipment. Specifically, this 

calculation developed the y-intercept values, referred to in the January 2009 final rule analysis as 

“offset factors.” These offset factors serve to represent energy consumption end effects inherent 

in equipment operation regardless of the size of the equipment, and originated out of stakeholder 

concerns during the 2009 rulemaking that standards based on a single analysis point could be 

insufficient to account for the energy consumption of smaller pieces of equipment. The offset 

factors prevent the allowable maximum energy use from going towards zero at small volume or 

total display area (TDA) values. Section 5.8 further explains the offset factor methodology that 

DOE used in developing its standard-level equations. 

Another auxiliary analysis sought to develop standards for the secondary equipment 

classes that were not directly analyzed in the cost and energy consumption models. In the 

January 2009 final rule analysis, DOE developed standards for these equipment classes using 

energy-consumption conversion factors called “extension multipliers.” These factors were 

developed using analytical correlations between energy-consumption values for sets of 

equipment classes with similar features. The extension multipliers were then applied to the 

standard-level equations developed for the primary classes to obtain standard-level equations for 

secondary classes. DOE adopted these same extension multipliers in developing standard-level 

equations for the notice of proposed rulemaking (NOPR) stage of this rulemaking; this 

methodology is explained in detail in section 5.9. 

5.3 EQUIPMENT CLASSES ANALYZED

5.3.1 Classes Chosen for Analysis

In the Framework document, DOE provided a list of nomenclature consisting of 49 

equipment class designations. This list includes the 38 equipment classes for which standards 

were set in the 2009 rulemaking, as well as 11 class designations for equipment covered by 

standards set in the Energy Policy Act of 2005 (EPACT 2005). In its analyses for the 2009 DOE 

final rule on commercial refrigeration equipment, DOE only analyzed 15 high-shipment-volume 

equipment classes (“primary” classes) and then extended the standards developed from those 

analyses to cover the remaining 23 equipment classes with smaller number of shipments

(“secondary” classes). 74 FR 1092, 1121 (Jan. 9, 2009). Because DOE did not receive any 

comments or data indicating that there had been major changes in shipment patterns since the 

2009 final rule or other reasons that would necessitate a change in the primary classes, DOE 

elected to retain the primary equipment classes from the 2009 rulemaking. DOE also directly 

analyzed 10 of the 11 classes consisting of equipment previously covered by the EPACT 2005 

standards, with the exception of the SOC.SC.L class (a low-shipment-volume class that was 

treated as a secondary class). Combined with the 15 primary equipment classes from the 2009 

final rule, the result is a total of 25 primary equipment classes that were directly analyzed in this 

engineering analysis and a total of 49 equipment classes for which DOE has proposed standards. 

Table 5.3.1 shows the equipment classes for which amended standards are being 

considered in this rulemaking, organized by equipment family, condensing unit type, and rating 

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temperature, and highlights the 25 primary equipment classes that DOE directly analyzed in the 

engineering analysis. 

Table 5.3.1 Equipment Classes Analyzed in the Engineering Analysis

Equipment 

Family

Remote Condensing Self-Contained

Medium Low Ice 

Cream Medium Low Ice Cream

Without 

Doors

VOP   x  x x

SVO  x x  x x

HZO   x   x

With 

Doors

VCT   x   

VCS x x x   

HCT x x x   

HCS x x x   x

SOC  x x  * x

PD **    **  **

 Primary equipment class.

x Secondary equipment class

* Class not analyzed in this rulemaking; see section 5.3.3. 

** Classes not covered in the rulemaking.

HCS = Horizontal Closed Solid.

HCT = Horizontal Closed Transparent.

HZO = Horizontal Open.

PD = Pull-Down.

SOC = Service Over Counter.

SVO = Semi-Vertical Open.

VCS = Vertical Closed Solid.

VCT = Vertical Closed Transparent.

VOP = Vertical Open.

The engineering analysis specifically considered refrigerators (medium temperature), 

freezers (low temperature), and ice-cream freezers (ice-cream temperature) individually, but it 

did not explicitly consider refrigerator-freezers (combinations of compartments at medium and 

low temperatures) directly. Instead, DOE plans to maintain the approach used in the 2009 final 

rule, in which DOE developed a method to combine the standards for refrigerators, freezers, and 

ice-cream freezers to create standards for refrigerator-freezers. Similarly, while the engineering 

analysis did not explicitly consider hybrid equipment, consisting of multiple compartments from 

different equipment families contained in a single unit, the 2009 final rule presented a 

methodology for combining standards to create standards for hybrid units. DOE intends to 

preserve that methodology for use with all of the equipment covered this rulemaking. The 2009 

final rule Federal Register notice describes this methodology in detail. 74 FR 1092, 1122 

(Jan. 9, 2009). 

5.3.2 Baseline Equipment

For the engineering analysis, DOE modeled each primary class starting at a baseline 

design option level, increasing unit efficiency as design options were upgraded to higher 

technology levels. Baseline efficiencies were established by reviewing available manufacturer 

data regarding equipment available at the time of the analysis and selecting components and 

design features that were representative of the most basic, widely manufactured models being 

sold on the market. Due to the timing of this analysis, the units for sale on the market that DOE 

examined were not necessarily in compliance with the January 2009 final rule. This is because 

the January 2009 final rule standards had a compliance date of January 1, 2012, falling after the 

time frame for the NOPR engineering analysis. Therefore, DOE instead retained the baseline 

specifications and associated technologies used in the January 2009 final rule engineering 

analysis and expanded its sets of representative equipment specifications to include the 

5-4 
equipment classes covered under standards established by the Energy Policy and Conservation 

Act (EPCA). DOE believes that this is the best approach to addressing the baseline for this 

equipment, because sufficient information on equipment compliant with the 2009 standards was 

not available at the time of the engineering analysis. 

5.3.3 Service over Counter Equipment

In the preliminary analysis for this rulemaking, DOE chose not to include the SOC.SC.M 

equipment class in the engineering analysis because of ongoing issues with the standards set for 

that class by EPACT 2005. Standards prescribed in EPCA, as amended by EPACT 2005, for 

self-contained refrigerators and freezers with doors were based on the California Energy

Commission Appliance Efficiency Regulations published in April 2005. (CEC-400-2005-012, 

section 1605.3) The California Energy Commission regulations set standards for “reach-in 

cabinets, pass-through cabinets, and roll-in or roll-through cabinets.” However, EPCA does not 

explicitly outline such equipment subsets beyond defining the terms “commercial refrigerator, 

freezer, and refrigerator-freezer” and “self-contained condensing unit,” among other definitions 

related to this equipment. These EPCA definitions resulted in the application of these standards 

to all self-contained refrigerators, freezers, and refrigerator-freezers, including SOC.SC.M. 

In December 2009, DOE’s Office of Hearings and Appeals (OHA) responded to an 

application for exception relief from a manufacturer of service over counter equipment. This 

manufacturer argued that it was entitled to relief because its service over counter units could not 

meet the EPACT 2005 standards for self-contained equipment with doors. OHA responded that 

DOE did not have jurisdiction to consider such exceptions for equipment covered by the 

statutorily mandated standards. (Case no. TEE-0066, Dec. 29, 2009) 

In response to the concerns manufacturers expressed in comments at the Framework 

public meeting and in written comments, as part of its preliminary analysis for this rulemaking

DOE compared the standards set for a specific type of service over counter units in the 2009 

final rule, namely remote condensing medium-temperature units, with the EPACT 2005 

standards for self-contained commercial refrigerators with transparent doors, which include selfcontained service over counter units. For a full description of the analysis and results, please see 

section 5.3.3 of the preliminary analysis TSD chapter 5. This analysis showed that SOC.SC.M 

equipment was not capable, even at the max-tech level, of meeting the required standard level set 

by EPACT 2005 for self-contained refrigerators with transparent doors. For that reason, and 

because DOE did not have the authority to lessen the stringency of the legislatively prescribed 

EPACT 2005 standards, DOE excluded SOC.SC.M equipment from its analysis. 

In December 2012, while the NOPR analysis for the current rulemaking was in progress, 

the American Energy Manufacturing Technical Corrections Act (AEMTCA), Pub. L. 112-210 

(2012), amended EPCA to establish standards for self-contained service over counter 

refrigerators that belong to the equipment class SOC.SC.M. Paragraph (3) of section 4 of 

AEMTCA states as follows: “Each SOC-SC-M manufactured on or after January 1, 2012, shall 

have a total daily energy consumption (in kilowatt hours per day) of not more than 0.6 × TDA + 

1.0.” AEMTCA also directed DOE to determine, within three years of January 1, 2012, whether 

the standard established for equipment class SOC.SC.M should be amended, and if DOE 

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determines that the standard should be amended, DOE should issue a final rule establishing an 

amended standard within 3 years of January 1, 2012. 

The inclusion of this language in EPCA by way of AEMTCA allowed DOE to fully 

analyze the SOC.SC.M equipment class along with all other primary equipment classes in this 

rulemaking, and to propose a standard level to satisfy the requirement that DOE make a 

determination of amendment of standards within 3 years of January 1, 2012. 

5.4 COST MODEL

One major output of the engineering analysis is the development of costs for the 

representative units analyzed at the baseline and at each higher design option level. These values

were developed using a cost model that was divided into two parts for this rulemaking. The first 

of these was as standalone core case cost model, based on physical teardowns, that was used for 

developing the core case costs for the cabinets of each of the 25 directly analyzed classes. These 

core case costs consisted of the costs to manufacture the refrigerated case itself, consisting of 

structural members, insulation, shelving, wiring, etc., without the components that could directly 

affect energy consumption. The second part of the cost model was a component of the 

engineering analytical model, and operated in unison with the energy consumption model). This 

model received inputs in the form of the core case costs and the prices for design options 

implemented at and above the baseline, such as baseline and improved glass doors, higherefficiency compressors, and higher-efficiency lighting. These two sets of data (core case costs 

and design option costs) were used to build up total system costs for each representative unit at 

each design option level modeled. 

5.4.1 Development of Core Case Costs 

The development of the case costs was based on physical teardowns of units available on 

the market at the time of the analysis. The first step in the assessment was the creation of a 

complete and structured bill of materials (BOM) from the disassembly of commercial 

refrigeration equipment from selected equipment classes. DOE dismantled each unit and 

characterized each part of the units according to weight, manufacturing processes, dimensions, 

material, and quantity. The result was a set of BOMs that included the costs for materials, 

components, and fasteners, and contained estimates for the cost of raw materials and purchased 

parts, and other costs such as labor, depreciation, and overhead costs. DOE based assumptions 

about the sourcing of parts and in-house fabrication on industry experience, information from

trade publications, and discussions with manufacturers. DOE conducted interviews and plant 

visits with manufacturers to ensure accuracy in methodology and pricing. 

The BOMs from the teardowns were fed into a factory model to produce estimates of 

MPCs for each of the units analyzed. Those estimates were then expanded to produce case costs 

for the equipment classes not directly examined via teardown. The cost model was based on 

production activities and divided factory costs into the categories shown in Table 5.4.1. 

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Table 5.4.1 Cost Model Output Classifications 

Major 

Category Sub-Category Description

Material Costs Direct Raw materials (e.g., coils of sheet metal) and purchased parts (e.g., 

fasteners, wiring)

Indirect Supplies (e.g., welding rods, die oil, release media)

Labor

Assembly Parts / unit assembly on manufacturing line

Fabrication Conversion of raw material into parts ready for assembly

Indirect

Fraction of overall labor not associated directly with equipment

fabrication or assembly (e.g., forklift drivers, quality control, 

purchasing of raw material and tools)

Supervisory Fraction of assembly, fabrication, and indirect labor is paid a higher 

wage 

Depreciation

Equipment, Conveyor, 

Building Straight-line depreciation over expected life.

Tooling Cost is allocated on a per-use basis or obsolescence, whichever is 

shorter

Other 

Overhead

Utilities A fixed fraction of all material costs meant to cover electricity and 

other utility costs

Facility and 

Equipment 

Maintenance

Based on installed equipment and tooling investment

Property Tax and 

Insurance A fixed fraction based on total unit costs

The cost model analysis created cost estimates for each of the commercial refrigeration 

equipment units analyzed. The cost model used certain assumptions to provide cost estimates; 

the following sections describe those assumptions. 

5.4.1.1 Selection of Units for Teardown Analysis 

The selection of units for physical teardown analysis was performed in a manner so as to 

allow for the greatest coverage of the range of equipment modeled in this analysis and to provide 

sufficient data to allow for the expansion of the modeling to classes for which teardowns were 

not performed. This equipment covered all of the equipment families except for the HZO family, 

and spanned all three of the DOE rating temperatures. All of the equipment selected for teardown 

was self-contained equipment so that DOE could gain additional data for its modeling of other 

components (e.g., coils and compressors) by analyzing the self-contained refrigeration systems. 

The equipment was chosen from the product lines of major manufacturers and at sizes similar to 

what DOE had determined to be an appropriate representative unit size for the given equipment 

class. All of the equipment selected for teardown analysis was at the current market baseline, 

without any customization or options intended to improve energy efficiency beyond the standard 

catalog offerings. 

5.4.1.2 Manufacturer Production Cost Estimates and Assumptions

MPC includes the sum of direct labor, direct material, and overhead, including 

investment depreciation. The cost of specific models―or costs to individual 

manufacturers―will vary, depending on the equipment’s precise characteristics, the actual 

manufacturing processes, the equipment mix in the factory, and other elements. There are also 

5-7 
considerable differences in the levels of vertical integration (companies with a large market share 

and/or revenue base tend to be more vertically integrated than their smaller competitors) that 

affect cost structure and thus the cost of equipment. Yet, DOE assumed that all manufacturers 

buy at least some of their parts and/or subsystems from outside vendors. 

The commercial refrigeration equipment market includes manufacturers that build a wide 

range of equipment—from mass-produced equipment to tailored, one-of-a-kind units. Most 

equipment listed in catalogs consists of general-purpose models that can then be customized to 

meet the particular needs of customers. Depending on the manufacturer and the degree of 

customization, engineering costs can thus represent a significant portion of the MPC for some 

producers of this equipment. 

DOE built a parametric model that allowed the scaling of most input factors. The 

assumptions behind the model are based on published data by manufacturers, general industry 

practice (based on site visits), manufacturer interviews, and previously published DOE reports. 

DOE compared the model results to published unit data and list prices. For example, DOE 

compared listed shipping weights with the calculated weights for cabinets of representative units

as a method of checking its results. 

The lack of detailed teardowns for every equipment class and the varying degrees of 

vertical integration in the industry made calculating representative investment requirements 

difficult. Not only does the market share vary for each manufacturer across every equipment 

class, the scale of operations also varies greatly. It is also quite likely that high-volume 

manufacturers derive a cost advantage based on their purchasing volume for common raw 

materials and purchased parts alike. Lacking detailed data, DOE did not try to account for lowversus high-volume purchasing power in the development of the cost model, instead using 

industry-averaged aggregate data to represent all equipment offerings modeled. 

5.4.1.3 Structure of the Cost Model

DOE used a detailed, component-focused manufacturing cost assessment methodology to 

estimate the MPC of each equipment class analyzed in the cost model, taking into account, for 

example, direct materials, direct labor, and factory overhead costs. 

Following the development of detailed BOMs for each piece of equipment physically 

examined, DOE identified the major manufacturing processes and developed the spreadsheet 

model. Table 5.4.2 lists these examples of these processes. 

Table 5.4.2 Examples of Major Manufacturing Processes

Fabrication Finishing Assembly/Joining

Fixturing Washing Adhesive bonding

Stamping/pressing Powder coating Spot welding

Brake forming De-burring Seam welding

Cutting and shearing Polishing Inspecting and testing

Insulating — —

DOE estimated fabrication process cycle times and entered them into the BOM. For this 

analysis, DOE estimated an average fully burdened hourly cost of labor based on the typical 

5-8 
annual wages and benefits of industry employees. In the final step of the cost assessment, DOE 

estimated assembly times and associated direct labor costs. 

Once the cost estimate for each unit was finalized, DOE prepared a detailed summary of 

relevant components, subassemblies, and processes. Because the intent of this cost modeling 

sub-analysis was solely to yield costs for the refrigerated case structures and not the design 

option components, assemblies accounted for by the design options (e.g., glass doors, heat 

exchangers) were stripped away from the BOMs for each unit. The result was a set of costs 

corresponding to the MPCs for the core cases of each of the unit types analyzed.

The final step in the cost modeling process was to expand the results to apply to the 

remainder of the primary equipment classes for which teardowns were not performed. To 

achieve this, DOE added parametric scaling features to the model, which allowed the teardown 

units to be virtually scaled by size within the model. It also allowed material types, numbers of 

components, etc. to be modulated in order to best simulate the construction of representative 

units from other equipment classes. DOE incorporated features into these additional BOMs to 

reflect the necessary changes between equipment classes. For example, receiver valves were 

added to the models for remote condensing cases, and additional insulation thickness was taken 

into account for ice cream equipment. DOE utilized manufacturer data sheets and information 

gathered from interviews to aid in the modeling of these cases. The end result was a full set of 25 

core case costs, which served as the starting point for the development of whole-system costs at 

the baseline and improved design option levels in the engineering model. 

5.4.1.4 Material Prices

The cost model uses multiple proprietary databases to determine raw material costs and 

purchased part prices. Most prices are based on the most up-to-date data that the DOE has been 

able to obtain. The sole exceptions are metals prices, which are averaged over a 5-year period to 

reduce price volatility. Metals prices can have a large impact on the overall raw material costs 

and picking any particular point in time to select a raw material cost may hence lead to a 

distorted MPC. 

As a general example, most refrigeration appliances contain significant amounts of 

copper in their heat exchangers, tubing, etc. Additionally, commercial refrigeration equipment is 

frequently externally clad in stainless steel for wash-down purposes. Figure 5.4.1 depicts copper 

and 304-series stainless steel price trends in the United States from 2002 to mid-2012. Note the 

extreme dip for both stainless steel and copper raw material costs in 2008. The price of copper 

more than halved from its previous high in 2007, a level that copper has since surpassed. In the 

example, the 5-year average price for copper is currently nearly a $1/lb lower than the current 

price while the two prices are about equivalent for 304-series stainless steel.

5-9 
Figure 5.4.1 Copper and Stainless Steel Price Trends

By averaging metals raw materials costs over a 5-year period, the analysis is less affected 

by metals price volatility. The swings for other inputs (e.g., plastics, purchased parts) are not as 

pronounced and hence current prices are used for them. Past quotes for materials and purchased 

parts are inflated using Bureau of Labor Statistics data and other sources, such as American 

Metal Market. Purchased part prices and raw material costs are reviewed with manufacturers at 

the appropriate purchasing volumes for accuracy. 

5.4.1.5 Results

The result of the development of the core case cost model, generation of BOMs, 

parameterization, and extension of the cost model to classes for which physical teardowns were 

not performed was a set of 25 core case cost values. These values comprise the cost, for each 

representative unit, of manufacturing the housing, structural members, shelving, solid doors, 

wiring, and other components of the refrigerated case that do not vary by design option level. 

These core costs were entered into the engineering model and served as the starting points from 

which the costs of the units at various design option levels were developed. 

5.4.2 Design Option Costs 

Design option costs were developed independently of costs for the core case and were 

procured through a combination of manufacturer estimates, wholesalers’ prices, list prices, and 

other sources. These data included the pricing information for components, including glass 

doors, compressors, lighting, heat exchangers, night curtains, and other componentry considered 

as design options. For a listing of all components considered as design options, please see 

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section 5.6.5. Data provided by industry through interviews were aggregated across all 

manufacturers and, where relevant, combined with cost data obtained from other sources to 

provide a general estimate of the prices paid by industry for baseline and higher efficiency 

components for each design option. For further details regarding the specific design options, 

please see section 5.6.5. 

5.4.2.1 Light-Emitting Diode Price Forecasting

After release of the preliminary analysis documents for this rulemaking, DOE received 

comments from stakeholders stating that forecasts of the light-emitting diode (LED) lighting 

industry, including those performed by the Department, suggest that LED lighting is an emerging 

technology that will continue to experience significant price decreases in coming years. For this 

reason, in an effort to capture the anticipated cost reduction in LED fixtures in the analyses for 

this rulemaking, DOE incorporated price projections from its Solid State Lighting program into 

its MPC values for the primary equipment classes. The price projections for LED case lighting 

were developed from projections developed for the DOE’s Solid State Lighting Program’s 2012 

report, Energy Savings Potential of Solid-State Lighting in General Illumination Applications 

2010 to 2030 (“the energy savings report”). In the appendix of this report, price projections from 

2010 to 2030 were provided in $/klm for LED lamps and LED luminaires. DOE analyzed the 

models used in the Solid State Lighting program work and determined that the LED luminaire 

projection would serve as an appropriate proxy for a cost projection to apply to refrigerated case 

LEDs.

The price projections presented in the Solid State Lighting program’s energy savings 

report are based on the DOE’s 2011 Solid State Lighting R&D Multi-Year Program Plan 

(MYPP). The MYPP is developed based on input from manufacturers, researchers, and other 

industry experts. This input is collected by the DOE at annual roundtable meetings and 

conferences. The projections are based on expectations that depend on the continued investment 

into solid-state lighting by the DOE.

DOE incorporated the price projection trends from the energy savings report into its 

engineering analysis by using the data to develop a curve of decreasing LED prices normalized 

to a base year. That base year corresponded to the year when LED price data was collected from 

catalogs, manufacturer interviews, and other sources for the NOPR analyses of this rulemaking. 

DOE started with this LED cost data specific to commercial refrigeration equipment and then 

applied the anticipated trend from the energy savings report to forecast the projected cost of LED 

fixtures for this equipment at the time of required compliance with the proposed rule (2017). 

These 2017 cost figures were incorporated into the engineering analysis as comprising the LED 

cost portions of the MPCs for the primary equipment classes. 

5.4.3 Representative Unit Manufacturer Production Cost Values

For each representative unit analyzed in the engineering analysis, the analytical model 

calculated a cost at the baseline, as well as a cost at each design option level above the baseline

up to the max-tech level. This was achieved by starting with the core case cost, developed as 

discussed in section 5.4.1, and adding to it the costs of the design options needed to represent all 

the components in a complete unit of the given equipment class. For example, a VCT self5-11
contained refrigerator would require the core case cost plus the cost of its evaporator and 

condenser coils and fans, compressor, glass doors, and lighting to yield a baseline MPC. For 

units above the baseline, costs for improved design option levels were substituted by the 

analytical model in the order in which those design options were implemented. 

5.5 MANUFACTURER SELLING PRICE 

The MSP is the price of the equipment when it is sold by the manufacturer to the first 

party in the distribution chain. It includes all direct and indirect production costs, manufacturer 

markup, and the cost of shipping the units from the manufacturer to the first party in the 

distribution chain. The components of MSP are shown in greater detail in Figure 5.5.1. 

Figure 5.5.1 Components of Manufacturer Selling Price

The MSP is expressed as the product of the MPC and the manufacturer markup, added to 

the outbound shipping cost, as shown in Eq. 5.1: 

MSP MPC markup +×= shipping

Eq. 5.1 

The markup and shipping costs are described in the following subsections. 

5.5.1 Manufacturer Markup

In its engineering analysis, DOE included manufacturer markup in the estimates of MSP. 

This markup consists of a value applied to the MPC estimates that accounts for non-productioncost elements of the MSP, including selling, general and administrative costs, research and 

development, interest, and profit. The manufacturer markup was calculated as a market share 

weighted average value applied to the entire industry. DOE developed this manufacturer markup 

by examining several major commercial refrigeration equipment manufacturers’ gross margin 

information from annual reports and Securities and Exchange Commission (SEC) 10-K reports.

Most of these companies are subsidiaries of more diversified parent companies that manufacture 

equipment other than commercial refrigeration equipment. Because the 10-K reports do not 

MSP

Manufacturer Production Cost

Direct 

Labor

Direct 

Material Overhead Depreciation

Non Production Costs Profit

EBIT

Research & 

Development 

Costs

Other 

Costs

Selling, 

General, and 

Administrative 

Costs

Shipping

Manufacturer Markup

5-12
provide gross margin information at the subsidiary level, the estimated markups represent the 

average markups that the parent company applies over its entire range of equipment offerings 

and does not necessarily represent the manufacturer markup of the subsidiary. In its preliminary 

analysis, DOE estimated the average manufacturer markup to be 1.39. Based on further analysis 

and discussion with manufacturers during the NOPR stage of this rulemaking, DOE has adjusted 

this average manufacturer markup value to 1.42. 

5.5.2 Representative Units

For each of the primary equipment classes analyzed in the engineering analysis, DOE 

developed a representative unit for which the cost and energy consumption would be modeled at 

each design option level. 

DOE defined each representative unit quantitatively in the form of a set of design 

specifications at the baseline. These specifications included case dimensions, numbers of 

components, nominal power ratings, and other features that were necessary to calculate the 

energy consumption of a given unit. Table 5.5.1 shows the specifications that DOE defined for 

each representative unit. Not all specifications shown are applicable to every equipment class 

modeled (e.g., specifications relating to doors would be inapplicable to open equipment). 

Table 5.5.1 Representative Unit Specifications

Specification Units

Case length ft

Case gross refrigerated volume ft3

Case total display area ft2

Number of doors #

Single door area ft2

Non-door glass area ft2

Non-door anti-sweat power W

Wall area (ft2) ft2

Insulation thickness In.

Case interior surface area ft2

Air curtain angle from vertical °

Infiltrated air mass flow lb/hr

Number of bulbs in conditioned space #

Number of bulbs not in conditioned space #

Number of ballasts in conditioned space #

Number of ballasts not in conditioned space #

Evaporator fan nominal rated wattage W

Number of evaporator fans per case #

Condenser fan nominal rated wattage W

Number of condenser fans per case #

Discharge air temperature (DAT) °F

Baseline evaporator temperature (SET) °F

Baseline saturated condenser temperature (SCT) °F

Compressor oversize multiplier #

Defrost mechanism n/a

Defrost time per day hr

Defrost and drain heater power W

Condensate pan heater power W

5-13
In conjunction with the lowest technological level of each design option (section 5.6.5), 

these specifications were used in the engineering model to define the energy consumption and 

cost of baseline equipment on the market. The specifications that did not vary as a function of 

any design option (e.g., case volume) were held constant from the baseline through to the maxtech configuration. Others (e.g., discharge air temperature) were modified due to the 

implementation of higher technological levels of various design options. At these higher design 

option levels, the updated specifications were used to produce cost-efficiency data for more 

efficient equipment. 

DOE established the baseline design specifications by reviewing available manufacturer 

data for equipment models offered across the range of available units within a given class. 

DOE focused this review on units exhibiting sizes and design characteristics that DOE had found 

through its market research to be most representative of the highest shipment volume offerings at 

the baseline for each equipment class analyzed. The aggregated data from this analysis were used 

to develop a representative unit for each equipment class with typical characteristics for physical 

parameters (e.g., volume, TDA) and design features (e.g., number of fans, number of light 

fixtures). Appendix 5A of this TSD provides these numerical specifications for each equipment 

class.

5.5.3 Shipping Costs

The third constituent component of the MSP, in addition to the MPC and the 

manufacturer markup, is the cost to ship the unit from the manufacturing facility to the first point 

on the distribution chain. Manufacturers stated that the specific party (manufacturer or buyer) 

that incurs that cost for a given shipment may vary based on the terms of the sale, the type of 

account, the manufacturer’s own business practices, and other factors. However, for consistency, 

DOE includes shipping costs as a component of MSP. In calculating the shipping costs, DOE 

first gathered estimates of the costs to ship a full trailer of manufactured equipment an average 

distance in the United States. DOE then used the representative unit sizes to calculate a volume 

for each unit. Along with the dimensions of a shipping trailer and a loading factor to account for 

inefficiencies in packing, DOE used this cost and volume information to develop an average 

shipping cost for each equipment class directly analyzed. 

5.6 ENERGY CONSUMPTION MODEL

The energy consumption model is the second key analytical model used in constructing 

cost-efficiency curves and is implemented in the engineering analysis spreadsheet. This model 

estimates the CDEC of commercial refrigeration equipment in kilowatt-hours (kWh) at various 

performance levels using a design option approach. The model is specific to the types of 

equipment covered under this rulemaking (described in chapter 3 of the TSD), but is sufficiently 

generalized to model the energy consumption of all covered equipment classes. DOE developed 

the energy consumption model, coupled with the system cost model, as a Microsoft Excel 

spreadsheet.

For a given equipment class, the model estimates the daily energy consumption for the 

baseline and the energy consumption of subsequent levels of performance above the baseline.

The model calculates the energy consumption of each design option level separately. 

5-14
5.6.1 Non-Numerical Assumptions

In developing the energy consumption model, DOE made certain general non-numerical 

assumptions about the analysis, as well as specific assumptions about load components and 

design options. 

DOE based its analysis on the modeling of new equipment tested in a controlledenvironment chamber subjected to the provisions of the DOE commercial refrigeration 

equipment test procedure. 77 FR 10292 (February 21, 2012). This test procedure incorporates 

Air-Conditioning, Heating, and Refrigeration Institute (AHRI) 1200-2010, which references the 

American National Standards Institute (ANSI)/American Society of Heating, Refrigerating and 

Air-Conditioning Engineers (ASHRAE) Standard 72-2005 (ASHRAE 72), Method of Testing 

Commercial Refrigerators and Freezers. Lighting occupancy sensors and scheduled controls, as 

well as night curtains, were modeled in the energy consumption model as specified in the DOE 

test procedure. Manufacturers that certify their equipment to comply with Federal standards will 

be required to test new units to this test method, which specifies ambient temperature, humidity, 

light level, and other requirements. 

In performing the energy consumption calculations, DOE used normalized hourly 

refrigeration load values for calculating compressor power. When options such as lighting 

controls and occupancy sensors or night curtains were implemented over a portion of the 24-hour 

period, the energy savings during these periods were distributed across all 24 hours. Then, the 

average heat load per hour was used in combination with the calculated compressor energy 

efficiency ratio (EER) to determine daily compressor energy consumption. However, the model 

selected the appropriate compressor size based upon the maximum load (i.e., the load without 

night curtains or occupancy sensors) to ensure sufficient heat-removal capacity. Normalization of 

heat loads was performed for the purposes of simplifying calculations and does not impact the 

final results. 

DOE did not include a pull-down load associated with re-shelving products because the 

test procedure does not address product re-shelving. Product re-shelving is the act of loading new 

products into refrigerated display cases as existing products are sold. Typically, commercial 

refrigeration equipment is not designed to pull down the temperature of warm products, but only 

to display products that were already chilled or frozen in a refrigerated storage unit. An 

exception to this is in the case of beverage merchandisers, which are represented by the pulldown class included in this rulemaking analysis; however, this equipment is still tested at steady 

state, so pull-down load effects will not be quantified by testing. 

While DOE did account for the heat load introduced into a case by defrost heaters, as 

well as the energy consumption of those heaters, DOE assumed that there are no pull-down loads 

associated with post-defrost periods. During defrost periods, the compressor (or the flow of 

refrigerant for remote condensing cases) stops and the coil warms to a temperature above 

freezing (aided by electric resistance heating in the case of electric defrosts). After the evaporator 

coil has been cleared of frost, the merchandise in the case will typically have warmed several 

degrees. The merchandise must be returned to normal operating temperature when the 

refrigeration cycle resumes, adding an additional load to the condensing unit. Between 

equipment families and even within equipment classes there is a large variation in defrost 

5-15
mechanism, defrost cycle time, temperature recovery time, and product mass. Because of the 

uncertainty of these factors, DOE was unable to calculate the defrost pull-down load with 

sufficient certainty and did not include it in the model, but understands the impact of this 

phenomenon on daily energy consumption to be very small. 

5.6.2 Numerical Constants and Assumptions

In developing the energy consumption model, DOE identified constants and made 

assumptions concerning numerical values used in the analysis. These include ambient conditions, 

financial assumptions, and parameters necessary to calculate the component and non-electric 

loads. Table 5.6.1 shows details of these assumptions. 

Table 5.6.1 Energy Consumption Model Numerical Constants and Assumptions 

Numerical Constants and Assumptions Value Source

Test chamber temperature (°F) 75 ASHRAE 721

Test chamber relative humidity (%) 55 ASHRAE 721

Test chamber pressure (pounds per square in 

(psi), absolute) 14.7 Assumed

Manufacturer markup ($/$) 1.42 Publicly available corporate financial data

Fraction of anti-sweat heater power into case 

(W/W) 0.7 DOE estimate based on discussions with manufacturers

Fraction of lighting power into case for 

lighting outside of air curtain (W/W) 0.5 Electric Power Research Institute (EPRI), Supermarket Simulation Tool v3.02

Lighting operating time per day (hr) 24 Assumed – for cases without occupancy sensors

Convective film coefficient inside case walls

(Btu/hr-ft2-°F) 4.00 Communication with the Southern California Edison Refrigeration & Thermal Test Center (RTTC)

Convective film coefficient outside case 

walls (Btu/hr-ft2-°F) 1.46 Communication with RTTC

Overall U-factor of single-pane glass 

(Btu/hr-ft2

-°F) 1.059 Lawrence Berkeley National Laboratory WINDOW 

5 Software6

Emissivity of test chamber walls (-) 0.9 Communication with RTTC

Emissivity of case inner walls (-) 0.9 Communication with RTTC

Area of test chamber walls (ft2) 1,000 Communication with RTTC

Case interior relative humidity (%) 65 R. Faramarzi, Efficient Display Case Refrigeration, 

ASHRAE Journal, November 19993

Evaporator coil overall bypass factor (%) 17 DOE estimate

High-efficiency compressor cost premium 5% Communication with manufacturers

High-efficiency compressor power reduction 10% Communication with manufacturers

5.6.3 Screened-In Technologies

The technology options that were analyzed (i.e., were not screened out as part of the 

screening analysis, chapter 4) are as follows:

• higher efficiency lighting 

• higher efficiency lighting ballasts

• remote lighting ballast location

• higher efficiency evaporator fan motors 

• variable-speed evaporator fan motors and evaporator fan motor controllers 

• improved evaporator coil design 

5-16
• higher efficiency evaporator fan blades 

• low-pressure differential evaporators

• case insulation increases or improvements 

• improved transparent doors 

• defrost mechanisms 

• defrost cycle controls 

• vacuum insulated panels 

• occupancy sensors for lighting controls 

• anti-fog films on transparent doors 

• night curtains (equipment without doors only) 

• higher efficiency compressors (self-contained equipment only) 

• improved condenser coil design (self-contained equipment only) 

• higher efficiency condenser fan motors (self-contained equipment only) 

• higher efficiency condenser fan blades (self-contained equipment only)

5.6.4 Screened-In Technologies Not Considered in the Engineering Analysis

In the market and technology assessment (chapter 3 of the TSD), DOE defined an initial 

list of technologies that can reduce the energy consumption of commercial refrigeration 

equipment. In the screening analysis (chapter 4), DOE first shortened this list by eliminating 

from consideration those technologies that could potentially reduce field energy consumption of 

commercial refrigeration equipment but do not reduce energy consumption as measured by the 

DOE test procedure, because the test procedure conditions and requirements do not allow for 

these technologies to have a significant impact on the energy consumption values. These include 

location of remote lighting ballasts, variable speed evaporator motors and evaporator fan motor 

controllers, higher efficiency evaporator and condenser fan blades, insulation low-pressure 

differential evaporators, defrost cycle controls, and defrost mechanisms. 

5.6.4.1 Remote Lighting Ballast Location 

Relocation of fluorescent lamp ballasts outside the refrigerated space can reduce energy 

consumption by lessening the refrigeration load on the compressor. However, for the majority of 

commercial refrigeration equipment currently manufactured, ballasts are already located in 

electrical trays outside the refrigerated space, in either the base or top of the equipment. The 

notable exceptions are the equipment classes in the VCT equipment family, where ballasts are 

most often located on the interior of each door mullion. 

Most commercial refrigeration equipment manufacturers purchase doors for VCT units 

that are preassembled with the entire lighting system in place rather than configured for separate 

ballasts. DOE believes that most commercial refrigeration equipment manufacturers choose 

these kinds of doors because it would be labor intensive and time consuming to relocate these 

ballasts at the factory and wire separate ballasts. This also aligns with the manufacturing 

practices of the door manufacturers, who often produce similar door designs, with integrated 

lighting, for many equipment types. Also, the potential energy savings are small because modern 

electronic ballasts are very efficient and do not significantly impact the refrigeration load. 

Therefore, DOE did not consider remote relocation of ballasts as a design option. 

5-17
5.6.4.2 Variable-Speed Evaporator Fan Motors and Evaporator Fan Motor 

Controllers

Variable-speed evaporator fan motors, as well as evaporator fan motor controllers, allow 

fan motors to run at variable speed to match changing conditions inside the case. In practice, 

there is some opportunity for energy savings because the pressure drop of air moving across the 

evaporator coil varies significantly depending on the level of frost buildup on the coil. 

Theoretically, less fan power is required when the coil is free of frost, and variable-speed motors 

or controllers could adapt motor operation to these conditions. Moreover, such a system would 

also allow the coil to operate at a more stable temperature during frost buildup by varying fan 

speed proportionally. 

However, there are also negative attributes to the implementation of such technologies. 

For example, the effectiveness of the air curtain in equipment without doors is very sensitive to 

changes in airflow, and fan motor controllers could disrupt the air curtain. The potential of 

disturbance to the air curtain, which could lead to higher infiltration loads, does not warrant the 

use of evaporator fan motor controllers in equipment without doors, even if there were some 

reduction in fan energy use. With respect to equipment with doors, DOE, in its discussions with 

manufacturers, found that there are concerns in industry about the implementation of variablespeed fan technology due to the need to meet food safety and maximum temperature 

requirements. Varying the fan speed would reduce the movement of air within the case, 

potentially leading to the development of “hot spots” in some areas of the case, where 

temperatures could exceed the desired value. Some industry representatives also stated that the 

use of such controllers could have unintended consequences, in which fans would be 

inadvertently run at full power to attempt to overcome a frosted or dirty coil, resulting in wasted 

energy. Due to the uncertainties that exist with these technologies, DOE did not consider 

variable-speed evaporator fan motors or evaporator fan motor controllers as a design option. 

5.6.4.3 Higher Efficiency Evaporator and Condenser Fan Blades

Higher efficiency evaporator and condenser fan blades reduce motor shaft power 

requirements by moving air more efficiently. Current technology used in commercial 

refrigeration equipment is stamped sheet metal or plastic axial fan blades. These fan blades are 

lightweight and inexpensive. DOE was not able to identify any axial fan blade technology that is 

significantly more efficient than what is currently used, but did identify one alternative fan blade 

technology that might improve efficiency: tangential fan blades. They can produce a wide, even 

airflow, and have the potential to allow for increased saturated evaporator temperature (SET) 

through improved air distribution across the evaporator coil, which would reduce compressor 

power. However, tangential fan blades in small sizes are themselves less efficient at moving air, 

and thus require greater motor shaft power. Because of these competing effects, DOE did not 

consider tangential fan blades as a design option. 

5.6.4.4 Low-Pressure Differential Evaporators

Low-pressure differential evaporators reduce energy consumption by reducing the power 

of evaporator fan motors, often by increasing the air gap between fins. However, in spaceconstrained equipment such as commercial refrigeration equipment, this reduction usually comes 

5-18
from a decrease in evaporator coil surface area, which generally requires a lower SET to achieve 

the same discharge air temperature and cooling potential. This, in turn, results in a reduction in 

compressor efficiency. Because of these competing effects, DOE did not consider low-pressure 

differential evaporators as a design option. 

5.6.4.5 Defrost Cycle Control

Defrost cycle control can reduce energy consumption by reducing the frequency and 

duration of defrost periods. The majority of equipment currently manufactured already uses 

partial defrost cycle control in the form of cycle temperature-termination control. However, 

defrost cycle initiation is still scheduled at regular intervals. Full defrost cycle control would 

involve a method of detecting frost buildup and initiating defrost. As described in the market and 

technology assessment (chapter 3), this could be accomplished through an optical sensor or 

sensing the temperature differential across the evaporator coil. However, DOE understands that 

both of these methods are currently unreliable due to fouling of the coil with dust and other 

surface contaminants, which becomes more of an issue as cases age. Because of these issues, 

DOE did not consider defrost cycle control as a design option. 

5.6.4.6 Defrost Mechanisms

Defrosting for medium-temperature equipment is typically accomplished with off-cycle 

defrost. Because off-cycle defrost uses no energy (and decreases compressor on-time), there is 

no defrost design option capable of reducing defrost energy in cases that use off-cycle defrost.

Some medium-temperature cases and all low-temperature and ice-cream temperature cases use 

supplemental heat for defrost. Electric resistance heating (electric defrost) is commonly used in 

these cases. An alternative to electric defrost in those cases that require supplemental defrost heat

is hot-gas defrost. This defrost mechanism involves using the hot compressor discharge gas to 

warm the evaporator from the refrigerant side. Manufacturers told DOE during interviews that 

the use of hot-gas defrost is a subject of division within the industry, with some manufacturers 

employing it on many of their models and others using it very rarely, if at all. These 

manufacturers mentioned various positive and negative attributes of the technology, depending 

on their stance on the issue. However, independent of the technical factors related to 

implementation of hot-gas defrost, the test procedure for commercial refrigeration equipment is 

not capable of quantifying the energy expenditure of the compressor during a hot-gas defrost 

cycle for remote condensing equipment. Therefore, DOE did not consider hot-gas defrost as a 

design option. 

5.6.4.7 Anti-Fog Films on Transparent Doors 

Anti-fog films are offered as an option by some manufacturers on their transparent 

display doors and consist of advanced hydrophobic materials that are applied to the glass surface 

on the inside of the door. Without such coatings, condensation can attach to the glass surface and 

form beads, resulting in visible fog that can obscure views of the product. These materials cause 

the water to instead simply slide off the surface of the door, maintaining a clear appearance. 

However, DOE understands that these films alone do not necessarily eliminate the need for antisweat heaters in many cases, including conditions of high ambient humidity, as these films do 

not eliminate the issue of potential condensation on the outside of the case, which can present a 

5-19
major problem for consumers. Moreover, DOE understands that delamination of anti-fog films 

presents a major issue, making them unreliable in the long term. Discussions with manufacturers 

have led DOE to believe that other improvements in door construction provide the capacity to 

reduce anti-sweat heat without the drawbacks previously discussed. Because of these issues, 

DOE did not consider anti-fog films on transparent doors as a design option. 

5.6.5 Design Options

After conducting the screening analysis and removing from consideration those 

technologies described above, DOE implemented the remaining technologies as design options 

in the energy consumption model: 

• higher efficiency lighting and occupancy sensors for VOP, SVO, and SOC equipment 

families (horizontal fixtures) 

• higher efficiency lighting and occupancy sensors for VCT and PD equipment families

(vertical fixtures)

• improved evaporator coil design 

• higher efficiency evaporator fan motors 

• improved case insulation 

• improved doors for VCT equipment family, low and ice-cream temperature 

• improved doors for VCT and PD equipment families, medium temperature 

• improved doors for HCT equipment family, low and ice-cream temperature 

• improved doors for HCT equipment family, medium temperature 

• improved doors for SOC equipment family, medium temperature 

• improved condenser coil design (for self-contained equipment only) 

• higher efficiency condenser fan motors (for self-contained equipment only) 

• higher efficiency compressors (for self-contained equipment only) 

• night curtains (equipment without doors only) 

Each design option has at least two technology levels, ranging from the minimum (lowest

performing) to the maximum (best performing) technology. The design options and the 

technology levels for each design option are described in the following sections. 

5.6.5.1 Higher Efficiency Lighting and Occupancy Sensors

Lighting is an important characteristic of commercial refrigeration equipment because it 

makes the product visible to the consumer. Lighting systems typically operate continuously and 

provide an opportunity for significant energy savings. As lighting system efficiency increases, 

reductions in total case energy consumption can be achieved through a direct reduction in 

electricity consumption by the lighting system, and a reduction of heat inside the case, thereby 

reducing compressor work. 

It is important that product illumination not degrade with higher design option levels 

because this would decrease the utility of the equipment. DOE tried to maintain approximately 

constant system illumination across all design option levels. This approach meant that DOE had 

to consider lighting as a system, rather than distinguishing lamps and ballasts as separate design 

5-20
options. This approach becomes more important when considering LED lighting systems, which 

do not use ballasts, as fluorescent lighting systems do.

Although LED systems generally have lower absolute efficacy in lumens per watt than 

fluorescent systems, the fixtures produce light that is much more directional in nature. And, 

while the total lumen output of LED systems is lower than comparable fluorescent systems, the 

amount of light incident on the product (illuminance) is roughly equivalent. Consultations with 

commercial refrigeration equipment manufacturers, lighting manufacturers, and other technical 

experts indicate that current LED technology provides product lighting that is adequate and in 

most cases comparable to fluorescent lighting. In recent years, according to discussions with 

manufacturers, the trend within the market has been toward a much greater use of LED lighting 

in this equipment. 

To account for the variation in design between equipment families, DOE used two 

lighting design options in the energy consumption model. DOE used the “higher efficiency 

lighting and ballasts for VOP, SVO, and SOC equipment families” design option for lighting in a 

horizontal configuration, and the “higher efficiency lighting and ballasts for VCT and PD 

equipment families” design option for the lighting in a vertical configuration. The VCS and HCS 

equipment families do not require lighting because they are not designed to display food, while 

the HCT and HZO equipment families typically do not have lighting because they rely on store 

ambient lighting for product illumination. Therefore, DOE did not consider lighting design 

options for these four equipment families.

DOE also considered occupancy sensors, which allow for case lighting to be reduced or 

shut off during periods of inactivity around the case, as part of the design options for the 

VCT/PD and VOP/SVO/SOC groupings. These equipment families generally are used for 

display purposes and include lighting for product illumination, making occupancy sensor 

implementation an option for this equipment. Because fluorescent lamps require a start-up period 

after being powered on and fluorescent lamp lifetime is greatly reduced by frequent cycling on 

and off, DOE only considered occupancy sensors to be an option compatible with LED lighting. 

In the preliminary engineering analysis, DOE based its modeling of occupancy sensors 

on past empirical studies and discussions with commercial refrigeration equipment 

manufacturers. For that analysis, DOE determined that a net 30-percent reduction in lighting run 

time due to the implementation of occupancy sensors would be an appropriate figure for 

modeling the performance of these sensors.4, 5 This value was directly implemented into the 

energy consumption model, such that a unit with occupancy sensors would see a lighting time 

reduction of 30 percent from the standard 24-hour daily run time. However, in the time since 

those analyses were performed, DOE published a final rule amending the commercial 

refrigeration equipment test procedure. 77 FR 10292 (February 21, 2012). That rule includes 

provisions for the testing of occupancy sensors and scheduled controls, allowing for 8 to 10.8 

hours of lighting off or dimmed, depending on whether lighting occupancy sensors, scheduled 

lighting controls, or both are installed on a case and whether the respective lighting technologies 

dim or turn off the lights. For this analysis, DOE assumed 2.8 hours of dimmed lighting from 

sensors and an 8-hour lighting run time reduction due to scheduled controls per 24-hour test 

period. DOE believes this is lighting configuration is representative of those found in the field, 

and DOE incorporated these specifications from the updated DOE test procedure into the 

5-21
standards NOPR engineering analysis. The reduction in lighting run time, as input into the 

model, affects both the calculated energy consumption of the lighting and the lighting 

contribution to the case heat load. Additionally, in some cases, where incremental 

implementation of occupancy sensors proved in the analysis to be more cost effective than the 

implementation of LEDs alone, DOE implemented the two together, going directly from T8 or 

Super T8 lighting to LEDs with occupancy sensors, without an intermediate option of LEDs 

alone. 

Because of the horizontal configuration of shelving and the linear nature of display case 

lineups in the VOP, SVO, and SOC equipment families, lighting for these cases is typically 

installed in the horizontal plane. Details for the “higher efficiency lighting and ballasts for VOP, 

SVO, and SOC equipment families” design option are shown in Table 5.6.2. Remote condensing 

versions of these display cases are most often sold in 8-foot and 12-foot sections, using multiples 

of 4-foot fixtures (either fluorescent bulbs or LED strips) to continuously light the entire width of 

the case. Self-contained versions are commonly sold in 4-foot lengths, so that a single 4-foot 

light fixture will light the full width of the case. Therefore, 4-foot fixtures were specified for all 

lighting systems in the horizontal configuration. This lighting was also required to have a color 

temperature of 3,500 kelvin (K), which is typical for this type of equipment. 

Table 5.6.2 Details for Lighting for VOP, SVO, HZO, and SOC Equipment Families Design 

Option

Level Description Lamp Type

Lamp 

Rated 

Power 

W

Lamp Rated 

Light 

Output 

lumens

System 

Efficacy 

lumens/W

System Light 

Output 

lumens

T8N 4 ft, T8 Elec. F32T8 32.0 2,850.0 85.0 2,679.0

T8S 4 ft, Super T8 Elec. F32T8/HL 32.0 3,100.0 94.6 2,697.0

LED 4 ft, LED LED 4 ft 15.0 888.0 59.2 888.0

OCC 4 ft, LED with 

Occupancy Sensors LED 4 ft 15.0 888.0 59.2 888.0

Because of the vertical configuration of the doors in the VCT and PD equipment families, 

fluorescent lamps typically are installed vertically behind the mullions between doors. Such 

lighting systems typically consist of a single 5-foot lamp and single ballast per mullion as well as 

a lamp installed at each end of the case. All lighting systems in the vertical configuration were 

specified to have 5-foot lamps and a color temperature of 4,100 K, which DOE found to be 

typical for this equipment family. Table 5.6.3 shows details for the “lighting for VCT and PD 

equipment families” design option. 

Table 5.6.3 Details for Lighting for VCT and PD Equipment Families Design Option

Level Description Lamp Type

Lamp 

Rated 

Power 

W

Lamp Rated 

Light 

Output 

lumens

System 

Efficacy 

lumens/W

System Light 

Output 

lumens

T8N 5 ft, T8 Elec. F58T8/835 58.0 5,400.0 93.1 5,400.0

LED 5 ft, LED LED 5 ft 29.0 1,564.0 53.9 1,564.0

OCC 5 ft, LED with 

Occupancy Sensors LED 5 ft 29.0 1,564.0 53.9 1,564.0

5-22
5.6.5.2 Higher Efficiency Evaporator Fan Motors

In conjunction with fan blades, fan motors are necessary for transferring heat from the 

display case to the refrigerant and, in the case of self-contained equipment, rejecting heat from 

the refrigerant into the ambient air. Fan motors are also responsible for maintaining product 

temperatures and air curtains on open cases. They must operate virtually continuously, and 

therefore use a significant amount of energy. As motor efficiency increases, reductions in total 

case energy consumption are achieved through a direct reduction both in electricity consumption 

and waste heat inside the case, reducing compressor load. 

Table 5.6.4 shows details for the evaporator fan motor design option. DOE considers 

shaded-pole motors (SPM) as the baseline (or lowest-efficiency) technology, permanent split 

capacitor (PSC) motors as the mid-level technology, and brushless direct current or 

electronically commutated motors (ECMs) as the maximum technology level. DOE adapted

motor efficiency levels, listed in Table 5.6.4, from the 2009 final rule and ongoing DOE 

rulemaking efforts. DOE verified these efficiency estimates through discussions with equipment 

manufacturers. During its discussions with manufacturers, some manufacturer representatives 

pointed out that there can be significant variations in efficiency between motors of the same type 

but different models. According to these manufacturers, this variation was largely a function of 

equipment supplier. Some manufacturers stated that, from higher quality suppliers, some specific 

models of PSC motors, for example, could reach efficiencies as high as 40 percent. However, 

manufacturers generally agreed that the values listed in Table 5.6.4 are fairly representative of 

the efficiencies of motors available for use in commercial refrigeration equipment. Therefore, 

DOE retained these values for use in its NOPR engineering analysis. 

Table 5.6.4 Details for Evaporator Fan Motor Design Option 

Rated 

Power

W 

Shaded-Pole Motor Permanent Split Capacitor 

Motor

Brushless DC Motor

(ECM)

Actual 

Power

W

Efficiency

%

Actual 

Power

W

Efficiency

%

Actual 

Power

W

Efficiency

%

12.0 60.0 20 41.4 29 18.2 66

9.0 45.0 20 31.0 29 13.6 66

6.0 30.0 20 20.7 29 9.1 66

5.6.5.3 Improved Evaporator Coil Design 

Evaporator coils are another component necessary for transferring heat from the display 

case to the refrigerant. Table 5.6.5 shows details for the evaporator coil design options used in 

the NOPR engineering analysis. In view of available information, DOE considered a baseline 

and a maximum technology level for this design option. For each level, DOE specified an overall 

UA-valuea and a coil cost. The UA-value is normalized to the standard coil value, and the coil 

cost is normalized to the heat removal capacity of the coil. This allowed DOE to apply these 

details of coil design across all equipment classes and at different capacities. In consultation with 

a The overall UA-value is the product of the overall heat transfer coefficient (Btu/h-ft2

-°F) and the total surface area 

(ft2

) of the coil. This value can be derived from the total heat transfer rate of the coil (Btu/h) divided by the average 

temperature difference between the discharge air and the saturated evaporator temperature (ΔT).

5-23

 
outside experts, DOE determined that applying the same coil design improvements to different 

sized coils would result in similar increases in coil performance. 

Table 5.6.5 Details for Evaporator Coil Design Option

Level Description Normalized UA (-)

EVAP1 Standard Coil 1

EVAP2 High-Performance Coil 1.745

DOE based the details of coil construction (Table 5.6.6) on baseline and prototype highperformance coil specifications developed by DOE contractors. These coil designs were 

developed by first performing teardown analyses of existing coils on the market and then using 

the data as inputs into a numerical simulation model to develop performance values for those 

baseline designs. The same modeling tools were then used to calculate new performance 

estimates for improved coil designs based on manipulation of the physical coil parameters. 

Finally, the baseline and improved coil designs were input into the cost model in the same 

manner as the core cases discussed in section 5.4.1 to yield costs to manufacture each design. 

The high-performance coil uses a combination of enhancements to the heat transfer surfaces to 

increase its overall UA-value. These enhancements include higher fin thickness, rifled tubing, 

and the addition of an extra row of tubes to the coil. In sum, these improvements allow the 

prototype coil to run at a SET that is warmer than the baseline coil while maintaining the same 

discharge air temperature and heat removal capacity. 

Table 5.6.6 Properties of Standard and Enhanced Evaporator Coil Designs

Property Standard Coil High-Performance Coil

Overall width (in.) 40.5 40.5

Overall height (in.) 8.0 10.0

Overall depth (in.) 6.25 7.50

Tube rows transverse to airflow 4 5

Tube rows parallel to airflow 5 6

Tubing material Copper Copper

Tubing outer diameter (in.) .375 .375

Tubing wall thickness (in.) .012 .012

Tubing inner surface Smooth Rifled

Fin material Aluminum Aluminum

Fin surface Flat Flat

Fin pitch (fins per inch) 3 3

Because compressor performance is directly related to SET, reductions in total case 

energy consumption are realized through an improved EER at the condensing unit. In 

consultation with outside experts, DOE determined that applying the same coil improvements to 

different sized coils and at different temperatures would result in similar SET improvements.

Consequently, the coil design was scaled as appropriate to model the coil in the representative 

unit for each equipment class analyzed. 

5.6.5.4 Improved Insulation and Vacuum Insulated Panels

Several technology levels representing improvements to case insulation were 

implemented in the engineering model. DOE included increased foam insulation thickness as a 

design option, and modeled a half-inch increase in insulation thickness for all equipment classes

5-24
based on discussions with manufacturers regarding case design and foam insulation fixturing. 

DOE added this increase in thickness to the baseline value of insulation thickness and 

recalculated the conduction load in the energy consumption model (section 5.6.6.5). The cost of 

increasing the insulation thickness includes a sunk cost per unit, considering foam fixture 

engineering and tooling costs, production line lifetime, and number of fixtures and units 

produced. In the 2009 final rule and in its preliminary engineering analysis for this rulemaking, 

DOE assumed the cost increase due to additional foam material to be insignificant compared to 

the cost of upgrading foam fixtures. However, in response to stakeholder comments after the 

preliminary analysis, DOE included the differential cost of additional foam insulation in the 

engineering analysis for the NOPR. DOE calculated the volume of additional insulation resulting 

from the added half inch of thickness and multiplied this by a cost per cubic foot for the foam 

and blowing agent. Table 5.6.7 provides details of the assumptions used to calculate the 

additional cost of insulation thickness increases. 

Table 5.6.7 Assumptions in Cost Calculation Methodology for Insulation Thickness 

Increase

Item Value Notes

Cost to upgrade single 

insulation fixture $100,000

Number of fixtures 25 Based on a survey of the number of products offered by each 

manufacturer

Engineering costs $416,667 Assumes $100,000 per year cost of labor and one month to 

complete redesign per machine plus one month for testing

Interest rate 7.0%

Product line lifetime (years) 7.0

Units per year 25,000

Sunk fixturing cost per unit $21.65

DOE also considered vacuum insulated panels (VIPs) as an option for improving the 

insulation performance of the insulated walls of commercial refrigeration equipment cases. Data 

regarding VIP performance was gathered from discussions with VIP manufacturers in 

conjunction with past and ongoing rulemakings on residential refrigerators and walk-in coolers 

and freezers. These discussions yielded a representative material cost for VIPs with an R-value 

of 30 per inch of thickness. This cost was then multiplied in the engineering cost model by the 

insulated wall area and thickness to produce a differential cost of upgrading from traditional 

foam insulation to VIPs. This model simulated the entire modeled case as being composed of 

VIP material, and assumed that the VIP material would be the dominant component of the 

thermal performance of the case. Additionally, as with the increased foam thickness design 

option, a sunk cost per unit of upgrading to VIPs was calculated and applied to the unit cost. This 

consisted of an estimate for the additional costs of product engineering and redesign, new 

production equipment, and new tooling, amortized over the typical equipment production 

lifetime and divided by the number of units per year. The result was a levelized cost per 

commercial refrigeration equipment case produced. The assumptions used for this design option 

are shown in Table 5.6.8. 

5-25
Table 5.6.8 Assumptions in Cost Calculation Methodology for Vacuum Insulated Panels 

Item Value

Additional tooling/engineering/product redesign costs $500,000

New equipment costs $300,000

Interest rate 7.0%

Product line lifetime (years) 7

Units per year 25,000

Sunk cost per unit $5.94

For each equipment class analyzed, DOE considered both the increase in conventional 

insulation thickness and the switch to VIPs as design options. While these insulation 

improvement design options benefit some equipment types more than others, DOE modeled 

them for each of the directly analyzed equipment classes, as conduction through the case is 

present in all equipment classes. Table 5.6.9 summarizes these design options. 

Table 5.6.9 Details for Insulation Design Options

Level Description

Additional 

Thickness Above 

Baseline 

inches

Insulation 

R-Value Per 

Inch Thickness

IN1 Baseline insulation 0 8

IN2

Extra 1/2-inch insulation 

thickness 0.5 8 

VIP Vacuum insulated panels 0 30

5.6.5.5 Improved Transparent Doors 

Transparent doors allow refrigerated products to be displayed to consumers while 

keeping cold air inside the display case. Transparent doors also allow heat to radiate into the 

display case and generally have a lower insulation value than solid insulated walls. In cases with 

transparent doors, these surfaces are responsible for a significant portion of the case heat load. 

On freezers and some refrigerators, glass doors must be heated to prevent frost or condensation 

from forming. These “anti-sweat” heaters, which are used to prevent formation of frost or 

condensation on the glass doors, often run continuously and consume significant amounts of 

energy. Reductions in total case energy consumption can be achieved both by improving the 

overall insulation value (U-factor) of the door and by reducing the required anti-sweat heater 

power. Improvements to heat transfer performance could include the use of additional panes of 

glass and expanded use of inert gas fill between panes of glass. The treatment of the window 

glass with advanced low-emissivity coatings and increasing the number of coated surfaces could 

also reduce losses resulting from radiation heat transfer. Reductions in the anti-sweat heater 

power needed can often be achieved as a function of improved conductive performance of the 

door, as well as in improvements to the gasketing and other door features. 

A wide variety of door types are used on the equipment covered in this rulemaking. Door 

construction and performance can vary by equipment family as well as operating temperature of 

the case. To account for this variation, DOE developed separate design option data for each of 

the different door types represented in the primary equipment classes that DOE analyzed. For 

selected door designs, DOE estimated the thermal performance of the door (expressed as an 

overall U-factor) using information about door construction obtained from manufacturers and the 

5-26
WINDOW 5 modeling software, available from Lawrence Berkley National Laboratory.6 This 

performance data was cross-referenced from DOE’s ongoing rulemaking on walk-in coolers and 

freezers, as the major door manufacturers for the commercial refrigeration equipment industry 

also possess a large share of the market for walk-in display doors and identical door designs are 

often shared across these applications. Cost estimates for transparent doors for commercial 

refrigeration equipment applications were obtained from manufacturer interviews and publicly 

available sales sheet data. DOE then extended this cost and performance data to apply to various 

geometries of horizontal and vertical display and service doors. 

Doors for the VCT equipment family operating at low and ice-cream temperature are 

hinged and are a representative size of 30 inches wide and 67 inches tall with three panes of 

glass. Table 5.6.10 shows details of thermal performance and anti-sweat heater requirements for 

this door type. 

DOE considered two technology levels for this design option: the high-performance door 

that uses a combination of low-emissivity coating, frame material, and inert fill-gas to reduce the 

overall U-factor; and a standard door. 

Table 5.6.10 Details for Doors for VCT Equipment Family, Low and Ice-Cream 

Temperature Design Option 

Level Description

Overall UFactor 

Btu/hr-ft2-°F

Anti-Sweat Heater 

Power 

W/door

DR1 Standard door 0.19 165

DR2 High-performance 

door

0.10 80

Doors for the VCT and PD equipment families operating at medium temperature are 

hinged and have a representative size of 30 inches wide and 67 inches tall with two panes of 

glass at the baseline. Table 5.6.11 shows details of thermal performance and anti-sweat heater 

requirements for this door type. 

DOE considered two technology levels for this design option. The high-performance door 

uses a combination of an additional pane of glass, low-emissivity coating, frame material, and 

inert fill-gas to reduce the overall U-factor compared to the standard door. Based on interviews 

conducted with commercial refrigeration equipment manufacturers, DOE understands that the 

implementation of these sorts of high-performance glass doors in medium-temperature 

equipment can allow for the complete elimination of anti-sweat power. As a result, the highperformance door design option for the VCT and PD families at medium temperature includes an 

anti-sweat heater power of zero.

Table 5.6.11 Details for Doors for VCT and PD Equipment Families, Medium Temperature 

Design Option

Level Description

Overall UFactor 

Btu/hr-ft2-°F

Anti-Sweat Heater 

Power 

W/door

DR1 Standard door 0.26 50

DR2 High-performance 

door

0.16 0 

5-27
Doors for the HCT equipment family operating at medium temperature are sliding and 

are a representative size of 18 inches wide and 20.5 inches tall with one pane of glass at the 

baseline. Table 5.6.12 shows details of thermal performance and anti-sweat heater requirements 

for this door type. 

DOE considered two technology levels for this design option. The high-performance door 

uses a combination of an additional pane of glass, low-emissivity coating, frame material, and 

inert fill-gas to reduce the overall U-factor compared to the standard door. Typically, these door 

types do not require anti-sweat power. 

Table 5.6.12 Details for HCT Equipment Family, Medium Temperature Design Option

Level Description

Overall UFactor 

Btu/hr-ft2-°F

Anti-Sweat Heater 

Power 

W/door

DR1 Standard door 1.05 0

DR2 High-performance 

door

0.26 0 

Doors for the HCT equipment family operating at low and ice-cream temperatures are 

sliding and are a representative size of 18 inches wide and 20.5 inches tall with one pane of glass 

at the baseline. Table 5.6.13 shows details of thermal performance and anti-sweat heater 

requirements for this door type. 

DOE considered two technology levels for this design option: a high-performance door 

that uses a combination of low-emissivity coating, frame material, and two extra panes of glass

with inert fill-gas to reduce the overall U-factor; and a standard door. Typically, these door types 

do not require anti-sweat heater power. Due to equipment design constraints, the doors 

considered for HCT equipment operating at low and ice-cream temperatures were identical to 

those considered for the medium-temperature equipment.

Table 5.6.13 Details for Doors for HCT Equipment Family, Low, and Ice-Cream 

Temperature Design Option

Level Description

Overall UFactor 

Btu/hr-ft2-°F

Anti-Sweat Heater 

Power 

W/door

DR1 Standard door 1.05 0

DR2 High-performance 

door

0.26 0 

Doors for the SOC equipment family operating at medium temperature are of the sliding 

type and have a representative size of 24 inches wide and 20 inches tall with two panes of glass. 

Table 5.6.14 shows details of door thermal performance and anti-sweat heater requirements for 

this door type. DOE considered two technology levels for this design option: a high-performance 

door that uses a combination of low-emissivity coating, frame material, and inert fill-gas to 

achieve a reduced overall U-factor; and a standard door. Typically, SOC doors do not require 

anti-sweat heater power.

5-28
Table 5.6.14 Details for Doors for SOC Equipment Family, Medium Temperature Design

Option

Level Description

Overall UFactor 

Btu/hr-ft2-°F

Anti-Sweat Heater 

Power 

W/door

DR1 Standard door 0.26 0

DR2 High-performance 

door

0.16 0 

5.6.5.6 Higher Efficiency Condenser Fan Motors

The condenser fan motor design option applies only to those equipment classes that are 

self-contained. Details for the condenser fan motor design option are identical to those shown in 

Table 5.6.4. As with evaporator fan motors, the SPM is the baseline technology, the PSC motor 

is the mid-level technology, and the ECM is the maximum technology level. Because condenser 

fan motors are outside the refrigerated space, efficiency improvements only affect the direct 

electrical consumption of the motors and not the total case heat load. 

5.6.5.7 Improved Condenser Coil Design

For the NOPR stage of this rulemaking, DOE performed additional analysis of condenser 

coils to develop a more thorough set of inputs to the energy consumption model for selfcontained equipment. Table 5.6.15 shows details for this design option. Details of coil 

construction are based on data from teardowns of equipment available on the market, as well as 

analytical modeling performed by DOE and its contractors. The methods used for developing the 

condenser coil model were the same as those used to model evaporator coils and are described in 

section 5.6.5.3. Based on this information, DOE considered both baseline and high-performance 

technology levels for this design option. For each level, DOE specified an overall UA-value and 

a coil cost. The UA-value is normalized to the standard coil, and the coil cost is normalized to 

the heat removal capacity of the modeled coil in British thermal units per hour. This approach 

allowed DOE to apply the details of coil design across all self-contained equipment classes. In 

consultation with outside experts, DOE determined that applying the same coil improvements to 

different sized coils would result in similar performance improvements.

Table 5.6.15 Details for “Increased Condenser Surface Area” Design Option

Level Description

Normalized 

UA 

(-)

COND1 Standard coil 1.00

COND2 High-performance coil 2.315

Table 5.6.16 shows details of coil construction. The high-performance coil uses a 

combination of enhancements to the heat transfer surfaces that increased its overall UA-value.

These enhancements include rifled tubing, increased fin pitch and thickness, and an added row of 

tubes. These improvements allow the prototype coil to run at a saturated condenser temperature 

(SCT) that is cooler than the baseline coil while maintaining the same heat rejection rate.

Because compressor performance is directly related to SCT, reductions in total case energy 

consumption are achieved through an improved EER at the condensing unit. 

5-29
Table 5.6.16 Properties of Standard and Enhanced Condenser Coil

Property Standard Coil High-Performance Coil

Overall width (in.) 27 27

Overall height (in.) 12.0 14.4

Overall depth (in.) 3.375 4.5

Tube rows transverse to airflow 10 12

Tube rows parallel to airflow 3 4

Tubing material Copper Copper

Tubing outer diameter (in.) .3825 .3825

Tubing wall thickness (in.) .02 .02

Tubing inner surface Smooth Rifled

Fin material Aluminum Aluminum

Fin surface Flat Flat

Fin pitch (fins per inch) 6 7

5.6.5.8 Higher Efficiency Compressors

In consultation with manufacturers and external technical experts, DOE determined that 

two levels of technology were applicable for the compressor design option. The baseline 

technology level is a standard single-speed hermetic compressor, and the maximum technology 

level is a high-efficiency single-speed hermetic compressor. Reductions in total case energy 

consumption are achieved through a reduction in compressor power consumption. 

Several manufacturers provide performance data for standard single-speed hermetic 

compressors over a range of capacities applicable to the covered equipment. DOE used this data 

to find appropriately sized compressors when developing each design option curve. (See section 

5.6.6.2 for information on the calculation of compressor energy consumption.) During the NOPR 

analyses, DOE updated its selection of compressor models within the engineering analytical 

spreadsheet to better account for the wide variations in capacity between the representative unit 

sizes analyzed for the various equipment classes.

Although several compressor manufacturers produce high-efficiency compressors, little 

data are currently available on their performance. Often, compressor manufacturers do not 

explicitly brand their compressors as “high-efficiency,” but instead maintain only one line of 

products for a given application. Therefore, DOE approximated a set of high-efficiency 

compressors by adjusting the power consumption of the standard compressors using a constant 

multiplier. This multiplier assumed a 10-percent reduction in energy consumption with an 

associated 5-percent cost premium. DOE developed this multiplier through its own research, 

consultation with outside experts, and verification through discussion with commercial 

refrigeration equipment manufacturers. 

Some manufacturers mentioned in interviews that scroll compressors were available from 

certain producers for commercial refrigeration equipment applications. However, these 

manufacturers also stated that the scroll compressors, while presenting a slight performance 

improvement over reciprocating compressors, had an extremely high associated cost premium. 

These manufacturers stated that this cost premium made scroll compressors a viable option only 

in specific design scenarios, such as when certain geometric configurations were required or in 

instances where noise reduction is very important. They also mentioned that scroll compressors 

were only available over a certain range of capacities, which would not cover the entire 

5-30
commercial refrigeration equipment market. As a result, DOE did not consider scroll 

compressors in its analysis. 

At the preliminary analysis public meeting and in written comments submitted during the 

preliminary analysis comment period, several stakeholders raised the subject of variable-speed 

compressors as applicable to commercial refrigeration equipment. DOE researched this subject 

and raised it during interviews with commercial refrigeration equipment manufacturers. 

According to these sources, only one compressor manufacturer currently sells a variable-speed 

compressor for commercial refrigeration applications in the United States, and that product is 

sized only for equipment with heat loads less than 3,000 Btu per hour. Such a compressor size 

would be applicable only to some smaller open cases and medium-sized equipment in classes 

with doors. Additionally, manufacturers raised concerns regarding the state of the technology at 

this time, saying that not enough research and development had been performed to evaluate the 

efficacy and reliability of variable-speed compressors for commercial refrigeration application. 

These compressors would also require complex controls and sensor-driven interfaces to be 

developed. As a result, DOE has elected not to consider variable-speed compressors explicitly in 

its analysis because its current understanding is that this technology has not yet been 

implemented for widespread use within the commercial refrigeration equipment industry. 

5.6.5.9 Night Curtains 

In response to stakeholder input and discussions with commercial refrigeration equipment 

manufacturers, DOE included night curtains as a design option for the VOP and SVO equipment 

families in the engineering analysis. DOE based its modeling of this design option on 

specifications obtained from manufacturer interviews, publicly available data from night curtain 

manufacturers, and past studies of night curtain performance. For cases with night curtains 

implemented, a curtain down time of 6 hours per day was used in the energy consumption model, 

in accordance with the time specified in the commercial refrigeration equipment test procedure 

final rule. 77 FR 10292 (February 21, 2012). The performance of the curtains in the model was 

based on a survey of field studies of night curtain effectiveness, which resulted in an average 39-

percent reduction in case heat load during periods when the night curtains were deployed.7,8

When the night curtain design option was implemented in the energy consumption model, the 

39-percent reduction in case heat load was applied over a period of 6 hours to the load calculated 

for the same configuration unit without night curtains, and the new heat load was normalized 

over 24 hours to give a standard hourly load. Table 5.6.17 shows the specifications for the night 

curtain design option. 

Table 5.6.17 Details for “Night Curtains” Design Option 

Level Description

Curtain 

Down Time 

hr

Case Heat Load Multiplier

OFF No night curtains 0 1.00

NC1 Night curtains 6 0.61

5.6.6 Model Components

Figure 5.6.1 presents a schematic showing the components in the energy consumption 

model. The model calculates energy consumption in two major subsections (expressed as 

5-31
kWh/day): compressor energy consumption and component energy consumption. Component 

energy consumption is the sum of electrical energy directly consumed by each fan motor, lamp, 

defrost and drain heater, anti-sweat heater, and pan heater. 

Compressor energy consumption is calculated from the total heat load (expressed as 

Btu/hr) and one of two compressor models: one version for remote condensing equipment, and 

one for self-contained equipment. The total heat load is a sum of the component load and the 

non-electric load. The component load is a sum of the heat emitted by evaporator fan motors, 

lighting, defrost heaters, drain heaters, and anti-sweat heaters inside and adjacent to the 

refrigerated space (condenser fan motors and pan heaters are outside the refrigerated space and 

do not contribute to the component heat load). The non-electric load is the sum of the heat 

contributed by radiation through glass and openings, heat conducted through walls and doors, 

and warm air infiltration through openings. 

Figure 5.6.1 Composition of the Energy Consumption Model 

5.6.6.1 Component Energy Consumption

Component energy consumption consists of calculated energy consumption of each of the 

system components that directly consumes energy. 

Fan motor energy consumption is calculated by summing the power draw of each 

evaporator and condenser fan motor and multiplying the total motor power by the total running 

time over a 24-hour period. 

Total Heat 

Load 

[Btu/h]

Component 

Load

[Btu/h]

Non-Electric 

Load

[Btu/h]

Radiation 

Load

[Btu/h]

Conduction 

Load

[Btu/h]

Infiltration 

Load

[Btu/h]

Daily Energy 

Consumption [kWh/day]

Compressor 

Energy 

Consumption 

[kWh/day]

Compressor Model 

(ARI 540)

Component 

Energy 

Consumption 

[kWh/day]

5-32
Lighting energy consumption is calculated by summing the power draw of each lamp and 

ballast and multiplying the total by the total operating time of the lighting system over a 24-hour 

period. (This calculation assumes that lighting operates continuously at the baseline.) For cases 

where lighting controls and occupancy sensors have been implemented, a run-time reduction is 

used, based on the specifications for lighting controls and occupancy sensors in the commercial 

refrigeration equipment test procedure. 

Daily defrost and drain heater energy consumption are calculated by summing the power 

draw of each defrost heater and drain heater and multiplying by the total time the case is in 

defrost operation over a 24-hour period. 

Anti-sweat energy consumption is calculated by summing the power draw of each antisweat heater and multiplying by the total operating time of the heaters over a 24-hour period. 

(This calculation assumes that anti-sweat heaters run continuously, a position supported by 

manufacturer literature and interviews.) 

Pan heater energy consumption is calculated by multiplying the power draw of each pan 

heater by the total operating time of the heater over a 24-hour period. The total operating time is 

calculated as the time it would take to evaporate all of the defrost meltwater. 

5.6.6.2 Compressor Energy Consumption

Compressor energy consumption (CEC) is calculated from the total heat load and one of 

two compressor models: one version for remote condensing equipment and one for selfcontained equipment. CEC for remote condensing equipment is calculated using default 

efficiency values from AHRI 1200. Table 1 in AHRI 1200 lists remote condensing compressor 

EER in Btu/W-h as a function of adjusted dew point temperature. 

Adjusted dew point (ADP) temperature (°F) is calculated as:

ADP = SET – 2 °F (for medium temperature)

Eq. 5.2 

ADP = SET – 3 °F (for low/ice-cream temperature) 

Eq. 5.3 

Where: 

SET = the saturated evaporator temperature (°F).

Once ADP is calculated, Table 1 in AHRI 1200 is used to find the corresponding EER 

value. The CEC (kWh/day) is then calculated as:

CEC = Qtot x (24 - tdefrost) / (EER × 1000) 

Eq. 5.4 

5-33
Where: 

Qtot = the total heat load (Btu/hr), and 

tdefrost = the total defrost time in a 24-hour period (hr). 

The CEC for self-contained equipment is calculated by using the compressor model 

described in section 6.4 of AHRI Standard 540-2004 (AHRI 540), Performance Rating of 

Positive Displacement Refrigerant Compressors and Compressor Units. This model is based on 

a 10-coefficient polynomial derived from empirical compressor performance data for power, 

mass flow, current, and efficiency. The coefficients are derived for each parameter as a function 

of SET and SCT. Compressor coefficients are available from compressor manufacturers. Similar 

to the method used for remote condensing equipment, the EER of any compressor can be 

determined given the SET and SCT values along with the 10 coefficients for the specific 

compressor model. Using Eq. 5.4 and the EER for the unit at the specific conditions being 

modeled, the CEC can be determined. 

In the engineering analysis, DOE uses adjusted capacities for compressors modeled, 

rather than capacities at standard ASHRAE rating evaporator and condenser rating conditions. 

This is because the actual ASHRAE 72 test conditions for most commercial refrigeration 

equipment are not the same as standard compressor rating conditions, causing capacities at the 

modeled test conditions to differ from listed capacities. The compressor model then uses a lookup function to select the most appropriate compressor based on the total refrigeration load in the 

case and the compressor oversize factor from the baseline design specifications. 

5.6.6.3 Component Load Model

The component load is the sum of the heat emitted by evaporator fan motors, lamps, 

defrost and drain heaters, and anti-sweat heater inside to the refrigerated space. Each component 

creates waste heat that is rejected to the refrigerated space and must be removed by the 

compressor. 

DOE assumed that all electrical energy consumed by the evaporator fan motors ends up 

as heat inside the refrigerated space. In electric motors, friction present within the motor 

windings, bearings, and other mechanical components converts much of the input electrical 

energy into heat. The rest of the energy is used in moving air inside the case. This moving air is 

slowed by friction, and the kinetic energy of the air is converted into heat. 

For lighting inside the refrigerated space, DOE assumed that all electrical energy 

consumed by the light fixtures ends up as heat inside the space. For lighting adjacent to the air 

curtain, DOE assumed that 50 percent of the electrical energy consumed ends up as heat inside 

the space. For fluorescent ballasts inside the refrigerated space, DOE assumed that all electrical 

energy that the ballasts consume ends up as heat inside the space. Ballasts outside the 

refrigerated space do not contribute any heat to the space. In cases in which occupancy sensors 

have been implemented as a design option, the heat inside the case resulting from lighting as 

calculated as above, but the run-time multiplier for the lighting is used to scale that heat load 

proportionately. 

5-34
The phase change that occurs when defrost heaters melt the frost from evaporator coils 

consumes most of the electrical energy that supplied during a defrost period. Over a 24-hour 

period, the total heat of melting is determined by: 

Q m H melt frost f water = ,

Eq. 5.5 

Where: 

Qmelt = the heat of melting (Btu/hr),

mfrost = the frost mass in a 24-hour period (lb/hr), and 

Hf,water = the heat of fusion of water (Btu/lb). 

DOE assumed that all the electrical energy that defrost heaters consume, other than what 

is used to melt the frost, ends up as heat inside the refrigerated space. For drain heaters, DOE 

assumed that all electrical energy ends up as heat inside the refrigerated space.

DOE assumed that, on average, 70 percent of the electrical energy consumed by antisweat heaters adjacent to the refrigerated space (frame, rail, glass, sill, and air grille heaters) ends 

up as heat inside the space. 

5.6.6.4 Radiation Load Model 

The radiation heat load model accounts for the gray-body radiation between the warm 

surfaces of the surrounding environment (the test chamber) and the cold inner surfaces of the 

refrigerated space. For cases without doors, the net radiation is determined as: 

( ) Q

T T

A A F A

rad

room case

room

room room room case room

case

case case

= −

− + + −

−

σ

ε

ε

ε

ε

4 4

1 1 1

Eq. 5.6 

Where: 

Qrad = the net radiation load (Btu/hr),

σ = the Stefan-Boltzmann constant (Btu/hr-ft2-°F4),

Troom = the temperature of the room walls (°F),

Tcase = the temperature of the case inner walls (°F),

εroom = the emissivity of the room walls (dimensionless),

εcase = the emissivity of the case inner walls (dimensionless),

Aroom = the area of the room walls (ft2),

Acase = the area of the interior of the case (ft2), and 

Fcase-room = the view factor from the case interior to the room walls (dimensionless).

DOE assumed that the wall temperatures of the case were in thermal equilibrium with the 

air temperature in the case, and that the wall temperatures of the room were in thermal 

5-35
equilibrium with the air temperature in the room. See Eq. 5.6 for numerical constants pertaining 

to the radiation model. 

For glass doors and other glass, the net radiation is incorporated into the overall U-factor

of the door (Table 5.6.10 through Table 5.6.14, and Eq. 5.7). See section 5.6.6.5 for a discussion 

of the calculation of the combined radiation and conduction loads for glass doors and other glass. 

5.6.6.5 Conduction Load Model

The conduction load model accounts for the heat conducted through walls and doors. For 

solid walls and doors, the conduction is given by: 

Q A

T T

h

d

k h

cond walls

room case

o

ins

ins i

= −

+ +

1 1

 Eq. 5.7 

Where: 

Awalls = the area of the exterior of the case (ft2

),

ho = the convective film coefficient on the outside of case walls (Btu/h-ft2-°F),

hi = the convective film coefficient on the inside of case walls (Btu/h-ft2-°F),

dins = the insulation thickness (in.), and 

kins = the insulation thermal conductivity (Btu-in/hr-ft2

-°F).

Because of its high thermal conductivity, the sheet metal that encloses the insulation has 

negligible effect on the conduction load, and therefore was not included in the calculation of 

conduction load. See Table 5.6.1 for numerical constants pertaining to the conduction model. 

For glass doors and other glass, the overall U-factor of the door assembly or glass is 

based on data obtained thought WINDOW 5 calculations (Table 5.6.1 and Table 5.6.10 through 

Table 5.6.14). The combined radiation and conduction load for glass doors and other glass is 

calculated as:

Q U A T T glass = overall glass room ( ) − case

Eq. 5.8 

Where: 

Uoverall = the overall U-factor, including convection and radiation (Btu/h-ft2-°F), and

Aglass = the area of the glass (ft2).

5.6.6.6 Infiltration Load Model 

In the engineering analysis, DOE used values for infiltrated air (in lb/hr) for all 

equipment classes. DOE estimated infiltrated air by using manufacturers’ detailed specification

sheets, recognizing that infiltration load is the only load component that cannot be directly 

5-36
calculated. These estimates were directly calculated for some equipment classes, and then 

extended for use in the remaining primary classes. DOE then used the infiltrated air mass data to 

calculate a sensible heat load and latent heat load due to infiltration, based on the thermodynamic 

properties of the water in the air as well as the assumed ambient and operating conditions. The 

sum of these two values constituted the portion of the case heat load attributed to ambient air 

infiltration. 

5.7 COST-EFFICIENCY CURVES

The result of the engineering analysis is a set of cost-efficiency curves. DOE developed 

25 curves representing the directly analyzed primary equipment classes, using the baseline 

specifications and design options described above. (See appendix 5A for details.) The 

methodology for developing curves started with determining the baseline energy consumption 

and MPC using the methodology discussed in this chapter. To develop engineering efficiency 

levels above the baseline, DOE implemented design options in order from highest to lowest 

return on cost. Only one design option was implemented at each design option level, except for 

LED lighting and lighting occupancy sensors, which, in some classes, were implemented 

simultaneously due to synergistic effects within the energy consumption model (See 

section 5.6.5.1 for details.) Design options were implemented until all equipment classes reached 

the max-tech level based upon the available design options. 

The 25 cost-efficiency curves are shown in Figure 5.7.1 through Figure 5.7.25 in the form 

of daily energy consumption versus MSP. Supporting data for each primary class, including 

CDEC, MPC, MSP, and the design option ordering used in DOE’s analysis, is shown in 

Table 5.7.2 through Table 5.7.26. Table 5.7.1 shows a list of the 25 analyzed equipment classes 

and their corresponding figure, table, and page numbers. 

5-37
Table 5.7.1 Figure, Table, and Page Numbers for Cost-Efficiency Results

Equipment Class Figure Table Page Number

VOP.RC.M Figure 5.7.1 Table 5.7.2 5-39

VOP.RC.L Figure 5.7.2 Table 5.7.3 5-40

VOP.SC.M Figure 5.7.3 Table 5.7.4 5-41

SVO.RC.M Figure 5.7.4 Table 5.7.5 5-42

SVO.SC.M Figure 5.7.5 Table 5.7.6 5-43

HZO.RC.M Figure 5.7.6 Table 5.7.7 5-44

HZO.RC.L Figure 5.7.7 Table 5.7.8 5-45

HZO.SC.M Figure 5.7.8 Table 5.7.9 5-46

HZO.SC.L Figure 5.7.9 Table 5.7.10 5-47

VCT.RC.M Figure 5.7.10 Table 5.7.11 5-48

VCT.RC.L Figure 5.7.11 Table 5.7.12 5-49

VCT.SC.M Figure 5.7.12 Table 5.7.13 5-50

VCT.SC.L Figure 5.7.13 Table 5.7.14 5-51

VCT.SC.I Figure 5.7.14 Table 5.7.15 5-52

VCS.SC.M Figure 5.7.15 Table 5.7.16 5-53

VCS.SC.L Figure 5.7.16 Table 5.7.17 5-54

VCS.SC.I Figure 5.7.17 Table 5.7.18 5-55

HCT.SC.M Figure 5.7.18 Table 5.7.19 5-56

HCT.SC.L Figure 5.7.19 Table 5.7.20 5-57

HCT.SC.I Figure 5.7.20 Table 5.7.21 5-58

HCS.SC.M Figure 5.7.21 Table 5.7.22 5-59

HCS.SC.L Figure 5.7.22 Table 5.7.23 5-60

SOC.RC.M Figure 5.7.23 Table 5.7.24 5-61

SOC.SC.M Figure 5.7.24 Table 5.7.25 5-62

PD.SC.M Figure 5.7.25 Table 5.7.26 5-63

As stated above, DOE used the cost-efficiency curves from the engineering analysis as an 

input to the life-cycle cost analysis to determine the overall cost to the customer of purchasing, 

installing, maintaining, and using a given piece of commercial refrigeration equipment over the 

duration of its lifetime (chapter 8 of the TSD). 

5-38
Figure 5.7.1 Cost-Efficiency Curve for the VOP.RC.M Equipment Class

Table 5.7.2 Cost-Efficiency Data for the VOP.RC.M Equipment Class

Design 

Option 

Level

Calculated Daily 

Energy 

Consumption 

kWh/day

Manufacturer 

Production Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 57.90 3,173.79 4,759.07 Baseline

AD2 55.28 3,198.60 4,794.31 

AD1 + Permanent Split 

Cap. Evap. Fan Motor

AD3 51.99 3,251.34 4,869.20 

AD2 + Brushless DC Evap. 

Fan Motor

AD4 50.52 3,280.30 4,910.32 AD3 + Super T8 Lighting

AD5 46.84 3,404.38 5,086.52 AD4 + Night Curtains

AD6 44.33 3,490.44 5,208.72 

AD5 + Enhanced-UA 

Evaporator Coil

AD7 35.71 4,207.18 6,226.49 

AD6 + LED Lighting with 

Occupancy Sensors

AD8 35.51 4,252.31 6,290.57 

AD7 + Additional 1/2" 

Insulation

AD9 35.06 6,123.48 8,947.63 

AD8 + Vacuum Insulated 

Panels

5-39
Figure 5.7.2 Cost-Efficiency Curve for the VOP.RC.L Equipment Class

Table 5.7.3 Cost-Efficiency Data for the VOP.RC.L Equipment Class

Design 

Option 

Level

Calculated Daily 

Energy 

Consumption 

kWh/day

Manufacturer 

Production Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 133.60

 

3,290.35 

 

4,924.60 Baseline

AD2 126.90

 

3,348.26 

 

5,006.83 

AD1 + Permanent Split 

Cap. Evap. Fan Motor

AD3 118.44

 

3,471.32 

 

5,181.56 

AD2 + Brushless DC Evap. 

Fan Motor

AD4 111.58

 

3,595.40 

 

5,357.77 AD3 + Night Curtains

AD5 110.92

 

3,607.81 

 

5,375.39 AD4 + Super T8 Lighting

AD6 106.22

 

3,709.13 

 

5,519.26 

AD5 + Enhanced-UA 

Evaporator Coil

AD7 101.03

 

3,957.44 

 

5,871.86 

AD6 + LED Lighting with 

Occupancy Sensors

AD8 100.51

 

4,007.48 

 

5,942.92 

AD7 + Additional 1/2" 

Insulation

AD9 98.87

 

7,061.66 

 

10,279.86 

AD8 + Vacuum Insulated 

Panels

5-40
Figure 5.7.3 Cost-Efficiency Curve for the VOP.SC.M Equipment Class

Table 5.7.4 Cost-Efficiency Data for the VOP.SC.M Equipment Class

Design 

Option 

Level

Calculated Daily 

Energy 

Consumption 

kWh/day

Manufacturer 

Production Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 39.60 1,669.61 2,439.74 Baseline

AD2 37.91

 

1,682.53 

 

2,458.10 

AD1 + High-Eff. 

Reciprocating Compressor

AD3 34.96

 

1,721.42 

 

2,513.31 

AD2 + Enhanced-UA 

Condenser Coil

AD4 34.35

 

1,730.72 

 

2,526.53 

AD3 + Permanent Split 

Cap. Evap. Fan Motor

AD5 32.81

 

1,759.75 

 

2,567.74 

AD4 + Enhanced-UA 

Evaporator Coil

AD6 32.09

 

1,774.74 

 

2,589.03 

AD5 + Brushless DC Evap. 

Fan Motor

AD7 31.58

 

1,785.60 

 

2,604.45 AD6 + Super T8 Lighting

AD8 30.37

 

1,826.96 

 

2,663.18 AD7 + Night Curtains

AD9 30.03

 

1,839.37 

 

2,680.80 

AD8 + Permanent Split 

Cap. Cond. Fan Motor

AD10 29.60

 

1,865.74 

 

2,718.25 

AD9 + Brushless DC 

Cond. Fan Motor

AD11 26.70

 

2,160.66 

 

3,137.04 

AD10 + LED Lighting 

with Occupancy Sensors

AD12 26.62

 

2,190.93 

 

3,180.03 

AD11 + Additional 1/2" 

Insulation

AD13 26.46

 

2,829.13 

 

4,086.26 

AD12 + Vacuum Insulated 

Panels

5-41
Figure 5.7.4 Cost-Efficiency Curve for the SVO.RC.M Equipment Class

Table 5.7.5 Cost-Efficiency Data for the SVO.RC.M Equipment Class

Design 

Option 

Level

Calculated Daily 

Energy 

Consumption 

kWh/day

Manufacturer 

Production Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 43.56

 

2,775.31 

 

4,080.77 Baseline

AD2 41.78

 

2,791.86 

 

4,104.26 

AD1 + Permanent Split 

Cap. Evap. Fan Motor

AD3 39.58

 

2,827.02 

 

4,154.19 

AD2 + Brushless DC Evap. 

Fan Motor

AD4 38.47

 

2,847.70 

 

4,183.56 AD3 + Super T8 Lighting

AD5 36.11

 

2,907.69 

 

4,268.75 

AD4 + Enhanced-UA 

Evaporator Coil

AD6 33.85

 

3,031.78 

 

4,444.96 AD5 + Night Curtains

AD7 27.71

 

3,578.80 

 

5,221.73 

AD6 + LED Lighting with 

Occupancy Sensors

AD8 27.57

 

3,615.85 

 

5,274.33 

AD7 + Additional 1/2" 

Insulation

AD9 27.26

 

4,816.22 

 

6,978.85 

AD8 + Vacuum Insulated 

Panels

5-42
Figure 5.7.5 Cost-Efficiency Curve for the SVO.SC.M Equipment Class

Table 5.7.6 Cost-Efficiency Data for the SVO.SC.M Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 34.93 1,350.11 1,959.71 Baseline

AD2 33.33

 

1,359.78 

 

1,973.44 

AD1 + High-Eff. Reciprocating 

Compressor

AD3 28.96

 

1,389.49 

 

2,015.63 

AD2 + Enhanced-UA Condenser 

Coil

AD4 28.66

 

1,394.14 

 

2,022.24 

AD3 + Permanent Split Cap. 

Evap. Fan Motor

AD5 28.27 1,401.64 2,032.89 AD4 + Super T8 Lighting

AD6 27.89

 

1,409.14 

 

2,043.53 

AD5 + Brushless DC Evap. Fan 

Motor

AD7 27.50

 

1,417.41 

 

2,055.28 

AD6 + Permanent Split Cap. 

Cond. Fan Motor

AD8 26.67 1,439.59 2,086.78 

AD7 + Enhanced-UA 

Evaporator Coil

AD9 25.74 1,480.96 2,145.51 AD8 + Night Curtains

AD10 25.36

 

1,498.54 

 

2,170.48 

AD9 + Brushless DC Cond. Fan 

Motor

AD11 23.29

 

1,739.04 

 

2,512.00 

AD10 + LED Lighting with 

Occupancy Sensors

AD12 23.24

 

1,766.62 

 

2,551.16 

AD11 + Additional 1/2" 

Insulation

AD13 23.12

 

2,181.67 

 

3,140.52 

AD12 + Vacuum Insulated 

Panels

5-43
Figure 5.7.6 Cost-Efficiency Curve for the HZO.RC.M Equipment Class

Table 5.7.7 Cost-Efficiency Data for the HZO.RC.M Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 19.63

 

2,498.58 

 

3,661.47 Baseline

AD2 17.89

 

2,515.13 

 

3,684.97 

AD1 + Permanent Split Cap. Evap. Fan 

Motor

AD3 15.73

 

2,550.29 

 

3,734.89 AD2 + Brushless DC Evap. Fan Motor

AD4 14.64

 

2,577.21 

 

3,773.12 AD3 + Enhanced-UA Evaporator Coil

AD5 14.48

 

2,611.65 

 

3,822.03 AD4 + Additional 1/2" Insulation

AD6 14.17

 

3,596.11 

 

5,219.96 AD5 + Vacuum Insulated Panels

5-44
Figure 5.7.7 Cost-Efficiency Curve for the HZO.RC.L Equipment Class

Table 5.7.8 Cost-Efficiency Data for the HZO.RC.L Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 40.44

 

2,530.49 

 

3,706.78 Baseline

AD2 38.39

 

2,547.03 

 

3,730.27 

AD1 + Permanent Split Cap. Evap. Fan 

Motor

AD3 35.84

 

2,582.19 

 

3,780.20 AD2 + Brushless DC Evap. Fan Motor

AD4 33.87

 

2,616.15 

 

3,828.42 AD3 + Enhanced-UA Evaporator Coil

AD5 33.43

 

2,656.63 

 

3,885.90 AD4 + Additional 1/2" Insulation

AD6 32.22

 

4,649.07 

 

6,715.17 AD5 + Vacuum Insulated Panels

5-45
Figure 5.7.8 Cost-Efficiency Curve for the HZO.SC.M Equipment Class 

Table 5.7.9 Cost-Efficiency Data for the HZO.SC.M Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 18.36

 

670.82 

 

972.84 Baseline

AD2 17.41

 

678.06 

 

983.11 

AD1 + High-Eff. Reciprocating 

Compressor

AD3 16.18

 

693.96 

 

1,005.69 AD2 + Enhanced-UA Condenser Coil

AD4 15.86

 

698.61 

 

1,012.30 

AD3 + Permanent Split Cap. Evap. Fan 

Motor

AD5 15.26

 

710.48 

 

1,029.15 AD4 + Enhanced-UA Evaporator Coil

AD6 14.89

 

717.98 

 

1,039.79 AD5 + Brushless DC Evap. Fan Motor

AD7 14.76

 

722.63 

 

1,046.40 

AD6 + Permanent Split Cap. Cond. Fan 

Motor

AD8 14.60

 

730.13 

 

1,057.05 AD7 + Brushless DC Cond. Fan Motor

AD9 14.49

 

759.49 

 

1,098.74 AD8 + Additional 1⁄2-inch Insulation

AD10 14.26

 

1,322.59 

 

1,898.34 AD9 + Vacuum Insulated Panels

5-46
Figure 5.7.9 Cost-Efficiency Curve for the HZO.SC.L Equipment Class

Table 5.7.10 Cost-Efficiency Data for the HZO.SC.L Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 39.25

 

882.63 

 

1,273.60 Baseline

AD2 36.93

 

897.42 

 

1,294.60 

AD1 + High-Eff. Reciprocating 

Compressor

AD3 36.38

 

901.55 

 

1,300.47 

AD2 + Permanent Split Cap. Evap. Fan 

Motor

AD4 33.08

 

929.41 

 

1,340.02 AD3 + Enhanced-UA Condenser Coil

AD5 31.37

 

950.20 

 

1,369.55 AD4 + Enhanced-UA Evaporator Coil

AD6 30.78

 

958.99 

 

1,382.03 AD5 + Brushless DC Evap. Fan Motor

AD7 30.67

 

963.64 

 

1,388.64 

AD6 + Permanent Split Cap. Cond. Fan 

Motor

AD8 30.54

 

971.14 

 

1,399.28 AD7 + Brushless DC Cond. Fan Motor

AD9 30.37

 

1,000.25 

 

1,440.62 AD8 + Additional 1⁄2-inch Insulation

AD10 29.91

 

1,730.09 

 

2,476.99 AD9 + Vacuum Insulated Panels

5-47
Figure 5.7.10 Cost-Efficiency Curve for the VCT.RC.M Equipment Class

Table 5.7.11 Cost-Efficiency Data for the VCT.RC.M Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 24.85

 

4,548.80 

 

6,694.37 Baseline

AD2 18.70

 

4,636.16 

 

6,818.41 AD1 + LED Lighting

AD3 17.30

 

4,659.42 

 

6,851.45 

AD2 + Permanent Split Cap. Evap. Fan 

Motor

AD4 15.56

 

4,696.91 

 

6,904.68 AD3 + Brushless DC Evap. Fan Motor

AD5 8.10

 

5,057.76 

 

7,417.09 AD4 + High-Performance Door

AD6 6.26

 

5,148.24 

 

7,545.57 

AD5 + LED Lighting with Occupancy 

Sensors

AD7 6.01

 

5,196.99 

 

7,614.80 AD6 + Additional 1⁄2-inch Insulation

AD8 5.97

 

5,214.09 

 

7,639.08 AD7 + Enhanced-UA Evaporator Coil

AD9 5.49

 

7,386.46 

 

10,723.85 AD8 + Vacuum Insulated Panels

5-48
Figure 5.7.11 Cost-Efficiency Curve for the VCT.RC.L Equipment Class 

Table 5.7.12 Cost-Efficiency Data for the VCT.RC.L Equipment Class

Design Option 

Level

Calculated

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 60.84

 

5,036.82 

 

7,387.35 Baseline

AD2 58.47

 

5,057.50 

 

7,416.72 

AD1 + Permanent Split Cap. Evap. Fan 

Motor

AD3 51.25

 

5,144.85 

 

7,540.76 AD2 + LED Lighting

AD4 48.31

 

5,188.80 

 

7,603.17 AD3 + Brushless DC Evap. Fan Motor

AD5 33.27

 

5,477.48 

 

8,013.09 AD4 + High-Performance Door

AD6 31.13

 

5,567.96 

 

8,141.58 

AD5 + LED Lighting with Occupancy 

Sensors

AD7 30.58

 

5,616.20 

 

8,210.08 AD6 + Additional 1⁄2-inch Insulation

AD8 30.29

 

5,646.64 

 

8,253.30 AD7 + Enhanced-UA Evaporator Coil

AD9 28.85

 

8,499.95 

 

12,305.00 AD8 + Vacuum Insulated Panels

5-49
Figure 5.7.12 Cost-Efficiency Curve for the VCT.SC.M Equipment Class

Table 5.7.13 Cost-Efficiency Data for the VCT.SC.M Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 14.38 1,749.80 2,546.52 Baseline

AD2 9.98

 

1,778.22 

 

2,586.88 AD1 + LED Lighting

AD3 9.56

 

1,783.91 

 

2,594.96 

AD2 + High-Eff. Reciprocating 

Compressor

AD4 8.88

 

1,793.22 

 

2,608.17 

AD3 + Permanent Split Cap. Evap. Fan 

Motor

AD5 8.36

 

1,802.46 

 

2,621.29 AD4 + Enhanced-UA Condenser Coil

AD6 7.56

 

1,817.45 

 

2,642.59 AD5 + Brushless DC Evap. Fan Motor

AD7 4.18

 

1,961.79 

 

2,847.55 AD6 + High-Performance Door

AD8 4.08

 

1,971.10 

 

2,860.76 

AD7 + Permanent Split Cap. Cond. Fan 

Motor

AD9 3.24

 

2,061.58 

 

2,989.25 

AD8 + LED Lighting with Occupancy 

Sensors

AD10 3.13

 

2,076.57 

 

3,010.54 AD9 + Brushless DC Cond. Fan Motor

AD11 2.98

 

2,108.40 

 

3,055.73 AD10 + Additional 1⁄2-inch Insulation

AD12 2.97

 

2,115.29 

 

3,065.52 AD11 + Enhanced-UA Evaporator Coil

AD13 2.68

 

2,882.44 

 

4,154.88 AD12 + Vacuum Insulated Panels

5-50
Figure 5.7.13 Cost-Efficiency Curve for the VCT.SC.L Equipment Class

Table 5.7.14 Cost-Efficiency Data for the VCT.SC.L Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 29.09 2,399.20 3,468.66 Baseline

AD2 24.32

 

2,427.62 

 

3,509.03 AD1 + LED Lighting

AD3 23.23

 

2,435.89 

 

3,520.78 

AD2 + Permanent Split Cap. Evap. Fan 

Motor

AD4 21.51

 

2,451.85 

 

3,543.43 AD3 + Enhanced-UA Condenser Coil

AD5 20.71

 

2,463.27 

 

3,559.65 

AD4 + High-Eff. Reciprocating 

Compressor

AD6 19.51

 

2,480.85 

 

3,584.62 AD5 + Brushless DC Evap. Fan Motor

AD7 13.48

 

2,596.32 

 

3,748.59 AD6 + High-Performance Door

AD8 13.30

 

2,608.23 

 

3,765.49 AD7 + Enhanced-UA Evaporator Coil

AD9 12.44

 

2,698.71 

 

3,893.98 

AD8 + LED Lighting with Occupancy 

Sensors

AD10 12.37

 

2,708.02 

 

3,907.19 

AD9 + Permanent Split Cap. Cond. Fan 

Motor

AD11 12.18

 

2,739.84 

 

3,952.38 AD10 + Additional 1⁄2-inch Insulation

AD12 12.09

 

2,754.84 

 

3,973.68 AD11 + Brushless DC Cond. Fan Motor

AD13 11.57

 

3,786.27 

 

5,438.31 AD12 + Vacuum Insulated Panels

5-51
Figure 5.7.14 Cost-Efficiency Curve for the VCT.SC.I Equipment Class

Table 5.7.15 Cost-Efficiency Data for the VCT.SC.I Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 38.26 2,485.76 3,594.62 Baseline

AD2 32.35

 

2,514.18 

 

3,634.99 AD1 + LED Lighting

AD3 31.03

 

2,522.46 

 

3,646.73 

AD2 + Permanent Split Cap. Evap. Fan 

Motor

AD4 28.23

 

2,540.95 

 

3,673.00 AD3 + Enhanced-UA Condenser Coil

AD5 26.98

 

2,554.75 

 

3,692.60 AD4 + Enhanced-UA Evaporator Coil

AD6 25.76

 

2,568.82 

 

3,712.57 

AD5 + High-Eff. Reciprocating 

Compressor

AD7 24.45

 

2,586.40 

 

3,737.53 AD6 + Brushless DC Evap. Fan Motor

AD8 17.57

 

2,701.87 

 

3,901.50 AD7 + High-Performance Door

AD9 17.45

 

2,711.17 

 

3,914.72 

AD8 + Permanent Split Cap. Cond. Fan 

Motor

AD10 16.51

 

2,801.66 

 

4,043.20 

AD9 + LED Lighting with Occupancy 

Sensors

AD11 16.36

 

2,816.65 

 

4,064.49 AD10 + Brushless DC Cond. Fan Motor

AD12 16.14

 

2,848.99 

 

4,110.41 AD11 + Additional 1⁄2-inch Insulation

AD13 15.37

 

4,216.21 

 

6,051.86 AD12 + Vacuum Insulated Panels

5-52
Figure 5.7.15 Cost-Efficiency Curve for the VCS.SC.M Equipment Class

Table 5.7.16 Cost-Efficiency Data for the VCS.SC.M Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 4.45

 

1,150.32 

 

1,694.25 Baseline

AD2 3.70

 

1,159.63 

 

1,707.47 

AD1 + Permanent Split Cap. Evap. Fan 

Motor

AD3 3.42

 

1,163.41 

 

1,712.84 AD2 + Enhanced-UA Condenser Coil

AD4 2.53

 

1,178.41 

 

1,734.13 AD3 + Brushless DC Evap. Fan Motor

AD5 2.36

 

1,182.49 

 

1,739.93 

AD4 + High-Eff. Reciprocating 

Compressor

AD6 2.30

 

1,185.31 

 

1,743.94 AD5 + Enhanced-UA Evaporator Coil

AD7 2.17

 

1,194.62 

 

1,757.16 

AD6 + Permanent Split Cap. Cond. Fan 

Motor

AD8 2.01

 

1,209.61 

 

1,778.45 AD7 + Brushless DC Cond. Fan Motor

AD9 1.81

 

1,241.44 

 

1,823.64 AD8 + Additional 1⁄2-inch Insulation

AD10 1.39

 

2,008.59 

 

2,912.99 AD9 + Vacuum Insulated Panels

5-53
Figure 5.7.16 Cost-Efficiency Curve for the VCS.SC.L Equipment Class

Table 5.7.17 Cost-Efficiency Data for the VCS.SC.L Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 11.00 1,281.21 1,880.11 Baseline

AD2 9.82 1,289.48 1,891.86

AD1 + Permanent Split Cap. Evap. Fan 

Motor

AD3 9.05 1,296.54 1,901.88 AD2 + Enhanced-UA Condenser Coil

AD4 7.69 1,314.12 1,926.84 AD3 + Brushless DC Evap. Fan Motor

AD5 7.26 1,323.06 1,939.54

AD4 + High-Eff. Reciprocating 

Compressor

AD6 7.07 1,328.33 1,947.02 AD5 + Enhanced-UA Evaporator Coil

AD7 6.75 1,360.15 1,992.21 AD6 + Additional 1⁄2-inch Insulation

AD8 6.66 1,369.46 2,005.42

AD7 + Permanent Split Cap. Cond. Fan 

Motor

AD9 6.56 1,384.45 2,026.71 AD8 + Brushless DC Cond. Fan Motor

AD10 5.71 2,415.88 3,491.34 AD9 + Vacuum Insulated Panels

5-54
Figure 5.7.17 Cost-Efficiency Curve for the VCS.SC.I Equipment Class

Table 5.7.18 Cost-Efficiency Data for the VCS.SC.I Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 25.12

 

1,483.43 

 

2,171.32 Baseline

AD2 22.82

 

1,495.60 

 

2,188.60 AD1 + Enhanced-UA Condenser Coil

AD3 21.57

 

1,503.87 

 

2,200.34 

AD2 + Permanent Split Cap. Evap. Fan 

Motor

AD4 20.48

 

1,512.95 

 

2,213.24 AD3 + Enhanced-UA Evaporator Coil

AD5 19.09

 

1,530.53 

 

2,238.20 AD4 + Brushless DC Evap. Fan Motor

AD6 18.24

 

1,544.60 

 

2,258.17 

AD5 + High-Eff. Reciprocating 

Compressor

AD7 18.11

 

1,553.90 

 

2,271.39 

AD6 + Permanent Split Cap. Cond. Fan 

Motor

AD8 17.79

 

1,586.24 

 

2,317.31 AD7 + Additional 1⁄2-inch Insulation

AD9 17.64

 

1,601.24 

 

2,338.60 AD8 + Brushless DC Cond. Fan Motor

AD10 16.53

 

2,968.45 

 

4,280.05 AD9 + Vacuum Insulated Panels

5-55
Figure 5.7.18 Cost-Efficiency Curve for the HCT.SC.M Equipment Class

Table 5.7.19 Cost-Efficiency Data for the HCT.SC.M Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 2.28

 

574.91 

 

836.64 Baseline

AD2 2.03

 

577.51 

 

840.33 AD1 + Enhanced-UA Condenser Coil

AD3 1.87

 

580.92 

 

845.17 

AD2 + High-Eff. Reciprocating 

Compressor

AD4 1.73

 

585.06 

 

851.04 

AD3 + Permanent Split Cap. Cond. Fan 

Motor

AD5 0.84

 

643.35 

 

933.83 AD4 + High-Performance Door

AD6 0.75

 

652.14 

 

946.31 AD5 + Brushless DC Cond. Fan Motor

AD7 0.67

 

679.02 

 

984.47 AD6 + Additional 1⁄2-inch Insulation

AD8 0.49

 

1,035.59 

 

1,490.80 AD7 + Vacuum Insulated Panels

5-56
Figure 5.7.19 Cost-Efficiency Curve for the HCT.SC.L Equipment Class

Table 5.7.20 Cost-Efficiency Data for the HCT.SC.L Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 5.17

 

661.43 

 

959.50 Baseline

AD2 4.52

 

666.13 

 

966.17 AD1 + Enhanced-UA Condenser Coil

AD3 4.11

 

673.06 

 

976.01 

AD2 + High-Eff. Reciprocating 

Compressor

AD4 1.83

 

731.35 

 

1,058.79 AD3 + High-Performance Door

AD5 1.77

 

735.49 

 

1,064.66 

AD4 + Permanent Split Cap. Cond. Fan 

Motor

AD6 1.70

 

744.28 

 

1,077.14 AD5 + Brushless DC Cond. Fan Motor

AD7 1.57

 

771.16 

 

1,115.31 AD6 + Additional 1⁄2-inch Insulation

AD8 1.18

 

1,253.50 

 

1,800.23 AD7 + Vacuum Insulated Panels

5-57
Figure 5.7.20 Cost-Efficiency Curve for the HCT.SC.I Equipment Class

Table 5.7.21 Cost-Efficiency Data for the HCT.SC.I Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 7.25

 

648.75 

 

939.46 Baseline

AD2 6.60

 

655.57 

 

949.15 

AD1 + High-Eff. Reciprocating 

Compressor

AD3 6.37

 

659.71 

 

955.02 

AD2 + Permanent Split Cap. Cond. Fan 

Motor

AD4 3.22

 

718.00 

 

1,037.80 AD3 + High-Performance Door

AD5 3.07

 

726.79 

 

1,050.29 AD4 + Brushless DC Cond. Fan Motor

AD6 2.86

 

753.93 

 

1,088.82 AD5 + Additional 1/2" Insulation

AD7 2.13

 

1,398.34 

 

2,003.87 AD6 + Vacuum Insulated Panels

5-58
Figure 5.7.21 Cost-Efficiency Curve for the HCS.SC.M Equipment Class

Table 5.7.22 Cost-Efficiency Data for the HCS.SC.M Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 0.73

 

509.12 

 

746.26 Baseline

AD2 0.65

 

509.96 

 

747.45 AD1 + Enhanced-UA Condenser Coil

AD3 0.60

 

513.37 

 

752.29 

AD2 + High-Eff. Reciprocating 

Compressor

AD4 0.56

 

517.51 

 

758.17 

AD3 + Permanent Split Cap. Cond. Fan 

Motor

AD5 0.50

 

526.30 

 

770.65 AD4 + Brushless DC Cond. Fan Motor

AD6 0.42

 

552.24 

 

807.48 AD5 + Additional 1⁄2-inch Insulation

AD7 0.25

 

831.03 

 

1,203.36 AD6 + Vacuum Insulated Panels

5-59
Figure 5.7.22 Cost-Efficiency Curve for the HCS.SC.L Equipment Class

Table 5.7.23 Cost-Efficiency Data for the HCS.SC.L Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 2.11

 

520.44 

 

762.34 Baseline

AD2 1.88

 

521.70 

 

764.12 AD1 + Enhanced-UA Condenser Coil

AD3 1.73

 

525.01 

 

768.82 

AD2 + High-Eff. Reciprocating 

Compressor

AD4 1.61

 

529.15 

 

774.69 

AD3 + Permanent Split Cap. Cond. Fan 

Motor

AD5 1.46

 

537.94 

 

787.18 AD4 + Brushless DC Cond. Fan Motor

AD6 1.27

 

563.88 

 

824.01 AD5 + Additional 1⁄2-inch Insulation

AD7 0.74

 

942.20 

 

1,361.22 AD6 + Vacuum Insulated Panels

5-60
Figure 5.7.23 Cost-Efficiency Curve for the SOC.RC.M Equipment Class

Table 5.7.24 Cost-Efficiency Data for the SOC.RC.M Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 29.30

 

5,022.51 

 

7,297.13 Baseline

AD2 28.18

 

5,041.13 

 

7,323.56 

AD1 + Permanent Split Cap. Evap. Fan 

Motor

AD3 27.01

 

5,061.81 

 

7,352.93 AD2 + Super T8 Lighting

AD4 25.62

 

5,091.80 

 

7,395.51 AD3 + Brushless DC Evap. Fan Motor

AD5 24.97

 

5,111.42 

 

7,423.38 AD4 + Enhanced-UA Evaporator Coil

AD6 20.43

 

5,438.96 

 

7,888.48 AD5 + LED Lighting

AD7 20.31

 

5,472.28 

 

7,935.80 AD6 + Additional 1⁄2-inch Insulation

AD8 20.15

 

5,575.69 

 

8,082.64 AD7 + High-Performance Door

AD9 19.93

 

6,467.08 

 

9,348.41 AD8 + Vacuum Insulated Panels

5-61
Figure 5.7.24 Cost-Efficiency Curve for the SOC.SC.M Equipment Class

Table 5.7.25 Cost-Efficiency Data for the SOC.SC.M Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 35.76 5,462.07 7,921.29 Baseline

AD2 34.32

 

5,471.63 

 

7,934.88 

AD1 + High-Eff. Reciprocating 

Compressor

AD3 31.97

 

5,497.92 

 

7,972.21 AD2 + Enhanced-UA Condenser Coil

AD4 30.77

 

5,516.54 

 

7,998.64 

AD3 + Permanent Split Cap. Evap. Fan 

Motor

AD5 29.53

 

5,537.22 

 

8,028.01 AD4 + Super T8 Lighting

AD6 28.04

 

5,567.21 

 

8,070.59 AD5 + Brushless DC Evap. Fan Motor

AD7 27.23

 

5,586.83 

 

8,098.45 AD6 + Enhanced-UA Evaporator Coil

AD8 27.04

 

5,596.14 

 

8,111.67 

AD7 + Permanent Split Cap. Cond. Fan 

Motor

AD9 26.80

 

5,611.13 

 

8,132.96 AD8 + Brushless DC Cond. Fan Motor

AD10 22.02

 

5,938.67 

 

8,598.07 AD9 + LED Lighting

AD11 21.88

 

5,971.99 

 

8,645.38 AD10 + Additional 1⁄2-inch Insulation

AD12 21.70

 

6,075.40 

 

8,792.22 AD11 + High-Performance Door

AD13 21.41

 

6,966.79 

 

10,057.99 AD12 + Vacuum Insulated Panels

5-62
Figure 5.7.25 Cost-Efficiency Curve for the PD.SC.M Equipment Class

Table 5.7.26 Cost-Efficiency Data for the PD.SC.M Equipment Class

Design Option 

Level

Calculated 

Daily Energy 

Consumption 

kWh/day

Manufacturer 

Production 

Cost 

$

Manufacturer 

Selling Price 

$

Design Option Added 

Above the Baseline

AD1 8.35 1,004.47 1,463.83 Baseline

AD2 5.14 1,019.71 1,485.48 AD1 + LED Lighting

AD3 4.80

 

1,024.37 

 

1,492.09 

AD2 + Permanent Split Cap. Evap. 

Fan Motor

AD4 4.49 1,030.03 1,500.13 AD3 + Enhanced-UA Condenser Coil

AD5 4.08 1,037.52 1,510.77 AD4 + Brushless DC Evap. Fan Motor

AD6 3.90

 

1,043.21 

 

1,518.85 

AD5 + High-Eff. Reciprocating 

Compressor

AD7 2.23 1,115.38 1,621.33 AD6 + High-Performance Door

AD8 2.20

 

1,120.03 

 

1,627.94 

AD7 + Permanent Split Cap. Cond. 

Fan Motor

AD9 2.16 1,127.53 1,638.58 AD8 + Brushless DC Cond. Fan Motor

AD10 1.75

 

1,218.01 

 

1,767.07 

AD9 + LED Lighting with Occupancy 

Sensors

AD11 1.64 1,247.84 1,809.42 AD10 + Additional 1⁄2-inch Insulation

AD12 1.64

 

1,252.07 

 

1,815.43 

AD11 + Enhanced-UA Evaporator 

Coil

AD13 1.42 1,853.57 2,669.56 AD12 + Vacuum Insulated Panels

5.8 OFFSET FACTORS

Equipment energy use scales with equipment size, but smaller equipment tends to use 

more energy per unit of TDA or volume than larger equipment in the same equipment class. This 

extra energy is attributed to components of case load that do not scale with equipment size. 

5-63
These load components therefore have a disproportionate effect on the energy consumption of 

small equipment. In its 2009 final rule, DOE developed offset factors to account for these load 

components, commonly referred to as “end effects,” as a way to adjust standards to allow more 

energy use for smaller equipment.

During the early stages of the 2009 final rule analysis, stakeholders raised concerns that 

standards developed for large sizes of equipment would be unfair when applied to smaller 

equipment in the same class, because of the end effects that disproportionately affect smaller 

equipment. In its engineering analysis, DOE developed cost-efficiency curves for a single size 

within each equipment class. The representative size selected for each class was toward the 

larger end of the equipment available within that class. DOE intended for standards to be based 

on this single analysis point (the point defined by TDA or volume and CDEC). Accordingly, in 

the 2009 rulemaking advance notice of proposed rulemaking, DOE expressed intent to 

implement standards by requiring equipment to meet an energy consumption limit defined by a 

line drawn between the origin and the point determined by the engineering cost-efficiency curve.

(See the left pane of Figure 5.8.1.) However, the stakeholder concerns previously mentioned led 

DOE to account for end effects in later stages of the rulemaking and in the final rule. As the right 

pane of Figure 5.8.1 shows, the offset factor fixes the left end of the standard equation at a fixed 

offset on the CDEC axis, effectively providing a higher limit on energy consumption for smaller 

equipment. 

Figure 5.8.1 Illustration of Offset Factor using TDA as the Normalization Metric

Using this methodology, a standard equation consists of two components: a sizedependent multiplier (slope) and a constant (offset factor). DOE calculated the slopes of the 

standard equations for its 2009 final rule standard levels as the difference between the CDEC at 

the analysis point corresponding to the selected standard level and the offset factor, divided by 

the value of the normalization metric at the analysis point. 

In determining offset factors in the 2009 final rule, DOE considered different end effects 

for each equipment family. For all open cases (VOP, SVO, and HZO), DOE considered the 

effects of heat conduction through the case ends, as well as the infiltration load end effects. For 

VCT cases, the conduction through the ends was taken into account, as well as the heat load and 

electrical load of one T8 lamp. In the remaining equipment families (SOC, HCT, VCS), DOE 

only considered the conduction effects through the case ends. DOE then summed these heat 

5-64
loads for each class and calculated the daily energy use of the compressor for that class. For all 

equipment classes except for those in the VCT equipment family, this became the offset factor. 

For VCT equipment, DOE also considered the amount of electrical energy consumed by lighting. 

These values then become the offset factors, representing energy use end effects for each 

equipment class in the 2009 final rule standard-level equations. Similarly, the EPACT 2005 

standard-level equations also contained analogous values that would provide a non-zero energy 

allowance at zero volume, representing the end effects for that equipment.

When developing standard-level equations for each primary equipment class at the five 

trial standard levels (TSLs) considered in this NOPR, DOE revised the offset factors in the 

current standard levels commensurately to reflect decreasing energy use by a given unit at higher 

TSLs. However, adjusting the offset factors and the analysis point (the energy consumption of 

the representative unit modeled in the engineering analysis) disproportionately in comparison to 

the values allowed by the current standards would cause a significant change in the slopes of the 

standard-level equations, resulting in standard levels that would negatively impact either smaller 

or larger units as compared to the existing EPACT 2005 and 2009 final rule standards. To avoid 

this, DOE instead scaled the existing offset factors from the 2009 final rule and EPACT 2005 

standards using the engineering analysis results for each equipment class at each TSL. DOE first 

calculated the allowable energy consumption under the existing standard for each class at the 

representative size analyzed, and then compared those standards values to the energy 

consumption values at each TSL produced by the engineering analysis. The ratio of these two 

values was then used as a multiplier on the existing offset factor for each equipment class at each 

TSL, and the resulting values were used as the offset factors for the new standard-level 

equations. 

5.9 EXTENSION OF ANALYSIS TO SECONDARY EQUIPMENT CLASSES

In its 2009 final rule, DOE did not analyze all covered equipment classes, but focused its 

analysis on 15 high-shipment equipment classes. In that rule, DOE developed an extension 

approach to apply the standards developed for these 15 “primary” classes to the remaining 23 

“secondary” classes. This approach involved extension multipliers developed with the 15 

primary results and a set of focused matched-pair analyses. The matched-pair analyses compared 

calculated energy consumption levels for pieces of equipment with similar designs but one major 

construction or operational difference corresponding to a change in the equipment family, 

condenser configuration, or operating temperature. For example, vertical open remote 

condensing cases operating at medium and low temperatures were compared in one portion of 

the analysis. The relationships between these sets of units were then used to determine the 

isolated effect of the given design or operational difference on applicable equipment. These 

extension multipliers represent the relationship in terms of energy consumption between 

different equipment classes, such as remote condensing and self-contained equipment with a 

given operating temperature and door configuration. In addition, DOE determined that standards 

for certain primary equipment classes could be directly applied to other similar secondary 

equipment classes, implying that the extension multiplier is equal to 1.0. Section 5.9.1 describes 

in detail the methodology that DOE used in the 2009 final rule analyses to develop extension 

multipliers. 

5-65
After examining the performance and characteristics of the equipment classes analyzed in 

the current rulemaking, DOE preserved the 2009 extension multiplier approach for application in 

this rulemaking. DOE’s use of this approach in the current rulemaking is discussed in detail in 

section 5.9.2. 

5.9.1 Development of Extension Multiplier Approach in 2009 Rulemaking 

During the 2009 rulemaking, DOE examined extending standards using the 15 primary 

equipment classes developed in its engineering analysis. Using size-normalized baseline energy 

consumption values, several trends became apparent for certain subgroups of equipment. DOE 

examined several related pairs of equipment classes to develop extension multipliers. 

First, DOE examined the energy consumption/TDA relationship between remote and 

self-contained medium-temperature equipment without doors (Table 5.9.1). There was 

reasonable agreement across equipment families among medium-temperature open equipment, 

with an average multiplier of 2.51 between remote and self-contained equipment. The 

differences between remote and self-contained equipment were similar for VOP, SVO, and HZO 

equipment. In addition to the inclusion of a self-contained condensing unit, which is less 

efficient than remote condensing systems, self-contained open equipment must have provisions 

for dealing with defrost meltwater. Because self-contained equipment is designed to be mobile, 

defrost meltwater must be collected in a drain pan and evaporated using electric-resistance 

heating. This feature adds considerable energy use to open self-contained equipment, helping to 

explain the larger energy consumption of self-contained equipment. The 2.51 multiplier was 

also applicable to low- and ice-cream-temperature equipment without doors. The differences in 

design were found to be similar for low-temperature and ice-cream-temperature equipment, 

consisting of a self-contained condensing unit and the addition of a defrost meltwater 

evaporation system. Thus, the 2.51 multiplier was applied to the following standard extensions 

in the 2009 final rule: 

• VOP.RC.L to VOP.SC.L

• SVO.RC.L to SVO.SC.L

• VOP.RC.I to VOP.SC.I

• SVO.RC.I to SVO.SC.I

• HZO.RC.I to HZO.SC.I

Table 5.9.1 Extension Multipliers for Remote and Self-Contained Equipment Without 

Doors 

Relationship CDEC/TDA Multiplier

VOP.RC.M to VOP.SC.M 2.431

SVO.RC.M to SVO.SC.M 2.376

HZO.RC.M to HZO.SC.M 2.712

DOE next examined the CDEC/TDA relationship between low-temperature and icecream-temperature remote equipment using a focused matched-pair analysis. The focused 

matched-pair analysis methodology established a correlation between rating temperature levels 

5-66
and CDEC/TDA, using data collected from manufacturer specification sheets. DOE quantified 

the differences in energy consumption for matched pairs of equipment classes that were very 

similar in features and dimensions but had different operating temperatures. Pairs of units at low 

and ice-cream temperatures were selected from several different manufacturers for comparison. 

From a given manufacturer DOE selected identical units designed to operate at multiple 

temperatures to isolate operating temperature as the only variable. 

The matched-pair results showed that VCT.RC.I units (at -15 °F) had on average 

CDEC/TDA values that were 1.17 times higher than comparable VCT.RC.L units. The 1.17 

multiplier was also applicable to other similar equipment types with doors. Differences in design 

consisted of a lower operating temperature (resulting in a lower compressor EER) and higher 

defrost and anti-sweat heater power. Thus, the 1.17 multiplier was applied to the following 

standard extensions: 

• SOC.RC.L to SOC.RC.I

• HCT.RC.L to HCT.RC.I

The matched-pair results further showed that HZO.RC.I units (at -15 °F) had on average 

CDEC/TDA values that were 1.27 times higher than comparable HZO.RC.L units. The 1.27 

multiplier was also applicable to other similar equipment types without doors. Differences in 

design consisted of a lower operating temperature (resulting in a lower compressor EER) and 

higher defrost and anti-sweat heater power. Thus, the 1.27 multiplier was applied to the 

following standard extensions: 

• VOP.RC.L to VOP.RC.I

• SVO.RC.L to SVO.RC.I

• VOP.SC.L to VOP.SC.I 

• SVO.SC.L to SVO.SC.I

• HZO.SC.L to HZO.SC.I

DOE next examined the CDEC/TDA relationship between remote and self-contained icecream-temperature equipment with transparent doors. To make this comparison, DOE used the 

matched-pair results to estimate the baseline CDEC/TDA values for VCT.RC.I equipment, and 

compared the results to VCT.SC.I equipment. The comparison showed that CDEC/TDA values 

for VCT.SC.I equipment were 1.40 times higher than VCT.RC.I equipment. DOE understood 

that this difference in energy use was due to the differences in efficiency of the self-contained 

condensing unit, as well as the addition of defrost meltwater evaporation systems. However, in 

contrast to open equipment, equipment with transparent doors is subject to a much lower 

infiltration load, and thus a lower meltwater evaporation requirement. This led to a lower 

multiplier than was seen for open equipment. The 1.40 multiplier was applied to the following 

standard extensions: 

• SOC.RC.I to SOC.SC.I 

• HCT.RC.I to HCT.SC.I

• VCS.RC.I to VCS.SC.I 

• HCS.RC.I to HCS.SC.I

5-67
Finally, DOE examined the relationship between medium- and low-temperature remote 

equipment with transparent doors. Both the VCT.RC.M and VCT.RC.L equipment classes were 

directly examined in the engineering analysis. Using the engineering results, the comparison 

showed that CDEC/TDA values for VCT.RC.L equipment were 2.10 times higher than 

VCT.RC.M equipment. This difference was due to the higher defrost heater power and antisweat heater power requirements of low-temperature equipment. The 2.10 multiplier was

applied to the standard extension from HCT.RC.M to HCT.RC.L in the 2009 final rule. 

5.9.2 Current Use of Extension Multiplier Methodology

In the current rulemaking, DOE preserved the extension multiplier approach and values

used in the 2009 final rule analysis (and described in section 5.9.1) for the classes covered under 

that rulemaking. As the standards set in the 2009 final rule carried a compliance date of January 

1, 2012, DOE was not able to analyze equipment manufactured to comply with those standards 

as part of its engineering analysis for the current rulemaking. Therefore DOE used, as discussed 

previously, a market baseline of available equipment specifications, which was the same as that 

used in the 2009 final rule. Because the extension multipliers were developed in the 2009 final 

rule based on normalized baseline energy consumption values, and the engineering baseline was 

not changed in this rulemaking, DOE believes that the multipliers from the 2009 rulemaking 

continue to accurately represent the relationship of the respective various equipment groups, and 

can be retained. Additionally, because these multipliers largely reflect the existence of basic 

differences in design features and thermal performance between classes, which will always exist 

regardless of efficiency improvement with the classes, DOE believes that these multipliers 

remain applicable to the equipment designs covered in the current rulemaking. 

DOE used these extension multipliers by applying them alone or in combination to the 

standard-level equations, based on the results of the engineering analysis and the offset factors 

calculated, that it had developed for the primary equipment classes at the baseline and each of 

the five TSLs. The result was a set of standard-level equations for all of the secondary equipment 

classes at the TSLs examined. The values of the extension multipliers used and the equipment 

type relationships to which they correspond are listed in Table 5.9.2. 

Table 5.9.2 Extension Multipliers

Extension 

Multiplier Value Extension Relationship

2.51 Medium temperature to low temperature; equipment without doors; Example, 

VOP.SC.M to VOP.SC.L

1.17 Low temperature to ice-cream temperature for equipment with transparent doors; 

Example, VCT.RC.L to VCT.RC.I

1.27 Low temperature to ice-cream temperature for equipment without doors; Example 

VOP.RC.L to VOP.RC.I

1.40 Remote condensing to self-contained for equipment with doors; Example 

VCS.RC.I to VCS.SC.I 

2.10 Medium temperature to low temperature for equipment with doors; Example 

SOC.RC.M to SOC.RC.L

These five extension multipliers were sufficient to extend standard-level equations from 

the primary equipment classes to all 24 secondary equipment classes. The specific extension 

5-68 
multiplier combinations used to yield standard-level equations at each TSL for the secondary 

classes are depicted in Table 5.9.3. 

Table 5.9.3 Extension Multipliers by Equipment Class

RC SC

I L M I L M

Open

VOP 1.27a a* b 1.27(2.51c) 2.51c c

SVO 1.27a a** d 1.27(2.51e) 2.51e e

HZO 1.27f f g 1.27h h i

Closed

SOC 1.17(2.10j) 2.10j j 1.40(1.17(2.10j)) 2.10p p

VCT 1.17k k l m

EPACT 2005 

Primary Classes†

HCT n/1.40 (n/1.40)/1.17 ((n/1.40)/1.17)/2.10 n

VCS o/1.40 (o/1.40)/1.17 ((o/1.40)/1.17)/2.10 o

HCS o/1.40 (o/1.40)/1.17 ((o/1.40)/1.17)/2.10 o**

*Classes represented by bold letters are primary classes examined directly in the engineering analysis

**The SVO.RC.L and HCS.SC.I classes were determined to have the exact same normalized baseline energy consumption levels 

as the VOP.RC.L and VCS.SC.I classes, respectively. †

Equipment classes for which standards were set in EPACT 2005 are all primary classes except for SOC.SC.L. Thus no 

extension multipliers were needed or relevant in developing proposed standards for these classes of EPACT 2005 equipment.

5-69
REFERENCES

1. ANSI/ASHRAE. Standard 72-2005, Method of Testing Commercial Refrigerators and 

Freezers. 2005. American Society of Heating, Refrigerating, and Air-Conditioning 

Engineers, Inc., Atlanta, GA. 

2. Electric Power Research Institute. Supermarket Simulation Tool v3.0. 2007. Palo Alto, 

CA.

3. Faramarzi, R. Efficient Display Case Refrigeration. ASHRAE Journal. November 1999. 

4. Watt Stopper/Legrand. Case Study – Watt Stopper/Legrand Helps Wal-Mart Achieve 

Environmental Goals. 2007. (Last accessed March 17, 2011.) 

<www.wattstopper.com/getdoc/2240/Casestudy_WalMart0707.pdf> 

5. U.S. DOE Solid State Lighting Technology Demonstration GATEWAY Program. 

Demonstration Assessment of Light-Emitting Diode (LED) Freezer Case Lighting. 2009. 

U.S. Department of Energy, Washington, D.C. 

6. Lawrence Berkley National Laboratory. Window 5.0. 2007. (Last accessed June 26, 2007.) 

<http://windows.lbl.gov/software/window/window.html> The June 26, 2007 material from 

this website is available in Docket #EE-2006-STD-0126. For more information, contact 

Brenda Edwards-Jones at (202) 586-2945. 

7. Southern California Edison Refrigeration Technology and Test Center. Effects of the Low 

Emissivity Shields on Performance and Power Use of a Refrigerated Display Case. 1997. 

Southern California Edison, Rancho Cucamonga, CA. 

8. Technischer Uberwachungs-Verein Rheinland E.V. Laboratory test results for energy 

savings on refrigerated dairy case, conducted for Econofrost. 

5-70
APPENDIX 5A. ENGINEERING DATA

TABLE OF CONTENTS

5A.1 INTRODUCTION ........................................................................................................ 5A-1

5A.2 BASELINE SPECIFICATIONS .................................................................................. 5A-1

5A.3 LIGHTING CONFIGURATIONS ............................................................................... 5A-8

LIST OF TABLES

Table 5A.2.1 Baseline Design Options ..................................................................................... 5A-2

Table 5A.2.2 Baseline Specifications ....................................................................................... 5A-5

LIST OF FIGURES

Figure 5A.3.1 Lighting Configurations for VCT.RC.M ......................................................... 5A-10

Figure 5A.3.2 Lighting Configurations for VCT.RC.L .......................................................... 5A-11

Figure 5A.3.3 Lighting Configurations for VCT.SC.M ......................................................... 5A-12

Figure 5A.3.4 Lighting Configurations for VCT.SC.L .......................................................... 5A-12

Figure 5A.3.5 Lighting Configurations for VCT.SC.I ........................................................... 5A-13

Figure 5A.3.6 Lighting Configurations for PD.SC.M ............................................................ 5A-13

Figure 5A.3.7 Lighting Configurations for VOP.RC.M ......................................................... 5A-14

Figure 5A.3.8 Lighting Configurations for VOP.SC.M ......................................................... 5A-15

Figure 5A.3.9 Lighting Configurations for VOP.RC.L .......................................................... 5A-15

Figure 5A.3.10 Lighting Configurations for SVO.RC.M ....................................................... 5A-16

Figure 5A.3.11 Lighting Configurations for SVO.SC.M ....................................................... 5A-16

Figure 5A.3.12 Lighting Configurations for SOC.RC.M ....................................................... 5A-17

5A-i 
APPENDIX 5A. ENGINEERING DATA

5A.1 INTRODUCTION

This appendix presents baseline specifications and other details for each of the 

commercial refrigeration equipment classes directly analyzed in the engineering analysis

(chapter 5 of the technical support document (TSD)). 

5A.2 BASELINE SPECIFICATIONS

Table 5A.2.1 shows baseline design options for each of the commercial refrigeration 

equipment classes analyzed in the engineering analysis. All changes to cost and efficiency are 

measured relative to this level in the engineering analysis. Refer to chapter 5 of the TSD for 

details about each baseline technology.

Table 5A.2.2 shows baseline specifications (or case design specifications) for each of the 

commercial refrigeration equipment classes analyzed in the engineering analysis. These 

specifications include dimensions, numbers of components, temperatures, nominal power 

ratings, and other case features that are necessary to calculate the energy consumption of each 

equipment class. In conjunction with baseline design option levels, the baseline specifications 

define the energy consumption and cost of the typical minimum technology equipment on the 

market.

5A-1 
Table 5A.2.1 Baseline Design Optionsa

VOP.RC.M VOP.RC.L VOP.SC.M SVO.RC.M SVO.SC.M HZO.RC.M HZO.RC.L HZO.SC.M

Lighting for VOP, SVO, 

and SOC

T8 

Electronic

T8 

Electronic

T8 

Electronic

T8 

Electronic

T8 Electronic - - -

Lighting for VCT and PD - - - - - - - -

Evaporator Coil Standard 

Coil

Standard 

Coil

Standard 

Coil

Standard 

Coil

Standard Coil Standard 

Coil

Standard 

Coil

Standard 

Coil

Evaporator Fan Motors Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded Pole

Case Insulation Standard Standard Standard Standard Standard Standard Standard Standard

Doors for VCT.XX.L/I - - - - - - - -

Doors for VCT/PD.XX.M - - - - - - - -

Doors for HCT.XX.L/I - - - - - - - -

Doors for HCT.XX.M - - - - - - - -

Doors for SOC.XX.L/I - - - - - - - -

Doors for SOC.XX.M - - - - - - - -

Condenser Coil Area 

(SC Only)

- - Standard - Standard - - Standard

Condenser Fan Motors 

(SC only)

- - Shaded Pole - Shaded Pole - - Shaded Pole

Compressor (SC only) - - SingleSpeed 

Hermetic

- Single-Speed 

Hermetic

- - SingleSpeed 

Hermetic

Night Curtains None None None None None - - -

a Equipment class designations consist of a combination—in sequential order separated by a period—of an equipment family code (VOP - vertical open, SVO - 

semivertical open, HZO - horizontal open, VCT - vertical closed transparent, VCS - vertical closed solid, HCT - horizontal closed transparent, HCS - horizontal 

closed solid, SOC - service over counter, or PD – pull-down equipment), an operating mode code (RC - remote condensing or SC - self-contained), and a rating 

temperature code (M - medium temperature, L - low temperature, or I - ice-cream temperature). See chapter 3, Market and Technology Assessment, for a more 

detailed explanation of the equipment class terminology.

5A-2 

 
Table 5A.2.1 (cont)

HZO.SC.L VCT.RC.M VCT.RC.L VCT.SC.M VCT.SC.L VCT.SC.I VCS.SC.M VCS.SC.L VCS.SC.I

Lighting for VOP, 

SVO, and SOC

- - - - - - - - -

Lighting for VCT and 

PD

- T8 

Electronic

T8 

Electronic

T8 

Electronic

T8 

Electronic

T8 

Electronic

- - -

Evaporator Coil Standard Standard Standard Standard Standard Standard Standard Standard Standard

Evaporator Fan 

Motors

Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded 

Pole

Case Insulation Standard Standard Standard Standard Standard Standard Standard Standard Standard

Doors for 

VCT.XX.L/I 

- - Standard - Standard Standard - - -

Doors for 

VCT/PD.XX.M

- Standard - Standard - - - - -

Doors for 

HCT.XX.L/I 

- - - - - - - - -

Doors for 

HCT.XX.M

- - - - - - - - -

Doors for 

SOC.XX.L/I

- - - - - - - - -

Doors for SOC.XX.M - - - - - - - - -

Condenser Coil Area 

(SC Only)

Standard - - Standard Standard Standard Standard Standard Standard

Condenser Fan 

Motors 

(SC only)

Shaded Pole - - Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded 

Pole

Compressor (SC 

only)

Single-Speed 

Hermetic

- - SingleSpeed 

Hermetic

SingleSpeed 

Hermetic

SingleSpeed 

Hermetic

SingleSpeed 

Hermetic

SingleSpeed 

Hermetic

SingleSpeed 

Hermetic

Night Curtains - - - - - - - - -

5A-3 
Table 5A.2.1 (cont)

HCT.SC.M HCT.SC.L HCT.SC.I HCS.SC.M HCS.SC.L SOC.SC.M SOC.RC.M PD.SC.M

Lighting for VOP, 

SVO, and SOC

- - - - - T8 

Electronic

T8 

Electronic

-

Lighting for VCT and 

PD

- - - - - - - T8 

Electronic

Evaporator Coil - - - - - Standard Standard Standard

Evaporator Fan 

Motors

- - - - - Shaded Pole Shaded Pole Shaded Pole

Case Insulation Standard Standard Standard Standard Standard Standard Standard Standard

Doors for 

VCT.XX.L/I 

- - - - - - - -

Doors for 

VCT/PD.XX.M

- - - - - - - Standard

Doors for 

HCT.XX.L/I 

- Standard Standard - - - - -

Doors for HCT.XX.M Standard - - - - - - -

Doors for 

SOC.XX.L/I

- - - - - - - -

Doors for SOC.XX.M - - - - - Standard Standard -

Condenser Coil Area 

(SC Only)

Standard Standard Standard Standard Standard Standard - Standard

Condenser Fan 

Motors 

(SC only)

Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded Pole Shaded Pole - Shaded Pole

Compressor (SC only) SingleSpeed 

Hermetic

SingleSpeed 

Hermetic

SingleSpeed 

Hermetic

SingleSpeed 

Hermetic

SingleSpeed 

Hermetic

SingleSpeed 

Hermetic

- SingleSpeed 

Hermetic

Night Curtains - - - - - - - -

5A-4 
Table 5A.2.2 Baseline Specifications

VOP.RC.M VOP.RC.L VOP.SC.M SVO.RC.M SVO.SC.M HZO.RC.M HZO.RC.L

Case Length (ft) 12 12 4 12 4 12 12

Case Gross Refrigerated Volume (ft3) 130.2 109.83 32 46.55 9.4 33 55

Case Total Display Area (ft2) 53.3 44.66 14.93 40 12.8 33 46

Number of Doors (#) 0 0 0 0 0 0 0

Single Door Area (ft2) 0 0 0 0 0 0 0

Non-Door Glass Area (ft2) 0 0 0 0 0 0 0

Non-Door Anti-Sweat Power (W) 0 600 0 50 100 50 200

Wall Area (ft2) 175.925 214 61 113.4 40.2 93.275 140

Insulation Thickness (in.) 1.5 2 1.5 1.5 1.5 1.5 2

Case Interior Surface Area (ft2) 130.225 118.5 47.5 72.5 21.3 48.35 82

Air Curtain Angle from Vertical (°) 8.5 7.28 6.05 47 57 82 90

Infiltrated Air Mass Flow (lb/hr) 860 530 300 590 220 250 140

Number of Bulbs in Conditioned Space (#) 12 0 4 9 3 0 0

Number of Bulbs Not in Conditioned Space (#) 9 9 3 6 2 0 0

Number of Ballasts in Conditioned Space (#) 0 0 0 0 0 0 0

Number of Ballasts Not in Conditioned Space (#) 7 3 3 5 2 0 0

Evaporator Fan Nominal Rated Wattage (W/fan) 9 9 6 9 6 9 9

Number of Evaporator Fans per Case (#) 6 14 2 4 1 4 4

Condenser Fan Nominal Rated Wattage (W/fan) 0 0 9 0 9 0 0

Number of Condenser Fans per Case (#) 0 0 3 0 2 0 0

Discharge Air Temperature (DAT) (F) 25 -10 25 25 25 25 -10

Baseline Evaporator Temperature (SET) (F) 15 -20 15 15 15 15 -20

Baseline Condenser Temperature (SCT) (F) 0 0 95 0 95 0 0

Compressor Oversize Multiplier 0 0 1.3 0 1.3 0 0

Defrost Mechanism (OFF, ELE, MAN) OFF ELE OFF OFF OFF ELE ELE

Defrost Time per Day (hr) 4.5 2 2.8 3 2.8 1 1

Defrost and Drain Heater Power (W) 0 8700 0 0 0 1000 3000

Condensate Pan Heater Power (W) 0 0 1500 0 1100 0 0

5A-5 
Table 5A.2.2 (cont)

HZO.SC.M HZO.SC.L VCT.RC.M VCT.RC.L VCT.SC.M VCT.SC.L VCT.SC.I

Case Length (ft) 4 4 12.725 12.74 4.5 4.5 4.3

Case Gross Refrigerated Volume (ft3) 7.5 7.4 142 133.5 49 49 48

Case Total Display Area (ft2) 12 12 65 65 20.7 20.7 26

Number of Doors (#) 0 0 5 5 2 2 2

Single Door Area (ft2) 0 0 13 13 10.35 10.35 13

Non-Door Glass Area (ft2) 4 4 0 0 0 0 0

Non-Door Anti-Sweat Power (W) 100 300 0 0 0 0 0

Wall Area (ft2) 54 52 204 200 73.02 73.02 77

Insulation Thickness (in.) 1.5 2 1.5 2 1.5 2 2.5

Case Interior Surface Area (ft2) 19.8 19.5 146.5 145 63.98 63.98 64

Air Curtain Angle from Vertical (°) 85 85 - - - - -

Infiltrated Air Mass Flow (lb/hr) 100 100 30 30 10.61 10.60 15

Number of Bulbs in Conditioned Space (#) 0 0 6 6 3 3 3

Number of Bulbs Not in Conditioned Space (#) 0 0 0 0 0 0 0

Number of Ballasts in Conditioned Space (#) 0 0 6 6 3 3 3

Number of Ballasts Not in Conditioned Space (#) 0 0 0 0 0 0 0

Evaporator Fan Nominal Rated Wattage (W/fan) 6 9 6 9 6 9 9

Number of Evaporator Fans per Case (#) 1 1 5 5 2 2 2

Condenser Fan Nominal Rated Wattage (W/fan) 6 6 0 0 6 6 6

Number of Condenser Fans per Case (#) 1 1 0 0 2 2 2

Discharge Air Temperature (DAT) (F) 25 -10 32 -5 32 -5 -20

Baseline Evaporator Temperature (SET) (F) 15 -20 27 -11 27 -11 -30

Baseline Condenser Temperature (SCT) (F) 95 95 0 0 95 95 95

Compressor Oversize Multiplier 1.3 1.3 0 0 1.3 1.3 1.3

Defrost Mechanism (OFF, ELE, MAN) ELE ELE OFF ELE OFF ELE ELE

Defrost Time per Day (hr) 1 1.5 1 1 1 1 1

Defrost and Drain Heater Power (W) 400 900 0 5000 0 1766.09 2580

Condensate Pan Heater Power (W) 300 400 0 0 0 200 200

 

5A-6 
Table 5A.2.2 (cont)

VCS.SC.M VCS.SC.L VCS.SC.I HCT.SC.M HCT.SC.L HCT.SC.I HCS.SC.M

Case Length (ft) 4.5 4.5 4.3 3.8 3.8 3.42 4.2

Case Gross Refrigerated Volume (ft3) 49 49 48 8.83 8.83 10.2 7.03

Case Total Display Area (ft2) 0 0 0 7.656 7.656 5.12 0

Number of Doors (#) 2 2 2 2 2 2 1

Single Door Area (ft2) 10.35 10.35 13 3.828 3.828 2.56 7.03

Non-Door Glass Area (ft2) 0 0 0 0 0 0 0

Non-Door Anti-Sweat Power (W) 0 0 250 0 0 0 0

Wall Area (ft2) 73.02 73.02 77 34.75 34.75 36.77 27.50

Insulation Thickness (in.) 1.5 2 2.5 1.5 2 2.5 1.5

Case Interior Surface Area (ft2) 0 0 0 0 21.34 26.1 0

Air Curtain Angle from Vertical (°) - - - - - - -

Infiltrated Air Mass Flow (lb/hr) 10.61 10.60 15 2.25 2.25 3 2.49

Number of Bulbs in Conditioned Space (#) 0 0 0 0 0 0 0

Number of Bulbs Not in Conditioned Space (#) 0 0 0 0 0 0 0

Number of Ballasts in Conditioned Space (#) 0 0 0 0 0 0 0

Number of Ballasts Not in Conditioned Space (#) 0 0 0 0 0 0 0

Evaporator Fan Nominal Rated Wattage (W/fan) 6 9 9 0 0 0 0

Number of Evaporator Fans per Case (#) 2 2 2 0 0 0 0

Condenser Fan Nominal Rated Wattage (W/fan) 6 6 6 9 9 9 9

Number of Condenser Fans per Case (#) 2 2 2 1 1 1 1

Discharge Air Temperature (DAT) (F) 32 -5 -20 32 -5 -20 32

Baseline Evaporator Temperature (SET) (F) 27 -11 -30 27 -11 -30 27

Baseline Condenser Temperature (SCT) (F) 95 95 95 95 95 95 95

Compressor Oversize Multiplier 1.3 1.3 1.3 1.3 1.3 1.3 1.3

Defrost Mechanism (OFF, ELE, MAN) OFF ELE ELE OFF MAN MAN OFF

Defrost Time per Day (hr) 1 1 1 1 0 0 1

Defrost and Drain Heater Power (W) 0 1766.09 2580 0 0 0 0

Condensate Pan Heater Power (W) 0 200 200 0 0 0 0

 

5A-7 
Table 5A.2.2 (cont)

HCS.SC.L SOC.SC.M SOC.RC.M PD.SC.M

Case Length (ft) 4.2 12 12 2.5

Case Gross Refrigerated Volume (ft3) 7.03 66 66 27

Case Total Display Area (ft2) 0 51 51 11.6

Number of Doors (#) 2 6 6 1

Single Door Area (ft2) 3.125 3.5 3.5 11.6

Non-Door Glass Area (ft2) 0 30 30 0

Non-Door Anti-Sweat Power (W) 0 200 200 0

Wall Area (ft2) 27.5 84.6 84.6 57.58

Insulation Thickness (in.) 2 1.5 1.5 1.5

Case Interior Surface Area (ft2) 0 61.6 61.6 46.71

Air Curtain Angle from Vertical (°) - - - -

Infiltrated Air Mass Flow (lb/hr) 2.49 15 15 5.89

Number of Bulbs in Conditioned Space (#) 0 15 15 2

Number of Bulbs Not in Conditioned Space (#) 0 0 0 0

Number of Ballasts in Conditioned Space (#) 0 0 0 1

Number of Ballasts Not in Conditioned Space (#) 0 5 5 0

Evaporator Fan Nominal Rated Wattage (W/fan) 0 6 6 6

Number of Evaporator Fans per Case (#) 0 4 4 1

Condenser Fan Nominal Rated Wattage (W/fan) 9 6 0 6

Number of Condenser Fans per Case (#) 1 2 0 1

Discharge Air Temperature (DAT) (F) -5 30 30 32

Baseline Evaporator Temperature (SET) (F) -11 20 20 27

Baseline Condenser Temperature (SCT) (F) 95 95 0 95

Compressor Oversize Multiplier 1.3 1.3 0 2

Defrost Mechanism (OFF, ELE, MAN) MAN ELE ELE OFF

Defrost Time per Day (hr) 0 1.2 1.2 1

Defrost and Drain Heater Power (W) 0 1600 1600 0

Condensate Pan Heater Power (W) 0 0 0 0

5A.3 LIGHTING CONFIGURATIONS

Lighting for use in cases with transparent doors functions differently than lighting for use 

in cases without doors. Cases with transparent doors typically display boxed merchandise, and 

only products on the front of the shelves are visible to the consumer. Therefore, the only portion 

of the display case that requires illumination is the area on the front surface of the case at the 

front of the shelves. Since this is only a limited area that requires lighting, light-emitting diodes 

(LEDs) offer an advantage over fluorescent lighting in vertical refrigerated cases with 

transparent doors because of the directional nature of LED lighting. 

As part of the engineering analysis for the 2009 final rule (74 FR 1092 (Jan. 9, 2009)), 

the U.S. Department of Energy (DOE), with input from manufacturers and other stakeholders, 

developed lighting configurations for cases with transparent doors. DOE has retained these 

configurations as part of this analysis, and has further developed additional configurations for 

equipment classes not covered in the 2009 rulemaking. For the VCT equipment family, DOE 

assumed one fluorescent bulb on each mullion and a fluorescent bulb on each end of the case. 

There are two different types of LED lighting used in cases with transparent doors. A center 

mullion lighting fixture is used between doors and is designed to have half of the LED emitters

directed toward one door and half of the LED chips directed toward the other door. An end 

mullion lighting fixture has half the light output, cost, and power consumption of a center 

5A-8 
mullion lighting fixture. The LED emitters in an end mullion lighting fixture are all directed 

toward the one door next to which they are located. Therefore, two end mullion lighting fixtures 

are the approximately equivalent to a single center mullion lighting fixture with regard to cost, 

light output, and power consumption. DOE modeled the LED lighting for the VCT equipment 

family using a center mullion lighting fixture and assumed one center mullion lighting fixture per 

door. Illustrative front views of the lighting configurations for both fluorescent and LED lighting 

for the VCT equipment family are shown in Figure 5A.3.1 through Figure 5A.3.6. The red strips 

represent a fluorescent bulb inside the refrigerated volume, the blue strips represent an LED 

center mullion lighting fixture inside the refrigerated volume, and the green strips represent an 

LED end mullion lighting fixture inside the refrigerated volume. 

5A-9 
Figure 5A.3.1 Lighting Configurations for VCT.RC.M

Bulb In =

LED In = Center Mullion

1/2 LED In = End Mullion (one on either end of case, resulting in the

 equivalent of a single center mullion)

VCT.RC.M

Lighting Type: Fluorescent

Case Length [ft]:12.7

Bulb Length [ft]: 5

Bulbs In: 6

Bulbs Out: 0

VCT.RC.M

Lighting Type: LED

Case Length [ft]:12.7

Bulb Length [ft]: 5

LEDs In: 5

LEDs Out: 0

5A-10
Figure 5A.3.2 Lighting Configurations for VCT.RC.L

VCT.RC.L

Lighting Type: Fluorescent

Case Length [ft]: 12.7

Bulb Length [ft]: 5

Bulbs In: 6

Bulbs Out: 0

VCT.RC.L

Lighting Type: LED

Case Length [ft]: 12.7

Bulb Length [ft]: 5

LEDs In: 5

LEDs Out: 0

5A-11
Figure 5A.3.3 Lighting Configurations for VCT.SC.M

Figure 5A.3.4 Lighting Configurations for VCT.SC.L

VCT.SC.M

Lighting Type: Fluorescent

Case Length [ft]: 4.5

Bulb Length [ft]: 5

Bulbs In: 3

Bulbs Out: 0

VCT.SC.M

Lighting Type: LED

Case Length [ft]: 4.5

Bulb Length [ft]: 5

LEDs In: 2

LEDs Out: 0

VCT.SC.L

Lighting Type: Fluorescent

Case Length [ft]: 4.5

Bulb Length [ft]: 5

Bulbs In: 3

Bulbs Out: 0

VCT.SC.L

Lighting Type: LED

Case Length [ft]: 4.5

Bulb Length [ft]: 5

LEDs In: 2

LEDs Out: 0

5A-12
Figure 5A.3.5 Lighting Configurations for VCT.SC.I

Figure 5A.3.6 Lighting Configurations for PD.SC.M

For equipment classes without doors (i.e., VOP, SVO, and HZO equipment families), as 

well as service over counter equipment, merchandise throughout the entire refrigerated volume is 

visible to the consumer. Therefore, the entire refrigerated volume must be illuminated.b For this 

application, the directionality characteristic of LED lighting tends to be less effective than 

fluorescent lighting, which outputs light in all directions surrounding the bulb. In the 2009 final 

b DOE assumes that the HZO equipment family does not contain any lighting because the ambient light of the store 

provides adequate illumination of the displayed merchandise. This is consistent with current manufacturer practice. 

VCT.SC.I

Lighting Type: Fluorescent

Case Length [ft]: 4.3

Bulb Length [ft]: 5

Bulbs In: 3

Bulbs Out: 0

VCT.SC.I

Lighting Type: LED

Case Length [ft]: 4.3

Bulb Length [ft]: 5

LEDs In: 2

LEDs Out: 0

PD.SC.M

Lighting Type: Fluorescent

Case Length [ft]: 2.5

Bulb Length [ft]: 5

Bulbs In: 2

Bulbs Out: 0

PD.SC.M

Lighting Type: LED

Case Length [ft]: 2.5

Bulb Length [ft]: 5

LEDs In: 1

LEDs Out: 0

5A-13

 
rule, DOE developed case lighting configurations for these classes as well. Based on discussions 

with LED refrigerated display case lighting manufacturers and comments from commercial 

refrigeration equipment manufacturers, DOE determined that there are two different types of 

LED luminaries used in this equipment. A shelf light is used to illuminate merchandise close to 

it. Due to the directionality of the light output from an LED luminary, DOE assumes that two 

shelf lights are used per shelf to provide the desired illumination throughout an entire shelf: one 

on the front of the shelf and one midway under the shelf. A canopy light is typically located on 

the canopy of a display case. A canopy light has effectively twice the light output, cost, and 

power consumption of a shelf light and is typically is used to provide additional illumination of 

the product in the bottom well of the display case. DOE modeled the LED lighting for the VOP, 

SVO, and SOC equipment families, in the engineering analysis, using a shelf light. DOE also 

assumed that the number of LED lighting fixtures per shelf would have to be doubled from what 

was assumed for fluorescent lighting to provide adequate illumination for the merchandise 

displayed on each shelf. Illustrative cross-sections of lighting configurations for both fluorescent 

and LED lighting for example classes in the VOP, SVO, and SOC equipment families are shown 

in Figure 5A.3.7 through Figure 5A.3.12. The green circles represent a bulb or LED inside the 

refrigerated volume and the red circles represent a bulb or LED outside the refrigerated volume. 

Figure 5A.3.7 Lighting Configurations for VOP.RC.M

Bulb/LED In =

Bulb/LED Out =

VOP.RC.M VOP.RC.M

Lighting Type: Fluorescent Lighting Type: LED

Case Length [ft]: 12 Case Length [ft]: 12

Bulb Length [ft]: 4 LED Length [ft]: 4

Bulbs In: 12 LEDs In: 24

Bulbs Out: 9 LEDs Out: 9

5A-14
Figure 5A.3.8 Lighting Configurations for VOP.SC.M

Figure 5A.3.9 Lighting Configurations for VOP.RC.L

VOP.SC.M VOP.SC.M

Lighting Type: Fluorescent Lighting Type: LED

Case Length [ft]: 4 Case Length [ft]: 4

Bulb Length [ft]: 4 LED Length [ft]: 4

Bulbs In: 4 LEDs In: 8

Bulbs Out: 3 LEDs Out: 3

VOP.RC.L VOP.RC.L

Lighting Type: Fluorescent Lighting Type: LED

Case Length [ft]: 12 Case Length [ft]: 12

Bulb Length [ft]: 4 LED Length [ft]: 4

Bulbs In: 0 LEDs In: 0

Bulbs Out: 9 LEDs Out: 9

5A-15
Figure 5A.3.10 Lighting Configurations for SVO.RC.M 

Figure 5A.3.11 Lighting Configurations for SVO.SC.M 

SVO.RC.M SVO.RC.M

Lighting Type: Fluorescent Lighting Type: LED

Case Length [ft]: 12 Case Length [ft]: 12

Bulb Length [ft]: 4 LED Length [ft]: 4

Bulbs In: 9 LEDs In: 18

Bulbs Out: 6 LEDs Out: 6

SVO.SC.M SVO.SC.M

Lighting Type: Fluorescent Lighting Type: LED

Case Length [ft]: 4 Case Length [ft]: 4

Bulb Length [ft]: 4 LED Length [ft]: 4

Bulbs In: 3 LEDs In: 6

Bulbs Out: 2 LEDs Out: 2

5A-16
Figure 5A.3.12 Lighting Configurations for SOC.RC.M 

SOC.RC.M SOC.RC.M

Lighting Type: Fluorescent Lighting Type: LED

Case Length [ft]: 12 Case Length [ft]: 12

Bulb Length [ft]: 4 LED Length [ft]: 4

Bulbs In: 15 LEDs In: 18

Bulbs Out: 0 LEDs Out: 0

5A-17
6-i 

CHAPTER 6. MARKUPS FOR EQUIPMENT PRICE DETERMINATION

TABLE OF CONTENTS

6.1 INTRODUCTION .............................................................................................................. 6-1

6.2 BASELINE, INCREMENTAL, AND OVERALL MARKUPS ........................................ 6-1

6.2.1 Baseline Markups ................................................................................................. 6-2

6.2.2 Incremental Markups ........................................................................................... 6-2

6.2.3 Distribution Channel Market Shares .................................................................... 6-3

6.2.4 Overall Markups .................................................................................................. 6-4

6.3 BASIC ASSUMPTIONS USED TO ESTIMATE WHOLESALER AND 

MECHANICAL CONTRACTOR MARKUPS ................................................................. 6-5

6.4 ESTIMATION OF WHOLESALER MARKUPS.............................................................. 6-6

6.5 ESTIMATION OF MECHANICAL CONTRACTOR MARKUPS .................................. 6-7

6.6 ESTIMATION OF NATIONAL ACCOUNT MARKUPS ................................................ 6-9

6.7 SALES TAX ..................................................................................................................... 6-10

6.8 MARKUPS RESULTS ..................................................................................................... 6-11

REFERENCES .......................................................................................................................... 6-13

LIST OF TABLES

Table 6.2.1 Distribution Channels Market Shares for Commercial Refrigeration 

Equipment ............................................................................................................ 6-4

Table 6.4.1 Wholesaler Expenses and Markups* ........................................................................ 6-7

Table 6.5.1 Mechanical Contractor Expenses and Markups* ...................................................... 6-8

Table 6.7.1 State Sales Tax Rates .............................................................................................. 6-11

Table 6.8.1 Baseline Markups by Distribution Channel and Overall Weighted Average 

Markup ............................................................................................................... 6-11

Table 6.8.2 Incremental Markups by Distribution Channel and Overall Weighted Average 

Markup ............................................................................................................... 6-11

LIST OF FIGURES

Figure 6.5.1 Cumulative Distribution of Mechanical Contractor Markups for Commercial 

Refrigeration Equipment ...................................................................................... 6-9
6-1 

CHAPTER 6. MARKUPS FOR EQUIPMENT PRICE DETERMINATION

6.1 INTRODUCTION

One of the most important inputs to the life-cycle cost (LCC) and payback period (PBP)

analysis and the national impact analysis (NIA) is the installed cost of the commercial 

refrigeration equipment. Installed cost includes equipment purchase price and installation costs. 

The U.S. Department of Energy (DOE) determines the equipment purchase price by using 

multipliers called “markups” that are applied to the manufacturer production cost (MPC) to 

obtain the customer purchase price of the equipment. The manufacturer markup, calculated as 

part of the engineering analysis (see chapter 5 of the technical support document (TSD)), 

converts the MPC into manufacturer selling price (MSP). Additional markups, called distribution 

channel markups, are applied to the MSP based on the distribution channels through which 

customers purchase the equipment to obtain the customer purchase price of the equipment. This 

chapter describes the methodology used by DOE to calculate the distribution channel markups 

and also the methodology by which the markups values are used to obtain the customer purchase 

price of the commercial refrigeration equipment.

DOE determined that commercial refrigeration equipment is purchased by the customers 

through three major distribution channels: 

Manufacturer  Customer (National Account Channel) 

Manufacturer  Wholesaler  Customer (Wholesaler Channel) 

Manufacturer  Wholesaler  Mechanical Contractor  Customer (Contractor Channel) 

In addition to the manufacturer markup and distribution channel markups, sales tax is 

applied to obtain the customer purchase price of the equipment. Sales tax varies by the state in 

which the equipment is installed. 

DOE first calculated national-average markup values for each distribution channel. DOE 

carried out the LCC analysis in the form of Monte Carlo simulations, and one of the inputs to 

each analysis simulation was the state (location) in which the equipment was installed (see TSD 

chapter 8 for detailed description). For each analysis simulation in the LCC analysis, the values 

used for the national account channel markup and wholesaler channel markup were the national 

average values. However, the contractor channel markup was varied by state (explained later in 

this chapter). The three distribution channel markup values were weighted-averaged using the 

market share of each distribution channel to obtain weighted-average distribution channel 

markups for each analysis simulation in the LCC analysis. In addition to the distribution channel 

markups, a sales tax was applied to obtain the customer purchase price of the equipment. 

6.2 BASELINE, INCREMENTAL, AND OVERALL MARKUPS

Baseline markups are the markups that convert the MSP of equipment of the baseline 

efficiency level to customer purchase price. Incremental markups are markups that convert the 

increase in MSP of equipment at higher efficiency levels to an increase in customer purchase 
6-2 

price compared to the price of equipment at the baseline efficiency level. Overall markups 

include the weighted-average distribution channel markups, based on the distribution channel 

market share, and sales tax.

6.2.1 Baseline Markups

If the baseline equipment is sold to a customer by the manufacturer through the national 

account channel, the following equation defines the equipment price: 

EQPNATL ACCT BASE = MFGBASE × MUNATL ACCT BASE × (1 + ST)

Eq. 6.1 

Where:

EQPNATL ACCNT BASE = national account price to the customer of baseline equipment ($), 

MFGBASE = MSP of baseline equipment ($), 

MUNATL ACCT BASE = national account markup on baseline equipment, and 

ST = sales tax rate.

If the baseline equipment is sold to a customer through the wholesaler channel: 

EQPWHOLE BASE = MFGBASE × MUWHOLE BASE × (1 + ST)

Eq. 6.2 

Where:

EQPWHOLE BASE = wholesaler price of baseline equipment ($), and 

MUWHOLE BASE = wholesaler markup on baseline equipment. 

If the baseline equipment is sold to a customer through the contractor channel: 

EQPMECH CONT BASE = MFGBASE × MUWHOLE BASE × MUMECH CONT BASE × (1 + ST)

Eq. 6.3 

Where:

EQPMECH CONT BASE = mechanical contractor price of baseline equipment ($), and 

MUMECH CONT BASE = mechanical contractor markup on baseline equipment. 

6.2.2 Incremental Markups

Incremental markups are cost multipliers that relate increments in the MSP of equipment 

at higher efficiency levels to the corresponding increments in the customer purchase price.

Similar to the baseline markups, DOE calculated one incremental markup value for each 

distribution channel. The increment in MSP of equipment at higher efficiency levels is obtained 

by subtracting the MSP of equipment at the baseline efficiency level (MFGBASE) from the MSP 

of equipment at higher efficiency levels. 
6-3 

MFGINCR = MFGHIGHER EFF LEVEL−MFGBASE

Eq. 6.4 

Where:

MFG INCR = increment in MSP of higher efficiency equipment ($), and 

MFGHIGHER EFF LEVEL = MSP of equipment at higher efficiency level ($). 

If the equipment is sold to a customer by the manufacturer through a national account, the 

following equation defines the increase in equipment price: 

EQPNATL ACCT INCR = MFGINCR × MUNATL ACCT INCR × (1 + ST)

Eq. 6.5 

Where:

EQPNATL ACCNT INCR = increment in customer purchase price to the national account customer ($),

and 

MUNATL ACCT INCR = national account channel incremental markup. 

If the customer acquires the higher efficiency equipment through the wholesaler or 

contractor channels: 

EQPWHOLE INCR = MFGINCR × MUWHOLE INCR × (1 + ST)

Eq. 6.6 

Where:

EQPWHOLE INCR = incremental wholesaler price ($), and 

MUWHOLE INCR = wholesaler channel incremental markup. 

EQPMECH CONT INCR = MFGINCR × MUWHOLE INCR × MUMECH CONT INCR × (1 + ST)

Eq. 6.7 

Where:

EQPMECH CONT INCR = incremental mechanical contractor price ($), and 

MUMECH CONT INCR = mechanical contractor channel incremental markup.

6.2.3 Distribution Channel Market Shares

For the 2009 final rule analysis, market shares of the three distribution channels were 

based on estimates provided by Carrier Corporation to DOE during the public review of the 

advanced notice of proposed rulemaking. 73 FR 50094 (Aug. 25, 2008). Also, during the 

preliminary analysis, DOE obtained additional data from articles on the Foodservice Equipment 

& Supplies (FE&S) magazine website,1

 which provided market shares for distribution channels 

for all foodservice equipment sales. Refrigeration equipment used in the foodservice industry is 

primarily composed of self-contained equipment. Refrigeration equipment constitutes only 

8 percent of the total equipment sales to the foodservice industry,

1 and the distribution channel 
6-4 

shares for refrigeration equipment may be different from the rest of the foodservice equipment. 

However, due to lack of availability of additional data, DOE used the market share values of the 

overall foodservice equipment sales for all self-contained commercial refrigeration equipment. 

During the preliminary analysis public meeting, many stakeholders commented that 

national accounts compose a larger share of the glass-door cases and that DOE’s market share 

values for self-contained equipment were applicable only to solid-door cases. Some 

manufacturers implied that their market share distribution for glass-doored cases was closer to 

that of the remote-condensing cases as they sold a major share of their glass-doored cases 

through national account channels. DOE also recognized that the data from FE&S magazine 

website1 was applicable more to solid-doored cases, which form a majority of equipment used in 

the foodservice industry. Therefore, DOE agreed with these comments from the stakeholders and 

consequently altered the market share of the distribution channels by grouping equipment 

families into two groups: (1) Display cases (VOP, SVO, HZO, VCT, HCT, SOC and PD), and 

(2) solid-door equipment (VCS and HCS). Table 6.2.1 provides the market shares of the three 

distribution channels for display cases and solid-door equipment used for the notice of proposed 

rulemaking (NOPR). DOE applied the market shares for remote-condensing equipment from the 

January 2009 final rule to display cases and used the FE&S magazine website data for the soliddoor equipment. 

Table 6.2.1 Distribution Channels Market Shares for Commercial Refrigeration 

Equipment

Equipment Type National 

Account Channel

Wholesaler 

Channel

Contractor 

Channel

Display Cases (VOP, SVO, HZO, VCT, HCT, SOC, and PD) 70 % 15% 15%

Solid-Door Equipment (VCS and HCS) 30% 60% 10%

6.2.4 Overall Markups

Overall markup values were separately obtained for both baseline and incremental 

markups by combining the state sales tax with the weighted-average distribution channel 

markups. Overall baseline markup values were calculated using the following: 

EQPCUST BASE = MFGBASE

× (WTNATL ACCT × MUNATL ACCT BASE + WTWHOLESALER × MUWHOLE BASE

+ WTMECH CONT × MUWHOLE BASE × MUMECH CONT BASE)

× (1 + ST) 

 = MFGBASE × MUOVERALL BASE

Eq. 6.8 

Where:

EQPCUST BASE = customer purchase price for baseline equipment ($),

WTNATL ACCT = market share of baseline equipment sales through national account channel (%), 
6-5 

WTWHOLESALER = market share of baseline equipment sales through wholesaler channel (%),

WTMECH CONT = market share of baseline equipment sales through contractor channel (%), and 

MUOVERALL BASE = overall baseline markup. 

Overall incremental markups were calculated using the following equation: 

EQPCUST INCR = MFGINCR

× (WTNATL ACCT × MUNATL ACCT INCR + WTWHOLESALER × MUWHOLE INCR

+ WTMECH CONT × MUWHOLE INCR × MUMECH CONT INCR) × (1 + ST) 

 = MFGINCR × MUOVERALL INCR 

Eq. 6.9 

Where:

EQPCUST INCR = increment in customer purchase price of equipment at a higher efficiency level 

compared to baseline equipment ($), 

MUOVERALL INCR = overall incremental markup. 

For a particular piece of equipment at a higher efficiency level, the total price of that 

equipment to the customer (EQPCUST ) is the sum of the baseline customer price (EQPCUST BASE) 

and the incremental customer price (EQPCUST INCR).

EQPCUST = EQPCUST BASE + EQPCUST INCR

Eq. 6.10 

6.3 BASIC ASSUMPTIONS USED TO ESTIMATE WHOLESALER AND 

MECHANICAL CONTRACTOR MARKUPS

DOE based the wholesaler markups on industry balance-sheet data and based the 

mechanical contractor markups on U.S. Census Bureau data for the plumbing, heating, and air 

conditioning (PHAC) industry.

2 DOE obtained the industry balance-sheet data from the Heating, 

Air conditioning & Refrigeration Distributors International (HARDI), the trade association

representing wholesalers of heating, ventilation, air-conditioning, and refrigeration (HVACR) 

equipment.3

 DOE compiled the U.S. Census Bureau PHAC data following the same format as 

the balance-sheet data for wholesalers. These balance sheets break out the components of all 

costs incurred by firms that supply and install PHAC equipment. DOE derived the wholesaler 

and mechanical contractor markups from three key assumptions about commercial refrigeration 

equipment costs: 

1. The firm balance sheets accurately represent the various average costs incurred by firms 

distributing and installing commercial refrigeration equipment. 

2. The wholesaler and contractor costs can be divided into two categories: (1) costs that 

vary in proportion to the MSP of commercial refrigeration equipment (variable costs); 
6-6 

and (2) costs that do not vary with the MSP of commercial refrigeration equipment (fixed 

costs).

3. Wholesaler and contractor prices vary in proportion to wholesaler and contractor costs 

included in the balance sheets.

The basis for the first assumption is that the industry balance sheets itemize firm costs 

into a number of cost categories, including direct costs to purchase or install the equipment, 

operating labor and occupancy costs, and other operating costs and profit. Although wholesalers 

and contractors tend to handle multiple commodity lines (including air conditioners, furnaces, 

and boilers) the data provides the most accurate available data for commercial refrigeration 

equipment costs. 

Information obtained from trade literature and from selected HVACR wholesalers,

contractors, and consultants, supports the second assumption that wholesale and contractor 

markups vary according to the quantity of labor and materials used to distribute and install 

HVACR equipment. In the following discussion, DOE assumes a division of costs between those 

that do not scale with the MSP (labor and occupancy expenses) and those that do vary with MSP 

(operating expenses and profit). This division of costs led to the estimate of wholesale and 

contractor markups described in section 6.4. 

The basis for the third assumption is that the HVACR wholesaler and contractor industry 

is competitive and consumer demand for commercial refrigeration, heating and air conditioning 

equipment is inelastic, (i.e., the demand is not expected to decrease significantly with an increase 

in price of equipment). The large number of HVACR firms listed in the 2007 economic census 

indicates the competitive nature of the market. For example, there are more than 700 HVACR 

manufacturers,

4

 1,300 wholesalers of refrigeration equipment,5 36,000 commercial and 

institutional building contractors,6 and 91,000 HVAC contractors7 listed in the 2007 economic 

census. Following standard economic theory, competitive firms facing inelastic demand either 

set prices in line with costs or quickly go out of business.8

6.4 ESTIMATION OF WHOLESALER MARKUPS

Annually, HARDI conducts a confidential survey of its member firms in which 

wholesalers report data. In the survey, HARDI itemizes revenues and costs into cost categories, 

including direct equipment expenses (cost of goods sold), labor expenses, occupancy expenses, 

other operating expenses, and profit. DOE presents the data for a typical HARDI distributor in 

terms of specific types of expense within these categories in appendix 6A. Table 6.4.1

summarizes these expenses in units of expenses per dollar sales revenue and revenue per dollar 

of goods sold. As shown in the first column of Table 6.4.1, the direct cost of equipment sold 

represents $0.737 per dollar of sales revenue. In other words, for every $1.00 wholesalers take in 

as sales revenue, they use $0.737 to pay for the direct equipment costs. Labor expenses account 

for $0.151 per dollar of sales revenue, occupancy expenses account for $0.036, other operating 

expenses account for $0.055, and profit accounts for $0.021 per dollar sales revenue.
6-7 

Table 6.4.1 Wholesaler Expenses and Markups*

Description

Wholesale Firm Expenses or Revenue

Per Dollar

Sales Revenue

Per Dollar 

Cost of Goods 

Sold

Direct Cost of Equipment Sales: Cost of goods sold $0.737 $1.000

Labor Expenses: Salaries and benefits $0.151 $0.205

Occupancy Expense: Rent, maintenance, and utilities $0.036 $0.049

Other Operating Expenses: Depreciation, advertising, and insurance $0.055 $0.075

Profit $0.021 $0.029

Baseline Markup (MUWHOLE BASE): Revenue per dollar cost of goods sold * 1.357

Incremental Markup (MUWHOLE INCR): Increased revenue per dollar increase cost of goods sold** 1.103

* Source: Heating, Airconditioning & Refrigeration Distributors International. 2012. 2012 Profit Report (2011 Data). Based on a 

Typical HARDI Distributor.

** Numbers include rounding errors and may not add up to the totals.

The last column of Table 6.4.1 shows the data converted from costs per dollar revenue 

into revenue per dollar cost of goods sold. DOE performed this conversion by dividing each cost 

category in the first data column of Table 6.4.1 by $0.737 (i.e., equipment expenditure per dollar 

revenue). The data in this column show that, for every $1.00 the wholesaler spends on equipment 

costs, the wholesaler earns $1.00 in sales revenue to cover the equipment cost, $0.205 to cover 

labor costs, $0.049 to cover occupancy expenses, $0.075 for other operating expenses, and 

$0.029 in profits. This totals to $1.357 in sales revenue earned for every $1.00 spent on 

equipment costs. Therefore, the wholesaler baseline markup (MUWHOLE BASE) is 1.357 ($1.357 ÷ 

$1.00). 

DOE also used the data in the last column of Table 6.4.1 to estimate the incremental 

markups. The incremental markup depends on which of the costs in Table 6.4.1 are variable and 

which are fixed. For example, for a $1.00 increase in the manufacturer equipment price, if all of 

the other costs scale with the manufacturer selling price (i.e., all costs are variable), the increase 

in wholesaler price will be $1.357, implying that the incremental markup is 1.357, or the same as 

the baseline markup. However, if none of the other costs is variable, then a $1.00 increase in the

manufacturer selling price will lead to a $1.00 increase in the wholesaler price, for an

incremental markup of 1.0. DOE assumes that the labor and occupancy costs will be fixed and 

that the other operating costs and profit will scale with the manufacturer selling price (i.e., be 

variable). In this case, for a $1.00 increase in the manufacturer selling price, the wholesaler 

price will increase by $0.103, which is the sum of other operating expenses and profit in the last 

column of Table 6.4.1. Therefore, the wholesaler incremental markup (MUWHOLE INCR) is 1.103 

($1.103 ÷ $1.00). See appendix 6A for additional details and data used for markup calculations.

6.5 ESTIMATION OF MECHANICAL CONTRACTOR MARKUPS

DOE derived markups for mechanical contractors from U.S. Census Bureau data for 

plumbing, heating, and air-conditioning contractors. This sector includes establishments 

primarily engaged in installing and servicing plumbing, heating, and air-conditioning equipment, 

which may include new work, additions, alterations, maintenance, and repairs. The U.S. Census 

Bureau data for the PHAC sector include detailed statistics for establishments with payrolls, 

similar to the data reported by HARDI for wholesalers. The primary difference is that the 

U.S. Census Bureau reports itemized revenues and expenses for the PHAC industry as a whole in 
6-8 

total dollars rather than in typical values for an average or representative business. Because of 

this, DOE assumed that the total dollar values that the U.S. Census Bureau reported, once 

converted to a percentage basis, represented revenues and expenses for an average or typical 

contracting business. As with the data for wholesalers, Table 6.5.1 summarizes the expenses for 

mechanical contractors. The expenses per dollar sales revenue are given in the first data column

of Table 6.5.1 (appendix 6A contains the full set of data). The direct cost of sales represents 

about $0.680 per dollar sales revenue to the mechanical contractor. Labor expenses account for 

$0.170 per dollar sales revenue, occupancy expenses account for $0.020 per dollar sales revenue, 

other operating expenses account for $0.040, and profit makes up $0.090 per dollar sales 

revenue. 

DOE converted these expenses per dollar sales into revenue per dollar cost of goods sold, 

by dividing each figure in the first data column by $0.678. The data in the last column of 

Table 6.5.1 show that, for every $1.00 the mechanical contractor spends on equipment costs, the 

mechanical contractor earns $1.00 in sales revenue to cover the equipment cost, $0.258 to cover 

labor costs, $0.032 to cover occupancy expenses, $0.058 for other operating expenses, and 

$0.127 in profits. This totals $1.475 in sales revenue earned for every $1.00 spent on equipment 

costs. Therefore, the mechanical contractor baseline markup (MUMECH CONT BASE) is 1.475 ($1.471 ÷ 

$1.00).

Table 6.5.1 Mechanical Contractor Expenses and Markups* 

Description

Mechanical Contractor Firm 

Expenses or Revenue

Per Dollar

Sales Revenue

Per Dollar 

Cost of 

Goods Sold

Direct Cost of Equipment Sales: Cost of goods sold $0.678 $1.000

Labor Expenses: Salaries (indirect) and benefits $0.175 $0.258

Occupancy Expense: Rent, maintenance, and utilities $0.022 $0.032

Other Operating Expenses: Depreciation, advertising, and insurance $0.039 $0.058

Net Profit Before Taxes $0.086 $0.127

Baseline Markup (MUMECH CONT BASE): Revenue per dollar cost of goods sold ** 1.475

Incremental Markup (MUMECH CONT INCR): Increased revenue per dollar increase cost of goods sold ** 1.185

* Source: U.S. Census Bureau. 2007. Plumbing, Heating, and Air-Conditioning Contractors. Sector 23: 238220. Construction: 

Geographic Area Series: Detailed Statistics for Establishments: 2007.

** Numbers include rounding errors and may not add up to the totals.

DOE was also able to use the data in the last column in Table 6.5.1 to estimate the 

incremental markups by separating the fixed and variable costs. For example, if all of the other 

costs scale with the equipment price (i.e., all costs are variable), the increase in mechanical

contractor price will be $1.475, implying that the incremental markup is 1.475, or the same as the 

baseline markup. However, if none of the other costs is variable, then a $1.00 increase in the 

equipment price will lead to a $1.00 increase in the mechanical contractor price, for an 

incremental markup of 1.0. DOE assumes the labor and occupancy costs to be fixed and the other 

operating costs and profit to scale with the equipment price (i.e., be variable). In this case, for a 

$1.00 increase in the equipment price, the mechanical contractor price will increase by $0.185, 

which is the sum of other operating expenses and profit in the last column of Table 6.5.1, giving 

a mechanical contractor incremental markup (MUMECH CONT INCR) of 1.185 ($1.185 ÷ $1.00).
6-9 

Mechanical contractor costs differ in various regions of the country for reasons including 

availability of labor, cost of living, and union versus non-union workforce. Because many 

mechanical contractor costs differ systematically by state, DOE characterized the markups 

developed from U.S. Census Bureau data with a probability distribution based on a state-by-state

analysis of U.S. Census Bureau data for PHAC contractors. The state-by-state analysis provided 

a distribution on the relative markups of mechanical contractors in the United States. 

Figure 6.5.1 shows the cumulative probability distribution of the state markup index that 

DOE used to characterize the mechanical contractor baseline and incremental markups. As 

mentioned in section 6.1, the contractor channel markup index was varied by state. The baseline 

and incremental markups in Table 6.5.1 are the national average markup values for the contractor 

channel. In the LCC analysis (TSD chapter 8), these national average values were multiplied by 

the state markup index to obtain the contractor channel markups for a particular state.

Figure 6.5.1 Cumulative Distribution of Mechanical Contractor Markups for Commercial 

Refrigeration Equipment

6.6 ESTIMATION OF NATIONAL ACCOUNT MARKUPS

Large customers of commercial refrigeration equipment use national accounts to 

circumvent the wholesaler channel, thereby allowing them to negotiate significantly lower 

equipment prices directly with the manufacturer. The manufacturer, in turn, must cover 

additional expenses related to the distribution of the equipment but gains in terms of negotiating 

agreed-upon sales volumes with the customer. 

To capture the price savings realized from equipment purchased through national 

accounts, DOE derived a national account markup, assuming that the resulting equipment price 

increase was one half of that realized from distribution through the wholesaler channel. In other 

words, if the price markup resulting from the wholesaler markups is $100, the national account 

markup is $50. DOE based the use of a national account markup that is one half of that realized 

from the wholesaler distribution channel on the assumption that the resulting national account 

0%

20%

40%

60%

80%

100%

1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9

Cumulative Percentages (%)

Markup

Mechanical Contractor Markup by State
6-10

equipment price must fall somewhere between the manufacturer selling price and the customer 

price under the wholesaler distribution channel. Because DOE does not have data suggesting 

typical values for the actual national account markup, it chose a value halfway between the MSP 

and the wholesaler markup. 

For example, using a baseline MSP of $1,000 for a piece of commercial refrigeration 

equipment delivered to a supermarket, and a baseline wholesaler markups of 1.357, the resulting 

baseline customer equipment price for sales through a wholesaler (without sales taxes) is $1,357 

($1,000 × 1.357). The dollar value increase due to the above distribution channel markups is 

$357 ($1,357 - $1,000). Under the assumption that national account customers realize equipment 

price increases equal to one half of that through the wholesale distribution channel, the dollar 

value of the equipment price increase under the national account is $178. The resulting 

equipment price is $1,178 ($178 + $1,000), which results in national account baseline markup of 

approximately 1.178 ($1,196 ÷ $1,000). A similar calculation using a value of 1.103 for the 

wholesaler incremental markup, results in a national account incremental markup of 1.052 

($1,052 ÷ $1,000). 

6.7 SALES TAX

Sales tax represents state and local sales taxes that are applied to the customer price of 

commercial refrigeration equipment. The sales tax is a multiplicative factor that increases the 

customer equipment price. DOE derived sales taxes representative of the combined state and 

local sales tax rates from the Sales Tax Clearinghouse, shown in Table 6.7.1. The state-level 

combined tax rates can be applied to the estimated value of state-level commercial refrigeration 

equipment shipments to obtain the total purchase cost to the customer located in any state. 

The distribution of sales tax rates ranges from a minimum of zero percent to a maximum 

of 9.5 percent with a mean value of 6.2 percent. DOE calculated the weighted-average nationallevel sales tax rate by multiplying the relative population of each state by the tax rates in

Table 6.7.1. The weighted national average sales tax rate was found to be 7.1 percent. The sales 

tax was applied in the LCC analysis (TSD chapter 8), according to the state in which the 

equipment was installed. 
6-11

Table 6.7.1 State Sales Tax Rates 

State

Combined 

State and 

Local Tax 

Rate

State

Combined 

State and 

Local Tax 

Rate

State

Combined 

State and 

Local Tax 

Rate

Alabama 8.55% Kentucky 6.00% North Dakota 5.95%

Alaska 1.35% Louisiana 8.75% Ohio 6.80%

Arizona 7.20% Maine 5.00% Oklahoma 8.40%

Arkansas 8.90% Maryland 6.00% Oregon 0.00%

California 8.45% Massachusetts 6.25% Pennsylvania 6.40%

Colorado 6.10% Michigan 6.00% Rhode Island 7.00%

Connecticut 6.35% Minnesota 7.20% South Carolina 7.20%

Delaware 0.00% Mississippi 7.00% South Dakota 5.40%

Dist. of Columbia 6.00% Missouri 7.45% Tennessee 9.45%

Florida 6.65% Montana 0.00% Texas 7.95%

Georgia 7.10% Nebraska 6.00% Utah 6.70%

Hawaii 4.40% Nevada 7.85% Vermont 6.05%

Idaho 6.05% New Hampshire 0.00% Virginia 5.60%

Illinois 8.05% New Jersey 6.95% Washington 8.90%

Indiana 7.00% New Mexico 6.60% West Virginia 6.05%

Iowa 6.85% New York 8.40% Wisconsin 5.45%

Kansas 7.85% North Carolina 6.90% Wyoming 5.50%

Source: The Sale Tax Clearinghouse, http://www.thestc.com/STrates.stm. Last accessed July 10, 2013.

6.8 MARKUPS RESULTS

Table 6.8.1 presents the baseline markup values for each distribution channel and the 

weighted-average baseline markup values for display cases and for solid-door cases. Table 6.8.2

presents the incremental markup values for each distribution channel and the weighted-average

incremental markup values for display cases and for solid-door cases. The mechanical contractor 

channel markup values presented in both the tables are the national average values.

Table 6.8.1 Baseline Markups by Distribution Channel and Overall Weighted Average 

Markup 

Wholesaler

Channel

Contractor Channel

(includes wholesaler 

markup)*

National 

Account

Channel

Weighted-Average Markup*

Display

Cases

Solid-Door 

Equipment

Markup 1.357 2.001 1.178 1.329 1.368

*National average value.

Table 6.8.2 Incremental Markups by Distribution Channel and Overall Weighted Average

Markup 

Wholesaler

Channel

Contractor Channel

(includes wholesaler 

markup)*

National 

Account

Channel

Weighted-Average Markup*

Display

Cases

Solid-Door 

Equipment

Markup 1.103 1.307 1.052 1.098 1.108

*National average value.

DOE used the weighted-average markups to estimate the customer price, before sales tax,

of baseline and higher efficiency equipment. For example, if the MSP of a baseline solid-door 

unit is $1,000, the customer purchase price before sales tax for this baseline equipment is 
6-12

obtained by multiplying the MSP by the weighted-average markup value of 1.368 to obtain the 

baseline customer purchase price, before sales tax, of $1,368. If the increment in the MSP of the 

equipment at a higher efficiency level is $100, then the customer purchase price increment, 

before sales tax, of this equipment can be obtained by multiplying by the weighted-average

incremental markup of 1.108 to obtain a customer purchase price increment, before sales tax, of 

$110.80. The customer purchase price of this higher efficiency equipment before sales tax is the 

sum of the baseline price and the increment, which is equal to $1,478.80 ($1,368 + $110.80).

Even though the example calculation has been shown with the national average values for the 

contractor channel markups included in the weighted-average markup, the calculations in the 

LCC analysis (TSD chapter 8) were performed by using the state-wise contractor channel 

markup values. Finally, the sales tax is applied to the customer purchase price, based on the state 

in which the equipment is installed, to obtain the final customer purchase price.
6-13

REFERENCES

1. Carbonara, J. M. 2010 Foodservice Industry Forecast: Achieving Stability. Foodservice 

Equipment & Supplies. 2009. (Last accessed December 10, 2010.) 

<http://www.fesmag.com/index.php/research/industry-forecast> 

2. U.S. Census Bureau. 2007 Economic Census, Release Date: 11/24/2009. Sector 23: 

EC0723A1: Construction: Geographic Area Series: Detailed Statistics for Establishments: 

2007. (Last accessed May 28, 2010.) 

<http://factfinder.census.gov/servlet/IBQTable?_bm=y&-ds_name=EC0723A1&-

NAICS2007=238220&-_lang=en.> 

3. Heating, Airconditioning & Refrigeration Distributors International. 2012 Profit Report 

(2011 Data). 2012. Columbus, OH. 

4. U.S. Census Bureau. 2007 Economic Census, Release Date: 10/30/2009, Sector 31: 

EC0731I1: Manufacturing: Industry Series: Detailed Statistics by Industry for the United 

States: 2007. Air-Conditioning, Refrigeration, and Forced Air Heating Manufacturing. (Last 

accessed March 2, 2011.) < http://factfinder.census.gov/servlet/IBQTable?_bm=y&-

fds_name=EC0700A1&-geo_id=&-_skip=300&-ds_name=EC0731I1&-_lang=en > 

5. U.S. Census Bureau. 2007 Economic Census, Release Date: 11/24/2009, Sector 42: 

EC0742I1: Wholesale Trade: Industry Series: Preliminary Summary Statistics for the United 

States: 2007. HVAC equip. merchant wholesalers. (Last accessed March 2, 2011.) 

<http://factfinder.census.gov/servlet/IBQTable?_bm=y&-geo_id=&-ds_name=EC0742I1&-

_lang=en> 

6. U.S. Census Bureau. 2007 Economic Census, Release Date: 8/14/2009, Construction: 

Industry Series: Preliminary Detailed Statistics for Establishments: 2007. Total of New 

single-family general contractors, New multifamily housing construction (except operative 

builders), New housing operative builders residential, and Residential remodelers; 

Commercial and institutional building construction. (Last accessed March 2, 2011.) 

<http://factfinder.census.gov/servlet/IBQTable?_bm=y&-geo_id=&-

fds_name=EC0700A1&-ds_name=EC0723I1&-_lang=en.> 

7. U.S. Census Bureau. 2007 Economic Census, Release Date: 8/14/2009, Sector 23: 

EC0723I1: Construction: Industry Series, Preliminary Detailed Statistics for Establishments: 

2007. Plumbing, heating, and air-conditioning contractors. (Last accessed March 2, 2011.) 

<http://factfinder.census.gov/servlet/IBQTable?_bm=y&-geo_id=&-ds_name=EC0723I1&-

_lang=en> 

8. Pindyck, R. and Rubinfeld, D. Microeconomics. s.l. : Prentice Hall, 2000.
APPENDIX 6A. DATA FOR EQUIPMENT PRICE MARKUPS

TABLE OF CONTENTS

6A.1 INTRODUCTION ........................................................................................................ 6A-1

6A.2 DETAILED WHOLESALER COST DATA ............................................................... 6A-1

6A.3 DETAILED MECHANICAL CONTRACTOR DATA ............................................... 6A-2

6A.4 ESTIMATION OF WHOLESALER AND MECHANICAL CONTRACTOR 

MARKUP STANDARD DEVIATIONS ..................................................................... 6A-2

LIST OF TABLES

Table 6A.2.1 Disaggregated Costs and Expenses for Wholesalers* ........................................ 6A-1

Table 6A.3.1 Mechanical Contractor Expenses and Markups* ................................................ 6A-2

Table 6A.4.1 Mechanical Contractor Baseline Markups by State, 2007* ................................ 6A-3

6A-i
APPENDIX 6A. DATA FOR EQUIPMENT PRICE MARKUPS

6A.1 INTRODUCTION

This appendix provides further details on information presented in chapter 6. 

6A.2 DETAILED WHOLESALER COST DATA

Chapter 6 presents wholesaler revenues and costs in aggregated form, based on the 

Heating, Airconditioning & Refrigeration Distributors International (HARDI) 2012 Profit Report 

(2011 Data). Table 6A.2.1 provides the complete breakdown of costs and expenses from the 

2012 Profit Report (2011 Data). The column labeled “Scaling” indicates which expenses were 

assumed to scale with only the baseline markup and which were assumed to scale with both the 

baseline and the incremental markups. As described in chapter 6, only those expenses that scale 

with incremental costs are marked up when there is an incremental change in equipment costs.

Table 6A.2.1 Disaggregated Costs and Expenses for Wholesalers*

Item Percent of Revenue Scaling

Cost of Goods Sold 73.7% Not applicable

Gross Margin 26.3%

Payroll Expenses 15.1% Baseline

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Executive Salaries & Bonuses 1.7%

Branch Manager Salaries and Commissions 1.5%

Sales Executive Salaries & Commissions 0.5%

Outside Sales Salaries & Commissions 2.1%

Inside/Counter Sales/Wages 2.8%

Purchasing Salaries/Wages 0.4%

Credit Salaries/Wages 0.2%

IT Salaries/Wages 0.1%

Warehouse Salaries/Wages 1.4%

Accounting 0.5%

Delivery Salaries/Wages 0.7%

All Other Salaries/Wages & Bonuses 0.8%

Payroll Taxes 1.0%

Group Insurance 1.1%

Benefit Plans 0.3%

Occupancy Expenses 3.6% Baseline

 

 

 

 

Utilities: Heat, Light, Power, Water 0.4%

Telephone 0.3%

Building Repairs & Maintenance 0.2%

Rent or Ownership in Real Estate 2.7%

Other Operating Expenses 5.5% Baseline & Incremental

 

 

 

 

 

 

 

 

Sales Expenses (incl. Advertising & Promotion) 0.9%

Insurance (business liability & casualty) 0.2%

Depreciation 0.4%

Vehicle Expenses 1.4%

Personal Property Taxes/Licenses 0.1%

Collection Exp (collection, credit card fees) 0.3%

Bad Debt Losses 0.2%

Data processing 0.3%

All Other Operating Expenses 1.7% -

6A-1
Table 6A.2.1 (cont)* 

Item Percent of Revenue Scaling

Total Operating Expenses 24.2% -

Operating Profit 2.1% Baseline & Incremental

Other Income 0.4%

Interest Expense 0.5%

Other Non-operating Expenses 0.0%

Profit Before Taxes 2.0% -

Source: Heating, Airconditioning & Refrigeration Distributors International. 2012 Profit Report (2011 Data). 2012. Columbus, OH.

*Wholesaler costs and expenses are percentage values as opposed to the per dollar of sales revenue values shown in chapter 6. 

6A.3 DETAILED MECHANICAL CONTRACTOR DATA

Chapter 6 presents mechanical contractor revenues and costs in aggregated form, based 

on U.S. Census Bureau data. Table 6A.3.1 shows the complete breakdown of costs and expenses 

provided by the U.S. Census Bureau. The column labeled “Scaling” indicates which expenses 

were assumed to scale with only the baseline markup and which were assumed to scale with both 

the baseline and incremental markups. As described in chapter 6, only those expenses that scale 

with incremental costs are marked up when there is an incremental change in equipment costs.

Table 6A.3.1 Mechanical Contractor Expenses and Markups*

Item Dollar Value Percentage Scaling

Total Cost of Equipment Sales $107,144,428 67.80% Baseline

Cost of materials, components, and supplies $59,023,964 37.35%

Payroll, construction workers $31,373,558 19.85%

Cost of construction work subcontracted out to others 13,646,192 8.64%

Cost of selected power, fuels, and lubricants $3,100,714 1.96%

Gross Margin $50,895,129 32.20% -

Payroll Expenses $27,626,376 17.48% Baseline

Fringe benefits, all employees $13,585,040 8.60%

Payroll, other employees $14,041,336 8.89%

Occupancy Expenses Baseline

Rental cost for machinery, equipment, and buildings; 

Cost of repairs to machinery and equipment; 

Purchased communication services

$3,436,208 2.17% Baseline

Other Operating Expenses $6,165,776 3.90% Baseline & Incremental

Depreciation charges during year $2,297,550 1.50%

Computers; Insurance and other business services; 

Advertising and promotions; Taxes and license fees

$3,868,226 2.40%

Net Profit Before Income Taxes $13,666,769 8.60% Baseline & Incremental

Source: U.S. Census Bureau. 2007 Economic Census, Release Date: 8/14/2009, Sector 23: EC0723I1: Construction: Industry 

Series: Preliminary Detailed Statistics for Establishments: 2007. (Last accessed, March 8, 2011.)

<http://factfinder.census.gov/servlet/IBQTable?_bm=y&-geo_id=&-ds_name=EC0723I1&-_lang=en> 

*Mechanical contractor costs and expenses are first presented as total dollar values and then converted to percentage values. 

This is in contrast to per dollar of sales revenue values shown in chapter 6. 

6A.4 ESTIMATION OF WHOLESALER AND MECHANICAL CONTRACTOR 

MARKUP STANDARD DEVIATIONS

The U.S. Department of Energy (DOE) used the U.S. Census Bureau’s Economic Census 

data to estimate commercial refrigeration equipment wholesaler and mechanical contractor 

markup distributions. In the case of wholesalers, 2007 Economic Census data were available 

6A-2
only at the national level. In the case of mechanical contractors, the 2007 census data included 

state-level plumbing, heating, and air conditioning data for total value of work, number of firms, 

cost of goods sold, cost of subcontract work, cost of materials, and construction payroll, as 

shown in Table 6A.4.1. The most recent census was performed in 2007.

DOE used the state-by-state variation in heating, ventilating, and air conditioning 

(HVAC) contractor markups as a component of state-by-state variation in the life-cycle cost 

(LCC) analysis. In the case of the contractor markups, the variation in contractor markup by state 

is captured explicitly in the subsequent LCC analysis. By “selecting” a state during the Monte 

Carlo analysis, DOE varied the installation costs. Looking at contractor markups on a relative 

basis, the lowest state is 90 percent of the average markup while the highest state is 119 percent 

of the average. Using population as a weighting factor, HVAC was combined with other factors 

that vary by state to create one of the key sets of cost components varied during the analysis.

Table 6A.4.1 Mechanical Contractor Baseline Markups by State, 2007* 

State

Number 

of 

Firms

Value of 

Construction 

($000)

Cost of 

Subcontract 

Work 

($000)

Cost of 

Materials 

($000)

Construction 

Payroll 

($000)

Baseline 

Markup

Alabama 1,425 2,010,305 113,782 876,341 411,100 1.435

Alaska 229 583,171 52,245 171,575 120,909 1.692

Arizona 1,510 3,522,116 179,103 1,508,903 638,469 1.514

Arkansas 1,045 1,065,754 68,417 461,924 213,054 1.434

California 7,272 16,726,969 1,070,065 6,330,469 3,464,667 1.539

Colorado 2,015 3,056,988 261,734 1,195,057 627,663 1.467

Connecticut 1,321 1,704,668 145,740 628,720 361,411 1.501

Delaware 306 481,900 D D 163,343 1.421

District of Columbia 22 34,600 D D 50,439 1.458

Florida 5,069 9,061,426 783,859 3,736,811 1,733,721 1.449

Georgia 2,534 4,700,799 365,010 2,224,110 740,722 1.412

Hawaii 280 800,221 46,753 270,723 137,646 1.758

Idaho 594 900,698 62,252 387,181 167,732 1.459

Illinois 3,848 7,641,642 602,251 2,833,489 1,622,307 1.511

Indiana 1,867 4,002,323 431,558 1,319,523 854,157 1.536

Iowa 1,066 1,868,483 144,869 801,239 359,775 1.431

Kansas 966 1,395,359 106,307 580,764 279,636 1.443

Kentucky 1,219 1,747,925 128,902 674,500 353,958 1.510

Louisiana 1,469 1,997,044 162,063 776,784 378,582 1.516

Maine 458 580,816 46,692 234,993 113,162 1.471

Maryland 2,024 5,329,135 698,381 2,009,957 1,031,222 1.425

Massachusetts 2,520 4,099,301 488,098 1,475,525 817,754 1.474

Michigan 3,051 4,420,638 604,850 1,569,113 841,985 1.466

Minnesota 1,635 3,402,921 386,669 1,230,126 698,535 1.470

Mississippi 655 1,025,452 76,709 449,851 189,011 1.433

Missouri 1,816 3,335,124 345,285 1,319,142 689,171 1.417

Montana 432 483,578 42,988 216,792 85,678 1.400

Nebraska 683 1,004,296 94,170 455,264 205,904 1.330

Nevada 498 2,327,842 121,091 988,605 490,859 1.454

New Hampshire 531 620,761 39,784 D 128,512 1.472

New Jersey 3,551 5,062,336 496,174 1,825,407 1,015,432 1.517

New Mexico 599 891,914 67,987 356,961 170,711 1.497

6A-3
Table 6A.4.1 (cont)* 

New York 5,750 10,364,779 1,219,468 3,568,182 1,972,687 1.533

North Carolina 2,978 5,111,396 341,129 2,288,841 1,001,832 1.407

North Dakota 272 360,683 36,037 148,617 70,403 1.414

Ohio 3,514 5,618,591 568,837 2,115,568 1,125,401 1.475

Oklahoma 1,158 1,352,943 94,153 581,079 249,032 1.464

Oregon 1,031 1,893,678 124,070 701,468 412,418 1.530

Pennsylvania 3,653 6,487,476 579,901 2,628,602 1,370,864 1.417

Rhode Island 397 631,202 56,234 229,692 124,727 1.537

South Carolina 1,472 1,991,303 126,123 847,690 352,877 1.501

South Dakota 337 386,186 11,037 158,375 69,605 1.616

Tennessee 1,370 2,595,613 189,293 1,159,952 484,997 1.415

Texas 5,653 10,810,308 823,920 4,605,624 2,102,520 1.435

Utah 892 1,746,398 146,052 769,140 319,812 1.414

Vermont 282 294,806 21,021 D 63,015 1.472

Virginia 2,547 4,623,151 347,055 1,791,740 960,534 1.492

Washington 1,602 4,111,543 370,741 1,546,819 816,533 1.504

West Virginia 416 655,100 D D 90,660 1.464

Wisconsin 1,839 2,926,545 234,962 1,125,779 662,893 1.446

Wyoming 262 289,391 14,391 128,922 54,792 1.461

Average Baseline Markup 1.477

Standard Deviation 0.070

Relative Standard Deviation 0.048

Source: U.S. Census Bureau. 2007 Economic Census, Release Date: 11/24/2009, Sector 23: EC0723A1: Construction: 

Geographic Area Series: Detailed Statistics for Establishments: 2007. (Last accessed May 28, 2010.)

<http://factfinder.census.gov/servlet/IBQTable?_bm=y&-ds_name=EC0723A1&-NAICS2007=238220&-_lang=en> 

*The Census Bureau withheld data for some states due to sample sizes and the size of errors relative to means. For states where a 

D appears under the headings for Subcontractor Costs, Materials & Supplies, or Construction Payroll, data was withheld. States 

missing one or more variables were set equal to an average of neighboring states' baseline markup.

6A-4
CHAPTER 7. ENERGY USE ANALYSIS 

TABLE OF CONTENTS

7.1 INTRODUCTION .............................................................................................................. 7-1

7-i 
CHAPTER 7. ENERGY USE ANALYSIS

7.1 INTRODUCTION

An energy use analysis is generally carried out for appliance standards rulemakings to 

calculate the energy consumption of the equipment in question. For commercial refrigeration 

equipment, the U.S. Department of Energy (DOE) calculated the energy consumption of the 

equipment as part of the engineering analysis (see technical support document (TSD) chapter 5) 

using an energy consumption model. During the analysis for the 2009 final rule for commercial 

refrigeration equipment (74 FR 1092 (Jan. 9, 2009)), DOE conducted an energy use analysis for 

certain remote condensing equipment and concluded that the results agreed reasonably well with 

those calculated by the energy consumption model used in the engineering analysis. Even though 

self-contained and remote condensing equipment differ with respect to their compressor and 

condenser configurations, the equipment load calculations, which include conduction, radiation 

and infiltration loads, and loads from the electrical components, are similar for both types of 

equipment. Therefore, for the current rulemaking, DOE retained the 2009 final rule analysis 

conclusions and used the engineering analysis energy consumption model calculations of 

equipment energy consumption values for life-cycle cost and payback period analysis (TSD 

chapter 8) and national impact analysis (TSD chapter 10). DOE did not carry out a separate 

energy use analysis for this rulemaking. 

7-1 
8-i 

CHAPTER 8. LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS

TABLE OF CONTENTS

8.1 INTRODUCTION ........................................................................................................... 8-1

8.1.1 General Approach for Life-Cycle Cost and Payback Period Analysis ................ 8-1

8.1.2 Overview of Life-Cycle Cost and Payback Period Inputs ................................... 8-4

8.1.3 Effect of Current Standards ................................................................................. 8-6

8.2 LIFE-CYCLE COST INPUTS ........................................................................................ 8-8

8.2.1 Definition ............................................................................................................. 8-8

8.2.2 Total Installed Cost Inputs ................................................................................... 8-9

8.2.2.1 Baseline Manufacturer Selling Price .................................................... 8-9

8.2.2.2 Candidate Standard Level Energy Consumption and Manufacturer 

Selling Price Increases ....................................................................................... 8-11

8.2.2.3 Price Trends ........................................................................................ 8-13

8.2.2.4 Markups .............................................................................................. 8-14

8.2.2.5 Installation Cost .................................................................................. 8-14

8.2.2.6 Weighted-Average Total Installed Cost .............................................. 8-15

8.2.3 Operating Cost Inputs ........................................................................................ 8-18

8.2.3.1 Electricity Price Analysis .................................................................... 8-19

8.2.3.2 Electricity Price Trend ........................................................................ 8-21

8.2.3.3 Repair Cost.......................................................................................... 8-22

8.2.3.4 Maintenance Costs .............................................................................. 8-23

8.2.3.5 Lifetime ............................................................................................... 8-27

8.2.3.6 Discount Rate ...................................................................................... 8-29

8.2.3.7 Compliance Date of Standard ............................................................. 8-32

8.3 PAYBACK PERIOD INPUTS ...................................................................................... 8-32

8.3.1 Definition ........................................................................................................... 8-32

8.3.2 Inputs.................................................................................................................. 8-33

8.4 LIFE-CYCLE COST AND PAYBACK PERIOD RESULTS ...................................... 8-33

8.4.1 Life-Cycle Cost Results ..................................................................................... 8-33

8.4.2 Payback Period Results ...................................................................................... 8-37

8.4.3 Rebuttable Presumption Payback Period ........................................................... 8-40

8.5 DETAILED RESULTS ................................................................................................. 8-41

REFERENCES .......................................................................................................................... 8-43

LIST OF TABLES

Table 8.1.1 Summary Information of Inputs for the Determination of Life-Cycle Cost and 

Payback Period..................................................................................................... 8-6

Table 8.1.2 Design Option Levels for VOP.SC.M Obtained from Engineering Analysis .......... 8-8

Table 8.1.3 Efficiency Levels for VOP.SC.M ............................................................................. 8-8

Table 8.2.1 Inputs for Total Installed Costs ................................................................................. 8-9

Table 8.2.2 Equipment Classes Evaluated for LCC Analysis ................................................... 8-10
8-ii

Table 8.2.3 Baseline Energy Consumption Levels and MSP Values for the Representative 

Commercial Refrigeration Equipment Units of All 24 Primary Equipment Classes

............................................................................................................................ 8-11

Table 8.2.4 CSL MSP Increases (Price Increases Relative to the Price of Baseline Efficiency 

Level) ................................................................................................................. 8-12

Table 8.2.5 Energy Consumption Values for Representative Commercial Refrigeration 

Equipment Units of the 25 Primary Equipment Classes at All Efficiency Levels 8-

13

Table 8.2.6 Installation Cost Indices (National Value = 100.0) ................................................ 8-15

Table 8.2.7 Costs and Markups for Determination of Weighted-Average Total Installed Costs for 

Convenience Stores (VCT.SC.L)* ..................................................................... 8-16

Table 8.2.8 Weighted-Average Equipment Price, Installation Cost, and Total Installed Costs for 

VCT.SC.L at U.S. Average Conditions (2012$) ............................................... 8-18

Table 8.2.9 Inputs for Operating Costs ...................................................................................... 8-18

Table 8.2.10 Commercial Electricity Prices by State (2012 cents/kWh) .................................. 8-19

Table 8.2.11 Derived Average Commercial Electricity Price by Business Type ...................... 8-20

Table 8.2.12 Estimated Replacement Rate of Components During Equipment Service Life 

(Values Retained from January 2009 Final Rule Analysis)............................... 8-23

Table 8.2.13 Annualized Lighting Maintenance Costs by Equipment Class for Each CSL for the 

Representative Units Analyzed in the Engineering Analysis ............................ 8-27

Table 8.2.14 Probability of Equipment Failure by Year ............................................................ 8-29

Table 8.2.15 Derivation of Real Discount Rates by Building Type .......................................... 8-31

Table 8.4.1 LCC Savings Distribution Results for Equipment Class VCT.SC.L ...................... 8-35

Table 8.4.2 Mean LCC Savings for All Equipment Classes and CSLs ..................................... 8-36

Table 8.4.3 Median LCC Savings for All Equipment Classes and CSLs .................................. 8-37

Table 8.4.4 Payback Period Distribution Results for VCT.SC.L .............................................. 8-38

Table 8.4.5 Mean Payback Period for All Equipment Classes and CSLs ................................. 8-39

Table 8.4.6 Median Payback Period for All Equipment Classes and CSLs .............................. 8-40

Table 8.4.7 Rebuttable Presumption Payback Periods by CSL and Equipment Class .............. 8-41

Table 8.5.1 Summary of Results of LCC and PBP Analysis for VCT.SC.L Equipment Class . 8-42

LIST OF FIGURES

Figure 8.1.1 Flow Diagram of Inputs for the Determination of Life-Cycle Cost and Payback 

Period ................................................................................................................... 8-5

Figure 8.2.1 Cumulative Probability Distribution Showing the Electricity Prices Paid by 

Convenience/Small Market Sector in 2012 (2012$) .......................................... 8-21

Figure 8.2.2 Electricity Price Trends for Commercial Rates to 2046 ........................................ 8-22

Figure 8.2.3 Survival Function for Display Cases in Large Grocery Stores and Supermarkets and 

for All Self-Contained Equipment ..................................................................... 8-28

Figure 8.2.4 Survival Function for Display Cases in Small Grocery Stores ............................. 8-28

Figure 8.4.1 LCC and Installed Cost Variation over CSLs for the VCT.SC.L Equipment Class . 8-

34

Figure 8.4.2 LCC Savings Distribution for All the CSLs for Equipment Class VCT.SC.L ...... 8-35

Figure 8.4.3 Mean Payback Period for All CSLs for the Equipment Class VCT.SC.L ............ 8-38
8-1 

CHAPTER 8. LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS

8.1 INTRODUCTION

This chapter describes the analysis the U.S. Department of Energy (DOE) has carried out 

to evaluate the economic impacts of amended energy conservation standards developed for 

commercial refrigeration equipment on individual commercial customers, henceforth referred to 

as customers. The effect of standards on customers includes a change in operating cost (usually 

decreased) and a change in purchase cost (usually increased). This chapter describes two metrics 

used to determine the effect of standards on customers: 

• Life-cycle cost (LCC). The total customer cost over the life of the equipment is the 

sum of installed cost (purchase and installation costs) and operating costs 

(maintenance, repair, and energy costs). Future operating costs are discounted to the 

time of purchase and summed over the lifetime of equipment. 

• Payback period (PBP). Payback period is the estimated amount of time it would take 

customers to recover the higher purchase price of more efficient equipment through 

lower operating costs. 

An efficiency improvement to commercial refrigeration equipment that is financially 

attractive to a customer will typically have a low PBP and a low LCC associated with it. 

This chapter is organized as follows. The remainder of this section outlines the general 

approach and provides an overview of the inputs to the LCC and PBP analysis of commercial 

refrigeration equipment. Inputs to the LCC and PBP analysis are discussed in detail in sections 

8.2 and 8.3. Results for the LCC and PBP analysis are presented in sections 8.4 and 8.5. 

The calculations discussed in this chapter were performed with a series of Microsoft 

Excelspreadsheets, which are available at 

www1.eere.energy.gov/buildings/appliance_standards/product.aspx/productid/52. Instructions 

for using the spreadsheets are included in appendix 8A of this technical support document 

(TSD). Detailed results are presented in appendix 8B. 

8.1.1 General Approach for Life-Cycle Cost and Payback Period Analysis 

This section summarizes DOE’s approach to the LCC and PBP analysis for commercial 

refrigeration equipment.

As part of the engineering analysis (TSD chapter 5), design option levels were ordered on 

the basis of increasing efficiency (decreased energy consumption) and increasing manufacturer 

selling price (MSP) values. The order was determined based on the cost-effectiveness of each 

design option; that is, the ratio of incremental cost increase to incremental energy savings. For 

the LCC and PBP analysis, DOE chose a maximum of eight levels, henceforth referred to as 

efficiency levels, from the list of engineering design option levels. For those equipment classes 

for which fewer than eight design option levels were defined in the engineering analysis, each

design option level was assigned a corresponding efficiency level. However, for equipment 

classes where more than eight design option levels were defined, DOE selected specific levels to 

analyze based on three criteria:
8-2 

1. The lowest and highest energy consumption levels provided in the engineering analysis 

were preserved. 

2. If the difference in reported energy consumptions and reported manufacturer price 

between sequential levels was small, only the design option level with the lower amount 

of energy consumption was selected to be an efficiency level. 

3. If the energy consumption savings benefit relative to the increased cost was similar 

across multiple, sequential design option levels, intermediate design option levels were

removed. 

The first efficiency level or baseline efficiency level (Level 1) in each equipment class 

represents the least efficient and the least expensive equipment in that equipment class. The 

higher efficiency levels (Level 2 and up) have a progressive increase in efficiency and cost from 

Level 1. The highest efficiency level in each equipment class corresponds to the max-tech level

(see TSD chapter 5 for details). DOE treats each efficiency level as a candidate standard level

(CSL), as each efficiency level represents a potential standard level. The words “efficiency 

level” and “CSL” can be used interchangeably.

The installed cost of equipment to a customer is the sum of the equipment purchase price 

and installation costs. The purchase price includes manufacturer production cost, to which a 

manufacturer markup and outbound freight costs are applied to obtain the MSP. This value is 

calculated as part of the engineering analysis (TSD chapter 5). DOE then applies additional 

markups to the equipment to account for the markups associated with the distribution channels

for this type of equipment (TSD chapter 6). Installation costs vary by state, depending on the 

prevailing labor rates. 

Operating costs for commercial refrigeration equipment are a sum of maintenance costs, 

repair costs, and energy costs. These costs are incurred over the life of the equipment and 

therefore are discounted to the base year (2017, which is the compliance date of the amended 

standards that will be established as part of this rulemaking). The sum of the installed cost and 

the operating cost, discounted to reflect the present value, is termed the life-cycle cost or LCC.

Generally, customers incur higher installed costs when they purchase higher efficiency 

equipment, and these cost increments will be offset partially or wholly by savings in the 

operating costs over the lifetime of the equipment. Usually, the savings in operating costs are due 

to savings in energy costs because higher efficiency equipment uses less energy over the lifetime 

of the equipment. LCC savings are calculated for each CSL of each equipment class.

The PBP of a CSL is obtained by dividing the increase in the installed cost (from the 

baseline efficiency level) by the decrease in annual operating cost (from the baseline efficiency 

level). For this calculation, DOE uses the first year operating cost changes as the estimate of the 

decrease in operating cost, noting that some of the repair and replacement costs used herein are 

annualized estimates of costs. PBP is calculated for each CSL of each equipment class. 

Apart from MSP, installation costs, and maintenance and repair costs, other important 

inputs for the LCC analysis are markups and sales tax, equipment energy consumption, 

electricity prices and future price trends, equipment lifetime, and discount rates.
8-3 

Many inputs for the LCC analysis are estimated from the best available data in the 

market, and in some cases the inputs are generally accepted representative values within the 

commercial refrigeration equipment industry. However, in most cases each input has a range of 

values. For example, even though the average (and representative) lifetime of commercial 

refrigeration units in certain equipment classes may be 10 years, in general, equipment lifetimes 

of a typical refrigerator belonging to that equipment class may vary from 5 years to 15 years. 

While calculations based on the representative values yield average or representative values for 

the outputs (such as LCC or PBP), such values do not give an estimate of the ranges of values 

that these outputs could lie in. Therefore, DOE performed the LCC analysis in the form of Monte 

Carlo simulations in which certain inputs are provided a range of values and probability 

distributions. The results of the LCC analysis are presented in the form of mean and median LCC 

savings; percentages of customers experiencing net savings, net cost, and no impact in LCC; and 

median PBP. For each equipment class, 10,000 Monte Carlo simulations were carried out. The 

simulations were conducted using Microsoft Excel and Crystal Ball, a commercially available 

Excel add-in for carrying out Monte Carlo simulations. 

Usually, the equipment available in the market will have a distribution of efficiencies; 

that is, each CSL within an equipment class will have a corresponding market share associated 

with it. Usually, within an equipment class, the market share of the baseline efficiency level is 

the highest, and the market share values decrease with an increase in CSL. LCC savings and PBP 

are calculated by comparing the installed costs and LCC values of the standards-case scenarios 

against those of the base-case scenario. The base-case scenario is the scenario in which 

equipment is assumed to be purchased by customers in the absence of the proposed amended 

energy conservation standards. Standards-case scenarios are scenarios in which equipment is 

assumed to be purchased by customers after the amended energy conservation standards go into 

effect. The number of standards-case scenarios for an equipment class is equal to one less than 

the total number of efficiency levels in that equipment class because each CSL above the 

baseline efficiency level represents a potential new standard. For the standards-case scenario at a 

particular CSL, the market share of the efficiency levels were obtained using a roll-up scenario, 

in which market shares of the efficiency levels (in the base-case scenario) below the 

corresponding CSL were rolled-up into the CSL. For the base-case scenario in the LCC analysis, 

DOE calculated the market shares of the efficiency levels using a method described in TSD 

chapter 10. 

Recognizing that each commercial building that uses the commercial refrigeration 

equipment is unique, DOE analyzed the LCC and PBP calculations for seven types of 

businesses: (1) supermarkets; (2) wholesaler/retailer multi-line stores, such as “big-box stores,” 

“warehouses,” and “supercenters;” (3) convenience and small specialty stores, such as meat 

markets, wine, beer, and liquor stores; (4) convenience stores associated with gasoline stations; 

(5) full service restaurants; (6) limited service restaurants; and (7) other foodservice businesses, 

such as caterers and cafeterias. Different types of businesses face different energy prices and also 

exhibit differing discount rates that they apply to purchase decisions.

Equipment lifetime is another input that does not justify usage of a single value for each 

equipment class. Therefore, DOE assumes a distribution of equipment lifetimes that are defined 

by Weibull survival functions. 
8-4 

Another important factor influencing the LCC analysis is the state (location) in which the 

commercial refrigeration equipment is installed. Inputs that vary based on this factor include 

energy prices, installation costs, contractor markups, and sales tax. At the national level, the 

spreadsheets explicitly modeled variability in the model inputs for electricity price and markups 

using probability distributions based on the relative shipments of units to different states and 

business types. 

Appendix 8C presents additional discussion about the uncertainty and variability in 

inputs and the advantages of Monte Carlo simulations. 

8.1.2 Overview of Life-Cycle Cost and Payback Period Inputs

Inputs to the LCC analysis are categorized as follows: (1) inputs for establishing the total 

installed cost; and (2) inputs for calculating the operating cost. 

The primary inputs for establishing the total installed cost are as follows: 

• Baseline MSP is the MSP of equipment meeting the baseline efficiency level. 

• Price trends (experiential learning): A method of adjusting the MSP over time to 

account for increasing cost efficiency in the production of commercial refrigeration 

equipment. DOE assumed that, with time and experience, the real cost of producing 

equipment will decrease marginally

• CSL MSP increase is the difference in MSP of a CSL and the baseline MSP. 

• Markups and sales tax are the markups and sales tax associated with converting the 

MSP to a customer purchase price (see TSD chapter 6). 

• Installation cost is the cost to the customer of installing the equipment. It includes 

cost of labor, overhead, and miscellaneous materials and parts. 

The primary inputs for calculating the operating costs are as follows: 

• Equipment energy consumption: Consumption is the total daily energy consumption 

of the commercial refrigeration equipment. This value is calculated as part of the 

engineering analysis (TSD chapter 5) for each design option level in each equipment 

class. 

• Electricity prices: Electricity prices used in the analysis are the price per kilowatthour paid by each customer for electricity. Electricity prices are determined using 

average commercial electricity prices in each state, as determined from the Energy 

Information Administration (EIA) data for 2012. The 2012 average commercial 

prices derived were modified to reflect the fact that the seven types of businesses 

analyzed pay electricity prices that are different from the average commercial prices.

• Electricity price trends: The EIA’s Annual Energy Outlook 20131

 (AEO2013) is used 

to forecast future electricity prices. For the results presented in this chapter, DOE 

used the regional prices from the AEO2013 Reference Case to forecast future 

electricity prices. 

• Maintenance costs: The labor and materials costs associated with maintaining the 

operation of the equipment. 
8-5 

• Repair costs: The labor and materials costs associated with repairing or replacing 

components that have failed. 

• Equipment lifetime: The age at which the commercial refrigeration equipment is 

retired from service.

• Discount rate: The rate at which future costs are discounted to establish their present 

value. 

Figure 8.1.1 depicts the relationships between the installed cost and operating cost inputs 

for the calculation of the LCC and PBP. Table 8.1.1 summarizes the characteristics of the inputs 

to the LCC and PBP analysis and lists the corresponding reference chapter in the TSD for details 

on the calculation of the inputs. 

Figure 8.1.1 Flow Diagram of Inputs for the Determination of Life-Cycle Cost and Payback 

Period

Installation Costs Installation Costs

Repair Costs Repair Costs Lifetimes Lifetimes

Annual Maintenance

Electricity 

Consumption Electricity 

Consumption

Manufacturer Base 

Price

Total Installed Cost 

(Std i –Base)

Manufacturer Base 

Price

Contractor Markups

Markups

Wholesaler/ 

Distributor Markup

Electricity Prices

National Account 

Markup

Equipment Prices

Sales Tax

Manufacturer Base 

Price

Installation Costs

Manufacturer Std 1 

Base Price

Manufacturer Std 1 

Base Price

Manufacturer Price

Standard i= 1...n

Electricity 

Consumption Annual Energy Costs

Annual Maintenance

Repair Costs

Annual Operating 

Cost (Std i - Base)

Payback 

Period

Discount Rate

Lifetimes

Lifetime 

Operating 

Cost (Std 

i – Base)

Lifecycle 

Cost

Annual Maintenance 

Costs

Installation Costs Installation Costs

Repair Costs Repair Costs Lifetimes Lifetimes

Annual Maintenance

Electricity 

Consumption Electricity 

Consumption

Manufacturer Base 

Price

Total Installed Cost 

(Std i –Base)

Manufacturer Base 

Price

Contractor Markups

Markups

Wholesaler/ 

Distributor Markup

Electricity Prices

National Account 

Markup

Equipment Prices

Sales Tax

Manufacturer Base 

Price

Installation Costs

Manufacturer Std 1 

Base Price

Manufacturer Std 1 

Base Price

Manufacturer Price

Standard i= 1...n

Electricity 

Consumption Annual Energy Costs

Annual Maintenance

Repair Costs

Annual Operating 

Cost (Std i - Base)

Payback 

Period

Discount Rate

Lifetimes

Lifetime 

Operating 

Cost (Std 

i – Base)

Lifecycle 

Cost

Annual Maintenance 

Costs
8-6 

Table 8.1.1 Summary Information of Inputs for the Determination of Life-Cycle Cost and 

Payback Period 

Input Description TSD Chapter 

Reference

Total Installed Cost Primary Inputs

Baseline MSP Varies with equipment class. Chapter 5

Candidate standard level 

MSP increases

Vary with equipment class and candidate standard level within 

an equipment class.

Chapter 5

Price trends (experiential

learning)

Applies to baseline MSP and MSP increases of all equipment 

classes

Chapters 8, 10 

Markups and sales tax Markups vary with distribution channel, and sales tax varies with 

location (state) where equipment is installed.

Chapter 6

Installation price Varies with location (state) where equipment is installed. Chapter 8

Operating Cost Primary Inputs

Equipment energy 

consumption

Varies with equipment class and candidate standard level within 

an equipment class.

Chapter 5

Electricity prices Vary with location, building type. Chapter 8

Electricity price trends Vary with location (regional) and price scenario. Chapter 8

Maintenance costs Vary with equipment class and candidate standard level within 

equipment class.

Chapter 8

Repair costs Vary with equipment class and candidate standard level within 

equipment class.

Chapter 8

Lifetime Weibull survival functions. Average values assumed to be 10 

years for large grocery store equipment and 15 years for small 

retail stores for remote condensing equipment. Average values 

assumed to be 10 years for all self-contained equipment.

Chapters 3, 8

Discount rate Varies with type of business. Chapter 8

All of the inputs depicted in Figure 8.1.1 and summarized in Table 8.1.1 are discussed in 

sections 8.2 and 8.3. 

8.1.3 Effect of Current Standards

Standards set by this rulemaking are likely to go into effect in 2017, and the standards set 

by the 2009 DOE final rule on commercial refrigeration equipment (the January 9, 2009 final 

rule) went into effect on January 1, 2012. 74 FR at 1092. DOE does not have sufficient data 

concerning the commercial refrigeration equipment market at the time the notice of proposed 

rulemaking (NOPR) analyses was conducted. However, DOE assumed that the equipment 

manufactured before 2017 will be compliant with the January 2009 final rule standards. The 

general practice in DOE appliance standards rulemakings is to assume that the current 

technology level of the market will continue to remain at, or very near, the current level until 

new DOE standards are brought into effect at a future date. The design option levels for each 

equipment class (TSD chapter 5) were chosen based on technology levels in the commercial 

refrigeration equipment market at the time of the NOPR analysis (TSD chapter 3). However, the 

composition of this market will change as a result of the January 2009 final rule standards, which 

go into effect before 2017, at which time the standards established by the current rulemaking 

would go into effect. While it is difficult to predict the state of the market in the year 2017, DOE 

devised a method to estimate the efficiency level of the market baseline in 2017 based on certain 

assumptions. 
8-7 

DOE assumed that the standards established by the January 2009 final rule will form the 

lowest efficiency level before the amended standards, established as part of this rulemaking—

which will be in effect in 2017. This is a reasonable assumption considering that the 2009 

standards are appreciably more stringent than the then-prevailing market baseline and that 

notable technology improvements are necessary to reach the efficiency levels prescribed by the 

2009 final rule. DOE is not in a position to speculate on the other potential improvements of 

equipment efficiency in the market from the time the 2009 final rule standards go into effect and 

2017, aside from assuming compliance with the 2009 final rule standards. As a result, even 

though the market could potentially continue to improve the efficiency of commercial

refrigeration equipment beyond that required by the standards established by the 2009 final rule, 

DOE assumed that the market will remain in a similar state from the compliance date of the 2009 

final rule standards until 2017. To approximate this assumed market efficiency level in 2017 in 

the current analysis, DOE introduced a new baseline efficiency level—henceforth referred to as 

the standards baseline level—that is set at the same level as the 2009 final rule standard. Any

design option levels from the engineering analysis that were less efficient than the corresponding 

standards baseline level were disregarded for the downstream analyses (LCC analysis and 

national impact analysis (NIA)); that is, they were not included as efficiency levels (candidate 

standard levels). Design option levels from the engineering results that were more efficient than 

the standards baseline level were considered for higher efficiency levels (Level 2, Level 3, and 

so on). It should be noted that, in general, there is no design option level from the engineering 

analysis that corresponds specifically to this assumed market baseline (standards baseline). The 

process of estimating the 2017 market baseline level is explained with the aid of an example in 

the following paragraph. 

Table 8.1.2 shows the 13 design option levels for equipment class VOP.SC.M (selfcontained vertical open refrigerator), obtained from the engineering analysis. This table 

represents the current (2012) technology levels modeled for VOP.SC.M equipment on the 

market. The energy conservation standard for this class prescribed by the January 2009 final rule 

is given by the expression 1.74×TDA+4.71 kilowatt-hours per day (kWh/day), where TDA (in 

ft2

) represents the total display area of the equipment. The TDA value for this representative 

VOP.SC.M unit, which was modeled in the engineering analysis, is 14.93 ft2

. When substituted 

into the expression, it yields a maximum allowable total daily energy consumption value of 

30.69 kWh/day. This value, when compared against the list of design option levels (Table 8.1.2), 

is between the design option levels 7 and 8 (AD7 and AD8). As explained in the previous 

paragraph, DOE assumed that when the January 2009 final rule standards go into effect, 

30.69 kWh/day would represent the minimum efficiency level of the market for this unit and that 

it would remain so until 2017. To approximate this state of market technology, DOE assumed the 

efficiency levels shown in Table 8.1.3 for VOP.SC.M equipment. The first column of 

Table 8.1.3 represents the efficiency levels for the LCC analysis, and the second column 

represents the corresponding design option levels. As stated in the preceding paragraph, there is 

no design option level in the current rulemaking that corresponds directly to the first efficiency 

level. Instead, this design option level is designated as “SB,” which stands for “standards 

baseline.” The total daily energy consumption for Efficiency Level 1 of this unit is equal to 30.69 

kWh/day, which is the same as the January 2009 final rule standards level. The MSP

corresponding to Efficiency Level 1 was obtained by interpolating the prices between AD7 and 

AD8 in Table 8.1.2. 
8-8 

Table 8.1.2 Design Option Levels for VOP.SC.M Obtained from Engineering Analysis 

Design 

Option 

Level

Total Daily 

Energy 

Consumption 

kWh/day

Manufacturer 

Selling Price 

2012$

Design Option Added* 

AD1 39.60 $2,439.74 Baseline 

AD2 37.91 $2,458.10 High-Eff. Reciprocating Compressor 

AD3 34.96 $2,513.31 Enhanced-UA Condenser Coil 

AD4 34.35 $2,526.53 Permanent Split Cap. Evap. Fan Motor 

AD5 32.81 $2,567.74 Enhanced-UA Evaporator Coil 

AD6 32.09 $2,589.03 Brushless DC Evap. Fan Motor 

AD7 31.58 $2,604.45 Super T8 Lighting 

AD8 30.37 $2,663.18 Night Curtains 

AD9 30.03 $2,680.80 Permanent Split Cap. Cond. Fan Motor 

AD10 29.60 $2,718.25 Brushless DC Cond. Fan Motor 

AD11 26.70 $3,137.04 LED Lighting with Occupancy Sensors 

AD12 26.62 $3,180.03 Additional 1⁄2-inch Insulation 

AD13 26.46 $4,086.26 Vacuum Insulated Panels 

*For information about specific technologies, refer to chapter 5 and appendix 5A.

Table 8.1.3 Efficiency Levels for VOP.SC.M 

Efficiency 

Level for 

LCC 

Analysis

Corresponding 

Design Option 

Level

Total Daily 

Energy 

Consumption 

kWh/day

Manufacturer 

Selling Price 

2012$

Level 1 SB 30.69 $2,647.69 

Level 2 AD8 30.37 $2,663.18 

Level 3 AD9 30.03 $2,680.80 

Level 4 AD10 29.60 $2,718.25 

Level 5 AD11 26.70 $3,137.04 

Level 6 AD12 26.62 $3,180.03 

Level 7 AD13 26.46 $4,086.26 

8.2 LIFE-CYCLE COST INPUTS

8.2.1 Definition

Life-cycle cost is the total customer cost over the life of a piece of equipment, including 

purchase cost and operating costs (energy costs, maintenance costs, and repair costs). Future 

operating costs are discounted to the time of purchase and summed over the lifetime of the 

equipment. Life-cycle cost is defined by the following equation: 

∑=

+= +

N

t

t

t ICLCC OC r

1

/( )1

Eq. 8.1 
8-9 

Where: 

LCC = life-cycle cost ($), 

IC = total installed cost ($), 

N = lifetime of equipment (years), 

OCt = operating cost ($) of the equipment in year t, 

r = discount rate, and 

t = year for which operating cost is being determined. 

DOE expressed all costs in 2012$. Total installed cost, operating cost, lifetime, and 

discount rate are discussed in the following sections. In the LCC analysis, the first year of 

equipment purchase is assumed to be 2017. 

8.2.2 Total Installed Cost Inputs

The total installed cost to the customer is defined by the following equation: 

IC EQP += INST

Eq. 8.2 

Where: 

EQP = customer purchase price for the equipment ($), and

INST= installation cost or the customer price to install equipment ($).

The remainder of this section provides information about the inputs DOE used to 

calculate the total installed cost for commercial refrigeration equipment. Table 8.2.1 shows 

inputs for the determination of total installed cost. 

Table 8.2.1 Inputs for Total Installed Costs

Baseline manufacturer selling price ($)

Candidate standard level manufacturer selling price increases ($)

Experiential Learning coefficient (0.9945)

Wholesaler markup

Mechanical contractor markup

National account markup

Sales tax ($)

Installation cost ($)

8.2.2.1 Baseline Manufacturer Selling Price

The baseline MSP is the price charged by manufacturers for equipment meeting existing 

minimum efficiency (or baseline) standards. DOE developed MSP values for the 25 primary 

equipment classes (TSD chapter 5). Table 8.2.2 shows the set of 25 primary equipment classes 

that DOE evaluated during the current rulemaking. 
8-10

Table 8.2.2 Equipment Classes Evaluated for LCC Analysis 

Description (Equipment Family. Operating Mode. 

Temperature)

Abbreviation Current Standards

Set By

Vertical Open.Remote Condensing.Medium VOP.RC.M January 2009 final rule

Vertical Open.Remote Condensing.Low VOP.RC.L January 2009 final rule

Vertical Open.Self-Contained.Medium VOP.SC.M January 2009 final rule

Vertical Closed Transparent.Remote Condensing.Medium VCT.RC.M January 2009 final rule

Vertical Closed Transparent.Remote Condensing.Low VCT.RC.L January 2009 final rule

Vertical Closed Transparent.Self-Contained.Medium VCT.SC.M EPCA

Vertical Closed Transparent.Self-Contained.Low VCT.SC.L EPCA

Vertical Closed Transparent.Self-Contained.Ice Cream VCT.SC.I January 2009 final rule

Vertical Closed Solid.Self-Contained.Medium VCS.SC.M EPCA

Vertical Closed Solid.Self-Contained.Low VCS.SC.L EPCA

Vertical Closed Solid.Self-Contained.Ice Cream VCS.SC.I January 2009 final rule

Semi-Vertical Open.Remote Condensing.Medium SVO.RC.M January 2009 final rule

Semi-Vertical Open.Self-Contained.Medium SVO.SC.M January 2009 final rule

Service Over Counter.Remote Condensing.Medium SOC.RC.M January 2009 final rule

Horizontal Open.Remote Condensing.Medium HZO.RC.M January 2009 final rule

Horizontal Open.Remote Condensing.Low HZO.RC.L January 2009 final rule

Horizontal Open.Self-Contained.Medium HZO.SC.M January 2009 final rule

Horizontal Open.Self-Contained.Low HZO.SC.L January 2009 final rule

Horizontal Closed Transparent.Self-Contained.Medium HCT.SC.M EPCA

Horizontal Closed Transparent.Self-Contained.Low HCT.SC.L EPCA

Horizontal Closed Transparent.Self-Contained.Ice Cream HCT.SC.I January 2009 final rule

Horizontal Closed Solid.Self-Contained.Medium HCS.SC.M EPCA

Horizontal Closed Solid.Self-Contained.Low HCS.SC.L EPCA

Pull-Down.Self-Contained.Medium PD.SC.M EPCA

Service Over Counter. Self-Contained. Medium SOC.SC.M AEMTCA

Nine primary equipment classes in Table 8.2.2 are subject to standards set by the Energy 

Policy and Conservation Act (EPCA) as amended by the Energy Policy Act of 2005 (42 U.S.C. 

6313(c)(2)–(3)); 15 primary equipment classes are subject to standards set by DOE in the 

January 9, 2009 final rule (74 FR at 1092), and one primary equipment class is subject to 

standards set by the American Energy Manufacturing Technical Corrections Act (AEMTCA) (42 

U.S.C. 6313(c)(4)). Table 8.2.3 presents the baseline energy consumption values and the baseline 

MSPs used in the LCC analysis for the representative sizes for each of the 25 primary equipment 

classes (TSD chapter 5). Table 8.2.3 also identifies whether the baseline was obtained from the 

engineering analysis or was set at the standards baseline, as explained in section 8.1.3. For some 

equipment classes, the January 2009 final rule standards, EPCA standards, or AEMTCA 

standard form the baseline efficiency level, and for the remaining equipment classes, the market 

baseline (from the engineering analysis) forms the baseline efficiency level because the market 

baseline for these equipment classes was found to be more efficient than the current standard 

level. 
8-11

Table 8.2.3 Baseline Energy Consumption Levels and MSP Values for the Representative 

Commercial Refrigeration Equipment Units of All 24 Primary Equipment Classes

Equipment 

Class

Baseline energy 

consumption 

kWh/day

Manufacturer Selling 

Price

2012$

Baseline Type

VOP.RC.M 47.78 5,041.54 Standards Baseline

VOP.RC.L 108.23 5,457.86 Standards Baseline

VOP.SC.M 30.69 2,647.69 Standards Baseline

VCT.RC.M 16.25 6,883.56 Standards Baseline

VCT.RC.L 39.01 7,856.68 Standards Baseline

VCT.SC.M 9.22 2,601.64 Standards Baseline

VCT.SC.L 29.09 3,468.66 Engineering Baseline

VCT.SC.I 20.71 3,826.67 Standards Baseline

VCS.SC.M 4.45 1,694.25 Engineering Baseline

VCS.SC.L 11.00 1,880.11 Engineering Baseline

VCS.SC.I 19.12 2,237.74 Standards Baseline

SVO.RC.M 36.38 4,258.91 Standards Baseline

SVO.SC.M 26.73 2,084.45 Standards Baseline

SOC.RC.M 26.12 7,380.31 Standards Baseline

HZO.RC.M 14.43 4,065.55 Standards Baseline

HZO.RC.L 33.10 4,658.43 Standards Baseline

HZO.SC.M 14.79 1,044.88 Standards Baseline

HZO.SC.L 30.12 1,998.28 Standards Baseline

HCT.SC.M 2.28 836.64 Engineering Baseline

HCT.SC.L 5.17 959.50 Engineering Baseline

HCT.SC.I 3.30 1,035.70 Standards Baseline

HCS.SC.M 0.73 746.26 Engineering Baseline

HCS.SC.L 2.11 762.34 Engineering Baseline

PD.SC.M 6.91 1,473.54 Standards Baseline

SOC.SC.M 31.60 7,980.38 Standards Baseline

8.2.2.2 Candidate Standard Level Energy Consumption and Manufacturer 

Selling Price Increases

The CSL MSP increase is the change in MSP associated with producing equipment at 

higher efficiency levels above the baseline. Increases in MSP as a function of equipment 

efficiency were developed for each of the 25 primary equipment classes (TSD chapter 5). The 

engineering analysis (TSD chapter 5) established a series of MSP increases for each CSL. 

Table 8.2.4 presents the increase in MSP values corresponding to all efficiency levels for each 

equipment class. Table 8.2.5 presents the daily energy consumption of the representative units 

belonging to each of the 25 primary equipment classes that were selected for the engineering 

analysis (TSD chapter 5). 
8-12

Table 8.2.4 CSL MSP Increases (Price Increases Relative to the Price of Baseline Efficiency 

Level) 

Equipment 

Class

Increase in MSP by Efficiency Level*

2012$

Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M $44.98 $167.18 $1,184.95 $1,249.03 $3,906.09 NA NA

VOP.RC.L $61.40 $414.00 $485.07 $4,822.00 NA NA NA

VOP.SC.M $15.50 $33.12 $70.56 $489.36 $532.34 $1,438.58 NA

VCT.RC.M $21.12 $533.52 $662.01 $731.24 $755.52 $3,840.29 NA

VCT.RC.L $156.41 $284.89 $353.39 $396.62 $4,448.32 NA NA

VCT.SC.M $40.95 $259.13 $387.61 $408.90 $454.09 $463.89 $1,553.24 

VCT.SC.L $74.76 $279.92 $296.83 $425.31 $438.53 $505.01 $1,969.64 

VCT.SC.I $74.83 $88.05 $216.53 $237.82 $283.74 $2,225.19 NA

VCS.SC.M $39.88 $45.68 $49.69 $62.90 $84.19 $129.38 $1,218.74 

VCS.SC.L $46.73 $59.43 $66.91 $112.10 $125.31 $146.60 $1,611.23 

VCS.SC.I $0.46 $20.43 $33.65 $79.57 $100.86 $2,042.31 NA

SVO.RC.M $9.84 $186.04 $962.82 $1,015.42 $2,719.94 NA NA

SVO.SC.M $2.33 $61.07 $86.03 $427.55 $466.72 $1,056.08 NA

SOC.RC.M $15.20 $43.06 $508.17 $555.49 $702.32 $1,968.09 NA

HZO.RC.M $1,154.40 NA NA NA NA NA NA

HZO.RC.L $2,056.74 NA NA NA NA NA NA

HZO.SC.M $1.52 $12.17 $53.87 $853.46 NA NA NA

HZO.SC.L $478.71 NA NA NA NA NA NA

HCT.SC.M $3.69 $8.53 $14.41 $97.19 $109.67 $147.84 $654.17 

HCT.SC.L $6.67 $16.51 $99.29 $105.16 $117.64 $155.81 $840.73 

HCT.SC.I $2.11 $14.59 $53.13 $968.18 NA NA NA

HCS.SC.M $1.19 $6.03 $11.91 $24.39 $61.22 $457.10 NA

HCS.SC.L $1.79 $6.49 $12.36 $24.84 $61.68 $598.89 NA

PD.SC.M $45.31 $147.79 $154.40 $165.04 $293.53 $341.89 $1,196.02 

SOC.SC.M $90.20 $131.29 $152.58 $617.69 $665.00 $811.84 $2,077.61 

* “NA” implies no design options associated with the efficiency level
8-13

Table 8.2.5 Energy Consumption Values for Representative Commercial Refrigeration 

Equipment Units of the 25 Primary Equipment Classes at All Efficiency Levels 

Equipment

Class

Total Annual Energy Usage*

kWh/day

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M 47.78 46.84 44.33 35.71 35.51 35.06 NA NA

VOP.RC.L 108.23 106.22 101.03 100.51 98.87 NA NA NA

VOP.SC.M 30.69 30.37 30.03 29.60 26.70 26.62 26.46 NA

VCT.RC.M 16.25 15.56 8.10 6.26 6.01 5.97 5.49 NA

VCT.RC.L 39.01 33.27 31.13 30.58 30.29 28.85 NA NA

VCT.SC.M 9.22 7.56 4.08 3.24 3.13 2.98 2.97 2.68

VCT.SC.L 29.09 21.51 13.48 13.30 12.44 12.37 12.09 11.57

VCT.SC.I 20.71 17.57 17.45 16.51 16.36 16.14 15.37 NA

VCS.SC.M 4.45 2.53 2.36 2.30 2.17 2.01 1.81 1.39

VCS.SC.L 11.00 7.69 7.26 7.07 6.75 6.66 6.56 5.71

VCS.SC.I 19.12 19.09 18.24 18.11 17.79 17.64 16.53 NA

SVO.RC.M 36.38 36.11 33.85 27.71 27.57 27.26 NA NA

SVO.SC.M 26.73 26.67 25.74 25.36 23.29 23.24 23.12 NA

SOC.RC.M 26.12 25.62 24.97 20.43 20.31 20.15 19.93 NA

HZO.RC.M 14.43 14.17 NA NA NA NA NA NA

HZO.RC.L 33.10 32.22 NA NA NA NA NA NA

HZO.SC.M 14.79 14.76 14.60 14.49 14.26 NA NA NA

HZO.SC.L 30.12 29.91 NA NA NA NA NA NA

HCT.SC.M 2.28 2.03 1.87 1.73 0.84 0.75 0.67 0.49

HCT.SC.L 5.17 4.52 4.11 1.83 1.77 1.70 1.57 1.18

HCT.SC.I 3.30 3.22 3.07 2.86 2.13 NA NA NA

HCS.SC.M 0.73 0.65 0.60 0.56 0.50 0.42 0.25 NA

HCS.SC.L 2.11 1.88 1.73 1.61 1.46 1.27 0.74 NA

PD.SC.M 6.91 3.90 2.23 2.20 2.16 1.75 1.64 1.42

SOC.SC.M 31.60 28.04 27.04 26.80 22.02 21.88 21.70 21.41

* “NA” implies no design options associated with the efficiency level

8.2.2.3 Price Trends

In prior energy conservation standards rulemakings, DOE estimated the total installed 

costs per unit for equipment, and then assumed that costs remain constant throughout the 

analysis period. This assumption is conservative because installed costs tend to decrease over 

time. In 2011, DOE issued a notice of data availability (NODA) titled Equipment Price 

Forecasting in Energy Conservation Standards Analysis. 76 FR 9696 (Feb. 22, 2011) In the 

NODA, DOE proposed a methodology for analyzing whether equipment prices have trended 

downward in real terms. The methodology examines so-called experiential learning, wherein, 

with ever-increasing experience with the production of a product, manufacturers are able to 

reduce their production costs through innovations in technology and process. 

To account for increased efficiency in the commercial refrigeration equipment 

manufacturing process over time, DOE used a price forecast methodology based on experiential 

learning (see appendix 8D for more information on experiential learning). For the LCC model, 

the impact of experiential learning was a decrease in the MSP to account for changes from the 

time prices were developed (2012) until the start of the LCC analysis (2017). The experiential 

learning factor used in the LCC and Payback Period Analysis was 0.9945, which means MSPs 

shown on Table 8.2.4 were reduced by 0.55 percent in the development of total installed costs. 
8-14

8.2.2.4 Markups 

As discussed in TSD chapter 6, DOE calculated distribution channel markups to 

determine the equipment purchase price to customers from the equipment MSP. DOE calculated 

baseline markups to convert baseline MSP to baseline customer purchase price and incremental 

markups to convert the increments in MSP into increments in customer purchase price. DOE 

used these markup values in the LCC analysis for calculation of baseline and higher efficiency 

equipment price to customers. 

8.2.2.5 Installation Cost

Most refrigerated display cases are installed in fairly standard configurations, which helps 

in creating standardized estimates for the cost of installation across all equipment classes. For 

example, supermarkets commonly configure display cases as part of a “lineup” of similar cases.

Horizontal open cases are commonly installed as single units placed in appropriate store 

locations. Self-contained display cases are used for portable or temporary product displays, or 

sometimes used as end-caps of aisles.

For remote condensing equipment, typical steps in the installation of display cases in a 

lineup are as follows: 

• move new case to lineup position in store; 

• position case in lineup, providing shims for vertical spacing as needed; 

• caulk or seal adjacent cases together; 

• bolt adjacent cases together; 

• trim cases together for good visual look (installing bumpers and covering seams); 

• braze refrigerant lines as necessary to system piping (already in place); 

• if hot gas defrost is used, braze hot gas defrost refrigerant lines as necessary to defrost 

piping (already in place); 

• provide electrical conduit and tie-in electrical connections to case; 

• install display lamps; and 

• set refrigerant and defrost control settings. 

Note that final operational testing of cases is undertaken after initial installation of all 

cases in a lineup and refrigerant is piped to each case. 

For self-contained refrigeration equipment, typical installation steps are as follows: 

• move new equipment to the target position in store; 

• where applicable, make sure that the condensate pan is installed properly; 

• plug cord into electrical outlet and turn on main power; 

• make sure the evaporator and condenser fans are functioning properly;

• where applicable, turn on lights; and 

• adjust temperature settings to desired levels.

The installation steps just listed for both self-contained and remote condensing equipment 

are not influenced by any of the engineering design options accounted for in this rulemaking. 
8-15

DOE assumes that the night curtains (for open display cases) are provided by the manufacturer in 

pre-installed condition and hence that no additional costs are incurred for installation of night 

curtains. From conversations with consultants with experience in retrofitting display cases with 

light-emitting diode (LED) lighting and occupancy sensors, DOE determined that the additional 

costs incurred in installation of occupancy sensors are minimal, and it is unlikely that installers 

would bill additional charges to the customers. Therefore, DOE assumes that the installation 

costs do not vary with efficiency levels in any equipment class. 

The installation costs may vary from one equipment class to another, but they do not vary 

with efficiency levels within an equipment class. Costs that do not vary with efficiency levels do 

not impact the LCC, PBP, or NIA results. DOE retained the nationally representative installation 

cost values from the January 2009 final rule analysis for all remote condensing equipment as 

$2,000 and for all self-contained equipment as $750, and simply escalated the values from 2007$ 

to 2012$, resulting in 2012 installation costs of $2,299 and $862, respectively. DOE designed the 

LCC spreadsheet such that installation costs can be varied by CSL, but DOE has modeled 

installation cost as constant across CSLs for the NOPR analysis.

Table 8.2.6 shows installation cost indices for installations in each of the 50 states, plus 

the District of Columbia, which were used to adjust the nationally representative installation 

costs for each state. To arrive at an average index for each state, DOE first weighted the city 

indices in each state by their population within the state. DOE used city-level population 

estimates for 2011 and state-level population weights for 2012 from the U.S. Census Bureau to 

calculate a weighted-average index for each state. 

8.2.2.6 Weighted-Average Total Installed Cost

As presented in Eq. 8.2, the total installed cost is the sum of the equipment price and the 

installation cost. DOE derived the customer equipment price for any given standard level by 

multiplying the baseline MSP by the baseline markup and sales tax and adding to it the product 

of the incremental MSP and the incremental markup and sales tax. Because MSPs, markups, and 

the sales tax all can take on a variety of values depending on location (state), the resulting total 

installed cost for a particular CSL will not be a single-point value, but rather a distribution of 

values.

Table 8.2.6 Installation Cost Indices (National Value = 100.0) 

State Index State Index State Index

Alabama 56.4 Kentucky 84.8 North Dakota 62.6

Alaska 112.1 Louisiana 64.2 Ohio 99.2

Arizona 83.9 Maine 81.4 Oklahoma 56.0

Arkansas 59.3 Maryland 88.5 Oregon 106.4

California 132.9 Massachusetts 128.4 Pennsylvania 127.4

Colorado 83.5 Michigan 108.1 Rhode Island 119.2

Connecticut 126.2 Minnesota 122.3 South Carolina 38.4

Delaware 125.4 Mississippi 58.2 South Dakota 44.1

Dist. of Columbia 101.5 Missouri 105.8 Tennessee 76.3

Florida 72.2 Montana 78.1 Texas 61.9

Georgia 70.0 Nebraska 83.6 Utah 75.9

Hawaii 121.1 Nevada 106.1 Vermont 76.7

Idaho 74.0 New Hampshire 95.3 Virginia 78.4
8-16

Table 8.2.6 (cont) 

State Index State Index State Index

Illinois 138.6 New Jersey 135.4 Washington 115.0

Indiana 86.3 New Mexico 74.1 West Virginia 92.7

Iowa 84.9 New York 170.6 Wisconsin 103.1

Kansas 73.7 North Carolina 57.9 Wyoming 71.2

The weighted-average costs for the VCT.SC.L equipment class are presented in 

Table 8.2.7 for the baseline level at national average markup rates and national average 

installation costs for illustration purposes. Derivation of the total installed cost is straightforward.

The baseline MSP and the standard level MSP increases are the starting points for determining 

the total installed cost (values are taken directly from Table 8.2.4 and Table 8.2.5). DOE used the 

baseline and incremental markups, the sales tax, and installation costs to convert the MSPs into 

total installed costs for a case where the incremental installation costs are held flat. Table 8.2.7

summarizes the weighted average or mean costs and markups necessary for determining the 

weighted-average baseline and standard level total installed costs for convenience stores as an 

example. 

Table 8.2.7 Costs and Markups for Determination of Weighted-Average Total Installed 

Costs for Convenience Stores (VCT.SC.L)* 

Variable Weighted Average or Mean Value

Baseline MSP $3,468.66 

Standard Level MSP Increase (Efficiency Level 4) $296.83 

Experiential Learning 0.9945

Overall Markup Factor–Baseline 1.4236

Overall Markup Factor–Incremental 1.1761

Installation Cost–Baseline $862 

Installation Cost Factor, for U.S. Average 1

*Installation costs apply to the baseline unit, with no incremental installation costs.

To illustrate the derivation of the weighted-average total installed cost based on the data 

shown in Table 8.2.7, DOE presents the following calculation for the baseline (Level 1) and for a 

higher efficiency level (Level 4) VCT.SC.L equipment class. For the baseline product, the 

calculation of the total installed cost at national average conditions is as follows:

a

ICBASE VCT.SC.L = EQPBASE VCT.SC.L + INSTBASE VCT.SC.L × ISTINDEX

= MFGBASE VCT.SC.L × MUBASE VCT.SC.L × EL + INSTBASE VCT.SC.L

× ISTINDEX

= $3,468.66 × (1.4236) × 0.9945 + $862 x (1.00) 

= $4,911 + $862 

= $5,773 

Eq. 8.3 

 

a Note that the numbers shown in Eq. 8.3 have been rounded and do not exactly match the numbers in the analysis.
8-17

Where: 

ICBASE VCT.SC.L = total installed cost of VCT.SC.L equipment at baseline efficiency level ($), 

EQPBASE VCT.SC.L = equipment purchase price of VCT.SC.L equipment at baseline efficiency level 

($),

EL = experiential learning factor applied to all MSP baseline and incremental values,

INSTBASE VCT.SC.L = installation cost of VCT.SC.L equipment at baseline efficiency level ($),

MFGBASE VCT.SC.L = MSP of VCT.SC.L equipment at baseline efficiency level ($), 

MUBASE VCT.SC.L = overall baseline markup for equipment class VCT.SC.L, and 

ISTINDEX = location-dependent multiplier on installation costs; approximately 1.0 at a national 

average.

The calculation of the higher Efficiency Level 4 total installed cost includes the use of an 

MSP increment. DOE uses an incremental markup factor that applies to incremental increases in 

MSP. The Level 4 price is equal to the baseline price calculated in Eq. 8.3, plus the MSP

increment for a higher efficiency level multiplied by the incremental markup. 

As an example, DOE calculated the national average Level 4 total installed cost (ICVCT,SC,L

LEVEL4) as follows:b

ICVCT.SC.L LEVEL4 = EQPVCT.SC.L LEVEL4 + INSTVCT.SC.L LEVEL4 × ISTINDEX

= MFGBASE VCT.SC.L × MUBASE VCT.SC.L + ∆MFGVCT.SC.L LEVEL4 × MUVCT.SC.L LEVEL4 +

 INSTVCT.SC.L LEVEL4 × ISTINDEX 

= $3,468.66 × (1.4236) × 0.9945 + $296.83 × (1.1761) × 0.9945 

 + $862 × (1.000) 

= $6,120 

Eq. 8.4 

Where: 

ICVCT.SC.L LEVEL4 = total installed cost of VCT.SC.L equipment at Efficiency Level 4 ($), 

EQP VCT.SC.L LEVEL4 = equipment price of VCT.SC.L equipment at Efficiency Level 4 ($), 

INST VCT.SC.L LEVEL4 = installation cost of VCT.SC.L equipment at Efficiency Level 4 ($), 

ΔMFG VCT.SC.L LEVEL4 = incremental increase in MSP of VCT.SC.L equipment at Efficiency Level 

4 compared to equipment at baseline efficiency level ($), and 

MU VCT.SC.L LEVEL4 = incremental markup for equipment class VCT.SC.L. 

Table 8.2.8 presents the weighted-average equipment price, installation costs, and total

installed costs for the VCT.SC.L equipment classes at the baseline level and each higher 

efficiency level examined. 

 

b Note that the numbers shown in Eq. 8.4 have been rounded and do not exactly match the numbers in the analysis.
8-18

Table 8.2.8 Weighted-Average Equipment Price, Installation Cost, and Total Installed 

Costs for VCT.SC.L at U.S. Average Conditions (2012$)c

Efficiency Level Equipment Price (MSP) Installation Cost Total Installed Cost

1 (Baseline) $3,468.66 $862 $5,773

2 $3,543.43 $862 $5,860 

3 $3,748.59 $862 $6,100 

4 $3,765.49 $862 $6,120 

5 $3,893.98 $862 $6,270 

6 $3,907.19 $862 $6,286 

7 $3,973.68 $862 $6,363 

8 $5,438.31 $862 $8,077 

8.2.3 Operating Cost Inputs

DOE defines the operating cost as the sum of energy cost, repair cost, and maintenance 

cost, as shown in the following equation: 

OC = EC+ RC+ MC

Eq. 8.5 

Where: 

OC = operating cost ($), 

EC = energy cost ($), 

RC = repair cost ($), and 

MC = maintenance cost ($). 

The remainder of this section provides information about the variables that DOE used to 

calculate the operating cost for commercial refrigeration equipment. Table 8.2.9 shows the inputs 

for the determination of operating costs. 

Table 8.2.9 Inputs for Operating Costs

Electricity price (cents/kWh)

Electricity price trend

Repair cost ($)

Maintenance cost ($)

Lifetime (years)

Discount rate (%)

Effective date of standard

Baseline electricity consumption (kWh/day)

Standard case electricity consumption (kWh/day)

 

c Figures shown in the table are rounded and do not match values in the analysis. In the LCC model, none of the 

numbers in this series of calculations are rounded so total installed cost in the analysis differs from values on this 

table.
8-19

8.2.3.1 Electricity Price Analysis

This section describes the electricity price analysis used to develop the energy portion of 

the annual operating costs for commercial refrigeration equipment used in different commercial 

building types. 

Subdivision of the Country. Because of the wide variation in electricity consumption 

patterns, wholesale costs, and retail rates across the country, it is important to consider regional 

differences in electricity prices. For this reason, DOE divided the United States into the 50 states 

and the District of Columbia. DOE used reported average effective commercial electricity prices 

at the state level from the EIA publication Form EIA-826 Database Monthly Electric Utility 

Sales and Revenue Data.

2 The prices used from this source are for the calendar year 2012. 

Table 8.2.10 provides data on the adjusted electricity prices. 

Table 8.2.10 Commercial Electricity Prices by State (2012 cents/kWh) 

State

Commercial 

Electricity 

Price

cents/kWh

State

Commercial 

Electricity 

Price

cents/kWh

State

Commercial 

Electricity 

Price

cents/kWh

Alabama 10.58 Kentucky 8.66 North Dakota 7.98

Alaska 14.79 Louisiana 7.79 Ohio 9.47

Arizona 9.54 Maine 11.58 Oklahoma 7.26

Arkansas 7.68 Maryland 10.52 Oregon 8.34

California 13.60 Massachusetts 13.97 Pennsylvania 9.37

Colorado 9.34 Michigan 10.95 Rhode Island 12.04

Connecticut 14.70 Minnesota 8.86 South Carolina 9.57

Delaware 10.11 Mississippi 9.28 South Dakota 8.01

Dist. of Col. 12.00 Missouri 8.16 Tennessee 10.29

Florida 9.76 Montana 9.16 Texas 8.17

Georgia 9.47 Nebraska 8.40 Utah 8.05

Hawaii 34.83 Nevada 8.86 Vermont 14.30

Idaho 6.83 New Hampshire 13.40 Virginia 8.11

Illinois 8.19 New Jersey 12.83 Washington 7.67

Indiana 9.07 New Mexico 9.30 West Virginia 8.42

Iowa 8.00 New York 15.08 Wisconsin 10.54

Kansas 9.13 North Carolina 8.61 Wyoming 8.23

DOE recognized that different kinds of businesses typically use electricity in different 

amounts at different times of the day, week, and year, and therefore face different effective 

prices. To make this adjustment, DOE used the 2003 Commercial Buildings Energy 

Consumption Survey (CBECS) data set to identify the average prices paid by the seven kinds of 

businesses in this analysis compared with the average prices paid by all commercial customers.

Since multi-line retail is not explicitly recognized as a CBECS building type, it was identified by 

identifying retail stores with data indicating the presence of walk-in refrigeration and other 

commercial refrigeration on the premises. Eq. 8.6 shows the ratios of prices paid by the seven 

types of businesses that were used to increase or decrease the average commercial prices.

EPRICECOM BLDGTYPE STATE 2012 = EPRICECOM STATE 2012 × �

EPRICEBLDGTYPE US 2003

EPRICECOM US 2003

� 

Eq. 8.6 
8-20

Where: 

EPRICECOM BLDGTYPE STATE 2012 = average commercial sector electricity price in a specific building 

type (such as supermarkets, convenience stores, and restaurants) in a specific state in 2012 

EPRICE COM STATE 2012 = average commercial sector electricity price in a specific state in 2012, 

EPRICE BLDGTYPE US 2003 = national average commercial sector electricity price in a specific building 

type in 2003 CBECS, and 

EPRICE COM US 2003 = national average commercial sector electricity price in 2003 CBECS. 

Table 8.2.11 shows the derivation of the EPRICE ratios from CBECS.

Table 8.2.11 Derived Average Commercial Electricity Price by Business Type

Business Type Electricity Price 

cents/kWh

Ratio of Electricity Price to Average Price 

for all Commercial Buildings

Grocery store/food market 0.07222 0.910

Convenience store * 0.08583 1.082

Convenience store with gas station 0.07722 0.973

Multi-line retail ** 0.07262 0.915

Limited service restaurant 0.07962 1.003

Full service restaurant 0.08467 1.067

Other food service 0.07664 0.966

All commercial buildings 0.07936 1.000

Source: CBECS 2003

* This group is assumed to include convenience stores without gas stations, specialty stores (such as meat markets), and beer, 

wine, and liquor stores.

**This group is assumed to include mainly large multi-line retailers and supercenters that sell both grocery and non-grocery 

items.

The derived ratio of commercial electricity prices by building type to the overall average 

commercial building price was then combined with state-by-state commercial rates to derive a 

series of prices for each state and for each building type. Future prices were forecasted as 

described in section 8.2.3.2. To obtain a weighted-average national price, DOE weighted the 

prices paid by each business in each state by the 2012 population in each state.

3

For evaluation purposes, the resulting electricity prices and the calculated market 

weighting factors can be depicted as a cumulative probability distribution. The effective prices 

range from approximately 6.22 cents per kilowatt-hour to approximately 31.70 cents per 

kilowatt-hour. Figure 8.2.1 illustrates the results for the convenience and small food retail market 

sector.
8-21

Figure 8.2.1 Cumulative Probability Distribution Showing the Electricity Prices Paid by 

Convenience/Small Market Sector in 2012 (2012$) 

8.2.3.2 Electricity Price Trend

The electricity price trend provides the relative change in electricity prices for future

years out to 2046. Estimating future electricity prices is difficult, especially considering that 

there are efforts in many states throughout the country to restructure the electricity supply 

industry. 

DOE applied a projected trend in national average electricity prices to each customer’s 

energy prices based on the AEO2013 price scenarios. The discussion in this chapter refers to the 

2012 reference price scenario. In the LCC analysis, the following four scenarios can be analyzed: 

1. Constant (real) energy prices at 2012 values (i.e., a constant index of 1.0 in Figure 8.2.2) 

2. AEO2013, High Economic Growth (“AEO2013 High Growth” in Figure 8.2.2) 

3. AEO2013, Reference Case (“AEO2013 Reference” in Figure 8.2.2) 

4. AEO2013, Low Economic Growth (“AEO2013 Low Growth” in Figure 8.2.2) 

Figure 8.2.2 shows the trends for the three AEO2013 price projections where prices are 

assumed to change. DOE extrapolated the values in later years (i.e., after 2040—the last year of 

the AEO2013 forecast). To arrive at values for these later years, DOE used the price trend from 

2031 to 2040 of each forecast scenario to establish prices for the years 2041 to 2046. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

5 10 15 20 25 30 35 40

Cumulative Percentage of Electricity Prices

Cents/kWh

Electricity Prices Faced By CREs Sold To Convenience 

Stores

Elec Price
8-22

Figure 8.2.2 Electricity Price Trends for Commercial Rates to 2046 

The default electricity price trend scenario used in the LCC analysis is the trend from the

AEO2013 Reference Case, shown in Figure 8.2.2. Spreadsheets used in calculating the LCC have 

the capability to analyze the other electricity price trend scenarios, namely, the AEO2013 High 

Growth and the AEO2013 Low Growth price trends and constant energy prices. 

8.2.3.3 Repair Cost

The repair cost is the cost to the customer for replacing or repairing failed components in 

commercial refrigeration equipment. For the January 2009 final rule analysis, DOE obtained 

estimated rates of component failures as shown in Table 8.2.12. DOE based the annualized repair 

cost on the following expression: 

RC = k × EQPOEM × MUREPLACE/LIFE 

Eq. 8.7 

Where: 

RC = repair cost ($), 

k = fraction of the components likely to be replaced during the equipment lifetime, 

EQPOEM = original equipment manufacturer cost of the component ($), 

0.800

0.850

0.900

0.950

1.000

1.050

1.100

1.150

1.200

1.250

1.300

1.350

1.400

2010 2015 2020 2025 2030 2035 2040 2045

Index (2012=1.00)

Year

Electricity Price Index Projections 

AEO 2013 High Growth AEO 2013 Reference AEO 2013 Low Growth
8-23

MUREPLACE = markup applied to original equipment manufacturer cost of the component to the 

cost to replace the component (includes the labor cost to replace/repair), and

LIFE = lifetime of the equipment in years.

As the components used for higher efficiency commercial refrigeration equipment have a 

higher original equipment manufacturer (OEM) cost, Eq. 8.7 yields an increasing repair costs 

scenario for higher efficiency equipment. 

There are other refrigeration parts that typically require repair, such as door handles, 

hinges, shelves, drain pans, and condensate pan heaters. However, these parts are the same for all 

efficiency levels, so the repair costs for these parts remain constant for all efficiency levels. 

Therefore, these additional repair costs were not taken into consideration for the analysis.

Table 8.2.12 Estimated Replacement Rate of Components During Equipment Service Life 

(Values Retained from January 2009 Final Rule Analysis) 

Component Estimated Replacement Rate

(over 10 year period)

Evaporator fans 50%

Condenser fans 25%

Compressors 25%

Coils* 5%

Doors 5%

*Applied only to remote condensing equipment

8.2.3.4 Maintenance Costs 

Maintenance costs are the costs to the customer of maintaining installed equipment. 

Maintenance costs are not the costs associated with the replacement or repair of components that 

have failed (as discussed in section 8.2.3.3). Rather, they are the costs associated with general 

maintenance. 

DOE obtained annualized maintenance costs for commercial refrigeration equipment

from data in RS Means Facilities Maintenance & Repair Cost Data.4RS Means provides 

estimates on the person-hours, labor rates, and materials required to maintain commercial 

refrigeration equipment. RS Means specifies preventative maintenance activities for commercial 

display cases expected to occur on a semi-annual basis as including the following actions: 

cleaning evaporator coils, drain pans, fans, and intake screens; lubricating motors; inspecting 

door gaskets and seals, and lubricating hinges; cleaning condenser coils; checking refrigerant 

pressures and compressor oil as necessary; checking starter panels and controls; and checking 

defrost system operation. From the RS Means data DOE obtained costs of $220 per year (2012$) 

for preventative maintenance activities for all remote condensing equipment classes and $35 per 

year (2012$) for self-contained equipment classes. Because data were not available to indicate 

how maintenance costs vary with CSL, DOE decided to use preventative maintenance costs that 

remain constant as equipment efficiency is increased. It should be noted that since the 

preventative maintenance cost is assumed to be constant over all CSLs within an equipment 

class, it does not affect the LCC analysis or NIA results because only costs that vary with CSLs 

(incremental costs) lead to changes in these results.
8-24

DOE considered lamp replacements and other lighting maintenance activities as required 

maintenance for commercial refrigeration equipment, and apart from preventative maintenance. 

Thus, DOE did not itemize them in the preventative maintenance activities described by RS 

Means. Different commercial refrigeration equipment classes have different numbers of lamps 

(and ballasts), and many of the technologies DOE considered in the engineering analysis 

involved changes to the lighting configuration (lamp, ballast, or use of LED lighting systems).

Because the lighting configurations can vary by CSL, DOE estimated the relative maintenance 

costs for lighting for each equipment class at each CSL. DOE’s methodology was to estimate the 

frequency of failure and replacement of individual lighting components, to estimate the cost of 

replacement in the field, and to develop an annualized maintenance cost based on the sum of the 

total lighting maintenance costs (in 2012$) over the estimated life of the equipment divided by 

the estimated life of the equipment.

Lifetime estimates for particular lighting components were as follows: 

• Fluorescent lamps would be replaced every 24 months in a preventative fashion. 

• Fluorescent lamp ballasts would be replaced once over the estimated 10-year life of 

the equipment based on a typical ballast life of 80,000 hours. 

• LED lamps would be replaced once every 5.7 years based on a typical fixture life of 

50,000 hours.5

 

The approach taken was to estimate the costs of field replacement using labor cost hours 

from RS Means Electrical Cost Data6 for typical lamp or ballast replacement as baseline values. 

The costs for replacement of lamps and ballasts can be split into cost of material and cost of 

labor. The cost of labor was determined from the RS Means database as the cost to replace one 

fluorescent bulb and the cost to replace one fluorescent lamp ballast. The cost of equipment was 

determined by using the OEM costs of the lamps and ballasts and applying material cost 

markups to reflect retail pricing as explained below. 

DOE estimated the material cost markup to be 250 percent by comparing the OEM costs 

of fluorescent lamps and ballasts with typical retail prices. However, typically, when large food 

retailers replace lamps or ballasts in their display cases, they tend to replace the lamps and 

ballasts in all display cases at the same time. Large food retailers house a large number of remote 

condensing display cases, and therefore tend to purchase lamps and ballasts in bulk. DOE 

estimated that through such bulk purchases large food retailers are able to negotiate a largevolume discount. Therefore, for remote condensing equipment, the material cost markup was 

assumed to be a 150-percent multiplier on OEM costs for lamps and ballasts. Small businesses, 

such as restaurants, that typically house only self-contained equipment do not get such a volume 

discount because they do not purchase a large number of lamps and ballasts. Therefore, for selfcontained equipment, the material cost markup was assumed to be a 250-percent multiplier on 

OEM costs for lamps and ballasts to reflect retail pricing. DOE is aware that many large food 

retail stores also house self-contained equipment, and some small businesses may use remote

condensing equipment. However, DOE does not have the data to reliably determine the fraction 

of self-contained equipment in large food retail stores and the remote condensing equipment in 

small business establishments. DOE believes the assumptions detailed in this section reflect a 

reasonable compromise in the calculation of the lighting maintenance costs. 
8-25

Based on the cost values from RS Means database, the typical markup value on labor 

costs (labor cost markup) was calculated to be approximately 157 percent. However, this labor 

cost markup was applied to the RS Means labor cost values for self-contained equipment only. 

No labor cost markup was applied to the RS Means labor cost values for remote condensing 

equipment. Once again, the assumption was that the remote condensing equipment that is housed 

mainly in large food retail stores has the advantage of volume discount, whereas self-contained 

equipment, which is typically housed in small business establishments, does not have the 

advantage of volume discount. In effect, no markup for remote condensing equipment amounts 

to the assumption that large food retailers use in-house labor for replacement of lamps and 

ballasts. DOE believes these assumptions provide reasonably accurate estimates for lighting 

maintenance costs.

The lamp and ballast replacement costs obtained from the RS Means database are

applicable for replacement of lamps and ballasts in overhead lamp fixtures. The labor effort and 

time involved in replacing lamps and ballasts in display cases is much lower compared those 

associated with overhead lamp fixtures. DOE assumed that the labor costs for replacing lamps 

and ballasts in display cases would be about half of the costs for overhead lamp fixtures. 

Fluorescent lamp and ballast technology is mature. Available information suggests that 

there would be no change in inflation-adjusted costs for these components. However, because of 

rapid technological improvement, costs for LED lamps are declining. As discussed in TSD 

chapter 5, DOE estimated the annual reduction in the prices of LED lamps from 2013 through 

2030. DOE used these price reductions to estimate the cost of LED lamps in 2022, 6 years into 

the compliance date of this rule when LED lamps would be first replaced for equipment installed 

in the year of compliance (2017). 

DOE determined that the effort required to replace a fluorescent lamp ballast is similar to 

the effort required to replace the power supply (driver) of an LED lamp. However, replacement 

of LED lamps involves additional effort to replace the LED lighting fixture. DOE estimated that 

the total labor cost to replace an LED lamp (lighting fixture and power supply) would be 

approximately 25 percent higher than the cost to replace a fluorescent lamp ballast. The 

assumption of material cost markup (of 150-percent for remote condensing equipment and 250-

percent for self-contained equipment) was retained for LED lamps replacement cost estimation. 

The total costs for lamp, ballast, or LED fixture replacement were annualized by dividing 

the total estimated replacement costs over the lifetime of commercial refrigeration equipment as 

shown in Eq. 8.8. 

Annualized Lighting Maintenance Cost = 

1

Life ∑ �OEM_Cost Life Lamp/Ballast ×

MarkupRetail +

�NBulb × LaborBulb + NBallast × LaborBallast + NLED_Lamps × LaborLED_Lamps� ×

MarkupLabor� 

Eq. 8.8 

Where: 
8-26

Annualized Lighting Maintenance Cost = annualized lighting maintenance cost ($) for an 

efficiency level, 

Life = commercial refrigeration equipment lifetime (years), 

OEM_CostLamp/Ballast = OEM costs for all the fluorescent bulbs, LED lamps, and fluorescent lamp

ballasts in each unit of equipment; obtained from engineering analysis (TSD chapter 5) ($), 

MarkupRetail = 250 percent for self-contained equipment, and 150 percent for remote condensing 

equipment, 

NBulb = number of fluorescent bulbs in the particular efficiency level of the equipment class 

analyzed, 

LaborBulb = labor cost to replace one fluorescent bulb ($), 

NBallast = number of fluorescent lamp ballasts in the particular efficiency level of equipment class 

analyzed, 

LaborBallast = labor cost to replace one fluorescent ballast ($), 

NLED_Lamps = number of LED lamps in the particular efficiency level of equipment class analyzed,

LaborLED_Lamps = labor cost to replace one LED lamp, including the power supply ($). This value 

is 1.25 times LaborBallast, and 

MarkupLabor = 157 percent for self-contained equipment, and 100 percent for remote condensing 

equipment. 

Table 8.2.13 shows the annualized lighting maintenance costs for each efficiency level

for the representative units defined in the engineering analysis. Total annualized maintenance 

costs are the sum of the preventative maintenance and the lighting maintenance costs. 
8-27

Table 8.2.13 Annualized Lighting Maintenance Costs by Equipment Class for Each CSL

for the Representative Units Analyzed in the Engineering Analysis

Equipment 

Class

Annualized Lighting Maintenance Costs by Efficiency Level

2012$/yr

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M 95.86 95.86 95.86 118.53 118.53 118.53 NA NA

VOP.RC.L 41.08 41.08 35.85 35.85 35.85 NA NA NA

VOP.SC.M 55.02 55.02 55.02 55.02 63.96 63.96 63.96 NA

VCT.RC.M 32.35 32.35 32.35 32.35 32.35 32.35 32.35 NA

VCT.RC.L 32.35 32.35 32.35 32.35 32.35 32.35 NA NA

VCT.SC.M 23.85 23.85 23.85 23.85 23.85 23.85 23.85 23.85

VCT.SC.L 42.89 23.85 23.85 23.85 23.85 23.85 23.85 23.85

VCT.SC.I 23.85 23.85 23.85 23.85 23.85 23.85 23.85 NA

VCS.SC.M - - - - - - - -

VCS.SC.L - - - - - - - -

VCS.SC.I - - - - - - - NA

SVO.RC.M 68.47 68.47 68.47 92.36 92.36 92.36 NA NA

SVO.SC.M 38.50 38.50 38.50 38.50 49.74 49.74 49.74 NA

SOC.RC.M 68.47 68.47 68.47 71.69 71.69 71.69 71.69 NA

HZO.RC.M - - NA NA NA NA NA NA

HZO.RC.L - - NA NA NA NA NA NA

HZO.SC.M - - - - - NA NA NA

HZO.SC.L - - NA NA NA NA NA NA

HCT.SC.M - - - - - - - -

HCT.SC.L - - - - - - - -

HCT.SC.I - - - - - NA NA NA

HCS.SC.M - - - - - - - NA

HCS.SC.L - - - - - - - NA

PD.SC.M 12.73 14.45 14.45 14.45 14.45 14.45 14.45 14.45

SOC.SC.M 93.15 109.88 109.88 109.88 115.70 115.70 115.70 115.70

“-” is used for equipment classes that do not feature lighting. NA implies there are no associated efficiency levels.

8.2.3.5 Lifetime

DOE defines lifetime as the age at which a commercial refrigeration equipment unit is 

retired from service. DOE based its estimates of equipment lifetime on discussions with industry 

experts and concluded that a typical lifetime of 10 years is appropriate for most commercial 

refrigeration equipment in large grocery/multi-line stores and restaurants. TSD chapter 3, Market 

and Technology Assessment, discusses equipment life and tabulates estimates from various 

sources used in assessing equipment life. Remote condensing commercial refrigeration 

equipment units typically are replaced when stores are renovated, which is before the 

commercial refrigeration equipment units would have physically worn out. Typically, the gap 

between store renovations is around 8 to 9 years for major store chains.7 DOE assumed that an 

average grocery store or supermarket renovates every 10 years. Because some equipment thus 

has remaining useful life, there is a market for commercial refrigeration equipment that has been 

removed from service. DOE understands, however, that the salvage value to the original 

purchaser is very low, and thus has not taken this into account in the LCC. Operators of small 

food retail stores, on the other hand, tend to use display cases for a longer duration. DOE used 15 

years as the average equipment lifetime for display cases used in such retail stores. 
8-28

DOE assumed the average lifetime of all self-contained equipment to be 10 years based 

on discussions with various retailers, manufacturers, and industry experts. During the 

preliminary analysis public meeting, the stakeholders generally agreed that 10 years is a 

reasonable estimate for the lifetime of self-contained equipment. 

To account for uncertainty and variability, DOE determined the probability that a unit of 

commercial refrigeration equipment of age a will break or will be replaced using a Weibull 

survival distribution function W(8,10.62) for display cases in large grocery stores and 

supermarkets, and all self-contained equipment. This Weibull survival function (Figure 8.2.3) 

yielded an average lifetime of 10 years. The minimum lifetime was truncated at 5 years, and the

maximum lifetime was truncated at 15 years to remove the unrealistic probabilities associated 

with the lifetimes outside this range, which were mostly an artifact of the assumption of the 

Weibull function. For display cases used in small grocery stores, the equipment lifetimes were 

represented by the Weibull function W(8,16), which yielded an average lifetime of 15 years. The 

Weibull function was truncated above and below the range of 10 to 20 years (Figure 8.2.4) to 

remove the unrealistic probabilities associated with the lifetimes outside this range, which were 

mostly an artifact of the assumption of the Weibull function. The probabilities of failure in a 

given future year for both equipment lifetime categories are shown on Table 8.2.14. 

Figure 8.2.3 Survival Function for Display Cases in Large Grocery Stores and 

Supermarkets and for All Self-Contained Equipment

Figure 8.2.4 Survival Function for Display Cases in Small Grocery Stores
8-29

Table 8.2.14 Probability of Equipment Failure by Year

Year 10-Year 

Equipment

15-Year 

Equipment

5 0.2%

6 0.8%

7 2.5%

8 6.4%

9 13.5%

10 22.7% 1.3%

11 27.3% 2.6%

12 19.6% 4.7%

13 6.4% 7.9%

14 0.6% 11.9%

15 0.0% 16.1%

16 18.5%

17 17.3%

18 12.2%

19 5.8%

20 1.7%

8.2.3.6 Discount Rate

The discount rate is the rate at which future expenditures are discounted to establish their 

present value. DOE derived the discount rates for the commercial refrigeration equipment 

analysis by estimating the cost of capital for companies that purchase commercial refrigeration 

equipment. The cost of capital is commonly used to estimate the present value of cash flows to 

be derived from a typical company project or investment. Most companies use both debt and 

equity capital to fund investments, so their cost of capital is the weighted average of the cost to 

the company of equity and debt financing. 

DOE estimated the cost of equity financing by using the Capital Asset Pricing Model 

(CAPM).

8 The CAPM, among the most widely used models to estimate the cost of equity 

financing, assumes that the cost of equity is proportional to the amount of systemic risk 

associated with a company. The cost of equity financing tends to be high when a company faces 

a large degree of systemic risk and it tends to be low when the company faces a small degree of 

systematic risk.

DOE determined the cost of equity financing by using several variables, including the 

risk coefficient of a company, β (beta); the expected return on “risk-free” assets (Rf); and the 

additional return expected on assets facing average market risk, also known as the equity risk 

premium or ERP. The risk coefficient of a company, β, indicates the degree of risk associated 

with a given firm relative to the level of risk (or price variability) in the overall stock market.

Risk coefficients usually vary between 0.5 and 2.0. A company with a risk coefficient of 

0.5 faces half the risk of other stocks in the market; a company with a risk coefficient of 

2.0 faces twice the overall stock market risk.

The following equation gives the cost of equity financing for a particular company: 
8-30

ke = Rf + (β x ERP)

Eq. 8.9 

Where: 

ke = the cost of equity for a company (%), 

Rf = the expected return of the risk-free asset (%), 

β = the risk coefficient, and 

ERP = the expected equity risk premium (%). 

DOE defined the risk-free rate as the 40-year geometric average yield on long-term 

government bonds. The risk-free rate was calculated using Federal Reserve data for the period 

1973 to 2012,9 with a resulting rate of 6.41 percent. DOE used a 3.99 percent estimate for the 

ERP based on the difference between the risk-free rate and a 40-year average return on the S&P 

500 index derived from data from the Damodaran Online10 site.

The cost of debt financing (kd) is the interest rate paid on money borrowed by a company. 

The cost of debt is estimated by adding a risk adjustment factor (Ra) to the risk-free rate. 

+= RRk afd , 

Eq. 8.10 

Where:

kd = the cost of debt financing for each firm (%), 

Rf = the expected return on risk-free assets (%), and 

Ra = the risk adjustment factor to risk-free rate for each firm (%). 

The risk adjustment factor depends on the variability of stock returns represented by 

standard deviations in stock prices and was taken from Damodaran Online individual company

cost of capital worksheets.11 The weighted-average cost of capital (WACC) of a company is the 

weighted-average cost of debt and equity financing: 

k =ke x we+ kd x wd 

Eq. 8.11 

Where: 

k = the (nominal) cost of capital (%),

ke = the expected rate of return on equity (%),

kd = the expected rate of return on debt (%),

we = the proportion of equity financing in total annual financing, and 

wd = the proportion of debt financing in total annual financing. 

The cost of capital is a nominal rate, because it includes anticipated future inflation in the

expected returns from stocks and bonds. The real discount rate or WACC deducts expected 

inflation (r) from the nominal rate. DOE calculated inflation (3.68 percent) as the 40-year 
8-31

average gross domestic product deflator derived from U.S. Bureau of Labor Statistics data 

covering the 1973–2012 period.12 

To estimate the WACC of commercial refrigeration equipment purchasers, DOE used a 

sample of companies involved in grocery and multi-line retailing and restaurants drawn from a 

database of U.S. companies given on the Damodaran Online individual company worksheet cited 

earlier. The Damodaran database includes most of the publicly traded companies in the United 

States.

DOE divided the companies into categories according to their type of activity (e.g., Small 

Grocery & Convenience, which covers convenience stores with and without gasoline stations).

DOE used financial information for all of the firms in the Damodaran database engaged in each 

of the seven classes of business. Two classes—Other Food Service and Gas Station with 

Convenience Store—were not identifiable and therefore were calculated differently. 

Table 8.2.15 outlines the building type and ownership categories as well as the number of 

companies used for determining discount rates. For five of the seven building categories there is 

a mixture of large companies with stock traded on major U.S. stock exchanges and smaller

companies that are not publicly traded—e.g., single-store or small, local chains of convenience 

stores or restaurants. The cost of capital for small, independent grocers, convenience store 

franchisees, gasoline station owner-operators, and others with more limited access to capital is 

more difficult to determine than for publicly traded companies. Individual credit-worthiness 

varies considerably, and some franchisees have access to the financial resources of the 

franchising corporation. To model this cost of capital difference, DOE uses a small business 

premium of 1.9 percent (real) based on data compiled from the Small Business Administration 

website.

13

Table 8.2.15 Derivation of Real Discount Rates by Building Type 

Building Type Description

Major Chain Local or 

Non-Chain Governmental

No. 

Obs.* WACC

Percent

of

Stock

Small 

Firm 

Premium

Percent

of

Stock

Muni 

Bond 

Rate

Percent

of 

Stock

Discount 

Rate

Large Grocery 4.16% 100% 0.0% 0% 0% 0% 4.16% 18

Small Grocery & 

Convenience

4.20% 50% 1.9% 50% 0% 0% 5.19% 5

Gas Station With 

Convenience Store

4.20% 50% 1.9% 50% 0% 0% 5.19% NA

Multi-Line Retail 4.33% 100% 0.0% 0% 0% 0% 4.33% 6

Restaurant - Limited Service 5.29% 50% 1.9% 50% 0% 0% 6.29% 21

Restaurant - Full Service 5.61% 50% 1.9% 50% 0% 0% 6.62% 24

Restaurant - Other Food 

Service

5.61% 25% 1.9% 25% 2.34% 50% 4.48% NA

Source: Pacific Northwest National Laboratory (PNNL) WACC calculations applied to firms sampled from the Damodaran Online 

web site. Assumptions for weighting factors for convenience and food service reflect lack of reliable data sources.

*Number of Damodaran observations available.

For two building types, Gas Station with Convenience Store and Restaurant – Other Food 

Service, no representative data was identifiable in the Damodaran database. Gas Station with 

Convenience Store was set equal to the discount rate for Small Grocery and Convenience. Other 
8-32

Food Service was based on the WACC derived for Full Service Restaurants. The main difference 

between the resulting discount rate is that a significant portion of this building category consists 

of cafeterias, a large percentage of which are located in schools, universities, and governmental 

buildings. No data exist on the exact percentage, so it was weighted as 50 percent schools and 50 

percent privately owned. The discount rate for schools, universities, and governmental buildings 

was set equal to a 40-year geometric average of municipal bond rates, mixed quality, obtained 

from the Federal Reserve Bank of St. Louis.14

DOE’s research identified multiple data sources indicating the percentages of building 

stock represented by major chains and by local or non-chain establishments. All of the data 

sources exhibited ambiguities and in many cases contradicted other data sources. For the NOPR, 

the percentages were set to approximate, round values to reflect the uncertainty of the data, as 

shown in Table 8.2.15. Both Large Grocery and Multi-Line Retail were assumed to be 

dominated by major chains, and the percentage divisions were set accordingly. 

8.2.3.7 Compliance Date of Standard

The compliance date is the future date after which all manufacturers selling equipment in 

the United States should comply by the standards. Under 42 U.S.C. 6313(a)(6)(c), the 

compliance date of any new energy conservation standard for commercial refrigeration 

equipment will be 3 years after the final rule is published. DOE calculated the LCC for all 

customers as if they each would purchase a new commercial refrigeration equipment unit in the 

year starting on the compliance date. Consistent with its published regulatory agenda, DOE

assumed that the final rule will be issued in 2014 and therefore the compliance date for the new 

standards will be in 2017. For the LCC analysis, the year of equipment purchase was assumed to 

be 2017. All dollar values are expressed in 2012$. 

8.3 PAYBACK PERIOD INPUTS 

8.3.1 Definition

Payback period is the amount of time it takes the customer to recover the higher purchase 

cost of more energy efficient equipment as a result of lower operating costs. Numerically, the 

PBP is the ratio of the increase in purchase cost to the decrease in annual operating expenditures.

This type of calculation is known as a “simple” payback period because it does not take into 

account changes in operating cost over time or the time value of money; that is, the calculation is 

done at an effective discount rate of zero percent. 

The equation for PBP is: 

PBP =∆IC/∆OC 

Eq. 8.12 

Where: 

PBP = payback period in years,
8-33

∆IC = difference in the total installed cost between the CSL and the baseline level equipment, 

and 

∆OC = difference in the first year annual operating costs between the CSL and the baseline level 

equipment. 

PBPs are expressed in years. PBPs greater than the life of the product mean that the 

increased total installed cost of the CSL is not likely to be recovered in reduced operating costs 

over the life of the equipment. 

8.3.2 Inputs

The data inputs to PBP are the total installed cost of the equipment to the customer for 

each CSL and the annual (first year) operating costs for each CSL. The inputs to the total 

installed cost are the equipment price and the installation cost. The inputs to the operating costs 

are the annual energy cost, the annual repair cost, and the annual maintenance cost. The PBP 

calculation uses the same inputs as the LCC analysis described in section 8.2, except that 

electricity price trends and discount rates are not required because the PBP is a “simple”

(undiscounted) payback and the required electricity price is only for the year in which a new 

efficiency standard is to take effect—in this case, the year 2017. The electricity price used in the 

PBP calculation of electricity cost was the price projected for 2017, expressed in 2012$. 

Discount rates are not used in the PBP calculation.

8.4 LIFE-CYCLE COST AND PAYBACK PERIOD RESULTS

This section presents the results of the LCC and PBP analysis, including the mean and 

median values of LCC savings and PBP. Appendix 8B presents additional details along with 

distribution of impacts on customers. 

8.4.1 Life-Cycle Cost Results

Figure 8.4.1 shows the change in LCC over the eight efficiency levels for an example 

equipment class (VCT.SC.L). The LCC values on this chart are mean values obtained from the 

LCC analysis. This curve is presented here as an example to illustrate the typical relationship 

between installation cost and LCC over all the efficiency levels for an equipment class. The 

installed costs increase steadily from the baseline to the highest possible efficiency level (Level 

8) and the LCCs decrease from Level 1 to Level 7. The increase in installed cost from Level 7 to 

Level 8 is not offset by the decrease in operating cost because of the large increase in installed 

cost with relatively small gains in energy savings. Therefore, for this equipment class there is an 

increase in LCC at Level 8 when compared to Level 7. 
8-34

Figure 8.4.1 LCC and Installed Cost Variation over CSLs for the VCT.SC.L Equipment 

Class 

Since the LCC analysis was carried out in the form of Monte Carlo simulations, the LCC 

savings outputs obtained from the LCC analysis are in the form of distributions. LCC savings 

distributions are illustrated here with the example of the VCT.SC.L equipment class as shown in 

Figure 8.4.2. Similar plots of LCC savings distribution are presented in appendix 8B for all 

equipment classes analyzed. Table 8.4.1 presents the numerical values associated with the plot in 

Figure 8.4.2. Figure 8.4.2 illustrates the mean and median values on the plot with the help of red 

and blue markers, respectively. The elongated large rectangular box is used to represent the 25th

and 75th percentile values. The lower edge of the elongated rectangle represents 25th percentile, 

which means that 25 percent of the customers would experience LCC savings of $2,498 or less if 

the standard were to be set at Level 2, $2,658 or less in LCC savings if the standards were set at 

Level 3, and so on. The median value of LCC savings is equal to the 50th percentile. The upper 

edge of the elongated rectangle represents the 75th percentile. The two ends of the vertical black 

line for each efficiency level represent the 5th percentile (lower end) and 95th percentile (upper 

end). 

Mean and median LCC savings for all equipment classes analyzed are summarized in 

Table 8.4.2 and Table 8.4.3, respectively.

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

Life Cycle Cost $20,302.86 $17,205.24 $14,322.65 $14,270.45 $14,081.92 $14,076.18 $14,055.79 $15,562.45

Installed Cost $5,773.19 $5,860.64 $6,100.60 $6,120.37 $6,270.65 $6,286.11 $6,363.86 $8,076.92

 $-

 $5,000.00

 $10,000.00

 $15,000.00

 $20,000.00

 $25,000.00

VCT.SC.L: Life Cycle and Installed Costs
8-35 

Figure 8.4.2 LCC Savings Distribution for All the CSLs for Equipment Class VCT.SC.L

Table 8.4.1 LCC Savings Distribution Results for Equipment Class VCT.SC.L

Efficiency Level 2 3 4 5 6 7 8

LCC Savings* 

2012$

Mean 3,037 4,186 2,523 1,984 1,587 1,343 (343)

Median 

(50th Percentile)

2,931 3,773 2,333 323 239 196 (1,370)

5th Percentile 1,987 1,889 32 96 0 (6) (1,572)

25th Percentile 2,498 2,658 53 181 101 36 (1,495)

75th Percentile 3,464 5,369 4,302 3,433 2,877 2,283 (847)

95th Percentile 4,494 7,978 7,191 6,921 6,529 6,210 4,491

* Values in parentheses are negative numbers.

-4000

-2000

0

2000

4000

6000

8000

10000

1 2 3 4 5 6 7 8

Life-cycle Cost Savings ($)

Efficiency Level

Mean

Median

`
8-36

Table 8.4.2 Mean LCC Savings for All Equipment Classes and CSLs

Equipment

Class

Mean LCC Savings*,**

2012$

Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M $235.92 $743.00 $1,788.85 $1,493.72 ($1,668.79) NA NA

VOP.RC.L $537.27 $1,516.59 $1,129.51 ($3,692.90) NA NA NA

VOP.SC.M $115.53 $170.78 $227.17 $814.91 $691.27 ($376.52) NA

VCT.RC.M $175.23 $1,864.44 $1,758.73 $1,363.59 $1,108.13 ($2,508.61) NA

VCT.RC.L $1,658.64 $1,357.25 $1,004.72 $797.91 ($3,624.20) NA NA

VCT.SC.M $566.18 $1,363.60 $1,122.14 $894.21 $748.09 $641.05 ($595.52)

VCT.SC.L $3,037.41 $4,186.06 $2,522.67 $1,984.45 $1,587.41 $1,342.84 ($343.16)

VCT.SC.I $1,151.77 $572.05 $608.48 $486.28 $431.88 ($1,591.87) NA

VCS.SC.M $508.27 $278.84 $195.52 $162.88 $144.16 $131.80 ($1,042.03)

VCS.SC.L $924.24 $524.52 $382.36 $329.33 $267.81 $220.83 ($1,274.03)

VCS.SC.I $6.93 $236.77 $171.90 $176.83 $152.69 ($1,818.87) NA

SVO.RC.M $73.77 $551.98 $1,216.77 $1,008.46 ($1,015.16) NA NA

SVO.SC.M $21.89 $324.33 $334.89 $587.90 $491.99 ($201.61) NA

SOC.RC.M $118.36 $226.26 $997.89 $765.75 $494.51 ($982.21) NA

HZO.RC.M ($1,271.24) NA NA NA NA NA NA

HZO.RC.L ($2,134.96) NA NA NA NA NA NA

HZO.SC.M $8.85 $48.60 $28.78 ($821.57) NA NA NA

HZO.SC.L ($473.71) NA NA NA NA NA NA

HCT.SC.M $99.20 $106.59 $117.59 $359.48 $307.26 $253.60 ($293.54)

HCT.SC.L $204.67 $217.19 $790.53 $571.07 $446.02 $368.92 ($354.75)

HCT.SC.I $21.83 $34.69 $42.48 ($811.31) NA NA NA

HCS.SC.M $23.07 $19.18 $16.66 $8.68 ($10.26) ($422.79) NA

HCS.SC.L $68.03 $71.83 $74.69 $80.97 $80.72 ($400.63) NA

PD.SC.M $1,009.53 $933.59 $615.94 $456.97 $368.81 $310.43 ($637.94)

SOC.SC.M $794.63 $646.15 $466.47 $1,241.60 $1,015.62 $739.75 ($735.33)

* NA implies there are no associated CSLs. 

**Values in parentheses are negative values.
8-37

Table 8.4.3 Median LCC Savings for All Equipment Classes and CSLs

Equipment 

Class

Median LCC Savings*,**

2012$

Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M $218.97 $692.78 $1,597.21 $1,386.60 ($1,769.27) NA NA

VOP.RC.L $499.00 $1,414.37 $1,189.56 ($3,852.38) NA NA NA

VOP.SC.M $109.17 $159.78 $203.28 $737.39 $655.36 ($393.19) NA

VCT.RC.M $161.37 $1,698.77 $1,720.74 $1,300.46 $535.18 ($3,164.25) NA

VCT.RC.L $1,548.46 $1,007.99 $590.56 $330.01 ($4,069.46) NA NA

VCT.SC.M $540.88 $1,263.78 $1,144.46 $835.95 $267.37 $142.91 ($1,093.09)

VCT.SC.L $2,930.96 $3,772.61 $2,332.55 $323.16 $238.78 $195.53 ($1,370.50)

VCT.SC.I $1,106.11 $48.55 $292.20 $244.77 $210.18 ($1,814.20) NA

VCS.SC.M $476.34 $63.09 $49.96 $47.04 $46.03 $44.77 ($1,118.86)

VCS.SC.L $870.59 $159.76 $141.53 $129.48 $91.41 $62.97 ($1,411.62)

VCS.SC.I $6.50 $220.74 $199.83 $128.26 $87.82 ($1,865.05) NA

SVO.RC.M $67.77 $502.00 $1,052.23 $882.01 ($1,151.94) NA NA

SVO.SC.M $20.87 $305.70 $342.61 $527.63 $442.48 ($262.18) NA

SOC.RC.M $107.95 $211.62 $895.27 $751.76 $490.36 ($1,061.05) NA

HZO.RC.M ($1,273.12) NA NA NA NA NA NA

HZO.RC.L ($2,143.56) NA NA NA NA NA NA

HZO.SC.M $8.38 $45.07 $25.02 ($830.11) NA NA NA

HZO.SC.L ($475.85) NA NA NA NA NA NA

HCT.SC.M $93.69 $92.35 $96.94 $332.55 $304.32 $260.44 ($294.96)

HCT.SC.L $190.27 $184.31 $737.43 $613.99 $483.70 $31.61 ($630.30)

HCT.SC.I $20.55 $32.43 $36.45 ($824.21) NA NA NA

HCS.SC.M $21.79 $15.60 $10.06 $2.40 ($16.02) ($426.21) NA

HCS.SC.L $64.38 $60.95 $60.13 $66.76 $63.51 ($420.71) NA

PD.SC.M $968.08 $720.68 $431.23 $9.94 $38.80 $9.34 ($903.62)

SOC.SC.M $730.27 $431.69 $267.79 $1,076.79 $916.50 $665.93 ($829.93)

* NA implies there are no associated CSLs.

**Values in parentheses are negative values.

8.4.2 Payback Period Results

Figure 8.4.3 presents the distribution of the PBP results for CSLs 2 to 8 of an example 

equipment class (VCT.SC.L). The numerical values associated with this plot are presented in 

Table 8.4.4. The red marker represents the mean and the blue marker represents the median PBP

for each CSL. The lower edge of the elongated rectangular box represents the 25th percentile, 

which means that 25 percent of the customers would experience a PBP of 0.25 years or less if the 

energy conservation standard were to be set at Level 2, 0.47 years or less if the energy 

conservation standard were to be set at Level 3, and so on. The upper edge of the rectangular box 

represents the 75th percentile. The two ends of the vertical line represent the 5th percentile (lower 

end) and 95th percentile (upper end). Table 8.4.5 and Table 8.4.6 summarize the mean and 

median PBPs, respectively, for all CSLs of all the analyzed equipment classes. Results similar to 

Figure 8.4.3 are presented in appendix 8B for all equipment classes.
8-38

Figure 8.4.3 Mean Payback Period for All CSLs for the Equipment Class VCT.SC.L

Table 8.4.4 Payback Period Distribution Results for VCT.SC.L

CSL 2 3 4 5 6 7 8

Payback period 

years

Mean 0.29 0.56 0.59 0.80 0.82 0.93 3.53 

Median 

(50th Percentile)

0.31 0.58 0.61 0.83 0.85 0.96 3.65 

5th Percentile 0.21 0.39 0.41 0.56 0.57 0.65 2.45 

25th Percentile 0.25 0.47 0.49 0.66 0.68 0.77 2.93 

75th Percentile 0.33 0.64 0.67 0.91 0.93 1.06 4.01 

95th Percentile 0.37 0.70 0.74 1.00 1.03 1.17 4.43 

0.0

1.0

2.0

3.0

4.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Efficiency Level

Mean

Median
8-39

Table 8.4.5 Mean Payback Period for All Equipment Classes and CSLs

Equipment

Class

Mean Payback Period* 

years

Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M 1.67 1.72 3.66 3.79 11.42 NA NA

VOP.RC.L 1.08 1.97 2.16 17.76 NA NA NA

VOP.SC.M 1.51 1.63 2.20 4.17 4.44 11.50 NA

VCT.RC.M 1.20 2.34 2.36 2.54 2.61 12.67 NA

VCT.RC.L 0.95 1.26 1.46 1.59 15.25 NA NA

VCT.SC.M 0.83 1.67 2.13 2.22 2.41 2.45 7.84

VCT.SC.L 0.29 0.56 0.59 0.80 0.82 0.93 3.53

VCT.SC.I 0.75 0.86 1.63 1.75 1.98 13.26 NA

VCS.SC.M 0.72 0.75 0.80 0.96 1.21 1.71 13.73

VCS.SC.L 0.48 0.54 0.57 0.88 0.97 1.12 10.26

VCS.SC.I 0.62 0.78 1.15 2.02 2.35 26.46 NA

SVO.RC.M 1.26 2.55 4.20 4.36 11.23 NA NA

SVO.SC.M 1.21 1.93 2.02 4.34 4.66 10.16 NA

SOC.RC.M 1.21 1.39 3.21 3.44 4.27 11.51 NA

HZO.RC.M 157.02 NA NA NA NA NA NA

HZO.RC.L 81.59 NA NA NA NA NA NA

HZO.SC.M 1.85 2.37 6.25 54.42 NA NA NA

HZO.SC.L 71.79 NA NA NA NA NA NA

HCT.SC.M 0.47 0.68 0.86 2.19 2.37 3.02 12.01

HCT.SC.L 0.34 0.52 0.99 1.03 1.14 1.45 7.06

HCT.SC.I 0.87 2.35 4.21 27.56 NA NA NA

HCS.SC.M 0.48 1.60 2.47 4.18 7.24 33.15 NA

HCS.SC.L 0.25 0.57 0.84 1.33 2.50 14.58 NA

PD.SC.M 0.52 1.08 1.12 1.19 1.95 2.21 7.43

SOC.SC.M 1.01 1.09 1.21 2.28 2.42 2.91 7.21

* NA implies there are no associated CSLs.
8-40

Table 8.4.6 Median Payback Period for All Equipment Classes and CSLs

Equipment 

Class

Median Payback Period*

years

Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M 1.73 1.77 3.77 3.91 11.76 NA NA

VOP.RC.L 1.11 2.03 2.22 18.30 NA NA NA

VOP.SC.M 1.50 1.61 2.17 4.12 4.39 11.37 NA

VCT.RC.M 1.23 2.42 2.43 2.62 2.70 13.09 NA

VCT.RC.L 0.98 1.30 1.51 1.64 15.75 NA NA

VCT.SC.M 0.86 1.73 2.21 2.30 2.49 2.54 8.13

VCT.SC.L 0.31 0.58 0.61 0.83 0.85 0.96 3.65

VCT.SC.I 0.75 0.86 1.63 1.74 1.97 13.21 NA

VCS.SC.M 0.74 0.78 0.82 0.98 1.25 1.75 14.11

VCS.SC.L 0.49 0.55 0.59 0.91 1.00 1.15 10.54

VCS.SC.I 0.64 0.80 1.18 2.07 2.42 27.19 NA

SVO.RC.M 1.31 2.64 4.34 4.50 11.60 NA NA

SVO.SC.M 1.24 1.97 2.06 4.43 4.75 10.36 NA

SOC.RC.M 1.25 1.44 3.31 3.55 4.41 11.88 NA

HZO.RC.M 161.23 NA NA NA NA NA NA

HZO.RC.L 83.78 NA NA NA NA NA NA

HZO.SC.M 1.89 2.42 6.40 55.78 NA NA NA

HZO.SC.L 73.62 NA NA NA NA NA NA

HCT.SC.M 0.48 0.69 0.88 2.24 2.42 3.08 12.26

HCT.SC.L 0.34 0.53 1.00 1.05 1.15 1.47 7.15

HCT.SC.I 0.88 2.39 4.28 27.99 NA NA NA

HCS.SC.M 0.50 1.64 2.54 4.28 7.43 34.05 NA

HCS.SC.L 0.26 0.58 0.86 1.36 2.57 14.98 NA

PD.SC.M 0.53 1.10 1.15 1.22 1.99 2.27 7.61

SOC.SC.M 1.03 1.12 1.24 2.35 2.49 2.99 7.42

* NA implies there are no associated CSLs.

8.4.3 Rebuttable Presumption Payback Period

Sections 325(o)(2)(B)(iii) and 345(e)(1)(A) of EPCA (42 U.S.C. 6295(o)(2)(B)(iii) and 

42 U.S.C. 6316(e)(1)(A)) establish a rebuttable presumption for commercial refrigeration 

equipment. The rebuttable presumption states that a standard is economically justified if the 

Secretary finds that “the additional cost to the consumer of purchasing a product complying with 

an energy conservation standard level will be less than three times the value of the energy 

savings during the first year that the consumer will receive as a result of the standard, as 

calculated under the applicable test procedure.” This rebuttable presumption test is an alternative 

path to establishing economic justification.

To evaluate the rebuttable presumption, DOE estimated the additional cost of purchasing 

more efficient, standards-compliant equipment, and compared this cost to the value of the energy 

saved during the first year of operation of the equipment. DOE interprets that the increased cost 

of purchasing standards-compliant equipment includes the cost of installing the equipment for 

use by the purchaser. DOE calculated the rebuttable presumption payback period (RPBP), or the 

ratio of the value of the increased installed price above the baseline efficiency level to the first 
8-41

year’s energy cost savings. When RPBP is less than 3 years, the rebuttable presumption is 

satisfied; when RPBP is equal to or more than 3 years, the rebuttable presumption is not 

satisfied. Note that this RPBP calculation does not include other components to the annual 

operating cost of the equipment (i.e., maintenance costs and repair costs). The RPBPs calculated 

can thus be different from the PBPs calculated in section 8.4.2. 

DOE calculated the RPBPs for the distribution of installed costs and energy prices 

discussed in sections 8.4.1 and 8.4.2, which are representative of the same seven types of 

businesses and all 50 states. The RPBP was calculated for each CSL within each equipment 

class. 

Table 8.4.7 shows the nationally averaged RPBPs calculated for all equipment classes 

and CSLs. 

Table 8.4.7 Rebuttable Presumption Payback Periods by CSL and Equipment Class

Equipment 

Class

Median Rebuttable Presumption Payback Period*

years

Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M 1.66 1.68 3.39 3.52 10.62 NA NA

VOP.RC.L 1.06 1.99 2.17 17.82 NA NA NA

VOP.SC.M 1.44 1.48 1.92 3.64 3.88 10.09 NA

VCT.RC.M 1.05 2.25 2.28 2.46 2.53 12.27 NA

VCT.RC.L 0.94 1.24 1.44 1.56 15.06 NA NA

VCT.SC.M 0.79 1.62 2.08 2.15 2.34 2.38 7.63

VCT.SC.L 0.32 0.58 0.60 0.82 0.84 0.95 3.61

VCT.SC.I 0.71 0.81 1.53 1.63 1.85 12.41 NA

VCS.SC.M 0.66 0.70 0.74 0.88 1.10 1.56 12.72

VCS.SC.L 0.45 0.51 0.54 0.84 0.92 1.05 9.73

VCS.SC.I 0.58 0.74 1.07 1.90 2.17 25.18 NA

SVO.RC.M 1.24 2.53 3.83 3.97 10.27 NA NA

SVO.SC.M 1.14 1.84 1.86 3.70 3.98 8.71 NA

SOC.RC.M 1.06 1.30 3.09 3.30 4.07 10.99 NA

HZO.RC.M 154.95 NA NA NA NA NA NA

HZO.RC.L 80.51 NA NA NA NA NA NA

HZO.SC.M 1.68 2.10 5.81 52.29 NA NA NA

HZO.SC.L 71.92 NA NA NA NA NA NA

HCT.SC.M 0.45 0.63 0.79 2.02 2.15 2.75 10.98

HCT.SC.L 0.33 0.50 0.96 1.00 1.09 1.39 6.79

HCT.SC.I 0.84 2.08 3.92 26.54 NA NA NA

HCS.SC.M 0.48 1.47 2.17 3.39 6.22 30.01 NA

HCS.SC.L 0.25 0.55 0.79 1.23 2.35 13.99 NA

PD.SC.M 0.49 1.03 1.07 1.13 1.85 2.11 7.09

SOC.SC.M 0.80 0.91 1.00 2.04 2.16 2.59 6.44

* NA implies there are no associated CSLs.

8.5 DETAILED RESULTS

DOE presents detailed results from the LCC analysis in appendix 8B. Plots similar to 

Figure 8.4.2 and Figure 8.4.3 are presented in the appendix for all equipment classes. In addition, 
8-42

summary tables with all the necessary data in one table for each equipment class are presented in 

appendix 8B. Table 8.5.1 is a reproduction of the summary table for an example equipment class, 

VCT.SC.L. This table presents the mean values of installed costs, annual operating costs, LCC, 

LCC savings, and median values of PBP for all the CSLs. It also presents the distribution of 

customer impacts in the form of percentages of customers who experience net cost, no impact, 

and net benefit as compared to the base-case scenario. The average LCC savings and the 

percentage of customers experiencing a net benefit or cost are based on the market shares of the 

efficiency levels. In the base case, not all customers are assumed to be buying equipment at the 

baseline efficiency (Level 1). Some are assumed to be buying at higher efficiency levels. The 

LCC savings is an average of the savings achieved by customers who, in the base case, were 

buying less efficient equipment than the efficiency level examined. Customers with no impact 

were assumed in the base case to be already buying more efficient equipment, so the efficiency 

level in question would not affect them. Summary tables for each of the equipment classes are 

provided in appendix 8B.

Table 8.5.1 Summary of Results of LCC and PBP Analysis for VCT.SC.L Equipment Class 

Efficiency 

Level

Energy 

Consumption 

kWh/yr

Mean Values of Life-Cycle Cost Savings Median 

Payback 

Period 

years

Installed 

Cost 

2012$

Annual 

Operating 

Cost 

2012$

LCC

2012$

Average 

Savings

2012$ 

% of Customers that 

Experience*

Net

Cost

No 

Impact

Net 

Benefit

1 10,618 5,773 14,530 20,303 NA NA NA NA NA

2 7,852 5,861 11,345 17,205 3,037 0 90 10 0.31

3 4,921 6,101 8,222 14,323 4,186 0 76 24 0.58

4 4,853 6,120 8,150 14,270 2,523 0 60 40 0.61

5 4,541 6,271 7,811 14,082 1,984 0 44 56 0.83

6 4,514 6,286 7,790 14,076 1,587 3 29 68 0.85

7 4,411 6,364 7,692 14,056 1,343 7 15 78 0.96

8 4,222 8,077 7,486 15,562 (343) 74 2 24 3.65

* Percentages may not add up to 100 due to rounding.
8-43

REFERENCES 

1. U.S. Department of Energy–Energy Information Administration. Annual Energy Outlook 

2013. 2013. Washington D.C. DOE/EIA-0383(2013).

2. U.S. Department of Energy–Energy Information Administration. Form EIA-826 Database 

Monthly Electric Utility Sales and Revenue Data (EIA-826 Sales and Revenue 

Spreadsheets). (Last accessed June 26, 2013.) <http://www.eia.gov/electricity/data.cfm> 

3. U.S. Census Bureau. Annual Population Estimates 2000 to 2009. Table 1. Annual 

Estimates of the Population for the United States, Regions, States, and Puerto Rico: April 

1, 2010 to July 1, 2011. <http://www.census.gov/popest/states/NST-ann-est.html> Also: 

Annual Estimates of Incorporated Places: April 1, 2010 to July 1, 2011. 

<http://www.census.gov/popest/data/cities/totals/2011/index.html> Last accessed July 20, 

2012. 

4. RS Means Company, Inc. Means Costworks 2013: Facility Maintenance & Repair Cost 

Data. 2013. Kingston, MA. 

5. General Electric Company (GE Lighting). Efficiency, Pure and Simple: LED lighting 

solutions for interiors and outdoors. 2010. East Cleveland, OH.

<www.gelighting.com/eu/resources/literature_library/catalogs/lamp_catalog/downloads/G

E_LED_catalogue2011.pdf > 

6. RS Means Company, Inc. 2013 RS Means Electrical Cost Data. 2013. Kingston, MA. 

7. FMI Research. The Food Retailing Industry Speak 2011. 2011. Food Marketing Institute, 

Arlington, VA. 

8. Harris, R.S. Applying the Capital Asset Pricing Model. UVA-F-1456. Available at SSRN: 

http://ssrn.com/abstract=909893

9. U.S. Federal Reserve. H.15: Selected Interest Rates. (Last accessed February 20, 2013.) 

<www.federalreserve.gov/releases/h15/data.htm.> 

10. Damodaran Online. The Data Page. 2012. S&P 500 data from Annual Returns on Stock, 

T.Bonds and T.Bills: 1928 - Current. (Last accessed February 20, 2013.) 

<http://pages.stern.nyu.edu/~adamodar/New_Home_Page/data.html> 

11. Damodaran Online. The Data Page. Individual Company Information, 2012. (Last accessed 

February 20, 2013.) <http://pages.stern.nyu.edu/~adamodar/New_Home_Page/data.html> 

The data used herein was the individual company data for the U.S. for January 2012. 

12. U.S. Bureau of Economic Analysis. All NIPA Tables, Section 1 – Domestic Product and 

Income, Table 1.1.9, Implicit Price Deflators for Gross Domestic Product. (Last accessed 

February 20, 2013.) <www.bea.gov/national/nipaweb/SelectTable.asp> 
8-44

13. Small Business Administration. Data on loans between $10,000 and $99,000 compared to 

AAA Corporate Rates. <http://www.sba.gov/advocacy/7540/6282> Data compiled June 

20, 2013. 

14. Federal Reserve Bank of St. Louis. Data for 1973-2011 retrieved using the ”FRED” data 

tool. Data for 2012 from the U.S. Federal Reserve H15 data. (Last accessed February 20, 

2012) <http://research.stlouisfed.org/fred2/series/MSLB20/downloaddata?cid=32995> 
APPENDIX 8A. USER INSTRUCTIONS FOR LIFE-CYCLE COST SPREADSHEET

TABLE OF CONTENTS

8A.1 INTRODUCTION ........................................................................................................ 8A-1

8A.2 USER INSTRUCTIONS FOR LIFE-CYCLE COST SPREADSHEET ...................... 8A-1

LIST OF TABLES

Table 8A.2.1 Description of Worksheets in LCC Spreadsheet ................................................ 8A-1

8A-i 
APPENDIX 8A. USER INSTRUCTIONS FOR LIFE-CYCLE COST SPREADSHEET

8A.1 INTRODUCTION

Detailed results of the life-cycle cost (LCC) and payback period (PBP) analyses for 

commercial refrigeration equipment can be examined using a Microsoft Excel spreadsheet 

available on the U.S. Department of Energy’s (DOE’s) Building Technologies (BT) website at 

www.eere.energy.gov/buildings/appliance_standards/commercial_products.html. 

8A.2 USER INSTRUCTIONS FOR LIFE-CYCLE COST SPREADSHEET

The spreadsheet allows the user to perform LCC analyses of any of 25 separate 

equipment classes of commercial refrigeration equipment. To fully execute the spreadsheet 

requires Microsoft Excel and Oracle’s Crystal Ball software, both of which are commercially 

available. 

The spreadsheet posted on the DOE website represents the latest version of the applicable 

model and has been developed and tested with Excel 2010 and with Crystal Ball, Fusion Edition, 

Release 11.1.2.1.000. Table 8A.2.1 describes the worksheets in the LCC spreadsheet. 

Table 8A.2.1 Description of Worksheets in LCC Spreadsheet

Worksheet Description

Summary Contains the input selections and a summary table of energy use, operating 

costs, LCC, and payback.

Ranges Provides the name, location, definition, and purpose of each of the named 

ranges in the LCC model.

CH Lifecycle vs Inst Cost Provides a graph of the LCC versus installed cost by efficiency level for the 

selected equipment class. 

CH Payback vs Inst Cost Provides a graph of the simple PBP in years versus installed cost by 

efficiency level for the selected equipment class.

CB_Outputs Stores Crystal Ball outputs. When Crystal Ball performs a 10,000-run 

analysis, it stores a large amount of data in active memory. At the end of 

the analysis, the spreadsheet captures (via formulas and a Visual Basic for 

Applications macro) statistical data from the Crystal Ball analyses. These 

data are stored in this worksheet.

Eq Distributions Provides distributions for various inputs used by Crystal Ball during the 

Monte Carlo analyses.

OutputUS Provides LCC and PBP output for all of the equipment classes, efficiency 

levels, and building types, but only for average U.S. conditions.

Equipment Parameters Contains calculations of equipment purchase, maintenance and repair costs, 

and energy usage data used in the National Impact Analysis model.

Energy Expenditures Summarizes energy expenditure data for all building types and all 

equipment classes. Data includes the 25 equipment classes currently being 

analyzed.

Engineering Contains the per-unit manufacturer price data and energy use data for a 

standard-sized unit of equipment for each of the 25 equipment classes 

currently being analyzed. Also includes calculation of equipment price 

(including retail markups and the sales tax), the installation price, and the 

repair and maintenance costs per unit.

8A-1 
Table 8A.2.1 (cont) 

Worksheet Description

Markups and Market Calculates the wholesale and retail markup for the selected equipment 

class, including any state and local sales tax. Also calculates weighted 

average sales tax rates and weighted average contractor’s markup.

Contains data on maintenance and repair costs and market channels.

Contractor Markup Index Contains data on contractor markups by state for calculating state-level 

overall wholesale and retail markups.

Building Energy Captures the per-unit energy usage for a standard-sized unit of equipment 

in each equipment class, efficiency level, and state in kilowatt-hours and 

million British thermal units.

AEO2013 Projections Contains projections of future energy prices and price indices from the 

2013 Annual Energy Outlook (AEO2013). Also contains estimates of 

commercial sector energy prices by state, and an index of energy prices by 

business type relative to the commercial average.

Electricity Prices Ratios CBECS Contains data from the 2003 Commercial Building Energy Consumption 

Survey (CBECS) on electricity prices paid by selected business types.

State Energy Price Detail Contains data on prices paid for energy by commercial sector customers 

from the Energy Information Administration (EIA) Form EIA-826 

Database, “Sales and revenue data by state, monthly back to 1990 (Form 

EIA-826),” for 2012, together with calculations to estimate the 2012 prices.

Installation Cost by State Contains multipliers to vary the installation cost by state. Derived from data 

published by RS Means Construction Publishers & Consultants, Kingston, 

MA.

Discount Rate Contains data from which an average discount rate and a distribution of 

discount rates are determined using weighted average cost of capital

derived from data on individual firms published at the Damodaran Online 

website.

Sales Tax Contains data on sales tax rates by state and population data by state. Also 

contains census data on sales of refrigerated and frozen food by state for 

food sales. Calculates population weights for all business types, and 

shipment weights for the four business types with available food shipment 

data (supermarkets, convenience stores and small specialty stores, 

convenience stores with gas pumps, and large multi-line retailers). Contains 

a selection of the weights to be used for each state for calculating weighted 

average national values. Currently uses population weighting given the lack 

of food shipment information for foodservice building types.

GDP Deflator Contains Gross Domestic Product Implicit Price Deflators (GDP Deflators) 

from the AEO2013 database. The primary use of the data is inflating to 

2012 dollars.

Lifetime Contains the estimated average commercial refrigeration equipment 

lifetime in years.

Labels Used as an interface between user inputs and the rest of the worksheets —

do not modify this sheet

Basic instructions for operating the LCC spreadsheets are as follows:

1. Once you have downloaded the LCC file from the DOE BT website, open the file using 

Excel. Select Yes when asked if you want to enable macros. Select No when asked if you 

want to update data. At the bottom of the Excel window, click the tab for the Summary

sheet. Note that if you plan to run the Monte Carlo routine, you must have Crystal Ball 

loaded as an add-in and activated. 

8A-2 
2. Use Excel’s View/Zoom commands at the top menu bar to size the display to your 

monitor. 

3. You can interact with the spreadsheet by clicking choices or entering data using the 

graphical interface on the Summary tab. Select from the inputs listed under the User 

Options heading. 

4. Under the User Defined Inputs heading, select from the buttons and boxes for the 

following: (1) energy price projection; (2) start year; (3) region (state); (4) equipment 

family; (5) equipment operating mode; (6) rating temperature; (7) baseline efficiency 

level; (8) selected efficiency level; (9) building type; (10) analysis type; (11) installation 

options; (12) installation cost projection; and (13) repair cost projection. If you are 

investigating the impacts of reducing first costs (e.g., by a tax credit), enter percentage 

reductions at each efficiency level affected. The default calculation is a single sample 

case, which runs almost instantaneously. You can run all cases for U.S. average 

conditions by clicking All US Cases. You can start a complete Crystal Ball simulation by 

clicking the Monte Carlo button. While there is no macro button, you can run all cases for 

all states by running the macro on the Developer tab titled AllRunner_15. To change 

inputs listed under User Defined Inputs, select the input you wish to change by either 

clicking the appropriate button or selecting the appropriate input from the input box. 

a. Equipment classes are defined as particular combinations of equipment families, 

operating modes, and rating temperatures. Because there are ten potential equipment 

families, two potential operating modes (remote and self contained), and three 

possible temperature ratings provided, there are 60 potential equipment classes that 

could be analyzed. If you select a combination of equipment family, operating mode, 

and temperature ranges that results in a potential equipment class that has not been 

analyzed by DOE (because few or no shipments have been identified), the Annual 

Electricity Bill shown on the Summary tab will be $0 per year and the cells 

containing those data will turn red and will be cross-hatched out. In addition, there 

will be a blue background note on the summary tab that reads “Not an Analyzed 

Equipment Class.” If data exist for the equipment class, the note will read 

“Equipment Class O.K.” If the All US Cases option is run, the last case is not an 

analyzed equipment class, so the note panel will read “Not an Analyzed Equipment 

Class” at the conclusion of the run. 

b. There are up to eight possible efficiency levels. If an equipment class contains fewer 

than eight levels, the extra levels will be shown as #NA in the Total Installed Price 

column on the Summary tab. 

c. A new discount rate or lifetime can also be entered if a value other than the default 

value or default distribution is wanted; however, this will overwrite the existing 

formula. As a result, DOE does not recommend saving the spreadsheet after the code 

is changed. The default discount rate can be changed by going to the Discount Rate 

tab and changing the default values in cells C4 through C10. A different lifetime can 

be selected by going to the Lifetime tab and entering a different value in the white

box at cell D3. 

8A-3 
5. This spreadsheet gives the user three types of calculation methods: 

a. If nothing is selected for a calculation method (Sample Calculation), then all 

calculations are performed for a set of single input values, usually an average. The 

new results are shown on the Summary tab as soon as the new input values are 

entered.

b. Alternatively, if the Monte Carlo button is clicked, the spreadsheet generates a set of 

results from calculations for each equipment family, equipment operating mode, and 

rating temperature (which together define an equipment class). For a number of 

inputs, the Crystal Ball software has custom distributions that it uses to set the level 

of the input. The model runs each of the studied classes in turn, performing 10,000 

model runs for each. At the end of each equipment class run, the model records to the 

CB_Outputs worksheet a large number of outputs that you can then use for further 

analyses. The Monte Carlo button executes a macro written in Visual Basic for 

Applications to loop through all equipment classes and selected efficiency levels. The 

Monte Carlo analysis takes as little as 8 hours on a powerful desktop computer with 

four processors and as long as 15 hours on a new, powerful but compact, laptop 

computer. In short, if you run the Monte Carlo analysis, have a backup computer 

available. 

c. The third alternative, All US Cases, runs each equipment class for each building type 

and efficiency level only at U.S. average prices, markups, etc. This option produces 

the required output file to run the National Energy Savings/National Impact 

Assessment spreadsheet.

8A-4 
APPENDIX 8B. DETAILED LIFE-CYCLE COST AND PAYBACK PERIOD 

ANALYSIS RESULTS

TABLE OF CONTENTS

8B.1 INTRODUCTION .........................................................................................................8B-1

8B.2 LCC RESULTS .............................................................................................................8B-2

8B.2.1 Life-Cycle Cost Results for Vertical Open, Remote Condensing, Medium 

Temperature (VOP.RC.M).................................................................................8B-2

8B.2.2 Life-Cycle Cost Results for Vertical Open, Remote Condensing, Low 

Temperature (VOP.RC.L) ..................................................................................8B-4

8B.2.3 Life-Cycle Cost Results for Vertical Open, Self-Contained, Medium 

Temperature (VOP.SC.M) .................................................................................8B-6

8B.2.4 Life-Cycle Cost Results for Vertical Closed Transparent, Remote Condensing, 

Medium Temperature (VCT.RC.M) ..................................................................8B-8

8B.2.5 Life-Cycle Cost Results for Vertical Closed Transparent, Remote Condensing, 

Low Temperature (VCT.RC.L) .......................................................................8B-10

8B.2.6 Life-Cycle Cost Results for Vertical Closed Transparent, Self-Contained, 

Medium Temperature (VCT.SC.M) ................................................................8B-12

8B.2.7 Life-Cycle Cost Results for Vertical Closed Transparent, Self-Contained, Low 

Temperature (VCT.SC.L) ................................................................................8B-14

8B.2.8 Life-Cycle Cost Results for Vertical Closed Transparent, Self-Contained, IceCream Temperature (VCT.SC.I)......................................................................8B-15

8B.2.9 Life-Cycle Cost Results for Vertical Closed Solid, Self-Contained, Medium 

Temperature (VCS.SC.M) ...............................................................................8B-17

8B.2.10 Life-Cycle Cost Results for Vertical Closed Solid, Self-Contained, Low 

Temperature (VCS.SC.L) ................................................................................8B-19

8B.2.11 Life-Cycle Cost Results for Vertical Closed Solid, Self-Contained, IceCream Temperature (VCS.SC.I) ......................................................................8B-21

8B.2.12 Life-Cycle Cost Results for Semi-Vertical Open, Remote Condensing, 

Medium Temperature (SVO.RC.M) ................................................................8B-23

8B.2.13 Life-Cycle Cost Results for Semi-Vertical Open, Self-Contained, Medium 

Temperature (SVO.SC.M) ...............................................................................8B-25

8B.2.14 Life-Cycle Cost Results for Service Over Counter, Remote Condensing, 

Medium Temperature (SOC.RC.M) ................................................................8B-27

8B.2.15 Life-Cycle Cost Results for Service Over Counter, Self-Contained, Medium 

Temperature (SOC.SC.M) ...............................................................................8B-29

8B.2.16 Life-Cycle Cost Results for Horizontal Open, Remote Condensing, Medium 

Temperature (HZO.RC.M) ..............................................................................8B-31

8B.2.17 Life-Cycle Cost Results for Horizontal Open, Remote Condensing, Low 

Temperature (HZO.RC.L) ...............................................................................8B-33

8B.2.18 Life-Cycle Cost Results for Horizontal Open, Self-Contained, Medium 

Temperature (HZO.SC.M) ...............................................................................8B-35

8B.2.19 Life-Cycle Cost Results for Horizontal Open, Self-Contained, Low 

Temperature (HZO.SC.L) ................................................................................8B-37

8B-i 
8B.2.20 Life-Cycle Cost Results for Horizontal Closed Transparent, Self-Contained, 

Medium Temperature (HCT.SC.M) ................................................................8B-39

8B.2.21 Life-Cycle Cost Results for Horizontal Closed Transparent, Self-Contained, 

Low Temperature (HCT.SC.L) ........................................................................8B-41

8B.2.22 Life-Cycle Cost Results for Horizontal Closed Transparent, Self-Contained, 

Ice-Cream Temperature (HCT.SC.I) ...............................................................8B-43

8B.2.23 Life-Cycle Cost Results for Horizontal Closed Solid, Self-Contained, 

Medium Temperature (HCS.SC.M) .................................................................8B-45

8B.2.24 Life-Cycle Cost Results for Horizontal Closed Solid, Self-Contained, Low 

Temperature (HCS.SC.L) ................................................................................8B-47

8B.2.25 Life-Cycle Cost Results for Pull-Down, Self-Contained, Medium 

Temperature (PD.SC.M) ..................................................................................8B-49

LIST OF TABLES

Table 8B.2.1 LCC Results for Vertical Open, Remote Condensing, Medium Temperature 

(VOP.RC.M) ......................................................................................................8B-2

Table 8B.2.2 LCC Results for Vertical Open, Remote Condensing, Low Temperature 

(VOP.RC.L) .......................................................................................................8B-4

Table 8B.2.3 LCC Results for Vertical Open, Self-Contained, Medium Temperature 

(VOP.SC.M) ......................................................................................................8B-6

Table 8B.2.4 LCC Results for Vertical Closed Transparent, Remote Condensing, Medium 

Temperature (VCT.RC.M).................................................................................8B-8

Table 8B.2.5 LCC Results for Vertical Closed Transparent, Remote Condensing, Low 

Temperature (VCT.RC.L) ................................................................................8B-10

Table 8B.2.6 LCC Results for Vertical Closed Transparent, Self-Contained, Medium 

Temperature (VCT.SC.M) ...............................................................................8B-12

Table 8B.2.7 LCC Results for Vertical Closed Transparent, Self-Contained, Low 

Temperature (VCT.SC.L) ................................................................................8B-14

Table 8B.2.8 LCC Results for Vertical Closed Transparent, Self-Contained, Ice-Cream 

Temperature (VCT.SC.I) .................................................................................8B-15

Table 8B.2.9 LCC Results for Vertical Closed Solid, Self-Contained, Medium Temperature 

(VCS.SC.M) .....................................................................................................8B-17

Table 8B.2.10 LCC Results for Vertical Closed Solid, Self-Contained, Low Temperature 

(VCS.SC.L) ......................................................................................................8B-19

Table 8B.2.11 LCC Results for Vertical Closed Solid, Self-Contained, Ice-Cream 

Temperature (VCS.SC.I) .................................................................................8B-21

Table 8B.2.12 LCC Results for Semi-Vertical Open, Remote Condensing, Medium 

Temperature (SVO.RC.M)...............................................................................8B-23

Table 8B.2.13 LCC Results for Semi-Vertical Open, Self-Contained, Medium Temperature 

(SVO.SC.M) ....................................................................................................8B-25

Table 8B.2.14 LCC Results for Service Over Counter, Remote Condensing, Medium 

Temperature (SOC.RC.M) ...............................................................................8B-27

Table 8B.2.15 LCC Results for Service Over Counter, Self-Contained, Medium Temperature 

(SOC.SC.M) .....................................................................................................8B-29

8B-ii
Table 8B.2.16 LCC Results for Horizontal Open, Remote Condensing, Medium Temperature 

(HZO.RC.M) ....................................................................................................8B-31

Table 8B.2.17 LCC Results for Horizontal Open, Remote Condensing, Low Temperature 

(HZO.RC.L) .....................................................................................................8B-33

Table 8B.2.18 LCC Results for Horizontal Open, Self-Contained, Medium Temperature 

(HZO.SC.M) ....................................................................................................8B-35

Table 8B.2.19 LCC Results for Horizontal Open, Self-Contained, Low Temperature 

(HZO.SC.L) .....................................................................................................8B-37

Table 8B.2.20 LCC Results for Horizontal Closed Transparent, Self-Contained, Medium 

Temperature (HCT.SC.M) ...............................................................................8B-39

Table 8B.2.21 LCC Results for Horizontal Closed Transparent, Self-Contained, Low 

Temperature (HCT.SC.L) ................................................................................8B-41

Table 8B.2.22 LCC Results for Horizontal Closed Transparent, Self-Contained, Ice-Cream 

Temperature (HCT.SC.I) .................................................................................8B-43

Table 8B.2.23 LCC Results for Horizontal Closed Solid, Self-Contained, Medium 

Temperature (HCS.SC.M) ...............................................................................8B-45

Table 8B.2.24 LCC Results for Horizontal Closed Solid, Self-Contained, Low Temperature 

(HCS.SC.L) ......................................................................................................8B-47

Table 8B.2.25 LCC Results for Pull-Down, Self-Contained, Medium Temperature 

(PD.SC.M) .......................................................................................................8B-49

LIST OF FIGURES

Figure 8B.2.1 LCC Savings Statistical Results for Vertical Open, Remote Condensing, 

Medium Temperature (VOP.RC.M) ..................................................................8B-2

Figure 8B.2.2 PBP Statistical Results for Vertical Open, Remote Condensing, Medium 

Temperature (VOP.RC.M).................................................................................8B-3

Figure 8B.2.3 LCC Savings Statistical Results for Vertical Open, Remote Condensing, Low 

Temperature (VOP.RC.L) ..................................................................................8B-4

Figure 8B.2.4 PBP Statistical Results for Vertical Open, Remote Condensing, Low 

Temperature (VOP.RC.L) ..................................................................................8B-5

Figure 8B.2.5 LCC Savings Statistical Results for Vertical Open, Self-Contained, Medium 

Temperature (VOP.SC.M) .................................................................................8B-6

Figure 8B.2.6 PBP Statistical Results for Vertical Open, Self-Contained, Medium 

Temperature (VOP.SC.M) .................................................................................8B-7

Figure 8B.2.7 LCC Savings Statistical Results for Vertical Closed Transparent, Remote 

Condensing, Medium Temperature (VCT.RC.M) .............................................8B-8

Figure 8B.2.8 PBP Statistical Results for Vertical Closed Transparent, Remote Condensing, 

Medium Temperature (VCT.RC.M) ..................................................................8B-9

Figure 8B.2.9 LCC Savings Statistical Results for Vertical Closed Transparent, Remote 

Condensing, Low Temperature (VCT.RC.L) ..................................................8B-10

Figure 8B.2.10 PBP Statistical Results for Vertical Closed Transparent, Remote Condensing, 

Low Temperature (VCT.RC.L) .......................................................................8B-11

Figure 8B.2.11 LCC Savings Statistical Results for Vertical Closed Transparent, SelfContained, Medium Temperature (VCT.SC.M) ..............................................8B-12

8B-iii
Figure 8B.2.12 PBP Statistical Results for Vertical Closed Transparent, Self-Contained, 

Medium Temperature (VCT.SC.M) ................................................................8B-13

Figure 8B.2.13 LCC Savings Statistical Results for Vertical Closed Transparent, SelfContained, Low Temperature (VCT.SC.L) .....................................................8B-14

Figure 8B.2.14 PBP Statistical Results for Vertical Closed Transparent, Self-Contained, Low 

Temperature (VCT.SC.L) ................................................................................8B-15

Figure 8B.2.15 LCC Savings Statistical Results for Vertical Closed Transparent, SelfContained, Ice-Cream Temperature (VCT.SC.I) .............................................8B-16

Figure 8B.2.16 PBP Statistical Results for Vertical Closed Transparent, Self-Contained, IceCream Temperature (VCT.SC.I)......................................................................8B-16

Figure 8B.2.17 LCC Savings Statistical Results for Vertical Closed Solid, Self-Contained, 

Medium Temperature (VCS.SC.M) .................................................................8B-17

Figure 8B.2.18 PBP Statistical Results for Vertical Closed Solid, Self-Contained, Medium 

Temperature (VCS.SC.M) ...............................................................................8B-18

Figure 8B.2.19 LCC Savings Statistical Results for Vertical Closed Solid, Self-Contained, 

Low Temperature (VCS.SC.L) ........................................................................8B-19

Figure 8B.2.20 PBP Statistical Results for Vertical Closed Solid, Self-Contained, Low 

Temperature (VCS.SC.L) ................................................................................8B-20

Figure 8B.2.21 LCC Savings Statistical Results for Vertical Closed Solid, Self-Contained, 

Ice-Cream Temperature (VCS.SC.I) ................................................................8B-21

Figure 8B.2.22 PBP Statistical Results for Vertical Closed Solid, Self-Contained, Ice-Cream 

Temperature (VCS.SC.I) .................................................................................8B-22

Figure 8B.2.23 LCC Savings Statistical Results for Semi-Vertical Open, Remote 

Condensing, Medium Temperature (SVO.RC.M) ...........................................8B-23

Figure 8B.2.24 PBP Statistical Results for Semi-Vertical Open, Remote Condensing, 

Medium Temperature (SVO.RC.M) ................................................................8B-24

Figure 8B.2.25 LCC Savings Statistical Results for Semi-Vertical Open, Self-Contained, 

Medium Temperature (SVO.SC.M) ................................................................8B-25

Figure 8B.2.26 PBP Statistical Results for Semi-Vertical Open, Self-Contained, Medium 

Temperature (SVO.SC.M) ...............................................................................8B-26

Figure 8B.2.27 LCC Savings Statistical Results for Service Over Counter, Remote 

Condensing, Medium Temperature (SOC.RC.M) ...........................................8B-27

Figure 8B.2.28 PBP Statistical Results for Service Over Counter, Remote Condensing, 

Medium Temperature (SOC.RC.M) ................................................................8B-28

Figure 8B.2.29 LCC Savings Statistical Results for Service Over Counter, Self-Contained, 

Medium Temperature (SOC.SC.M) .................................................................8B-29

Figure 8B.2.30 PBP Statistical Results for Service Over Counter, Self-Contained, Medium 

Temperature (SOC.SC.M) ...............................................................................8B-30

Figure 8B.2.31 LCC Savings Statistical Results for Horizontal Open, Remote Condensing, 

Medium Temperature (HZO.RC.M) ................................................................8B-31

Figure 8B.2.32 PBP Statistical Results for Horizontal Open, Remote Condensing, Medium 

Temperature (HZO.RC.M) ..............................................................................8B-32

Figure 8B.2.33 LCC Savings Statistical Results for Horizontal Open, Remote Condensing, 

Low Temperature (HZO.RC.L) .......................................................................8B-33

Figure 8B.2.34 PBP Statistical Results for Horizontal Open, Remote Condensing, Low 

Temperature (HZO.RC.L) ...............................................................................8B-34

8B-iv
Figure 8B.2.35 LCC Savings Statistical Results for Horizontal Open, Self-Contained, 

Medium Temperature (HZO.SC.M) ................................................................8B-35

Figure 8B.2.36 PBP Statistical Results for Horizontal Open, Self-Contained, Medium 

Temperature (HZO.SC.M) ...............................................................................8B-36

Figure 8B.2.37 LCC Savings Statistical Results for Horizontal Open, Self-Contained, Low 

Temperature (HZO.SC.L) ................................................................................8B-37

Figure 8B.2.38 PBP Statistical Results for Horizontal Open, Self-Contained, Low 

Temperature (HZO.SC.L) ................................................................................8B-38

Figure 8B.2.39 LCC Savings Statistical Results for Horizontal Closed Transparent, SelfContained, Medium Temperature (HCT.SC.M) ..............................................8B-39

Figure 8B.2.40 PBP Statistical Results for Horizontal Closed Transparent, Self-Contained, 

Medium Temperature (HCT.SC.M) ................................................................8B-40

Figure 8B.2.41 LCC Savings Statistical Results for Horizontal Closed Transparent, SelfContained, Low Temperature (HCT.SC.L) .....................................................8B-41

Figure 8B.2.42 PBP Statistical Results for Horizontal Closed Transparent, Self-Contained, 

Low Temperature (HCT.SC.L) ........................................................................8B-42

Figure 8B.2.43 LCC Savings Statistical Results for Horizontal Closed Transparent, SelfContained, Ice-Cream Temperature (HCT.SC.I) .............................................8B-43

Figure 8B.2.44 PBP Statistical Results for Horizontal Closed Transparent, Self-Contained, 

Ice-Cream Temperature (HCT.SC.I) ...............................................................8B-44

Figure 8B.2.45 LCC Savings Statistical Results for Horizontal Closed Solid, Self-Contained, 

Medium Temperature (HCS.SC.M) .................................................................8B-45

Figure 8B.2.46 PBP Statistical Results for Horizontal Closed Solid, Self-Contained, Medium 

Temperature (HCS.SC.M) ...............................................................................8B-46

Figure 8B.2.47 LCC Savings Statistical Results for Horizontal Closed Solid, Self-Contained, 

Low Temperature (HCS.SC.L) ........................................................................8B-47

Figure 8B.2.48 PBP Statistical Results for Horizontal Closed Solid, Self-Contained, Low 

Temperature (HCS.SC.L) ................................................................................8B-48

Figure 8B.2.49 LCC Savings Statistical Results for Pull-Down, Self-Contained, Medium 

Temperature (PD.SC.M) ..................................................................................8B-49

Figure 8B.2.50 PBP Statistical Results for Pull-Down, Self-Contained, Medium Temperature 

(PD.SC.M) .......................................................................................................8B-50

8B-v 
APPENDIX 8B. DETAILED LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS 

RESULTS

8B.1 INTRODUCTION

This appendix contains detailed output from the life-cycle cost (LCC) analysis for 

commercial refrigeration equipment using the LCC spreadsheet. LCC and payback periods 

(PBPs) are presented for each of the 25 product classes at each efficiency level. See chapter 8 of 

the technical support document for an explanation of the LCC spreadsheet. 

LCC savings output obtained from the LCC analysis are in the form of distributions. LCC 

savings distributions were generated by performing 10,000 separate simulations using the LCC 

spreadsheet, and allowing the spreadsheet to select values for numerous inputs given probability 

distributions for each input. Given the results of the LCC model simulations for each equipment 

type, the U.S. Department of Energy (DOE) calculated summary statistics—average values for 

the LCC, product installation costs, and operating costs for a distribution of customers who: (1) 

receive benefits in the form of lower LCC results; (2) are not affected by the standards; or 

(3) experience a cost in the form of increased LCC from equipment ownership. Results of the 

LCC and accompanying PBP analyses are shown in the tables in this appendix. 

Also included in this appendix are two graphical presentations for each of the LCC and 

PBP results. One of these presentations plots the LCC savings distribution for all equipment 

classes analyzed. The figures illustrate the mean and median values on the plot with the help of 

red and blue markers, respectively. Additionally, the mean and median values are surrounded by 

rectangular boxes used to represent the 25th and 75th percentile values. The lower edge of the 

elongated rectangle represents the 25th percentile, which means that 25 percent of the customers 

will experience LCC savings below the value represented by the bottom of the rectangle if the 

standard were set at the level in question. The upper edge of the elongated rectangle represents 

the 75th percentile. Finally, each of the rectangles includes two “tails,” or two vertical black 

lines, extending downward to represent the 5th percentile (lower end) and upward to represent 

the 95th percentile (upper end). 

The remainder of this appendix presents the tabular and graphical results for each of the 

25 equipment classes analyzed for the commercial refrigeration equipment rulemaking.

8B-1 
8B.2 LCC RESULTS

8B.2.1 Life-Cycle Cost Results for Vertical Open, Remote Condensing, Medium 

Temperature (VOP.RC.M)

Table 8B.2.1 LCC Results for Vertical Open, Remote Condensing, Medium Temperature 

(VOP.RC.M)

Figure 8B.2.1 LCC Savings Statistical Results for Vertical Open, Remote Condensing, 

Medium Temperature (VOP.RC.M)

1 17,438 9,437 20,911 30,348 NA NA NA NA NA 

2 17,095 9,490 20,618 30,108 236 0 76 24 1.73 

3 16,180 9,633 19,849 29,482 743 0 52 48 1.77 

4 13,033 10,823 17,364 28,187 1,789 0 28 72 3.77 

5 12,962 10,898 17,303 28,201 1,494 11 15 74 3.91 

6 12,798 14,006 17,162 31,168 (1,669) 90 2 8 11.76 

7 12,798 NA NA NA NA NA NA NA NA 

8 12,798 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

No Impact

(%)

Net

Benefit

(%)

Efficiency 

Level (kWh/yr)

Net

Cost

(%)

-4000

-3000

-2000

-1000

0

1000

2000

3000

4000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-2 
Figure 8B.2.2 PBP Statistical Results for Vertical Open, Remote Condensing, Medium 

Temperature (VOP.RC.M)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-3 
8B.2.2 Life-Cycle Cost Results for Vertical Open, Remote Condensing, Low Temperature 

(VOP.RC.L)

Table 8B.2.2 LCC Results for Vertical Open, Remote Condensing, Low Temperature 

(VOP.RC.L)

Figure 8B.2.3 LCC Savings Statistical Results for Vertical Open, Remote Condensing, Low 

Temperature (VOP.RC.L)

1 39,503 10,027 39,803 49,830 NA NA NA NA NA 

2 38,770 10,099 39,184 49,282 537 0 74 26 1.11 

3 36,877 10,511 37,520 48,031 1,517 0 48 52 2.03 

4 36,685 10,594 37,356 47,950 1,130 0 25 75 2.22 

5 36,088 15,667 36,847 52,513 (3,693) 98 2 0 18.30 

6 36,088 NA NA NA NA NA NA NA NA 

7 36,088 NA NA NA NA NA NA NA NA 

8 36,088 NA NA NA NA NA NA NA NA 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

 Payback 

Period, 

Median 

(Years) 

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-6000

-5000

-4000

-3000

-2000

-1000

0

1000

2000

3000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-4 
Figure 8B.2.4 PBP Statistical Results for Vertical Open, Remote Condensing, Low 

Temperature (VOP.RC.L)

0.0

5.0

10.0

15.0

20.0

25.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-5 
8B.2.3 Life-Cycle Cost Results for Vertical Open, Self-Contained, Medium Temperature 

(VOP.SC.M)

Table 8B.2.3 LCC Results for Vertical Open, Self-Contained, Medium Temperature 

(VOP.SC.M) 

Figure 8B.2.5 LCC Savings Statistical Results for Vertical Open, Self-Contained, Medium 

Temperature (VOP.SC.M)

1 11,201 4,611 15,740 20,351 NA NA NA NA NA 

2 11,085 4,629 15,605 20,234 116 0 81 19 1.50 

3 10,960 4,650 15,471 20,120 171 0 62 38 1.61 

4 10,804 4,693 15,314 20,008 227 0 43 57 2.17 

5 9,747 5,183 14,180 19,364 815 0 25 75 4.12 

6 9,718 5,234 14,147 19,381 691 11 14 75 4.39 

7 9,660 6,293 14,079 20,373 (377) 77 3 20 11.37 

8 9,660 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

-1500

-1000

-500

0

500

1000

1500

2000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-6 
Figure 8B.2.6 PBP Statistical Results for Vertical Open, Self-Contained, Medium 

Temperature (VOP.SC.M)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-7 
8B.2.4 Life-Cycle Cost Results for Vertical Closed Transparent, Remote Condensing, 

Medium Temperature (VCT.RC.M)

Table 8B.2.4 LCC Results for Vertical Closed Transparent, Remote Condensing, Medium 

Temperature (VCT.RC.M) 

Figure 8B.2.7 LCC Savings Statistical Results for Vertical Closed Transparent, Remote 

Condensing, Medium Temperature (VCT.RC.M)

1 5,931 12,045 12,003 24,048 NA NA NA NA NA 

2 5,679 12,070 11,800 23,870 175 0 81 19 1.23 

3 2,955 12,669 9,411 22,081 1,864 0 62 38 2.42 

4 2,285 12,819 8,809 21,629 1,759 0 46 54 2.43 

5 2,195 12,900 8,729 21,629 1,364 9 31 60 2.62 

6 2,177 12,929 8,715 21,644 1,108 26 16 57 2.70 

7 2,005 16,537 8,560 25,097 (2,509) 94 2 4 13.09 

8 2,005 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-4000

-3000

-2000

-1000

0

1000

2000

3000

4000

5000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-8 
Figure 8B.2.8 PBP Statistical Results for Vertical Closed Transparent, Remote 

Condensing, Medium Temperature (VCT.RC.M)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-9 
8B.2.5 Life-Cycle Cost Results for Vertical Closed Transparent, Remote Condensing, 

Low Temperature (VCT.RC.L)

Table 8B.2.5 LCC Results for Vertical Closed Transparent, Remote Condensing, Low 

Temperature (VCT.RC.L) 

Figure 8B.2.9 LCC Savings Statistical Results for Vertical Closed Transparent, Remote 

Condensing, Low Temperature (VCT.RC.L)

1 14,239 13,423 20,148 33,571 NA NA NA NA NA 

2 12,144 13,606 18,284 31,890 1,659 0 81 19 0.98 

3 11,362 13,756 17,581 31,337 1,357 0 60 40 1.30 

4 11,161 13,836 17,401 31,237 1,005 0 40 60 1.51 

5 11,056 13,887 17,311 31,198 798 0 21 79 1.64 

6 10,531 18,626 16,840 35,466 (3,624) 97 2 1 15.75 

7 10,531 NA NA NA NA NA NA NA NA 

8 10,531 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-5000

-4000

-3000

-2000

-1000

0

1000

2000

3000

4000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-10
Figure 8B.2.10 PBP Statistical Results for Vertical Closed Transparent, Remote 

Condensing, Low Temperature (VCT.RC.L)

0.0

5.0

10.0

15.0

20.0

25.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-11
8B.2.6 Life-Cycle Cost Results for Vertical Closed Transparent, Self-Contained, Medium 

Temperature (VCT.SC.M)

Table 8B.2.6 LCC Results for Vertical Closed Transparent, Self-Contained, Medium 

Temperature (VCT.SC.M) 

Figure 8B.2.11 LCC Savings Statistical Results for Vertical Closed Transparent, SelfContained, Medium Temperature (VCT.SC.M)

1 3,365 4,546 5,884 10,430 NA NA NA NA NA 

2 2,758 4,594 5,261 9,855 566 0 83 17 0.86 

3 1,488 4,849 3,916 8,764 1,364 0 66 34 1.73 

4 1,182 4,999 3,583 8,582 1,122 0 51 49 2.21 

5 1,141 5,024 3,552 8,576 894 4 38 58 2.30 

6 1,088 5,077 3,495 8,571 748 11 25 64 2.49 

7 1,082 5,088 3,489 8,578 641 27 13 60 2.54 

8 979 6,362 3,377 9,739 (596) 74 2 24 8.13 

 Payback 

Period, 

Median 

(Years) 

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

-1500

-1000

-500

0

500

1000

1500

2000

2500

3000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-12
Figure 8B.2.12 PBP Statistical Results for Vertical Closed Transparent, Self-Contained, 

Medium Temperature (VCT.SC.M)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-13
8B.2.7 Life-Cycle Cost Results for Vertical Closed Transparent, Self-Contained, Low 

Temperature (VCT.SC.L)

Table 8B.2.7 LCC Results for Vertical Closed Transparent, Self-Contained, Low 

Temperature (VCT.SC.L) 

Figure 8B.2.13 LCC Savings Statistical Results for Vertical Closed Transparent, SelfContained, Low Temperature (VCT.SC.L) 

1 10,618 5,773 14,530 20,303 NA NA NA NA NA 

2 7,852 5,861 11,345 17,205 3,037 0 90 10 0.31 

3 4,921 6,101 8,222 14,323 4,186 0 76 24 0.58 

4 4,853 6,120 8,150 14,270 2,523 0 60 40 0.61 

5 4,541 6,271 7,811 14,082 1,984 0 44 56 0.83 

6 4,514 6,286 7,790 14,076 1,587 3 29 68 0.85 

7 4,411 6,364 7,692 14,056 1,343 7 15 78 0.96 

8 4,222 8,077 7,486 15,562 (343) 74 2 24 3.65 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-4000

-2000

0

2000

4000

6000

8000

10000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-14
Figure 8B.2.14 PBP Statistical Results for Vertical Closed Transparent, Self-Contained, 

Low Temperature (VCT.SC.L)

8B.2.8 Life-Cycle Cost Results for Vertical Closed Transparent, Self-Contained, IceCream Temperature (VCT.SC.I)

Table 8B.2.8 LCC Results for Vertical Closed Transparent, Self-Contained, Ice-Cream 

Temperature (VCT.SC.I) 

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

1 7,559 6,280 11,456 17,736 NA NA NA NA NA 

2 6,414 6,368 10,200 16,567 1,152 0 84 16 0.75 

3 6,370 6,383 10,160 16,543 572 0 65 35 0.86 

4 6,024 6,533 9,778 16,311 608 0 48 52 1.63 

5 5,972 6,558 9,733 16,292 486 1 32 68 1.74 

6 5,891 6,612 9,644 16,256 432 1 16 83 1.97 

7 5,609 8,883 9,332 18,215 (1,592) 95 1 3 13.21 

8 5,609 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

8B-15
Figure 8B.2.15 LCC Savings Statistical Results for Vertical Closed Transparent, SelfContained, Ice-Cream Temperature (VCT.SC.I)

Figure 8B.2.16 PBP Statistical Results for Vertical Closed Transparent, Self-Contained, 

Ice-Cream Temperature (VCT.SC.I)

-2500

-2000

-1500

-1000

-500

0

500

1000

1500

2000

2500

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-16
8B.2.9 Life-Cycle Cost Results for Vertical Closed Solid, Self-Contained, Medium 

Temperature (VCS.SC.M)

Table 8B.2.9 LCC Results for Vertical Closed Solid, Self-Contained, Medium Temperature 

(VCS.SC.M) 

Figure 8B.2.17 LCC Savings Statistical Results for Vertical Closed Solid, Self-Contained, 

Medium Temperature (VCS.SC.M)

1 1,625 3,332 2,733 6,065 NA NA NA NA NA 

2 923 3,379 2,171 5,550 508 0 87 13 0.74 

3 863 3,386 2,122 5,508 279 0 72 28 0.78 

4 840 3,390 2,104 5,494 196 0 57 43 0.82 

5 793 3,406 2,070 5,476 163 0 42 58 0.98 

6 735 3,431 2,031 5,462 144 1 27 72 1.25 

7 659 3,484 1,967 5,451 132 7 13 80 1.75 

8 507 4,771 1,837 6,608 (1,042) 99 1 0 14.11 

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

-1500

-1000

-500

0

500

1000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-17
Figure 8B.2.18 PBP Statistical Results for Vertical Closed Solid, Self-Contained, Medium 

Temperature (VCS.SC.M)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-18
8B.2.10 Life-Cycle Cost Results for Vertical Closed Solid, Self-Contained, Low 

Temperature (VCS.SC.L)

Table 8B.2.10 LCC Results for Vertical Closed Solid, Self-Contained, Low Temperature 

(VCS.SC.L) 

Figure 8B.2.19 LCC Savings Statistical Results for Vertical Closed Solid, Self-Contained, 

Low Temperature (VCS.SC.L)

1 4,014 3,603 4,947 8,549 NA NA NA NA NA 

2 2,808 3,658 3,957 7,615 924 0 88 12 0.49 

3 2,649 3,673 3,829 7,501 525 0 73 27 0.55 

4 2,582 3,682 3,772 7,454 382 0 58 43 0.59 

5 2,463 3,735 3,671 7,405 329 0 42 58 0.91 

6 2,432 3,751 3,651 7,402 268 5 28 68 1.00 

7 2,394 3,776 3,630 7,405 221 20 14 66 1.15 

8 2,084 5,505 3,366 8,871 (1,274) 97 1 2 10.54 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-2000

-1500

-1000

-500

0

500

1000

1500

2000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-19
Figure 8B.2.20 PBP Statistical Results for Vertical Closed Solid, Self-Contained, Low 

Temperature (VCS.SC.L)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-20
8B.2.11 Life-Cycle Cost Results for Vertical Closed Solid, Self-Contained, Ice-Cream 

Temperature (VCS.SC.I)

Table 8B.2.11 LCC Results for Vertical Closed Solid, Self-Contained, Ice-Cream 

Temperature (VCS.SC.I) 

Figure 8B.2.21 LCC Savings Statistical Results for Vertical Closed Solid, Self-Contained, 

Ice-Cream Temperature (VCS.SC.I)

1 6,979 4,124 7,790 11,913 NA NA NA NA NA 

2 6,969 4,124 7,782 11,906 7 0 83 17 0.64 

3 6,657 4,148 7,526 11,674 237 0 67 33 0.80 

4 6,612 4,164 7,494 11,658 172 0 49 51 1.18 

5 6,492 4,218 7,392 11,610 177 0 32 68 2.07 

6 6,438 4,243 7,357 11,600 153 3 16 81 2.42 

7 6,034 6,535 7,013 13,548 (1,819) 99 1 0 27.19 

8 6,034 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-2500

-2000

-1500

-1000

-500

0

500

1000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-21
Figure 8B.2.22 PBP Statistical Results for Vertical Closed Solid, Self-Contained, Ice-Cream 

Temperature (VCS.SC.I)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-22
8B.2.12 Life-Cycle Cost Results for Semi-Vertical Open, Remote Condensing, Medium 

Temperature (SVO.RC.M)

Table 8B.2.12 LCC Results for Semi-Vertical Open, Remote Condensing, Medium

Temperature (SVO.RC.M) 

Figure 8B.2.23 LCC Savings Statistical Results for Semi-Vertical Open, Remote 

Condensing, Medium Temperature (SVO.RC.M)

1 13,279 8,329 16,907 25,236 NA NA NA NA NA 

2 13,179 8,341 16,821 25,161 74 0 75 25 1.31 

3 12,355 8,547 16,098 24,645 552 0 51 49 2.64 

4 10,114 9,455 14,347 23,802 1,217 0 29 71 4.34 

5 10,065 9,517 14,304 23,821 1,008 13 16 72 4.50 

6 9,949 11,511 14,202 25,713 (1,015) 85 3 12 11.60 

7 9,949 NA NA NA NA NA NA NA NA 

8 9,949 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

No Impact

(%)

Net

Benefit

(%)

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

-2500

-2000

-1500

-1000

-500

0

500

1000

1500

2000

2500

3000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-23
Figure 8B.2.24 PBP Statistical Results for Semi-Vertical Open, Remote Condensing, 

Medium Temperature (SVO.RC.M)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-24
8B.2.13 Life-Cycle Cost Results for Semi-Vertical Open, Self-Contained, Medium 

Temperature (SVO.SC.M)

Table 8B.2.13 LCC Results for Semi-Vertical Open, Self-Contained, Medium Temperature 

(SVO.SC.M) 

Figure 8B.2.25 LCC Savings Statistical Results for Semi-Vertical Open, Self-Contained, 

Medium Temperature (SVO.SC.M)

1 9,758 3,813 13,153 16,966 NA NA NA NA NA 

2 9,736 3,816 13,128 16,944 22 0 81 19 1.24 

3 9,396 3,885 12,744 16,629 324 0 61 39 1.97 

4 9,255 3,914 12,600 16,514 335 0 43 57 2.06 

5 8,501 4,314 11,866 16,180 588 0 25 75 4.43 

6 8,481 4,359 11,843 16,202 492 12 14 75 4.75 

7 8,439 5,049 11,796 16,844 (202) 69 4 27 10.36 

8 8,439 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-1000

-500

0

500

1000

1500

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-25
Figure 8B.2.26 PBP Statistical Results for Semi-Vertical Open, Self-Contained, Medium 

Temperature (SVO.SC.M)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-26
8B.2.14 Life-Cycle Cost Results for Service Over Counter, Remote Condensing, Medium 

Temperature (SOC.RC.M)

Table 8B.2.14 LCC Results for Service Over Counter, Remote Condensing, Medium 

Temperature (SOC.RC.M) 

Figure 8B.2.27 LCC Savings Statistical Results for Service Over Counter, Remote 

Condensing, Medium Temperature (SOC.RC.M)

1 9,534 12,748 15,245 27,993 NA NA NA NA NA 

2 9,353 12,766 15,106 27,872 118 0 82 18 1.25 

3 9,115 12,799 14,906 27,704 226 0 64 36 1.44 

4 7,455 13,343 13,511 26,854 998 0 47 53 3.31 

5 7,413 13,398 13,475 26,873 766 14 32 54 3.55 

6 7,356 13,570 13,443 27,012 495 29 18 53 4.41 

7 7,274 15,050 13,372 28,423 (982) 89 5 6 11.88 

8 7,274 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-2000

-1500

-1000

-500

0

500

1000

1500

2000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-27
Figure 8B.2.28 PBP Statistical Results for Service Over Counter, Remote Condensing, 

Medium Temperature (SOC.RC.M)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-28
8B.2.15 Life-Cycle Cost Results for Service Over Counter, Self-Contained, Medium 

Temperature (SOC.SC.M)

Table 8B.2.15 LCC Results for Service Over Counter, Self-Contained, Medium 

Temperature (SOC.SC.M) 

Figure 8B.2.29 LCC Savings Statistical Results for Service Over Counter, Self-Contained, 

Medium Temperature (SOC.SC.M)

1 11,534 12,161 15,575 27,736 NA NA NA NA NA 

2 10,235 12,266 14,666 26,932 795 0 85 15 1.03 

3 9,869 12,314 14,364 26,678 646 0 70 30 1.12 

4 9,783 12,339 14,301 26,640 466 0 55 45 1.24 

5 8,039 12,883 12,863 25,747 1,242 0 40 60 2.35 

6 7,986 12,939 12,819 25,757 1,016 11 28 62 2.49 

7 7,920 13,110 12,777 25,887 740 25 16 60 2.99 

8 7,814 14,591 12,687 27,277 (735) 80 5 16 7.42 

No Impact

(%)

Benefit

(%)

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

ota

Discounted

Operating

Cost

CC,

All 

Customers

(2012$)

ected

Customers'

Average

Savings

% of Customers that Experience

Cost

(%)

-2000

-1500

-1000

-500

0

500

1000

1500

2000

2500

3000

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-29
Figure 8B.2.30 PBP Statistical Results for Service Over Counter, Self-Contained, Medium 

Temperature (SOC.SC.M)

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-30
8B.2.16 Life-Cycle Cost Results for Horizontal Open, Remote Condensing, Medium 

Temperature (HZO.RC.M)

Table 8B.2.16 LCC Results for Horizontal Open, Remote Condensing, Medium 

Temperature (HZO.RC.M) 

Figure 8B.2.31 LCC Savings Statistical Results for Horizontal Open, Remote Condensing, 

Medium Temperature (HZO.RC.M)

1 5,267 8,056 8,916 16,972 NA NA NA NA NA 

2 5,173 9,406 8,837 18,243 (1,271) 78 22 0 161.23 

3 5,173 NA NA NA NA NA NA NA NA 

4 5,173 NA NA NA NA NA NA NA NA 

5 5,173 NA NA NA NA NA NA NA NA 

6 5,173 NA NA NA NA NA NA NA NA 

7 5,173 NA NA NA NA NA NA NA NA 

8 5,173 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

-1320

-1300

-1280

-1260

-1240

-1220

-1200

-1180

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-31
Figure 8B.2.32 PBP Statistical Results for Horizontal Open, Remote Condensing, Medium 

Temperature (HZO.RC.M)

0.0

50.0

100.0

150.0

200.0

250.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-32
8B.2.17 Life-Cycle Cost Results for Horizontal Open, Remote Condensing, Low 

Temperature (HZO.RC.L)

Table 8B.2.17 LCC Results for Horizontal Open, Remote Condensing, Low Temperature 

(HZO.RC.L) 

Figure 8B.2.33 LCC Savings Statistical Results for Horizontal Open, Remote Condensing, 

Low Temperature (HZO.RC.L)

1 12,082 8,895 14,989 23,884 NA NA NA NA NA 

2 11,759 11,301 14,718 26,019 (2,135) 86 14 0 83.78 

3 11,759 NA NA NA NA NA NA NA NA 

4 11,759 NA NA NA NA NA NA NA NA 

5 11,759 NA NA NA NA NA NA NA NA 

6 11,759 NA NA NA NA NA NA NA NA 

7 11,759 NA NA NA NA NA NA NA NA 

8 11,759 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-2300

-2250

-2200

-2150

-2100

-2050

-2000

-1950

-1900

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-33
Figure 8B.2.34 PBP Statistical Results for Horizontal Open, Remote Condensing, Low 

Temperature (HZO.RC.L)

0.0

20.0

40.0

60.0

80.0

100.0

120.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-34
8B.2.18 Life-Cycle Cost Results for Horizontal Open, Self-Contained, Medium 

Temperature (HZO.SC.M)

Table 8B.2.18 LCC Results for Horizontal Open, Self-Contained, Medium Temperature 

(HZO.SC.M) 

Figure 8B.2.35 LCC Savings Statistical Results for Horizontal Open, Self-Contained, 

Medium Temperature (HZO.SC.M)

1 5,398 2,342 7,066 9,408 NA NA NA NA NA 

2 5,388 2,343 7,055 9,399 9 0 75 25 1.89 

3 5,330 2,356 6,999 9,354 49 0 49 51 2.42 

4 5,289 2,405 6,954 9,358 29 19 24 57 6.40 

5 5,206 3,340 6,862 10,202 (822) 98 2 0 55.78 

6 5,206 NA NA NA NA NA NA NA NA 

7 5,206 NA NA NA NA NA NA NA NA 

8 5,206 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-1000

-800

-600

-400

-200

0

200

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-35
Figure 8B.2.36 PBP Statistical Results for Horizontal Open, Self-Contained, Medium 

Temperature (HZO.SC.M)

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-36
8B.2.19 Life-Cycle Cost Results for Horizontal Open, Self-Contained, Low Temperature 

(HZO.SC.L) 

Table 8B.2.19 LCC Results for Horizontal Open, Self-Contained, Low Temperature 

(HZO.SC.L) 

Figure 8B.2.37 LCC Savings Statistical Results for Horizontal Open, Self-Contained, Low 

Temperature (HZO.SC.L)

1 10,994 3,691 13,891 17,582 NA NA NA NA NA 

2 10,916 4,251 13,804 18,056 (474) 72 28 0 73.62 

3 10,916 NA NA NA NA NA NA NA NA 

4 10,916 NA NA NA NA NA NA NA NA 

5 10,916 NA NA NA NA NA NA NA NA 

6 10,916 NA NA NA NA NA NA NA NA 

7 10,916 NA NA NA NA NA NA NA NA 

8 10,916 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

-520

-500

-480

-460

-440

-420

-400

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-37
Figure 8B.2.38 PBP Statistical Results for Horizontal Open, Self-Contained, Low 

Temperature (HZO.SC.L) 

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-38
8B.2.20 Life-Cycle Cost Results for Horizontal Closed Transparent, Self-Contained, 

Medium Temperature (HCT.SC.M)

Table 8B.2.20 LCC Results for Horizontal Closed Transparent, Self-Contained, Medium 

Temperature (HCT.SC.M) 

Figure 8B.2.39 LCC Savings Statistical Results for Horizontal Closed Transparent, SelfContained, Medium Temperature (HCT.SC.M)

1 831 2,047 1,854 3,900 NA NA NA NA NA 

2 741 2,051 1,749 3,800 99 0 85 15 0.48 

3 683 2,057 1,685 3,742 107 0 70 30 0.69 

4 632 2,064 1,631 3,695 118 0 54 46 0.88 

5 305 2,161 1,263 3,423 359 0 38 62 2.24 

6 275 2,175 1,236 3,411 307 0 25 75 2.42 

7 244 2,220 1,200 3,420 254 18 12 70 3.08 

8 181 2,812 1,127 3,939 (294) 89 1 10 12.26 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-800

-600

-400

-200

0

200

400

600

800

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-39
Figure 8B.2.40 PBP Statistical Results for Horizontal Closed Transparent, Self-Contained, 

Medium Temperature (HCT.SC.M)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-40
8B.2.21 Life-Cycle Cost Results for Horizontal Closed Transparent, Self-Contained, Low 

Temperature (HCT.SC.L)

Table 8B.2.21 LCC Results for Horizontal Closed Transparent, Self-Contained, Low 

Temperature (HCT.SC.L) 

Figure 8B.2.41 LCC Savings Statistical Results for Horizontal Closed Transparent, SelfContained, Low Temperature (HCT.SC.L) 

1 1,887 2,221 2,683 4,904 NA NA NA NA NA 

2 1,649 2,229 2,467 4,696 205 0 88 12 0.34 

3 1,499 2,240 2,336 4,576 217 0 75 26 0.53 

4 667 2,337 1,589 3,926 791 0 61 39 1.00 

5 647 2,344 1,574 3,918 571 0 45 55 1.05 

6 622 2,358 1,558 3,917 446 11 29 60 1.15 

7 572 2,403 1,513 3,916 369 23 14 63 1.47 

8 432 3,204 1,385 4,590 (355) 76 1 23 7.15 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-1000

-500

0

500

1000

1500

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-41
Figure 8B.2.42 PBP Statistical Results for Horizontal Closed Transparent, Self-Contained, 

Low Temperature (HCT.SC.L)

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-42
8B.2.22 Life-Cycle Cost Results for Horizontal Closed Transparent, Self-Contained, IceCream Temperature (HCT.SC.I)

Table 8B.2.22 LCC Results for Horizontal Closed Transparent, Self-Contained, Ice-Cream 

Temperature (HCT.SC.I) 

Figure 8B.2.43 LCC Savings Statistical Results for Horizontal Closed Transparent, SelfContained, Ice-Cream Temperature (HCT.SC.I)

1 1,203 2,329 2,016 4,344 NA NA NA NA NA 

2 1,174 2,331 1,991 4,322 22 0 74 26 0.88 

3 1,121 2,346 1,953 4,299 35 0 49 51 2.39 

4 1,045 2,391 1,889 4,279 42 2 23 75 4.28 

5 776 3,461 1,663 5,124 (811) 99 1 0 27.99 

6 776 NA NA NA NA NA NA NA NA 

7 776 NA NA NA NA NA NA NA NA 

8 776 NA NA NA NA NA NA NA NA 

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

-1000

-800

-600

-400

-200

0

200

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-43
Figure 8B.2.44 PBP Statistical Results for Horizontal Closed Transparent, Self-Contained, 

Ice-Cream Temperature (HCT.SC.I)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-44
8B.2.23 Life-Cycle Cost Results for Horizontal Closed Solid, Self-Contained, Medium 

Temperature (HCS.SC.M)

Table 8B.2.23 LCC Results for Horizontal Closed Solid, Self-Contained, Medium 

Temperature (HCS.SC.M) 

Figure 8B.2.45 LCC Savings Statistical Results for Horizontal Closed Solid, SelfContained, Medium Temperature (HCS.SC.M)

1 267 1,950 997 2,947 NA NA NA NA NA 

2 238 1,951 972 2,924 23 0 83 17 0.50 

3 220 1,957 959 2,916 19 0 65 35 1.64 

4 203 1,964 948 2,912 17 1 48 51 2.54 

5 183 1,979 937 2,916 9 29 31 40 4.28 

6 153 2,022 911 2,933 (10) 66 15 19 7.43 

7 90 2,490 857 3,347 (423) 98 2 0 34.05 

8 90 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-500

-400

-300

-200

-100

0

100

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-45
Figure 8B.2.46 PBP Statistical Results for Horizontal Closed Solid, Self-Contained, 

Medium Temperature (HCS.SC.M)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-46
8B.2.24 Life-Cycle Cost Results for Horizontal Closed Solid, Self-Contained, Low 

Temperature (HCS.SC.L)

Table 8B.2.24 LCC Results for Horizontal Closed Solid, Self-Contained, Low Temperature 

(HCS.SC.L) 

Figure 8B.2.47 LCC Savings Statistical Results for Horizontal Closed Solid, SelfContained, Low Temperature (HCS.SC.L) 

1 770 1,973 1,433 3,406 NA NA NA NA NA 

2 686 1,976 1,362 3,338 68 0 84 16 0.26 

3 632 1,981 1,318 3,299 72 0 67 33 0.58 

4 588 1,988 1,284 3,272 75 0 50 50 0.86 

5 534 2,003 1,244 3,246 81 0 33 67 1.36 

6 464 2,046 1,184 3,231 81 2 16 82 2.57 

7 271 2,681 1,020 3,700 (401) 98 2 0 14.98 

8 271 NA NA NA NA NA NA NA NA 

 Payback 

Period, 

Median 

(Years) 

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

-600

-500

-400

-300

-200

-100

0

100

200

300

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-47
Figure 8B.2.48 PBP Statistical Results for Horizontal Closed Solid, Self-Contained, Low 

Temperature (HCS.SC.L)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-48
8B.2.25 Life-Cycle Cost Results for Pull-Down, Self-Contained, Medium Temperature 

(PD.SC.M)

Table 8B.2.25 LCC Results for Pull-Down, Self-Contained, Medium Temperature 

(PD.SC.M) 

Figure 8B.2.49 LCC Savings Statistical Results for Pull-Down, Self-Contained, Medium 

Temperature (PD.SC.M)

1 2,523 2,949 3,998 6,946 NA NA NA NA NA 

2 1,423 3,002 2,926 5,927 1,010 0 86 14 0.53 

3 815 3,121 2,322 5,444 934 0 69 31 1.10 

4 804 3,129 2,315 5,444 616 10 53 37 1.15 

5 790 3,142 2,307 5,449 457 27 37 36 1.22 

6 641 3,292 2,156 5,448 369 27 22 51 1.99 

7 597 3,348 2,112 5,460 310 41 11 48 2.27 

8 517 4,347 2,031 6,379 (638) 86 1 13 7.61 

 Payback 

Period, 

Median 

(Years) 

Net

Cost

(%)

No Impact

(%)

Net

Benefit

(%)

Efficiency 

Level 

Number

Efficiency 

Level (kWh/yr)

Life-Cycle Cost, All Customers Life-Cycle Cost Savings

Installed

Cost

(2012$)

Total

Discounted

Operating

Cost

(2012$)

LCC,

All 

Customers

(2012$)

Affected

Customers'

Average

Savings

(2012$)

% of Customers that Experience

-1500

-1000

-500

0

500

1000

1500

2000

2500

1 2 3 4 5 6 7 8

Life-Cycle Cost Savings ($)

Median Mean Efficiency Level

`

8B-49
Figure 8B.2.50 PBP Statistical Results for Pull-Down, Self-Contained, Medium 

Temperature (PD.SC.M)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

1 2 3 4 5 6 7 8

Payback Period (Years)

Median Mean Efficiency Level

`

8B-50
APPENDIX 8C. UNCERTAINTY AND VARIABILITY IN LIFE-CYCLE COST 

ANALYSIS

TABLE OF CONTENTS

8C.1 INTRODUCTION .........................................................................................................8C-1

8C.2 UNCERTAINTY ...........................................................................................................8C-1

8C.3 VARIABILITY ..............................................................................................................8C-1

8C.4 APPROACHES TO UNCERTAINTY AND VARIABILITY .....................................8C-1

8C.5 PROBABILITY ANALYSIS AND THE USE OF CRYSTAL BALL® ......................8C-2

8C-i
APPENDIX 8C. UNCERTAINTY AND VARIABILITY IN LCC ANALYSIS

8C.1 INTRODUCTION

The U.S. Department of Energy’s (DOE’s) approach to analysis of an energy-efficiency 

standard also includes analyzing the range of potential impacts of higher efficiency equipment on 

consumers. DOE uses the consumer life-cycle cost (LCC) as the key metric for this analysis and 

examines the variability of the LCC of higher efficiency equipment by varying a wide range of 

input assumptions. To perform the calculation, analysts must first: 1) specify the equation or 

model that will be used; 2) define the quantities in the equation; and 3) provide numerical values 

for each quantity. In the simplest case, the equation is unambiguous (contains all relevant 

quantities and no others), each quantity has a single numerical value, and the calculation results 

in a single value. However, in most cases, the model and/or the numerical values for each

quantity in the model are not completely known (i.e., there is uncertainty), and/or the numerical 

values for each quantity in the model depend upon other conditions (i.e., there is variability).

Thorough analysis involves accounting for uncertainty and variability. While the simplest 

analysis involves a single numerical value for each quantity in a calculation, arguments can arise

about what the appropriate value is for each quantity. Explicit analysis of uncertainty and 

variability is intended to provide more complete information to the decision-making process for 

establishing standards for commercial refrigeration equipment.

8C.2 UNCERTAINTY

When making observations of past events or speculating about the future, imperfect 

knowledge is the rule rather than the exception. For example, the lifetime of a refrigerator used 

in a restaurant is not available at the time of purchase, but rather estimated based upon available 

historic information. When estimating numerical values expected for quantities at some future 

date, the exact outcome is rarely known in advance. 

8C.3 VARIABILITY

Variability means that different applications or situations produce different numerical 

values when calculating a quantity. Specifying an exact value for a quantity may be difficult

because the value depends on another parameter. For example, the electricity price rate faced by 

a customer is dependent on the state where the customer’s business is located and the type of 

business. 

8C.4 APPROACHES TO UNCERTAINTY AND VARIABILITY 

This section describes two approaches to uncertainty and variability: scenario analysis 

and probability analysis.

Scenario analysis uses a single numerical value for each quantity in a calculation, then

changes one (or more) of the numerical values and repeats the calculation. A number of

calculations are done, which provides some indication of the extent to which the result depends 

on the assumptions. The advantages of scenario analysis are that each calculation is simple, a 

range of estimates is used, and crossover points can be identified. (An example of a crossover 

8C-1
point is the energy price rate at which the consumer achieves savings in operating expense that 

more than compensate for the increased purchase expense.) The disadvantage of scenario 

analysis is that there is no information about the likelihood of each scenario. 

Probability analysis considers the probabilities within a range of values. For quantities 

with variability (e.g., electricity price rates paid by different users), surveys can be used to 

generate a frequency distribution of numerical values (e.g., the number of commercial buildings

with electricity rates at particular levels) to estimate the probability of each value. For quantities 

with uncertainty, statistical or subjective measures can be used to provide probabilities (e.g.,

manufacturing cost to improve energy efficiency to some level may be estimated to be 

$100 ± $20). The major disadvantage of the probability approach is that it requires more 

information, namely information about the shapes and magnitudes of the variability and 

uncertainty of each quantity. The advantage of the probability approach is that it provides greater 

information about the outcome of the calculations (i.e., it provides the probability that the 

outcome will be in a particular range). Scenario and probability analysis provide some indication 

of the robustness of the policy given the uncertainties and variability. A policy is robust when the 

impacts are acceptable over a wide range of possible conditions. 

8C.5 PROBABILITY ANALYSIS AND THE USE OF CRYSTAL BALL®

To quantify the uncertainty and variability that exist in inputs to the engineering, LCC, 

and payback period analyses, DOE used Microsoft Excel spreadsheets combined with Crystal 

Ball, a commercially available add-in, to conduct probability analyses. The probability analysis 

is carried out in the form of Monte Carlo simulations. Simulation refers to any analytical method 

meant to imitate a real-life system, especially when other analyses are mathematically complex 

or difficult to reproduce. Without the aid of simulation, a spreadsheet model will only reveal a 

single outcome, generally the most likely or average scenario. 

Monte Carlo simulations are carried out by performing the LCC analysis multiple times 

(10,000 times for each equipment class for this rulemaking). Each simulation has one particular 

set of inputs. The inputs are chosen from their respective probability distributions. For example, 

there are 50 states in the United States and the probability of choosing one state for a simulation 

is based on the population of the state. The higher the population of a state, the higher the 

probability of choosing that state for a particular simulation. Similarly, the equipment lifetime is 

specified by Weibull distribution curves with mean equipment lifetime of 10 or 15 years. Crystal 

Ball chooses the equipment lifetime for any particular simulation based on the Weibull 

probability distribution curve. Thus, each Monte Carlo simulation is a random combination of 

input values, with each input value chosen according to its respective probability distribution. 

That is, during a single trial, Crystal Ball selects a value from the defined possibilities (the range 

and shape of the probability distribution) for each uncertain variable and then recalculates the 

spreadsheet.

8C-2
8D-i 

APPENDIX 8D. ESTIMATION OF POTENTIAL EQUIPMENT PRICE TRENDS FOR 

COMMERCIAL REFRIGERATION EQUIPMENT 

TABLE OF CONTENTS

8D.1 INTRODUCTION ........................................................................................................ 8D-1

8D.2 DATA EVALUATION AND ANALYSIS .................................................................. 8D-2

8D.3 REFERENCES ............................................................................................................. 8D-5

LIST OF FIGURES

Figure 8D.1.1 PPI Data for Commercial Refrigeration Equipment .......................................... 8D-2

Figure 8D.2.1 Projected Annual Shipments for Commercial Refrigeration Equipment .......... 8D-3

Figure 8D.2.2 Model Fit for Commercial Refrigeration Equipment ........................................ 8D-4
8D-1 

APPENDIX 8D. ESTIMATION OF POTENTIAL EQUIPMENT PRICE TRENDS FOR 

COMMERCIAL REFRIGERATION EQUIPMENT

8D.1 INTRODUCTION

In developing the proposed standards, the U.S. Department of Energy (DOE) assumes

that the manufacturer costs and retail prices of products meeting various efficiency levels remain 

fixed, in real terms, after 2011 (the year for which the engineering analysis estimated costs) and

throughout the period of the analysis. In its notice of data availability (NODA) published on 

February 22, 2011, DOE stated that it may consider improving regulatory analysis by addressing 

equipment price trends. 76 FR 9696. Consistent with the NODA, DOE examined historical 

producer price indices for commercial refrigeration equipment. 

DOE stated in the NODA that 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. 76 FR 9696 (Feb. 22, 2011). Economic literature and 

historical data suggest that the real costs of these products may in fact trend downward over time 

according to “learning” or “experience” curves, or alternatively that the price trends for certain 

sectors of the U.S. economy may be different than the price trends for the economy as a whole. 

A draft paper, “Using the Experience Curve Approach for Appliance Price Forecasting,” 

available

at http://www1.eere.energy.gov/buildings/appliance_standards/pdfs/experience_curve_appliance

_price_forecasting_3-16-11.pdf, summarizes the data and literature currently available to DOE 

that is relevant to price forecasts for selected appliances and equipment. 

The extensive literature on the “learning” or “experience” curve phenomenon is 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 manufactured 

product. To explain the empirical relationship, DOE would use the theory of technology learning 

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

Eq. 8D.1 

Where:

a = an initial price (or cost), 

b = a positive constant known as the learning rate parameter, 

X = cumulative production, and 

Y = 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: 
8D-2 

LR = 1 – 2-b 

Eq. 8D.2 

In typical learning curve formulations, the learning rate parameter is derived using two 

historical data series: cumulative production and price (or cost). 

DOE examined historical prices using the Bureau of Labor Statistics’ (BLS) Producer 

Price Index (PPI) and gross domestic product (GDP) deflator, available from the Bureau of 

Economic Analysis (BEA). The PPI data for commercial refrigerators and related equipment is 

available for 1978–2012 and is used to represent aggregate commercial refrigeration equipment 

prices. Figure 8D.1.1 shows the PPI data series used. 

Figure 8D.1.1 PPI Data for Commercial Refrigeration Equipment

Inflation-adjusted price indices were calculated by dividing the fitted PPI series by the 

GDP deflator for the same years. The GDP deflator was used as opposed to the Consumer Price 

Index because nearly all commercial refrigeration equipment is shipped to commercial customers 

and use of the GDP deflator was consistent with energy price forecast assumptions by Energy 

Information Administration (EIA).

8D.2 DATA EVALUATION AND ANALYSIS

Figure 8D.1.1 shows an apparent price trend in commercial refrigeration equipment that 

is trending slightly upward from 1978 to 2012, but shows a decrease in the real PPI during two 

significant periods of time: 1982 to 1988 and1992 to 2004. Based on these price trends, DOE 

expects that the PPI is likely to resume a downward trend in the future. 
8D-3 

To perform an experience curve fit, DOE assembled a time-series of annual shipments for 

1950 to 2009 for commercial refrigeration equipment (for calculating cumulative production)

based on shipments data for 2009. 

Projected shipments after 2009 were obtained from the base-case projections made for 

the national impact analysis (see chapter 10 of this technical support document). Projected 

annual shipments are depicted in Figure 8D.2.1. 

Figure 8D.2.1 Projected Annual Shipments for Commercial Refrigeration Equipment

To estimate potential product price trends, DOE performed a least-squares power-law fit 

on the commercial refrigeration equipment price index versus cumulative shipments. The form 

of the fitting equation is: 

P(X) = PoX-b

Eq. 8D.3 

Where:

b = the learning rate parameter, and 

Po = the price or cost of the first unit of production. 

Both b and Po are obtained by fitting the model to the data. 

DOE notes that the cumulative shipments on the right-hand side of the equation can 

depend on price, so there is an issue with simultaneity where the independent variable is not truly 
8D-4 

independent. DOE’s use of a simple least-squares fit is equivalent to an assumption of no 

significant first price elasticity effects in the cumulative shipments variable. 

After modeling the data to the Eq. 8D.3, DOE estimated the learning rate (defined as the 

fractional reduction in price expected from each doubling of cumulative production) as 3 percent. 

With cumulative shipments through 2046 projected to reach 215.3 million linear feet 

(compared with 92.4 million linear feet in 2010), the modeled trend predicts a drop of 

3.3 percent in real price compared to the 2012 prices in the economy as a whole. Figure 8D.2.2

shows the model fit for the projected values for the period after 2009. 

Figure 8D.2.2 Model Fit for Commercial Refrigeration Equipment
8D-5 

8D.3 REFERENCES

1. Weiss, M., Junginger, H.M., Patel, M.K., Blok, K., (2010). A Review of Experience Curve 

Analyses for Energy Demand Technologies. Technological Forecasting & Social Change. 

77:411-428.
CHAPTER 9. SHIPMENTS ANALYSIS

TABLE OF CONTENTS

9.1 INTRODUCTION .............................................................................................................. 9-1

9.2 SHIPMENTS MODEL EQUATIONS ............................................................................... 9-2

9.2.1 Shipments Model .................................................................................................... 9-2

9.2.2 Stock Events............................................................................................................ 9-3

9.2.2.1 Replacing Equipment ............................................................................... 9-3

9.2.2.2 New Equipment ....................................................................................... 9-3

9.3 DATA INPUTS .................................................................................................................. 9-4

9.3.1 Historical Shipments ............................................................................................... 9-4

9.3.2 Historical Shipments and Projected Building Stock Additions .............................. 9-6

9.3.3 Commercial Floor Space and Market Saturation .................................................... 9-8

9.3.3.1 Floor Space – New Construction ............................................................. 9-8

9.3.3.2 Market Shipments .................................................................................... 9-9

9.3.4 Equipment Utility.................................................................................................... 9-9

9.3.5 Equipment Price ...................................................................................................... 9-9

9.3.5.1 Operating Costs ...................................................................................... 9-10

9.3.5.2 Discounted Costs ................................................................................... 9-10

9.4 RESULTS ......................................................................................................................... 9-10

REFERENCES .......................................................................................................................... 9-12

LIST OF TABLES

Table 9.3.1 Estimated Distribution of 2009 Linear Feet of Commercial Refrigeration Equipment 

Shipments Among New vs. Replacement Equipment ......................................... 9-6

Table 9.3.2 AEO2013 Forecast of New Food Sales and Foodservice Square Footage ............... 9-7

Table 9.3.3 Equipment Linear Dimensions Assumed for Shipments Analysis ........................... 9-7

Table 9.3.4 Percent of Shipped Linear Feet of Commercial Refrigeration Equipment ............... 9-8

Table 9.4.1 Forecasted Shipments of New and Replacement Commercial Refrigeration 

Equipment by Building Type, 2017−2046 (Base Case) .................................... 9-10

Table 9.4.2 Forecasted Shipments for Commercial Refrigeration Equipment, 2017−2046, by 

Equipment Type (Base Case)............................................................................. 9-11

LIST OF FIGURES

Figure 9.1.1 Flow Chart Showing Inputs to the Shipments Model ............................................. 9-1

9-i 
CHAPTER 9. SHIPMENTS ANALYSIS

9.1 INTRODUCTION

Commercial refrigeration equipment shipment numbers are key inputs to the national 

energy savings analysis, net present value calculations, and the manufacturer impacts analysis.

This chapter describes the U.S. Department of Energy’s (DOE’s) methodology for estimating 

commercial refrigeration equipment shipments and annual equipment stocks for 2009 through 

2046. 

The Shipments Model results are driven primarily by historical shipments data for the 

25 primary classes of commercial refrigeration equipment under consideration. Figure 9.1.1

outlines the structure of the Shipments Model. 

Figure 9.1.1 Flow Chart Showing Inputs to the Shipments Model

The model assumes that, in each year, a given unit that is part of the existing commercial 

refrigeration equipment stock either ages by one year or breaks. Broken equipment is replaced.

In addition, new equipment can be installed into new commercial floor space, and old equipment 

can be removed through demolitions (not shown in the diagram). 

Section 9.2 presents the mathematical formulation of the model, section 9.3 describes the

data input to the model, and section 9.4 presents the results for the base-case level scenario and 

discusses the development of higher standard scenarios. 

Initial Shipments to 

New Construction

Shipments 

Estimates Based on 

Historic Shipments 

Initial Replacement 

Shipments

Shipments to New 

Construction

NEMS Foodservices 

Bldg. Construction 

Forecast

Initial CRE Stock

Total Shipments by 

Product Class

Percent Shipments 

by Product Class 

(2005)

Replacement 

Shipments

Estimated Lifetime 

of CRE Stock

CRE Stock by 

Product Class

9-1 
9.2 SHIPMENTS MODEL EQUATIONS

The Shipments Model is a description of commercial refrigeration equipment stock flows 

as a function of year and age. While 25 equipment classes are examined in the model, it is 

assumed that there is no coupling between the shipments of the various equipment classes, so the 

equations are applicable to each equipment class independently. 

DOE formulated the Shipments Model equations as updates of the distribution of stock in 

year t to year t+1 as a function of age a. DOE first converted the equipment units to linear feet of 

refrigerator/freezer space using national statistics on sales of equipment and representative

equipment size (linear feet). DOE used this calculation of existing stock, and the average age of 

the equipment, as a basis for calculating replacement sales. Then, DOE subtracted replacement 

sales from historical total sales statistics to calculate new sales of commercial refrigeration 

equipment. DOE forecasted new sales as a function of new construction of retail food sales and 

foodservice space. Sales of new and replacement equipment were recorded by the year sold, and 

each annual vintage was depreciated over the estimated life of the equipment. Sales in each year 

were allocated to the 25 equipment classes in proportion to their relative historical sales. 

9.2.1 Shipments Model

DOE uses two commercial refrigeration equipment stock categories. The category U0(t,a) 

is the stock of existing units. All units are assumed to have had normal repairs that do not affect 

the lifetime of the equipment. 

As discussed in chapter 8 of this technical support document (TSD), the average lifetime 

of a unit is estimated to be 10 years for remote condensing display cases in large grocery stores 

and supermarkets and all self-contained equipment, and 15 years for remote condensing display 

cases in small grocery stores such as convenience stores. Also, the average age of the initial 

existing stock of equipment is assumed to be 5 years, based on the 10-year lifetime of a unit of 

equipment and annual replacements going back 10 years. The total stock of age a in a given year 

t is represented by

U(t,a) = U0 (t,a) 

Eq. 9.1 

Where:

U(t,a) = total stock of age a in a given year t, 

U0(t,a) = stock of existing units, 

a = age of stock (year), and 

t = year.

The shipments of new stock in a given year are Uship(t). By definition, the age of the 

equipment is zero in the year that it is shipped, so that Uship(t) = U(t,0). 

9-2 
9.2.2 Stock Events

In the transition from year t to year t+1, two things could happen to the stock of 

commercial refrigeration equipment: (1) existing equipment could break or be removed during a 

store renovation and be replaced; or (2) the stock could simply age by 1 year.

In the model, early replacements (i.e., existing equipment that is replaced before it is 

broken) are not considered, and all broken equipment is assumed to be replaced. The following 

sections present the equations used to represent each possible event. 

9.2.2.1 Replacing Equipment

DOE determines the probability that commercial refrigeration equipment of age a from 

stock U0 will break or will be replaced using a Weibull survival distribution function 

PB0(a) = W(8,10.62) for large food sales and for foodservice applications. This results in a 

10-year average lifetime, a minimum lifetime of about 7 years, and a maximum lifetime of about 

13 years, consistent with industry comments. The function PB0(a) = W(8,16) was used for small 

food sales outlets (i.e., convenience stores with and without gas stations). This results in an 

average lifetime of 15 years, with a minimum of about 9 years and a maximum of about 

20 years, again consistent with industry comments. Similarly, the probability that equipment of 

age a from stock U1 will break is given by the same function PB1(a). These probabilities do not 

depend on the model year t. DOE defines the quantities of replaced equipment as 

UB(t,a) = PB0(a) × U0(t,a) 

Eq. 9.2

Where:

UB(t,a) = quantity of replacement units of age a in year t, 

PB0(a) = probability that stock of existing units of age a will break or will be replaced, 

U0(t,a) = stock of existing units of age a in year t, 

a = age of stock (years), and 

t = year.

9.2.2.2 New Equipment

The model assumes that new commercial refrigeration equipment is purchased to replace 

the existing units at the end of their lifetime, and for service in new buildings. Available 

information suggests that the purchase of new equipment for use in new buildings is driven by 

the rate of construction of food sales and foodservice floor space. 

By definition, for each type of building: 

EFS(t+1) = EFS(t) + NFS(t) – DFS(t) 

Eq. 9.3

9-3 
Where:

EFS(t) = the square footage of existing floor space in year t, 

NFS(t) = the square footage of new floor space added in year t, and

DFS(t) = the square footage demolished in year t. 

The linear footage of units installed in new buildings is 

UN(t) = UN(t-1) × A0 × NFS(t)/ NFS(t-1) 

Eq. 9.4

Where:

UN(t) = the number of units installed, in linear feet, in new buildings in year t, and

A0 = an overall scale factor that accounts for the number of units covered by the standard, which 

are not used in all commercial building types; the default value for A0 is 1.0. 

DOE has no information on the variation in the market saturation of commercial 

refrigeration equipment by building type or over time. Therefore, in the model, the purchase of 

new equipment is driven by the construction of new floor space and the assumption that broken 

or removed equipment is replaced on a one-to-one basis. 

9.3 DATA INPUTS

9.3.1 Historical Shipments

Shipments data for commercial refrigeration equipment could not be obtained in a 

complete form from any one source; therefore, DOE used data from multiple sources to estimate 

shipments and to compare and cross-verify the shipments data from one source to another. The 

major sources were 2005 shipments data provided by the Air-Conditioning, Heating, and 

Refrigeration Institute (AHRI) as part of its comments to the 2009 rulemaking Framework 

document (Docket No. EERE-2006-STD-0126, ARI, No. 7, Exhibit B at p. 1); Commercial 

Refrigeration Equipment to 2014 by Freedonia Group, Inc. (the Freedonia 2010 report)1

; 2008 

Size and Shape of Industry by the North American Association of Food Equipment 

Manufacturers (NAFEM 2008 report)2 and 2010 Size and Shape of Industry by the North 

American Association of Food Equipment Manufacturers (NAFEM 2010 report)3; and Energy 

Savings Potential and R&D Opportunities for Commercial Refrigeration prepared by Navigant 

Consulting, Inc., for DOE (NCI 2009 report).4 Further details about these data sources can be 

obtained from TSD chapter 3.

The AHRI 2005 shipments data was a compilation of shipments numbers provided by 

AHRI members, and as such did not represent the entire commercial refrigeration equipment 

market. However, the AHRI 2005 shipments data contained shipments explicitly broken down 

by DOE equipment class. The Freedonia 2010 report provided shipments data in terms of total 

dollar sales and number of units shipped. Shipments were split by market type (e.g., foodservice 

industry, food and beverage retail industry) and by certain equipment types (e.g., open display 

cases, reach-ins). The NAFEM 2008 and 2010 reports provided shipment numbers and dollar 

sales values for refrigeration and ice machines used in the foodservice industry. Reach-in 

9-4 
refrigerators and freezers, chest freezers, milk coolers, and ice-cream storage and dipping 

cabinets make up the majority of the commercial refrigeration equipment used in the foodservice 

industry. 

Because complete shipments data could not be obtained from a single source, DOE 

compiled data from all of the aforementioned sources and developed the 2009 shipments 

numbers using some basic assumptions. The Freedonia 2010 report contains historical data used 

to derive a year-to-year percentage change in the total commercial refrigeration equipment sales. 

DOE assumed that subsequent years’ shipments of the equipment reported in the 2005 AHRI 

summary grew at the year-to-year growth rates reported by Freedonia, and used the percentage 

changes from the Freedonia 2010 report to derive the 2009 AHRI shipments estimates from the 

AHRI reported shipments for the year 2005. 

The 2009 shipments numbers derived from the 2005 AHRI shipments data were modified 

for certain equipment classes using shipments data obtained from the other sources. Shipments 

for equipment classes VCS.SC.M and VCS.SC.L were obtained from estimates from the 

NAFEM 2008 and 2010 reports. (Chapter 3 of this TSD defines the acronyms used for the 

equipment classes in this section.) The Freedonia 2010 report provided shipments for open 

display cases that operate at normal (medium) and low temperatures, and closed display cases 

that operate at normal (medium), low, and ice-cream temperatures. These aggregate numbers 

could not be further split into the equipment classes. For example, the open display cases could 

not be split into VOP, SVO, and HZO cases. However, the aggregate shipments numbers for 

normal and low-temperature display cases compared reasonably well with the corresponding 

aggregate shipments numbers from 2005 AHRI shipments data. While the aggregate shipments 

numbers for ice-cream display cases compared well for both the 2005 AHRI shipments data and 

Freedonia 2010 report, the 2005 AHRI shipments number of 9,056 units for HCT.SC.I seemed 

too high, especially considering the fact that the shipments number for HCT.SC.L is zero. 

HCT.SC.L equipment is predominantly used in ice-cream stores in the form of ice-cream dipping 

cabinets. While this equipment is advertised as ice-cream dipping cabinets, the operating 

temperature range is typically -10 °F to 5 °F, which is above the ice-cream rating temperature of 

-15 °F. DOE assumed that the AHRI shipments numbers for HCT.SC.L may have been 

subsumed into the HCT.SC.I numbers. DOE allocated half of the shipments from HCT.SC.I to 

HCT.SC.L. These numbers compared reasonably well to the ice-cream cabinets, freezer, and 

dispensers numbers from the NAFEM reports. Shipments for equipment class PD.SC.M were 

obtained based on estimates from the NCI 2009 report. However, based on inputs from other 

sources, the shipments number for PD.SC.M units was increased by 25 percent compared to the 

estimates in the NCI 2009 report. 

As previously mentioned, shipments by equipment class were available only from the 

2005 AHRI data. To allocate the shipments to different equipment classes from the other 

sources, DOE made assumptions about the definitions of the equipment types and the market 

share split for certain equipment classes. Shipments numbers and assumptions have been 

withheld because the NAFEM reports and Freedonia 2010 report are not public documents and 

are available only for purchase.

9-5 
9.3.2 Historical Shipments and Projected Building Stock Additions

Historical linear feet of shipped units depicts the annual amount of commercial 

refrigeration equipment capacity shipped and is an alternative way to express shipments data. 

DOE determined the linear feet shipped for any given year by multiplying each unit shipped by 

its associated average length, and then summing all the linear footage values. 

DOE converted the estimated 2009 shipments data in each equipment class to 

percentages of total shipped linear feet of commercial refrigeration equipment for use in the 

Shipments Model. This established the commercial refrigeration equipment market share 

attributed to each equipment class. DOE calculated the percent of shipped linear footage by

dividing the linear footage shipped for each equipment class by the overall linear footage shipped 

for all commercial refrigeration equipment covered in this rulemaking. 

Table 9.3.1 summarizes DOE’s estimated division of historical annual shipments into

new and replacement categories by building type. The distributions shown in Table 9.3.1 are the 

result of several discrete steps. First, equipment types were identified by the type of business 

they generally serve. For example, vertical open cases with remote compressors are generally 

associated with large grocers and multi-line retail stores. Remote condensing equipment is 

generally associated with large food sales stores, while self-contained units are associated with 

food service and convenience or small food sales stores. When there was no strong association 

between the building type and equipment class, equipment was distributed across broader 

classes. Second, a ratio of new versus replacement was developed based on commercial floor 

space estimates (floor space estimates are discussed in section 9.3.3). Using the expected useful 

life of commercial refrigeration equipment and commercial floor space stock, additions, and 

retirements, ratios were developed that yielded values for the amount of new versus replacement 

stock for use in this analysis. Using these and related factors (e.g., the division of foodservice 

into the three building types: limited service restaurants, full-service restaurants, and other), 

DOE distributed commercial refrigeration equipment shipments among building types and new 

versus replacement shipments as shown in Table 9.3.1. 

Table 9.3.1 Estimated Distribution of 2009 Linear Feet of Commercial Refrigeration 

Equipment Shipments Among New vs. Replacement Equipment

Building Type Replacement New Total

Large Grocery / Multi-Line Retail 30.5% 8.6% 39.1%

Small Grocery / Convenience 14.6% 4.1% 18.7%

Limited Service Restaurants 9.5% 3.3% 12.7%

Full Service Restaurants 9.8% 3.4% 13.2%

Other 12.1% 4.2% 16.3%

Total 76.4% 23.6% 100.0%

Table 9.3.2 shows the forecasted square footage of new construction used to scale annual 

new commercial refrigeration equipment shipments. As the data in Table 9.3.2 show, forecasted 

square footage additions to the building stocks vary from year to year, with the first few years 

exhibiting lower levels of growth due to the lingering impacts of the U.S. economic recession. 

The forecasted commercial refrigeration equipment shipments therefore show some variability as 

well, tracking the forecasted square footage floor space additions. The annual floor space 

additions expressed as a percentage of total surviving floor space, averaged over the last 10 years 

9-6 
of the Annual Energy Outlook (AEO) forecast (2031 through 2040), were used to extend the AEO

forecast out until the year 2046 in order to develop the full 30-year forecast needed for the 

national impacts analysis (see TSD chapter 10). 

Table 9.3.2 AEO2013 Forecast of New Food Sales and Foodservice Square Footage 

Year

New Construction

million ft2

Foodservice Food Sales

2009 47.715 34.070

2012 31.455 22.149

2017 49.076 34.496

2020 47.617 33.447

2025 47.522 33.416

2030 53.630 37.836

2035 55.536 39.107

2040 55.814 39.243

Annual Growth Factor, 2031-2040 2.41% 2.27%

Source: U.S. Department of Energy, Energy Information Administration, Annual Energy Outlook 2013.

DOE used the AHRI shipments data to derive shipped linear footage for each of the 

25 primary equipment classes. Table 9.3.3 presents the representative equipment class lengths 

used for the conversion of per-unit shipments to linear footage within each equipment class.

Table 9.3.3 Equipment Linear Dimensions Assumed for Shipments Analysis

Equipment

Class

Assumed Length

ft Basis

VOP.RC.M 10 Average of 8 ft and 12 ft, manufacturer interviews

VOP.RC.L 10 Average of 8 ft and 12 ft, manufacturer interviews

VOP.SC.M 4 Baseline equipment used for engineering analysis

SVO.RC.M 10 Average of 8 ft and 12 ft, manufacturer interviews

SVO.SC.M 4 Baseline equipment used for engineering analysis

HZO.RC.M 10 Average of 8 ft and 12 ft, manufacturer interviews

HZO.RC.L 10 Average of 8 ft and 12 ft, manufacturer interviews

HZO.SC.M 4 Baseline equipment used for engineering analysis

HZO.SC.L 4 Baseline equipment used for engineering analysis

VCT.RC.M 10 Average of 3-door and 5-door (30 in. per door), manufacturer interviews

VCT.RC.L 10 Average of 3-door and 5–door (3 in. per door), manufacturer interviews

VCT.SC.M 4 Engineering estimate*

VCT.SC.L 3.5 Average of 1-door and 2-door freezer

VCT.SC.I 5 Baseline equipment used for engineering analysis

VCS.SC.M 4 Engineering estimate

VCS.SC.L 3.5 Average of 1-door and 2-door freezer

VCS.SC.I 5 Baseline equipment used for engineering analysis

HCT.SC.M 3.0 Engineering estimate*

HCT.SC.L 3.0 Engineering estimate*

HCT.SC.I 3.4 Baseline equipment used for engineering analysis

HCS.SC.M 4.0 Engineering estimate*

HCS.SC.L 5.0 Engineering estimate*

SOC.RC.M 8 Average of 4 ft, 8ft, 12 ft, all common equipment lengths

PD.SC.M 2.5 Baseline equipment used for engineering analysis

SOC.SC.M 5 Engineering estimate*

*For equipment classes that exhibit a wide range of equipment lengths in the market, DOE assumed a value for equipment length

based on the best engineering judgment. 

9-7 
DOE then calculated the annual linear footage shipped for each of the 25 equipment 

classes. The shipments analysis relies on the 25 equipment classes to represent the commercial 

refrigeration equipment market. Table 9.3.4 shows the fraction of the linear footage shipped by 

each of these 25 equipment classes.

Table 9.3.4 Percent of Shipped Linear Feet of Commercial Refrigeration Equipment

Equipment Class* Percentage of Linear 

Feet Shipped*

Equipment 

Class

Percentage of Linear 

Feet Shipped*

VOP.RC.M 11.59% SVO.SC.M 1.23%

VOP.RC.L 0.61% SOC.RC.M 2.34%

VOP.SC.M 0.82% HZO.RC.M 1.43%

VCT.RC.M 0.87% HZO.RC.L 4.49%

VCT.RC.L 12.11% HZO.SC.M 0.11%

VCT.SC.M 5.46% HZO.SC.L 0.22%

VCT.SC.L 0.27% HCT.SC.M 0.07%

VCT.SC.I 0.30% HCT.SC.L 0.43%

VCS.SC.M 22.11% HCT.SC.I 0.48%

VCS.SC.L 11.25% HCS.SC.M 5.01%

VCS.SC.I 0.07% HCS.SC.L 0.65%

SVO.RC.M 9.30% PD.SC.M 8.58%

SOC.SC.M 0.17%

*Numbers do not add to 100% because secondary equipment classes (chapter 5) are excluded from the table.

9.3.3 Commercial Floor Space and Market Saturation

The amount of commercial floor space is the main driver for commercial refrigeration 

equipment shipments and is appropriately one of the basic inputs into the Shipments Model. As 

discussed in section 9.2.2, the model divides commercial space into two components: space from 

new construction floor space (NFS), and existing floor space (EFS). 

For this analysis, commercial square footage with commercial refrigeration equipment

refers to both new and existing stock of buildings. 

9.3.3.1 Floor Space – New Construction

DOE used the projected floor space construction after the year 2009 from the National 

Energy Modeling System projection underlying AEO2013.

5 DOE extracted annual estimates of 

new floor space additions from an AEO2013 data file for the 2009 through 2040 period. As 

stated earlier, the last 10 years of the AEO forecast were used to develop growth rates used to 

extend the forecast to 2046. 

The total value for the new length of equipment is the estimated total shipments in linear 

feet for 2009, divided between the food sales and foodservice sectors and multiplied by indexes

of new construction of square feet for each building type. The index for each building type was 

developed by dividing floor space projections in each future year by the value from the prior 

year. All existing display space is presumed to be replaced when demolished.

9-8 
9.3.3.2 Market Shipments

DOE used the above shipments data to estimate the market shipments in year t of each 

commercial refrigeration equipment class y, MKTSHIP(t,y), defined in terms of linear feet of 

space occupied by the new and replacement shipments of equipment class y. Because the market 

share by percent of each equipment class shipments is relatively constant over time and the 

lifetime of each class remains same, the ratio of shipments of a specific equipment class indicates

the market share for that class, MKT(y). DOE estimated the MKT(y) for a particular equipment 

class to be a constant value equal to the average of the yearly percent historical shipments to that 

class. These percentages are reported in Table 9.3.4. 

MMMMMMMMMMMMMM(tt, yy) = MMMMMM(yy) × (UUUU(tt) + UUUU(tt))

Eq. 9.5 

Where:

MKTSHIP(t,y) = total market shipments, in linear feet of display space, of equipment class y

in year t, 

MKT(y) = percentage of total market shipments in equipment class y (%),

UN(t) = total shipments to new buildings in year t, and

UB(t) = total replacement shipments in year t. 

9.3.4 Equipment Utility 

The equipment utility is a measure of the economic value of a linear foot of commercial 

refrigeration equipment to the customer. This is the value associated with energy savings.

Because there are insufficient historical data available on the commercial refrigeration 

equipment market to develop and calibrate a full supply and demand model, economic factors 

are used to calculate annualized cost and to calibrate market shares for the Shipments Model. 

These economic factors are discussed below. 

9.3.5 Equipment Price

Equipment price is the price paid by the customer for a unit of commercial refrigeration 

equipment. It includes both the purchase price of the equipment and the installation costs. DOE

converts the equipment price to a price per linear-foot-cooled based on the length of the 

equipment class.

As discussed in the engineering analysis (chapter 5) and the life-cycle cost and payback

period analysis (chapter 8), equipment prices in this analysis are a function of energy efficiency

level. DOE based equipment price projections on energy consumption level, but did not develop 

estimates of market trends in efficiency. DOE developed a mix of energy consumption levels for 

the base case (i.e., the case without new energy conservation standards) and for each candidate 

standard level envisioned. The efficiency mixes are discussed in detail in chapter 10. 

9-9 
9.3.5.1 Operating Costs 

Operating costs consist of maintenance, repair, and energy costs. A detailed description 

of all the operating costs can be found in chapter 8. 

9.3.5.2 Discounted Costs

When purchasing commercial refrigeration equipment, a budget-conscious customer will 

consider the total lifetime cost of the equipment. Typically, these lifetime costs are discounted to 

represent the present value of these costs. DOE discounted the total operating costs (i.e., 

maintenance, repair, and energy costs) over the full lifetime of the equipment. Commercial 

refrigeration equipment lifetimes range from 1 to as many as 20 years. However, based on 

discussions with industry, the typical lifetime of commercial refrigeration equipment is 10 years

in large food retailers and 15 years in small retailers. This is because large grocery stores either 

undergo renovation or replace the refrigeration equipment for aesthetic reasons at roughly 

10-year intervals, but small food retailers with fewer resources to direct towards capital 

improvements usually try to make their equipment last longer and update it less frequently

(see chapter 8 for further details). Equipment life was modeled as 10 years in foodservice sectors 

for reasons similar to the large retailers.

9.4 RESULTS

Table 9.4.1 shows the shipments forecast for the commercial refrigeration equipment 

classes at the base-case energy consumption level (or Level 1) divided into new and replacement 

units for large and small food sales and foodservice outlets. Table 9.4.2 shows total shipments by 

equipment type. 

Table 9.4.1 Forecasted Shipments of New and Replacement Commercial Refrigeration 

Equipment by Building Type, 2017−2046 (Base Case) 

Building Type Thousands of Linear Feet Shipped by Year and Equipment Class

2017 2020 2025 2030 2035 2040 2045 Total

Large Grocery

– New 253 237 245 278 287 288 314 8,276

– Replacement* 853 935 964 1,078 1,145 1,272 1,372 33,176

Small Grocery

– New 121 118 118 133 138 138 151 3,963

– Replacement* 386 381 417 428 443 474 506 13,115

Foodservice

– New 326 316 315 356 369 370 404 10,631

– Replacement* 882 993 1,039 1,193 1,286 1,456 1,590 36,899

Total 2,822 2,980 3,098 3,467 3,667 3,999 4,338 106,061

* Replacement includes equipment replaced from original stock (installed before the standards set by the 

current rulemaking takes effect) and the standards level equipment replaced in subsequent years.

9-10
Table 9.4.2 Forecasted Shipments for Commercial Refrigeration Equipment, 2017−2046, 

by Equipment Type (Base Case)

Equipment 

Class

Thousands of Linear Feet Shipped by Year and Equipment Class*

2017 2020 2025 2030 2035 2040 2045 2046 Cumulative

VOP.RC.M 327 346 359 402 425 463 503 513 12,287 

VOP.RC.L 17 18 19 21 22 24 26 27 647 

VOP.SC.M 23 24 25 28 30 33 36 36 870 

VCT.RC.M 25 26 27 30 32 35 38 39 924 

VCT.RC.L 342 362 375 420 444 484 525 537 12,847 

VCT.SC.M 154 163 169 189 200 218 237 242 5,792 

VCT.SC.L 8 8 8 9 10 11 12 12 289 

VCT.SC.I 8 9 9 10 11 12 13 13 317 

VCS.SC.M 624 661 685 766 811 884 959 979 23,447 

VCS.SC.L 318 336 349 390 413 450 488 499 11,935 

VCS.SC.I 2 2 2 3 3 3 3 3 78 

SVO.RC.M 263 278 288 322 341 372 403 412 9,866 

SVO.SC.M 35 37 38 43 45 49 53 54 1,302 

SOC.RC.M 66 70 73 81 86 94 102 104 2,487 

HZO.RC.M 40 43 44 50 52 57 62 63 1,516 

HZO.RC.L 127 134 139 156 165 180 195 199 4,767 

HZO.SC.M 3 3 3 4 4 4 5 5 112 

HZO.SC.L 6 7 7 8 8 9 9 10 232 

HCT.SC.M 2 2 2 2 3 3 3 3 73 

HCT.SC.L 12 13 13 15 16 17 19 19 453 

HCT.SC.I 14 14 15 17 18 19 21 21 514 

HCS.SC.M 141 150 155 174 184 200 217 222 5,310 

HCS.SC.L 18 19 20 22 24 26 28 29 686 

PD.SC.M 242 256 266 297 315 343 372 380 9,101 

SOC.SC.M 5 5 5 6 6 7 8 8 185 

Total 2,821 2,987 3,097 3,466 3,666 3,998 4,337 4,429 106,034 

*Values include only equipment classes modeled in the engineering, life-cycle cost, and national impact analyses. 

As equipment purchase price increases with lower energy consumption levels, a drop in 

shipments could be expected relative to the base case. Although there is a provision in the 

Shipments Model spreadsheet for a change in shipments as the efficiency level increases (or 

energy consumption level decreases), DOE has no information with which to calibrate such a 

relationship. Therefore, for the notice of proposed rulemaking, DOE presumes that the shipments 

do not change in response to the higher efficiency levels that form potential candidate standard 

levels. 

9-11
REFERENCES 

1. Freedonia Group, Inc. Commercial Refrigeration Equipment to 2014. 2010. Cleveland, Ohio. 

Study 2261. <http://www.freedoniagroup.com/Commercial-Refrigeration-Equipment.html> 

2. North American Association of Food Equipment Manufacturers. 2008 Size and Shape of 

Industry. 2008. Chicago, IL. 

3. North American Association of Food Equipment Manufacturers. 2010 Size and Shape of 

Industry. 2010. Chicago, IL. 

4. Navigant Consulting, Inc. Energy Savings Potential and R&D Opportunities for Commercial 

Refrigeration. 2009. Prepared by Navigant Consulting, Inc. for the U.S. Department of 

Energy, Washington, D.C. 

5. U.S. Department of Energy-Energy Information Administration. Annual Energy Outlook 

2013. 2013. Washington D.C. DOE/EIA-0383(2013). 

9-12
CHAPTER 10. NATIONAL IMPACT ANALYSIS

TABLE OF CONTENTS

10.1 INTRODUCTION ............................................................................................................ 10-1

10.2 NATIONAL ENERGY SAVINGS .................................................................................. 10-1

10.2.1 National Energy Savings Definition ..................................................................... 10-1

10.2.2 National Energy Savings Inputs............................................................................ 10-2

10.2.2.1 Annual Unit Energy Consumption......................................................... 10-2

10.2.2.2 Shipments ............................................................................................... 10-7

10.2.2.3 Equipment Stock .................................................................................... 10-7

10.2.2.4 National Annual Energy Consumption .................................................. 10-7

10.2.2.5 Site-to-Source Conversion Factor .......................................................... 10-8

10.2.2.6 Full-Fuel-Cycle Energy ......................................................................... 10-8

10.3 NET PRESENT VALUE .................................................................................................. 10-9

10.3.1 Net Present Value Definition ................................................................................ 10-9

10.3.2 Net Present Value Inputs .................................................................................... 10-10

10.3.2.1 Total Annual Installed Cost ................................................................. 10-10

10.3.2.2 MPC Price Trends ................................................................................ 10-12

10.3.2.3 Light Technology Price Trends ........................................................... 10-14

10.3.2.4 Total Annual Operating Cost Savings ................................................. 10-14

10.3.2.5 Discount Factor .................................................................................... 10-18

10.3.2.6 Present Value of Costs ......................................................................... 10-19

10.3.2.7 Present Value of Savings ..................................................................... 10-19

10.4 NATIONAL ENERGY SAVINGS AND NET PRESENT VALUE RESULTS ........... 10-19

10.4.1 National Energy Savings and Net Present Value Input Summary ...................... 10-19

10.4.2 National Energy Savings Results ........................................................................ 10-20

10.4.3 Annual Costs and Savings .................................................................................. 10-24

10.4.4 Net Present Value Results ................................................................................... 10-25

10.5 ANNUALIZED NATIONAL COSTS AND BENEFITS .............................................. 10-29

10.5.1 Calculation Method ............................................................................................. 10-30

10.5.2 Results for the Adopted Standards ...................................................................... 10-31

REFERENCES ........................................................................................................................ 10-33

LIST OF TABLES

Table 10.2.1 National Energy Saving Inputs ............................................................................. 10-2

Table 10.2.2 Risk Premiums by Risk Class (j) Derived from the NEMS Commercial Model . 10-4

Table 10.2.3 Market Shares of Efficiency Level, Base Case ..................................................... 10-5

Table 10.2.4 Average Annual Unit Energy Consumption per Linear Foot by 

Efficiency Level ................................................................................................. 10-6

Table 10.2.5 Shipment-Weighted Average Annual Energy Consumption per Linear Foot by 

Efficiency Level ................................................................................................. 10-7

Table 10.2.6 Site-to-Source Conversion Factors* ..................................................................... 10-8

Table 10.2.7 Full-Fuel-Cycle Energy Multipliers (Based on AEO2013) .................................. 10-9

Table 10.3.1 Net Present Value Inputs .................................................................................... 10-10

Table 10.3.2 Average Installed Cost per Linear Foot by Efficiency Level ............................. 10-10

10-i
Table 10.3.3 Shipment-Weighted Average Total Installed Cost per Linear Foot by Efficiency 

Level ................................................................................................................ 10-12

Table 10.3.4 Price Trend Scenarios ......................................................................................... 10-13

Table 10.3.5 LED price deflators used in the NOPR analysis. ................................................ 10-14

Table 10.3.6 Average Annual Repair Cost per Linear Foot by Efficiency Level ................... 10-15

Table 10.3.7 Shipment-Weighted Average Annual Repair Cost per Linear Foot by 

Efficiency Level ............................................................................................... 10-16

Table 10.3.8 Average Annual Maintenance Cost per Linear Foot by Efficiency Level ......... 10-17

Table 10.3.9 Shipment-Weighted Average Annual Maintenance Cost per Linear Foot by 

Efficiency Level ............................................................................................... 10-18

Table 10.4.1 NES and NPV Inputs .......................................................................................... 10-20

Table 10.4.2 Cumulative National Energy Savings, without Full-Fuel-Cycle, by CSL for 

Equipment Purchased in 2017–2046 ............................................................... 10-21

Table 10.4.3 Cumulative National Energy Savings, without Full-Fuel-Cycle, by TSL for 

Equipment Purchased in 2017–2046 ............................................................... 10-22

Table 10.4.4 Cumulative National Energy Savings, with Full-Fuel-Cycle, by CSL for 

Equipment purchased in 2017–2046 ................................................................ 10-22

Table 10.4.5 Cumulative Energy Savings, with Full-Fuel-Cycle, by TSL for Equipment 

Purchased in 2017–2046 .................................................................................. 10-23

Table 10.4.6 Cumulative Energy Savings, with Full-Fuel-Cycle, by TSL Expressed as a 

Percentage of Cumulative Base-Case Energy Usage of the Total 

Equipment Stock .............................................................................................. 10-24

Table 10.4.7 Cumulative NPV Results by CSL Based on a 7-Percent Discount Rate 

(billion 2012$) ................................................................................................. 10-26

Table 10.4.8 Cumulative NPV Results by TSL Based on a 7-Percent Discount Rate 

(billion 2012$) ................................................................................................. 10-27

Table 10.4.9 Cumulative NPV Results by CSL Based on a 3-Percent Discount Rate 

(billion 2012$) ................................................................................................. 10-28

Table 10.4.10 Cumulative NPV Results by TSL Based on a 3-Percent Discount Rate 

(billion 2012$) ................................................................................................. 10-29

Table 10.5.1 Annualized Benefits and Costs of New and Amended Standards for 

Commercial Refrigeration Equipment Shipped in 2017–2046* ...................... 10-31

LIST OF FIGURES

Figure 10.4.1 National Annual Costs and Savings for Efficiency Level 4 for Equipment 

Class VOP.RC.M ............................................................................................. 10-25

10-ii
CHAPTER 10. NATIONAL IMPACT ANALYSIS

10.1 INTRODUCTION

This chapter describes the method for estimating the magnitude and net present value 

(NPV) of future national energy savings (NES) from possible standards levels for commercial 

refrigeration equipment. Results of the national impact analysis (NIA) described in this chapter 

include NES, monetary value of energy savings to the nation as a result of standards, increased 

total installed costs to the nation as a result of standards, and the NPV of future savings (the 

difference between the present monetary values of energy savings and increased total installed 

costs). 

The U.S. Department of Energy (DOE) determined both the NPV and NES for each

candidate standard level (CSL) it considered for each of the 25 primary equipment classes of 

commercial refrigeration equipment analyzed in this rulemaking. Sections 10.2 and 10.3 present 

the definitions and the inputs to NES and NPV, respectively. Section 10.4 presents the results of 

the NIA. DOE performed all calculations using a Microsoft Excelspreadsheet, which is available

at http://www1.eere.energy.gov/buildings/appliance_standards/product.aspx/productid/52. 

Details and instructions for using the spreadsheet are discussed in appendix 10A of the technical 

support document (TSD). 

10.2 NATIONAL ENERGY SAVINGS

10.2.1 National Energy Savings Definition

DOE calculates annual NES for a given year (denoted as t, below) as the difference 

between two scenarios: a base-case scenario without new energy conservation standards and 

standards-case scenarios with new energy conservation standards. Positive values of NES 

correspond to net energy savings (i.e., national annual energy consumption (AEC) with standards 

is less than national AEC in the base case). 

NNNNNNtt = AA AAbbbbbbbb,tt − AA AA ssss ssss ,tt

Eq. 10.1 

Where:

NESt = national energy savings in the year t (quadrillion British thermal units (quads)), 

AECbase,t = annual national energy consumption in the year t in the base-case scenario (quads),

and

AECstandards,t = annual national energy consumption in the year t in a standards-case scenario 

(quads). 

Annual NES from each year, starting with the year when the standards that are the subject 

of this rulemaking become effective (2017), can be summed to calculate the cumulative NES

(NEScum). 

NNNNNNcccccc = ∑ NNNNNNtttt

Eq. 10.2 

10-1
For each equipment class, DOE calculated the AEC for base-case and standards-case 

scenarios by multiplying the stock of commercial refrigeration equipment (by vintage) by the 

unit energy consumption (UEC) (also by vintage) as shown by the following equation:

AA AAtt = ∑ ( SSSS SSVV × UU VV VV ) × ssssss_ cccccctt

Eq. 10.3 

Where:

AECt = national annual energy consumption in the year t (quads), summed over vintages of 

commercial refrigeration equipment stock, 

STOCKV = stock of commercial refrigeration equipment (millions of units) of vintage V surviving 

in the year for which DOE calculated annual energy consumption; vintages range from 1 to 

approximately 10 years (or 15 years for certain equipment and building types, see chapter 8 

of the TSD), a function of an assumed 10-year (or 15-year) lifetime of the equipment, 

UECV = annual unit energy consumption in kilowatt-hours (kWh) for equipment of vintage V, 

src_convt = time-dependent conversion factor to convert from site energy to source energy 

(British thermal units per kilowatt-hour (Btu/kWh)), and

t = year of forecast.

The stock of commercial refrigeration equipment is dependent on annual shipments and 

the lifetime of the equipment. DOE acknowledges that the shipment projections under the 

standards-case scenarios could be lower than those in the base-case scenario, because the higher 

installed costs could cause some customers to forego or delay discretionary equipment purchases 

that are not occasioned by the need to replace failed equipment or to furnish a new building. 

However, DOE has no information that would allow a calculation of this effect, so shipments 

were assumed to be the same in both base-case and standards-case scenarios. 

10.2.2 National Energy Savings Inputs

Table 10.2.1 lists the inputs for the determination of NES.

Table 10.2.1 National Energy Saving Inputs 

Input

Annual Unit Energy Consumption (UEC)

Shipments

Equipment Stock (STOCKV)

Site-to-Source Conversion Factor (src_conv)

10.2.2.1 Annual Unit Energy Consumption 

The annual UEC is the site energy consumed by a commercial refrigeration unit in a 

given year. Because the equipment classes analyzed represent equipment sold across a range of 

sizes, DOE’s “unit” in the NES is actually expressed as a linear foot of equipment in an 

equipment class and not an individual unit of commercial refrigeration equipment of a specific 

size. As described in this section, DOE determined annual forecasted shipment-weighted average 

equipment efficiencies that, in turn, enabled determination of shipment-weighted AEC values.

10-2
DOE did not have data on the market shares by efficiency level within each of the 

equipment classes. For this notice of proposed rulemaking (NOPR), DOE used the same 

methodology employed in the January 9, 2009 final rule to estimate market shares of each 

efficiency level within each equipment class. 74 FR at 1092. The methodology is a cost-based 

method consistent with the approaches that were used in the Energy Information 

Administration’s (EIA’s) National Energy Modeling System1 (NEMS) and in the Canadian 

Integrated Modeling System (CIMS) a,2 for estimating efficiency choices within each equipment 

class. DOE then extrapolated future scenarios of the equipment efficiency for the base case and 

standards cases using the same cost-based method. The difference in equipment efficiency 

between the base case and standards case was the basis for determining the reduction in UEC

resulting from new standards. 

The market share for each equipment class by efficiency level is defined as

EFF_Level_Share(i,y), for each equipment class, y, at each efficiency level, i. Because DOE had 

no information regarding future changes in market shares between equipment classes, DOE 

assumed the market share for a particular equipment class to be constant over time. DOE 

calculated the EFF_Level_Share(i,y) for each efficiency level i using the following formula, 

based on the relative annualized cost of each efficiency level. 

∑

∑

=

−

−

−

−

=

















+

+−

×

















+

+−

×

×=

k

i

v

n yi

j

j

yi

v

n yi

j

j

yi m

j

j

OC

r

r

IC

OC

r

r

IC

EFF Level byiShare

1

),( ).(

),( ).(

1

)1(1

)1(1

),(__

 Eq. 10.4 

Where: 

EFF_Level_Share(i,y) = the market share of efficiency level i for equipment class y, 

IC(i, y) = installed cost of equipment class y with efficiency level i, k is the number of efficiency 

levels in equipment class y, 

OC(i,y) = annual operating cost (maintenance, repair, and energy cost) of equipment class y with

efficiency level i, 

k = number of efficiency levels in the equipment class,

rj = private, risk-adjusted discount rate for risk class j, which is derived for each class by adding 

a time preference premium to the measure of risk-free real rate of return in the marketplace 

(6.41 percent historical 40-year geometric average long-term Treasury bond rate minus longterm inflation rate of 3.68 percent, or 2.72 percent), 

bj = market share of equipment users with risk class j, j = 1 to m, 

v = risk penalty factor (also known as a measure of market heterogeneity), and

n = equipment lifetime. 

a The CIMS Model was originally known as the Canadian Integrated Modeling System, but as the model is now 

being applied to other countries, the acronym is now used as its proper name.

10-3

 
The components for IC and OC come from the same inputs as the life-cycle cost (LCC)

analysis (see TSD chapter 8). The annualization factor rj/(1-(1+rj)

-n) converts installed cost into 

its annual equivalent, so that market shares are based on the relative annual costs of each 

efficiency level, with (generally) higher annualized costs of higher efficiency levels leading to 

lower relative market shares. For each risk class rj, Table 10.2.2 displays the implied discount 

rates taken from the NEMS commercial model. These, combined with the default value of v = 

10, taken from the CIMS, and equipment lifetimes, were used to distribute equipment shipments 

across efficiency levels. 

Table 10.2.2 Risk Premiums by Risk Class (j) Derived from the NEMS Commercial Model

Percentage of Users in 

Class

Time Preference 

Premium

Implied Real Discount 

Rate

0.3% 0.0% 2.72%

0.4% 6.5% 9.22%

9.7% 15.0% 17.72%

16.9% 25.0% 27.72%

21.5% 45.0% 47.72%

24.7% 100.0% 102.72%

26.5% 1000.0% 1002.72%

100%

Source: NEMS Commercial Model

Table 10.2.3 provides estimated base-case market shares of efficiency levels for each of 

the 25 equipment classes analyzed in this rulemaking. 

DOE used a “roll-up” method to obtain the market share of the efficiency levels in the 

standards-case scenarios. In the roll-up method, the market shares of all efficiency levels below 

the efficiency level corresponding to the standards-case scenario would be reassigned to the 

efficiency level corresponding to the standards-case scenario. For example, if a Level 4 standard 

were imposed in 2017 on the VOP.RC.M equipment class (vertical open refrigerator connected 

to a remote condensing unit), then the market shares for Levels 1, 2, and 3 would be assigned to 

Level 4. This would result in a market share of 85.1 percent (24.3 percent + 24.0 percent + 

23.4 percent + 13.4 percent) from the first four columns of the first row in Table 10.2.3) for 

Level 4, beginning in 2017. The market shares for Levels 5−8 would not be affected because the 

market already has a choice of that equipment with Level 4 also available. DOE assumed that the 

standard level (Level 4) would not affect the relative attractiveness of equipment with 

efficiencies higher than the standard level. 

10-4
Table 10.2.3 Market Shares of Efficiency Level, Base Case

Equipment 

Class

Shipment-Weighted Market Shares by Efficiency Level*,**

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M 24.3% 24.0% 23.4% 13.4% 12.8% 2.0% NA NA

VOP.RC.L 26.0% 26.1% 23.2% 22.4% 2.2% NA NA NA

VOP.SC.M 19.1% 19.0% 18.8% 18.1% 11.3% 10.7% 3.1% NA

VCT.RC.M 18.8% 18.8% 15.9% 15.5% 14.8% 14.5% 1.7% NA

VCT.RC.L 19.5% 20.4% 20.0% 19.4% 19.0% 1.8% NA NA

VCT.SC.M 16.7% 17.4% 15.4% 13.0% 12.6% 11.7% 11.5% 1.7%

VCT.SC.L 10.5% 13.2% 16.4% 16.2% 14.4% 14.2% 13.1% 2.0%

VCT.SC.I 16.4% 18.1% 17.8% 15.9% 15.5% 14.8% 1.5% NA

VCS.SC.M 13.1% 14.9% 15.0% 15.0% 14.6% 14.0% 12.6% 0.8%

VCS.SC.L 12.1% 15.1% 15.3% 15.4% 14.3% 13.9% 13.3% 0.6%

VCS.SC.I 16.7% 16.8% 17.4% 17.0% 16.0% 15.4% 0.7% NA

SVO.RC.M 24.5% 24.5% 22.2% 13.2% 12.6% 3.0% NA NA

SVO.SC.M 19.5% 19.5% 18.5% 18.0% 10.8% 10.1% 3.7% NA

SOC.RC.M 17.7% 17.8% 17.8% 14.5% 14.1% 12.7% 5.4% NA

HZO.RC.M 78.4% 21.6% NA NA NA NA NA NA

HZO.RC.L 86.2% 13.8% NA NA NA NA NA NA

HZO.SC.M 25.4% 25.4% 25.0% 21.9% 2.4% NA NA NA

HZO.SC.L 71.8% 28.2% NA NA NA NA NA NA

HCT.SC.M 14.8% 15.4% 15.6% 15.7% 13.4% 12.8% 11.0% 1.4%

HCT.SC.L 12.3% 13.3% 13.6% 15.8% 15.6% 15.0% 13.2% 1.2%

HCT.SC.I 25.6% 25.8% 25.1% 22.3% 1.1% NA NA NA

HCS.SC.M 17.2% 17.5% 17.2% 16.8% 15.9% 13.3% 2.1% NA

HCS.SC.L 16.2% 17.0% 17.2% 17.1% 16.6% 14.5% 1.5% NA

PD.SC.M 14.0% 17.2% 16.1% 15.8% 15.3% 11.0% 9.7% 1.0%

SOC.SC.M 14.7% 15.1% 15.1% 15.0% 12.5% 12.1% 11.0% 4.6%

* Shares may not add to 100% exactly due to rounding. 

** A value of “NA” indicates that there are no associated efficiency levels at this level for this equipment class.

Table 10.2.4 provides the annual UEC values for each efficiency level for all 25 primary 

equipment classes obtained from the LCC analysis (chapter 8 of the TSD). Since the equipment 

is available in various sizes within each equipment class, DOE used a linear foot of equipment as 

the unit measure for commercial refrigeration equipment. Therefore, the UEC values are 

expressed in kilowatt-hour per linear foot per year (kWh/linear foot/year). The UEC value 

multiplied by the length of a piece of equipment gives the average AEC of that piece of 

equipment. DOE combined the UEC values in Table 10.2.4 with the market shares of efficiency 

levels (base-case scenario) in Table 10.2.3 to obtain shipment-weighted UEC values for each 

efficiency level in the base-case scenario, presented in the column titled “Level 1” in 

Table 10.2.5. The market shares of efficiency levels in the standards-case scenarios were 

obtained by the roll-up scenario (described above in this section) and combined with the UEC 

values in Table 10.2.4 to obtain the shipment-weighted UEC values at all the standards-case 

scenarios, presented in columns titled “Level 2” through “Level 8” in Table 10.2.5. 

10-5
Table 10.2.4 Average Annual Unit Energy Consumption per Linear Foot by Efficiency 

Level 

Equipment 

Class

Average Annual Unit Energy Consumption by Efficiency Level*

kWh/linear foot/year

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M 1,453 1,425 1,348 1,086 1,080 1,066 NA NA

VOP.RC.L 3,292 3,231 3,073 3,057 3,007 NA NA NA

VOP.SC.M 2,800 2,771 2,740 2,701 2,437 2,430 2,415 NA

VCT.RC.M 466 446 232 180 173 171 158 NA

VCT.RC.L 1,118 953 892 876 868 827 NA NA

VCT.SC.M 748 613 331 263 254 242 241 217

VCT.SC.L 2,360 1,745 1,094 1,078 1,009 1,003 980 938

VCT.SC.I 1,758 1,492 1,481 1,401 1,389 1,370 1,304 NA

VCS.SC.M 361 205 192 187 176 163 146 113

VCS.SC.L 892 624 589 574 547 540 532 463

VCS.SC.I 1,623 1,621 1,548 1,538 1,510 1,497 1,403 NA

SVO.RC.M 1,107 1,098 1,030 843 839 829 NA NA

SVO.SC.M 2,439 2,434 2,349 2,314 2,125 2,120 2,110 NA

SOC.RC.M 794 779 760 621 618 613 606 NA

HZO.RC.M 439 431 NA NA NA NA NA NA

HZO.RC.L 1,007 980 NA NA NA NA NA NA

HZO.SC.M 1,350 1,347 1,333 1,322 1,302 NA NA NA

HZO.SC.L 2,748 2,729 NA NA NA NA NA NA

HCT.SC.M 219 195 180 166 80 72 64 48

HCT.SC.L 497 434 394 176 170 164 150 114

HCT.SC.I 352 343 328 305 227 NA NA NA

HCS.SC.M 64 57 52 48 44 36 21 NA

HCS.SC.L 183 163 150 140 127 111 64 NA

PD.SC.M 1,009 569 326 322 316 256 239 207

SOC.SC.M 961 853 822 815 670 666 660 651

* A value of “NA” indicates that there are no associated efficiency levels at this level for this equipment class.

10-6
Table 10.2.5 Shipment-Weighted Average Annual Energy Consumption per Linear Foot by 

Efficiency Level 

Equipment 

Class

Shipment-Weighted Average Annual Energy Consumption by Standard Level*

kWh/linear foot/year

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M 1,317 1,310 1,273 1,085 1,080 1,066 NA NA

VOP.RC.L 3,166 3,150 3,068 3,056 3,007 NA NA NA

VOP.SC.M 2,673 2,667 2,655 2,633 2,435 2,429 2,415 NA

VCT.RC.M 289 286 205 177 172 171 158 NA

VCT.RC.L 940 908 883 874 867 827 NA NA

VCT.SC.M 408 386 289 256 250 241 240 217 

VCT.SC.L 1,267 1,203 1,048 1,042 1,003 999 979 938 

VCT.SC.I 1,482 1,439 1,435 1,393 1,385 1,369 1,304 NA

VCS.SC.M 203 182 178 176 170 161 146 113 

VCS.SC.L 607 575 565 559 544 539 532 463 

VCS.SC.I 1,556 1,556 1,531 1,526 1,507 1,497 1,403 NA

SVO.RC.M 1,010 1,008 975 842 838 829 NA NA

SVO.SC.M 2,321 2,320 2,287 2,266 2,124 2,120 2,110 NA

SOC.RC.M 702 700 693 619 617 613 606 NA

HZO.RC.M 437 431 NA NA NA NA NA NA

HZO.RC.L 1,003 980 NA NA NA NA NA NA

HZO.SC.M 1,338 1,337 1,330 1,322 1,302 NA NA NA

HZO.SC.L 2,743 2,729 NA NA NA NA NA NA

HCT.SC.M 144 141 136 130 77 71 64 48 

HCT.SC.L 272 265 255 169 166 161 150 114 

HCT.SC.I 332 330 322 305 227 NA NA NA

HCS.SC.M 50 49 47 45 42 36 21 NA

HCS.SC.L 145 142 138 132 124 110 64 NA

PD.SC.M 444 382 307 304 301 254 238 207 

SOC.SC.M 783 767 758 754 667 664 660 651 

* A value of “NA” indicates that there are no associated efficiency levels at this level for this equipment class.

10.2.2.2 Shipments

DOE forecasted shipments for the base case and all standards cases. These results are 

presented in TSD chapter 9, Shipments Analysis. 

10.2.2.3 Equipment Stock 

The commercial refrigeration equipment stock in a given year is the total linear footage 

of commercial refrigeration equipment shipped from earlier years that is still in service during 

that year. The NES spreadsheet model keeps track of the total linear footage of commercial 

refrigeration units shipped each year. For equipment with an average lifetime of 10 years, the 

replacement rate per year is 10 percent, and for equipment with 15-year average lifetime, the 

replacement rate is 6.67 percent. For units shipped in 2046, any units still remaining at the end of 

2060 were assumed to be replaced. 

10.2.2.4 National Annual Energy Consumption 

The national AEC is the product of the annual UEC and the stocks of commercial 

refrigeration equipment units of each vintage for each equipment class, as shown in Eq. 10.3. 

10-7
DOE initially calculated the AEC at the site (i.e., electricity in kilowatt-hours consumed 

by the commercial refrigeration equipment units); then DOE calculated primary energy 

consumption from site energy consumption by applying a site-to-source conversion factor. 

10.2.2.5 Site-to-Source Conversion Factor 

DOE calculates primary energy savings (power plant consumption) by applying a factor 

to account for losses associated with the generation, transmission, and distribution of electricity. 

DOE derived annual average site-to-power plant factors based on the version of the National 

Energy Modeling System (NEMS) that corresponds to EIA’s Annual Energy Outlook 2013 

(AEO2013).3 The factors change over time in response to projected changes in the types of 

power plants projected to provide electricity to the nation. Table 10.2.6 shows the site-to-power 

plant factors from 2017 to the end of the projection period. For years after 2040 (the last year in 

the AEO), DOE extrapolated the trend from 2036 through 2040. 

Table 10.2.6 Site-to-Source Conversion Factors* 

Year

Site-to-Source 

Conversion Factor

Btu/kWh

Year

Site-to-Source 

Conversion Factor

Btu/kWh

2017 8,500 2039 8,771 

2018 8,500 2040 8,771 

2019 8,500 2041 8,665 

2020 8,500 2042 8,665 

2021 8,299 2043 8,665 

2022 8,299 2044 8,665 

2023 8,299 2045 8,665 

2024 8,299 2046 8,559 

2025 8,299 2047 8,559 

2026 7,954 2048 8,559 

2027 7,954 2049 8,559 

2028 7,954 2050 8,559 

2029 7,954 2051 8,559 

2030 7,954 2052 8,559 

2031 8,205 2053 8,559 

2032 8,205 2054 8,559 

2033 8,205 2055 8,559 

2034 8,205 2056 8,559 

2035 8,205 2057 8,559 

2036 8,771 2058 8,559 

2037 8,771 2059 8,559 

2038 8,771 2060 8,559 

10.2.2.6 Full-Fuel-Cycle Energy

The full-fuel-cycle (FFC) measure includes point-of-use (site) energy, the energy losses 

associated with generation, transmission, and distribution of electricity, and the energy consumed 

in extracting, processing, and transporting or distributing primary fuels. DOE’s traditional 

approach encompasses site energy and the energy losses associated with generation, 

transmission, and distribution of electricity. To complete the full-fuel-cycle by encompassing the 

energy consumed in extracting, processing, and transporting or distributing primary fuels, which 

10-8
we refer to as “upstream” activities, DOE developed FFC multipliers using the data and 

projections generated by NEMS and published in AEO2013. While the AEO does not provide 

direct calculations of full fuel cycle metrics, it does provide extensive information about the 

energy system, including projections of future oil, natural gas and coal supply, energy use for oil 

and gas field and refinery operations, and fuel consumption and emissions related to electric 

power production. This information can be used to define a set of parameters representing the 

energy intensity of energy production. 

Table 10.2.7 shows the FFC energy multipliers used for commercial refrigeration 

equipment for selected years. The method used to calculate a time series of FFC energy 

multipliers is described in appendix 10D. 

Table 10.2.7 Full-Fuel-Cycle Energy Multipliers (Based on AEO2013)

Fuel 2017 2020 2025 2030 2035 2040 to 2060

Electricity (power plant energy use) 1.042 1.041 1.040 1.040 1.041 1.040

10.3 NET PRESENT VALUE

10.3.1 Net Present Value Definition

The NPV is the value in the present of a time series of costs and savings. The NPV is 

given by the equation: 

NPV = PVS – PVC 

Eq. 10.5 

Where: 

PVS = present value of operating cost savings (energy, repair, and maintenance costs), and

PVC = present value of increased total installed costs (equipment purchase price and installation

cost).

The PVS and PVC are determined according to the following expressions: 

PPPP = ∑tt tt × DDDDtt

Eq. 10.6 

PPPP = ∑tt TT tt × DDDDtt

Eq. 10.7 

Where: 

OCSt = total annual operating cost savings in the year t ($), 

TICt = total annual installed cost increases in the year t ($), 

DFt = discount factor for the year t, and

t = year (PVS is summed over 2017−2060, and PVC is summed over 2017−2046). 

10-9
DOE determined the contribution to PVC for each year, from the compliance date of the

standard (2017) through 2046, discounted to 2013. Likewise, the contribution to PVS was 

determined for each year, from the compliance date of the standard (2017) to the year when units 

purchased in 2017-2046 would be retired. DOE calculated costs and savings as the difference 

between a standards case and a base case. DOE calculated a discount factor from the discount 

rate and the number of years between the “present” (i.e., year to which the sum is being 

discounted) and the year in which the costs and savings occur. DOE calculated the NPV as the 

sum over time of the discounted net savings. 

10.3.2 Net Present Value Inputs

Table 10.3.1 summarizes the inputs to the NPV calculation.

Table 10.3.1 Net Present Value Inputs

Input

Total Annual Installed Cost (TICt)

Total Annual Operating Cost Savings (OCSt)

Discount Factor (DFt)

Present Value of Costs (PVC)

Present Value of Savings (PVS)

10.3.2.1 Total Annual Installed Cost 

The increase in the total annual installed cost for each standards case is equal to the 

annual change in the per-unit installed cost (difference between base case and standards case) 

multiplied by the shipments forecasted in the standards case. The total installed cost includes the 

manufacturer selling price, distribution channel markups, and installation costs. (See chapter 8 of 

the TSD for a discussion of the development of installed cost.) Table 10.3.2 shows the average 

total installed costs per linear foot for each of the equipment classes of commercial refrigeration 

units by efficiency level obtained from the LCC analysis (chapter 8 of the TSD). 

As discussed in section 10.2.2.1, DOE first developed the market shares of efficiency 

levels for the base-case scenario and then used them in combination with the roll-up method 

(section 10.2.2.1) to estimate the market shares of efficiency levels in the standards-case 

scenarios. DOE used these base-case and standards-case market shares of efficiency levels in 

combination with the installation costs in Table 10.3.2 to calculate a weighted-average installed 

costs for each standards-case scenario, which are also referred to as the shipment-weighted 

average installation costs. These results are shown in Table 10.3.3. 

Table 10.3.2 Average Installed Cost per Linear Foot by Efficiency Level

Equipment 

Class

Average Installed Cost per Linear Foot*

2012$/linear foot

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M $786 $791 $803 $902 $908 $1,167 NA NA

VOP.RC.L $835 $841 $876 $883 $1,305 NA NA NA

VOP.SC.M $1,153 $1,157 $1,162 $1,173 $1,296 $1,308 $1,573 NA

VCT.RC.M $946 $948 $996 $1,007 $1,014 $1,016 $1,299 NA

VCT.RC.L $1,054 $1,068 $1,080 $1,086 $1,090 $1,462 NA NA

VCT.SC.M $1,010 $1,021 $1,077 $1,111 $1,116 $1,128 $1,131 $1,414

10-10
Table 10.3.2 (cont)

Equipment 

Class

Average Installed Cost per Linear Foot*

2012$/linear foot

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VCT.SC.L $1,283 $1,302 $1,356 $1,360 $1,393 $1,397 $1,414 $1,795

VCT.SC.I $1,460 $1,481 $1,484 $1,519 $1,525 $1,538 $2,066 NA

VCS.SC.M $740 $751 $752 $753 $757 $762 $774 $1,060

VCS.SC.L $800 $813 $816 $818 $830 $833 $839 $1,223

VCS.SC.I $959 $959 $965 $968 $981 $987 $1,520 NA

SVO.RC.M $694 $695 $712 $788 $793 $959 NA NA

SVO.SC.M $953 $954 $971 $978 $1,078 $1,090 $1,262 NA

SOC.RC.M $1,062 $1,064 $1,066 $1,112 $1,116 $1,131 $1,254 NA

HZO.RC.M $671 $784 NA NA NA NA NA NA

HZO.RC.L $741 $942 NA NA NA NA NA NA

HZO.SC.M $585 $586 $589 $601 $835 NA NA NA

HZO.SC.L $923 $1,063 NA NA NA NA NA NA

HCT.SC.M $539 $540 $541 $543 $568 $572 $584 $740

HCT.SC.L $584 $586 $589 $615 $617 $621 $632 $843

HCT.SC.I $681 $681 $686 $699 $1,012 NA NA NA

HCS.SC.M $464 $465 $466 $468 $471 $481 $593 NA

HCS.SC.L $470 $470 $472 $473 $477 $487 $638 NA

PD.SC.M $1,179 $1,200 $1,248 $1,251 $1,256 $1,317 $1,339 $1,739

SOC.SC.M $1,013 $1,022 $1,026 $1,028 $1,074 $1,078 $1,092 $1,216

* A value of “NA” indicates that there are no associated efficiency levels at this level for this equipment class. 

10-11
Table 10.3.3 Shipment-Weighted Average Total Installed Cost per Linear Foot by 

Efficiency Level

Equipment 

Class

Shipment-Weighted Average Total Installed Cost per Linear Foot*

2012$/linear foot

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M $830 $831 $837 $908 $913 $1,167 NA NA

VOP.RC.L $867 $869 $887 $892 $1,305 NA NA NA

VOP.SC.M $1,205 $1,206 $1,208 $1,214 $1,306 $1,317 $1,573 NA

VCT.RC.M $990 $990 $1,008 $1,014 $1,019 $1,021 $1,299 NA

VCT.RC.L $1,082 $1,085 $1,090 $1,093 $1,097 $1,462 NA NA

VCT.SC.M $1,083 $1,085 $1,104 $1,121 $1,124 $1,133 $1,135 $1,414

VCT.SC.L $1,369 $1,371 $1,384 $1,386 $1,405 $1,407 $1,422 $1,795

VCT.SC.I $1,508 $1,511 $1,513 $1,531 $1,535 $1,545 $2,066 NA

VCS.SC.M $758 $759 $760 $760 $762 $766 $777 $1,060

VCS.SC.L $824 $826 $826 $827 $834 $837 $841 $1,223

VCS.SC.I $973 $973 $975 $977 $985 $990 $1,520 NA

SVO.RC.M $731 $731 $740 $794 $798 $959 NA NA

SVO.SC.M $1,000 $1,000 $1,007 $1,011 $1,086 $1,096 $1,262 NA

SOC.RC.M $1,097 $1,097 $1,098 $1,123 $1,126 $1,137 $1,254 NA

HZO.RC.M $696 $784 NA NA NA NA NA NA

HZO.RC.L $769 $942 NA NA NA NA NA NA

HZO.SC.M $596 $596 $597 $607 $835 NA NA NA

HZO.SC.L $962 $1,063 NA NA NA NA NA NA

HCT.SC.M $556 $556 $556 $557 $573 $576 $586 $740

HCT.SC.L $610 $610 $611 $621 $622 $625 $635 $843

HCT.SC.I $690 $690 $692 $702 $1,012 NA NA NA

HCS.SC.M $471 $471 $472 $473 $475 $484 $593 NA

HCS.SC.L $477 $477 $477 $478 $481 $489 $638 NA

PD.SC.M $1,253 $1,256 $1,271 $1,273 $1,276 $1,323 $1,343 $1,739

SOC.SC.M $1,052 $1,053 $1,055 $1,056 $1,083 $1,086 $1,098 $1,216

* A value of “NA” indicates that there are no associated efficiency levels at this level for this equipment class.

10.3.2.2 MPC Price Trends

In prior energy conservation standards rulemakings, DOE estimated the total installed 

costs per unit for equipment, and then assumed that costs remain constant throughout the 

analysis period. This assumption is conservative because installed costs tend to decrease over 

time. In 2011, DOE issued a notice of data availability (NODA) titled Equipment Price 

Forecasting in Energy Conservation Standards Analysis. 76 FR 9696 (Feb. 22, 2011). In the 

NODA, DOE proposed a methodology for analyzing whether equipment prices have trended 

downward in real terms. The methodology examines so-called experiential learning, wherein, 

with ever-increasing experience with the production of a product, manufacturers are able to 

reduce their production costs through innovations in technology and process. 

To account for increased efficiency in the CRE manufacturing process over time, DOE 

used a price forecast methodology based on experiential learning (see appendixes 8D and 10B 

for more information on experiential learning). To project the manufacturer selling price of a 

unit, DOE multiplied the selling price by a coefficient specific to the year of purchase relative to 

the year in which prices were estimated (2012). The coefficient accounts for the effects of 

experiential learning.

10-12
Table 10.3.4 summarizes four learning scenarios that DOE developed. One scenario, 

constant prices, is consistent with the analyses DOE historically performed. In this scenario, 

prices are held constant, so the learning coefficient is 1.00. DOE developed three scenarios–the 

high, reference, and low learning scenarios–for this rulemaking from historical CRE shipments 

and Producer Price Index data. Appendix 10B of this TSD documents the development of the 

price learning scenarios. For this notice, DOE used the historically derived reference scenario for 

the results presented in this chapter and in the NOPR. 

Table 10.3.4 Price Trend Scenarios

Year Constant Prices Historically Derived Price Trends

High Reference Low

2012 100.00% 100.00% 100.00% 100.00%

2013 100.00% 100.03% 99.89% 99.75%

2014 100.00% 100.06% 99.78% 99.50%

2015 100.00% 100.10% 99.67% 99.25%

2016 100.00% 100.13% 99.56% 99.00%

2017 100.00% 100.16% 99.45% 98.75%

2018 100.00% 100.19% 99.34% 98.50%

2019 100.00% 100.23% 99.23% 98.24%

2020 100.00% 100.26% 99.12% 98.00%

2021 100.00% 100.29% 99.02% 97.77%

2022 100.00% 100.32% 98.92% 97.54%

2023 100.00% 100.35% 98.82% 97.32%

2024 100.00% 100.38% 98.72% 97.10%

2025 100.00% 100.41% 98.62% 96.87%

2026 100.00% 100.44% 98.52% 96.65%

2027 100.00% 100.47% 98.43% 96.43%

2028 100.00% 100.50% 98.33% 96.20%

2029 100.00% 100.53% 98.23% 95.98%

2030 100.00% 100.55% 98.13% 95.76%

2031 100.00% 100.58% 98.03% 95.55%

2032 100.00% 100.61% 97.94% 95.34%

2033 100.00% 100.64% 97.85% 95.13%

2034 100.00% 100.67% 97.76% 94.93%

2035 100.00% 100.69% 97.66% 94.73%

2036 100.00% 100.72% 97.57% 94.52%

2037 100.00% 100.75% 97.48% 94.32%

2038 100.00% 100.78% 97.39% 94.11%

2039 100.00% 100.80% 97.30% 93.91%

2040 100.00% 100.83% 97.21% 93.71%

2041 100.00% 100.86% 97.12% 93.52%

2042 100.00% 100.89% 97.03% 93.32%

2043 100.00% 100.91% 96.94% 93.13%

2044 100.00% 100.94% 96.86% 92.94%

2045 100.00% 100.97% 96.77% 92.75%

2046 100.00% 100.99% 96.68% 92.56%

10-13
10.3.2.3 Light Technology Price Trends

As discussed in the engineering (chapter 5) and life-cycle cost (chapter 8) chapters of this 

TSD, DOE assumed that light-emitting diode (LED) lighting technologies are declining in price.

DOE incorporated the price projections into the NIA in the form of reductions in the cost 

of lighting for applicable equipment and CSL combination. Table 10.3.5 shows the normalized 

LED price deflators used to reduce the price of the LED design option where applicable. For the 

period of 2017 through 2030, the cost of equipment with LED lighting included was reduced by 

an amount corresponding to a reduction in LED prices following the deflators shown on 

Table 10.3.5. 

Table 10.3.5 LED price deflators used in the NOPR analysis.

Year Normalized 

to 2013

Normalized 

to 2017 Year Normalized to 2013

Normalized 

to 2017

2010 2.998 5.652 2021 0.361 0.681

2011 1.799 3.392 2022 0.335 0.631

2012 1.285 2.423 2023 0.312 0.588

2013 1.000 1.885 2024 0.292 0.550

2014 0.819 1.543 2025 0.274 0.517

2015 0.693 1.306 2026 0.259 0.488

2016 0.601 1.133 2027 0.245 0.462

2017 0.530 1.000 2028 0.232 0.438

2018 0.475 0.895 2029 0.221 0.417

2019 0.430 0.810 2030 0.211 0.398

2020 0.393 0.740 2031-2046* 0.211 0.398

* DOE did not have data available to project prices beyond 2030. Therefore, for the NOPR analysis, it was 

assumed that the LED prices stay constant after 2030.

The reductions in lighting maintenance costs due to reduction in LED prices for 

equipment installed in 2017 to 2030 were also calculated and appropriately deducted from the 

lighting maintenance costs.

10.3.2.4 Total Annual Operating Cost Savings 

The annual operating cost savings to the nation are equal to the change in the annual

operating costs (difference between base case and standards case) per unit multiplied by the 

shipments forecasted in the standards case. The annual operating cost includes energy, repair, 

and maintenance costs.

Annual Electricity Cost Savings. As described in TSD chapter 8, Life-Cycle Cost and 

Payback Period Analysis, DOE calculated annual electricity costs based on average state-level 

commercial electricity prices. To calculate annual energy cost savings for a particular equipment 

class in a given year, DOE first calculated the annual energy costs in each forecast year at the 

base-case scenario and each standards-case scenario by multiplying the weighted-average energy 

consumption at each efficiency level from Table 10.2.5 by the linear feet of equipment stock in 

the equipment class in each year, and then by the sales-weighted national average electricity 

prices for the seven building types in TSD chapter 8. To determine energy savings at each 

standards-case scenario, the national energy costs at each standards-case scenario were then 

subtracted from the national energy costs at the base-case scenario. Because projections of the 

10-14
stock of commercial refrigeration equipment (expressed in linear feet) are the primary driver 

used to estimate future commercial refrigeration equipment shipments, DOE calculated the 

national energy cost by expressing the AEC on a linear-footage basis. 

Annual Repair Costs. DOE based average annual repair costs on the value of the 

components of the equipment at each efficiency level (see TSD chapter 8). Table 10.3.6 shows 

the average repair costs per linear foot for each efficiency level for the equipment classes 

analyzed. Table 10.3.7 presents the shipment-weighted average annual repair costs per linear 

foot for the base-case and all standards-case scenarios for each equipment class.

Table 10.3.6 Average Annual Repair Cost per Linear Foot by Efficiency Level

Equipment 

Class

Average Annual Repair Cost per Linear Foot*

2012$/linear foot

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M $32.29 $32.29 $32.41 $32.41 $32.41 $32.41 NA NA

VOP.RC.L $37.52 $37.58 $37.58 $37.58 $37.58 NA NA NA

VOP.SC.M $56.58 $56.58 $56.85 $57.43 $57.43 $57.43 $57.43 NA

VCT.RC.M $42.09 $42.29 $42.79 $42.79 $42.79 $42.81 $42.81 NA

VCT.RC.L $48.59 $48.74 $48.74 $48.74 $48.78 $48.78 NA NA

VCT.SC.M $47.40 $48.20 $48.95 $48.95 $49.24 $49.24 $49.26 $49.26

VCT.SC.L $63.80 $64.19 $65.54 $65.59 $65.59 $65.77 $66.06 $66.06

VCT.SC.I $75.54 $75.76 $75.95 $75.95 $76.25 $76.25 $76.25 NA

VCS.SC.M $30.24 $31.20 $31.28 $31.29 $31.47 $31.76 $31.76 $31.76

VCS.SC.L $35.28 $36.31 $36.49 $36.51 $36.51 $36.69 $36.98 $36.98

VCS.SC.I $46.32 $46.34 $46.62 $46.81 $46.81 $47.12 $47.12 NA

SVO.RC.M $26.94 $26.95 $26.95 $26.95 $26.95 $26.95 NA NA

SVO.SC.M $43.87 $43.87 $43.87 $44.26 $44.26 $44.26 $44.26 NA

SOC.RC.M $45.62 $45.78 $45.81 $45.81 $45.81 $45.96 $45.96 NA

HZO.RC.M $25.59 $25.59 NA NA NA NA NA NA

HZO.RC.L $29.15 $29.15 NA NA NA NA NA NA

HZO.SC.M $23.54 $23.56 $23.73 $23.73 $23.73 NA NA NA

HZO.SC.L $44.57 $44.57 NA NA NA NA NA NA

HCT.SC.M $17.81 $17.82 $17.90 $17.99 $18.26 $18.46 $18.46 $18.46

HCT.SC.L $21.77 $21.79 $21.95 $22.22 $22.32 $22.52 $22.52 $22.52

HCT.SC.I $26.28 $26.29 $26.52 $26.52 $26.52 NA NA NA

HCS.SC.M $14.65 $14.66 $14.73 $14.81 $15.00 $15.00 $15.00 NA

HCS.SC.L $14.90 $14.90 $14.97 $15.06 $15.24 $15.24 $15.24 NA

PD.SC.M $49.34 $50.43 $50.94 $51.10 $51.36 $51.36 $51.39 $51.39

SOC.SC.M $50.42 $51.05 $51.14 $51.25 $51.25 $51.25 $51.40 $51.40

* A value of “NA” indicates that there are no associated efficiency levels at this level for this equipment class. 

10-15
Table 10.3.7 Shipment-Weighted Average Annual Repair Cost per Linear Foot by 

Efficiency Level

Equipment 

Class

Shipment-Weighted Average Annual Repair Cost per Linear Foot*

2012$/linear foot

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M $32.35 $32.35 $32.41 $32.41 $32.41 $32.41 NA NA

VOP.RC.L $37.56 $37.58 $37.58 $37.58 $37.58 NA NA NA

VOP.SC.M $57.00 $57.00 $57.10 $57.43 $57.43 $57.43 $57.43 NA

VCT.RC.M $42.57 $42.60 $42.79 $42.79 $42.79 $42.81 $42.81 NA

VCT.RC.L $48.72 $48.75 $48.75 $48.75 $48.78 $48.78 NA NA

VCT.SC.M $48.67 $48.81 $49.06 $49.06 $49.24 $49.24 $49.26 $49.26

VCT.SC.L $65.30 $65.34 $65.67 $65.69 $65.69 $65.81 $66.06 $66.06

VCT.SC.I $75.94 $75.98 $76.05 $76.05 $76.25 $76.25 $76.25 NA

VCS.SC.M $31.30 $31.42 $31.44 $31.45 $31.55 $31.76 $31.76 $31.76

VCS.SC.L $36.42 $36.54 $36.59 $36.60 $36.60 $36.73 $36.98 $36.98

VCS.SC.I $46.67 $46.67 $46.76 $46.86 $46.86 $47.12 $47.12 NA

SVO.RC.M $26.95 $26.95 $26.95 $26.95 $26.95 $26.95 NA NA

SVO.SC.M $44.03 $44.04 $44.04 $44.26 $44.26 $44.26 $44.26 NA

SOC.RC.M $45.79 $45.82 $45.83 $45.83 $45.83 $45.96 $45.96 NA

HZO.RC.M $25.59 $25.59 NA NA NA NA NA NA

HZO.RC.L $29.15 $29.15 NA NA NA NA NA NA

HZO.SC.M $23.64 $23.65 $23.73 $23.73 $23.73 NA NA NA

HZO.SC.L $44.57 $44.57 NA NA NA NA NA NA

HCT.SC.M $18.08 $18.08 $18.10 $18.15 $18.31 $18.46 $18.46 $18.46

HCT.SC.L $22.18 $22.18 $22.22 $22.33 $22.38 $22.52 $22.52 $22.52

HCT.SC.I $26.40 $26.40 $26.52 $26.52 $26.52 NA NA NA

HCS.SC.M $14.80 $14.80 $14.83 $14.87 $15.00 $15.00 $15.00 NA

HCS.SC.L $15.05 $15.05 $15.07 $15.12 $15.24 $15.24 $15.24 NA

PD.SC.M $50.81 $50.97 $51.12 $51.20 $51.37 $51.37 $51.39 $51.39

SOC.SC.M $51.11 $51.20 $51.23 $51.28 $51.28 $51.28 $51.40 $51.40

* A value of “NA” indicates that there are no associated efficiency levels at this level for this equipment class. 

Annual Maintenance Costs. DOE determined average annual maintenance costs in two 

parts. The first was a preventative maintenance cost of $35/year for self-contained units and 

$220/year for remote condensing units (see TSD chapter 8). The second was a lighting 

maintenance cost for equipment classes that feature lights within the equipment. The lighting 

cost varied with efficiency level because the costs were directly proportional to the original 

equipment manufacturer costs of the lighting (see TSD chapter 8). Table 10.3.8 shows the 

resulting annual maintenance costs per linear foot by efficiency level. Table 10.3.9 shows the 

corresponding shipments-weighted annual maintenance cost per linear foot by efficiency level.

10-16
Table 10.3.8 Average Annual Maintenance Cost per Linear Foot by Efficiency Level 

Equipment 

Class

Average Annual Maintenance Cost per Linear Foot*

2012$/linear foot

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M $26.65 $26.65 $26.65 $28.54 $28.54 $28.54 NA NA

VOP.RC.L $22.08 $22.08 $21.65 $21.65 $21.65 NA NA NA

VOP.SC.M $22.66 $22.66 $22.66 $22.66 $24.90 $24.90 $24.90 NA

VCT.RC.M $20.14 $20.14 $20.14 $20.14 $20.14 $20.14 $20.14 NA

VCT.RC.L $20.11 $20.11 $20.11 $20.11 $20.11 $20.11 NA NA

VCT.SC.M $13.22 $13.22 $13.22 $13.22 $13.22 $13.22 $13.22 $13.22

VCT.SC.L $17.45 $13.22 $13.22 $13.22 $13.22 $13.22 $13.22 $13.22

VCT.SC.I $13.83 $13.83 $13.83 $13.83 $13.83 $13.83 $13.83 NA

VCS.SC.M $7.92 $7.92 $7.92 $7.92 $7.92 $7.92 $7.92 $7.92

VCS.SC.L $7.92 $7.92 $7.92 $7.92 $7.92 $7.92 $7.92 $7.92

VCS.SC.I $8.28 $8.28 $8.28 $8.28 $8.28 $8.28 $8.28 NA

SVO.RC.M $24.36 $24.36 $24.36 $26.36 $26.36 $26.36 NA NA

SVO.SC.M $18.53 $18.53 $18.53 $18.53 $21.34 $21.34 $21.34 NA

SOC.RC.M $24.36 $24.36 $24.36 $24.63 $24.63 $24.63 $24.63 NA

HZO.RC.M $18.66 $18.66 NA NA NA NA NA NA

HZO.RC.L $18.66 $18.66 NA NA NA NA NA NA

HZO.SC.M $8.91 $8.91 $8.91 $8.91 $8.91 NA NA NA

HZO.SC.L $8.91 $8.91 NA NA NA NA NA NA

HCT.SC.M $9.37 $9.37 $9.37 $9.37 $9.37 $9.37 $9.37 $9.37

HCT.SC.L $9.37 $9.37 $9.37 $9.37 $9.37 $9.37 $9.37 $9.37

HCT.SC.I $10.42 $10.42 $10.42 $10.42 $10.42 NA NA NA

HCS.SC.M $8.48 $8.48 $8.48 $8.48 $8.48 $8.48 $8.48 NA

HCS.SC.L $8.48 $8.48 $8.48 $8.48 $8.48 $8.48 $8.48 NA

PD.SC.M $19.34 $20.03 $20.03 $20.03 $20.03 $20.03 $20.03 $20.03

SOC.SC.M $10.73 $12.12 $12.12 $12.12 $12.61 $12.61 $12.61 $12.61

* A value of “NA” indicates that there are no associated efficiency levels at this level for this equipment class. 

10-17
Table 10.3.9 Shipment-Weighted Average Annual Maintenance Cost per Linear Foot by 

Efficiency Level 

Equipment 

Class

Shipment-Weighted Average Annual Maintenance Cost per Linear Foot*

2012$/linear foot

Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M $27.18 $27.18 $27.18 $28.54 $28.54 $28.54 NA NA

VOP.RC.L $21.87 $21.87 $21.65 $21.65 $21.65 NA NA NA

VOP.SC.M $23.22 $23.22 $23.22 $23.22 $24.90 $24.90 $24.90 NA

VCT.RC.M $20.14 $20.14 $20.14 $20.14 $20.14 $20.14 $20.14 NA

VCT.RC.L $20.11 $20.11 $20.11 $20.11 $20.11 $20.11 NA NA

VCT.SC.M $13.22 $13.22 $13.22 $13.22 $13.22 $13.22 $13.22 $13.22

VCT.SC.L $13.66 $13.22 $13.22 $13.22 $13.22 $13.22 $13.22 $13.22

VCT.SC.I $13.83 $13.83 $13.83 $13.83 $13.83 $13.83 $13.83 NA

VCS.SC.M $7.92 $7.92 $7.92 $7.92 $7.92 $7.92 $7.92 $7.92

VCS.SC.L $7.92 $7.92 $7.92 $7.92 $7.92 $7.92 $7.92 $7.92

VCS.SC.I $8.28 $8.28 $8.28 $8.28 $8.28 $8.28 $8.28 NA

SVO.RC.M $24.94 $24.94 $24.94 $26.36 $26.36 $26.36 NA NA

SVO.SC.M $19.22 $19.22 $19.22 $19.22 $21.34 $21.34 $21.34 NA

SOC.RC.M $24.49 $24.49 $24.49 $24.63 $24.63 $24.63 $24.63 NA

HZO.RC.M $18.66 $18.66 NA NA NA NA NA NA

HZO.RC.L $18.66 $18.66 NA NA NA NA NA NA

HZO.SC.M $8.91 $8.91 $8.91 $8.91 $8.91 NA NA NA

HZO.SC.L $8.91 $8.91 NA NA NA NA NA NA

HCT.SC.M $9.37 $9.37 $9.37 $9.37 $9.37 $9.37 $9.37 $9.37

HCT.SC.L $9.37 $9.37 $9.37 $9.37 $9.37 $9.37 $9.37 $9.37

HCT.SC.I $10.42 $10.42 $10.42 $10.42 $10.42 NA NA NA

HCS.SC.M $8.48 $8.48 $8.48 $8.48 $8.48 $8.48 $8.48 NA

HCS.SC.L $8.48 $8.48 $8.48 $8.48 $8.48 $8.48 $8.48 NA

PD.SC.M $19.93 $20.03 $20.03 $20.03 $20.03 $20.03 $20.03 $20.03

SOC.SC.M $12.12 $12.32 $12.32 $12.32 $12.61 $12.61 $12.61 $12.61

* A value of “NA” indicates that there are no associated efficiency levels at this level for this equipment class.

10.3.2.5 Discount Factor 

DOE multiplied monetary values in future years by the discount factor in order to 

determine the present value of costs and savings. The discount factor (DF) is described by the 

equation: 

DDDD = 1

(1+ )�tt−ttpp�

Eq. 10.8 

Where: 

r = discount rate,

t = year of the monetary value, and

tp = year in which the present value is being determined.

DOE estimated national impacts with both a 3-percent and a 7-percent real discount rate 

as the average real rate of return on private investment in the U.S. economy. These discount rates 

are used in accordance with the Office of Management and Budget (OMB) guidance to Federal 

10-18
agencies on the development of regulatory analysis (OMB Circular A-4, September 17, 2003), 

and section E, “Identifying and Measuring Benefits and Costs,” therein. DOE defined the present 

year as 2013 for the NOPR. 

10.3.2.6 Present Value of Costs 

The present value of increased installed costs is the annual installed cost increase in each

year (i.e., the difference between the standards case and base case) discounted to the present year

and summed for the time period over which DOE is considering the installation of commercial 

refrigeration equipment (i.e., from the compliance date of standards, 2017, through the year 

2046).

The increase in total installed cost refers to both equipment cost and installation cost 

associated with the higher energy efficiency of commercial refrigeration units purchased in the 

standards case compared to the base case. DOE calculated annual installed costs as the difference 

in total installed cost for new equipment purchased each year, multiplied by the shipments in the 

standards case.

10.3.2.7 Present Value of Savings 

The present value of the operating cost savings is the annual operating cost savings 

(i.e., the difference between the base case and standards case) discounted to the present year, and 

summed over the period from the compliance date of the standard, 2017, to the time when the 

last unit installed in 2017-2046 is retired from service. Savings are decreases in operating costs 

(including electricity, repair, and maintenance) associated with the higher energy efficiency of 

commercial refrigeration units purchased in the standards case compared to the base case. Total 

annual operating cost savings are the savings per unit multiplied by the number of units of each 

vintage surviving in a particular year. Equipment consumes energy over its entire lifetime, and 

for units purchased in 2046, the present value of savings includes energy consumed until the unit 

is retired from service at the end of 2060. 

10.4 NATIONAL ENERGY SAVINGS AND NET PRESENT VALUE RESULTS

The NES spreadsheet model provides estimates of the NES and NPV due to various 

efficiency levels. The inputs to the NES spreadsheet are discussed in sections 10.2.2 and 10.3.2. 

DOE generated the NES and NPV results using a Microsoft Excelspreadsheet, which is available 

at http://www1.eere.energy.gov/buildings/appliance_standards/product.aspx/productid/52. 

Details and instructions for using the spreadsheet are provided in appendix 10A. 

For this NOPR analysis, DOE selected five trial standard level (TSL) groupings based on 

the NPV values calculated for each CSL. Appendix 10C discusses the criteria used for selection 

of TSLs. The NIA results in this section are presented for CSLs and TSLs. 

10.4.1 National Energy Savings and Net Present Value Input Summary

Table 10.4.1 summarizes the inputs to the NES spreadsheet model. For each input, a brief

description of the data source is given. 

10-19
Table 10.4.1 NES and NPV Inputs

Input Data Description

Shipments Annual shipments from shipments model (see TSD chapter 9, Shipments Analysis).

Effective Date of Standard 2017

Base-Case Efficiencies Distribution of base-case shipments by efficiency level.

Standards-Case Efficiencies Distribution of shipments by efficiency level for each standards case. Standardscase annual market shares by efficiency level remain constant over time for the 

base case and each standards case.

Annual Energy Consumption 

per Linear Foot

Annual weighted-average values are a function of efficiency level (established in 

the engineering analysis, TSD chapter 5) converted to a per-linear-foot basis.

Total Installed Cost per 

Linear Foot 

Annual weighted-average values of installed cost are a function of efficiency level

(see TSD chapter 8), expressed on a per-linear-foot basis.

Repair Cost per Linear Foot Annual weighted-average values of repair costs are constant with efficiency level

(see TSD chapter 8). Converted to a per-linear-foot basis.

Maintenance Cost per Linear 

Foot

Annual weighted-average value equals $35 for self-contained and $220 for remote 

condensing units (see TSD chapter 8), plus lighting maintenance cost. Converted to 

a per-linear-foot basis.

Escalation of Electricity

Prices 

EIA AEO2013 forecasts (to 2040) and extrapolation for 2040 and beyond (see TSD 

chapter 8).

Electricity Site-to-Source 

Conversion

Conversion varies yearly and is generated by DOE’s version of the EIA NEMS 

program (a time series conversion factor; includes electric generation, transmission, 

and distribution losses).

Full-fuel-cycle conversion 

factors

Conversion varies yearly and is generated by DOE’s version of the EIA NEMS 

program (a time series conversion factor to account for the energy consumed in 

extracting, processing, and transporting or delivering primary fuels to electricity 

generation stations).

Discount Rate 3- and 7-percent real

Present Year Future costs are discounted to year 2013.

10.4.2 National Energy Savings Results 

This section provides NES results for each energy consumption level considered for the 

25 equipment classes of commercial refrigeration equipment DOE directly analyzed. Results are 

cumulative to 2060 and are shown as primary energy savings in quads. Inputs to the NES 

spreadsheet model are based on weighted-average values, yielding results that are discrete point 

values, rather than a distribution of values as in the LCC analysis. 

Table 10.4.2 shows the NES results, without FFC, for all CSLs for all equipment classes. 

Table 10.4.3 shows the NES results, without FFC, by TSLs. Table 10.4.4 shows the NES results, 

with FFC, for all CSLs for all equipment classes. Table 10.4.5 shows the NES results, with FFC, 

by TSLs. Table 10.4.6 presents the NES values with FFC at the five TSLs expressed as a 

percentage of total base-case energy usage of the equipment stock in the period 2017–2060. 

10-20
Table 10.4.2 Cumulative National Energy Savings, without Full-Fuel-Cycle, by CSL for 

Equipment Purchased in 2017–2046 

Equipment 

Class

National Energy Savings by CSL*,**

quads

Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M 0.007 0.045 0.238 0.244 0.257 NA NA

VOP.RC.L 0.001 0.005 0.006 0.009 NA NA NA

VOP.SC.M 0.000 0.001 0.003 0.017 0.018 0.019 NA

VCT.RC.M 0.000 0.007 0.009 0.009 0.009 0.010 NA

VCT.RC.L 0.034 0.061 0.071 0.078 0.121 NA NA

VCT.SC.M 0.011 0.057 0.074 0.077 0.081 0.081 0.092

VCT.SC.L 0.002 0.005 0.005 0.006 0.006 0.007 0.008

VCT.SC.I 0.001 0.001 0.002 0.003 0.003 0.005 NA

VCS.SC.M 0.040 0.047 0.052 0.064 0.082 0.111 0.176

VCS.SC.L 0.032 0.042 0.048 0.064 0.068 0.076 0.144

VCS.SC.I 0.000 0.000 0.000 0.000 0.000 0.001 NA

SVO.RC.M 0.002 0.029 0.139 0.142 0.150 NA NA

SVO.SC.M 0.000 0.004 0.006 0.021 0.022 0.023 NA

SOC.RC.M 0.001 0.002 0.017 0.018 0.019 0.020 NA

HZO.RC.M 0.001 NA NA NA NA NA NA

HZO.RC.L 0.009 NA NA NA NA NA NA

HZO.SC.M 0.000 0.000 0.000 0.000 NA NA NA

HZO.SC.L 0.000 NA NA NA NA NA NA

HCT.SC.M 0.000 0.000 0.000 0.000 0.000 0.000 0.001

HCT.SC.L 0.000 0.001 0.004 0.004 0.004 0.005 0.006

HCT.SC.I 0.000 0.000 0.001 0.005 NA NA NA

HCS.SC.M 0.001 0.001 0.002 0.004 0.006 0.013 NA

HCS.SC.L 0.000 0.000 0.001 0.001 0.002 0.005 NA

PD.SC.M 0.047 0.105 0.106 0.109 0.145 0.157 0.181

SOC.SC.M 0.000 0.000 0.000 0.002 0.002 0.002 0.002

* A value of “NA” indicates that there are no associated efficiency levels at this level for this equipment class. 

** 0.000 indicates savings are less than 0.0005 quads.

10-21
Table 10.4.3 Cumulative National Energy Savings, without Full-Fuel-Cycle, by TSL for 

Equipment Purchased in 2017–2046 

Equipment Class

National Energy Savings by TSL*

quads

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VOP.RC.M 0.007 0.045 0.238 0.244 0.257

VOP.RC.L 0.001 0.005 0.006 0.006 0.009

VOP.SC.M 0.001 0.003 0.017 0.018 0.019

VCT.RC.M 0.000 0.007 0.009 0.009 0.010

VCT.RC.L 0.061 0.071 0.078 0.078 0.121

VCT.SC.M 0.011 0.057 0.074 0.081 0.092

VCT.SC.L 0.005 0.005 0.006 0.007 0.008

VCT.SC.I 0.001 0.003 0.003 0.003 0.005

VCS.SC.M 0.047 0.064 0.111 0.111 0.176

VCS.SC.L 0.042 0.064 0.068 0.076 0.144

VCS.SC.I 0.000 0.000 0.000 0.000 0.001

SVO.RC.M 0.002 0.029 0.139 0.142 0.150

SVO.SC.M 0.004 0.006 0.021 0.022 0.023

SOC.RC.M 0.001 0.002 0.017 0.019 0.020

HZO.RC.M – – – – 0.001

HZO.RC.L – – – – 0.009

HZO.SC.M 0.000 0.000 0.000 0.000 0.000

HZO.SC.L – – – – 0.000

HCT.SC.M 0.000 0.000 0.000 0.000 0.001

HCT.SC.L 0.001 0.004 0.004 0.005 0.006

HCT.SC.I 0.000 0.000 0.001 0.001 0.005

HCS.SC.M 0.001 0.001 0.002 0.004 0.013

HCS.SC.L 0.001 0.001 0.002 0.002 0.005

PD.SC.M 0.047 0.047 0.105 0.157 0.181

SOC.SC.M 0.000 0.000 0.002 0.002 0.002

Net NES 0.233 0.416 0.905 0.985 1.257

“–” represents zero energy savings, since TSLs 1 through 4 for the equipment classes HZO.RC.M, HZO.RC.L and 

HZO.SC.L are associated with the baseline efficiency level.

*A value of 0.000 means NES values are less than 0.0005 quads.

Table 10.4.4 Cumulative National Energy Savings, with Full-Fuel-Cycle, by CSL for 

Equipment purchased in 2017–2046 

Equipment 

Class 

National Energy Savings (quads) by Standard Level*

Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M 0.007 0.046 0.242 0.248 0.262 NA NA

VOP.RC.L 0.001 0.005 0.006 0.009 NA NA NA

VOP.SC.M 0.000 0.001 0.003 0.018 0.018 0.019 NA

VCT.RC.M 0.000 0.007 0.009 0.009 0.009 0.010 NA

VCT.RC.L 0.035 0.062 0.072 0.079 0.123 NA NA

VCT.SC.M 0.011 0.058 0.075 0.078 0.082 0.083 0.094

VCT.SC.L 0.002 0.005 0.006 0.006 0.007 0.007 0.008

VCT.SC.I 0.001 0.001 0.002 0.003 0.003 0.005 NA

VCS.SC.M 0.041 0.048 0.053 0.065 0.083 0.112 0.179

VCS.SC.L 0.033 0.043 0.049 0.065 0.070 0.077 0.146

VCS.SC.I 0.000 0.000 0.000 0.000 0.000 0.001 NA

SVO.RC.M 0.002 0.030 0.141 0.144 0.152 NA NA

SVO.SC.M 0.000 0.004 0.006 0.022 0.022 0.023 NA

SOC.RC.M 0.001 0.002 0.018 0.018 0.019 0.020 NA

10-22
Table 10.4.4 (cont)

Equipment 

Class 

National Energy Savings (quads) by Standard Level*

Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

HZO.RC.M 0.001 NA NA NA NA NA NA

HZO.RC.L 0.009 NA NA NA NA NA NA

HZO.SC.M 0.000 0.000 0.000 0.000 NA NA NA

HZO.SC.L 0.000 NA NA NA NA NA NA

HCT.SC.M 0.000 0.000 0.000 0.000 0.000 0.000 0.001

HCT.SC.L 0.000 0.001 0.004 0.004 0.004 0.005 0.006

HCT.SC.I 0.000 0.000 0.001 0.005 NA NA NA

HCS.SC.M 0.001 0.001 0.002 0.004 0.006 0.013 NA

HCS.SC.L 0.000 0.000 0.001 0.001 0.002 0.005 NA

PD.SC.M 0.048 0.106 0.108 0.111 0.147 0.159 0.184

SOC.SC.M 0.000 0.000 0.000 0.002 0.002 0.002 0.002

*A value of 0.000 means NES values are less than 0.0005 quads.

Table 10.4.5 Cumulative Energy Savings, with Full-Fuel-Cycle, by TSL for Equipment 

Purchased in 2017–2046 

Equipment Class

Standard Level*

TSL1 TSL2 TSL3 TSL4 TSL5

VOP.RC.M 0.007 0.046 0.242 0.248 0.262

VOP.RC.L 0.001 0.005 0.006 0.006 0.009

VOP.SC.M 0.001 0.003 0.018 0.018 0.019

VCT.RC.M 0.000 0.007 0.009 0.009 0.010

VCT.RC.L 0.062 0.072 0.079 0.079 0.123

VCT.SC.M 0.011 0.058 0.075 0.083 0.094

VCT.SC.L 0.005 0.006 0.007 0.007 0.008

VCT.SC.I 0.001 0.003 0.003 0.003 0.005

VCS.SC.M 0.048 0.065 0.112 0.112 0.179

VCS.SC.L 0.043 0.065 0.070 0.077 0.146

VCS.SC.I 0.000 0.000 0.000 0.000 0.001

SVO.RC.M 0.002 0.030 0.141 0.144 0.152

SVO.SC.M 0.004 0.006 0.022 0.022 0.023

SOC.RC.M 0.001 0.002 0.018 0.019 0.020

HZO.RC.M – – – – 0.001

HZO.RC.L – – – – 0.009

HZO.SC.M 0.000 0.000 0.000 0.000 0.000

HZO.SC.L – – – – 0.000

HCT.SC.M 0.000 0.000 0.000 0.000 0.001

HCT.SC.L 0.001 0.004 0.004 0.005 0.006

HCT.SC.I 0.000 0.000 0.001 0.001 0.005

HCS.SC.M 0.001 0.001 0.002 0.004 0.013

HCS.SC.L 0.001 0.001 0.002 0.002 0.005

PD.SC.M 0.048 0.048 0.106 0.159 0.184

SOC.SC.M 0.000 0.000 0.002 0.002 0.002

Total 0.236 0.422 0.920 1.001 1.278

“–” represents zero energy savings, since TSLs 1 through 4 for the equipment classes HZO.RC.M, 

HZO.RC.L and HZO.SC.L are associated with the baseline efficiency level.

*A value of 0.000 means NES values are less than 0.0005 quads.

10-23
Table 10.4.6 Cumulative Energy Savings, with Full-Fuel-Cycle, by TSL Expressed as a 

Percentage of Cumulative Base-Case Energy Usage of the Total Equipment Stock

Equipment 

Class

Total Base-Case 

Energy Use

2017-2060* 

quads

TSL Savings as Percent of Total Base-Case Energy Use

TSL 1 TSL 2 TSL 3 TSL 4 TSL5

VOP.RC.M 1.606 0 3 15 15 16

VOP.RC.L 0.203 0 3 3 3 4

VOP.SC.M 0.231 1 1 8 8 8

VCT.RC.M 0.027 1 25 33 35 39

VCT.RC.L 1.198 5 6 7 7 10

VCT.SC.M 0.235 5 25 32 35 40

VCT.SC.L 0.036 15 15 18 19 22

VCT.SC.I 0.047 3 6 7 7 10

VCS.SC.M 0.472 10 14 24 24 38

VCS.SC.L 0.720 6 9 10 11 20

VCS.SC.I 0.012 1 3 3 3 8

SVO.RC.M 0.990 0 3 14 15 15

SVO.SC.M 0.300 1 2 7 7 8

SOC.RC.M 0.173 0 1 10 11 12

HZO.RC.M 0.066 0 0 0 0 1

HZO.RC.L 0.475 0 0 0 0 2

HZO.SC.M 0.015 0 0 1 1 2

HZO.SC.L 0.063 0 0 0 0 0

HCT.SC.M 0.001 5 40 43 48 57

HCT.SC.L 0.012 6 33 33 38 50

HCT.SC.I 0.017 1 3 7 7 27

HCS.SC.M 0.026 2 5 8 14 49

HCS.SC.L 0.010 8 13 21 21 48

PD.SC.M 0.401 12 12 27 40 46

SOC.SC.M 0.014 3 3 13 13 14

Totals 7.349 3 6 13 14 17

* Stock energy usage with base-case efficiency distribution across efficiency levels.

10.4.3 Annual Costs and Savings 

This section presents the annual equipment cost increases and annual operating cost savings at 

the national level. Figure 10.4.1 shows the changes over time of the non-discounted annual 

equipment price increases and the non-discounted operating cost savings at Level 4 for the 

VOP.RC.M equipment class. The total net annual impact is the discounted value of the 

difference between annual equipment purchases and annual operating costs at a 7-percent 

discount rate. The NIA model can produce similar figures for all efficiency levels for all

equipment classes. On the figure, net annual impact is the difference between the savings and 

costs for each year with appropriate discounting. The annual equipment price change is the 

increase in equipment price for equipment purchased each year over the period 2017–2046. The 

annual operating savings is the savings in operating costs for equipment purchased, and which 

has not been retired, for each year over the time period 2017−2060. 

10-24
Figure 10.4.1 National Annual Costs and Savings for Efficiency Level 4 for Equipment 

Class VOP.RC.M

Figure 10.4.1 initially shows smaller annual operating cost savings compared to the 

increased equipment price costs (shown on the figure as operating savings). Operating cost 

savings increase with time, as more and more equipment meeting the efficiency level replaces 

less efficient equipment in the commercial refrigeration equipment stock. 

10.4.4 Net Present Value Results

This section provides NPV results for the CSLs considered for the selected equipment 

classes of commercial refrigeration units. Results are cumulative and are shown as the 

discounted values of these savings in dollar terms. The inputs to the NES spreadsheet model are 

based on weighted-average values, yielding results that are discrete point values rather than a 

distribution of values as in the LCC analysis. The present value of increased total installed costs 

is the total installed cost increase (i.e., the difference between the standards case and base case) 

discounted to 2013 and summed over the time period in which DOE evaluates the impact of 

standards. 

Savings are decreases in operating costs (including electricity, repair, and maintenance)

associated with the higher energy efficiency of commercial refrigeration units purchased in the 

Product Class: VOP.RC.M

Efficiency Level 4

-0.0400

-0.0200

0.0000

0.0200

0.0400

0.0600

0.0800

0.1000

0.1200

0.1400

Billion 2012$

Year

Net Savings

Undiscounted Total Annual Operating Savings

Undiscounted Annual Equipment Purchase Savings

Discounted Total Net Annual Impact

10-25
standards case compared to the base case. Total operating cost savings are the savings per unit 

multiplied by the number of units of each vintage (i.e., the year of manufacture) that remain in 

operation in a particular year. Commercial refrigeration equipment consumes energy and must be 

maintained over its entire lifetime. The operating cost includes energy consumed and 

maintenance and repair costs incurred until all units purchased in the analysis period 2017–2046 

are retired from service (2060). 

Table 10.4.7 shows the NPV results for the CSLs considered for commercial refrigeration 

equipment based on a 7-percent discount rate. DOE based all results on electricity price forecasts 

from the AEO2013 Reference Case. Table 10.4.8 presents the NPV results by TSL for the 7-

percent discount rate. 

Table 10.4.7 Cumulative NPV Results by CSL Based on a 7-Percent Discount Rate 

(billion 2012$) 

Equipment 

Class

billion 2012$*,**,†

Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M 0.016 0.099 0.466 0.461 (0.466) NA NA

VOP.RC.L 0.002 0.013 0.014 (0.062) NA NA NA

VOP.SC.M 0.001 0.003 0.005 0.027 0.025 (0.041) NA

VCT.RC.M 0.001 0.013 0.017 0.017 0.017 (0.060) NA

VCT.RC.L 0.085 0.141 0.155 0.161 (1.170) NA NA

VCT.SC.M 0.026 0.120 0.136 0.135 0.132 0.129 (0.340)

VCT.SC.L 0.005 0.014 0.014 0.015 0.015 0.015 (0.016)

VCT.SC.I 0.003 0.003 0.004 0.004 0.005 (0.042) NA

VCS.SC.M 0.097 0.113 0.122 0.135 0.147 0.153 (1.720)

VCS.SC.L 0.083 0.105 0.120 0.138 0.139 0.135 (1.084)

VCS.SC.I 0.000 0.000 0.000 0.001 0.001 (0.011) NA

SVO.RC.M 0.004 0.057 0.245 0.240 (0.231) NA NA

SVO.SC.M 0.000 0.008 0.012 0.029 0.027 (0.037) NA

SOC.RC.M 0.001 0.004 0.039 0.038 0.031 (0.056) NA

HZO.RC.M (0.039) NA NA NA NA NA NA

HZO.RC.L (0.229) NA NA NA NA NA NA

HZO.SC.M 0.000 0.000 0.000 (0.007) NA NA NA

HZO.SC.L (0.006) NA NA NA NA NA NA

HCT.SC.M 0.000 0.000 0.000 0.001 0.001 0.001 (0.003)

HCT.SC.L 0.001 0.002 0.009 0.010 0.010 0.009 (0.016)

HCT.SC.I 0.000 0.001 0.001 (0.039) NA NA NA

HCS.SC.M 0.001 0.002 0.003 0.001 (0.005) (0.166) NA

HCS.SC.L 0.001 0.001 0.002 0.002 0.003 (0.021) NA

PD.SC.M 0.119 0.237 0.236 0.231 0.200 0.176 (0.872)

SOC.SC.M 0.000 0.001 0.001 0.004 0.004 0.003 (0.003)

* A value of “NA” indicates that there are no associated efficiency levels at this level for this equipment class. 

** 0.000 indicates savings are less than $0.0005 billion 2012$. † Values in parentheses are negative values.

10-26
Table 10.4.8 Cumulative NPV Results by TSL Based on a 7-Percent Discount Rate 

(billion 2012$) 

Equipment Class billion 2012$*,

**,†

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VOP.RC.M 0.016 0.099 0.466 0.461 (0.466)

VOP.RC.L 0.002 0.013 0.014 0.014 (0.062)

VOP.SC.M 0.003 0.005 0.027 0.025 (0.041)

VCT.RC.M 0.001 0.013 0.017 0.017 (0.060)

VCT.RC.L 0.141 0.155 0.161 0.161 (1.170)

VCT.SC.M 0.026 0.120 0.136 0.129 (0.340)

VCT.SC.L 0.014 0.014 0.015 0.015 (0.016)

VCT.SC.I 0.003 0.004 0.005 0.005 (0.042)

VCS.SC.M 0.113 0.135 0.153 0.153 (1.720)

VCS.SC.L 0.105 0.138 0.139 0.135 (1.084)

VCS.SC.I 0.000 0.001 0.001 0.001 (0.011)

SVO.RC.M 0.004 0.057 0.245 0.240 (0.231)

SVO.SC.M 0.008 0.012 0.029 0.027 (0.037)

SOC.RC.M 0.001 0.004 0.039 0.031 (0.056)

HZO.RC.M – – – – (0.039)

HZO.RC.L – – – – (0.229)

HZO.SC.M 0.000 0.000 0.000 0.000 (0.007)

HZO.SC.L – – – – (0.006)

HCT.SC.M 0.000 0.001 0.001 0.001 (0.003)

HCT.SC.L 0.002 0.009 0.010 0.009 (0.016)

HCT.SC.I 0.000 0.001 0.001 0.001 (0.039)

HCS.SC.M 0.001 0.002 0.003 0.001 (0.166)

HCS.SC.L 0.002 0.002 0.003 0.003 (0.021)

PD.SC.M 0.119 0.119 0.237 0.176 (0.872)

SOC.SC.M 0.001 0.001 0.004 0.003 (0.003)

Total 0.561 0.905 1.705 1.606 (6.735)

* A “–” represents zero energy savings, since TSLs 1 to for the equipment classes HZO.RC.M, 

HZO.RC.L, and HZO.SC.L are associated with the baseline efficiency level.

**A value of 0.000 means NES values are less than $0.0005 billion 2012$.

† Values in parentheses are negative values.

Table 10.4.9 provides the NPV results for each CSL based on the 3-percent discount rate 

and electricity price forecasts from the AEO2013 Reference Case. Table 10.4.10 presents the 

NPV results based on the 3-percent discount rate by TSL. 

10-27
Table 10.4.9 Cumulative NPV Results by CSL Based on a 3-Percent Discount Rate 

(billion 2012$) 

Equipment 

Class

Standard Level*,**,†

billion 2012$

Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M 0.037 0.233 1.144 1.140 (0.549) NA NA

VOP.RC.L 0.005 0.030 0.032 (0.104) NA NA NA

VOP.SC.M 0.002 0.006 0.012 0.070 0.068 (0.053) NA

VCT.RC.M 0.001 0.031 0.041 0.041 0.041 (0.100) NA

VCT.RC.L 0.194 0.327 0.363 0.383 (2.017) NA NA

VCT.SC.M 0.059 0.283 0.331 0.332 0.330 0.326 (0.524)

VCT.SC.L 0.010 0.031 0.032 0.035 0.035 0.035 (0.020)

VCT.SC.I 0.007 0.007 0.011 0.011 0.012 (0.071) NA

VCS.SC.M 0.221 0.259 0.279 0.316 0.354 0.398 (2.976)

VCS.SC.L 0.187 0.239 0.273 0.323 0.329 0.327 (1.837)

VCS.SC.I 0.000 0.001 0.001 0.001 0.002 (0.018) NA

SVO.RC.M 0.008 0.137 0.615 0.608 (0.249) NA NA

SVO.SC.M 0.001 0.018 0.028 0.078 0.074 (0.043) NA

SOC.RC.M 0.003 0.010 0.093 0.092 0.079 (0.078) NA

HZO.RC.M (0.071) NA NA NA NA NA NA

HZO.RC.L (0.411) NA NA NA NA NA NA

HZO.SC.M 0.000 0.000 0.000 (0.013) NA NA NA

HZO.SC.L (0.012) NA NA NA NA NA NA

HCT.SC.M 0.000 0.000 0.000 0.002 0.002 0.002 (0.004)

HCT.SC.L 0.002 0.004 0.022 0.022 0.022 0.022 (0.023)

HCT.SC.I 0.001 0.002 0.003 (0.066) NA NA NA

HCS.SC.M 0.003 0.005 0.007 0.006 (0.003) (0.292) NA

HCS.SC.L 0.001 0.002 0.004 0.006 0.007 (0.034) NA

PD.SC.M 0.270 0.551 0.550 0.543 0.525 0.494 (1.406)

SOC.SC.M 0.001 0.002 0.002 0.009 0.009 0.008 (0.003)

* A value of “NA” is used to indicate that there are no associated efficiency levels at this level for this equipment class. 

** 0.000 indicates savings are less than $0.0005 billion 2012$. 

† Values in parentheses are negative values.

10-28
Table 10.4.10 Cumulative NPV Results by TSL Based on a 3-Percent Discount Rate 

(billion 2012$) 

Equipment Class billion 2012$*,

**,†

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VOP.RC.M 0.037 0.233 1.144 1.140 (0.549)

VOP.RC.L 0.005 0.030 0.032 0.032 (0.104)

VOP.SC.M 0.006 0.012 0.070 0.068 (0.053)

VCT.RC.M 0.001 0.031 0.041 0.041 (0.100)

VCT.RC.L 0.327 0.363 0.383 0.383 (2.017)

VCT.SC.M 0.059 0.283 0.331 0.326 (0.524)

VCT.SC.L 0.031 0.032 0.035 0.035 (0.020)

VCT.SC.I 0.007 0.011 0.012 0.012 (0.071)

VCS.SC.M 0.259 0.316 0.398 0.398 (2.976)

VCS.SC.L 0.239 0.323 0.329 0.327 (1.837)

VCS.SC.I 0.001 0.001 0.002 0.002 (0.018)

SVO.RC.M 0.008 0.137 0.615 0.608 (0.249)

SVO.SC.M 0.018 0.028 0.078 0.074 (0.043)

SOC.RC.M 0.003 0.010 0.093 0.079 (0.078)

HZO.RC.M – – – – (0.071)

HZO.RC.L – – – – (0.411)

HZO.SC.M 0.000 0.000 0.000 0.000 (0.013)

HZO.SC.L – – – – (0.012)

HCT.SC.M 0.000 0.002 0.002 0.002 (0.004)

HCT.SC.L 0.004 0.022 0.022 0.022 (0.023)

HCT.SC.I 0.001 0.002 0.003 0.003 (0.066)

HCS.SC.M 0.003 0.005 0.007 0.006 (0.292)

HCS.SC.L 0.004 0.006 0.007 0.007 (0.034)

PD.SC.M 0.270 0.270 0.551 0.494 (1.406)

SOC.SC.M 0.002 0.002 0.009 0.008 (0.003)

Total 1.285 2.118 4.165 4.067 (10.972)

* A “–” represents zero energy savings, since TSLs 1 to 4 for the equipment classes HZO.RC.M, 

HZO.RC.L, and HZO.SC.L are associated with the baseline efficiency level.

**A value of 0.000 means NES values are less than $0.0005 billion 2012$.

† Values in parentheses are negative values.

10.5 ANNUALIZED NATIONAL COSTS AND BENEFITS

The benefits and costs of today’s proposed standards, for equipment sold in 2017–2060, 

can be expressed in terms of annualized values. The annualized monetary values are the sum of 

(1) the annualized national economic value of the benefits from customer operation of equipment 

that meet the proposed standards (consisting primarily of operating cost savings from using less 

energy, minus increases in equipment purchase and installation costs, which is another way of 

representing customer NPV) and (2) the annualized monetary value of the benefits of emission 

reductions, including carbon dioxide (CO2) emission reductions. The derivation of the monetary 

value of the benefits of emission reductions is described in chapter 14 of this NOPR TSD. The 

value of the CO2 reductions, otherwise known as the Social Cost of Carbon (SCC), is calculated 

using a range of values per metric ton of CO2 developed by a recent interagency process. The 

derivation of the time series of SCC values is discussed in appendix 14A of this NOPR TSD.

Although combining the values of operating savings and CO2 reductions provides a 

useful perspective, two issues should be considered. First, the national operating cost savings are 

10-29
domestic U.S. customer monetary savings that occur as a result of market transactions, while the 

value of CO2 reductions is based on a global value. Second, the assessments of operating cost 

savings and CO2 savings are performed with different methods that use quite different time 

frames for analysis. The national operating cost savings is measured for the lifetime of 

equipment shipped in the 30-year analysis period. The SCC values, on the other hand, reflect the 

present value of future climate-related impacts resulting from the emission of 1 ton of CO2 in 

each year. These impacts go well beyond 2100. 

10.5.1 Calculation Method

DOE uses a two-step calculation process to convert each time series of costs and benefits 

into annualized values. First, DOE calculates a present value in the “present” year used in 

discounting the NPV of total customer costs and savings.b For this calculation, DOE uses 

discount rates of 3 and 7 percent for all costs and benefits except for the value of CO2 reductions. 

For the latter, DOE uses the discount rate appropriate for each SCC time series (see TSD chapter 

16 for discussion). 

PPPPxx = � (xx(tt) ∙ (1 + xx)yyNNNNNN−tt)

tt=yy1,yyTT

Eq. 10.9 

Where:

xx(tt)= time series under evaluation, 

PPPPxx= present value of the time series xx, 

yy1= first year in the analysis period,

yyT = last year in the analysis period,

yyNPV= year to which the NPV of customers’ costs and savings are being discounted, and 

xx = discount rate used to discount the annual values of time series xx to year yyNPV. 

In the second step, DOE calculates, from the present values, the fixed annual payments 

over a 30-year period, starting in the first year of the analysis period (i.e., the compliance year), 

which yields the same present values with discount rates of 3 and 7 percent. This requires 

projecting the present values in the “present” year ahead to the compliance year. The fixed 

annual payments are the annualized values. 

AA xx, = PPPPxx ∙ ffyy1−yyNNNNNN, ∙ aa30, = PPPPxx ∙ (1 + )yy1−yyNNNNNN ∙ ∙ (1 + )30

(1 + )30 − 1

Eq. 10.10 

Where:

AA xx, = annualized value of the time series xx, 

ff , = factor to project a value years aheadc with discount rate, and 

aa30, = factor to annualize present values over a 30-year period with discount rate. 

b For the value of emissions reductions, DOE uses a time-series that corresponds to the time period used in 

calculating the operating cost savings (i.e., through the final year in which equipment shipped are still operating). c n is the number of years between the “present” year and the compliance year.

10-30

 
Although DOE calculates annualized values, this does not imply that the time series of 

cost and benefits from which the annualized values were determined would be a steady stream of 

payments. 

10.5.2 Results for the Adopted Standards

The NOPR associated with this TSD states that DOE is adopting amended energy 

conservation standards for commercial refrigeration equipment that correspond to TSL 4. 

Estimates of annualized values for the proposed standards are shown in Table 10.5.1. 

Table 10.5.1 Annualized Benefits and Costs of New and Amended Standards for 

Commercial Refrigeration Equipment Shipped in 2017–2046* 

Discount Rate

Primary 

Estimate High Estimate Low Estimate

Monetized

million 2012$/year

Benefits

Operating Cost Savings 7% 203 197 212

3% 299 288 314

CO2 Reduction at $12.9/t** 5% 19 19 19

CO2 Reduction at $40.8/t** 3% 75 75 75

CO2 Reduction at $62.2/t** 2.50% 114 114 114

CO2 Reduction at $117.0/t** 3% 225 225 225

NOX Reduction at $2636/t** 7% 3.75 3.75 3.75

3% 5.33 5.33 5.33

Total (Operating Cost Savings, 

CO2 Reduction and NOX

Reduction)†

7% plus CO2 range 226 to 432 220 to 426 235 to 441

7% 281 275 290

3% 323 to 530 312 to 519 338 to 545

3% plus CO2 range 379 368 394

Costs

Incremental Equipment Costs 7% 82 84 80

3% 97 100 95

Net Benefits/Costs

Total (Operating Cost Savings, 

CO2 Reduction and NOX

Reduction, Minus Incremental 

Equipment Costs)†

7% plus CO2 range 144 to 350 138 to 344 153 to 359

7% 199 191 210

3% 226 to 432 215 to 421 241 to 447

3% plus CO2 range 281 268 299

* This table presents the annualized costs and benefits associated with commercial refrigeration equipment shipped in 2017–2046. 

These results include benefits to customers that accrue after 2046 from the commercial refrigeration equipment purchased from 

2017 through 2046. Costs incurred by manufacturers, some of which may be incurred before 2017 in preparation for the rule, are 

not directly included but are indirectly included as part of incremental equipment costs. In addition, incremental equipment costs 

reflect a medium decline rate for projected product price trends in the Primary Estimate, a low decline rate for projected equipment 

price trends in the Low Benefits Estimate, and a high decline rate for projected equipment price trends in the High Benefits 

Estimate. The methods used to derive projected price trends are explained in Appendix 10B. 

** The CO2 values represent global monetized values (in 2012$) of the social cost of CO2 emissions in 2015 under several 

scenarios. The values of $12.9, $40.8, and $62.2 per metric ton are the averages of SCC distributions calculated using 5-percent, 3-

percent, and 2.5-percent discount rates, respectively. The value of $117.0/t represents the 95th percentile of the SCC distribution 

calculated using a 3-percent discount rate. The value for NOx (in 2012$) is $2,639.

† Total benefits for both the 3-percent and 7-percent cases are derived using the SCC value calculated at a 3-percent discount rate, 

which is $40.8/t in 2015 (in 2012$). In the rows labeled as “7% plus CO2 range” and “3% plus CO2 range,” the operating cost and 

NOx benefits are calculated using the labeled discount rate, and those values are added to the full range of CO2 values.

10-31
Appendix 10E of this NOPR TSD presents detailed Regulatory Information Service 

Center (RISC) & Office of Information and Regulatory Affairs, OMB (OIRA) Consolidated 

Information System (ROCIS) tables with annualized benefits and costs by equipment class 

grouping for all TSLs considered in this NOPR.

10-32
REFERENCES

1. U.S. Department of Energy—Energy Information Administration. Commercial Demand 

Module of the National Energy Modeling System: Model Documentation 2012. 2012. 

Washington, D.C. DOE/EIA-M066. 

2. Energy Research Group / M.K. Jaccard & Associates. Integration of GHG Emission 

Reduction Options using CIMS. 2000. Vancouver, B.C. 

<http://www.emrg.sfu.ca/media/publications/Reports%20for%20Natural%20Resources%20

Canada/Rollup.pdf> 

3. U. S. Department of Energy—Energy Information Administration. 2013 Annual Energy 

Outlook. 2013. Washington D.C. DOE/EIA-0383(2013). (Last accessed June 14, 2013.) 

<www.eia.gov/oiaf/aeo/tablebrowser/> 

10-33
APPENDIX 10A. USER INSTRUCTIONS FOR NIA SPREADSHEET

TABLE OF CONTENTS

10A.1 INTRODUCTION ...................................................................................................... 10A-1

10A.2 USER INSTRUCTIONS FOR NIA SPREADSHEET ............................................... 10A-1

REFERENCES ....................................................................................................................... 10A-6

LIST OF TABLES

Table 10A.2.1 Description of Tabs in the NIA Spreadsheet .................................................. 10A-1

10A-i 
APPENDIX 10A. USER INSTRUCTIONS FOR NIA SPREADSHEET

10A.1 INTRODUCTION

The results of the national impact analysis (NIA) for commercial refrigeration equipment

can be examined and reproduced using a Microsoft Excel spreadsheet available on the U.S. 

Department of Energy (DOE) Building Technologies (BT) website at 

www.eere.energy.gov/buildings/appliance_standards/commercial_products.html. 

The spreadsheet enables the user to analyze up to 25 classes of commercial refrigeration 

equipment. The spreadsheet was designed and tested using Excel 2010. 

10A.2 USER INSTRUCTIONS FOR NIA SPREADSHEET

The NIA spreadsheet performs calculations to forecast the change in national energy use 

due to an energy efficiency standard for commercial refrigeration equipment, and net present 

value (NPV) of the change in energy usage. The energy use and associated costs for a given 

standard are determined first by calculating the shipments and then calculating the energy use 

and costs for commercial refrigeration equipment shipped under that standard. The differences 

between the standards and base cases can then be compared and the overall energy savings and 

present values determined.

The NIA spreadsheet or workbook consists of the following worksheets (Table 10A.2.1). 

Some detailed worksheets are hidden to make it easier to examine the final results quickly, but 

can be retrieved by using the command option on the Excel 2010 Home tab: Format, Visibility – 

Hide & Unhide, Unhide Sheet. 

Table 10A.2.1 Description of Tabs in the NIA Spreadsheet

Tab Description

Analysis Flow Figure that illustrates the calculations performed by the NIA 

spreadsheet.

Summary of Results Worksheet that contains user input selections and, for the selected 

equipment class, a Summary table, Shipments graph, Cumulative 

Energy Savings and NPV graph, and an Annual Non-Discounted 

Savings Trend plot, which also contains a plot of discounted net 

savings by year.

Shipments-Weighted Data Worksheet that contains calculated tables of both input data and 

results from the spreadsheet. For the notice of proposed 

rulemaking (NOPR) technical support document (TSD), data for

many summary tables were compiled on this worksheet, including 

the Cumulative NPV and Energy Savings results.

Savings Summary Accounting worksheet used to store the results of the shipments 

and energy savings calculations for an individual equipment class 

and up to seven efficiency levels (e.g., Levels 2–8).

Details_Save (hidden) Accounting worksheet used to tally the energy and cost savings 

year by year for an individual equipment class and standard level. 

The energy and cost savings in a single year are the difference 

between the base case energy use and costs for that year and the 

standards case energy use and costs in the same year.

10A-1 
Table 10A.2.1 (cont)

Tab Description

Details_Stock (hidden) Worksheet that keeps track of all surviving stock of commercial 

refrigeration equipment in an equipment class from the start year 

forward. Stock is updated for each year.

Initial Stock Details (hidden) Worksheet that keeps track of all surviving stock of commercial 

refrigeration equipment in an equipment class from 2010 to the 

start year of the forecast (2017). Stock is updated for each year.

Shares Output 1, Shares Output 2, 

Shares Output 3, Shares Output 4,

Shares Output 5, Shares Output 6, 

Shares Output 7 (all are hidden)

Seven worksheets that estimate percentage distribution shipments 

for all equipment classes of commercial refrigeration equipment, 

by efficiency level and year, from the start year of the forecast 

forward. Each worksheet applies to a different type of business 

(supermarkets, convenience and specialty stores, convenience 

stores with gas pumps, large multi-line retailers, limited service 

restaurants, full service restaurants, and other foodservice).

Shares Processing (hidden) Worksheet that performs the detailed calculations based on 

annualized cost to estimate market shares of an equipment class, 

by efficiency level, in a business type, based on risk preferences of 

purchasers for a baseline market condition and up to seven 

candidate standard levels.

Input (hidden) Worksheet that performs detailed calculations by risk preference 

class to estimate annualized cost for a newly purchased unit of an 

equipment class of commercial refrigeration equipment by 

efficiency level in a business type. 

CRE Cost List Contains input data on installed cost (total price), repair and 

maintenance cost, and annual electricity cost for units of 

commercial refrigeration equipment, calculated by the life-cycle 

cost (LCC) model by equipment class, business type, and 

efficiency level at U.S. average prices and market conditions.

Details_ Ship (hidden) Calculates total shipments by efficiency level for an equipment 

class by year, given a candidate standard level. Also contains 

market weighted-average percentages of shipments by efficiency 

level of each equipment class of new commercial refrigeration 

equipment for baseline market conditions and up to seven 

candidate standard levels. Percentages are reported for each year 

from the start year forward.

Initial Shipments Detail (hidden) Calculates total shipments by efficiency level and market 

weighted-average percentages of shipments by efficiency level of 

each equipment class of new commercial refrigeration equipment 

for baseline market conditions and up to seven candidate standard 

levels. Values are reported for each year from 2010 to the start 

year of the forecast (2017).

Shipments_Summary Contains estimated shipments of an equipment class of 

commercial refrigeration equipment by efficiency level and year, 

for the last class/efficiency level combination calculated by the 

model. Also contains estimates of total shipments of each 

equipment class by year for each candidate standard level.

Base Product Market Share Calcd Worksheet that performs calculations to estimate total market 

shipments by equipment class and year in the base case. 

Product Shares Contains percentages of overall commercial refrigeration 

equipment shipments (linear feet) by equipment class based on 

2009 historical data. Populated from Summary of Results. 

Econ Trends Worksheet that contains historical and projected economic values 

as well as shipments data. 

10A-2 
Table 10A.2.1 (cont)

Tab Description

Equipment Parameters Worksheet that contains the economic, energy, and size 

parameters for commercial refrigeration equipment.

Labels Used as an interface between user inputs and the rest of the 

worksheets—do not modify this sheet

National Impacts Summary (hidden) Tables for TSD, summarizing impacts, formatted for the 

document. Results linked from Shipment-Weighted Data 

worksheet.

ROCIS* (hidden) Worksheet summarizing inputs and results from several NIA base 

and sensitivity runs, plus emissions and emission valuation results, 

for use in the Office of Management and Budget (OMB) process.

Shipments (hidden) Worksheet that contains a single tabular summary of shipments for 

use in chapter 6 of the TSD.

*ROCIS is an acronym for Regulatory Information Service Center (RISC) and Office of Information and Regulatory Affairs 

(OIRA) Consolidated Information System.

Basic instructions for using the NIA spreadsheet are as follows:

1. Once the NIA spreadsheet file has been downloaded from the DOE BT website, open the 

file using Excel. If you receive a dialog box that asks whether you want to enable macros, 

select Yes. At the bottom of the Excel window, click on the tab for the worksheet 

Summary of Results.

2. Use Excel’s View/Zoom commands at the top menu bar to size the display to your 

monitor. 

3. You can change the model parameters listed in the gray box labeled “User defined 

inputs.” The parameters are the following: 

a. Equipment Class: To change the value, select the menu box. A drop-down list

appears. Select the desired equipment class. Many of the potential classes have no 

shipments, and are not being modeled. If you select one these classes, a warning will 

appear in the space immediately above the menu box and the first row in the 

summary of results will show up as zeroes; the cells will turn red and will be crosshatched out. 

b. Efficiency Level: Select the efficiency level used in the non-discounted annual net 

impacts figure. The efficiency level must be less than or equal to the max tech level

for the equipment class selected. If a higher standard level than max tech is selected, 

no results will be available for the levels above max tech. 

c. Max Tech: This value is currently set by the data contained within the model, not by 

the user, and is provided on the Summary of Results worksheet for the model user. 

(See the table found at cells S3 through Y30.) There is a routine within the model that 

requires the max tech be set at a level no greater than the currently modeled limit. 

Thus, max tech is presently not treated as a variable.

10A-3 
d. Discounting Reference Year: To change the year to which monetary values are 

discounted, select from the drop-down menu. For the NOPR phase, monetary values 

were discounted to 2013. 

e. Growth in Energy Prices: To the change value, select the Growth in Energy Prices

box. A drop-down menu pops up. Select the desired growth level (Constant, 

Reference, Low, or High). The scenarios refer to the Energy Information 

Administration’s (EIA’s) projected U.S. national average rates from Annual Energy 

Outlook 2013.

1

f. Standard First Year: This is the first year in which the standard will take effect. This 

should be set to 2017 for the NOPR phase, but other options are available. 

g. Discount Rate: To the change value, select the Discount Rate box. A drop-down 

menu pops up. Select the desired discount rate. Three options are provided: 3, 7 and 

9 percent.

h. Price Learning: Also known as Experiential Learning, price learning controls the 

scenario for up-front prices for equipment. 

4. Once the user parameters have been reset, the model must be re-run. To re-run the model 

for single equipment option, click the Update Values button. Note: The output values are 

not correctly updated until the Update Values button is clicked. To run all equipment 

classes, click the Run All Cases button. The Sales-Weighted Data worksheet is only 

updated when the Run All Cases button is used. This takes a few minutes. The SalesWeighted Data worksheet is not updated by Update Values or by simply changing any of 

the input parameters. 

5. If a new set of LCC results has been loaded into the CRE Cost List and Equipment 

Parameters worksheets, it will be necessary to recalculate the baseline equipment 

shipment shares by efficiency level in sheets Output1–Output7. To do this, click the 

Shares Processing button. The shares automatically update (this process takes about 3 

minutes), but it will not be necessary to update again unless LCC input data change. 

 

6. Tabular results are presented to the right of the “User defined inputs” box for the base 

case (Level 1) and the Level 2 through Level 8 standards cases. Tabular results are 

summarized as: (1) cumulative shipments; (2) percentage change in total shipments as 

efficiency level increases (currently, this does not change); (3) present value of national 

equipment cost savings in billions of dollars; (4) present value of national operating cost 

savings in billions of dollars; (5) national net present value in billions of dollars; and (6) 

cumulative national energy savings in quadrillion British thermal units (quads). Energy 

savings results for all standards cases are tabulated for two periods: 2017–2046 and 

2017–2060. Net present value results are tabulated for 2017–2060, with equipment costs 

included for the period 2017–2046. 

10A-4 
Graphical results are presented for the main tabular results. Two charts are provided for 

the given model parameters: (1) shipments forecasts for the base case and all standards 

cases and (2) national energy savings and net present values for all the standards cases.

For a given set of user-defined equipment choices and parameters, you can view the 

annual trend in the non-discounted net impacts for individual candidate standard levels. 

To view an efficiency level, select the drop-down menu bar with that title, and select the 

desired candidate standard level from the drop-down list. The annual purchase savings 

and operating cost savings are not discounted values. However, the net savings value in 

each year is shown as a discounted value.

10A-5 
REFERENCES 

1. U.S. Department of Energy–Energy Information Administration. Annual Energy Outlook 

2013. 2013. Washington D.C. DOE/EIA-0383(2013).

10A-6 
APPENDIX 10B. NATIONAL NET PRESENT VALUE USING 

ALTERNATIVE PRICE FORECASTS 

TABLE OF CONTENTS

10B.1 ALTERNATIVE NET PRESENT VALUES ............................................................. 10B-1

LIST OF TABLES

Table 10B.1.1 Price Factor Indicies Used in Default Case and Sensitivity Cases ..................10B-3

Table 10B.1.2 CRE NPV in Billions (2012$) at a 7 Percent Discount Rate – High Price 

Scenario............................................................................................................10B-4

Table 10B.1.3 CRE NPV in Billions (2012$) at a 3 Percent Discount Rate – High Price 

Scenario............................................................................................................10B-5

Table 10B.1.4 CRE NPV in Billions (2012$) at a 7 Percent Discount Rate – Low Price 

Scenario............................................................................................................10B-6

Table 10B.1.5 CRE NPV in Billions (2012$) at a 3 Percent Discount Rate – Low Price 

Scenario............................................................................................................10B-7

Table 10B.1.6 CRE NPV in Billions (2012$) at a 7 Percent Discount Rate – Constant Real 

Price Scenario ..................................................................................................10B-8

Table 10B.1.7 CRE NPV in Billions (2012$) at a 3 Percent Discount Rate – Constant Real 

Price Scenario ..................................................................................................10B-9

LIST OF FIGURES

Figure 10B.1.1 CRE Price Factor Indices for Default Case and Sensitivity Cases .................10B-2

10B-i 
APPENDIX 10B. NATIONAL NET PRESENT VALUE USING 

ALTERNATIVE PRICE FORECASTS

10B.1 ALTERNATIVE NET PRESENT VALUES

The net present value (NPV) results presented in chapter 10 of this technical 

support document (TSD) reflect a price trend based on an experience curve derived using 

historical data on shipments and refrigeration equipment producer price index (PPI). 

The average annual rate of price decline in the default case for the 2017–2046 analysis 

period is 0.11 percent and is based on historical PPI data for refrigeration equipment 

between 1978–2012 as discussed in Appendix 8D. For the national impact analysis 

(NIA), DOE analyzed two additional sensitivity cases that also use a price trend based on 

an exponential-in-time extrapolation of refrigeration equipment PPI data. DOE developed

a high price decline case and a low price decline case in this analysis. The high price 

decline case is based on the upper end of the 95 percent confidence interval for an 

exponential fit to the inflation-adjusted PPI series of 1978 to 2012. The low price forecast

case is based on the lower end of the 95 percent confidence interval for an exponential fit 

to the nominal PPI series of 1978 to 2012. The average annual rate of price decline over 

the analysis period is 0.25 percent in the low price forecast case. In the high price forecast 

the average annual rate of change is an increase of 0.03 percent. Because of the nature of 

the exponential experience curve, greater annual price declines are found in earlier years 

in the analysis period and lesser annual price declines are found in the latter years in the 

analysis period. DOE investigated the impact of these different product price forecasts on 

the consumer net NPV for the considered trial standard levels (TSLs) for commercial 

refrigeration equipment. 

For the NPV sensitivity, DOE considered three product price forecast sensitivity 

cases: 1) a high price case based on the PPI trend of 1978–2012, 2) a low price case

based on the PPI trend in 1978–2012, and 3) a constant real price case. Each price 

scenario is expressed in terms of a price factor index time series, which is applied to the 

2012 price estimate to forecast per unit prices over the 2017–2046 analysis period. 

Figure 10B.1.1 shows the equipment price factor indices for the default case and the three 

additional price decline forecasts considered in this sensitivity analysis. Table 10B.1.1

shows the price factor indices tabulated.

Table 10B.1.2 and Table 10B.1.3 provide NPV results for commercial 

refrigeration equipment at each TSL level based on the high price forecast case for 7 and 

3 percent discount rates, respectively. Table 10B.1.4 and Table 10B.1.5 provide NPV 

results for commercial refrigeration equipment based on the low price forecast case at 7

and 3 percent discount rates, respectively. Table 10B.1.6 and Table 10B.1.7 provide NPV 

results for refrigeration systems based on a constant real price case at 7 and 3 percent

discount rates, respectively. These results can be directly compared with the commercial 

refrigeration equipment NPV results using the default price decline scenario shown in 

chapter 10 of this TSD. 

10B-1 
Figure 10B.1.1 Commercial Refrigeration Equipment Price Factor Indices for 

Default Case and Sensitivity Cases 

10B-2 
Table 10B.1.1 Price Factor Indicies Used in Default Case and Sensitivity Cases

Year

Price Factor Index

2012$

Default High Price 

Forecast

Low Price 

Forecast Constant Real

2012 1.000 1.000 1.000 1.0000

2013 0.999 1.000 0.997 1.0000

2014 0.998 1.001 0.995 1.0000

2015 0.997 1.001 0.992 1.0000

2016 0.996 1.001 0.990 1.0000

2017 0.995 1.002 0.987 1.0000

2018 0.993 1.002 0.985 1.0000

2019 0.992 1.002 0.982 1.0000

2020 0.991 1.003 0.980 1.0000

2021 0.990 1.003 0.978 1.0000

2022 0.989 1.003 0.975 1.0000

2023 0.988 1.003 0.973 1.0000

2024 0.987 1.004 0.971 1.0000

2025 0.986 1.004 0.969 1.0000

2026 0.985 1.004 0.967 1.0000

2027 0.984 1.005 0.964 1.0000

2028 0.983 1.005 0.962 1.0000

2029 0.982 1.005 0.960 1.0000

2030 0.981 1.006 0.958 1.0000

2031 0.980 1.006 0.955 1.0000

2032 0.979 1.006 0.953 1.0000

2033 0.978 1.006 0.951 1.0000

2034 0.978 1.007 0.949 1.0000

2035 0.977 1.007 0.947 1.0000

2036 0.976 1.007 0.945 1.0000

2037 0.975 1.007 0.943 1.0000

2038 0.974 1.008 0.941 1.0000

2039 0.973 1.008 0.939 1.0000

2040 0.972 1.008 0.937 1.0000

2041 0.971 1.009 0.935 1.0000

2042 0.970 1.009 0.933 1.0000

2043 0.969 1.009 0.931 1.0000

2044 0.969 1.009 0.929 1.0000

2045 0.968 1.010 0.928 1.0000

2046 0.967 1.010 0.926 1.0000 

10B-3 
Table 10B.1.2 Commercial Refrigeration Equipment: Net Present Value in Billions 

(2012$) at a 7 Percent Discount Rate – High Price Scenario

billion 2012$

TSL1 TSL2 TSL3 TSL4 TSL5

VOP.RC.M 0.016 0.099 0.462 0.456 (0.491)

VOP.RC.L 0.002 0.013 0.013 0.013 (0.064)

VOP.SC.M 0.003 0.005 0.027 0.025 (0.043)

VCT.RC.M 0.001 0.013 0.017 0.016 (0.062)

VCT.RC.L 0.140 0.154 0.160 0.160 (1.202)

VCT.SC.M 0.026 0.119 0.135 0.127 (0.352)

VCT.SC.L 0.014 0.014 0.015 0.015 (0.016)

VCT.SC.I 0.003 0.004 0.005 0.005 (0.043)

VCS.SC.M 0.113 0.135 0.150 0.150 (1.767)

VCS.SC.L 0.105 0.137 0.138 0.133 (1.115)

VCS.SC.I 0.000 0.001 0.001 0.001 (0.011)

SVO.RC.M 0.004 0.056 0.242 0.237 (0.244)

SVO.SC.M 0.008 0.012 0.029 0.026 (0.039)

SOC.RC.M 0.001 0.004 0.039 0.030 (0.058)

SOC.SC.M 0.001 0.001 0.004 0.003 (0.003)

HZO.RC.M - - - - (0.040)

HZO.RC.L - - - - (0.234)

HZO.SC.M 0.000 0.000 0.000 0.000 (0.008)

HZO.SC.L - - - - (0.007)

HCT.SC.M 0.000 0.001 0.001 0.001 (0.003)

HCT.SC.L 0.002 0.009 0.010 0.009 (0.017)

HCT.SC.I 0.000 0.001 0.001 0.001 (0.040)

HCS.SC.M 0.001 0.002 0.003 0.001 (0.170)

HCS.SC.L 0.002 0.002 0.003 0.003 (0.022)

PD.SC.M 0.119 0.119 0.236 0.170 (0.901)

Total 0.559 0.900 1.689 1.583 (6.952)

“-” represents zero energy savings, since TSLs 1 to 4 for equipment classes HZO.RC.M, HZO.RC.L 

and HZO.SC.L are associated with the baseline efficiency level.

*A value of 0.000 means national energy savings (NES) values are less than $0.0005 billion 2012$.

10B-4 
Table 10B.1.3 Commercial Refrigeration Equipment: Net Present Value in Billions 

(2012$) at a 3 Percent Discount Rate – High Price Scenario

billion 2012$

TSL1 TSL2 TSL3 TSL4 TSL5

VOP.RC.M 0.036 0.232 1.136 1.131 (0.603)

VOP.RC.L 0.005 0.030 0.032 0.032 (0.108)

VOP.SC.M 0.006 0.012 0.069 0.067 (0.057)

VCT.RC.M 0.001 0.030 0.041 0.040 (0.104)

VCT.RC.L 0.326 0.361 0.380 0.380 (2.086)

VCT.SC.M 0.059 0.281 0.328 0.321 (0.551)

VCT.SC.L 0.031 0.032 0.035 0.035 (0.022)

VCT.SC.I 0.007 0.011 0.012 0.012 (0.074)

VCS.SC.M 0.259 0.314 0.391 0.391 (3.076)

VCS.SC.L 0.238 0.322 0.327 0.324 (1.905)

VCS.SC.I 0.001 0.001 0.002 0.002 (0.019)

SVO.RC.M 0.008 0.136 0.609 0.602 (0.277)

SVO.SC.M 0.018 0.028 0.077 0.072 (0.047)

SOC.RC.M 0.003 0.010 0.093 0.078 (0.083)

SOC.SC.M 0.002 0.002 0.009 0.008 (0.004)

HZO.RC.M - - - - (0.073)

HZO.RC.L - - - - (0.423)

HZO.SC.M 0.000 0.000 0.000 0.000 (0.014)

HZO.SC.L - - - - (0.012)

HCT.SC.M 0.000 0.002 0.002 0.002 (0.004)

HCT.SC.L 0.004 0.022 0.022 0.022 (0.024)

HCT.SC.I 0.001 0.002 0.003 0.003 (0.068)

HCS.SC.M 0.003 0.005 0.007 0.006 (0.301)

HCS.SC.L 0.004 0.006 0.007 0.007 (0.036)

PD.SC.M 0.269 0.269 0.548 0.482 (1.469)

Total 1.281 2.107 4.132 4.019 (11.438)

“-” represents zero energy savings, since TSLs 1 to 4 for equipment classes HZO.RC.M, HZO.RC.L and 

HZO.SC.L are associated with the baseline efficiency level.

*A value of 0.000 means NES values are less than $0.0005 billion 2012$.

10B-5 
Table 10B.1.4 Commercial Refrigeration Equipment: Net Present Value in Billions 

(2012$) at a 7 Percent Discount Rate – Low Price Scenario

billion 2012$

TSL1 TSL2 TSL3 TSL4 TSL5

VOP.RC.M 0.016 0.100 0.470 0.465 (0.442)

VOP.RC.L 0.002 0.013 0.014 0.014 (0.060)

VOP.SC.M 0.003 0.005 0.027 0.026 (0.039)

VCT.RC.M 0.001 0.013 0.017 0.017 (0.058)

VCT.RC.L 0.142 0.156 0.162 0.162 (1.138)

VCT.SC.M 0.026 0.120 0.138 0.131 (0.327)

VCT.SC.L 0.014 0.014 0.015 0.015 (0.015)

VCT.SC.I 0.003 0.005 0.005 0.005 (0.040)

VCS.SC.M 0.114 0.136 0.156 0.156 (1.675)

VCS.SC.L 0.105 0.139 0.140 0.136 (1.053)

VCS.SC.I 0.000 0.001 0.001 0.001 (0.010)

SVO.RC.M 0.004 0.057 0.247 0.243 (0.218)

SVO.SC.M 0.008 0.012 0.030 0.027 (0.035)

SOC.RC.M 0.001 0.004 0.039 0.031 (0.053)

SOC.SC.M 0.001 0.001 0.004 0.003 (0.003)

HZO.RC.M - - - - (0.038)

HZO.RC.L - - - - (0.224)

HZO.SC.M 0.000 0.000 0.000 0.000 (0.007)

HZO.SC.L - - - - (0.006)

HCT.SC.M 0.000 0.001 0.001 0.001 (0.002)

HCT.SC.L 0.002 0.009 0.010 0.009 (0.015)

HCT.SC.I 0.000 0.001 0.001 0.001 (0.038)

HCS.SC.M 0.001 0.002 0.003 0.002 (0.162)

HCS.SC.L 0.002 0.002 0.003 0.003 (0.021)

PD.SC.M 0.119 0.119 0.238 0.181 (0.843)

Total 0.563 0.910 1.721 1.628 (6.523)

“-” represents zero energy savings, since TSLs 1 to 4 for equipment classes HZO.RC.M, HZO.RC.L 

and HZO.SC.L are associated with the baseline efficiency level.

*A value of 0.000 means NES values are less than $0.0005 billion 2012$.

10B-6 
Table 10B.1.5 Commercial Refrigeration Equipment: Net Present Value in Billions 

(2012$) at a 3 Percent Discount Rate – Low Price Scenario

billion 2012$

TSL1 TSL2 TSL3 TSL4 TSL5

VOP.RC.M 0.037 0.234 1.152 1.149 (0.498)

VOP.RC.L 0.005 0.030 0.032 0.032 (0.100)

VOP.SC.M 0.006 0.012 0.071 0.069 (0.049)

VCT.RC.M 0.001 0.031 0.041 0.041 (0.096)

VCT.RC.L 0.328 0.365 0.386 0.386 (1.949)

VCT.SC.M 0.059 0.285 0.334 0.330 (0.497)

VCT.SC.L 0.031 0.032 0.035 0.035 (0.018)

VCT.SC.I 0.007 0.011 0.012 0.012 (0.069)

VCS.SC.M 0.260 0.317 0.404 0.404 (2.878)

VCS.SC.L 0.239 0.325 0.331 0.330 (1.771)

VCS.SC.I 0.001 0.001 0.002 0.002 (0.018)

SVO.RC.M 0.009 0.138 0.620 0.614 (0.221)

SVO.SC.M 0.018 0.028 0.079 0.075 (0.038)

SOC.RC.M 0.003 0.010 0.094 0.080 (0.073)

SOC.SC.M 0.002 0.002 0.009 0.008 (0.003)

HZO.RC.M - - - - (0.069)

HZO.RC.L - - - - (0.399)

HZO.SC.M 0.000 0.000 0.000 0.000 (0.013)

HZO.SC.L - - - - (0.011)

HCT.SC.M 0.000 0.002 0.002 0.002 (0.004)

HCT.SC.L 0.004 0.022 0.022 0.022 (0.021)

HCT.SC.I 0.001 0.002 0.004 0.004 (0.064)

HCS.SC.M 0.003 0.005 0.007 0.006 (0.283)

HCS.SC.L 0.004 0.006 0.007 0.007 (0.033)

PD.SC.M 0.270 0.270 0.553 0.505 (1.345)

Total 1.288 2.129 4.198 4.113 (10.521)

“-” represents zero energy savings, since TSLs 1 to 4 for equipment classes HZO.RC.M, HZO.RC.L and 

HZO.SC.L are associated with the baseline efficiency level.

*A value of 0.000 means NES values are less than $0.0005 billion 2012$.

10B-7 
Table 10B.1.6 Commercial Refrigeration Equipment: Net Present Value in Billions 

(2012$) at a 7 Percent Discount Rate – Constant Real Price Scenario

billion 2012$

TSL1 TSL2 TSL3 TSL4 TSL5

VOP.RC.M 0.016 0.099 0.463 0.457 (0.485)

VOP.RC.L 0.002 0.013 0.014 0.014 (0.063)

VOP.SC.M 0.003 0.005 0.027 0.025 (0.042)

VCT.RC.M 0.001 0.013 0.017 0.016 (0.062)

VCT.RC.L 0.140 0.154 0.160 0.160 (1.195)

VCT.SC.M 0.026 0.119 0.135 0.127 (0.349)

VCT.SC.L 0.014 0.014 0.015 0.015 (0.016)

VCT.SC.I 0.003 0.004 0.005 0.005 (0.042)

VCS.SC.M 0.113 0.135 0.151 0.151 (1.757)

VCS.SC.L 0.105 0.137 0.138 0.134 (1.108)

VCS.SC.I 0.000 0.001 0.001 0.001 (0.011)

SVO.RC.M 0.004 0.056 0.243 0.237 (0.241)

SVO.SC.M 0.008 0.012 0.029 0.026 (0.039)

SOC.RC.M 0.001 0.004 0.039 0.030 (0.057)

SOC.SC.M 0.001 0.001 0.004 0.003 (0.003)

HZO.RC.M - - - - (0.040)

HZO.RC.L - - - - (0.233)

HZO.SC.M 0.000 0.000 0.000 0.000 (0.007)

HZO.SC.L - - - - (0.007)

HCT.SC.M 0.000 0.001 0.001 0.001 (0.003)

HCT.SC.L 0.002 0.009 0.010 0.009 (0.017)

HCT.SC.I 0.000 0.001 0.001 0.001 (0.039)

HCS.SC.M 0.001 0.002 0.003 0.001 (0.169)

HCS.SC.L 0.002 0.002 0.003 0.003 (0.022)

PD.SC.M 0.119 0.119 0.236 0.172 (0.894)

Total 0.560 0.901 1.693 1.588 (6.903)

“-” represents zero energy savings, since TSLs 1 to 4 for equipment classes HZO.RC.M, HZO.RC.L 

and HZO.SC.L are associated with the baseline efficiency level.

*A value of 0.000 means NES values are less than $0.0005 billion 2012$.

10B-8 
Table 10B.1.7 Commercial Refrigeration Equipment: Net Present Value in Billions 

(2012$) at a 3 Percent Discount Rate – Constant Real Price Scenario

billion 2012$

TSL1 TSL2 TSL3 TSL4 TSL5

VOP.RC.M 0.036 0.232 1.138 1.133 (0.590)

VOP.RC.L 0.005 0.030 0.032 0.032 (0.107)

VOP.SC.M 0.006 0.012 0.070 0.067 (0.056)

VCT.RC.M 0.001 0.030 0.041 0.040 (0.103)

VCT.RC.L 0.326 0.362 0.381 0.381 (2.070)

VCT.SC.M 0.059 0.282 0.329 0.322 (0.545)

VCT.SC.L 0.031 0.032 0.035 0.035 (0.021)

VCT.SC.I 0.007 0.011 0.012 0.012 (0.073)

VCS.SC.M 0.259 0.314 0.393 0.393 (3.053)

VCS.SC.L 0.239 0.322 0.328 0.325 (1.889)

VCS.SC.I 0.001 0.001 0.002 0.002 (0.019)

SVO.RC.M 0.008 0.136 0.610 0.604 (0.271)

SVO.SC.M 0.018 0.028 0.077 0.073 (0.046)

SOC.RC.M 0.003 0.010 0.093 0.078 (0.082)

SOC.SC.M 0.002 0.002 0.009 0.008 (0.004)

HZO.RC.M - - - - (0.073)

HZO.RC.L - - - - (0.420)

HZO.SC.M 0.000 0.000 0.000 0.000 (0.013)

HZO.SC.L - - - - (0.012)

HCT.SC.M 0.000 0.002 0.002 0.002 (0.004)

HCT.SC.L 0.004 0.022 0.022 0.022 (0.024)

HCT.SC.I 0.001 0.002 0.003 0.003 (0.068)

HCS.SC.M 0.003 0.005 0.007 0.006 (0.299)

HCS.SC.L 0.004 0.006 0.007 0.007 (0.036)

PD.SC.M 0.269 0.269 0.549 0.485 (1.454)

Total 1.282 2.110 4.139 4.030 (11.331)

“-” represents zero energy savings, since TSLs 1 to 4 for equipment classes HZO.RC.M, HZO.RC.L and 

HZO.SC.L are associated with the baseline efficiency level.

*A value of 0.000 means NES values are less than $0.0005 billion 2012$.

10B-9 
10C-i

APPENDIX 10C. TRIAL STANDARD LEVELS AND STANDARDS EQUATIONS

TABLE OF CONTENTS

10C.1 INTRODUCTION .......................................................................................................10C-1

10C.2 TRIAL STANDARD LEVEL SELECTION CRITERIA ...........................................10C-1

10C.3 TRIAL STANDARD LEVEL EQUATIONS .............................................................10C-8

LIST OF TABLES

Table 10C.2.1 TSL and Efficiency Levels Mapping ...............................................................10C-2

Table 10C.2.2 Design Options at Each TSL ............................................................................10C-3

Table 10C.2.3 TSL and Design Option Levels Mapping ........................................................10C-6

Table 10C.2.4 Efficiency Levels and Design Option Levels Mapping ...................................10C-7

Table 10C.3.1 CDEC Values by TSL for Representative Units Analyzed in the Engineering 

Analysis for Each Primary Equipment Class ...................................................10C-9

Table 10C.3.2 Equations Representing the Standards at Each TSL for All Primary Equipment 

Classes............................................................................................................10C-10

Table 10C.3.3 Equations Representing the Standards at Each TSL for All Secondary 

Equipment Classes .........................................................................................10C-12
10C-1 

APPENDIX 10C. TRIAL STANDARD LEVELS AND STANDARDS EQUATIONS

10C.1 INTRODUCTION

The U.S. Department of Energy (DOE) carried out the life-cycle cost (LCC) analysis and 

national impact analysis (NIA) by defining efficiency levels within each equipment class of 

commercial refrigeration equipment. These efficiency levels were chosen from the design option 

levels defined as part of the engineering analysis. These design option levels were defined based 

on the available energy efficiency technologies in the current market and are, generally, different 

for different equipment classes. Therefore, in general, the efficiency levels belonging to different 

equipment classes are independent of one another. For example, Efficiency Level 4 of one 

equipment class is not related to, or is dependent of the Efficiency Level 4 belonging to another 

equipment class (see chapter 8 of the technical support document (TSD) for criteria used in the 

selection of efficiency levels from the available design option levels). 

DOE developed trial standard levels (TSLs) by combining selected efficiency levels from 

each equipment class into TSL groupings based on a set of specific criteria. This process enables 

the grouping of efficiency levels across all equipment classes such that the efficiency levels 

belonging to a TSL grouping all have a certain uniform characteristic or criterion associated with 

them. DOE evaluated the national impacts, such as national energy savings (NES), net present 

value (NPV), employment impacts, impacts on manufacturers, and environmental impacts, at 

each TSL. Based on the results, DOE proposes to set the standard at a particular TSL. 

This appendix describes DOE’s method for selecting TSLs for commercial refrigeration 

equipment. The following sections describe the criteria used for TSL selection and standard level 

equations associated with each TSL. 

10C.2 TRIAL STANDARD LEVEL SELECTION CRITERIA

DOE selected five TSLs for this rulemaking based on the following criteria: 

1. TSL 5 was set at the maximum technologically feasible (max-tech) level for each 

equipment class. 

2. TSL 4 was chosen so as to include the highest efficiency level, within each equipment 

class, with a positive NPV at a 7-percent discount rate. 

3. TSL 3 was chosen to represent the efficiency level within each equipment class with the 

highest NPV at a 7-percent discount rate. 

4. For TSL 2, the efficiency levels were chosen to be one level below the efficiency levels 

belonging to TSL 3. However, in the instances where such a choice had NPV values close 

to the efficiency level belonging to TSL 3, the next lower level was chosen. 

5. For TSL 1, the efficiency levels were chosen to be one level below the efficiency levels 

belonging to TSL 2. However, in the instances where such a choice had NPV values 

close to the efficiency level belonging to TSL 2, the next lower level was chosen. 
10C-2 

Table 10C.2.1 presents the efficiency levels within each equipment class that belong to

the five TSL groupings. Equipment classes HZO.RC.M, HZO.RC.L and HZO.SC.L, have only 

two efficiency levels defined for the LCC analysis and NIA. Level 1 is the baseline efficiency 

level and Level 2 is the max-tech level. Also, the NPV values at Level 2 were negative and, 

therefore, did not satisfy the criteria for TSL 3 and TSL 4. Hence, Level 2, for each of these three 

equipment classes, was assigned to TSL 5, and Level 1 was allocated to TSL 1 through TSL 4. 

Table 10C.2.2 presents the design options at each TSL. Design options are generally cumulative 

as described in chapter 5, and particular technologies incorporated at a given TSL (e.g., TSL 4) 

dependent on equipment class. At TSL 5, the max tech, the final design option incorporated in 

most equipment classes was the use of Vacuum Insulated Panel (VIP) insulation. 

Table 10C.2.1 TSL and Efficiency Levels Mapping

Equipment 

Class

Intermediate 

Level*

Intermediate 

Level**

Max 

NPV***

Max Eff. Level 

with Pos-NPV†

MaxTech

Baseline TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VOP.RC.M Level 1 Level 2 Level 3 Level 4 Level 5 Level 6

VOP.RC.L Level 1 Level 2 Level 3 Level 4 Level 4 Level 5

VOP.SC.M Level 1 Level 3 Level 4 Level 5 Level 6 Level 7

VCT.RC.M Level 1 Level 2 Level 3 Level 4 Level 6 Level 7

VCT.RC.L Level 1 Level 3 Level 4 Level 5 Level 5 Level 6

VCT.SC.M Level 1 Level 2 Level 3 Level 4 Level 7 Level 8

VCT.SC.L Level 1 Level 3 Level 4 Level 5 Level 7 Level 8

VCT.SC.I Level 1 Level 3 Level 5 Level 6 Level 6 Level 7

VCS.SC.M Level 1 Level 3 Level 5 Level 7 Level 7 Level 8

VCS.SC.L Level 1 Level 3 Level 5 Level 6 Level 7 Level 8

VCS.SC.I Level 1 Level 3 Level 5 Level 6 Level 6 Level 7

SVO.RC.M Level 1 Level 2 Level 3 Level 4 Level 5 Level 6

SVO.SC.M Level 1 Level 3 Level 4 Level 5 Level 6 Level 7

SOC.RC.M Level 1 Level 2 Level 3 Level 4 Level 6 Level 7

HZO.RC.M‡ Level 1 Level 1 Level 1 Level 1 Level 1 Level 2

HZO.RC.L‡ Level 1 Level 1 Level 1 Level 1 Level 1 Level 2

HZO.SC.M Level 1 Level 2 Level 2 Level 3 Level 4 Level 5

HZO.SC.L‡ Level 1 Level 1 Level 1 Level 1 Level 1 Level 2

HCT.SC.M Level 1 Level 3 Level 5 Level 6 Level 7 Level 8

HCT.SC.L Level 1 Level 3 Level 4 Level 5 Level 7 Level 8

HCT.SC.I Level 1 Level 2 Level 3 Level 4 Level 4 Level 5

HCS.SC.M Level 1 Level 2 Level 3 Level 4 Level 5 Level 7

HCS.SC.L Level 1 Level 4 Level 5 Level 6 Level 6 Level 7

PD.SC.M Level 1 Level 2 Level 2 Level 3 Level 7 Level 8

SOC.SC.M Level 1 Level 3 Level 4 Level 5 Level 7 Level 8

“Level” stands for “Efficiency Level.”

* TSL generally chosen as one level below TSL 2, but could be lower if the immediate lower level is too close to 

TSL 2 when the NPV values are compared. **TSL generally chosen as one level below TS L3, but could be lower if the immediate lower level is too close to 

TSL 3 when the NPV values are compared. ***Efficiency level that has the highest NPV at a 7-percent discount rate.

†

Highest efficiency level with a positive NPV at a 7-percent discount rate.

‡

TSLs 1 through 4 for these equipment classes do not satisfy the criteria for the corresponding TSL selection. They 

were assigned the baseline efficiency level for TSLs 1 through 4.
10C-3 

Table 10C.2.2 Design Options at Each TSL

Equipment 

Class Baseline TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VOP.RC.M ECM Evaporator Fan, 

Super T8 Lighting Night Curtains Enhanced EvaporatorCoil

LED with Occupancy

Sensor

1/2" insulation VIP

VOP.RC.L

ECM Evaporator Fan, 

Night Curtains, Super 

T8 Lighting

Enhanced Evaporator

Coil

LED with Occupancy

Sensor

1/2" insulation Same as TSL 3 VIP

VOP.SC.M

High-Efficiency

Compressor, Enhanced 

Condenser Coil, ECM 

Evaporator Fan, Super 

T8 Lighting

Night Curtains PSC Condenser Fan ECM Condenser Fan 1/2" insulation VIP

VCT.RC.M LED, PSC Evaporator

Fan ECM Evaporator Fan High-PerformanceDoor Occupancy Sensor

1/2" insulation, 

Enhanced Evaporator

Coil

VIP

VCT.RC.L LED, ECM Evaporator

Fan

High-Performance

Door, LED with 

Occupancy Sensor

1/2" insulation Enhanced Evaporator

Coil Same as TSL 3 VIP

VCT.SC.M LED, High-Efficiency

Compressor 

Enhanced Evaporator

Coil, ECM Evaporator

Fan

High-Performance

Door, PSC Condenser

Fan

Occupancy Sensor

ECM Condenser Fan, 

1/2" insulation, 

Enhanced Evaporator

Coil

VIP

VCT.SC.L Baseline

LED, Enhanced 

Condenser Coil, HighEfficiency Compressor, 

ECM Evaporator Fan, 

High-Performance

Door

Enhanced Evaporator

Coil Occupancy Sensor

1/2" insulation, ECM 

Condenser Fan VIP

VCT.SC.I

LED, Enhanced 

Evaporator Coil, 

Enhanced Condenser

Coil, High-Efficiency

Compressor, ECM Fan 

Motor

High-Perform Door, 

PSC Condenser Fan

Occupancy Sensor, 

ECM Con Fan 1/2" insulation Same as TSL 3 VIP

ECM = Electronically Commutated Motors PSC = Permanent Split Capacitor Motor LED = Light Emitting Diode VIP = Vacuum Insulated Panels

High-Efficiency Compressor = High-Efficiency Reciprocating Compressor Occupancy Sensor = Occupancy Sensor (with LED lighting)
10C-4 

Table 10C.2.2 (cont)

Equipment 

Class Baseline TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VCS.SC.M Baseline

Enhanced Condenser

Coil, ECM Evaporator

Fan, High-Efficiency

Compressor

Enhanced Evaporator

Coil, PSC Condenser

Fan

ECM Condenser Fan, 

1/2" insulation Same as TSL 3 VIP

VCS.SC.L Baseline

Enhanced Condenser

Coil, ECM Evaporator

Fan, High-Efficiency

Compressor

Enhanced Evaporator

Coil, 1/2" insulation PSC Condenser Fan ECM Condenser Fan VIP

VCS.SC.I

Enhanced Condenser

Coil, PSC Evaporator

Fan, Enhanced 

Evaporator Coil

ECM Evaporator Fan, 

High-Efficiency

Compressor 

PSC Condenser Fan, 

1/2" insulation ECM Condenser Fan Same as TSL 3 VIP

SVO.RC.M ECM Evaporator Fan, 

Super T8 Lighting

Enhanced Evaporator

Coil Night Curtains LED with OccupancySensor

1/2" insulation VIP

SVO.SC.M

High-Efficiency

Compressor, Enhanced 

Cond Coil, Super T8 

Lighting, ECM 

Evaporator Fan, PSC 

Cond Fan

Enhanced Evap Coil, 

Night Curtains ECM Cond Fan LED with OccupancySensor

1/2" insulation VIP

SOC.RC.M PSC Evaporator Fan, 

Super T8 Lighting ECM Evaporator Fan Enhanced EvaporatorCoil LED 1/2" insulation, HighPerformance Door VIP

HZO.RC.M

ECM Evaporator Fan, 

Enhanced Evaporator

Coil, 1/2" insulation

Baseline Baseline Baseline Baseline VIP

HZO.RC.L

ECM Evaporator Fan, 

Enhanced Evaporator

Coil, 1/2" insulation

Baseline Baseline Baseline Baseline VIP

HZO.SC.M

High-Efficiency

Compressor, Enhanced 

Condenser Coil, 

Enhanced Evaporator

Coil, ECM Evaporator

Fan

PSC Condenser Fan Same as TSL 1 ECM Condenser Fan 1/2" insulation VIP

ECM = Electronically Commutated Motors PSC = Permanent Split Capacitor Motor LED = Light Emitting Diode VIP = Vacuum Insulated Panels

High-Efficiency Compressor = High-Efficiency Reciprocating Compressor Occupancy Sensor = Occupancy Sensor (with LED lighting)
10C-5 

Table 10C.2.2 (cont)

Equipment 

Class Baseline TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

HZO.SC.L

High-Efficiency

Compressor, Enhanced 

Condenser Coil, 

Enhanced Evaporator

Coil, ECM Evaporator

Fan, PSC Condenser

Fan, 1/2" insulation

Baseline Baseline Baseline Baseline VIP

HCT.SC.M Baseline

Enhanced Condenser

Coil, High-Efficiency

Compressor

PSC Condenser Fan, 

High-Performance

Door

ECM Condenser Fan 1/2" insulation VIP

HCT.SC.L Baseline

Enhanced Condenser

Coil, High-Efficiency

Compressor

High-Performance

Door, PSC Condenser

Fan

ECM Condenser Fan 1/2" insulation VIP

HCT.SC.I

High-Efficiency

Compressor, PSC 

Condenser Fan

High-Performance

Door ECM Condenser Fan 1/2" insulation Same as TSL 3 VIP

HCS.SC.M Baseline Enhanced Condenser

Coil

High-Efficiency

Compressor 

PSC Condenser Fan ECM Condenser Fan

1/2" 

insulation, 

VIP

HCS.SC.L Baseline

Enhanced Condenser

Coil, High-Efficiency

Compressor, PSC 

Condenser Fan

ECM Condenser Fan 1/2" insulation Same as TSL 3 VIP

PD.SC.M Baseline

LED, Enhanced 

Condenser Coil, ECM 

Evaporator Fan, HighEfficiency Compressor, 

Same as TSL 1 High-Performance

Door

ECM Condenser Fan, 

Occupancy Sensor, 

1/2" insulation, 

Enhanced Evaporator

Coil

VIP

SOC.SC.M

High-Efficiency

Compressor, Enhanced 

Condenser Coil

Super T8 Lighting, 

ECM Evaporator Fan ECM Condenser Fan LED 1/2" insulation, HighPerformance Door VIP

ECM = Electronically Commutated Motors PSC = Permanent Split Capacitor Motor LED = Light Emitting Diode VIP = Vacuum Insulated Panels

High-Efficiency Compressor = High-Efficiency Reciprocating Compressor Occupancy Sensor = Occupancy Sensor (with LED lighting)
10C-6 

Table 10C.2.3 presents the mapping between the TSLs and design option levels. 

Table 10C.2.4 presents the mapping between efficiency levels and design option levels.

Table 10C.2.3 TSL and Design Option Levels Mapping

Equipment 

Class Baseline TSL 1 TSL 2 TSL 3 TSL 4 TSL 5 

VOP.RC.M SB AD5 AD6 AD7 AD8 AD9

VOP.RC.L SB AD6 AD7 AD8 AD8 AD9

VOP.SC.M SB AD9 AD10 AD11 AD12 AD13

VCT.RC.M SB AD4 AD5 AD6 AD8 AD9

VCT.RC.L SB AD6 AD7 AD8 AD8 AD9

VCT.SC.M SB AD6 AD8 AD9 AD12 AD13

VCT.SC.L AD1 AD7 AD8 AD9 AD12 AD13

VCT.SC.I SB AD9 AD11 AD12 AD12 AD13

VCS.SC.M AD1 AD5 AD7 AD9 AD9 AD10

VCS.SC.L AD1 AD5 AD7 AD8 AD9 AD10

VCS.SC.I SB AD6 AD8 AD9 AD9 AD10

SVO.RC.M SB AD5 AD6 AD7 AD8 AD9

SVO.SC.M SB AD9 AD10 AD11 AD12 AD13

SOC.RC.M SB AD4 AD5 AD6 AD8 AD9

HZO.RC.M SB SB SB SB SB AD6

HZO.RC.L SB SB SB SB SB AD6

HZO.SC.M SB AD7 AD7 AD8 AD9 AD10

HZO.SC.L SB SB SB SB SB AD10

HCT.SC.M AD1 AD3 AD5 AD6 AD7 AD8

HCT.SC.L AD1 AD3 AD4 AD5 AD7 AD8

HCT.SC.I SB AD4 AD5 AD6 AD6 AD7

HCS.SC.M AD1 AD2 AD3 AD4 AD5 AD7

HCS.SC.L AD1 AD4 AD5 AD6 AD6 AD7

PD.SC.M SB AD6 AD6 AD7 AD12 AD13

SOC.SC.M SB AD8 AD9 AD10 AD12 AD13

“AD” represents “Design Option Level.” For example, AD12 represents Design Option Level 12. For details on 

the design options associated with each design option level within each equipment class, see TSD chapter 5.

“

SB” stands for “Standards Baseline.” See TSD chapter 8 for a discussion related to the selection of the standards 

baseline.
10C-7 

Table 10C.2.4 Efficiency Levels and Design Option Levels Mapping

Equipment 

Class Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 8

VOP.RC.M SB AD5 AD6 AD7 AD8 AD9 NA NA

VOP.RC.L SB AD6 AD7 AD8 AD9 NA NA NA

VOP.SC.M SB AD8 AD9 AD10 AD11 AD12 AD13 AD13

VCT.RC.M SB AD4 AD5 AD6 AD7 AD8 AD9 NA

VCT.RC.L SB AD5 AD6 AD7 AD8 AD9 NA NA

VCT.SC.M SB AD6 AD8 AD9 AD10 AD11 AD12 AD13

VCT.SC.L AD1 AD4 AD7 AD8 AD9 AD10 AD12 AD13

VCT.SC.I SB AD8 AD9 AD10 AD11 AD12 AD13 NA

VCS.SC.M AD1 AD4 AD5 AD6 AD7 AD8 AD9 AD10

VCS.SC.L AD1 AD4 AD5 AD6 AD7 AD8 AD9 AD10

VCS.SC.I SB AD5 AD6 AD7 AD8 AD9 AD10 NA

SVO.RC.M SB AD5 AD6 AD7 AD8 AD9 NA NA

SVO.SC.M SB AD8 AD9 AD10 AD11 AD12 AD13 NA

SOC.RC.M SB AD4 AD5 AD6 AD7 AD8 AD9 NA

HZO.RC.M SB AD6 NA NA NA NA NA NA

HZO.RC.L SB AD6 NA NA NA NA NA NA

HZO.SC.M SB AD7 AD8 AD9 AD10 NA NA NA

HZO.SC.L SB AD10 NA NA NA NA NA NA

HCT.SC.M AD1 AD2 AD3 AD4 AD5 AD6 AD7 AD8

HCT.SC.L AD1 AD2 AD3 AD4 AD5 AD6 AD7 AD8

HCT.SC.I SB AD4 AD5 AD6 AD7 NA NA NA

HCS.SC.M AD1 AD2 AD3 AD4 AD5 AD6 AD7 NA

HCS.SC.L AD1 AD2 AD3 AD4 AD5 AD6 AD7 NA

PD.SC.M SB AD6 AD7 AD8 AD9 AD10 AD12 AD13

SOC.SC.M SB AD6 AD8 AD9 AD10 AD11 AD12 AD13

“AD” represents “Design Option Level.” For example, AD12 represents Design Option Level 12. For details on the design 

options associated with each design option level within each equipment class, see TSD chapter 5.

“SB” stands for “Standards Baseline”. See TSD chapter 8 for a discussion related to the selection of standards baseline.

“NA” stands for not applicable, and is used where the number of efficiency levels for an equipment class is less than 8.

“Level” stands for “Efficiency Level.”

DOE considered two additional criteria for TSL groupings. One criterion was to group 

the efficiency levels with the lowest LCC (Minimum-LCC grouping) and the other criterion was 

to group the highest efficiency levels with payback periods less than 3 years (Payback Period 

grouping). The Minimum-LCC grouping had the same efficiency levels as TSL 3 except for 

three equipment classes, which had efficiency levels one level higher than TSL 3. The net NES 

and NPV values associated with this grouping were almost identical to those of TSL 3. The 

Payback Period grouping was infeasible because certain equipment classes did not have any 

efficiency levels with payback periods less than 3 years. For the equipment classes that had 

efficiency levels with payback periods less than 3 years, the efficiency levels were higher than 

those of TSL 3 in some equipment classes, lower in some others, and equal in the rest. Neither of 

these additional TSL groupings showed a distinct advantage over the five TSL groupings 

described above. Therefore, these additional groupings were discarded for the downstream 

analyses. 
10C-8 

10C.3 TRIAL STANDARD LEVEL EQUATIONS

Because of the equipment size variation within each equipment class and the use of daily 

energy consumption as the efficiency metric, DOE developed a methodology to express 

efficiency standards in terms of a normalizing metric. DOE utilized one of two normalizing 

metrics for each equipment class: (1) volume (V) or (2) total display area (TDA). The use of 

these two normalization metrics allowed for the development of the energy conservation 

standard in the form of a linear equation that could be used to represent the entire range of 

equipment sizes within a given equipment class. DOE retained the respective normalization 

metric (TDA or volume) previously used in the Energy Policy Act of 2005 (EPACT 2005), the 

January 2009 final rule standards for each covered equipment class, or the American Energy 

Manufacturing Technical Corrections Act (AEMTCA). (42 U.S.C. 6313(c)(2)–(3)); 74 FR 1092, 

1093 (Jan. 9, 2009); (42 U.S.C. 6313(c)(4)). 

In its January 2009 final rule, DOE developed offset factors as a way to adjust the energy 

efficiency requirements for smaller equipment in each equipment class analyzed. These offset 

factors, which form the y-intercept on a plot of each standard level equation (representing a 

fictitious case of zero volume or zero TDA), accounted for certain components of the 

refrigeration load (such as conduction end effects) that remain constant even when equipment 

sizes vary. These constant loads affect smaller cases disproportionately. The offset factors were 

intended to approximate these constant loads and provide a fixed end point in an equation that 

describes the relationship between energy consumption and the corresponding normalization 

metric. 74 FR at 1118–19 (Jan. 9, 2009).The standard levels equations prescribed by EPACT 

2005 also contained similar fixed parts not multiplied by the volume metric and which 

correspond to these offset factors. In this notice of proposed rulemaking, DOE modified the 

January 2009 final rule (74 FR at 1118–19 (Jan. 9, 2009)) and EPACT 2005 offset factors at 

each TSL to reflect the proportional changes in energy consumption for each equipment class, as 

modeled in the engineering analysis. See chapter 5 of the TSD for further details and discussion 

of offset factors. 

For the equipment classes covered under this rulemaking, the standards equation at each

TSL is proposed in the form of maximum daily energy consumption (MDEC) (in kilowatt-hours 

(kWh) per day) normalized by a volume (V) or TDA metric. These equations take the form:

MDEC = A × TDA + B (for equipment using TDA as a normalizing metric)

or 

MDEC = A × V + B (for equipment using volume as a normalizing metric)

For equipment classes directly analyzed in the engineering analysis, the offset factor, B, 

was calculated for each class (see chapter 5 of the TSD for discussion of offset factors). The 

slope, A, was derived based on the offset factor, B, and the calculated daily energy consumption 

(CDEC) of the representative unit modeled in the engineering analysis for that equipment class 

(presented in Table 10C.3.1). The standards equations (presented in Table 10C.3.2 at each TSL)

would be used to prescribe the MDEC for equipment of different sizes within a given equipment 

class.
10C-9 

Table 10C.3.1 CDEC Values by TSL for Representative Units Analyzed in the Engineering 

Analysis for Each Primary Equipment Class

Equipment Class

CDEC Values by TSL

kWh/day

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VOP.RC.M 46.84 44.33 35.71 35.51 35.06

VOP.RC.L 106.22 101.03 100.51 100.51 98.87

VOP.SC.M 30.03 29.60 26.70 26.62 26.46

VCT.RC.M 15.56 8.10 6.26 5.97 5.49

VCT.RC.L 31.13 30.58 30.29 30.29 28.85

VCT.SC.M 7.56 4.08 3.24 2.97 2.68

VCT.SC.L 13.48 13.30 12.44 12.09 11.57

VCT.SC.I 17.45 16.36 16.14 16.14 15.37

VCS.SC.M 2.36 2.17 1.81 1.81 1.39

VCS.SC.L 7.26 6.75 6.66 6.56 5.71

VCS.SC.I 18.24 17.79 17.64 17.64 16.53

SVO.RC.M 36.11 33.85 27.71 27.57 27.26

SVO.SC.M 25.74 25.36 23.29 23.24 23.12

SOC.RC.M 25.62 24.97 20.43 20.15 19.93

HZO.RC.M 14.43 14.43 14.43 14.43 14.17

HZO.RC.L 33.10 33.10 33.10 33.10 32.22

HZO.SC.M 14.76 14.76 14.60 14.49 14.26

HZO.SC.L 30.12 30.12 30.12 30.12 29.91

HCT.SC.M 1.87 0.84 0.75 0.67 0.49

HCT.SC.L 4.11 1.83 1.77 1.57 1.18

HCT.SC.I 3.22 3.07 2.86 2.86 2.13

HCS.SC.M 0.65 0.60 0.56 0.50 0.25

HCS.SC.L 1.61 1.46 1.27 1.27 0.74

PD.SC.M 3.90 3.90 2.23 1.64 1.42

SOC.SC.M 27.04 26.80 22.02 21.70 21.41
10C-10

Table 10C.3.2 Equations Representing the Standards at Each TSL for All Primary Equipment Classes

Equipment 

Class

Trial Standard Levels for Primary Equipment Classes Analyzed

Baseline TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VCT.RC.L 0.56 × TDA + 2.61 0.45 × TDA + 2.08 0.44 × TDA + 2.05 0.43 × TDA + 2.03 0.43 × TDA + 2.03 0.41 × TDA + 1.93

VOP.RC.M 0.82 × TDA + 4.07 0.8 × TDA + 3.99 0.76 × TDA + 3.78 0.61 × TDA + 3.04 0.61 × TDA + 3.03 0.6 × TDA + 2.99

SVO.RC.M 0.83 × TDA + 3.18 0.82 × TDA + 3.16 0.77 × TDA + 2.96 0.63 × TDA + 2.42 0.63 × TDA + 2.41 0.62 × TDA + 2.38

HZO.RC.L 0.57 × TDA + 6.88 0.57 × TDA + 6.88 0.57 × TDA + 6.88 0.57 × TDA + 6.88 0.57 × TDA + 6.88 0.55 × TDA + 6.7

HZO.RC.M 0.35 × TDA + 2.88 0.35 × TDA + 2.88 0.35 × TDA + 2.88 0.35 × TDA + 2.88 0.35 × TDA + 2.88 0.34 × TDA + 2.83

VCT.RC.M 0.22 × TDA + 1.95 0.21 × TDA + 1.87 0.11 × TDA + 0.97 0.08 × TDA + 0.75 0.08 × TDA + 0.72 0.07 × TDA + 0.66

VOP.RC.L 2.27 × TDA + 6.85 2.23 × TDA + 6.72 2.12 × TDA + 6.39 2.11 × TDA + 6.36 2.11 × TDA + 6.36 2.07 × TDA + 6.26

SOC.RC.M 0.51 × TDA + 0.11 0.5 × TDA + 0.11 0.49 × TDA + 0.11 0.4 × TDA + 0.09 0.39 × TDA + 0.08 0.39 × TDA + 0.08

VOP.SC.M 1.74 × TDA + 4.71 1.7 × TDA + 4.61 1.68 × TDA + 4.54 1.51 × TDA + 4.1 1.51 × TDA + 4.09 1.5 × TDA + 4.06

SVO.SC.M 1.73 × TDA + 4.59 1.67 × TDA + 4.42 1.64 × TDA + 4.35 1.51 × TDA + 4. 1.5 × TDA + 3.99 1.5 × TDA + 3.97

HZO.SC.L 1.92 × TDA + 7.08 1.92 × TDA + 7.08 1.92 × TDA + 7.08 1.92 × TDA + 7.08 1.92 × TDA + 7.08 1.91 × TDA + 7.03

HZO.SC.M 0.77 × TDA + 5.55 0.77 × TDA + 5.54 0.77 × TDA + 5.54 0.76 × TDA + 5.48 0.75 × TDA + 5.44 0.74 × TDA + 5.35

HCT.SC.I 0.56 × TDA + 0.43 0.55 × TDA + 0.42 0.52 × TDA + 0.4 0.49 × TDA + 0.37 0.49 × TDA + 0.37 0.36 × TDA + 0.28

VCT.SC.I 0.67 × TDA + 3.29 0.56 × TDA + 2.77 0.53 × TDA + 2.6 0.52 × TDA + 2.56 0.52 × TDA + 2.56 0.5 × TDA + 2.44

VCS.SC.I 0.38 × V + 0.88 0.36 × V + 0.84 0.35 × V + 0.82 0.35 × V + 0.81 0.35 × V + 0.81 0.33 × V + 0.76

VCT.SC.M 0.12 × V + 3.34 0.1 × V + 2.74 0.05 × V + 1.48 0.04 × V + 1.17 0.04 × V + 1.07 0.03 × V + 0.97

VCT.SC.L 0.53 × V + 2.92 0.25 × V + 1.35 0.24 × V + 1.33 0.23 × V + 1.25 0.22 × V + 1.21 0.21 × V + 1.16

VCS.SC.M 0.06 × V + 1.31 0.03 × V + 0.69 0.03 × V + 0.64 0.03 × V + 0.53 0.03 × V + 0.53 0.02 × V + 0.41

VCS.SC.L 0.21 × V + 0.72 0.14 × V + 0.48 0.13 × V + 0.44 0.13 × V + 0.44 0.13 × V + 0.43 0.11 × V + 0.38

HCT.SC.M 0.06 × V + 1.73 0.05 × V + 1.42 0.02 × V + 0.63 0.02 × V + 0.57 0.02 × V + 0.51 0.01 × V + 0.38

HCT.SC.L 0.36 × V + 1.98 0.29 × V + 1.57 0.13 × V + 0.70 0.12 × V + 0.68 0.11 × V + 0.6 0.08 × V + 0.45

HCS.SC.M 0.03 × V + 0.54 0.02 × V + 0.49 0.02 × V + 0.45 0.02 × V + 0.41 0.02 × V + 0.37 0.01 × V + 0.18

HCS.SC.L 0.2 × V + 0.69 0.15 × V + 0.53 0.14 × V + 0.48 0.12 × V + 0.42 0.12 × V + 0.42 0.07 × V + 0.24

PD.SC.M 0.13 × V + 3.51 0.07 × V + 1.98 0.07 × V + 1.98 0.04 × V + 1.13 0.03 × V + 0.83 0.03 × V + 0.72

SOC.SC.M 0.6 × TDA + 1.0 0.4 × TDA + 0.67 0.4 × TDA + 0.66 0.33 × TDA + 0.54 0.32 × TDA + 0.53 0.32 × TDA + 0.53
10C-11

In addition to the 25 primary equipment classes analyzed, DOE intends to amend 

standards for 24 secondary classes of commercial refrigeration equipment covered in this 

rulemaking that were not directly analyzed in the engineering analysis. DOE’s approach involves 

extension multipliers developed using the primary equipment classes analyzed and a set of 

matched-pair analyses performed during the January 2009 final rule analysis. In addition, DOE 

believes that standards for certain primary equipment classes can be directly applied to similar 

secondary equipment classes. Chapter 5 of the TSD discusses the development of the extension 

multipliers. 

Using the extension multiplier approach, DOE developed an additional set of TSLs and 

associated equations for the secondary equipment classes, as shown in Table 10C.3.3. The TSLs

shown in Table 10C.3.3 do not necessarily satisfy the criteria spelled out in section 10C.2

because the analyses required to evaluate the criteria were not performed for those classes. DOE 

is presenting the standards equations developed for each TSL for all 49 equipment classes to 

allow interested parties to better review the ramifications of each TSL across the range of 

product sizes on the market. 
10C-12

Table 10C.3.3 Equations Representing the Standards at Each TSL for All Secondary Equipment Classes

Equipment 

Class

Trial Standard Levels for Secondary Equipment Classes Analyzed

Baseline TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VOP.RC.I 2.89 × TDA + 8.7 2.83 × TDA + 8.54 2.69 × TDA + 8.12 2.68 × TDA + 8.08 2.68 × TDA + 8.08 2.63 × TDA + 7.95

SVO.RC.L 2.27 × TDA + 6.85 2.23 × TDA + 6.72 2.12 × TDA + 6.39 2.11 × TDA + 6.36 2.11 × TDA + 6.36 2.07 × TDA + 6.26

SVO.RC.I 2.89 × TDA + 8.7 2.83 × TDA + 8.54 2.69 × TDA + 8.12 2.68 × TDA + 8.08 2.68 × TDA + 8.08 2.63 × TDA + 7.95

HZO.RC.I 0.72 × TDA + 8.74 0.72 × TDA + 8.74 0.72 × TDA + 8.74 0.72 × TDA + 8.74 0.72 × TDA + 8.74 0.7 × TDA + 8.5

VOP.SC.L 4.37 × TDA + 11.82 4.27 × TDA + 11.57 4.21 × TDA + 11.4 3.8 × TDA + 10.29 3.79 × TDA + 10.26 3.77 × TDA + 10.2

VOP.SC.I 5.55 × TDA + 15.02 5.43 × TDA + 14.69 5.35 × TDA + 14.48 4.83 × TDA + 13.06 4.81 × TDA + 13.03 4.78 × TDA + 12.95

SVO.SC.L 4.34 × TDA + 11.51 4.18 × TDA + 11.09 4.12 × TDA + 10.93 3.78 × TDA + 10.04 3.77 × TDA + 10.01 3.76 × TDA + 9.96

SVO.SC.I 5.52 × TDA + 14.63 5.31 × TDA + 14.09 5.23 × TDA + 13.88 4.8 × TDA + 12.75 4.79 × TDA + 12.72 4.77 × TDA + 12.65

HZO.SC.I 2.44 × TDA + 9.0 2.44 × TDA + 9.0 2.44 × TDA + 9.0 2.44 × TDA + 9.0 2.44 × TDA + 9.0 2.42 × TDA + 8.93

SOC.RC.L 1.08 × TDA + 0.22 1.05 × TDA + 0.23 1.02 × TDA + 0.22 0.84 × TDA + 0.18 0.83 × TDA + 0.18 0.82 × TDA + 0.18

SOC.RC.I 1.26 × TDA + 0.26 1.23 × TDA + 0.27 1.2 × TDA + 0.26 0.98 × TDA + 0.21 0.97 × TDA + 0.21 0.96 × TDA + 0.21

SOC.SC.I 1.76 × TDA + 0.36 1.72 × TDA + 0.37 1.68 × TDA + 0.36 1.37 × TDA + 0.3 1.35 × TDA + 0.29 1.34 × TDA + 0.29

VCT.RC.I 0.66 × TDA + 3.05 0.52 × TDA + 2.44 0.51 × TDA + 2.39 0.51 × TDA + 2.37 0.51 × TDA + 2.37 0.48 × TDA + 2.26

HCT.RC.M 0.16 × TDA + 0.13 0.16 × TDA + 0.12 0.15 × TDA + 0.12 0.14 × TDA + 0.11 0.14 × TDA + 0.11 0.1 × TDA + 0.08

HCT.RC.L 0.34 × TDA + 0.26 0.33 × TDA + 0.26 0.32 × TDA + 0.24 0.3 × TDA + 0.23 0.3 × TDA + 0.23 0.22 × TDA + 0.17

HCT.RC.I 0.4 × TDA + 0.31 0.39 × TDA + 0.3 0.37 × TDA + 0.29 0.35 × TDA + 0.27 0.35 × TDA + 0.27 0.26 × TDA + 0.2

VCS.RC.M 0.11 × V + 0.26 0.11 × V + 0.24 0.1 × V + 0.24 0.1 × V + 0.24 0.1 × V + 0.24 0.1 × V + 0.22

VCS.RC.L 0.23 × V + 0.54 0.22 × V + 0.51 0.22 × V + 0.5 0.21 × V + 0.5 0.21 × V + 0.5 0.2 × V + 0.46

VCS.RC.I 0.27 × V + 0.63 0.26 × V + 0.6 0.25 × V + 0.58 0.25 × V + 0.58 0.25 × V + 0.58 0.23 × V + 0.54

HCS.SC.I 0.38 × V + 0.88 0.36 × V + 0.84 0.35 × V + 0.82 0.35 × V + 0.81 0.35 × V + 0.81 0.33 × V + 0.76

HCS.RC.M 0.11 × V + 0.26 0.11 × V + 0.24 0.1 × V + 0.24 0.1 × V + 0.24 0.1 × V + 0.24 0.1 × V + 0.22

HCS.RC.L 0.23 × V + 0.54 0.22 × V + 0.51 0.22 × V + 0.5 0.21 × V + 0.5 0.21 × V + 0.5 0.2 × V + 0.46

HCS.RC.I 0.27 × V + 0.63 0.26 × V + 0.6 0.25 × V + 0.58 0.25 × V + 0.58 0.25 × V + 0.58 0.23 × V + 0.54

SOC.SC.L 0.75 × V + 4.10 0.84 × TDA + 1.4 0.83 × TDA + 1.39 0.68 × TDA + 1.14 0.67 × TDA + 1.12 0.66 × TDA + 1.11
APPENDIX 10D. FULL-FUEL-CYCLE MULTIPLIERS

TABLE OF CONTENTS

10D.1 INTRODUCTION ...................................................................................................... 10D-1

10D.2 METHODOLOGY ..................................................................................................... 10D-1

10D.3 FULL-FUEL-CYCLE ENERGY MULTIPLIERS .................................................... 10D-3

REFERENCES ....................................................................................................................... 10D-4

LIST OF TABLES

Table 10D.2.1 Dependence of FFC Parameters on AEO Inputs ............................................. 10D-3

Table 10D.3.1 Full-Fuel-Cycle Energy Multipliers (Based on AEO2013) ............................ 10D-3

 

10D-i 
APPENDIX 10D. FULL-FUEL-CYCLE MULTIPLIERS

10D.1 INTRODUCTION

This appendix summarizes the methods used to calculate full-fuel-cycle (FFC) energy 

savings expected to result from potential standards. The FFC measure includes point-of-use (site) 

energy, the energy losses associated with generation, transmission, and distribution of electricity, and 

the energy consumed in extracting, processing, and transporting or distributing primary fuels. The 

U.S. Department of Energy’s (DOE’s) traditional approach encompassed only site energy and the 

energy losses associated with generation, transmission, and distribution of electricity. Per DOE’s 

2011 Statement of Policy for Adopting Full Fuel Cycle Analyses, DOE now uses FFC measures of 

energy use and emissions in its energy conservation standards analyses.76 FR 51281 (Aug. 18, 

2011), as amended at 77 FR 49701 (Aug. 17, 2012). This appendix summarizes the methods used 

to incorporate the FFC impacts into the analysis. 

This analysis uses several different terms to reference energy use. The physical sources of 

energy are the primary fuels such as coal, natural gas, liquid fuels, etc. Primary energy is equal to 

the heat content (British thermal units) of the primary fuels used to provide an end-use service. 

Site energy use is defined as the energy consumed at the point-of-use in a building or industrial 

process. Where natural gas and petroleum fuels are consumed at the site (for example, in a 

furnace), site energy is identical to primary energy, with both equal to the heat content of the 

primary fuel consumed. For electricity, site energy is measured in kilowatt-hours. In this case, 

the primary energy is equal to the quadrillion British thermal units (quads) of primary energy 

required to generate and deliver the site electricity. This primary energy is calculated by 

multiplying the site kilowatt-hours by the site-to-power plant energy use factor, given in chapter 

10. For the FFC analysis, the upstream energy use is defined as the energy consumed in 

extracting, processing, and transporting or distributing primary fuels. FFC energy use is the sum 

of primary plus upstream energy use. 

Both primary fuels and electricity are used in upstream activities. The treatment of 

electricity in fuel cycle analysis must distinguish between electricity generated by fossil fuels 

and uranium, and electricity generated from renewable fluxes (wind, solar, and hydro). For the 

former, the upstream fuel cycle impacts are derived from the amount of fuel consumed at the 

power plant. For the latter, no fuel per se is used, so there is no upstream component. 

10D.2 METHODOLOGY

The mathematical approach is discussed in the paper A Mathematical Analysis of Full 

Fuel Cycle Energy Use,

1

 and details on the fuel production chain analysis are presented in the 

paper Projections of Full Fuel Cycle Energy and Emissions Metrics.

2 The following discussion 

provides a brief summary of the methods used to calculate FFC energy. 

When all energy quantities are normalized to the same units, the FFC energy use can be 

represented as the product of the primary energy use and an FFC multiplier. The FFC multiplier 

is defined mathematically as a function of a set of parameters representing the energy intensity 

and material losses at each production stage. These parameters depend only on physical data, so 

the calculations do not require any assumptions about prices or other economic data. While in 

10D-1 
general these parameter values may vary by geographic region, for this analysis national 

averages are used. 

In the notation below, the indices x and y are used to indicate fuel type, with x=c for coal, 

x=g for natural gas, x=p for petroleum fuels, x=u for uranium, and x=r for renewable fluxes. The 

fuel cycle parameters are the following: 

• ax is the quantity of fuel x burned per unit of electricity output, on average, for grid 

electricity. The calculation of ax includes a factor to account for transmission and 

distribution system losses. 

• by is the amount of grid electricity used in production of fuel y, in megawatt-hours per 

physical unit of fuel y. 

• cxy is the amount of fuel x consumed in producing one unit of fuel y. 

• qx is the heat content of fuel x (million British thermal units/physical unit) 

• zx(s) is the emissions intensity for fuel x (mass of pollutant s per physical unit of x) 

The parameters are calculated as a function of time with an annual time step; hence, a 

time series of annual values is used to estimate the FFC energy and emissions savings in each 

year of the analysis period. Fossil fuel quantities are converted to energy units using the heat 

content factors qx. To convert electricity in kilowatt-hours to primary energy units, on-site 

electricity consumption is multiplied by the site-to-power plant energy use factor. The site-topower plant energy use factor is defined as the ratio of the total primary energy consumption by 

the electric power sector (in quads) divided by the total electricity generation in each year. 

The FFC multiplier is denoted μ (mu). A separate multiplier is calculated for each fuel 

used on site. A multiplier is also calculated for electricity reflecting the fuel mix used in its 

generation. The multipliers are dimensionless numbers that are applied to primary energy 

savings to obtain the FFC energy savings. The upstream component of the energy savings is 

proportional to (μ-1). The fuel type is denoted by a subscript on the multiplier μ. 

For DOE’s appliance standards energy savings estimates, the fuel cycle analysis 

methodology is designed to make use of data and projections published in the Annual Energy 

Outlook (AEO). Table 10D.2.1 provides a summary of the AEO data used as inputs to the 

different parameter calculations. The AEO does not provide all the information needed to 

estimate total energy use in the fuel production chain. Projections of Full Fuel Cycle Energy and 

Emissions Metrics describes the additional data sources used to complete the analysis. However, 

the time dependence in the FFC multipliers arises exclusively from variables taken from the 

AEO.

2 The FFC analysis for CRE used data from Annual Energy Outlook 2013 (AEO2013).3

AEO2013 provides projections to 2040. 

10D-2 
Table 10D.2.1 Dependence of FFC Parameters on AEO Inputs

Parameter Fuel AEO Table Variables

qx all Conversion Factors MMBtu per physical unit 

ax all Electricity Supply, Disposition, Prices, and Emissions Generation by fuel type 

Energy Consumption by Sector and Source Electric power sector energy 

consumption 

bc, cnc, cpc coal Coal Production by Region and Type Production by coal type and 

sulfur content 

bp, cnp, 

cpp 

petroleum Refining Industry Energy Consumption Refining only energy use 

Liquid Fuels Supply and Disposition Crude supply by source 

International Liquids Supply and Disposition Crude oil imports 

Oil and Gas Supply Crude oil domestic 

production 

cnn natural 

gas 

Oil and Gas Supply US dry gas production 

Natural Gas Supply, Disposition and Prices Pipeline, lease and plant fuel 

zx all Electricity Supply, Disposition, Prices and Emissions Power sector emissions 

10D.3 FULL-FUEL-CYCLE ENERGY MULTIPLIERS 

FFC energy multipliers are presented in Table 10D.3.1 for selected years. To extend the 

analysis period beyond 2040, the last year in the AEO2013 projection, the multipliers are 

assumed constant through the final year of the analysis period. The multiplier for electricity 

reflects the shares of various primary fuels in total electricity generation over the forecast period. 

Table 10D.3.1 Full-Fuel-Cycle Energy Multipliers (Based on AEO2013) 

2015 2020 2025 2030 2035 2040

Electricity (power plant primary energy use) 1.042 1.041 1.040 1.040 1.041 1.040

Natural Gas (site) 1.103 1.101 1.100 1.098 1.099 1.100

Petroleum Fuels (site) 1.132 1.140 1.148 1.158 1.166 1.168

10D-3 
REFERENCES

1. Coughlin, K. A Mathematical Analysis of Full Fuel Cycle Energy Use. Energy, 2012. 

37(1): pp. 698-708. (Last accessed July 8, 2013.) 

<www.sciencedirect.com/science/article/pii/S0360544211006803>.

2. Coughlin, K. 2013. Projections of Full-Fuel-Cycle Energy and Emissions Metrics. 

Lawrence Berkeley National Laboratory, Berkeley, CA. Report No. LBNL-6025E. 

3. U.S. Department of Energy - Energy Information Administration. Annual Energy Outlook 

2013. April 2013. Washington, D.C. <www.eia.gov/forecasts/aeo/pdf/0383%282012%29.pdf>.

10D-4 
APPENDIX 10E. RISC & OIRA CONSOLIDATED INFORMATION SYSTEM 

(ROCIS) TABLES

TABLE OF CONTENTS

10E.1 INTRODUCTION ....................................................................................................... 10E-1

LIST OF TABLES

Table 10E.1.1 Equipment Class Groupings ............................................................................. 10E-1

Table 10E.1.2 Cumulative and Annualized Benefits and Costs of Considered Standard Levels 

for CRE Units Shipped in the Period 2017–2046 (TSL 1, 3 Percent Discount 

Rate) ................................................................................................................. 10E-2

Table 10E.1.3 Cumulative and Annualized Benefits and Costs of Considered Standard Levels 

for CRE Units Shipped in the Period 2017–2046 (TSL 2, 3 Percent Discount 

Rate) ................................................................................................................. 10E-4

Table 10E.1.4 Cumulative and Annualized Benefits and Costs of Considered Standard Levels 

for CRE Units Shipped in the Period 2017–2046 (TSL 3, 3 Percent Discount 

Rate) ................................................................................................................. 10E-6

Table 10E.1.5 Cumulative and Annualized Benefits and Costs of Considered Standard Levels 

for CRE Units Shipped in the Period 2017–2046 (TSL 4, 3 Percent Discount 

Rate) ................................................................................................................. 10E-8

Table 10E.1.6 Cumulative and Annualized Benefits and Costs of Considered Standard Levels 

for CRE Units Shipped in the Period 2017–2046 (TSL 5, 3 Percent Discount 

Rate) ............................................................................................................... 10E-10

Table 10E.1.7 Cumulative and Annualized Benefits and Costs of Considered Standard Levels 

for CRE Units Shipped in the Period 2017–2046 (TSL 1, 7 Percent Discount 

Rate) ............................................................................................................... 10E-12

Table 10E.1.8 Cumulative and Annualized Benefits and Costs of Considered Standard Levels 

for CRE Units Shipped in the Period 2017–2046 (TSL 2, 7 Percent Discount 

Rate) ............................................................................................................... 10E-14

Table 10E.1.9 Cumulative and Annualized Benefits and Costs of Considered Standard Levels 

for CRE Units Shipped in the Period 2017–2046 (TSL 3, 7 Percent Discount 

Rate) ............................................................................................................... 10E-16

Table 10E.1.10 Cumulative and Annualized Benefits and Costs of Considered Standard 

Levels for CRE Units Shipped in the Period 2017–2046 (TSL 4, 7 Percent 

Discount Rate) ............................................................................................... 10E-18

Table 10E.1.11 Cumulative and Annualized Benefits and Costs of Considered Standard 

Levels for CRE Units Shipped in the Period 2017–2046 (TSL 5, 7 Percent 

Discount Rate) ............................................................................................... 10E-20

10E-i 
APPENDIX 10E. RISC & OIRA CONSOLIDATED INFORMATION 

SYSTEM (ROCIS) TABLES 

10E.1 INTRODUCTION

The net present value (NPV) of the monetized benefits associated with emissions 

reductions can be viewed as a complement to the NPV of the customer savings calculated for 

each trial standard level (TSL) considered in this notice of public rulemaking (NOPR) for 

commercial refrigeration equipment (CRE). In Table 10E.1.2 through Table 10E.1.11, the top 

half of the table presents the NPV values that would result if the U.S. Department of Energy 

(DOE) were to add the estimates of the potential economic benefits resulting from reduced 

carbon dioxide (CO2) and nitrogen oxide (NOx) emissions to the NPV of customer savings 

calculated for each TSL considered in this NOPR, at both a 7 percent and 3 percent discount rate. 

Although combining the values of operating savings and CO2 reductions provides a 

useful perspective, two issues should be considered. First, the national operating savings are 

domestic U.S. consumer monetary savings that occur as a result of market transactions while the 

value of CO2 reductions is based on a global value. Second, the assessments of operating cost 

savings and CO2 savings are performed with different methods that use quite different time 

frames for analysis. The national operating cost savings is measured for the lifetime of products 

shipped in the 30-year analysis period. The social cost of carbon values, on the other hand, 

reflect the present value of future climate-related impacts resulting from the emission of one ton 

of CO2 in each year. These impacts go well beyond 2100. 

The benefits and costs of today’s considered standard levels, for products sold in 2017 

through 2046, also can be expressed in terms of annualized values. The annualized monetary 

values shown in Table 10E.1.2 through Table 10E.1.11 present the sum of 1) the annualized 

national economic value, expressed in 2012 dollars (2012$), of the benefits from customer 

operation of products that meet the considered standard levels (consisting primarily of operating 

cost savings from using less energy, minus increases in equipment purchase and installation 

costs, which is another way of representing customer NPV) and 2) the annualized monetary 

value of the benefits of emission reductions, including CO2 emission reductions. These results 

tables address all TSLs and equipment class groups. For the sake of brevity, the 25 equipment 

classes have been grouped into 7 groups as shown in Table 10E.1.1. 

Table 10E.1.1 Equipment Class Groupings 

Group Name Equipment Classes Belonging to the Group

VOP.RC Equipment VOP.RC.M and VOP.RC.L

SVO.RC and HZO.RC Equipment SVO.RC.M, HZO.RC.M, and HZO.RC.L

Open Self-Contained Equipment VOP.SC.M, SVO.SC.M, HZO.SC.M, and HZO.SC.L

EPCA Refrigerators and Pull-Down 

Equipment

VCS.SC.M, VCT.SC.M, HCS.SC.M, HCT.SC.M, PD.SC.M, 

and SOC.SC.M

EPCA Freezers VCS.SC.L, VCT.SC.L, HCS.SC.L, and HCT.SC.L

VCT.RC and SOC.RC Equipment VCT.RC.M, VCT.RC.L, and SOC.RC.M

Ice-cream Freezers VCT.SC.I, VCS.SC.I, and HCT.SC.I

 

10E-1
Table 10E.1.2 Cumulative and Annualized Benefits and Costs of Considered Standard Levels for CRE Units Shipped in the 

Period 2017–2046 (TSL 1, 3 Percent Discount Rate) 

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-Cream 

Freezers Total

Cumulative Results 

Energy Savings

Full-Fuel Cycle quads 0.008 0.002 0.005 0.108 0.049 0.063 0.002 0.236

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.009 0.002 0.007 0.047 0.019 0.057 0.001 0.142

Operating Cost Savings billion 2012$ 0.051 0.011 0.031 0.640 0.297 0.388 0.009 1.427

NPV billion 2012$ 0.041 0.008 0.025 0.593 0.278 0.331 0.008 1.285

Emissions Savings (physical)

Full-Fuel Cycle

CO2 million metric ton 0.446 0.094 0.278 5.917 2.706 3.429 0.084 12.953

NOx kilo-ton 0.659 0.138 0.410 8.741 3.997 5.066 0.124 19.135

Hg ton 0.001 0.000 0.001 0.012 0.006 0.007 0.000 0.027

SO2 kilo-ton 0.570 0.120 0.355 7.558 3.456 4.380 0.107 16.546

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 2.501 0.525 1.558 33.183 15.175 19.231 0.472 72.644

3% dr, average million 2012$ 12.227 2.568 7.615 162.207 74.179 94.005 2.306 355.107

2.5% dr, average million 2012$ 19.924 4.184 12.409 264.320 120.876 153.183 3.758 578.655

3% dr, 95th perc million 2012$ 36.992 7.768 23.039 490.747 224.423 284.405 6.978 1074.352

CO2 (domestic)

5% dr, average million 2012$ 0.2 to 0.6 0.0 to 0.1 0.1 to 0.4 2.3 to 7.6 1.1 to 3.5 1.3 to 4.4 0.0 to 0.1 5.1 to 16.7

3% dr, average million 2012$ 0.9 to 2.8 0.2 to 0.6 0.5 to 1.8 11.4 to 37.3 5.2 to 17.1 6.6 to 21.6 0.2 to 0.5 24.9 to 81.7

2.5% dr, average million 2012$ 1.4 to 4.6 0.3 to 1.0 0.9 to 2.9 18.5 to 60.8 8.5 to 27.8 10.7 to 35.2 0.3 to 0.9 40.5 to 133.1

3% dr, 95th perc million 2012$ 2.6 to 8.5 0.5 to 1.8 1.6 to 5.3 34.4 to 112.9 15.7 to 51.6 19.9 to 65.4 0.5 to 1.6 75.2 to 247.1

NOx (3% dr)

At 468 2012$/ton million 2012$ 0.155 0.033 0.097 2.059 0.941 1.193 0.029 4.507

At 2,639 2012$/ton million 2012$ 0.875 0.184 0.545 11.606 5.308 6.726 0.165 25.408

At 4,809 2012$/ton million 2012$ 1.594 0.335 0.993 21.149 9.672 12.256 0.301 46.299

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.044 0.009 0.026 0.628 0.294 0.351 0.009 1.362

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.054 0.011 0.033 0.767 0.358 0.432 0.011 1.665

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.062 0.013 0.037 0.869 0.404 0.491 0.012 1.889

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.080 0.017 0.049 1.105 0.512 0.628 0.016 2.406

10E-2
Table 10E.1.2 (cont)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-Cream 

Freezers Total

Annualized Results 

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.000 0.000 0.000 0.002 0.001 0.003 0.000 0.007

Operating Cost Savings billion 2012$ 0.003 0.001 0.002 0.032 0.015 0.019 0.000 0.071

NPV billion 2012$ 0.002 0.000 0.001 0.029 0.014 0.016 0.000 0.064

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 0.155 0.033 0.097 2.056 0.940 1.191 0.029 4.501

3% dr, average million 2012$ 0.606 0.127 0.377 8.035 3.674 4.656 0.114 17.590

2.5% dr, average million 2012$ 0.929 0.195 0.578 12.321 5.634 7.140 0.175 26.972

3% dr, 95th perc million 2012$ 1.832 0.385 1.141 24.308 11.116 14.088 0.346 53.216

CO2 (domestic)

5% dr, average million 2012$ 0.01 to 0.04 0.00 to 0.01 0.01 to 0.02 0.14 to 0.47 0.07 to 0.22 0.08 to 0.27 0.00 to 0.01 0.32 to 1.04

3% dr, average million 2012$ 0.04 to 0.14 0.01 to 0.03 0.03 to 0.09 0.56 to 1.85 0.26 to 0.85 0.33 to 1.07 0.01 to 0.03 1.23 to 4.05

2.5% dr, average million 2012$ 0.07 to 0.21 0.01 to 0.04 0.04 to 0.13 0.86 to 2.83 0.39 to 1.30 0.50 to 1.64 0.01 to 0.04 1.89 to 6.20

3% dr, 95th perc million 2012$ 0.13 to 0.42 0.03 to 0.09 0.08 to 0.26 1.70 to 5.59 0.78 to 2.56 0.99 to 3.24 0.02 to 0.08 3.73 to 12.24

NOx (3% dr)

At 468 2012$/ton million 2012$ 0.008 0.002 0.005 0.102 0.047 0.059 0.001 0.223

At 2,639 2012$/ton million 2012$ 0.043 0.009 0.027 0.575 0.263 0.333 0.008 1.259

At 4,809 2012$/ton million 2012$ 0.079 0.017 0.049 1.048 0.479 0.607 0.015 2.293

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.002 0.000 0.001 0.032 0.015 0.018 0.000 0.068

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.003 0.001 0.002 0.038 0.018 0.021 0.001 0.082

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.003 0.001 0.002 0.042 0.020 0.024 0.001 0.092

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.004 0.001 0.002 0.055 0.025 0.031 0.001 0.119

10E-3
Table 10E.1.3 Cumulative and Annualized Benefits and Costs of Considered Standard Levels for CRE Units Shipped in the 

Period 2017–2046 (TSL 2, 3 Percent Discount Rate)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-Cream 

Freezers Total

Cumulative Results 

Energy Savings

Full-Fuel Cycle quads 0.051 0.030 0.009 0.173 0.075 0.081 0.003 0.422

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.054 0.049 0.013 0.146 0.075 0.095 0.006 0.439

Operating Cost Savings billion 2012$ 0.317 0.186 0.053 1.023 0.458 0.499 0.020 2.557

NPV billion 2012$ 0.263 0.137 0.040 0.877 0.383 0.404 0.014 2.118

Emissions Savings (physical)

Full-Fuel Cycle

CO2 million metric ton 2.807 1.640 0.491 9.468 4.130 4.420 0.186 23.142

NOx kilo-ton 4.147 2.422 0.725 13.987 6.101 6.530 0.275 34.187

Hg ton 0.006 0.003 0.001 0.019 0.008 0.009 0.000 0.047

SO2 kilo-ton 3.585 2.094 0.627 12.094 5.275 5.646 0.238 29.561

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 15.742 9.196 2.753 53.099 23.161 24.790 1.046 129.788

3% dr, average million 2012$ 76.951 44.952 13.459 259.566 113.220 121.183 5.112 634.442

2.5% dr, average million 2012$ 125.394 73.250 21.931 422.968 184.494 197.469 8.330 1033.836

3% dr, 95th perc million 2012$ 232.811 135.998 40.719 785.299 342.538 366.629 15.466 1919.460

CO2 (domestic)

5% dr, average million 2012$ 1.1 to 3.6 0.6 to 2.1 0.2 to 0.6 3.7 to 12.2 1.6 to 5.3 1.7 to 5.7 0.1 to 0.2 9.1 to 29.9

3% dr, average million 2012$ 5.4 to 17.7 3.1 to 10.3 0.9 to 3.1 18.2 to 59.7 7.9 to 26.0 8.5 to 27.9 0.4 to 1.2 44.4 to 145.9

2.5% dr, average million 2012$ 8.8 to 28.8 5.1 to 16.8 1.5 to 5.0 29.6 to 97.3 12.9 to 42.4 13.8 to 45.4 0.6 to 1.9 72.4 to 237.8

3% dr, 95th perc million 2012$ 16.3 to 53.5 9.5 to 31.3 2.9 to 9.4 55.0 to 180.6 24.0 to 78.8 25.7 to 84.3 1.1 to 3.6 134.4 to 441.5

NOx (3% dr)

At 468 2012$/ton million 2012$ 0.977 0.570 0.171 3.294 1.437 1.538 0.065 8.052

At 2,639 2012$/ton million 2012$ 5.506 3.216 0.963 18.572 8.101 8.671 0.366 45.395

At 4,809 2012$/ton million 2012$ 10.033 5.861 1.755 33.843 14.762 15.800 0.666 82.719

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.279 0.147 0.043 0.934 0.407 0.431 0.015 2.256

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.345 0.185 0.054 1.156 0.504 0.534 0.020 2.798

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.394 0.213 0.063 1.319 0.575 0.611 0.023 3.197

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.506 0.279 0.082 1.697 0.740 0.787 0.030 4.120

10E-4
Table 10E.1.3 (cont)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-Cream 

Freezers Total

Annualized Results 

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.003 0.002 0.001 0.007 0.004 0.005 0.000 0.022

Operating Cost Savings billion 2012$ 0.016 0.009 0.003 0.051 0.023 0.025 0.001 0.127

NPV billion 2012$ 0.013 0.007 0.002 0.043 0.019 0.020 0.001 0.105

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 0.975 0.570 0.171 3.290 1.435 1.536 0.065 8.041

3% dr, average million 2012$ 3.812 2.227 0.667 12.857 5.608 6.003 0.253 31.426

2.5% dr, average million 2012$ 5.845 3.414 1.022 19.716 8.600 9.205 0.388 48.190

3% dr, 95th perc million 2012$ 11.532 6.736 2.017 38.898 16.967 18.160 0.766 95.077

CO2 (domestic)

5% dr, average million 2012$ 0.07 to 0.22 0.04 to 0.13 0.01 to 0.04 0.23 to 0.76 0.10 to 0.33 0.11 to 0.35 0.00 to 0.01 0.56 to 1.85

3% dr, average million 2012$ 0.27 to 0.88 0.16 to 0.51 0.05 to 0.15 0.90 to 2.96 0.39 to 1.29 0.42 to 1.38 0.02 to 0.06 2.20 to 7.23

2.5% dr, average million 2012$ 0.41 to 1.34 0.24 to 0.79 0.07 to 0.24 1.38 to 4.53 0.60 to 1.98 0.64 to 2.12 0.03 to 0.09 3.37 to 11.08

3% dr, 95th perc million 2012$ 0.81 to 2.65 0.47 to 1.55 0.14 to 0.46 2.72 to 8.95 1.19 to 3.90 1.27 to 4.18 0.05 to 0.18 6.66 to 21.87

NOx (3% dr)

At 468 2012$/ton million 2012$ 0.048 0.028 0.008 0.163 0.071 0.076 0.003 0.399

At 2,639 2012$/ton million 2012$ 0.273 0.159 0.048 0.920 0.401 0.429 0.018 2.249

At 4,809 2012$/ton million 2012$ 0.497 0.290 0.087 1.676 0.731 0.783 0.033 4.097

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.014 0.007 0.002 0.047 0.020 0.022 0.001 0.113

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.017 0.009 0.003 0.057 0.025 0.026 0.001 0.139

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.019 0.010 0.003 0.064 0.028 0.030 0.001 0.155

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.025 0.014 0.004 0.084 0.037 0.039 0.002 0.204

 

10E-5
Table 10E.1.4 Cumulative and Annualized Benefits and Costs of Considered Standard Levels for CRE Units Shipped in the 

Period 2017–2046 (TSL 3, 3 Percent Discount Rate) 

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Cumulative Results 

Energy Savings

Full-Fuel Cycle quads 0.248 0.141 0.039 0.298 0.082 0.106 0.005 0.920

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.355 0.237 0.083 0.474 0.099 0.139 0.011 1.399

Operating Cost Savings billion 2012$ 1.532 0.852 0.232 1.772 0.493 0.657 0.028 5.564

NPV billion 2012$ 1.176 0.615 0.148 1.298 0.394 0.518 0.017 4.165

Emissions Savings (physical)

Full-Fuel Cycle

CO2 million metric ton 13.612 7.750 2.158 16.339 4.504 5.789 0.255 50.406

NOx kilo-ton 20.108 11.449 3.189 24.136 6.654 8.551 0.376 74.463

Hg ton 0.028 0.016 0.004 0.033 0.009 0.012 0.001 0.103

SO2 kilo-ton 17.387 9.899 2.757 20.870 5.753 7.394 0.325 64.386

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 76.338 43.463 12.105 91.629 25.261 32.463 1.428 282.687

3% dr, average million 2012$ 373.163 212.461 59.172 447.914 123.481 158.691 6.979 1381.862

2.5% dr, average million 2012$ 608.077 346.210 96.423 729.885 201.216 258.590 11.373 2251.773

3% dr, 95th perc million 2012$ 1128.978 642.786 179.022 1355.132 373.584 480.108 21.115 4180.726

CO2 (domestic)

5% dr, average million 2012$ 5.3 to 17.6 3.0 to 10.0 0.8 to 2.8 6.4 to 21.1 1.8 to 5.8 2.3 to 7.5 0.1 to 0.3 19.8 to 65.0

3% dr, average million 2012$ 26.1 to 85.8 14.9 to 48.9 4.1 to 13.6 31.4 to 103.0 8.6 to 28.4 11.1 to 36.5 0.5 to 1.6 96.7 to 317.8

2.5% dr, average million 2012$ 42.6 to 139.9 24.2 to 79.6 6.7 to 22.2 51.1 to 167.9 14.1 to 46.3 18.1 to 59.5 0.8 to 2.6 157.6 to 517.9

3% dr, 95th perc million 2012$ 79.0 to 259.7 45.0 to 147.8 12.5 to 41.2 94.9 to 311.7 26.2 to 85.9 33.6 to 110.4 1.5 to 4.9 292.7 to 961.6

NOx (3% dr)

At 468 2012$/ton million 2012$ 4.736 2.696 0.751 5.685 1.567 2.014 0.089 17.538

At 2,639 2012$/ton million 2012$ 26.700 15.202 4.234 32.048 8.835 11.354 0.499 98.873

At 4,809 2012$/ton million 2012$ 48.653 27.701 7.715 58.400 16.100 20.690 0.910 180.169

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 1.258 0.661 0.161 1.395 0.420 0.552 0.018 4.466

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 1.576 0.842 0.212 1.778 0.526 0.688 0.024 5.646

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 1.811 0.976 0.249 2.060 0.604 0.787 0.029 6.516

Consumers + CO2 (4th) + NOx (High) billion 2012$ 2.354 1.285 0.335 2.712 0.783 1.018 0.039 8.526

10E-6
Table 10E.1.4 (cont)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Annualized Results 

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.018 0.012 0.004 0.023 0.005 0.007 0.001 0.069

Operating Cost Savings billion 2012$ 0.076 0.042 0.011 0.088 0.024 0.033 0.001 0.276

NPV billion 2012$ 0.058 0.030 0.007 0.064 0.019 0.026 0.001 0.206

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 4.729 2.693 0.750 5.677 1.565 2.011 0.088 17.513

3% dr, average million 2012$ 18.484 10.524 2.931 22.187 6.116 7.860 0.346 68.448

2.5% dr, average million 2012$ 28.344 16.138 4.494 34.022 9.379 12.053 0.530 104.960

3% dr, 95th perc million 2012$ 55.922 31.839 8.868 67.124 18.505 23.781 1.046 207.085

CO2 (domestic)

5% dr, average million 2012$ 0.33 to 1.09 0.19 to 0.62 0.05 to 0.17 0.40 to 1.31 0.11 to 0.36 0.14 to 0.46 0.01 to 0.02 1.23 to 4.03

3% dr, average million 2012$ 1.29 to 4.25 0.74 to 2.42 0.21 to 0.67 1.55 to 5.10 0.43 to 1.41 0.55 to 1.81 0.02 to 0.08 4.79 to 15.74

2.5% dr, average million 2012$ 1.98 to 6.52 1.13 to 3.71 0.31 to 1.03 2.38 to 7.82 0.66 to 2.16 0.84 to 2.77 0.04 to 0.12 7.35 to 24.14

3% dr, 95th perc million 2012$ 3.91 to 12.86 2.23 to 7.32 0.62 to 2.04 4.70 to 15.44 1.30 to 4.26 1.66 to 5.47 0.07 to 0.24 14.50 to 47.63

NOx (3% dr)

At 468 2012$/ton million 2012$ 0.235 0.134 0.037 0.282 0.078 0.100 0.004 0.869

At 2,639 2012$/ton million 2012$ 1.323 0.753 0.210 1.587 0.438 0.562 0.025 4.897

At 4,809 2012$/ton million 2012$ 2.410 1.372 0.382 2.893 0.797 1.025 0.045 8.924

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.063 0.033 0.008 0.070 0.021 0.028 0.001 0.225

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.078 0.042 0.010 0.088 0.026 0.034 0.001 0.280

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.088 0.047 0.012 0.100 0.029 0.038 0.001 0.316

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.117 0.064 0.017 0.134 0.039 0.050 0.002 0.422

10E-7
Table 10E.1.5 Cumulative and Annualized Benefits and Costs of Considered Standard Levels for CRE Units Shipped in the 

Period 2017–2046 (TSL 4, 3 Percent Discount Rate)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Cumulative Results 

Energy Savings

Full-Fuel Cycle quads 0.254 0.144 0.040 0.360 0.091 0.107 0.005 1.001

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.393 0.261 0.097 0.904 0.138 0.164 0.011 1.967

Operating Cost Savings billion 2012$ 1.565 0.870 0.238 2.137 0.530 0.666 0.028 6.034

NPV billion 2012$ 1.172 0.608 0.141 1.233 0.392 0.503 0.017 4.067

Emissions Savings (physical)

Full-Fuel Cycle

CO2 million metric ton 13.900 7.909 2.214 19.740 4.973 5.887 0.255 54.878

NOx kilo-ton 20.534 11.684 3.271 29.162 7.346 8.697 0.376 81.070

Hg ton 0.028 0.016 0.005 0.040 0.010 0.012 0.001 0.112

SO2 kilo-ton 17.755 10.103 2.829 25.215 6.352 7.520 0.325 70.099

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 77.955 44.356 12.419 110.708 27.888 33.016 1.428 307.769

3% dr, average million 2012$ 381.068 216.827 60.706 541.173 136.323 161.394 6.979 1504.471

2.5% dr, average million 2012$ 620.958 353.324 98.921 881.853 222.142 262.995 11.373 2451.567

3% dr, 95th perc million 2012$ 1152.895 655.995 183.661 1637.282 412.437 488.287 21.115 4551.672

CO2 (domestic)

5% dr, average million 2012$ 5.5 to 17.9 3.1 to 10.2 0.9 to 2.9 7.7 to 25.5 2.0 to 6.4 2.3 to 7.6 0.1 to 0.3 21.5 to 70.8

3% dr, average million 2012$ 26.7 to 87.6 15.2 to 49.9 4.2 to 14.0 37.9 to 124.5 9.5 to 31.4 11.3 to 37.1 0.5 to 1.6 105.3 to 346.0

2.5% dr, average million 2012$ 43.5 to 142.8 24.7 to 81.3 6.9 to 22.8 61.7 to 202.8 15.5 to 51.1 18.4 to 60.5 0.8 to 2.6 171.6 to 563.9

3% dr, 95th perc million 2012$ 80.7 to 265.2 45.9 to 150.9 12.9 to 42.2 114.6 to 376.6 28.9 to 94.9 34.2 to 112.3 1.5 to 4.9 318.6 to 1046.9

NOx (3% dr)

At 468 2012$/ton million 2012$ 4.836 2.752 0.770 6.868 1.730 2.048 0.089 19.094

At 2,639 2012$/ton million 2012$ 27.266 15.514 4.344 38.721 9.754 11.548 0.499 107.645

At 4,809 2012$/ton million 2012$ 49.684 28.270 7.915 70.559 17.774 21.043 0.910 196.155

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 1.255 0.655 0.155 1.351 0.422 0.538 0.018 4.394

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 1.580 0.841 0.206 1.813 0.538 0.676 0.024 5.679

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 1.820 0.977 0.245 2.154 0.624 0.777 0.029 6.626

Consumers + CO2 (4th) + NOx (High) billion 2012$ 2.375 1.293 0.333 2.941 0.822 1.012 0.039 8.815

10E-8
Table 10E.1.5 (cont)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Annualized Results 

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.019 0.013 0.005 0.045 0.007 0.008 0.001 0.097

Operating Cost Savings billion 2012$ 0.078 0.043 0.012 0.106 0.026 0.033 0.001 0.299

NPV billion 2012$ 0.058 0.030 0.007 0.061 0.019 0.025 0.001 0.201

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 4.830 2.748 0.769 6.859 1.728 2.045 0.088 19.067

3% dr, average million 2012$ 18.876 10.740 3.007 26.806 6.753 7.994 0.346 74.521

2.5% dr, average million 2012$ 28.944 16.469 4.611 41.105 10.355 12.259 0.530 114.273

3% dr, 95th perc million 2012$ 57.107 32.494 9.097 81.100 20.429 24.186 1.046 225.459

CO2 (domestic)

5% dr, average million 2012$ 0.34 to 1.11 0.19 to 0.63 0.05 to 0.18 0.48 to 1.58 0.12 to 0.40 0.14 to 0.47 0.01 to 0.02 1.33 to 4.39

3% dr, average million 2012$ 1.32 to 4.34 0.75 to 2.47 0.21 to 0.69 1.88 to 6.17 0.47 to 1.55 0.56 to 1.84 0.02 to 0.08 5.22 to 17.14

2.5% dr, average million 2012$ 2.03 to 6.66 1.15 to 3.79 0.32 to 1.06 2.88 to 9.45 0.72 to 2.38 0.86 to 2.82 0.04 to 0.12 8.00 to 26.28

3% dr, 95th perc million 2012$ 4.00 to 13.13 2.27 to 7.47 0.64 to 2.09 5.68 to 18.65 1.43 to 4.70 1.69 to 5.56 0.07 to 0.24 15.78 to 51.86

NOx (3% dr)

At 468 2012$/ton million 2012$ 0.240 0.136 0.038 0.340 0.086 0.101 0.004 0.946

At 2,639 2012$/ton million 2012$ 1.351 0.768 0.215 1.918 0.483 0.572 0.025 5.332

At 4,809 2012$/ton million 2012$ 2.461 1.400 0.392 3.495 0.880 1.042 0.045 9.716

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.063 0.033 0.008 0.068 0.021 0.027 0.001 0.221

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.078 0.042 0.010 0.090 0.027 0.033 0.001 0.281

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.088 0.047 0.012 0.104 0.030 0.038 0.001 0.321

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.118 0.064 0.016 0.146 0.041 0.050 0.002 0.437

10E-9
Table 10E.1.6 Cumulative and Annualized Benefits and Costs of Considered Standard Levels for CRE Units Shipped in the 

Period 2017–2046 (TSL 5, 3 Percent Discount Rate)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Cumulative Results 

Energy Savings

Full-Fuel Cycle quads 0.270 0.162 0.043 0.472 0.165 0.154 0.010 1.278

Economic Impacts

Incremental Equipment Cost billion 2012$ 2.322 1.713 0.375 8.039 2.909 3.150 0.219 18.727

Operating Cost Savings billion 2012$ 1.669 0.982 0.255 2.834 0.995 0.956 0.064 7.755

NPV billion 2012$ -0.653 -0.731 -0.120 -5.205 -1.914 -2.194 -0.156 -10.972

Emissions Savings (physical)

Full-Fuel Cycle

CO2 million metric ton 14.816 8.897 2.359 25.873 9.056 8.438 0.570 70.008

NOx kilo-ton 21.888 13.143 3.484 38.221 13.378 12.464 0.843 103.420

Hg ton 0.030 0.018 0.005 0.053 0.019 0.017 0.001 0.143

SO2 kilo-ton 18.926 11.364 3.013 33.049 11.567 10.778 0.729 89.425

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 83.093 49.893 13.227 145.101 50.786 47.319 3.199 392.618

3% dr, average million 2012$ 406.184 243.894 64.657 709.298 248.259 231.312 15.636 1919.241

2.5% dr, average million 2012$ 661.885 397.431 105.361 1155.817 404.544 376.927 25.479 3127.443

3% dr, 95th perc million 2012$ 1228.881 737.886 195.617 2145.933 751.091 699.817 47.305 5806.529

CO2 (domestic)

5% dr, average million 2012$ 5.8 to 19.1 3.5 to 11.5 0.9 to 3.0 10.2 to 33.4 3.6 to 11.7 3.3 to 10.9 0.2 to 0.7 27.5 to 90.3

3% dr, average million 2012$ 28.4 to 93.4 17.1 to 56.1 4.5 to 14.9 49.7 to 163.1 17.4 to 57.1 16.2 to 53.2 1.1 to 3.6 134.3 to 441.4

2.5% dr, average million 2012$ 46.3 to 152.2 27.8 to 91.4 7.4 to 24.2 80.9 to 265.8 28.3 to 93.0 26.4 to 86.7 1.8 to 5.9 218.9 to 719.3

3% dr, 95th perc million 2012$ 86.0 to 282.6 51.7 to 169.7 13.7 to 45.0 150.2 to 493.6 52.6 to 172.8 49.0 to 161.0 3.3 to 10.9 406.5 to 1335.5

NOx (3% dr)

At 468 2012$/ton million 2012$ 5.155 3.095 0.821 9.002 3.151 2.936 0.198 24.358

At 2,639 2012$/ton million 2012$ 29.063 17.451 4.626 50.751 17.763 16.550 1.119 137.322

At 4,809 2012$/ton million 2012$ 52.959 31.799 8.430 92.479 32.368 30.159 2.039 250.233

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ -0.565 -0.678 -0.106 -5.050 -1.860 -2.144 -0.152 -10.555

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ -0.218 -0.470 -0.051 -4.444 -1.648 -1.946 -0.139 -8.916

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.038 -0.316 -0.010 -3.998 -1.492 -1.800 -0.129 -7.708

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.629 0.039 0.084 -2.966 -1.131 -1.464 -0.106 -4.916

10E-10
Table 10E.1.6 (cont)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Annualized Results 

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.115 0.085 0.019 0.398 0.144 0.156 0.011 0.928

Operating Cost Savings billion 2012$ 0.083 0.049 0.013 0.140 0.049 0.047 0.003 0.384

NPV billion 2012$ -0.032 -0.036 -0.006 -0.258 -0.095 -0.109 -0.008 -0.544

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 5.148 3.091 0.819 8.990 3.146 2.932 0.198 24.324

3% dr, average million 2012$ 20.120 12.081 3.203 35.134 12.297 11.458 0.774 95.066

2.5% dr, average million 2012$ 30.852 18.525 4.911 53.875 18.857 17.569 1.188 145.777

3% dr, 95th perc million 2012$ 60.871 36.550 9.690 106.295 37.204 34.664 2.343 287.616

CO2 (domestic)

5% dr, average million 2012$ 0.36 to 1.18 0.22 to 0.71 0.06 to 0.19 0.63 to 2.07 0.22 to 0.72 0.21 to 0.67 0.01 to 0.05 1.70 to 5.59

3% dr, average million 2012$ 1.41 to 4.63 0.85 to 2.78 0.22 to 0.74 2.46 to 8.08 0.86 to 2.83 0.80 to 2.64 0.05 to 0.18 6.65 to 21.87

2.5% dr, average million 2012$ 2.16 to 7.10 1.30 to 4.26 0.34 to 1.13 3.77 to 12.39 1.32 to 4.34 1.23 to 4.04 0.08 to 0.27 10.20 to 33.53

3% dr, 95th perc million 2012$ 4.26 to 14.00 2.56 to 8.41 0.68 to 2.23 7.44 to 24.45 2.60 to 8.56 2.43 to 7.97 0.16 to 0.54 20.13 to 66.15

NOx (3% dr)

At 468 2012$/ton million 2012$ 0.255 0.153 0.041 0.446 0.156 0.145 0.010 1.207

At 2,639 2012$/ton million 2012$ 1.440 0.864 0.229 2.514 0.880 0.820 0.055 6.802

At 4,809 2012$/ton million 2012$ 2.623 1.575 0.418 4.581 1.603 1.494 0.101 12.395

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ -0.027 -0.033 -0.005 -0.248 -0.092 -0.106 -0.007 -0.518

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ -0.011 -0.023 -0.003 -0.220 -0.082 -0.096 -0.007 -0.442

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.000 -0.017 -0.001 -0.201 -0.075 -0.090 -0.006 -0.391

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.031 0.002 0.004 -0.147 -0.056 -0.073 -0.005 -0.243

10E-11
Table 10E.1.7 Cumulative and Annualized Benefits and Costs of Considered Standard Levels for CRE Units Shipped in the 

Period 2017–2046 (TSL 1, 7 Percent Discount Rate)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Cumulative Results 

Energy Savings

Full-Fuel Cycle quads 0.008 0.002 0.005 0.108 0.049 0.063 0.002 0.236

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.005 0.001 0.004 0.025 0.010 0.031 0.001 0.077

Operating Cost Savings billion 2012$ 0.023 0.005 0.014 0.286 0.133 0.173 0.004 0.638

NPV billion 2012$ 0.018 0.004 0.010 0.261 0.122 0.143 0.004 0.561

Emissions Savings (physical)

Full-Fuel Cycle

CO2 million metric ton 0.446 0.094 0.278 5.917 2.706 3.429 0.084 12.953

NOx kilo-ton 0.659 0.138 0.410 8.741 3.997 5.066 0.124 19.135

Hg ton 0.001 0.000 0.001 0.012 0.006 0.007 0.000 0.027

SO2 kilo-ton 0.570 0.120 0.355 7.558 3.456 4.380 0.107 16.546

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 2.501 0.525 1.558 33.183 15.175 19.231 0.472 72.644

3% dr, average million 2012$ 12.227 2.568 7.615 162.207 74.179 94.005 2.306 355.107

2.5% dr, average million 2012$ 19.924 4.184 12.409 264.320 120.876 153.183 3.758 578.655

3% dr, 95th perc million 2012$ 36.992 7.768 23.039 490.747 224.423 284.405 6.978 1074.352

CO2 (domestic)

5% dr, average million 2012$ 0.2 to 0.6 0.0 to 0.1 0.1 to 0.4 2.3 to 7.6 1.1 to 3.5 1.3 to 4.4 0.0 to 0.1 5.1 to 16.7

3% dr, average million 2012$ 0.9 to 2.8 0.2 to 0.6 0.5 to 1.8 11.4 to 37.3 5.2 to 17.1 6.6 to 21.6 0.2 to 0.5 24.9 to 81.7

2.5% dr, average million 2012$ 1.4 to 4.6 0.3 to 1.0 0.9 to 2.9 18.5 to 60.8 8.5 to 27.8 10.7 to 35.2 0.3 to 0.9 40.5 to 133.1

3% dr, 95th perc million 2012$ 2.6 to 8.5 0.5 to 1.8 1.6 to 5.3 34.4 to 112.9 15.7 to 51.6 19.9 to 65.4 0.5 to 1.6 75.2 to 247.1

NOx (7% dr)

At 468 2012$/ton million 2012$ 0.072 0.015 0.045 0.952 0.435 0.552 0.014 2.083

At 2,639 2012$/ton million 2012$ 0.404 0.085 0.252 5.365 2.454 3.109 0.076 11.746

At 4,809 2012$/ton million 2012$ 0.737 0.155 0.459 9.777 4.471 5.666 0.139 21.404

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.020 0.004 0.012 0.295 0.138 0.162 0.004 0.636

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.030 0.006 0.018 0.428 0.199 0.240 0.006 0.928

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.038 0.008 0.023 0.530 0.246 0.299 0.007 1.151

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.055 0.012 0.034 0.761 0.351 0.433 0.011 1.657

10E-12
Table 10E.1.7 (cont)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Annualized Results 

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.000 0.000 0.000 0.002 0.001 0.002 0.000 0.006

Operating Cost Savings billion 2012$ 0.002 0.000 0.001 0.022 0.010 0.013 0.000 0.048

NPV billion 2012$ 0.001 0.000 0.001 0.020 0.009 0.011 0.000 0.042

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 0.155 0.033 0.097 2.056 0.940 1.191 0.029 4.501

3% dr, average million 2012$ 0.606 0.127 0.377 8.035 3.674 4.656 0.114 17.590

2.5% dr, average million 2012$ 0.929 0.195 0.578 12.321 5.634 7.140 0.175 26.972

3% dr, 95th perc million 2012$ 1.832 0.385 1.141 24.308 11.116 14.088 0.346 53.216

CO2 (domestic)

5% dr, average million 2012$ 0.01 to 0.04 0.00 to 0.01 0.01 to 0.02 0.14 to 0.47 0.07 to 0.22 0.08 to 0.27 0.00 to 0.01 0.32 to 1.04

3% dr, average million 2012$ 0.04 to 0.14 0.01 to 0.03 0.03 to 0.09 0.56 to 1.85 0.26 to 0.85 0.33 to 1.07 0.01 to 0.03 1.23 to 4.05

2.5% dr, average million 2012$ 0.07 to 0.21 0.01 to 0.04 0.04 to 0.13 0.86 to 2.83 0.39 to 1.30 0.50 to 1.64 0.01 to 0.04 1.89 to 6.20

3% dr, 95th perc million 2012$ 0.13 to 0.42 0.03 to 0.09 0.08 to 0.26 1.70 to 5.59 0.78 to 2.56 0.99 to 3.24 0.02 to 0.08 3.73 to 12.24

NOx (7% dr)

At 468 2012$/ton million 2012$ 0.005 0.001 0.003 0.072 0.033 0.042 0.001 0.157

At 2,639 2012$/ton million 2012$ 0.030 0.006 0.019 0.404 0.185 0.234 0.006 0.885

At 4,809 2012$/ton million 2012$ 0.056 0.012 0.035 0.736 0.337 0.427 0.010 1.612

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.001 0.000 0.001 0.022 0.010 0.012 0.000 0.047

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.002 0.000 0.001 0.028 0.013 0.016 0.000 0.061

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.002 0.000 0.001 0.032 0.015 0.018 0.000 0.070

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.003 0.001 0.002 0.045 0.021 0.025 0.001 0.097

10E-13
Table 10E.1.8 Cumulative and Annualized Benefits and Costs of Considered Standard Levels for CRE Units Shipped in the 

Period 2017–2046 (TSL 2, 7 Percent Discount Rate)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Cumulative Results 

Energy Savings

Full-Fuel Cycle quads 0.051 0.030 0.009 0.173 0.075 0.081 0.003 0.422

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.029 0.027 0.007 0.079 0.041 0.052 0.003 0.238

Operating Cost Savings billion 2012$ 0.142 0.083 0.023 0.457 0.205 0.223 0.009 1.143

NPV billion 2012$ 0.112 0.057 0.017 0.378 0.164 0.172 0.006 0.905

Emissions Savings (physical)

Full-Fuel Cycle

CO2 million metric ton 2.807 1.640 0.491 9.468 4.130 4.420 0.186 23.142

NOx kilo-ton 4.147 2.422 0.725 13.987 6.101 6.530 0.275 34.187

Hg ton 0.006 0.003 0.001 0.019 0.008 0.009 0.000 0.047

SO2 kilo-ton 3.585 2.094 0.627 12.094 5.275 5.646 0.238 29.561

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 15.742 9.196 2.753 53.099 23.161 24.790 1.046 129.788

3% dr, average million 2012$ 76.951 44.952 13.459 259.566 113.220 121.183 5.112 634.442

2.5% dr, average million 2012$ 125.394 73.250 21.931 422.968 184.494 197.469 8.330 1033.836

3% dr, 95th perc million 2012$ 232.811 135.998 40.719 785.299 342.538 366.629 15.466 1919.460

CO2 (domestic)

5% dr, average million 2012$ 1.1 to 3.6 0.6 to 2.1 0.2 to 0.6 3.7 to 12.2 1.6 to 5.3 1.7 to 5.7 0.1 to 0.2 9.1 to 29.9

3% dr, average million 2012$ 5.4 to 17.7 3.1 to 10.3 0.9 to 3.1 18.2 to 59.7 7.9 to 26.0 8.5 to 27.9 0.4 to 1.2 44.4 to 145.9

2.5% dr, average million 2012$ 8.8 to 28.8 5.1 to 16.8 1.5 to 5.0 29.6 to 97.3 12.9 to 42.4 13.8 to 45.4 0.6 to 1.9 72.4 to 237.8

3% dr, 95th perc million 2012$ 16.3 to 53.5 9.5 to 31.3 2.9 to 9.4 55.0 to 180.6 24.0 to 78.8 25.7 to 84.3 1.1 to 3.6 134.4 to 441.5

NOx (7% dr)

At 468 2012$/ton million 2012$ 0.451 0.264 0.079 1.523 0.664 0.711 0.030 3.722

At 2,639 2012$/ton million 2012$ 2.545 1.487 0.445 8.586 3.745 4.008 0.169 20.986

At 4,809 2012$/ton million 2012$ 4.638 2.709 0.811 15.645 6.824 7.304 0.308 38.241

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.128 0.066 0.019 0.433 0.188 0.197 0.007 1.038

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.192 0.103 0.030 0.646 0.281 0.297 0.011 1.560

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.240 0.131 0.039 0.810 0.352 0.373 0.014 1.959

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.350 0.195 0.058 1.179 0.513 0.546 0.022 2.862

10E-14
Table 10E.1.8 (cont)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Annualized Results 

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.002 0.002 0.001 0.006 0.003 0.004 0.000 0.018

Operating Cost Savings billion 2012$ 0.011 0.006 0.002 0.034 0.015 0.017 0.001 0.086

NPV billion 2012$ 0.008 0.004 0.001 0.028 0.012 0.013 0.000 0.068

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 0.975 0.570 0.171 3.290 1.435 1.536 0.065 8.041

3% dr, average million 2012$ 3.812 2.227 0.667 12.857 5.608 6.003 0.253 31.426

2.5% dr, average million 2012$ 5.845 3.414 1.022 19.716 8.600 9.205 0.388 48.190

3% dr, 95th perc million 2012$ 11.532 6.736 2.017 38.898 16.967 18.160 0.766 95.077

CO2 (domestic)

5% dr, average million 2012$ 0.07 to 0.22 0.04 to 0.13 0.01 to 0.04 0.23 to 0.76 0.10 to 0.33 0.11 to 0.35 0.00 to 0.01 0.56 to 1.85

3% dr, average million 2012$ 0.27 to 0.88 0.16 to 0.51 0.05 to 0.15 0.90 to 2.96 0.39 to 1.29 0.42 to 1.38 0.02 to 0.06 2.20 to 7.23

2.5% dr, average million 2012$ 0.41 to 1.34 0.24 to 0.79 0.07 to 0.24 1.38 to 4.53 0.60 to 1.98 0.64 to 2.12 0.03 to 0.09 3.37 to 11.08

3% dr, 95th perc million 2012$ 0.81 to 2.65 0.47 to 1.55 0.14 to 0.46 2.72 to 8.95 1.19 to 3.90 1.27 to 4.18 0.05 to 0.18 6.66 to 21.87

NOx (7% dr)

At 468 2012$/ton million 2012$ 0.034 0.020 0.006 0.115 0.050 0.054 0.002 0.280

At 2,639 2012$/ton million 2012$ 0.192 0.112 0.034 0.647 0.282 0.302 0.013 1.581

At 4,809 2012$/ton million 2012$ 0.349 0.204 0.061 1.178 0.514 0.550 0.023 2.880

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.009 0.005 0.001 0.032 0.014 0.015 0.001 0.076

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.012 0.007 0.002 0.042 0.018 0.019 0.001 0.101

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.014 0.008 0.002 0.049 0.021 0.022 0.001 0.118

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.020 0.011 0.003 0.069 0.030 0.032 0.001 0.166

10E-15
Table 10E.1.9 Cumulative and Annualized Benefits and Costs of Considered Standard Levels for CRE Units Shipped in the 

Period 2017–2046 (TSL 3, 7 Percent Discount Rate) 

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Cumulative Results 

Energy Savings

Full-Fuel Cycle quads 0.248 0.141 0.039 0.298 0.082 0.106 0.005 0.920

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.204 0.135 0.047 0.257 0.054 0.076 0.006 0.780

Operating Cost Savings billion 2012$ 0.684 0.380 0.103 0.792 0.220 0.294 0.013 2.485

NPV billion 2012$ 0.480 0.245 0.056 0.534 0.166 0.217 0.006 1.705

Emissions Savings (physical)

Full-Fuel Cycle

CO2 million metric ton 13.612 7.750 2.158 16.339 4.504 5.789 0.255 50.406

NOx kilo-ton 20.108 11.449 3.189 24.136 6.654 8.551 0.376 74.463

Hg ton 0.028 0.016 0.004 0.033 0.009 0.012 0.001 0.103

SO2 kilo-ton 17.387 9.899 2.757 20.870 5.753 7.394 0.325 64.386

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 76.338 43.463 12.105 91.629 25.261 32.463 1.428 282.687

3% dr, average million 2012$ 373.163 212.461 59.172 447.914 123.481 158.691 6.979 1381.862

2.5% dr, average million 2012$ 608.077 346.210 96.423 729.885 201.216 258.590 11.373 2251.773

3% dr, 95th perc million 2012$ 1128.978 642.786 179.022 1355.132 373.584 480.108 21.115 4180.726

CO2 (domestic)

5% dr, average million 2012$ 5.3 to 17.6 3.0 to 10.0 0.8 to 2.8 6.4 to 21.1 1.8 to 5.8 2.3 to 7.5 0.1 to 0.3 19.8 to 65.0

3% dr, average million 2012$ 26.1 to 85.8 14.9 to 48.9 4.1 to 13.6 31.4 to 103.0 8.6 to 28.4 11.1 to 36.5 0.5 to 1.6 96.7 to 317.8

2.5% dr, average million 2012$ 42.6 to 139.9 24.2 to 79.6 6.7 to 22.2 51.1 to 167.9 14.1 to 46.3 18.1 to 59.5 0.8 to 2.6 157.6 to 517.9

3% dr, 95th perc million 2012$ 79.0 to 259.7 45.0 to 147.8 12.5 to 41.2 94.9 to 311.7 26.2 to 85.9 33.6 to 110.4 1.5 to 4.9 292.7 to 961.6

NOx (7% dr)

At 468 2012$/ton million 2012$ 2.189 1.247 0.347 2.628 0.724 0.931 0.041 8.108

At 2,639 2012$/ton million 2012$ 12.343 7.028 1.957 14.816 4.084 5.249 0.231 45.709

At 4,809 2012$/ton million 2012$ 22.492 12.806 3.567 26.998 7.443 9.565 0.421 83.292

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.558 0.290 0.069 0.628 0.192 0.251 0.008 1.996

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.865 0.464 0.117 0.997 0.294 0.381 0.014 3.133

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 1.100 0.598 0.155 1.279 0.372 0.481 0.018 4.002

Consumers + CO2 (4th) + NOx (High) billion 2012$ 1.631 0.900 0.239 1.916 0.547 0.707 0.028 5.969

10E-16
Table 10E.1.9 (cont)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Annualized Results 

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.015 0.010 0.004 0.019 0.004 0.006 0.000 0.059

Operating Cost Savings billion 2012$ 0.052 0.029 0.008 0.060 0.017 0.022 0.001 0.187

NPV billion 2012$ 0.036 0.018 0.004 0.040 0.013 0.016 0.000 0.128

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 4.729 2.693 0.750 5.677 1.565 2.011 0.088 17.513

3% dr, average million 2012$ 18.484 10.524 2.931 22.187 6.116 7.860 0.346 68.448

2.5% dr, average million 2012$ 28.344 16.138 4.494 34.022 9.379 12.053 0.530 104.960

3% dr, 95th perc million 2012$ 55.922 31.839 8.868 67.124 18.505 23.781 1.046 207.085

CO2 (domestic)

5% dr, average million 2012$ 0.33 to 1.09 0.19 to 0.62 0.05 to 0.17 0.40 to 1.31 0.11 to 0.36 0.14 to 0.46 0.01 to 0.02 1.23 to 4.03

3% dr, average million 2012$ 1.29 to 4.25 0.74 to 2.42 0.21 to 0.67 1.55 to 5.10 0.43 to 1.41 0.55 to 1.81 0.02 to 0.08 4.79 to 15.74

2.5% dr, average million 2012$ 1.98 to 6.52 1.13 to 3.71 0.31 to 1.03 2.38 to 7.82 0.66 to 2.16 0.84 to 2.77 0.04 to 0.12 7.35 to 24.14

3% dr, 95th perc million 2012$ 3.91 to 12.86 2.23 to 7.32 0.62 to 2.04 4.70 to 15.44 1.30 to 4.26 1.66 to 5.47 0.07 to 0.24 14.50 to 47.63

NOx (7% dr)

At 468 2012$/ton million 2012$ 0.165 0.094 0.026 0.198 0.055 0.070 0.003 0.611

At 2,639 2012$/ton million 2012$ 0.930 0.529 0.147 1.116 0.308 0.395 0.017 3.443

At 4,809 2012$/ton million 2012$ 1.694 0.964 0.269 2.033 0.561 0.720 0.032 6.273

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.041 0.021 0.005 0.046 0.014 0.018 0.001 0.147

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.056 0.029 0.007 0.064 0.019 0.025 0.001 0.200

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.065 0.035 0.009 0.075 0.022 0.029 0.001 0.237

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.094 0.051 0.013 0.109 0.032 0.041 0.002 0.342

10E-17
Table 10E.1.10 Cumulative and Annualized Benefits and Costs of Considered Standard Levels for CRE Units Shipped in the 

Period 2017–2046 (TSL 4, 7 Percent Discount Rate) 

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Cumulative Results 

Energy Savings

Full-Fuel Cycle quads 0.254 0.144 0.040 0.360 0.091 0.107 0.005 1.001

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.224 0.148 0.054 0.491 0.075 0.090 0.006 1.089

Operating Cost Savings billion 2012$ 0.699 0.388 0.106 0.955 0.237 0.298 0.013 2.695

NPV billion 2012$ 0.474 0.240 0.052 0.463 0.162 0.208 0.006 1.606

Emissions Savings (physical)

Full-Fuel Cycle

CO2 million metric ton 13.900 7.909 2.214 19.740 4.973 5.887 0.255 54.878

NOx kilo-ton 20.534 11.684 3.271 29.162 7.346 8.697 0.376 81.070

Hg ton 0.028 0.016 0.005 0.040 0.010 0.012 0.001 0.112

SO2 kilo-ton 17.755 10.103 2.829 25.215 6.352 7.520 0.325 70.099

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 77.955 44.356 12.419 110.708 27.888 33.016 1.428 307.769

3% dr, average million 2012$ 381.068 216.827 60.706 541.173 136.323 161.394 6.979 1504.471

2.5% dr, average million 2012$ 620.958 353.324 98.921 881.853 222.142 262.995 11.373 2451.567

3% dr, 95th perc million 2012$ 1152.895 655.995 183.661 1637.282 412.437 488.287 21.115 4551.672

CO2 (domestic)

5% dr, average million 2012$ 5.5 to 17.9 3.1 to 10.2 0.9 to 2.9 7.7 to 25.5 2.0 to 6.4 2.3 to 7.6 0.1 to 0.3 21.5 to 70.8

3% dr, average million 2012$ 26.7 to 87.6 15.2 to 49.9 4.2 to 14.0 37.9 to 124.5 9.5 to 31.4 11.3 to 37.1 0.5 to 1.6 105.3 to 346.0

2.5% dr, average million 2012$ 43.5 to 142.8 24.7 to 81.3 6.9 to 22.8 61.7 to 202.8 15.5 to 51.1 18.4 to 60.5 0.8 to 2.6 171.6 to 563.9

3% dr, 95th perc million 2012$ 80.7 to 265.2 45.9 to 150.9 12.9 to 42.2 114.6 to 376.6 28.9 to 94.9 34.2 to 112.3 1.5 to 4.9 318.6 to 1046.9

NOx (7% dr)

At 468 2012$/ton million 2012$ 2.236 1.272 0.356 3.175 0.800 0.947 0.041 8.827

At 2,639 2012$/ton million 2012$ 12.605 7.172 2.008 17.901 4.509 5.339 0.231 49.764

At 4,809 2012$/ton million 2012$ 22.969 13.069 3.659 32.619 8.217 9.728 0.421 90.682

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.554 0.285 0.065 0.577 0.190 0.242 0.008 1.922

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.868 0.464 0.115 1.023 0.303 0.375 0.014 3.160

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 1.108 0.600 0.153 1.363 0.388 0.477 0.018 4.107

Consumers + CO2 (4th) + NOx (High) billion 2012$ 1.650 0.909 0.239 2.133 0.582 0.706 0.028 6.248

10E-18
Table 10E.1.10 (cont)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Annualized Results 

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.017 0.011 0.004 0.037 0.006 0.007 0.000 0.082

Operating Cost Savings billion 2012$ 0.053 0.029 0.008 0.072 0.018 0.022 0.001 0.203

NPV billion 2012$ 0.036 0.018 0.004 0.035 0.012 0.016 0.000 0.121

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 4.830 2.748 0.769 6.859 1.728 2.045 0.088 19.067

3% dr, average million 2012$ 18.876 10.740 3.007 26.806 6.753 7.994 0.346 74.521

2.5% dr, average million 2012$ 28.944 16.469 4.611 41.105 10.355 12.259 0.530 114.273

3% dr, 95th perc million 2012$ 57.107 32.494 9.097 81.100 20.429 24.186 1.046 225.459

CO2 (domestic)

5% dr, average million 2012$ 0.34 to 1.11 0.19 to 0.63 0.05 to 0.18 0.48 to 1.58 0.12 to 0.40 0.14 to 0.47 0.01 to 0.02 1.33 to 4.39

3% dr, average million 2012$ 1.32 to 4.34 0.75 to 2.47 0.21 to 0.69 1.88 to 6.17 0.47 to 1.55 0.56 to 1.84 0.02 to 0.08 5.22 to 17.14

2.5% dr, average million 2012$ 2.03 to 6.66 1.15 to 3.79 0.32 to 1.06 2.88 to 9.45 0.72 to 2.38 0.86 to 2.82 0.04 to 0.12 8.00 to 26.28

3% dr, 95th perc million 2012$ 4.00 to 13.13 2.27 to 7.47 0.64 to 2.09 5.68 to 18.65 1.43 to 4.70 1.69 to 5.56 0.07 to 0.24 15.78 to 51.86

NOx (7% dr)

At 468 2012$/ton million 2012$ 0.168 0.096 0.027 0.239 0.060 0.071 0.003 0.665

At 2,639 2012$/ton million 2012$ 0.949 0.540 0.151 1.348 0.340 0.402 0.017 3.748

At 4,809 2012$/ton million 2012$ 1.730 0.984 0.276 2.457 0.619 0.733 0.032 6.830

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ 0.041 0.021 0.005 0.042 0.014 0.018 0.001 0.141

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ 0.056 0.029 0.007 0.063 0.019 0.024 0.001 0.199

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.066 0.035 0.009 0.077 0.023 0.028 0.001 0.239

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.095 0.052 0.013 0.118 0.033 0.041 0.002 0.353

10E-19
Table 10E.1.11 Cumulative and Annualized Benefits and Costs of Considered Standard Levels for CRE Units Shipped in the 

Period 2017–2046 (TSL 5, 7 Percent Discount Rate)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Cumulative Results 

Energy Savings

Full-Fuel Cycle quads 0.270 0.162 0.043 0.472 0.165 0.154 0.010 1.278

Economic Impacts

Incremental Equipment Cost billion 2012$ 1.273 0.937 0.205 4.370 1.581 1.713 0.119 10.200

Operating Cost Savings billion 2012$ 0.745 0.438 0.114 1.267 0.445 0.428 0.029 3.465

NPV billion 2012$ -0.528 -0.499 -0.092 -3.103 -1.137 -1.286 -0.091 -6.735

Emissions Savings (physical)

Full-Fuel Cycle

CO2 million metric ton 14.816 8.897 2.359 25.873 9.056 8.438 0.570 70.008

NOx kilo-ton 21.888 13.143 3.484 38.221 13.378 12.464 0.843 103.420

Hg ton 0.030 0.018 0.005 0.053 0.019 0.017 0.001 0.143

SO2 kilo-ton 18.926 11.364 3.013 33.049 11.567 10.778 0.729 89.425

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 83.093 49.893 13.227 145.101 50.786 47.319 3.199 392.618

3% dr, average million 2012$ 406.184 243.894 64.657 709.298 248.259 231.312 15.636 1919.241

2.5% dr, average million 2012$ 661.885 397.431 105.361 1155.817 404.544 376.927 25.479 3127.443

3% dr, 95th perc million 2012$ 1228.881 737.886 195.617 2145.933 751.091 699.817 47.305 5806.529

CO2 (domestic)

5% dr, average million 2012$ 5.8 to 19.1 3.5 to 11.5 0.9 to 3.0 10.2 to 33.4 3.6 to 11.7 3.3 to 10.9 0.2 to 0.7 27.5 to 90.3

3% dr, average million 2012$ 28.4 to 93.4 17.1 to 56.1 4.5 to 14.9 49.7 to 163.1 17.4 to 57.1 16.2 to 53.2 1.1 to 3.6 134.3 to 441.4

2.5% dr, average million 2012$ 46.3 to 152.2 27.8 to 91.4 7.4 to 24.2 80.9 to 265.8 28.3 to 93.0 26.4 to 86.7 1.8 to 5.9 218.9 to 719.3

3% dr, 95th perc million 2012$ 86.0 to 282.6 51.7 to 169.7 13.7 to 45.0 150.2 to 493.6 52.6 to 172.8 49.0 to 161.0 3.3 to 10.9 406.5 to 1335.5

NOx (7% dr)

At 468 2012$/ton million 2012$ 2.383 1.431 0.379 4.162 1.457 1.357 0.092 11.260

At 2,639 2012$/ton million 2012$ 13.436 8.067 2.139 23.462 8.212 7.651 0.517 63.484

At 4,809 2012$/ton million 2012$ 24.483 14.701 3.897 42.753 14.964 13.942 0.942 115.682

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ -0.442 -0.448 -0.078 -2.954 -1.084 -1.237 -0.087 -6.331

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ -0.108 -0.247 -0.025 -2.370 -0.880 -1.047 -0.075 -4.752

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ 0.147 -0.094 0.016 -1.924 -0.724 -0.901 -0.065 -3.544

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.725 0.253 0.108 -0.914 -0.371 -0.572 -0.042 -0.813

10E-20
Table 10E.1.11 (cont)

Units VOP.RC 

Equipment

SVO.RC 

and 

HZO.RC 

Equipment

Open SelfContained 

Equipment

EPCA 

Refrigerators 

and PullDown 

Equipment

EPCA 

Freezers

VCT.RC 

and 

SOC.RC 

Equipment

Ice-cream 

Freezers Total

Annualized Results 

Economic Impacts

Incremental Equipment Cost billion 2012$ 0.096 0.071 0.015 0.329 0.119 0.129 0.009 0.768

Operating Cost Savings billion 2012$ 0.056 0.033 0.009 0.095 0.033 0.032 0.002 0.261

NPV billion 2012$ -0.040 -0.038 -0.007 -0.234 -0.086 -0.097 -0.007 -0.507

Emissions Savings (monetized)

Full-Fuel Cycle

CO2 (global)

5% dr, average million 2012$ 5.148 3.091 0.819 8.990 3.146 2.932 0.198 24.324

3% dr, average million 2012$ 20.120 12.081 3.203 35.134 12.297 11.458 0.774 95.066

2.5% dr, average million 2012$ 30.852 18.525 4.911 53.875 18.857 17.569 1.188 145.777

3% dr, 95th perc million 2012$ 60.871 36.550 9.690 106.295 37.204 34.664 2.343 287.616

CO2 (domestic)

5% dr, average million 2012$ 0.36 to 1.18 0.22 to 0.71 0.06 to 0.19 0.63 to 2.07 0.22 to 0.72 0.21 to 0.67 0.01 to 0.05 1.70 to 5.59

3% dr, average million 2012$ 1.41 to 4.63 0.85 to 2.78 0.22 to 0.74 2.46 to 8.08 0.86 to 2.83 0.80 to 2.64 0.05 to 0.18 6.65 to 21.87

2.5% dr, average million 2012$ 2.16 to 7.10 1.30 to 4.26 0.34 to 1.13 3.77 to 12.39 1.32 to 4.34 1.23 to 4.04 0.08 to 0.27 10.20 to 33.53

3% dr, 95th perc million 2012$ 4.26 to 14.00 2.56 to 8.41 0.68 to 2.23 7.44 to 24.45 2.60 to 8.56 2.43 to 7.97 0.16 to 0.54 20.13 to 66.15

NOx (7% dr)

At 468 2012$/ton million 2012$ 0.179 0.108 0.029 0.313 0.110 0.102 0.007 0.848

At 2,639 2012$/ton million 2012$ 1.012 0.608 0.161 1.767 0.618 0.576 0.039 4.781

At 4,809 2012$/ton million 2012$ 1.844 1.107 0.294 3.220 1.127 1.050 0.071 8.713

NPV

Consumer & Emissions Value 

Consumers + CO2 (1st) + NOx (Low) billion 2012$ -0.034 -0.034 -0.006 -0.224 -0.082 -0.094 -0.007 -0.482

Consumers + CO2 (2nd) + NOx (Med) billion 2012$ -0.019 -0.025 -0.004 -0.197 -0.073 -0.085 -0.006 -0.407

Consumers + CO2 (3rd) + NOx (Med) billion 2012$ -0.008 -0.018 -0.002 -0.178 -0.066 -0.079 -0.006 -0.357

Consumers + CO2 (4th) + NOx (High) billion 2012$ 0.023 0.000 0.003 -0.124 -0.047 -0.061 -0.004 -0.211

10E-21
11-i 

CHAPTER 11. CUSTOMER SUBGROUP ANALYSIS

TABLE OF CONTENTS

11.1 INTRODUCTION ............................................................................................................ 11-1

11.2 IDENTIFYING THE CUSTOMER SUBGROUPS ......................................................... 11-1

11.3 LIFE-CYCLE COST AND PAYBACK PERIOD RESULTS FOR SMALL BUSINESS 

SUBGROUPS ................................................................................................................... 11-7

REFERENCES ........................................................................................................................ 11-15

 

LIST OF TABLES

Table 11.2.1 SBA Size Standards for Businesses that Use Commercial Refrigeration 

Equipment .......................................................................................................... 11-2

Table 11.2.2 Single Unit and Multiunit Firms Census Data for Supermarket and Other 

Grocery (Except Convenience) Stores ............................................................... 11-3

Table 11.2.3 Single Unit and Multiunit Firms Census Data for Convenience Stores ............... 11-4

Table 11.2.4 Single Unit and Multiunit Firms Census Data for Gasoline Stations with 

Convenience Stores ............................................................................................ 11-5

Table 11.2.5 Single Unit and Multiunit Firms Census Data for Full-Service Restaurants ........ 11-5

Table 11.2.6 Single Unit and Multiunit Firms Census Data for Limited-Service 

Restaurants ......................................................................................................... 11-6

Table 11.3.1 Comparison of Mean LCC Savings for the Small Business Subgroup in the 

Foodservice Sector with the National Average Values ..................................... 11-8

Table 11.3.2 Percentage Change in Mean LCC Savings for the Small Business Subgroup 

in the Foodservice Sector Compared to National Average Values .................... 11-9

Table 11.3.3 Comparison of Median Payback Periods for the Small Business Subgroup in 

the Foodservice Sector with National Median Values ....................................... 11-9

Table 11.3.4 Comparison of LCC Savings for the Small Business Subgroup in the FoodRetail Sector with the National Average Values ............................................. 11-11

Table 11.3.5 Percentage Change in the Mean LCC Savings for the Small Business 

Subgroup in the Food-Retail Sector Compared to the National Average 

Values. ............................................................................................................. 11-12

Table 11.3.6 Comparison of Median Payback Periods for the Small Business Subgroup in 

the Food-Retail Sector with the National Median Values ............................... 11-13
11-1 

CHAPTER 11. CUSTOMER SUBGROUP ANALYSIS

11.1 INTRODUCTION

The customer subgroup analysis evaluates impacts on identifiable groups of customers of 

commercial refrigeration equipment who may be disproportionately affected by amended energy 

conservation standards. The life-cycle cost (LCC) and payback period (PBP) analysis described 

in chapter 8 of the technical support document (TSD) is applied to seven major types of 

businesses belonging to the food-retail and foodservice sectors that use a majority of the 

commercial refrigeration equipment. Although the inputs for different types of businesses are 

different in the LCC and PBP analysis, the final results may not reflect the results experienced by 

certain customer subgroups. In other words, some of the adverse impacts on businesses that are 

disproportionately disadvantaged may be masked by the averaging effect of the LCC and PBP 

analysis. Therefore, the U.S. Department of Energy (DOE) carried out the customer subgroup 

analysis by using the LCC and PBP analysis spreadsheet, but applying the inputs that are 

applicable only to the identified subgroups. The LCC spreadsheet model is accessible at

http://www1.eere.energy.gov/buildings/appliance_standards/product.aspx/productid/52. 

11.2 IDENTIFYING THE CUSTOMER SUBGROUPS

DOE identified small businesses as a subgroup that could potentially be affected 

disproportionately by the amended energy conservation standard for commercial refrigeration 

equipment. DOE was concerned that increases in the purchase price of commercial refrigeration 

equipment could have negative impacts on small businesses (i.e., those with low annual 

revenues). To identify small businesses, DOE used size standards from the Small Business 

Administration (SBA) to define which business entities are considered to be small. The SBA 

established size standards for types of economic activity, or industry, under the North American 

Industry Classification System (NAICS).1 Table 11.2.1 presents the size standards established by 

SBA for various businesses that use commercial refrigeration equipment. 
11-2 

Table 11.2.1 SBA Size Standards for Businesses that Use Commercial Refrigeration 

Equipment

Business Type

SBA Size Standard 

Annual Sales 

millions

Supermarkets and Other Grocery 

(except Convenience) Stores $30.0 

Convenience Stores $27.0 

Meat Markets $7.0 

Fish and Seafood Markets $7.0 

Fruit and Vegetable Markets $7.0 

Baked Goods Stores $7.0 

Confectionery and Nut Stores $7.0 

All Other Specialty Food Stores $7.0 

Beer, Wine and Liquor Stores $7.0 

Gasoline Stations with 

Convenience Stores $27.0 

Full-Service Restaurants $7.0 

Limited-Service Restaurants $10.0 

Cafeterias, Grill Buffets, and 

Buffets $25.5 

Snack and Nonalcoholic Beverage 

Bars $7.0 

Food Service Contractors $35.5 

Caterers $7.0 

Mobile Food Services $7.0 

Drinking Places (Alcoholic 

Beverages) $7.0 

Source: Size Standards Used To Define Small Business Concerns

(13 CFR 121.201); also available at 

http://www.sba.gov/content/table-small-business-size-standards

(Last accessed on October 4, 2011).

 In examining the businesses that purchase and use commercial refrigeration equipment, 

DOE analyzed detailed statistical data from the 2007 economic census data.2 Table 11.2.2, Table 

11.2.3, Table 11.2.4, Table 11.2.5 and Table 11.2.6 present the census data for single unit and 

multiunit firms for five different types of businesses that constitute a dominant share of the 

commercial refrigeration equipment market.

Table 11.2.2 presents the data for supermarkets and other grocery (except convenience) 

stores. The data show that 98.9 percent of the firms in this category fall under the SBA definition 

of small business concerns, and comprise of 66 percent of the total number of establishments, 23 

percent of employment, and 18 percent of sales. 
11-3 

Table 11.2.2 Single Unit and Multiunit Firms Census Data for Supermarket and Other 

Grocery (Except Convenience) Stores

 Description Number 

of Firms

Total 

Employment

Number of 

Establishments

Sales per 

Firm 

1000$

Is 

Average 

Firm a 

Small 

Business?

Supermarkets & other grocery (except 

convenience) stores* 

All firms 41,885 2,432,425 64,881 11,131 Yes

Single unit firms 39,878 438,104 39,878 1,676 Yes

Multiunit firms 2,007 1,994,321 25,003 198,998 No

Firms with 1 establishment 577 18,882 577 4,481 Yes

Firms with 2 establishments 597 49,967 1,194 11,824 Yes

Firms with 3 or 4 establishments 374 62,813 1,233 25,250 Yes

Firms with 5 to 9 establishments 235 87,447 1,514 64,030 No

Firms with 10 to 24 establishments 128 125,436 1,797 178,695 No

Firms with 25 to 49 establishments 38 88,107 1,262 422,285 No

Firms with 50 to 99 establishments 22 133,964 1,533 1,130,223 No

Firms with 100 establishments or 

more

36 1,427,705 15,893 8,374,159 No

Fraction of firms classed as small business 0.989

Fraction of establishments that belong to firms 

classified as small businesses 0.661

Fraction of employment in small businesses 0.234

Fraction of sales in small businesses 0.184

*Small business concerns in this category are firms with annual sales less than $30 million.

Table 11.2.3 presents the data for convenience stores. The data show that 99.9 percent of 

the firms in this category fall under the SBA definition of small business concerns, and comprise 

of 90 percent of the total number of establishments, 77 percent of employment, and 76 percent of 

sales.
11-4 

Table 11.2.3 Single Unit and Multiunit Firms Census Data for Convenience Stores

 Description Number 

of Firms

Total 

Employment

Number of 

Establishments

Sales per 

Firm 

1000$

Is 

Average 

Firm a 

Small 

Business?

Convenience Stores*

All firms 22,168 118,787 25,510 942 Yes

Single unit firms 21,529 79,302 21,529 661 Yes

Multiunit firms 639 39,485 3,981 10,408 Yes

Firms with 1 establishment 300 2,458 300 1,087 Yes

Firms with 2 establishments 183 2,804 366 2,318 Yes

Firms with 3 or 4 establishments 86 2,251 281 4,111 Yes

Firms with 5 to 9 establishments 25 1,014 151 5,843 Yes

Firms with 10 to 24 establishments 19 3,369 302 23,634 Yes

Firms with 25 to 49 establishments 12 3,320 443 45,925 No

Firms with 50 to 99 establishments 10 6,365 694 116,707 No

Firms with 100 establishments or 

more

4 17,904 1,444 808,383 No

Fraction of firms classed as small business 0.999

Fraction of establishments that belong to firms 

classified as small businesses 0.899

Fraction of employment in small businesses 0.768

Fraction of sales in small businesses 0.763

*Small business concerns in this category are firms with annual sales less than $27 million.

Table 11.2.4 presents the data for gasoline stations with convenience stores. The data 

show that 98.8 percent of the firms in this category fall under the SBA definition of small 

business concerns, and comprise of 60 percent of the total number of establishments, 52 percent 

of employment, and 43 percent of sales. 
11-5 

Table 11.2.4 Single Unit and Multiunit Firms Census Data for Gasoline Stations with 

Convenience Stores

 Description Number 

of Firms

Total 

Employment

Number of 

Establishments

Sales per 

Firm 

1000$

Is 

Average 

Firm a 

Small 

Business?

Gasoline Stations with Convenience Stores*

All firms 53,375 719,108 97,508 6,300 Yes

Single unit firms 49,010 287,220 49,010 2,249 Yes

Multiunit firms 4,365 431,888 48,498 51,788 No

Firms with 1 establishment 1,160 11,836 1,160 3,363 Yes

Firms with 2 establishments 1,168 21,386 2,336 6,622 Yes

Firms with 3 or 4 establishments 802 24,023 2,697 11,713 Yes

Firms with 5 to 9 establishments 573 30,488 3,709 22,945 Yes

Firms with 10 to 24 establishments 402 47,037 5,978 51,678 No

Firms with 25 to 49 establishments 150 45,235 5,020 128,070 No

Firms with 50 to 99 establishments 58 31,187 3,865 272,955 No

Firms with 100 establishments or 

more

52 220,696 23,733 2,616,567 No

Fraction of firms classed as small business 0.988

Fraction of establishments that belong to firms 

classified as small businesses 0.604

Fraction of employment in small businesses 0.521

Fraction of sales in small businesses 0.429

*Small business concerns in this category are firms with annual sales less than $27 million.

Table 11.2.5 presents the data for full-service restaurants. The data show that 99.5 

percent of the firms in this category fall under the SBA definition of small business concerns, 

and comprise of 87 percent of the total number of establishments, 64 percent of employment, and 

65 percent of sales.

Table 11.2.5 Single Unit and Multiunit Firms Census Data for Full-Service Restaurants

 Description Number 

of Firms

Total 

Employment

Number of 

Establishments

Sales per 

Firm 

1000$

Is Average 

Firm a 

Small 

Business?

Full-service Restaurants*

All firms 188,758 4,603,747 220,089 1,019 Yes

Single unit firms 183,759 2,633,075 183,759 614 Yes

Multiunit firms 4,999 1,970,672 36,330 15,880 No

Firms with 1 establishment 1,477 57,098 1,477 1,696 Yes

Firms with 2 establishments 1,762 119,803 3,524 2,797 Yes

Firms with 3 or 4 establishments 833 115,801 2,796 5,638 Yes

Firms with 5 to 9 establishments 455 142,324 2,966 12,156 No

Firms with 10 establishments or 

more

472 1,535,646 25,567 130,770 No

Fraction of firms classed as small business 0.995

Fraction of establishments that belong to 

firms classified as small businesses 0.870

Fraction of employment in small businesses 0.636

Fraction of sales in small businesses 0.650

*Small business concerns in this category are firms with annual sales less than $7 million.
11-6 

Table 11.2.6 presents the data for limited-service restaurants. The data show that 99 

percent of the firms in this category fall under the SBA definition of small business concerns, 

and comprise of 73 percent of the total number of establishments, 58 percent of employment, and 

58 percent of sales.

Table 11.2.6 Single Unit and Multiunit Firms Census Data for Limited-Service Restaurants

 Description Number 

of Firms

Total 

Employment

Number of 

Establishments

Sales per 

Firm 

1000$

Is Average 

Firm a 

Small 

Business?

Limited-service Restaurants*

All firms 136,505 3,384,517 211,313 1,109 Yes

Single unit firms 126,341 1,263,854 126,341 447 Yes

Multiunit firms 10,164 2,120,663 84,972 9,331 Yes

Firms with 1 establishment 1,271 27,674 1,271 981 Yes

Firms with 2 establishments 2,821 143,768 5,642 2,151 Yes

Firms with 3 or 4 establishments 2,717 221,095 9,174 3,460 Yes

Firms with 5 to 9 establishments 1,934 319,625 12,391 7,154 Yes

Firms with 10 establishments or 

more 1,421 1,408,501 56,494 45,239 No

Fraction of firms classed as small business 0.990

Fraction of establishments that belong to 

firms classified as small businesses 0.733

Fraction of employment in small businesses 0.584

Fraction of sales in small businesses 0.575

*Small business concerns in this category are firms with annual sales less than $10 million.

The census data clearly show that nearly 99 percent of all the firms in both the food-retail 

and foodservice sectors fall under the SBA definition of small businesses. Therefore, it can be 

concluded that in all business types, there are a substantial number of firms that may be 

disproportionately disadvantaged by the new or amended standards. 

In general, the subgroups that face higher cost of capital and lower electricity price rates 

are more disadvantaged than others. Higher cost of capital imposes burden on the businesses 

because they have to borrow additional capital to purchase equipment that meets new or 

amended standards, compared to the case of where there are no new or amended standards. 

Lower electricity price rates result in lower savings in energy costs and, consequently, lower 

LCC savings and higher PBPs. Discount rates and average electricity price rates associated with 

different types of businesses are presented in TSD chapter 8. 

In the food-retail sector, small grocery and convenience stores and convenience stores 

with gas stations face similar discount rates, which are higher than the discount rates for large 

grocery stores (supermarkets) and multi-line retail stores (supercenters). However, convenience 

stores with gasoline station face a lower electricity price rate than small grocery and convenience 

stores. Even though large grocery stores and multi-line retail stores face lower electricity price 

rates, the far higher discount rates faced by convenience stores and small grocery stores make 

them likely to be disproportionally disadvantaged. 

In the foodservice sector, full-service restaurant face higher discount rates but lower 

electricity price rates compared to limited-service restaurants. In this case, it is a toss-up between 

full-service and limited-service restaurants. Full-service restaurants were chosen over limited-
11-7 

service restaurants because a greater share of firms in full-service restaurant category can be 

classified under the SBA definition of small business concerns (compare data in Table 11.2.5 and 

Table 11.2.6).

When the full-service restaurants and gasoline stations with convenience stores are 

compared to one another, full-service restaurants face a far higher discount rate, even though 

they face slightly lower electricity price rates. However, full-service restaurants use only limited 

types of commercial refrigeration equipment and some of the large types of equipment such as 

VOP.RC.M and SOC.RC.M are almost never seen in restaurants. Therefore, DOE identified one 

subgroup each in the food-retail and foodservice sectors for LCC subgroup analysis. In the foodretail sector, gasoline stations with convenience stores were selected, and in the foodservice 

sector, full-service restaurant were selected for LCC subgroup analysis.

DOE carried out two LCC subgroup analyses, one each for full-service restaurants and 

gasoline stations with convenience stores, by using the LCC spreadsheet described in TSD 

chapter 8, but with certain modifications. The input for business type was fixed to the identified 

subgroup, which ensured that the discount rates and electricity price rates associated with only 

that subgroup were selected in the Monte Carlo simulations (see TSD chapter 8). The discount 

rates for these small businesses were increased by adding the small firm premium to the 

weighted average cost of capital (see TSD chapter 8 for details). Another major change from the 

LCC analysis was an added assumption that the subgroups do not have access to national 

accounts, which results in higher distribution channel markups for the subgroups, leading to 

higher equipment purchase prices. Apart from these changes, all other inputs for LCC subgroup 

analysis are same as those in the LCC analysis described in TSD chapter 8. 

11.3 LIFE-CYCLE COST AND PAYBACK PERIOD RESULTS FOR SMALL 

BUSINESS SUBGROUPS

Table 11.3.1 presents the comparison of mean LCC savings for the small business 

subgroup in foodservice sector (full-service restaurants) with the national average values (LCC 

savings results from TSD chapter 8). The results are presented only for self-contained equipment 

classes because full-service restaurants that are small businesses generally do not use remote 

condensing equipment. For all trial standard levels (TSLs) in all equipment classes, the LCC

savings for the small business subgroup are lower than the national average values. Table 11.3.2

presents the percentage change in LCC savings compared to national average values. For a 

majority of equipment classes, the percentage decrease in LCC savings is less than 15 percent. 

Equipment classes that show a substantial decrease in LCC savings, compared to national 

average values, are VOP.SC.M, VCT.SC.M, VCT.SC.L, VCT.SC.I, SVO.SC.M, HZO.SC.M, 

HCT.SC.I, and PD.SC.M, which belong to the classification of self-contained display type 

equipment. It is uncommon to find display type equipment in small full-service restaurants. An 

overwhelming majority of commercial refrigeration equipment in small restaurants is comprised 

of solid door refrigerators and freezers that are used for food storage in the kitchen. The soliddoor equipment (VCS and HCS) exhibits relatively smaller percentage decrease in LCC savings. 

In any case, the value of LCC savings at TSL 4 is positive for all equipment classes. Therefore, 

even though the LCC savings for small business subgroup in foodservice sector are lower than 

the national average values, they are still positive, implying that small businesses still save 

money over the equipment lifetime at TSL 4. Table 11.3.3 presents the comparison of median 
11-8 

PBPs for the small business subgroup in foodservice sector with national median values (median 

PBPs from TSD chapter 8). The PBP values are higher for the small business subgroup in the 

majority of cases.

Table 11.3.1 Comparison of Mean LCC Savings for the Small Business Subgroup in the 

Foodservice Sector with the National Average Values 

Equipment 

Class* Category

Mean LCC Savings**

2012$

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VOP.SC.M Small Business $157.27 $205.50 $690.22 $576.21 ($586.43)

All Business Types $170.78 $227.17 $814.91 $691.27 ($376.52)

VCT.SC.M Small Business $421.59 $960.34 $752.15 $405.47 ($954.55)

All Business Types $566.18 $1,363.60 $1,122.14 $641.05 ($595.52)

VCT.SC.L Small Business $3,127.24 $1,879.37 $1,433.25 $941.77 ($906.58)

All Business Types $4,186.06 $2,522.67 $1,984.45 $1,342.84 ($343.16)

VCT.SC.I Small Business $414.02 $310.26 $261.24 $261.24 ($2,036.01)

All Business Types $572.05 $486.28 $431.88 $431.88 ($1,591.87)

VCS.SC.M Small Business $272.26 $158.67 $125.72 $125.72 ($1,079.78)

All Business Types $278.84 $162.88 $131.80 $131.80 ($1,042.03)

VCS.SC.L Small Business $511.64 $318.96 $259.10 $213.08 ($1,326.22)

All Business Types $524.52 $329.33 $267.81 $220.83 ($1,274.03)

VCS.SC.I Small Business $231.08 $170.13 $146.54 $146.54 ($1,884.22)

All Business Types $236.77 $176.83 $152.69 $152.69 ($1,818.87)

SVO.SC.M Small Business $296.25 $305.21 $486.70 $397.67 ($356.12)

All Business Types $324.33 $334.89 $587.90 $491.99 ($201.61)

HZO.SC.M Small Business $8.16 $8.16 $44.26 $18.90 ($925.33)

All Business Types $8.85 $8.85 $48.60 $28.78 ($821.57)

HZO.SC.L† Small Business NA NA NA NA ($532.72)

All Business Types NA NA NA NA ($473.71)

HCT.SC.M Small Business $99.52 $323.44 $274.76 $219.49 ($385.92)

All Business Types $106.59 $359.48 $307.26 $253.60 ($293.54)

HCT.SC.L Small Business $209.05 $754.27 $544.14 $344.36 ($458.19)

All Business Types $217.19 $790.53 $571.07 $368.92 ($354.75)

HCT.SC.I Small Business $21.15 $32.20 $35.19 $35.19 ($926.07)

All Business Types $21.83 $34.69 $42.48 $42.48 ($811.31)

HCS.SC.M Small Business $22.47 $18.59 $16.03 $7.99 ($436.55)

All Business Types $23.07 $19.18 $16.66 $8.68 ($422.79)

HCS.SC.L Small Business $72.79 $78.72 $76.67 $76.67 ($422.16)

All Business Types $74.69 $80.97 $80.72 $80.72 ($400.63)

PD.SC.M Small Business $815.04 $815.04 $729.72 $187.05 ($861.56)

All Business Types $1,009.53 $1,009.53 $933.59 $310.43 ($637.94)

SOC.SC.M Small Business $625.01 $449.27 $1,149.04 $651.93 ($959.99)

All Business Types $646.15 $466.47 $1,241.60 $739.75 ($735.33)

* Only self-contained equipment have been shown for this subgroup analysis because the remote condensing 

equipment is not generally used by small full-service restaurants.

** Values in parentheses are negative values. Negative percentage values imply decrease in LCC savings and positive percentage 

values imply increase in LCC savings.

†TSLs 1 through 4 for this equipment class are associated with the baseline efficiency level. Hence, the LCC savings 

are shown as zero.
11-9 

Table 11.3.2 Percentage Change in Mean LCC Savings for the Small Business Subgroup in 

the Foodservice Sector Compared to National Average Values 

Equipment Class* TSL 1** TSL 2** TSL 3** TSL 4** TSL 5**

VOP.SC.M (8%) (10%) (15%) (17%) (56%)

VCT.SC.M (26%) (30%) (33%) (37%) (60%)

VCT.SC.L (25%) (26%) (28%) (30%) (164%)

VCT.SC.I (28%) (36%) (40%) (40%) (28%)

VCS.SC.M (2%) (3%) (5%) (5%) (4%)

VCS.SC.L (2%) (3%) (3%) (4%) (4%)

VCS.SC.I (2%) (4%) (4%) (4%) (4%)

SVO.SC.M (9%) (9%) (17%) (19%) (77%)

HZO.SC.M (8%) (8%) (9%) (34%) (13%)

HZO.SC.L† NA NA NA NA (12%)

HCT.SC.M (7%) (10%) (11%) (13%) (31%)

HCT.SC.L (4%) (5%) (5%) (7%) (29%)

HCT.SC.I (3%) (7%) (17%) (17%) (14%)

HCS.SC.M (3%) (3%) (4%) (8%) (3%)

HCS.SC.L (3%) (3%) (5%) (5%) (5%)

PD.SC.M (19%) (19%) (22%) (40%) (35%)

SOC.SC.M (3%) (4%) (7%) (12%) (31%)

* Only self-contained equipment have been shown for this subgroup analysis because the remote 

condensing equipment is not generally used by small full-service restaurants.

** Values in parentheses are negative values. Negative percentage values imply decrease in LCC 

savings and positive percentage values imply increase in LCC savings.

† TSLs 1 through 4 for equipment class HZO.SC.L are associated with the baseline efficiency level. 

Hence, the percentage change in LCC savings are shown as ’NA’. 

‘0%’ means the value is in between -0.5% and 0.5%.

Table 11.3.3 Comparison of Median Payback Periods for the Small Business Subgroup in 

the Foodservice Sector with National Median Values

Equipment 

Class Category

Median Payback Period

years

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VOP.SC.M Small Business 1.77 2.38 4.52 4.81 12.46

All Business Types 1.61 2.17 4.12 4.39 11.37

VCT.SC.M Small Business 0.89 1.77 2.27 2.61 8.34

All Business Types 0.86 1.73 2.21 2.54 8.13

VCT.SC.L Small Business 0.60 0.63 0.85 0.99 3.76

All Business Types 0.58 0.61 0.83 0.96 3.65

VCT.SC.I Small Business 0.93 1.89 2.14 2.14 14.34

All Business Types 0.86 1.74 1.97 1.97 13.21

VCS.SC.M Small Business 0.74 0.94 1.68 1.68 13.51

All Business Types 0.78 0.98 1.75 1.75 14.11

VCS.SC.L Small Business 0.53 0.87 0.96 1.10 10.11

All Business Types 0.55 0.91 1.00 1.15 10.54

VCS.SC.I Small Business 0.77 1.99 2.32 2.32 26.08

All Business Types 0.80 2.07 2.42 2.42 27.19

SVO.SC.M Small Business 2.15 2.25 4.83 5.17 11.30

All Business Types 1.97 2.06 4.43 4.75 10.36

HZO.SC.M Small Business 2.07 2.07 2.64 6.98 60.83

All Business Types 1.89 1.89 2.42 6.40 55.78

HZO.SC.L* Small Business NA NA NA NA 80.27

All Business Types NA NA NA NA 73.62
11-10

Table 11.3.3 (cont)

Equipment 

Class Category

Median Payback Period

years

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

HCT.SC.M Small Business 0.77 2.49 2.69 3.43 13.64

All Business Types 0.69 2.24 2.42 3.08 12.26

HCT.SC.L Small Business 0.58 1.10 1.15 1.61 7.83

All Business Types 0.53 1.00 1.05 1.47 7.15

HCT.SC.I Small Business 0.96 2.60 4.67 4.67 30.57

All Business Types 0.88 2.39 4.28 4.28 27.99

HCS.SC.M Small Business 0.48 1.57 2.42 4.06 32.56

All Business Types 0.50 1.64 2.54 4.28 34.05

HCS.SC.L Small Business 0.82 1.30 2.47 2.47 14.38

All Business Types 0.86 1.36 2.57 2.57 14.98

PD.SC.M Small Business 0.53 0.53 1.11 2.28 7.63

All Business Types 0.53 0.53 1.10 2.27 7.61

SOC.SC.M Small Business 1.14 1.26 2.40 3.06 7.59

All Business Types 1.12 1.24 2.35 2.99 7.42

*TSLs 1 through 4 for this equipment class are associated with the baseline efficiency level. Hence, the PBP is 

shown as “NA.”

Table 11.3.4 presents the comparison of mean LCC savings for the small business 

subgroup in food-retail sector (convenience stores with gasoline stations) with the national 

average values (LCC savings results from TSD chapter 8). This comparison shows mixed results 

with higher LCC savings for the subgroup in some instances and lower in others. The higher LCC 

savings for the subgroup are exhibited in the case of large remote condensing display cases such 

as VOP.RC.M, VOP.RC.L, VCT.RC.M, VCT.RC.L, SVO.RC.M, and SOC.RC.M. This 

equipment is predominantly used in large grocery stores, where the average lifetime of the 

equipment was assumed to be 10 years, while the average lifetime of this equipment in 

convenience stores with gas stations was assumed to be 15 years (see TSD chapter 8 for 

discussion on equipment lifetime assumptions). In general, longer the equipment lifetime, the 

higher the LCC savings because of a longer available timeframe to offset the initial cost increases

by savings in energy costs. Because the large display type equipment is predominantly used in 

larger grocery and multi-line retail stores, the national average values show lower LCC savings 

compared to the LCC savings of the subgroup. Self-contained equipment, on the other hand, was 

assumed to have a 10-year average lifetime in all businesses. Consequently, for self-contained 

equipment, the subgroup LCC savings were lower than the national average LCC savings. 

Table 11.3.5 presents the percentage change in LCC savings of the customer subgroup in 

the food-retail sector compared to national average values at each TSL. For a majority of 

equipment classes that show a decrease in LCC savings for the subgroup, the percentage 

decrease in LCC savings is less than 15 percent. Equipment classes that show a substantial 

decrease in LCC savings, compared to national average values, are VOP.SC.M, SVO.SC.M,

HZO.SC.M, HCT.SC.M, HCT.SC.I, and HCS.SC.M. Among these, the equipment classes that 

show decrease in LCC savings of greater than 15 percent at TSL 4 are VOP.SC.M (27 percent), 

SVO.SC.M (26 percent), HZO.SC.M (38 percent), HCT.SC.M (21 percent), HCT.SC.I (17 

percent), and HCS.SC.M (15 percent). Even though the percentage decrease in LCC savings for 

these equipment classes may appear to be high, the absolute value of decrease in LCC savings is 

small when compared to the total LCC for each equipment class. Table 11.3.6 presents the 

comparison of median PBPs for small business subgroup in foodservice sector with national 
11-11

median values (median PBPs from TSD chapter 8). The PBP values are higher in the small 

business subgroup in all instances, including instances in which the LCC savings for the 

subgroup are higher compared to national average values. This is an expected outcome because 

the PBP values are obtained by dividing the increase in equipment installed cost by the first year 

savings in operating costs and are not affected by the higher average lifetime of the equipment in 

the convenience stores with gas stations. 

Table 11.3.4 Comparison of LCC Savings for the Small Business Subgroup in the FoodRetail Sector with the National Average Values 

Equipment 

Class Category

Mean LCC Savings*

2012$

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VOP.RC.M Small Business $295.31 $927.25 $2,347.11 $1,970.10 ($1,528.98)

All Business Types $235.92 $743.00 $1,788.85 $1,493.72 ($1,668.79)

VOP.RC.L Small Business $668.10 $1,899.69 $1,421.70 $1,421.70 ($3,855.19)

All Business Types $537.27 $1,516.59 $1,129.51 $1,129.51 ($3,692.90)

VOP.SC.M Small Business $145.72 $187.71 $608.29 $503.17 ($655.21)

All Business Types $170.78 $227.17 $814.91 $691.27 ($376.52)

VCT.RC.M Small Business $205.12 $2,200.61 $2,074.57 $1,313.23 ($2,663.30)

All Business Types $175.23 $1,864.44 $1,758.73 $1,108.13 ($2,508.61)

VCT.RC.L Small Business $1,586.15 $1,177.93 $937.97 $937.97 ($3,902.43)

All Business Types $1,357.25 $1,004.72 $797.91 $797.91 ($3,624.20)

VCT.SC.M Small Business $535.27 $1,264.79 $1,024.79 $574.38 ($784.35)

All Business Types $566.18 $1,363.60 $1,122.14 $641.05 ($595.52)

VCT.SC.L Small Business $3,980.86 $2,396.41 $1,864.97 $1,248.55 ($602.09)

All Business Types $4,186.06 $2,522.67 $1,984.45 $1,342.84 ($343.16)

VCT.SC.I Small Business $529.93 $430.30 $375.53 $375.53 ($1,881.48)

All Business Types $572.05 $486.28 $431.88 $431.88 ($1,591.87)

VCS.SC.M Small Business $271.17 $157.63 $124.30 $124.30 ($1,081.39)

All Business Types $278.84 $162.88 $131.80 $131.80 ($1,042.03)

VCS.SC.L Small Business $510.86 $318.22 $258.09 $211.59 ($1,328.25)

All Business Types $524.52 $329.33 $267.81 $220.83 ($1,274.03)

VCS.SC.I Small Business $230.24 $169.16 $145.08 $145.08 ($1,886.42)

All Business Types $236.77 $176.83 $152.69 $152.69 ($1,818.87)

SVO.RC.M Small Business $89.01 $674.27 $1,544.54 $1,286.98 ($949.64)

All Business Types $73.77 $551.98 $1,216.77 $1,008.46 ($1,015.16)

SVO.SC.M Small Business $285.37 $292.93 $449.78 $364.68 ($387.03)

All Business Types $324.33 $334.89 $587.90 $491.99 ($201.61)

SOC.RC.M Small Business $147.25 $280.43 $1,278.84 $670.29 ($960.27)

All Business Types $118.36 $226.26 $997.89 $494.51 ($982.21)

HZO.RC.M** Small Business NA NA NA NA ($1,384.63)

All Business Types NA NA NA NA ($1,271.24)

HZO.RC.L** Small Business NA NA NA NA ($2,306.30)

All Business Types NA NA NA NA ($2,134.96)

HZO.SC.M Small Business $8.05 $8.05 $43.45 $17.89 ($927.01)

All Business Types $8.85 $8.85 $48.60 $28.78 ($821.57)

HZO.SC.L** Small Business NA NA NA NA ($533.60)

All Business Types NA NA NA NA ($473.71)

HCT.SC.M Small Business $93.73 $299.66 $253.49 $199.55 ($407.29)

All Business Types $106.59 $359.48 $307.26 $253.60 ($293.54)

HCT.SC.L Small Business $249.39 $906.61 $655.15 $425.64 ($366.23)

All Business Types $217.19 $790.53 $571.07 $368.92 ($354.75)
11-12

Table 11.3.4 (cont)

Equipment 

Class Category

Mean LCC Savings

2010$

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

HCT.SC.I Small Business $21.15 $32.20 $35.19 $35.19 ($926.07)

All Business Types $21.83 $34.69 $42.48 $42.48 ($811.31)

HCS.SC.M Small Business $22.48 $18.44 $15.75 $7.40 ($437.16)

All Business Types $23.07 $19.18 $16.66 $8.68 ($422.79)

HCS.SC.L Small Business $72.46 $78.02 $75.98 $75.98 ($423.21)

All Business Types $74.69 $80.97 $80.72 $80.72 ($400.63)

PD.SC.M Small Business $1,026.80 $1,026.80 $945.24 $299.03 ($744.27)

All Business Types $1,009.53 $1,009.53 $933.59 $310.43 ($637.94)

SOC.SC.M Small Business $619.20 $444.70 $1,138.70 $643.60 ($967.59)

All Business Types $646.15 $466.47 $1,241.60 $739.75 ($735.33)

* Values in parentheses are negative values.

** TSLs 1 through 4 for equipment classes HZO.RC.M, HZO.RC.L and HZO.SC.L are associated with the baseline 

efficiency level. Hence, the LCC savings are shown as ‘NA.’

Table 11.3.5 Percentage Change in the Mean LCC Savings for the Small Business 

Subgroup in the Food-Retail Sector Compared to the National Average Values. 

Equipment Class TSL 1* TSL 2* TSL 3* TSL 4* TSL 5*

VOP.RC.M 25% 25% 31% 32% 8%

VOP.RC.L 24% 25% 26% 26% (4%)

VOP.SC.M (15%) (17%) (25%) (27%) (74%)

VCT.RC.M 17% 18% 18% 19% (6%)

VCT.RC.L 17% 17% 18% 18% (8%)

VCT.SC.M (5%) (7%) (9%) (10%) (32%)

VCT.SC.L (5%) (5%) (6%) (7%) (75%)

VCT.SC.I (7%) (12%) (13%) (13%) (18%)

VCS.SC.M (3%) (3%) (6%) (6%) (4%)

VCS.SC.L (3%) (3%) (4%) (4%) (4%)

VCS.SC.I (3%) (4%) (5%) (5%) (4%)

SVO.RC.M 21% 22% 27% 28% 6%

SVO.SC.M (12%) (13%) (23%) (26%) (92%)

SOC.RC.M 24% 24% 28% 36% 2%

HZO.RC.M** NA NA NA NA (9%)

HZO.RC.L** NA NA NA NA (8%)

HZO.SC.M (9%) (9%) (11%) (38%) (13%)

HZO.SC.L** NA NA NA NA (13%)

HCT.SC.M (12%) (17%) (17%) (21%) (39%)

HCT.SC.L 15% 15% 15% 15% (3%)

HCT.SC.I (3%) (7%) (17%) (17%) (14%)

HCS.SC.M (3%) (4%) (5%) (15%) (3%)

HCS.SC.L (3%) (4%) (6%) (6%) (6%)

PD.SC.M 2% 2% 1% (4%) (17%)

SOC.SC.M (4%) (5%) (8%) (13%) (32%)

* Values in parentheses are negative values. Negative percentage values imply decrease in 

LCC savings and positive percentage values imply increase in LCC savings. ** TSLs 1 through 4 for equipment classes HZO.RC.M, HZO.RC.L and HZO.SC.L are 

associated with the baseline efficiency level. Hence, the LCC savings are zero and the 

decrease in LCC savings are shown as ‘NA.’

‘0%’ means the value is in between -0.5% and 0.5%.
11-13

Table 11.3.6 Comparison of Median Payback Periods for the Small Business Subgroup in 

the Food-Retail Sector with the National Median Values 

Equipment 

Class Category

Median Payback Period

years

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

VOP.RC.M Small Business 1.78 1.83 3.88 4.02 12.09

All Business Types 1.73 1.77 3.77 3.91 11.76

VOP.RC.L Small Business 1.15 2.10 2.30 2.30 18.90

All Business Types 1.11 2.03 2.22 2.22 18.30

VOP.SC.M Small Business 1.95 2.65 5.02 5.34 13.84

All Business Types 1.61 2.17 4.12 4.39 11.37

VCT.RC.M Small Business 1.28 2.51 2.53 2.80 13.61

All Business Types 1.23 2.42 2.43 2.70 13.09

VCT.RC.L Small Business 1.35 1.57 1.71 1.71 16.40

All Business Types 1.30 1.51 1.64 1.64 15.75

VCT.SC.M Small Business 0.98 1.95 2.49 2.87 9.17

All Business Types 0.86 1.73 2.21 2.54 8.13

VCT.SC.L Small Business 0.65 0.68 0.93 1.09 4.12

All Business Types 0.58 0.61 0.83 0.96 3.65

VCT.SC.I Small Business 1.02 2.08 2.35 2.35 15.75

All Business Types 0.86 1.74 1.97 1.97 13.21

VCS.SC.M Small Business 0.79 1.01 1.79 1.79 14.45

All Business Types 0.78 0.98 1.75 1.75 14.11

VCS.SC.L Small Business 0.56 0.93 1.03 1.18 10.80

All Business Types 0.55 0.91 1.00 1.15 10.54

VCS.SC.I Small Business 0.82 2.12 2.48 2.48 27.85

All Business Types 0.80 2.07 2.42 2.42 27.19

SVO.RC.M Small Business 1.36 2.74 4.49 4.66 12.01

All Business Types 1.31 2.64 4.34 4.50 11.60

SVO.SC.M Small Business 2.29 2.40 5.18 5.55 12.12

All Business Types 1.97 2.06 4.43 4.75 10.36

SOC.RC.M Small Business 1.28 1.48 3.41 4.54 12.24

All Business Types 1.25 1.44 3.31 4.41 11.88

HZO.RC.M* Small Business NA NA NA NA 166.41

All Business Types NA NA NA NA 161.23

HZO.RC.L* Small Business NA NA NA NA 86.47

All Business Types NA NA NA NA 83.78

HZO.SC.M Small Business 2.14 2.14 2.74 7.23 62.97

All Business Types 1.89 1.89 2.42 6.40 55.78

HZO.SC.L* Small Business NA NA NA NA 83.02

All Business Types NA NA NA NA 73.62

HCT.SC.M Small Business 0.80 2.60 2.81 3.58 14.23

All Business Types 0.69 2.24 2.42 3.08 12.26

HCT.SC.L Small Business 0.59 1.12 1.17 1.65 8.01

All Business Types 0.53 1.00 1.05 1.47 7.15

HCT.SC.I Small Business 0.96 2.60 4.67 4.67 30.57

All Business Types 0.88 2.39 4.28 4.28 27.99

HCS.SC.M Small Business 0.51 1.68 2.60 4.39 34.88

All Business Types 0.50 1.64 2.54 4.28 34.05

HCS.SC.L Small Business 0.88 1.40 2.63 2.63 15.35

All Business Types 0.86 1.36 2.57 2.57 14.98
11-14

Table 11.3.6 (cont)

Equipment Class Category

Median Payback Period

years

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

PD.SC.M Small Business 0.58 0.58 1.22 2.50 8.40

All Business Types 0.53 0.53 1.10 2.27 7.61

SOC.SC.M Small Business 1.23 1.36 2.58 3.28 8.13

All Business Types 1.12 1.24 2.35 2.99 7.42

*TSLs 1 through 4 for equipment classes HZO.RC.M, HZO.RC.L and HZO.SC.L are associated with the baseline efficiency 

level. Hence, the payback period is shown as “NA.”

The LCC subgroup analysis results show that the identified subgroups in foodservice and 

food-retail sector face slightly lower LCC savings and higher PBP values. Comparison of LCC 

savings values at TSL 4 shows the decrease in LCC savings is less than 15 percent for a majority 

of the equipment used in small businesses. In all cases at TSL 4, and for both the subgroups, the 

LCC savings are positive, as are the national average values, indicating that although LCC 

savings are lower for the customer subgroups, customers still save money over the lifetimes of 

the equipment. Therefore, DOE concludes that the identified subgroups do not face a substantial 

disadvantage when compared with an average customer of commercial refrigeration equipment. 
11-15

REFERENCES

1. Title 13, Code of Federal Regulations, Chapter I–Small Business Administration, Part 121–Small 

Business Administration, Subpart A–Size Eligibility Provisions and Standards. May 4, 2005.

2. U.S. Census Bureau. 2007 Economic Census, Sector 44: Retail Trade: Subject Series–Estab & 

Firm Size: Summary Statistics for Single Unit and Multiunit Firms for the United States: 2007. 

(Last accessed October 20, 2011.) <http://factfinder.census.gov/servlet/IBQTable?_bm=y&-

geo_id=&-ds_name=EC0744SSSZ3&-_lang=en> 
CHAPTER 12. MANUFACTURER IMPACT ANALYSIS

TABLE OF CONTENTS

12.1 INTRODUCTION ............................................................................................................ 12-1

12.2 METHODOLOGY ........................................................................................................... 12-1

12.2.1 Phase I: Industry Profile........................................................................................ 12-1

12.2.2 Phase II: Industry Cash-Flow Analysis and Interview Guide ............................... 12-2

12.2.2.1 Industry Cash-Flow Analysis ................................................................. 12-2

12.2.2.2 Interview Guides .................................................................................... 12-2

12.2.3 Phase III: Subgroup Analysis................................................................................ 12-3

12.2.3.1 Manufacturer Interviews ........................................................................ 12-3

12.2.3.2 Revised Industry Cash-Flow Analysis ................................................... 12-3

12.2.3.3 Manufacturer Subgroup Analysis .......................................................... 12-3

12.2.3.4 Manufacturing Capacity Impact ............................................................ 12-5

12.2.3.5 Employment Impact ............................................................................... 12-5

12.2.3.6 Cumulative Regulatory Burden ............................................................. 12-5

12.3 MANUFACTURER IMPACT ANALYSIS KEY ISSUES ............................................. 12-5

12.3.1 Enforcement .......................................................................................................... 12-6

12.3.2 Certification, Compliance, and Enforcement Costs .............................................. 12-6

12.3.3 Disproportionate Impact on Small Businesses ..................................................... 12-6

12.3.4 Potential Loss of Product Utility and Decrease in Food Safety............................ 12-6

12.4 GRIM INPUTS AND ASSUMPTIONS ........................................................................... 12-7

12.4.1 Overview of the GRIM ......................................................................................... 12-7

12.4.2 Sources for GRIM Inputs ...................................................................................... 12-8

12.4.2.1 Corporate Annual Reports ..................................................................... 12-8

12.4.2.2 Standard and Poor’s Credit Ratings ....................................................... 12-9

12.4.2.3 Shipment Model ..................................................................................... 12-9

12.4.2.4 Engineering Analysis ............................................................................. 12-9

12.4.2.5 Manufacturer Interviews ........................................................................ 12-9

12.4.3 Financial Parameters ........................................................................................... 12-10

12.4.4 Corporate Discount Rate ..................................................................................... 12-10

12.4.5 Trial Standard Levels .......................................................................................... 12-12

12.4.6 NIA Shipments.................................................................................................... 12-13

12.4.7 Manufacturer Production Costs .......................................................................... 12-14

12.4.8 Conversion Costs ................................................................................................ 12-19

12.4.8.1 Capital Conversion Costs ..................................................................... 12-20

12.4.8.2 Product Conversion Costs .................................................................... 12-21

12.4.9 Markup Scenarios ............................................................................................... 12-21

12.4.9.1 Preservation of Gross Margin Percentage Scenario ............................. 12-22

12.4.9.2 Preservation of Operating Profit Scenario ........................................... 12-22

12.4.10 Experience Curve Rates ................................................................................. 12-22

12.4.11 Light-Emitting Diode Price Projections ......................................................... 12-22

12.5 INDUSTRY FINANCIAL IMPACTS ........................................................................... 12-23

12.5.1 Introduction ......................................................................................................... 12-23

12.5.2 Commercial Refrigeration Industry Financial Impacts ....................................... 12-24

12-i 
12.6 IMPACTS ON SMALL BUSINESS MANUFACTURERS .......................................... 12-26

12.7 OTHER IMPACTS ......................................................................................................... 12-27

12.7.1 Employment ........................................................................................................ 12-27

12.7.2 Production Capacity ............................................................................................ 12-29

12.7.3 Cumulative Regulatory Burden .......................................................................... 12-29

12.7.3.1 DOE Regulations for Other Products Produced by Commercial 

Refrigeration Equipment Manufacturers ............................................................ 12-29

12.7.3.2 Other DOE and Federal Actions Affecting the Commercial Refrigeration 

Equipment Industry ............................................................................................. 12-30

12.7.3.3 Other Regulations That Could Impact Commercial Refrigeration 

Equipment Manufacturers ................................................................................... 12-31

12.8 CONCLUSION ............................................................................................................... 12-32

REFERENCES ........................................................................................................................ 12-36

LIST OF TABLES

Table 12.2.1 SBA and NAICS Classification of Small Businesses Potentially Affected by This 

Rulemaking ........................................................................................................ 12-4

Table 12.4.1 GRIM Financial Parameters Based on 2004–2010 Weighted Company Financial 

Data .................................................................................................................. 12-10

Table 12.4.2 Cost of Equity Calculation .................................................................................. 12-11

Table 12.4.3 Cost of Debt Calculation..................................................................................... 12-12

Table 12.4.4 Trial Standard Levels for Energy Efficiency Analysis of Commercial Refrigeration 

Equipment ........................................................................................................ 12-13

Table 12.4.5 Manufacturer Production Cost Breakdown (2012$) for VOP.RC.M ................. 12-14

Table 12.4.6 Manufacturer Production Cost Breakdown (2012$) for VOP.RC.L .................. 12-14

Table 12.4.7 Manufacturer Production Cost Breakdown (2012$) for VOP.SC.M.................. 12-14

Table 12.4.8 Manufacturer Production Cost Breakdown (2012$) for VCT.RC.M ................. 12-15

Table 12.4.9 Manufacturer Production Cost Breakdown (2012$) for VCT.RC.L .................. 12-15

Table 12.4.10 Manufacturer Production Cost Breakdown (2012$) for VCT.SC.M ................ 12-15

Table 12.4.11 Manufacturer Production Cost Breakdown (2012$) for VCT.SC.L ................. 12-15

Table 12.4.12 Manufacturer Production Cost Breakdown (2012$) for VCT.SC.I .................. 12-16

Table 12.4.13 Manufacturer Production Cost Breakdown (2012$) for VCS.SC.M ................ 12-16

Table 12.4.14 Manufacturer Production Cost Breakdown (2012$) for VCS.SC.L ................. 12-16

Table 12.4.15 Manufacturer Production Cost Breakdown (2012$) for VCS.SC.I .................. 12-16

Table 12.4.16 Manufacturer Production Cost Breakdown (2012$) for SVO.RC.M ............... 12-17

Table 12.4.17 Manufacturer Production Cost Breakdown (2012$) for SVO.SC.M................ 12-17

Table 12.4.18 Manufacturer Production Cost Breakdown (2012$) for SOC.RC.M ............... 12-17

Table 12.4.19 Manufacturer Production Cost Breakdown (2012$) for HZO.RC.M ............... 12-17

Table 12.4.20 Manufacturer Production Cost Breakdown (2012$) for HZO.RC.L ................ 12-17

Table 12.4.21 Manufacturer Production Cost Breakdown (2012$) for HZO.SC.M ............... 12-17

Table 12.4.22 Manufacturer Production Cost Breakdown (2012$) for HZO.SC.L ................ 12-18

Table 12.4.23 Manufacturer Production Cost Breakdown (2012$) for HCT.SC.M ................ 12-18

Table 12.4.24 Manufacturer Production Cost Breakdown (2012$) for HCT.SC.L ................. 12-18

Table 12.4.25 Manufacturer Production Cost Breakdown (2012$) for HCT.SC.I .................. 12-18

Table 12.4.26 Manufacturer Production Cost Breakdown (2012$) for HCS.SC.M ................ 12-18

Table 12.4.27 Manufacturer Production Cost Breakdown (2012$) for HCS.SC.L ................. 12-19

12-ii
Table 12.4.28 Manufacturer Production Cost Breakdown (2012$) for PD.SC.M .................. 12-19

Table 12.4.29 Manufacturer Production Cost Breakdown (2012$) for SOC.SC.M ................ 12-19

Table 12.4.30 Industry Cumulative Capital Conversion Cost ................................................. 12-20

Table 12.4.31 Industry Cumulative Product Conversion Cost ................................................ 12-21

Table 12.5.1 Preservation of Gross Margin Percentage Scenario Changes in INPV for 

Commercial Refrigeration Equipment ............................................................. 12-24

Table 12.5.2 Preservation of Operating Profit Scenario Changes in INPV for Commercial 

Refrigeration Equipment .................................................................................. 12-24

Table 12.7.1 Potential Changes in the Number of Commercial Refrigeration Equipment 

Production Workers in 2017 ............................................................................ 12-28

Table 12.8.1 TSLs for the Commercial Refrigeration Equipment Rulemaking ...................... 12-33

LIST OF FIGURES

Figure 12.4.1 Using the GRIM to Calculate Cash Flow ............................................................ 12-8

Figure 12.5.1 Annual Industry Net Cash Flows for Commercial Refrigeration Equipment 

(Preservation of Gross Margin Percentage Markup Scenario) ........................ 12-25

Figure 12.5.2 Annual Industry Net Cash Flows for Commercial Refrigeration Equipment 

(Preservation of Operating Profit Markup Scenario) ....................................... 12-26

12-iii
CHAPTER 12. MANUFACTURER IMPACT ANALYSIS

12.1 INTRODUCTION

In determining whether a standard is economically justified, the U.S. Department of 

Energy (DOE or the Department) is required to consider the economic impact of the standard on 

the manufacturers and on the consumers of the products subject to such a standard. (42 U.S.C. 

6313(a)(6)(B)(i)) The law also calls for an assessment of the impact of any lessening of 

competition as determined in writing by the Attorney General. Id. DOE conducted a 

manufacturer impact analysis (MIA) to estimate the financial impact of amended energy 

conservation standards on manufacturers of commercial refrigeration equipment, and assessed 

the impact of such standards on direct employment and manufacturing capacity. 

The MIA has both quantitative and qualitative aspects. The quantitative part of the MIA 

primarily relies on the Government Regulatory Impact Model (GRIM), an industry cash-flow 

model adapted for each product in this rulemaking. The GRIM inputs include information on 

industry cost structure, shipments, and pricing strategies. The GRIM’s key output is the industry 

net present value (INPV). The model estimates the financial impact of more-stringent energy 

conservation standards for each product by comparing changes in INPV between a base case and 

the various trial standard levels (TSLs) in the standards case. The qualitative part of the MIA 

addresses product characteristics, manufacturer characteristics, and market and product trends, as 

well as the impact of standards on subgroups of manufacturers. 

12.2 METHODOLOGY

DOE conducted the MIA in three phases. Phase I, “Industry Profile,” consisted of 

preparing an industry characterization for the commercial refrigeration industry, including data 

on sales volumes, pricing, employment, and financial structure. In Phase II, “Industry Cash 

Flow,” DOE used the GRIM to assess the potential impacts of amended energy conservation 

standards on manufacturers. DOE also developed interview guides to gather information on the 

potential impacts on these manufacturers. In Phase III, “Subgroup Impact Analysis,” DOE 

interviewed manufacturers representing a broad cross-section of the commercial refrigeration

industry. Using information from Phase II, DOE refined its analysis in the GRIM, developed 

additional analyses for subgroups that required special consideration, and incorporated 

qualitative data from interviews into its analysis.

12.2.1 Phase I: Industry Profile

In Phase I of the MIA, DOE prepared a profile of the commercial refrigeration industry 

that built on the market and technology assessment prepared for this rulemaking (refer to chapter 

3 of the technical support document (TSD)). Before initiating the detailed impact studies, DOE 

collected information on the present and past structure and market characteristics of the 

commercial refrigeration industry. This information included shipments, manufacturer markups, 

and the cost structures of various manufacturers. The industry profile includes: (1) further detail 

on the overall market and product characteristics; (2) estimated manufacturer market shares; 

(3) financial parameters such as net plant, property, and equipment (PPE); selling, general and 

administrative (SG&A) expenses; cost of goods sold, etc.; and (4) trends in the number of firms, 

12-1 
market, and product characteristics. The industry profile included a top-down cost analysis of 

commercial refrigeration equipment manufacturers that DOE used to derive the preliminary 

financial inputs for the GRIM (e.g., revenues, depreciation, SG&A, and research and 

development (R&D) expenses). 

DOE also used public information to further calibrate its initial characterization of the 

industry, including Securities and Exchange Commission (SEC) 10-K reports,1 Standard & 

Poor’s (S&P) stock reports,2 market research tools (i.e., Hoovers3), corporate annual reports, and 

the U.S. Census Bureau’s 2011 Annual Survey of Manufacturers.4 DOE also characterized these 

industries using information from its engineering analysis and the life-cycle cost analysis.

12.2.2 Phase II: Industry Cash-Flow Analysis and Interview Guide 

Phase II focused on the financial impacts of potential amended energy conservation 

standards on manufacturers of commercial refrigeration equipment. More-stringent energy 

conservation standards can affect manufacturer cash flows in three distinct ways: (1) create a 

need for increased investment; (2) raise production costs per unit; and (3) alter revenue due to 

higher per-unit prices and/or possible changes in sales volumes. To quantify these impacts, DOE 

used the GRIM to perform a cash-flow analysis for the commercial refrigeration industry. In 

performing these analyses, DOE used the financial values derived during Phase I and the 

shipment scenarios used in the national impact analysis (NIA). In Phase II, DOE performed these 

preliminary industry cash-flow analyses and prepared written guides for manufacturer 

interviews.

12.2.2.1 Industry Cash-Flow Analysis 

The GRIM uses several factors to determine a series of annual cash flows from the 

announcement year of amended energy conservation standards until 30 years after the standards’ 

compliance date. These factors include annual expected revenues, costs of goods sold, SG&A, 

taxes, and capital expenditures related to the amended standards. Inputs to the GRIM include 

manufacturer production costs (MPCs), markup assumptions, and shipments forecasts developed 

in other analyses. DOE derived the manufacturing costs from the engineering analysis and 

information provided by the industry. It estimated typical manufacturer markups from public 

financial reports and interviews with manufacturers. DOE developed alternative markup 

scenarios for the GRIM based on discussions with manufacturers. DOE’s shipments analysis, 

presented in chapter 9 of the TSD, provided the basis for the shipment projections in the GRIM. 

The financial parameters were developed using publicly available manufacturer data and were 

revised with information submitted confidentially during manufacturer interviews. The GRIM 

results are compared to base case projections for the industry. The financial impact of amended 

energy conservation standards is the difference between the discounted annual cash flows in the 

base case and standards case at each TSL.

12.2.2.2 Interview Guides

During Phase II of the MIA, DOE interviewed manufacturers to gather information on 

the effects of amended energy conservation standards on revenues and finances, direct 

employment, capital assets, and industry competitiveness. Before the interviews, DOE 

12-2 
distributed an interview guide to interviewees. The interview guide provided a starting point for 

identifying relevant issues and impacts of amended energy conservation standards on individual 

manufacturers or subgroups of manufacturers. Information received from these meetings is 

protected by non-disclosure agreements and resides with DOE’s contractors. The MIA interview 

topics included: (1) key issues to this rulemaking; (2) company overview and organizational 

characteristics; (3) engineering analysis follow-up; (4) manufacturer markups and profitability; 

(5) shipment projections and market shares; (6) distribution channels; (7) financial parameters; 

(8) conversion costs; (9) cumulative regulatory burden; (10) direct employment impact 

assessment; (11) exports, foreign competition, and outsourcing; (12) consolidation; and (13) 

impacts on small businesses.

12.2.3 Phase III: Subgroup Analysis

For its analysis, DOE presented the impacts on all classes of commercial refrigeration 

equipment as a whole. While conducting the MIA, DOE interviewed a representative crosssection of commercial refrigeration equipment manufacturers. The MIA interviews broadened 

the discussion to include business-related topics. DOE sought feedback from industry on the 

approaches used in the GRIM as well as key issues and concerns. During interviews, DOE 

defined one manufacturer subgroup, small manufacturers, that could be disproportionately 

impacted by amended energy conservation standards. 

12.2.3.1 Manufacturer Interviews

The information gathered in Phase I and the cash-flow analysis performed in Phase II are 

supplemented with information gathered from manufacturer interviews in Phase III. The 

interview process provides an opportunity for interested parties to express their views on 

important issues privately, allowing confidential or sensitive information to be considered in the 

rulemaking process. 

DOE used these interviews to tailor the GRIM to reflect financial characteristics unique 

to the commercial refrigeration equipment industry. Interviews were scheduled well in advance 

to provide every opportunity for key individuals to be available for comment. Although a written 

response to the questionnaire was acceptable, DOE sought interactive interviews, which help 

clarify responses and identify additional issues. The resulting information provides valuable 

inputs to the GRIM developed for the equipment classes.

12.2.3.2 Revised Industry Cash-Flow Analysis 

In Phase II of the MIA, DOE provided manufacturers with preliminary GRIM input 

financial figures for review and evaluation. During the interviews, DOE requested comments on 

the values it selected for the parameters. DOE revised its industry cash-flow model based on this 

feedback. Section 12.4.3 provides more information on how DOE calculated the parameters. 

12.2.3.3 Manufacturer Subgroup Analysis 

Using average cost assumptions to develop an industry cash-flow estimate may not 

adequately assess differential impacts of amended energy conservation standards among 

manufacturer subgroups. For example, small manufacturers, niche players, or manufacturers 

12-3 
exhibiting a cost structure that largely differs from the industry average could be more negatively 

affected. To address this possible impact, DOE used the results of the industry characterization 

analysis in Phase I to group manufacturers that exhibit similar characteristics. 

During the interviews, DOE discussed the potential subgroups and subgroup members it 

identified for the analysis. DOE asked manufacturers and other interested parties to suggest what 

subgroups or characteristics are the most appropriate to analyze. As described in section 12.2.3, 

DOE presents the industry impacts on commercial refrigeration equipment manufacturers as a 

whole because most of the equipment classes represent the same market served by the same 

manufacturers. However, as discussed below, DOE identified one manufacturer subgroup that 

warranted a separate impact analysis: small manufacturers.

Small Business Manufacturer Subgroup 

DOE investigated whether small business manufacturers should be analyzed as a 

manufacturer subgroup. DOE used the Small Business Administration (SBA) small business size 

standards effective on November 5, 2010, as amended, and the North American Industry 

Classification System (NAICS) code, presented in Table 12.2.1, to determine whether any small 

entities would be affected by the rulemaking.5 For the equipment classes under review, the SBA 

bases its small business definition on the total number of employees for a business, its 

subsidiaries, and its parent companies. An aggregated business entity with fewer employees than 

the listed limit is considered a small business.

Table 12.2.1 SBA and NAICS Classification of Small Businesses Potentially Affected by 

This Rulemaking

Industry Description Revenue Limit Employee Limit NAICS

Air-conditioning and Warm Air Heating 

Equipment and Commercial and Industrial 

Refrigeration Equipment Manufacturing

N/A 750 333415

DOE used publicly available and proprietary information to identify potential small 

manufacturers. DOE’s research involved industry trade association membership directories 

(including American Heating and Refrigeration Institute (AHRI) and North American 

Association of Food Equipment Manufacturers (NAFEM)), product databases (e.g., AHRI 

Directory, NSF International listings, the SBA Database), individual company websites, and 

market research tools (e.g., Hoovers.com) to create a list of companies that manufacture or sell 

equipment covered by this rulemaking. DOE also asked stakeholders and industry 

representatives if they were aware of any other small manufacturers during manufacturer

interviews and at previous DOE public meetings. DOE screened out companies that did not offer 

equipment covered by this rulemaking, did not meet the definition of a “small business,” or are 

foreign owned and operated. 

Based on this analysis, DOE identified 32 commercial refrigeration equipment 

manufacturers that are small businesses. DOE made an effort to contact small businesses to 

solicit feedback on the potential impacts of energy conservation standards. The businesses 

replied with varying amounts of information in written responses and/or interviews. In addition 

to posing a subset of modified MIA interview questions, DOE solicited data on differential 

impacts these companies might experience from amended energy conservation standards. Based 

12-4 
on these interviews and industry research, DOE reports the potential impacts of this rulemaking 

on small manufacturers in section 12.6. 

12.2.3.4 Manufacturing Capacity Impact 

One significant outcome of amended energy conservation standards could be the 

obsolescence of existing manufacturing assets, including tooling and investment. The 

manufacturer interview guides have a series of questions to help identify impacts of amended 

standards on manufacturing capacity, specifically, capacity utilization and plant location 

decisions in the United States and North America, with and without amended standards; the 

ability of manufacturers to upgrade or remodel existing facilities to accommodate the new 

requirements; the nature and value of any stranded assets; and estimates for any one-time 

changes to existing PPE. DOE’s estimates of the one-time capital changes and stranded assets 

affect the cash flow estimates in the GRIM. These estimates can be found in section 12.4.8. 

DOE’s discussion of the capacity impact can be found in section 12.7.2. 

12.2.3.5 Employment Impact 

The impact of amended energy conservation standards on employment is an important 

consideration in the rulemaking process. To assess how domestic direct employment patterns 

might be affected, the interviews explored current employment trends in the commercial 

refrigeration industry. The interviews also solicited manufacturer views on changes in 

employment patterns that may result from more-stringent standards. The employment impacts 

section of the interview guide focused on current employment levels associated with 

manufacturers at each production facility, expected future employment levels with and without 

amended energy conservation standards, and differences in workforce skills and issues related to 

the retraining of employees. The employment impacts are reported in section 12.7.1. 

12.2.3.6 Cumulative Regulatory Burden

DOE seeks to mitigate the overlapping effects on manufacturers due to amended energy 

conservation standards and other regulatory actions affecting the same products. DOE analyzed 

the impact on manufacturers of multiple, product-specific regulatory actions. Based on its own 

research and discussions with manufacturers, DOE identified regulations relevant to commercial 

refrigeration equipment, such as State regulations and other Federal regulations that impact other 

products made by the same manufacturers. Discussion of the cumulative regulatory burden can 

be found in section 12.7.3. 

12.3 MANUFACTURER IMPACT ANALYSIS KEY ISSUES

Each MIA interview starts by asking: “What are the key issues for your company 

regarding the energy conservation standard rulemaking?” This question prompts manufacturers 

to identify the issues they feel DOE should explore and discuss further during the interview. The 

following sections describe the most significant issues identified by manufacturers. These 

summaries are provided in aggregate to protect manufacturer confidentiality. 

12-5 
12.3.1 Enforcement

Interviewed manufacturers expressed concern about the enforcement of an energy 

efficiency standard for commercial refrigeration equipment. Manufacturers believe that 

insufficient enforcement will lead to market distortions, as companies that make the necessary 

investments to meet standards and compliance requirements would be at a distinct pricing 

disadvantage to unscrupulous competitors that do not fully comply. The manufacturers requested 

that DOE take the enforcement action necessary to maintain a level playing field and to eliminate 

non-compliant products from the market. 

12.3.2 Certification, Compliance, and Enforcement Costs

Nearly all manufacturers expressed concern over certification, compliance, and 

enforcement (CC&E) costs. In particular, confusion over the definition of “basic model” and the 

implementation of alternative efficiency determination methods (AEDMs) has made it difficult 

for some manufacturers to anticipate their total testing needs and total testing costs. 

Manufacturers were concerned that CC&E requirements for commercial refrigeration 

equipment do not take into account the customized nature of the commercial refrigeration 

equipment industry. Manufacturers stated that their industry has a high level of end-user 

specification and low production volumes compared to other industries, such as residential 

refrigeration. As a result, the strictest interpretations of the CC&E requirements could lead to 

hundreds of thousands of tests per company. Additional clarification of how basic models and 

AEDMs apply to the commercial refrigeration equipment industry would help manufacturers 

understand the testing investments that will be necessary. DOE is aware of the confusion and 

issued a proposed rulemaking for AEDMs on May 24, 2012 to address these concerns. 

12.3.3 Disproportionate Impact on Small Businesses

Manufacturers noted that small businesses will be disproportionately impacted when 

compared to larger businesses. One manufacturer indicated that small and large manufacturers of 

the same equipment tend to have similar numbers of basic models, but large manufacturers offer 

a broader suite of products based on those basic models and have higher sales. Therefore, small 

manufacturers will be at a disadvantage because they will need to spread both industry 

certification and conversion costs over a smaller number of shipments. 

Also, small manufacturers indicated they have fewer resources to manage CC&E 

requirements. As a result, they will be forced to focus on compliance rather than innovation. 

Small manufacturers believe that their large competitors will have greater resources to continue 

innovating while meeting amended energy conservation standards requirements. 

12.3.4 Potential Loss of Product Utility and Decrease in Food Safety

A majority of manufacturers expressed concern about the potential impact of energy 

conservation standards on product performance. Specifically, manufacturers serving the 

foodservice industry were concerned about the impacts on food safety, while manufacturers 

serving the food retail industry were concerned about the impacts on merchandising design.

12-6 
One manufacturer of commercial refrigeration equipment for the foodservice industry 

summarized the challenge of amended energy conservation standards as “the design trade-off 

between product price, energy efficiency, and food safety.” In the foodservice industry, 

refrigeration equipment must maintain safe food temperatures despite frequent door openings in 

challenging environments, such as kitchens with high temperatures and high humidity. The 

infiltration of warm, moist air places additional burden on the refrigeration equipment and 

increases energy usage. Manufacturers were concerned that more-efficient equipment would 

have trouble maintaining food safety in extreme, but not uncommon, conditions. 

Manufacturers in the food retail market design their equipment to optimally present 

merchandise. Some manufacturers were concerned that energy conservation standards would 

limit their ability to tailor their commercial refrigeration equipment for specific merchandise.

Specifically, manufacturers noted that the highly directional light from light-emitting diode 

(LED) bulbs could potentially provide lower quality lighting in certain display case applications 

where the product is presented in multiple layers, such as prepared food display cases. 

Additionally, manufacturers were concerned that higher efficiency designs could result in less 

desirable presentation for meats and increased icing on products. In general, more-efficient 

standards limit manufacturer options for optimizing the presentation features of equipment. Food 

retail customers such as supermarkets make purchasing decisions based on the various 

presentation features of commercial refrigeration equipment offered by different manufacturers. 

12.4 GRIM INPUTS AND ASSUMPTIONS

The GRIM serves as the main tool for assessing the impacts on industry due to amended 

energy conservation standards. DOE relies on several sources to obtain inputs for the GRIM. 

Data and assumptions from these sources are then fed into an accounting model that calculates 

the industry cash flow both with and without amended energy conservation standards. 

12.4.1 Overview of the GRIM

The basic structure of the GRIM, illustrated in Figure 12.4.1, is an annual cash flow 

analysis that uses manufacturer prices, manufacturing costs, shipments, and industry financial 

information as inputs, and accepts a set of regulatory conditions such as changes in costs, 

investments, and associated margins. The GRIM spreadsheet uses a number of inputs to arrive at 

a series of annual cash flows, beginning with the base year of the analysis, 2013, and continuing 

to 2046. The model calculates the INPV by summing the stream of annual discounted cash flows 

during this period and adding a discounted terminal value.6

12-7 
Figure 12.4.1 Using the GRIM to Calculate Cash Flow 

The GRIM projects cash flows using standard accounting principles and compares 

changes in INPV between the base-case scenario and the standards-case scenario induced by 

amended energy conservation standards. The difference in INPV between the base case and the 

standards case(s) represents the estimated financial impact of the amended energy conservation 

standard on manufacturers. Appendix 12A provides more technical details and user information 

for the GRIM.

12.4.2 Sources for GRIM Inputs

The GRIM uses several different sources for data inputs in determining industry cash 

flow. These sources include corporate annual reports, company profiles, census data, credit 

ratings, the shipments model, the engineering analysis, and the manufacturer interviews. 

12.4.2.1 Corporate Annual Reports

Corporate annual reports to the SEC (SEC 10-Ks) provided many of the initial financial 

inputs to the GRIM. These reports exist for publicly held companies and are freely available to 

the general public. DOE developed initial financial inputs to the GRIM by examining the annual 

SEC 10-K reports filed by publicly traded manufacturers of commercial refrigeration equipment. 

Since these companies do not provide detailed information about their individual product lines, 

DOE used the financial information for the entire set of companies as its initial estimates of the 

financial parameters in the GRIM analysis. These figures were later revised using feedback from 

interviews to be representative of manufacturing for each product grouping. DOE used corporate 

annual reports to derive the following initial inputs to the GRIM: 

• tax rate

• working capital

• SG&A

• R&D

• depreciation

• capital expenditures

• net PPE

12-8 
12.4.2.2 Standard and Poor’s Credit Ratings

S&P provides independent credit ratings, research, and financial information. DOE relied 

on S&P reports to determine the industry’s average cost of debt when calculating the cost of 

capital.

12.4.2.3 Shipment Model

The GRIM used shipment projections derived from DOE’s shipments model in the NIA. 

Chapter 9 of the TSD describes the methodology and analytical model DOE used to forecast 

shipments. 

12.4.2.4 Engineering Analysis 

The engineering analysis establishes the relationship between manufacturer selling price 

(MSP) and energy efficiency for the equipment covered in this rulemaking. DOE adopted a 

design option approach to develop cost-efficiency curves in its engineering analysis. DOE began 

its analysis by conducting industry research to select equipment classes to directly analyze, 

develop baseline unit specifications, and select representative commercial refrigeration 

equipment for further analysis. Next, DOE determined efficiency levels based on the design 

options applicable to the specific equipment studied and the maximum technologically feasible 

efficiency level for each equipment class modeled. To develop cost estimates, DOE conducted a 

price analysis, based upon physical teardowns of selected units, cost estimates from publicly 

available sources, and price quotes from manufacturers. DOE then developed a cost model to 

determine MPCs. By applying derived manufacturer markups to the MPC, DOE calculated the 

MSP and constructed industry cost-efficiency curves. See chapter 5 of the TSD for a complete 

discussion of the engineering analysis. 

12.4.2.5 Manufacturer Interviews

During the course of the MIA, DOE conducted interviews with a representative crosssection of manufacturers. DOE also interviewed manufacturers representing a significant portion 

of sales in every equipment class. During these discussions, DOE obtained information to 

determine and verify GRIM input assumptions in each industry. Key topics discussed during the 

interviews and reflected in the GRIM include:

• capital conversion costs (one-time investments in PPE);

• product conversion costs (one-time investments in research, product development, 

testing, and marketing);

• product cost structure, or the portion of the MPCs related to materials, labor, 

overhead, and depreciation costs; 

• MPCs estimated in the engineering analysis; and

• possible profitability impacts.

12-9 
12.4.3 Financial Parameters

Table 12.4.1 provides financial parameters for seven large companies engaged in 

manufacturing and selling commercial refrigeration equipment. The values listed are averages 

over a 7-year period (2004 to 2010).

Table 12.4.1 GRIM Financial Parameters Based on 2004–2010 Weighted Company 

Financial Data 

Parameter

IndustryWeighted 

Average

Manufacturers

A B C D E F G 

Tax Rate 

(% of Taxable Income) 25% 27.3% 21.4% 34.3% 16.2% 31.5% 30.3% 25.8%

Working Capital

(% of Revenue) 9.2% 8.1% 22.4% 10.1% -7.9% 16.6% 10% 16.2%

SG&A 

(% of Revenue) 13.1% 11.5% 11.1% 19.3% 15.2% 23.1% 15.3% 5.1%

R&D 

(% of Revenues) 1.6% 3.1% 1.1% 1.3% 1.6% 0.5% 1.9% 0.6%

Depreciation 

(% of Revenues) 2% 2.3% 2.1% 1.4% 2.5% 2.3% 2.9% 0.6%

Capital Expenditures 

(% of Revenues) 1.7% 1.9% 1.9% 1.8% 1.6% 1.5% 2.8% 0.5%

While most of these companies also manufacture products not covered by this 

rulemaking, DOE used these parameters as initial estimates. During interviews, manufacturers 

were asked to provide their own figures for the parameters listed in Table 12.4.1. Where 

applicable, DOE adjusted the parameters in the GRIM using manufacturer feedback and market 

share information. 

12.4.4 Corporate Discount Rate 

DOE used the weighted-average cost of capital (WACC) as the discount rate to calculate 

the INPV. A company’s assets are financed by a combination of debt and equity. The WACC is 

the total cost of debt and equity weighted by their respective proportions in the capital structure 

of the industry. DOE estimated the WACC for the commercial refrigeration equipment industry 

based on several representative companies, using the following formula: 

WACC = After-Tax Cost of Debt × (Debt Ratio) + Cost of Equity × (Equity Ratio) 

The cost of equity is the rate of return that equity investors (including, potentially, the 

company) expect to earn on a company’s stock. These expectations are reflected in the market 

price of the company’s stock. The Capital Asset Pricing Model (CAPM) provides one widely 

used means to estimate the cost of equity. According to the CAPM, the cost of equity (expected 

return) is:

Cost of Equity = Riskless Rate of Return + β × Risk Premium

12-10
Where:

Riskless Rate of Return = the rate of return on a “safe” benchmark investment, typically 

considered the short-term Treasury Bill (T-Bill) yield,

Risk Premium = the difference between the expected return on stocks and the riskless rate, and 

Beta (β) = the correlation between the movement in the price of the stock and that of the broader 

market. In this case, Beta equals one if the stock is perfectly correlated with the S&P 500 

market index. A Beta lower than one means the stock is less volatile than the market index.

DOE calculated that the industry average cost of equity for the commercial refrigeration

industry is 14.7 percent (Table 12.4.2). 

Table 12.4.2 Cost of Equity Calculation 

Parameter

IndustryWeighted 

Average

A B C D E F G 

(1) Average Beta 1.55 1.30 2.70 0.76 1.77 0.91 1.29 1.29

(2) Yield on 10-Year

(1928-2010) 5.23%

(3) Market Risk 

Premium 6.09% 

Cost of Equity 

(2)+[(1)*(3)] 14.7%

Equity/Total Capital 61.9% 69.0% 19.8% 65.0% 73.4% 67.3% 71.0% 71.7%

Bond ratings are a tool to measure default risk and arrive at a cost of debt. Each bond 

rating is associated with a particular spread. One way of estimating a company’s cost of debt is 

to treat it as a spread (usually expressed in basis points) over the risk-free rate. DOE used this 

method to calculate the cost of debt for seven public manufacturers by using S&P ratings and 

adding the relevant spread to the risk-free rate. 

In practice, investors use a variety of different maturity Treasury bonds to estimate the 

risk-free rate. DOE used the 10-year Treasury bond return because it captures long-term inflation 

expectations and is less volatile than short-term rates. The risk-free rate is estimated to be 

approximately 5.2 percent, which is the average 10-year Treasury bond return between 1928 and 

2010. 

For the cost of debt, S&P’s Credit Services provided the average spread of corporate 

bonds for the seven manufacturers between 2004 and 2010. DOE added the industry-weighted 

average spread to the average T-Bill yield over the same period. Since proceeds from debt 

issuance are tax deductible, DOE adjusted the gross cost of debt by the industry average tax rate 

to determine the net cost of debt for the industry. Table 12.4.3 presents the derivation of the cost 

of debt and the capital structure of the industry (i.e., the debt ratio (debt/total capital)).

12-11
Table 12.4.3 Cost of Debt Calculation 

Parameter

IndustryWeighted 

Average

A B C D E F G 

S&P Bond Rating AAA CC AAA A AAA AAA AAA

(1) Yield on 10-Year

(1928-2010) 5.23% 

(2) Gross Cost of Debt 6.9% 6.23% 8.98% 6.83% 6.83% 5.73% 6.83% 6.23%

(3) Tax Rate 25% 27.3% 21.4% 34.3% 16.2% 31.5% 30.3% 25.8%

Net Cost of Debt

(2) x [1-(3)] 5.2%

Debt/Total Capital 38.1% 31.0% 80.2% 35.0% 26.6% 32.7% 29.0% 28.3%

Using public information for these seven companies, the initial estimate for the industry’s 

WACC was approximately 11.1 percent. Subtracting an inflation rate of 3.09 percent over the 

analysis period used in the initial estimate, the inflation-adjusted WACC and the initial estimate 

of the discount rate used in the straw-man GRIM is 8 percent. DOE also asked for feedback on 

the discount rate during manufacturer interviews. Based on this feedback, DOE used a discount 

rate of 10 percent for the commercial refrigeration industry. 

12.4.5 Trial Standard Levels 

DOE developed a number of efficiency levels for each type of equipment class. TSLs 

were then developed by selecting likely groupings of efficiency levels for all equipment types. 

Table 12.4.4 presents the TSLs used for energy efficiency analysis in the GRIM.

12-12
Table 12.4.4 Trial Standard Levels for Energy Efficiency Analysis of Commercial 

Refrigeration Equipment

Equipment Class

Baseline TSL1 TSL2 TSL3 TSL4 TSL5

VOP.RC.M Level 1 Level 2 Level 3 Level 4 Level 5 Level 6

VOP.RC.L Level 1 Level 2 Level 3 Level 4 Level 4 Level 5

VOP.SC.M Level 1 Level 3 Level 4 Level 5 Level 6 Level 7

VCT.RC.M Level 1 Level 2 Level 3 Level 4 Level 6 Level 7

VCT.RC.L Level 1 Level 3 Level 4 Level 5 Level 5 Level 6

VCT.SC.M Level 1 Level 2 Level 3 Level 4 Level 7 Level 8

VCT.SC.L Level 1 Level 3 Level 4 Level 5 Level 7 Level 8

VCT.SC.I Level 1 Level 3 Level 5 Level 6 Level 6 Level 7

VCS.SC.M Level 1 Level 3 Level 5 Level 7 Level 7 Level 8

VCS.SC.L Level 1 Level 3 Level 5 Level 6 Level 7 Level 8

VCS.SC.I Level 1 Level 3 Level 5 Level 6 Level 6 Level 7

SVO.RC.M Level 1 Level 2 Level 3 Level 4 Level 5 Level 6

SVO.SC.M Level 1 Level 3 Level 4 Level 5 Level 6 Level 7

SOC.RC.M Level 1 Level 2 Level 3 Level 4 Level 6 Level 7

HZO.RC.M Level 1 Level 1 Level 1 Level 1 Level 1 Level 2

HZO.RC.L Level 1 Level 1 Level 1 Level 1 Level 1 Level 2

HZO.SC.M Level 1 Level 2 Level 2 Level 3 Level 4 Level 5

HZO.SC.L Level 1 Level 1 Level 1 Level 1 Level 1 Level 2

HCT.SC.M Level 1 Level 3 Level 5 Level 6 Level 7 Level 8

HCT.SC.L Level 1 Level 3 Level 4 Level 5 Level 7 Level 8

HCT.SC.I Level 1 Level 2 Level 3 Level 4 Level 4 Level 5

HCS.SC.M Level 1 Level 2 Level 3 Level 4 Level 5 Level 7

HCS.SC.L Level 1 Level 4 Level 5 Level 6 Level 6 Level 7

PD.SC.M Level 1 Level 2 Level 2 Level 3 Level 7 Level 8

SOC.SC.M Level 1 Level 3 Level 4 Level 5 Level 7 Level 8

12.4.6 NIA Shipments

The GRIM estimates manufacturer revenues based on total-unit-shipment forecasts and 

the distribution of these values by efficiency level. Changes in the efficiency mix of the shipped 

units for a given standards case are a key driver of manufacturer finances. For this analysis, the 

GRIM applied the NIA shipments forecasts.

As part of the shipments analysis, DOE estimated the base-case shipment distribution by 

efficiency level for each equipment class. In the standards case, DOE determined efficiency 

distributions for cases in which a potential standard applies for 2017 and beyond. DOE assumed 

that all shipments in the base case that did not meet the standard under consideration would meet 

the new standard in 2017 under a roll-up scenario. Customers in the base case who purchase 

units above the standard level are not affected as they are assumed to continue to purchase the 

same base-case unit in the standards case. 

See chapter 9 of the TSD for more information on the commercial refrigeration 

equipment standards-case shipments. 

12-13
12.4.7 Manufacturer Production Costs 

Changes in production costs affect revenues and gross profits. Products that are more 

efficient typically cost more to produce than baseline products (as shown in chapter 5 of the 

TSD). For the MIA, DOE used the MPCs derived in the engineering analysis. 

Manufacturing a higher efficiency product is typically more expensive than 

manufacturing a baseline product. MPCs increase at higher efficiency levels due to the use of 

more complex components, which are more costly than baseline components. These changes in 

MPCs can affect the revenues, gross margins, and cash flow of the industry, making these 

product cost data key GRIM inputs for DOE’s analysis. 

To calculate baseline MSP, DOE followed a three-step process. First, DOE derived 

MPCs from the engineering and teardown analyses. Second, DOE applied a manufacturer 

markup, which varies with the markup scenario (discussed in detail in section 12.4.9), to the 

MPCs. Third, shipping costs from the engineering analysis were added to the marked-up MPCs. 

Table 12.4.5 through Table 12.4.29 show the production cost estimates used in the GRIM 

for each analyzed equipment class.

Table 12.4.5 Manufacturer Production Cost Breakdown (2012$) for VOP.RC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $2,620.53 $510.43 $102.60 $139.14 $3,372.71 $252.30 1.42 $5,041.54 

EL 2 $2,652.21 $510.43 $102.60 $139.14 $3,404.38 $252.30 1.42 $5,086.52 

EL 3 $2,738.26 $510.43 $102.60 $139.14 $3,490.44 $252.30 1.42 $5,208.72 

EL 4 $3,455.00 $510.43 $102.60 $139.14 $4,207.18 $252.30 1.42 $6,226.49 

EL 5 $3,500.13 $510.43 $102.60 $139.14 $4,252.31 $252.30 1.42 $6,290.57 

EL 6 $5,336.12 $545.61 $102.60 $139.14 $6,123.48 $252.30 1.42 $8,947.63 

Table 12.4.6 Manufacturer Production Cost Breakdown (2012$) for VOP.RC.L

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $2,913.14 $510.45 $102.60 $139.70 $3,665.89 $252.30 1.42 $5,457.86 

EL 2 $2,956.38 $510.45 $102.60 $139.70 $3,709.13 $252.30 1.42 $5,519.26 

EL 3 $3,204.69 $510.45 $102.60 $139.70 $3,957.44 $252.30 1.42 $5,871.86 

EL 4 $3,254.74 $510.45 $102.60 $139.70 $4,007.48 $252.30 1.42 $5,942.92 

EL 5 $6,266.11 $553.25 $102.60 $139.70 $7,061.66 $252.30 1.42 $10,279.86 

Table 12.4.7 Manufacturer Production Cost Breakdown (2012$) for VOP.SC.M 

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $1,496.08 $197.23 $57.09 $65.64 $1,816.05 $68.90 1.42 $2,647.69 

EL 2 $1,506.99 $197.23 $57.09 $65.64 $1,826.96 $68.90 1.42 $2,663.18 

EL 3 $1,519.40 $197.23 $57.09 $65.64 $1,839.37 $68.90 1.42 $2,680.80 

EL 4 $1,545.77 $197.23 $57.09 $65.64 $1,865.74 $68.90 1.42 $2,718.25 

EL 5 $1,840.69 $197.23 $57.09 $65.64 $2,160.66 $68.90 1.42 $3,137.04 

EL 6 $1,870.96 $197.23 $57.09 $65.64 $2,190.93 $68.90 1.42 $3,180.03 

EL 7 $2,496.96 $209.43 $57.09 $65.64 $2,829.13 $68.90 1.42 $4,086.26 

12-14
Table 12.4.8 Manufacturer Production Cost Breakdown (2012$) for VCT.RC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $3,842.91 $589.50 $111.60 $138.04 $4,682.04 $235.07 1.42 $6,883.57 

EL 2 $3,857.78 $589.50 $111.60 $138.04 $4,696.91 $235.07 1.42 $6,904.68 

EL 3 $4,218.63 $589.50 $111.60 $138.04 $5,057.76 $235.07 1.42 $7,417.09 

EL 4 $4,309.11 $589.50 $111.60 $138.04 $5,148.24 $235.07 1.42 $7,545.57 

EL 5 $4,357.86 $589.50 $111.60 $138.04 $5,196.99 $235.07 1.42 $7,614.80 

EL 6 $4,374.96 $589.50 $111.60 $138.04 $5,214.09 $235.07 1.42 $7,639.08 

EL 7 $6,506.53 $630.30 $111.60 $138.04 $7,386.46 $235.07 1.42 $10,723.85 

Table 12.4.9 Manufacturer Production Cost Breakdown (2012$) for VCT.RC.L

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $4,525.20 $589.64 $111.60 $140.89 $5,367.33 $235.07 1.42 $7,856.68 

EL 2 $4,635.35 $589.64 $111.60 $140.89 $5,477.48 $235.07 1.42 $8,013.09 

EL 3 $4,725.84 $589.64 $111.60 $140.89 $5,567.96 $235.07 1.42 $8,141.58 

EL 4 $4,774.07 $589.64 $111.60 $140.89 $5,616.20 $235.07 1.42 $8,210.08 

EL 5 $4,804.51 $589.64 $111.60 $140.89 $5,646.64 $235.07 1.42 $8,253.30 

EL 6 $7,617.82 $629.64 $111.60 $140.89 $8,499.95 $235.07 1.42 $12,305.00 

Table 12.4.10 Manufacturer Production Cost Breakdown (2012$) for VCT.SC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $1,421.52 $190.33 $104.04 $72.72 $1,788.61 $61.81 1.42 $2,601.63 

EL 2 $1,450.36 $190.33 $104.04 $72.72 $1,817.45 $61.81 1.42 $2,642.59 

EL 3 $1,604.00 $190.33 $104.04 $72.72 $1,971.10 $61.81 1.42 $2,860.76 

EL 4 $1,694.48 $190.33 $104.04 $72.72 $2,061.58 $61.81 1.42 $2,989.25 

EL 5 $1,709.48 $190.33 $104.04 $72.72 $2,076.57 $61.81 1.42 $3,010.54 

EL 6 $1,741.30 $190.33 $104.04 $72.72 $2,108.40 $61.81 1.42 $3,055.73 

EL 7 $1,748.20 $190.33 $104.04 $72.72 $2,115.29 $61.81 1.42 $3,065.52 

EL 8 $2,500.75 $204.93 $104.04 $72.72 $2,882.44 $61.81 1.42 $4,154.88 

Table 12.4.11 Manufacturer Production Cost Breakdown (2012$) for VCT.SC.L

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $2,044.03 $216.14 $69.21 $69.83 $2,399.20 $61.81 1.42 $3,468.67 

EL 2 $2,096.67 $216.14 $69.21 $69.83 $2,451.85 $61.81 1.42 $3,543.43 

EL 3 $2,241.15 $216.14 $69.21 $69.83 $2,596.32 $61.81 1.42 $3,748.59 

EL 4 $2,253.06 $216.14 $69.21 $69.83 $2,608.23 $61.81 1.42 $3,765.49 

EL 5 $2,343.54 $216.14 $69.21 $69.83 $2,698.71 $61.81 1.42 $3,893.98 

EL 6 $2,352.85 $216.14 $69.21 $69.83 $2,708.02 $61.81 1.42 $3,907.19 

EL 7 $2,399.66 $216.14 $69.21 $69.83 $2,754.84 $61.81 1.42 $3,973.68 

EL 8 $3,416.49 $230.74 $69.21 $69.83 $3,786.27 $61.81 1.42 $5,438.31 

12-15
Table 12.4.12 Manufacturer Production Cost Breakdown (2012$) for VCT.SC.I

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $2,293.43 $215.88 $69.21 $70.65 $2,649.17 $64.85 1.42 $3,826.67 

EL 2 $2,346.13 $215.88 $69.21 $70.65 $2,701.87 $64.85 1.42 $3,901.50 

EL 3 $2,355.44 $215.88 $69.21 $70.65 $2,711.17 $64.85 1.42 $3,914.72 

EL 4 $2,445.92 $215.88 $69.21 $70.65 $2,801.66 $64.85 1.42 $4,043.20 

EL 5 $2,460.91 $215.88 $69.21 $70.65 $2,816.65 $64.85 1.42 $4,064.49 

EL 6 $2,493.25 $215.88 $69.21 $70.65 $2,848.99 $64.85 1.42 $4,110.41 

EL 7 $3,845.07 $231.28 $69.21 $70.65 $4,216.21 $64.85 1.42 $6,051.86 

Table 12.4.13 Manufacturer Production Cost Breakdown (2012$) for VCS.SC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $729.30 $216.69 $121.26 $83.07 $1,150.32 $60.79 1.42 $1,694.25 

EL 2 $757.39 $216.69 $121.26 $83.07 $1,178.41 $60.79 1.42 $1,734.13 

EL 3 $761.47 $216.69 $121.26 $83.07 $1,182.49 $60.79 1.42 $1,739.93 

EL 4 $764.30 $216.69 $121.26 $83.07 $1,185.31 $60.79 1.42 $1,743.94 

EL 5 $773.60 $216.69 $121.26 $83.07 $1,194.62 $60.79 1.42 $1,757.16 

EL 6 $788.60 $216.69 $121.26 $83.07 $1,209.61 $60.79 1.42 $1,778.45 

EL 7 $820.42 $216.69 $121.26 $83.07 $1,241.44 $60.79 1.42 $1,823.64 

EL 8 $1,572.97 $231.29 $121.26 $83.07 $2,008.59 $60.79 1.42 $2,912.99 

Table 12.4.14 Manufacturer Production Cost Breakdown (2012$) for VCS.SC.L

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $859.57 $216.70 $121.26 $83.68 $1,281.21 $60.79 1.42 $1,880.11 

EL 2 $892.47 $216.70 $121.26 $83.68 $1,314.12 $60.79 1.42 $1,926.84 

EL 3 $901.42 $216.70 $121.26 $83.68 $1,323.06 $60.79 1.42 $1,939.54 

EL 4 $906.69 $216.70 $121.26 $83.68 $1,328.33 $60.79 1.42 $1,947.02 

EL 5 $938.51 $216.70 $121.26 $83.68 $1,360.15 $60.79 1.42 $1,992.21 

EL 6 $947.82 $216.70 $121.26 $83.68 $1,369.46 $60.79 1.42 $2,005.42 

EL 7 $962.81 $216.70 $121.26 $83.68 $1,384.45 $60.79 1.42 $2,026.71 

EL 8 $1,979.64 $231.30 $121.26 $83.68 $2,415.88 $60.79 1.42 $3,491.34 

Table 12.4.15 Manufacturer Production Cost Breakdown (2012$) for VCS.SC.I

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $1,105.52 $216.95 $121.26 $86.48 $1,530.21 $64.85 1.42 $2,237.75 

EL 2 $1,105.84 $216.95 $121.26 $86.48 $1,530.53 $64.85 1.42 $2,238.20 

EL 3 $1,119.90 $216.95 $121.26 $86.48 $1,544.60 $64.85 1.42 $2,258.17 

EL 4 $1,129.21 $216.95 $121.26 $86.48 $1,553.90 $64.85 1.42 $2,271.39 

EL 5 $1,161.55 $216.95 $121.26 $86.48 $1,586.24 $64.85 1.42 $2,317.31 

EL 6 $1,176.54 $216.95 $121.26 $86.48 $1,601.24 $64.85 1.42 $2,338.60 

EL 7 $2,528.36 $232.35 $121.26 $86.48 $2,968.45 $64.85 1.42 $4,280.05 

12-16
Table 12.4.16 Manufacturer Production Cost Breakdown (2012$) for SVO.RC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $2,215.79 $476.62 $87.89 $120.46 $2,900.76 $139.83 1.42 $4,258.91 

EL 2 $2,222.72 $476.62 $87.89 $120.46 $2,907.69 $139.83 1.42 $4,268.75 

EL 3 $2,346.81 $476.62 $87.89 $120.46 $3,031.78 $139.83 1.42 $4,444.96 

EL 4 $2,893.83 $476.62 $87.89 $120.46 $3,578.80 $139.83 1.42 $5,221.73 

EL 5 $2,930.88 $476.62 $87.89 $120.46 $3,615.85 $139.83 1.42 $5,274.33 

EL 6 $4,108.57 $499.30 $87.89 $120.46 $4,816.22 $139.83 1.42 $6,978.85 

Table 12.4.17 Manufacturer Production Cost Breakdown (2012$) for SVO.SC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $1,167.10 $156.74 $55.37 $58.74 $1,437.95 $42.56 1.42 $2,084.45 

EL 2 $1,168.74 $156.74 $55.37 $58.74 $1,439.59 $42.56 1.42 $2,086.78 

EL 3 $1,210.10 $156.74 $55.37 $58.74 $1,480.96 $42.56 1.42 $2,145.51 

EL 4 $1,227.68 $156.74 $55.37 $58.74 $1,498.54 $42.56 1.42 $2,170.48 

EL 5 $1,468.19 $156.74 $55.37 $58.74 $1,739.04 $42.56 1.42 $2,512.00 

EL 6 $1,495.77 $156.74 $55.37 $58.74 $1,766.62 $42.56 1.42 $2,551.16 

EL 7 $1,822.77 $244.78 $55.37 $58.74 $2,181.67 $42.56 1.42 $3,140.52 

Table 12.4.18 Manufacturer Production Cost Breakdown (2012$) for SOC.RC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $4,189.91 $600.96 $96.63 $193.59 $5,081.10 $165.16 1.42 $7,380.32 

EL 2 $4,200.61 $600.96 $96.63 $193.59 $5,091.80 $165.16 1.42 $7,395.51 

EL 3 $4,220.23 $600.96 $96.63 $193.59 $5,111.42 $165.16 1.42 $7,423.38 

EL 4 $4,547.77 $600.96 $96.63 $193.59 $5,438.96 $165.16 1.42 $7,888.48 

EL 5 $4,581.09 $600.96 $96.63 $193.59 $5,472.28 $165.16 1.42 $7,935.80 

EL 6 $4,684.50 $600.96 $96.63 $193.59 $5,575.69 $165.16 1.42 $8,082.64 

EL 7 $5,558.96 $617.88 $96.63 $193.59 $6,467.08 $165.16 1.42 $9,348.41 

Table 12.4.19 Manufacturer Production Cost Breakdown (2012$) for HZO.RC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $2,221.78 $371.95 $75.48 $113.94 $2,783.15 $113.48 1.42 $4,065.56 

EL 2 $3,016.08 $390.61 $75.48 $113.94 $3,596.11 $113.48 1.42 $5,219.96 

Table 12.4.20 Manufacturer Production Cost Breakdown (2012$) for HZO.RC.L

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $2,639.12 $371.89 $75.48 $114.18 $3,200.67 $113.48 1.42 $4,658.43 

EL 2 $4,059.52 $399.89 $75.48 $114.18 $4,649.07 $113.48 1.42 $6,715.17 

Table 12.4.21 Manufacturer Production Cost Breakdown (2012$) for HZO.SC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $588.56 $76.15 $30.78 $26.06 $721.56 $20.26 1.42 $1,044.88 

EL 2 $589.63 $76.15 $30.78 $26.06 $722.63 $20.26 1.42 $1,046.40 

EL 3 $597.13 $76.15 $30.78 $26.06 $730.13 $20.26 1.42 $1,057.05 

EL 4 $626.50 $76.15 $30.78 $26.06 $759.49 $20.26 1.42 $1,098.74 

EL 5 $1,178.79 $86.95 $30.78 $26.06 $1,322.59 $20.26 1.42 $1,898.34 

12-17
Table 12.4.22 Manufacturer Production Cost Breakdown (2012$) for HZO.SC.L

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $1,259.84 $76.16 $30.78 $26.18 $1,392.97 $20.26 1.42 $1,998.28 

EL 2 $1,586.56 $86.56 $30.78 $26.18 $1,730.09 $20.26 1.42 $2,476.99 

Table 12.4.23 Manufacturer Production Cost Breakdown (2012$) for HCT.SC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $410.31 $100.63 $37.39 $26.57 $574.91 $20.26 1.42 $836.64 

EL 2 $412.91 $100.63 $37.39 $26.57 $577.51 $20.26 1.42 $840.33 

EL 3 $416.32 $100.63 $37.39 $26.57 $580.92 $20.26 1.42 $845.17 

EL 4 $420.46 $100.63 $37.39 $26.57 $585.06 $20.26 1.42 $851.04 

EL 5 $478.76 $100.63 $37.39 $26.57 $643.35 $20.26 1.42 $933.83 

EL 6 $487.54 $100.63 $37.39 $26.57 $652.14 $20.26 1.42 $946.31 

EL 7 $514.42 $100.63 $37.39 $26.57 $679.02 $20.26 1.42 $984.47 

EL 8 $864.03 $107.59 $37.39 $26.57 $1,035.59 $20.26 1.42 $1,490.80 

Table 12.4.24 Manufacturer Production Cost Breakdown (2012$) for HCT.SC.L

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $496.60 $100.64 $37.39 $26.80 $661.43 $20.26 1.42 $959.50 

EL 2 $501.30 $100.64 $37.39 $26.80 $666.13 $20.26 1.42 $966.17 

EL 3 $508.23 $100.64 $37.39 $26.80 $673.06 $20.26 1.42 $976.01 

EL 4 $566.52 $100.64 $37.39 $26.80 $731.35 $20.26 1.42 $1,058.79 

EL 5 $570.66 $100.64 $37.39 $26.80 $735.49 $20.26 1.42 $1,064.66 

EL 6 $579.45 $100.64 $37.39 $26.80 $744.28 $20.26 1.42 $1,077.14 

EL 7 $606.32 $100.64 $37.39 $26.80 $771.16 $20.26 1.42 $1,115.31 

EL 8 $1,081.70 $107.60 $37.39 $26.80 $1,253.50 $20.26 1.42 $1,800.23 

Table 12.4.25 Manufacturer Production Cost Breakdown (2012$) for HCT.SC.I

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $552.63 $100.07 $37.32 $26.50 $716.52 $18.24 1.42 $1,035.70 

EL 2 $554.11 $100.07 $37.32 $26.50 $718.00 $18.24 1.42 $1,037.80 

EL 3 $562.90 $100.07 $37.32 $26.50 $726.79 $18.24 1.42 $1,050.29 

EL 4 $590.04 $100.07 $37.32 $26.50 $753.93 $18.24 1.42 $1,088.82 

EL 5 $1,227.08 $107.43 $37.32 $26.50 $1,398.34 $18.24 1.42 $2,003.87 

Table 12.4.26 Manufacturer Production Cost Breakdown (2012$) for HCS.SC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $361.00 $87.08 $34.24 $26.80 $509.12 $23.30 1.42 $746.25 

EL 2 $361.84 $87.08 $34.24 $26.80 $509.96 $23.30 1.42 $747.45 

EL 3 $365.26 $87.08 $34.24 $26.80 $513.37 $23.30 1.42 $752.29 

EL 4 $369.39 $87.08 $34.24 $26.80 $517.51 $23.30 1.42 $758.17 

EL 5 $378.18 $87.08 $34.24 $26.80 $526.30 $23.30 1.42 $770.65 

EL 6 $404.12 $87.08 $34.24 $26.80 $552.24 $23.30 1.42 $807.48 

EL 7 $677.41 $92.58 $34.24 $26.80 $831.03 $23.30 1.42 $1,203.36 

12-18
Table 12.4.27 Manufacturer Production Cost Breakdown (2012$) for HCS.SC.L

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $364.49 $94.55 $34.31 $27.09 $520.44 $23.30 1.42 $762.33 

EL 2 $365.75 $94.55 $34.31 $27.09 $521.70 $23.30 1.42 $764.12 

EL 3 $369.06 $94.55 $34.31 $27.09 $525.01 $23.30 1.42 $768.82 

EL 4 $373.19 $94.55 $34.31 $27.09 $529.15 $23.30 1.42 $774.69 

EL 5 $381.98 $94.55 $34.31 $27.09 $537.94 $23.30 1.42 $787.18 

EL 6 $407.92 $94.55 $34.31 $27.09 $563.88 $23.30 1.42 $824.01 

EL 7 $780.74 $100.05 $34.31 $27.09 $942.20 $23.30 1.42 $1,361.22 

Table 12.4.28 Manufacturer Production Cost Breakdown (2012$) for PD.SC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $772.78 $149.87 $51.55 $37.11 $1,011.30 $37.49 1.42 $1,473.54 

EL 2 $804.69 $149.87 $51.55 $37.11 $1,043.21 $37.49 1.42 $1,518.85 

EL 3 $876.86 $149.87 $51.55 $37.11 $1,115.38 $37.49 1.42 $1,621.33 

EL 4 $881.51 $149.87 $51.55 $37.11 $1,120.03 $37.49 1.42 $1,627.94 

EL 5 $889.01 $149.87 $51.55 $37.11 $1,127.53 $37.49 1.42 $1,638.58 

EL 6 $979.49 $149.87 $51.55 $37.11 $1,218.01 $37.49 1.42 $1,767.07 

EL 7 $1,013.54 $149.87 $51.55 $37.11 $1,252.07 $37.49 1.42 $1,815.43 

EL 8 $1,603.53 $161.39 $51.55 $37.11 $1,853.57 $37.49 1.42 $2,669.56 

Table 12.4.29 Manufacturer Production Cost Breakdown (2012$) for SOC.SC.M

Efficiency

Level Material Labor Depreciation Overhead MPC Shipping Markup MSP

EL 1 $4,583.36 $609.52 $105.61 $205.18 $5,503.68 $165.16 1.42 $7,980.38 

EL 2 $4,646.89 $609.52 $105.61 $205.18 $5,567.21 $165.16 1.42 $8,070.59 

EL 3 $4,675.82 $609.52 $105.61 $205.18 $5,596.14 $165.16 1.42 $8,111.67 

EL 4 $4,690.81 $609.52 $105.61 $205.18 $5,611.13 $165.16 1.42 $8,132.96 

EL 5 $5,018.35 $609.52 $105.61 $205.18 $5,938.67 $165.16 1.42 $8,598.07 

EL 6 $5,051.68 $609.52 $105.61 $205.18 $5,971.99 $165.16 1.42 $8,645.38 

EL 7 $5,155.08 $609.52 $105.61 $205.18 $6,075.40 $165.16 1.42 $8,792.22 

EL 8 $6,046.47 $609.52 $105.61 $205.18 $6,966.79 $165.16 1.42 $10,057.99 

12.4.8 Conversion Costs 

Amended energy conservation standards typically cause manufacturers to incur one-time 

conversion costs to bring their production facilities and product designs into compliance with 

new regulations. For the MIA, DOE classified these one-time conversion costs into two major 

groups: capital conversion costs and product conversion costs. Capital conversion costs are onetime investments in PPE to adapt or change existing production facilities in order to fabricate and 

assemble new product designs that comply with amended energy conservation standards. Product 

conversion costs are one-time investments in research, development, industry certification testing

(i.e., Underwriters Laboratories (UL) certifications and NSF International certifications), 

marketing, and other costs to make product designs comply with amended energy conservation 

standards. DOE based its estimates of the conversion costs for each efficiency level on 

information obtained from manufacturer interviews and the design pathways analyzed in the 

engineering analysis. 

12-19
12.4.8.1 Capital Conversion Costs 

To evaluate the level of capital conversion expenditures manufacturers would likely incur 

to comply with energy conservation standards, DOE used the manufacturer interviews to gather 

data on the level of capital investment required at each efficiency level. DOE validated 

manufacturer comments through estimates of capital expenditure requirements derived from the 

product teardown analysis and engineering model described in chapter 5 of the TSD.

In interviews, manufacturers noted that most of the design options being considered are 

offered as options today. As a result, many of the design options do not incur capital 

expenditures for new tooling or equipment. Overall, capital conversion costs are primarily driven 

by changes in equipment insulation. An increase in insulation thickness by one-half-inch was 

determined to require new foaming fixtures in most facilities. Additionally, manufacturers noted 

that changes in foam thickness could lead to foam reformulations. A move to vacuum insulated 

panels (VIPs) could require significant changes in production processes and, based on 

manufacturer input, was estimated to require capital expenditures that are double those of an 

increase in foam insulation thickness. Expected capital conversion costs for each TSL are listed 

in Table 12.4.30. 

Table 12.4.30 Industry Cumulative Capital Conversion Cost

TSL Capital Conversion Cost

$millions

TSL 1 0

TSL 2 18.4

TSL 3 42.9

TSL 4 76.3

TSL 5 252.4

At TSL 1, DOE does not expect any capital conversion costs. All design options 

considered at this level are currently offered by manufacturers today. 

At TSL 2, capital conversion costs ramp up to $18.4 million for the industry. These costs 

are associated with the production line updates and new tooling necessary to produce half-inch 

thicker insulation in the VCT.RC.L, VCS.SC.L, and VCS.SC.I equipment classes. A majority of 

the cost is for new foaming fixtures that can accommodate thicker foam insulation in cases.

From TSL 2 to TSL 4, the capital conversion costs for the industry steadily increase as 

more equipment classes will likely use thicker cases to meet the standard. At TSL 3, 8 equipment 

classes are expected to use thicker or improved insulation. At TSL 4, 18 of the 24 equipment 

classes are expected to use thicker or improved insulation. The tooling associated with thicker 

cases accounts for the increasing capital conversion costs. 

At TSL 5, DOE models a large increase in conversion costs. This increase is associated 

with the incorporation of VIPs into production units. Though the industry does not use VIPs 

today, feedback from manufacturers indicates that VIP equipment, new jigs, and additional 

equipment for structural members may be required to meet the standard. 

12-20
12.4.8.2 Product Conversion Costs

DOE assessed the product conversion costs at each level by integrating data from 

quantitative and qualitative sources. DOE considered feedback regarding the potential costs of 

each efficiency level from multiple manufacturers to determine conversion costs such as R&D 

expenditures and certification costs. Manufacturer numbers were aggregated to better reflect the 

industry as a whole and to protect confidential information. 

Based on both manufacturer feedback and the engineering analysis, many design options 

were considered to be component swaps, which required substitutions of new components but 

did not require product redesigns. Lighting changes, fan motor substitutions, compressor 

upgrades, and night curtain retrofits were understood to not require significant product 

development investments. However, changes in evaporator coil, condenser coil, and insulation 

were modeled to incur development expenses. Additionally, DOE included the cost of industry 

certifications in the product conversion costs. Expected product conversion costs for each TSL 

are listed in Table 12.4.31. 

Table 12.4.31 Industry Cumulative Product Conversion Cost

TSL Product Conversion Cost 

$millions

TSL 1 8.0

TSL 2 9.9

TSL 3 10.5

TSL 4 11.2

TSL 5 68.0

At TSL 1, product conversion costs may be incurred by the industry in order to 

incorporate the new components in existing designs. This product conversion cost is associated 

with sourcing, component testing, and writing the specifications for the new components. At 

TSL 2, product conversion costs ramp up as manufacturers make more significant changes that 

require engineering investments and could necessitate new industry certification, such as UL 

testing and NSF testing. These testing costs and redesign costs continue to ramp up at TSL 3 and 

TSL 4. At TSL 5, conversion costs increase significantly as the industry must develop VIP 

technology for use in commercial refrigeration equipment. All design and engineering resources 

would go into VIP panel development. 

12.4.9 Markup Scenarios

DOE used multiple standards-case markup scenarios to represent the uncertainty about 

the impacts of energy conservation standards on prices and profitability. In the base case, DOE 

used the same markups applied in the engineering analysis. In the standards case, DOE modeled 

two markup scenarios to represent the uncertainty about the potential impacts on prices and 

profitability following the implementation of amended energy conservation standards: (1) a 

preservation of gross margin percentage scenario and (2) a preservation of earnings before 

interest and tax (EBIT) scenario. These scenarios lead to different markup values that, when 

applied to the inputted MPCs, result in varying revenue and cash flow impacts. 

12-21
12.4.9.1 Preservation of Gross Margin Percentage Scenario

Under the preservation of gross margin percentage scenario, DOE applied a single 

uniform “gross margin percentage” markup across all efficiency levels. As production costs 

increase with efficiency, this scenario implies that the absolute dollar markup will increase as 

well. DOE assumed the non-production cost markup—which includes SG&A expenses, R&D

expenses, interest, and profit— to be 1.42 for the commercial refrigeration industry. This markup 

is equal to the one DOE assumed in the engineering analysis. Manufacturers indicated that it is 

optimistic to assume that, as their MPCs increase in response to an energy conservation standard, 

they would be able to maintain the same gross margin percentage markup. Therefore, DOE 

assumes that this scenario represents an upper bound to industry profitability under an energy 

conservation standard. 

12.4.9.2 Preservation of Operating Profit Scenario

During interviews, multiple manufacturers expressed concern that the higher production 

costs could harm profitability. Because of market characteristics, several manufacturers 

suggested that the additional costs of higher minimum efficiency products could not be fully 

passed through to customers. Incorporating this feedback, DOE modeled the preservation of 

operating profit scenario.

In the preservation of operating profit scenario, manufacturer markups are set so that 

operating profit one year after the compliance date of the new energy conservation standards is 

the same as in the base case. Under this scenario, as the cost of production and the cost of sales 

increase, manufacturers are generally required to reduce their markups to a level that maintains 

base-case operating profit. The implicit assumption behind this markup scenario is that the 

industry can only maintain its operating profit in absolute dollars after the standard. Operating 

margin in percentage terms is squeezed (reduced) between the base case and standards case.

12.4.10 Experience Curve Rates

For this rulemaking, DOE applied experience curve multipliers to both the base case and 

standards case MSP forecasts in the GRIM. The experience curve applied to the GRIM is 

identical to the experience curve applied to the NIA for this rule. A detailed discussion of the 

experience curve modeling is provided in Appendix 10B of the TSD. 

12.4.11 Light-Emitting Diode Price Projections

In an effort to capture the anticipated cost reduction of LED components in the 

rulemaking analyses, DOE incorporated price projections from its Solid State Lighting program 

into its MPC values for the primary equipment classes. As discussed in chapter 5 of the TSD, the 

price projections for LED case lighting were based on projections in the DOE’s Solid State 

Lighting Program’s 2012 report, Energy Savings Potential of Solid State Lighting in General 

Illumination Applications 2010 to 2030a (“the energy savings report”). The price projection 

a Navigant Consulting. "Energy Savings Potential of Solid-State Lighting in General Illumination Applications 2010 

to 2030." Building Technologies Program, Office of Energy Efficiency and Renewable Energy, U.S. Department of 

Energy, Feb. 2010. Web. Apr. 2013.

12-22

 
results in the component cost of LEDs decreasing over the analysis period for both the base case 

and standards case analysis in the GRIM. 

12.5 INDUSTRY FINANCIAL IMPACTS

Using the inputs and scenarios described in the previous sections, the GRIM estimated 

indicators of financial impacts on the commercial refrigeration industry. The following sections 

detail additional inputs and assumptions for commercial refrigeration equipment. The main 

results of the MIA are also reported in this section. The MIA consists of two key financial 

metrics: INPV and annual cash flows. 

12.5.1 Introduction

The INPV measures the industry value and is used in the MIA to compare the economic 

impacts of different TSLs in the standards case. The INPV is different from DOE’s net present 

value, which is applied to the U.S. economy. The INPV is the sum of all net cash flows 

discounted at the industry’s cost of capital or discount rate. The GRIM for this rulemaking 

estimates cash flows from 2013 to 2046, the same analysis period used in the NIA (chapter 10 of 

the TSD). This timeframe models both the short-term impacts on the industry from the base year

of the analysis until the compliance date (2013 until 2017) and a long-term assessment over the 

30-year analysis period used in the NIA (2017–2046).

In the MIA, DOE compares the INPV of the base case (no amended energy conservation 

standards) to that of each TSL. The difference between the base case and a standards case INPV 

is an estimate of the economic impacts the TSL would have on the industry. The markup 

scenarios are described in greater detail in section 12.4.9. 

While INPV is useful for evaluating the long-term effects of amended energy 

conservation standards, short-term changes in cash flow are also important indicators of the 

industry’s financial situation. For example, a large investment over one or two years could strain 

the industry’s access to capital. Consequently, the sharp drop in financial performance could 

cause investors to flee, even though recovery may be possible. Thus, a short-term disturbance 

can have long-term effects that the INPV cannot capture. To provide an idea of the behavior of 

short-term annual net cash flows, Figure 12.5.1 and Figure 12.5.2 present the annual net cash 

flows through 2027. 

Annual cash flows are discounted to the base year, 2013. After the standards 

announcement date (i.e., the publication date of the final rule), industry cash flows begin to 

decline as companies use their financial resources to prepare for the amended energy 

conservation standard. Cash flows between the announcement date and the compliance date are 

driven by the level of conversion costs and the proportion of these investments spent every year. 

The more stringent the amended energy conservation standard, the greater the impact on industry 

cash flows in the years leading up to the compliance date, as product conversion costs lower cash 

inflows from operations and capital conversion costs increase cash outflows for capital 

expenditures. 

Free cash flow in the year the amended energy conservation standards take effect is 

driven by two competing factors. In addition to capital and product conversion costs, amended 

12-23
energy conservation standards could create stranded assets, i.e., tooling and equipment that could 

have been used longer if the energy conservation standard had not made them obsolete. In this 

year, manufacturers write down the remaining book value of existing tooling and equipment 

whose value is affected by the amended energy conservation standard. This one-time write-down 

acts as a tax shield that alleviates decreases in cash flow from operations in the year of the writedown. In this year, there is also an increase in working capital that reduces cash flow from 

operations. A large increase in working capital is needed due to more costly production 

components and materials, higher inventory carrying to sell more expensive products, and higher 

accounts receivable for more expensive products. Depending on these two competing factors, 

cash flow can be either positively or negatively affected in the year the standard takes effect. 

12.5.2 Commercial Refrigeration Industry Financial Impacts

Table 12.5.1 and Table 12.5.2 provide the INPV estimates for commercial refrigeration 

equipment for the two markup scenarios. Figure 12.5.1 and Figure 12.5.2 present the net annual 

cash flows for the two scenarios. 

Table 12.5.1 Preservation of Gross Margin Percentage Scenario Changes in INPV for 

Commercial Refrigeration Equipment

Units Base 

Case

Trial Standard Level

1 2 3 4 5

INPV 2012$ M 1,162.0 1,158.4 1,146.9 1,135.7 1,116.1 1,136.5 

Change in 

INPV

2012$ M - (3.6) (15.2) (26.3) (45.9) (25.5)

(%) - (0.31) (1.30) (2.26) (3.95) (2.20)

* Numbers in parentheses indicate negative numbers. 

Table 12.5.2 Preservation of Operating Profit Scenario Changes in INPV for Commercial 

Refrigeration Equipment

Units Base 

Case

Trial Standard Level

1 2 3 4 5

INPV 2012$ M 1,162.0 1,155.2 1,135.6 1,102.8 1,069.4 646.0 

Change in 

INPV

2012$ M - (6.8) (26.4) (59.2) (92.6) (516.0)

(%) - (0.58) (2.27) (5.09) (7.97) (44.41)

* Numbers in parentheses indicate negative numbers. 

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Figure 12.5.1 Annual Industry Net Cash Flows for Commercial Refrigeration Equipment

(Preservation of Gross Margin Percentage Markup Scenario) 

-$100.00

-$50.00

$0.00

$50.00

$100.00

$150.00

$200.00

2012 $Millions

Year

Base Case TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

12-25
Figure 12.5.2 Annual Industry Net Cash Flows for Commercial Refrigeration Equipment

(Preservation of Operating Profit Markup Scenario)

12.6 IMPACTS ON SMALL BUSINESS MANUFACTURERS

DOE conducted a more focused inquiry of the companies that could be small business 

manufacturers of products covered by this rulemaking. For the category “Air-Conditioning and 

Warm Air Heating Equipment and Commercial and Industrial Refrigeration Equipment

Manufacturing,” the SBA has set a size threshold of 750 employees or less for an entity to be 

considered as a small business. During its market survey, DOE used all available public 

information to identify potential small manufacturers. DOE’s research involved industry trade 

association membership directories (including AHRI, NAFEM, and NSF International), product 

databases (e.g., Federal Trade Commission (FTC), The Thomas Register, California Energy 

Commission (CEC), and ENERGY STAR® databases), individual company websites, and 

market research tools (e.g., Hoovers reports) to create a comprehensive list of companies that 

manufacture or sell products covered by this rulemaking. DOE also asked stakeholders and 

industry representatives if they were aware of any other small manufacturers during 

manufacturer interviews and at previous DOE public meetings. DOE reviewed publicly available 

data and contacted select companies on its list, as necessary, to determine whether they met the 

SBA’s definition of a small business manufacturer of covered commercial refrigeration 

equipment. DOE screened out companies that did not offer products covered by this rulemaking, 

did not meet the definition of a “small business,” or are foreign owned and operated. 

DOE identified 45 manufacturers in the commercial refrigeration industry, and 32 of the 

manufacturers identified are believed to be small businesses. As part of the MIA, the Department 

-$60.00

-$40.00

-$20.00

$0.00

$20.00

$40.00

$60.00

$80.00

$100.00

$120.00

2012 $Millions

Year

Base Case TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

12-26
interviewed eight commercial refrigeration equipment manufacturers, including four small 

business operations. Based on the large number of small commercial refrigeration equipment 

manufacturers and the potential scope of the impact, DOE could not certify that the proposed 

standards would not have a significant impact on a significant number of small businesses with 

respect to the commercial refrigeration industry. 

DOE recognizes that amended energy conservation standards can potentially have 

disproportionate impacts on small businesses. Larger manufacturers could have a competitive 

advantage due to their size and ability to access capital that may not be available to small 

businesses. Larger businesses also have larger production volumes over which to spread costs. 

DOE provides additional analysis in section VI.B, “Review under the Regulatory Flexibility 

Act,” in the notice of proposed rulemaking. 

12.7 OTHER IMPACTS

12.7.1 Employment

To quantitatively assess the impacts of amended energy conservation standards on 

employment, DOE used the GRIM to estimate the domestic labor expenditures and number of 

employees in the base case and at each TSL from 2013 through 2046. DOE used statistical data 

from the U.S. Census Bureau’s 2011 Annual Survey of Manufacturers (ASM), the results of the 

engineering analysis, the commercial refrigeration equipment shipments forecast, and interviews 

with manufacturers to determine the inputs necessary to calculate industry-wide labor 

expenditures and domestic employment levels. Labor expenditures related to manufacturing of 

the product are a function of the labor intensity of the product, the sales volume, and an 

assumption that wages remain fixed in real terms over time. The total labor expenditures in each 

year are calculated by multiplying the MPCs by the labor percentage of MPCs. 

The total labor expenditures in the GRIM were then converted to domestic production 

employment levels by dividing production labor expenditures by the annual payment per 

production worker (production worker hours times the labor rate found in the U.S. Census 

Bureau’s 2011 ASM). The estimates of production workers in this section cover workers, 

including line supervisors who are directly involved in fabricating and assembling a product 

within the original equipment manufacturer facility. Workers performing services that are closely 

associated with production operations, such as materials handling tasks using forklifts, are also 

included as production labor. DOE’s estimates only account for production workers who 

manufacture the specific products covered by this rulemaking. 

12-27 
Table 12.7.1 Potential Changes in the Number of Commercial Refrigeration Equipment

Production Workers in 2017 

Trial Standard Level

 Base 

Case 1 2 3 4 5 

Total Number of Domestic 

Production Workers in 

2017 (assuming no 

changes in production 

locations)

3,672 3,672 3,672 3,672 3,672 3,925 

Range of Potential 

Changes in Domestic 

Production Workers in 

2017*

- -3,672 to 0 -3,672 to 0 -3,672 to 0 -3,672 to 0 -3,672 to 253

* DOE presents a range of potential employment impacts, where the lower range represents the scenario in which all domestic 

manufacturers move production to other countries.

The employment impacts shown in Table 12.7.1 represent the potential production 

employment changes that could result following the compliance date of an amended energy 

conservation standard. The upper end of the results in the table estimates the maximum increase 

in the number of production workers after the implementation of new energy conservation 

standards and it assumes that manufacturers would continue to produce the same scope of 

covered products within the United States. The lower end of the range indicates the total number 

of U.S. production workers in the industry who could lose their jobs if all existing production 

were moved outside of the United States. Though manufacturers stated in interviews that shifts 

in production to foreign countries is unlikely, the industry did not provide enough information 

for DOE fully quantify what percentage of the industry would move production at each evaluated 

standard level. 

The majority of design options analyzed in the engineering analysis require 

manufacturers to purchase more-efficient components from suppliers. These components do not 

require significant additional labor to assemble. A key component of a commercial refrigeration 

equipment unit that requires fabrication labor by the commercial refrigeration equipment 

manufacturer is the shell of the unit, which needs to be formed and foamed in. Although this 

activity may require new production equipment if thicker insulation is needed to meet higher 

efficiency levels, the process of building the panels would essentially remain the same, and 

therefore require no additional labor costs. As a result, labor needs are not expected to increase 

as the amended energy conservation standard increases from baseline to TSL 4. 

At TSL 5, the introduction of hybrid vacuum insulation panels may lead to higher labor 

requirements. In general, the production and handling of hybrid VIPs will require more labor 

than the production of standard panels. This is due to the delicate nature of VIPs and the 

additional labor necessary to embed them into a hybrid panel. The additional labor and handling 

associated with hybrid panels account for the increase in labor at the max-tech trial standard 

level. 

DOE notes that the employment impacts discussed here are independent of the 

employment impacts from the broader U.S. economy, which are documented in chapter 15 of the 

TSD. 

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12.7.2 Production Capacity 

According to the majority of commercial refrigeration equipment manufacturers 

interviewed, amended energy conservation standards will not significantly affect manufacturers’ 

production capacities. Any necessary redesign of commercial refrigeration equipment will not 

change the fundamental assembly of the equipment, but manufacturers do anticipate some 

potential for minor changes to tooling. The most significant of these would come as a result of 

any redesigns performed to accommodate additional foam insulation thickness. Additionally, 

most of the design options being evaluated are available on the market as product options today. 

Thus, DOE believe manufacturers will be able to maintain manufacturing capacity levels and 

continue to meet market demand under new energy conservation standards. 

12.7.3 Cumulative Regulatory Burden 

While any one regulation may not impose a significant burden on manufacturers, the 

combined effects of several impending regulations may have serious consequences for some 

manufacturers, groups of manufacturers, or an entire industry. Assessing the impact of a single 

regulation may overlook this cumulative regulatory burden. For the cumulative regulatory 

burden analysis, DOE looks at other significant product-specific regulations that could affect 

commercial refrigeration equipment manufacturers. In addition to the amended energy 

conservation regulations on commercial refrigeration equipment, several other Federal and State 

regulations apply to these products and other equipment produced by the same manufacturers. 

Companies that produce a wide range of regulated products may be faced with more 

capital and product development expenditures than competitors with a narrower scope of 

products. Regulatory burdens can prompt companies to exit the market or reduce their product 

offerings, potentially reducing competition. Smaller companies in particular can be 

disproportionately affected by regulatory costs since these companies have lower sales volumes 

over which they can amortize the costs of meeting new regulations. A proposed standard is not 

economically justified if it contributes to an unacceptable level of cumulative regulatory burden. 

12.7.3.1 DOE Regulations for Other Products Produced by Commercial 

Refrigeration Equipment Manufacturers

In addition to the amended energy conservation standards on commercial refrigeration 

equipment, other Federal regulations and pending regulations may apply to other products 

produced by the same manufacturers. The 2009 energy conservation standard final rule for 

commercial refrigeration equipment and the upcoming walk-in cooler and freezer energy 

conservation standard rulemaking are regulatory standards that could also affect manufacturers 

of commercial refrigeration in the years leading up to and after the compliance date of amended 

energy conservation standards for these products. 

2009 Commercial Refrigeration Equipment Energy Conservation Standard 

Rulemaking 

During interviews, some manufacturers commented on the burden of complying with a 

new set of standards for commercial refrigeration when the first set of standards was only 

recently announced in 2009 (with a compliance date of 2012). As a result, they must begin their 

12-29
transition to the new proposed standards when they have just begun to comply with the previous 

standards. Based on the MIA from the 2009 rulemaking, total conversion costs for the 

commercial refrigeration equipment industry would be $111.6 million, which would all be 

incurred in the years between the announcement date (2009) and the compliance date (2012). 

Total conversion costs expected for the current rulemaking at the proposed TSL are 

$87.5 million, which would also be incurred in the years between the announcement date (2014) 

and the compliance date (2017). Therefore, the commercial refrigeration equipment industry 

would need to make continuous investments to cover conversion costs of around $199 million 

from 2009 to 2017. 

Walk-in Cooler and Freezer Energy Conservation Standard Rulemaking 

Another DOE rulemaking that may have a significant impact on commercial refrigeration 

equipment manufacturers is the walk-in cooler and freezer rulemaking, which will have a 

compliance date of 2017. Nine commercial refrigeration equipment manufacturers also produce 

walk-ins, and therefore they must comply with two rulemakings that follow similar timelines. 

These manufacturers will incur conversion costs for both products at around the same time, 

which could be a significant strain on resources. 

12.7.3.2 Other DOE and Federal Actions Affecting the Commercial Refrigeration 

Equipment Industry

Certification, Compliance, and Enforcement Rule 

Many manufacturers have expressed concerns about the CC&E March 2011 final rule, 

which allows DOE to enforce the energy and water conservation standards for covered products 

and equipment, and provides for more accurate, comprehensive information about the energy and 

water use characteristics of products sold in the United States. The rule revises former

certification regulations so that the Department has the information it needs to ensure that 

regulated products sold in the United States comply with the law. According to the rule, 

manufacturers of covered consumer products and commercial and industrial equipment must 

certify on an annual basis, by means of a compliance statement and a certification report, that 

each of their basic models meets its applicable energy conservation, water conservation, and/or 

design standard before it is distributed within the United States. For purposes of certification 

testing, the determination that a basic model complies with the applicable conservation standard 

must be based on sampling procedures, which currently require that a minimum of two units of a 

basic model must be tested in order to certify that the model is compliant (unless the productspecific regulations specify otherwise). 76 FR 12422 (March 7, 2011). 

However, DOE recognizes that even a sample size of two units may not be practical for 

certain commercial refrigeration equipment manufacturers who build one-of-a kind customized 

units. Therefore, DOE is conducting a rulemaking to expand AEDM coverage and has issued a 

proposed rule to permit the application of AEDMs for commercial refrigeration equipment. An 

AEDM is a computer modeling or mathematical tool that predicts the performance of non-tested 

basic models. If finalized, the proposal would enable commercial refrigeration equipment

manufacturers to certify all of their basic models based on testing of a minimum of one unit from 

five distinct basic models. DOE believes that the allowance of AEDM application would reduce 

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manufacturer test burden for products that are highly customized, such as commercial 

refrigeration equipment. More information can be found at 

http://www1.eere.energy.gov/buildings/appliance_standards/implement_cert_and_enforce.html. 

EPA and ENERGY STAR

Some stakeholders have also expressed concern regarding potential conflicts with other 

certification programs, in particular U.S. Environmental Protection Agency (EPA) ENERGY 

STAR requirements. 

DOE realizes that the cumulative effect of several regulations on an industry may 

significantly increase the burden faced by manufacturers who need to comply with multiple 

regulations and certification programs from different organizations and levels of government. 

However, DOE notes that certain standards, such as ENERGY STAR, are optional for 

manufacturers.

12.7.3.3 Other Regulations That Could Impact Commercial Refrigeration 

Equipment Manufacturers

State Regulations

California Code of Regulations, Title 24

According to the latest California Code of Regulations, Title 24, part 6,

7 any appliance 

for which there is a California standard established in the Appliance Efficiency Regulations may 

be installed only if the manufacturer has certified to the Commission, as specified in those 

regulations, that the appliance complies with the applicable standard for that appliance. The 

Commission’s appliance efficiency regulations require that the maximum daily energy 

consumption (in kilowatt-hours) for commercial refrigerators manufactured on or after January 

1, 2010 does not exceed the following: 

• refrigerators with solid doors: 0.10V + 2.04 

• refrigerators with transparent doors: 0.12V + 3.34 

• freezers with solid doors: 0.40V + 1.38 

• freezers with transparent doors: 0.75V + 4.10 

• refrigerator/freezers with solid doors: the greater of 0.27AV–0.71 or 0.70 

• refrigerators with self-condensing unit designed for pull-down temperature 

applications: 0.126V + 3.51 

Since these standards are identical to the ones prescribed in the Energy Policy Act of 

2005 (EPACT 2005) and the efficiency levels set by the current rulemaking will either exceed or 

be equivalent to the EPACT 2005 levels, DOE does not expect the Title 24 regulations to create 

a cumulative regulatory burden on manufacturers. California has started a rulemaking proceeding 

to adopt changes to the building energy efficiency standards contained in the California Code of 

Regulations, Title 24, part 6. The proposed amended standards from this rulemaking will be 

adopted in 2014. More information can be found at: 

http://www.energy.ca.gov/title24/2013standards/rulemaking/index.html. 

12-31
Refrigerant Management Program

The California Air Resources Board (CARB) is currently limiting the in-state use of high 

global warming potential (GWP) refrigerants in non-residential refrigeration systems through its 

Refrigerant Management Program, effective January 1, 2011. According to this new regulation, 

facilities with refrigeration systems that have a refrigerant capacity exceeding 50 pounds must 

repair leaks within 14 days of detection, maintain on-site records of all leak repairs, and keep 

receipts of all refrigerant purchases. The regulation applies to any person or company that 

installs, services, or disposes of appliances with high-GWP refrigerants. Refrigeration systems 

with refrigerant capacity exceeding 50 pounds typically belong to food retail operations with 

remote condensing racks that store refrigerant serving multiple commercial refrigeration 

equipment units within a business. However, commercial refrigeration equipment units in food 

retail are usually installed and serviced by refrigeration contractors, not manufacturers. As a 

result, although these CARB regulations do apply to refrigeration technicians and owners of 

facilities with refrigeration systems, they are unlikely to be a regulatory burden for commercial 

refrigeration manufacturers.

12.8 CONCLUSION

The following section summarizes the impacts for the scenarios DOE believes are most 

likely to capture the range of impacts on commercial refrigeration equipment manufacturers as a 

result of amended energy conservation standards. DOE also notes that while these scenarios 

bound the range of most plausible impacts on manufacturers, there potentially could be 

circumstances that cause manufacturers to experience impacts outside of this range. 

For this rulemaking, TSLs are defined as shown in Table 12.8.1. 

12-32
Table 12.8.1 TSLs for the Commercial Refrigeration Equipment Rulemaking

Equipment Class

Baseline TSL1 TSL2 TSL3 TSL4 TSL5

VOP.RC.M Level 1 Level 2 Level 3 Level 4 Level 5 Level 6

VOP.RC.L Level 1 Level 2 Level 3 Level 4 Level 4 Level 5

VOP.SC.M Level 1 Level 3 Level 4 Level 5 Level 6 Level 7

VCT.RC.M Level 1 Level 2 Level 3 Level 4 Level 6 Level 7

VCT.RC.L Level 1 Level 3 Level 4 Level 5 Level 5 Level 6

VCT.SC.M Level 1 Level 2 Level 3 Level 4 Level 7 Level 8

VCT.SC.L Level 1 Level 3 Level 4 Level 5 Level 7 Level 8

VCT.SC.I Level 1 Level 3 Level 5 Level 6 Level 6 Level 7

VCS.SC.M Level 1 Level 3 Level 5 Level 7 Level 7 Level 8

VCS.SC.L Level 1 Level 3 Level 5 Level 6 Level 7 Level 8

VCS.SC.I Level 1 Level 3 Level 5 Level 6 Level 6 Level 7

SVO.RC.M Level 1 Level 2 Level 3 Level 4 Level 5 Level 6

SVO.SC.M Level 1 Level 3 Level 4 Level 5 Level 6 Level 7

SOC.RC.M Level 1 Level 2 Level 3 Level 4 Level 6 Level 7

HZO.RC.M Level 1 Level 1 Level 1 Level 1 Level 1 Level 2

HZO.RC.L Level 1 Level 1 Level 1 Level 1 Level 1 Level 2

HZO.SC.M Level 1 Level 2 Level 2 Level 3 Level 4 Level 5

HZO.SC.L Level 1 Level 1 Level 1 Level 1 Level 1 Level 2

HCT.SC.M Level 1 Level 3 Level 5 Level 6 Level 7 Level 8

HCT.SC.L Level 1 Level 3 Level 4 Level 5 Level 7 Level 8

HCT.SC.I Level 1 Level 2 Level 3 Level 4 Level 4 Level 5

HCS.SC.M Level 1 Level 2 Level 3 Level 4 Level 5 Level 7

HCS.SC.L Level 1 Level 4 Level 5 Level 6 Level 6 Level 7

PD.SC.M Level 1 Level 2 Level 2 Level 3 Level 7 Level 8

At TSL 1, DOE estimates impacts on INPV for commercial refrigeration equipment 

manufacturers to range from -$6.8 million to -$3.6 million, or a change in INPV of -0.58 percent 

to -0.31 percent. At this potential standard level, industry free cash flow is estimated to decrease 

by approximately 2.85 percent to $89.6 million, compared to the base-case value of $92.2 

million in the year before the compliance date (2016).

The INPV impacts at TSL 1 are relatively minor because DOE anticipates no capital 

conversion costs and very low product conversion costs. No capital conversion costs are 

expected because DOE anticipates that manufacturers would be able to make simple component 

swaps to meet the efficiency levels for each equipment class at this TSL. Low product 

conversion costs are expected for R&D to incorporate the new components into existing designs. 

Under the preservation of gross margin percentage markup scenario, impacts on 

manufacturers are marginally negative because while manufacturers can maintain their gross 

margin percentages, they also incur conversion costs that slightly reduce the higher profits that 

they gain from increasing their selling prices to accommodate higher production costs. However, 

the effects of these conversion costs are more apparent in the preservation of operating profit 

markup scenario because manufacturers earn the same operating profit at TSL 1 as they do in the 

base case. 

At TSL 2, DOE estimates impacts on INPV for commercial refrigeration equipment 

manufacturers to range from -$26.4 million to -$15.2 million, or a change in INPV of -2.27 

12-33
percent to -1.30 percent. At this potential standard level, industry free cash flow is estimated to 

decrease by approximately 12.48 percent to $80.7 million, compared to the base-case value of 

$92.2 million in the year before the compliance date (2016).

Although DOE continues to expect mild impacts on the industry at TSL 2, capital 

conversion costs do arise for a few of the equipment classes. Most of the costs are accounted for 

by the potential need for a half-inch increase in the thickness of foam insulation for the 

VCT.RC.L, VCS.SC.L, and VCS.SC.I equipment classes. In addition, product conversion costs 

will also slightly increase as design options that require new UL or NSF certification are 

incorporated.

The changes in INPV under both the preservation of gross margin percentage markup 

scenario and the preservation of operating profit markup scenario are due to the same underlying 

factors as those in TSL 1. However, the negative impacts are slightly higher due to the 

introduction of possible capital conversion costs for certain equipment classes in the commercial 

refrigeration equipment industry. 

At TSL 3, DOE estimates impacts on INPV for commercial refrigeration equipment 

manufacturers to range from -$59.2 million to -$26.3 million, or a change in INPV of -5.09 

percent to -2.26 percent. At this potential standard level, industry free cash flow is estimated to 

decrease by approximately 24.65 percent to $69.5 million, compared to the base-case value of 

$92.2 million in the year before the compliance date (2016).

DOE expects slightly higher conversion costs at TSL 3 due to the possible need for 

additional foam insulation for high-volume products, such as VCS.SC.M, which accounts for 

approximately 27 percent of total shipments, and for VCS.SC.L, which accounts for 

approximately 16 percent. In total, DOE expects 8 of the 24 equipment classes to require new 

production equipment due to higher standards at this level. 

The changes in INPV under both the preservation of gross margin percentage markup 

scenario and the preservation of operating profit markup scenario are due to the same underlying 

factors as those in TSL 1 and TSL 2. However, the negative impacts are higher due to the 

increase in capital conversion costs for high-volume equipment classes. 

At TSL 4, DOE estimates impacts on INPV for commercial refrigeration equipment 

manufacturers to range from -$92.6 million to -$45.9 million, or a change in INPV of -7.97 

percent to -3.95 percent. At this proposed standard level, industry free cash flow is estimated to 

decrease by approximately 41.19 percent to $54.2 million, compared to the base-case value of 

$92.2 million in the year before the compliance date (2016).

The drop in INPV at TSL 4 is primarily driven by continued increases in capital 

conversion costs, in particular the need for new tooling to accommodate additional foam 

insulation. At TSL 4, DOE expects 18 of the 24 equipment classes to require new production 

equipment for foam insulation due to higher standards. 

The changes in INPV under both the preservation of gross margin percentage markup 

scenario and the preservation of operating profit markup scenario are due to the same underlying 

12-34
factors as those in TSL 1, TSL 2, and TSL 3. However, the negative impacts are again higher due 

to the increase in capital conversion costs for the majority of equipment classes. 

At TSL 5, DOE estimates impacts on INPV for commercial refrigeration equipment 

manufacturers to range from -$516.0 million to -$25.5 million, or a change in INPV of -44.41 

percent to 2.20 percent. At this potential standard level, industry free cash flow is estimated to 

decrease by approximately 147.31 percent to -$43.6 million, compared to the base-case value of 

$92.2 million in the year before the compliance date (2016).

A substantial increase in conversion costs is expected at TSL 5 due to the possible need 

for VIP technology. VIPs are not currently used by any commercial refrigeration equipment

manufacturers and the production of VIPs would require processes different from those used to 

produce standard foam panels. Therefore, high R&D investments may be necessary to redesign 

commercial refrigeration equipment cases. It is possible that substantial new equipment would be 

necessary to produce VIPs for commercial refrigeration equipment applications. Furthermore, 

current panel production equipment that cannot be used to produce VIPs would be retired before 

it reaches the end of its useful life and would become a stranded asset. 

The changes in INPV under both the preservation of gross margin percentage markup 

scenario and the preservation of operating profit markup scenario are much greater at TSL 5 due 

to the very high capital conversion costs that would be required for the industry to transition to 

the use of VIPs. 

12-35
REFERENCES

1. U.S. Securities and Exchange Commission. Annual 10-K Reports. Various Years. (Last 

accessed October 22, 2011.) <www.sec.gov> 

2. Standard and Poor’s Financial Services LLC. Company Credit Ratings, Various 

Companies. (Last accessed October 22, 2011.) <www2.standardandpoors.com> 

3. Hoovers Inc. Company Profiles. Various Companies. (Last accessed October 22, 2011.) 

<www.hoovers.com/> 

4. U.S. Census Bureau. 2011 Annual Survey of Manufacturers. 2012. (Last accessed 

December 20, 2012.) < http://factfinder2.census.gov/faces/tableservices/jsf/pages/

productview.xhtml?pid=ASM_2011_31GS101&prodType=table >

5. U.S. Small Business Association. Table of Small Business Size Standards. 2007. (Last 

accessed November 22, 2011.) <www.sba.gov/content/table-small-business-sizestandards> 

6. McKinsey & Company, Inc. Valuation: Measuring and Managing the Value of Companies, 

3rd Edition, Copeland, Koller, Murrin. New York: John Wiley & Sons, 2000.

7. California Energy Commission. California’s Energy Efficiency Standards for Residential 

and Nonresidential Buildings: 2008. 2011. (Last accessed October 21, 2011.) 

<www.energy.ca.gov/title24/>

12-36
APPENDIX 12A. GOVERNMENT REGULATORY IMPACT MODEL (GRIM)

OVERVIEW

TABLE OF CONTENTS

12A.1 INTRODUCTION AND PURPOSE .......................................................................... 12A-1

12A.2 MODEL DESCRIPTION ........................................................................................... 12A-1

LIST OF TABLES

Table 12A.2.1 Detailed Cash Flow Example.......................................................................... 12A-4

12A-i 
APPENDIX 12A. GOVERNMENT REGULATORY IMPACT MODEL (GRIM) 

OVERVIEW

12A.1 INTRODUCTION AND PURPOSE

The purpose of the Government Regulatory Impact Model (GRIM) is to help quantify the 

impacts of energy conservation standards and other regulations on manufacturers. The basic 

mode of analysis is to estimate the change in the value of the industry or manufacturers(s) 

following a regulation or a series of regulations. The model structure also allows an analysis of 

multiple products with regulations taking effect over a period of time, and of multiple regulations 

on the same products. 

Industry net present value is defined, for the purpose of this analysis, as the discounted 

sum of industry free cash flows plus a discounted terminal value. The model calculates the actual 

cash flows by year and then determines the present value of those cash flows both without an 

energy conservation standard (i.e., the base case) and under different trial standard levels (i.e., 

the standards case).

Output from the model consists of summary financial metrics, graphs of major variables, 

and, when appropriate, access to the complete cash flow calculation.

12A.2 MODEL DESCRIPTION

The basic structure of the GRIM is a standard annual cash flow analysis that uses 

manufacturer selling prices, manufacturing costs, a shipments forecast, and financial parameters 

as inputs and accepts a set of regulatory conditions as changes in costs and investments. The cash 

flow analysis is separated into two major blocks: income and cash flow. The income calculation 

determines net operating profit after taxes. The cash flow calculation converts net operating 

profit after taxes into an annual cash flow by including investment and non-cash items. Below 

are definitions of listed items on the printout of the output sheet of the GRIM. 

(1) Unit Sales: Total annual shipments for the industry were obtained from the National Impact 

Analysis Spreadsheet. 

(2) Revenues: Annual revenues – computed by multiplying products’ unit prices at each 

efficiency level by the appropriate manufacturer markup. 

(3) Labor: The portion of cost of goods sold (COGS) that includes direct labor, commissions, 

dismissal pay, bonuses, vacation, sick leave, social security contributions, fringe, and 

assembly labor up-time. 

(4) Material: The portion of COGS that includes materials. 

(5) Overhead: The portion of COGS that includes indirect labor, indirect material, energy use, 

maintenance, depreciation, property taxes, and insurance related to assets. While included 

in overhead, the depreciation is shown as a separate line item. 

12A-1 
(6) Depreciation: The portion of overhead that includes an allowance for the total amount of 

fixed assets used to produce that one unit. Annual depreciation is computed as a percentage 

of COGS. While included in overhead, the depreciation is shown as a separate line item. 

(7) Stranded Assets: In the year the standard becomes effective, a one-time write-off of 

stranded assets is accounted for. 

(8) Standard SG&A: Selling, general, and administrative costs are computed as a percentage of 

Revenues (2). 

(9) R&D: GRIM separately accounts for ordinary research and development (R&D) as a 

percentage of Revenues (2). 

(10) Product Conversion Costs: Product conversion costs are one-time investments in research, 

development, testing, marketing, and other costs focused on making product’s designs 

comply with the new energy conservation standard. The GRIM allocates these costs over 

the period between the standard’s announcement and compliance dates. 

(11) Earnings Before Interest and Taxes (EBIT): Includes profits before deductions for interest 

paid and taxes. 

(12) EBIT as a Percentage of Sales (EBIT/Revenues): GRIM calculates EBIT as a percentage 

of sales to compare with the industry’s average reported in financial statements. 

(13) Taxes: Taxes on EBIT (11) are calculated by multiplying the tax rate contained in Major 

Assumptions by EBIT (11). 

(14) Net Operating Profits After Taxes (NOPAT): Computed by subtracting Cost of Goods 

Sold ((3) to (6)), SG&A (8), R&D (9), Product Conversion Costs (10), and Taxes (13)

from Revenues (2). 

(15) NOPAT repeated: NOPAT is repeated in the Statement of Cash Flows. 

(16) Depreciation repeated: Depreciation and Stranded Assets are added back in the Statement 

of Cash Flows because they are non-cash expenses. 

(17) Change in Working Capital: Change in cash tied up in accounts receivable, inventory, and 

other cash investments necessary to support operations is calculated by multiplying 

working capital (as a percentage of revenues) by the change in annual revenues. 

(18) Cash Flow From Operations: Calculated by taking NOPAT (15), adding back non-cash 

items such as a Depreciation (16), and subtracting the Change in Working Capital (17). 

(19) Ordinary Capital Expenditures: Ordinary investments in property, plant, and equipment to 

maintain and replace existing production assets, computed as a percentage of Revenues (2). 

(20) Capital Conversion Costs: Capital conversion costs are one-time investments in property, 

plant, and equipment to adapt or change existing production facilities so that new product 

12A-2 
designs can be fabricated and assembled under the new regulation. The GRIM allocates 

these costs over the period between the standard’s announcement and compliance dates. 

(21) Capital Investment: Total investments in property, plant, and equipment are computed by 

adding Ordinary Capital Expenditures (19) and Capital Conversion Costs (20). 

(22) Free Cash Flow: Annual cash flow from operations and investments; computed by 

subtracting Capital Investment (21) from Cash Flow from Operations (18). 

(23) Terminal Value: Estimate of the continuing value of the industry after the analysis period. 

Computed by growing the Free Cash Flow at the beginning of 2047 at a constant rate in 

perpetuity. 

(24) Present Value Factor: Factor used to calculate an estimate of the present value of an 

amount to be received in the future. 

(25) Discounted Cash Flow: Free Cash Flows (22) multiplied by the Present Value Factor 

(24). For the end of 2046, the discounted cash flow includes the discounted Terminal Value 

(23).

(26) Industry Value thru the end of 2046: The sum of Discounted Cash Flows (25). 

12A-3 
Table 12A.2.1 Detailed Cash Flow Example 

12A-4 
CHAPTER 13. EMISSIONS ANALYSIS

TABLE OF CONTENTS

13.1 INTRODUCTION ............................................................................................................ 13-1

13.2 AIR QUALITY REGULATION AND EMISSIONS IMPACTS .................................... 13-1

13.3 POWER SECTOR EMISSIONS FACTORS ................................................................... 13-3

13.4 UPSTREAM AND GREENHOUSE GAS EMISSIONS FACTORS .............................. 13-3

13.5 EMISSIONS IMPACT RESULTS ................................................................................... 13-4

REFERENCES .......................................................................................................................... 13-9

LIST OF TABLES

Table 13.3.1 Power Plant Emissions Factors ............................................................................. 13-3

Table 13.4.1 Electricity Upstream Emissions Factors ............................................................... 13-4

Table 13.5.1 Cumulative Emissions Reduction for Potential Standards for Commercial 

Refrigeration Equipment .................................................................................... 13-5

LIST OF FIGURES

Figure 13.5.1 Commercial Refrigeration Equipment: CO2 Total Emissions Reduction ........... 13-5

Figure 13.5.2 Commercial Refrigeration Equipment: SO2 Total Emissions Reduction ............ 13-6

Figure 13.5.3 Commercial Refrigeration Equipment: NOx Total Emissions Reduction ........... 13-6

Figure 13.5.4 Commercial Refrigeration Equipment: Hg Total Emissions Reduction ............. 13-7

Figure 13.5.5 Commercial Refrigeration Equipment: N2O Total Emissions Reduction ........... 13-7

Figure 13.5.6 Commercial Refrigeration Equipment: CH4 Total Emissions Reduction ........... 13-8

13-i 
CHAPTER 13. EMISSIONS ANALYSIS

13.1 INTRODUCTION

The emissions analysis consists of two components. The first component estimates the 

effect of potential energy conservation standards on power sector and site combustion emissions 

of carbon dioxide (CO2), nitrogen oxides (NOx), sulfur dioxide (SO2), and mercury (Hg). The 

second component estimates the impacts of a potential standard on emissions of two additional 

greenhouse gases, methane (CH4) and nitrous oxide (N2O), as well as the reductions to emissions 

of all species due to “upstream” activities in the fuel production chain. These upstream activities 

comprise extraction, processing, and transporting fuels to the site of combustion. The associated 

emissions are referred to as upstream emissions. Together, these emissions account for the fullfuel-cycle (FFC), in accordance with the U.S. Department of Energy’s (DOE’s) FFC Statement 

of Policy. 76 FR 51282 (Aug. 18, 2011), as amended at 77 FR 49701 (Aug. 17, 2012). 

The analysis of power sector emissions uses marginal emissions intensity factors derived 

from runs of DOE’s National Energy Modeling System – Building Technologies (NEMS-BT) 

model, described in chapter 14. DOE used the version of NEMS based on the Annual Energy 

Outlook 2013 (AEO2013).1 Each annual version of NEMS incorporates the projected impacts of 

existing air quality regulations on emissions. AEO2013 generally represents current Federal and 

State legislation and final implementation regulations in place as of the end of December 2012. 

Site emissions of CO2 and NOX are estimated using emissions intensity factors from a 

publication of the Environmental Protection Agency (EPA).2

Combustion emissions of CH4 and N2O are estimated using emissions intensity factors 

published by the U.S. Environmental Protection Agency (EPA), GHG Emissions Factors Hub.a

The FFC upstream emissions are estimated based on the methodology developed by Coughlin 

(2013).3

 The upstream emissions include both emissions from fuel combustion during extraction, 

processing, and transportation of fuel, and “fugitive” emissions (direct leakage to the 

atmosphere) of CH4 and CO2. 

The emissions intensity factors are expressed in terms of physical units per megawatthours (MWh) or million British thermal units (MMBtu) of site energy savings. Total emissions 

reductions are estimated using the energy savings calculated in the national impact analysis 

(chapter 10). 

13.2 AIR QUALITY REGULATION AND EMISSIONS IMPACTS

SO2 emissions from affected electric generating units (EGUs) are subject to nationwide 

and regional emissions cap and trading programs. Title IV of the Clean Air Act sets an annual 

emissions cap on SO2 for affected EGUs in the 48 contiguous States and the District of Columbia 

(D.C.). SO2 emissions from 28 eastern States and D.C. were also limited under the Clean Air 

Interstate Rule (CAIR), which created an allowance-based trading program that that operates 

along with the Title IV program in those States and D.C. 70 FR 25162 (May 12, 2005). CAIR 

was remanded to EPA by the U.S. Court of Appeals for the District of Columbia Circuit (D.C. 

a www.epa.gov/climateleadership/guidance/ghg-emissions.html

13-1 

 
Circuit), but parts of it remained in effect. See North Carolina v. EPA, 550 F.3d 1176 (D.C. Cir. 

2008); North Carolina v. EPA, 531 F.3d 896 (D.C. Cir. 2008). On July 6, 2011, EPA issued a 

replacement for CAIR, the Cross-State Air Pollution Rule (CSAPR). 76 FR 48208 (Aug. 8, 

2011). On August 21, 2012, the D.C. Circuit issued a decision to vacate CSAPR. See EME 

Homer City Generation, LP v. EPA, 696 F.3d 7, 38 (D.C. Cir. 2012). The court ordered EPA to 

continue administering CAIR. The AEO2013 emissions factors used for today’s notice of 

proposed rulemaking assume that CAIR remains a binding regulation through 2040. 

The attainment of emissions caps is typically flexible among affected EGUs and is 

enforced through the use of emissions allowances and tradable permits. Under existing EPA 

regulations, any excess SO2 emissions allowances resulting from the lower electricity demand 

caused by the imposition of an efficiency standard could be used to permit offsetting increases in 

SO2 emissions by any regulated EGU. In past rulemakings, DOE recognized that there was

uncertainty about the effects of efficiency standards on SO2 emissions covered by the existing 

cap-and-trade system, but it concluded that no reductions in power sector emissions would occur 

for SO2 as a result of standards. 

Beginning in 2015, however, SO2 emissions will fall as a result of the Mercury and Air 

Toxics Standards (MATS) for power plants, which were announced by EPA on December 21, 

2011. 77 FR 9304 (Feb. 16, 2012).b In the final MATS rule, EPA established a standard for 

hydrogen chloride as a surrogate for acid gas hazardous air pollutants (HAP), and also 

established a standard for SO2 (a non-HAP acid gas) as an alternative equivalent surrogate 

standard for acid gas HAP. The same controls are used to reduce HAP and non-HAP acid gas; 

thus, SO2 emissions will be reduced as a result of the control technologies installed on coal-fired 

power plants to comply with the MATS requirements for acid gas. AEO2013 assumes that, in 

order to continue operating, coal plants must have either flue gas desulfurization or dry sorbent 

injection systems installed by 2015. Both technologies, which are used to reduce acid gas 

emissions, also reduce SO2 emissions. Under the MATS, NEMS shows a reduction in SO2

emissions when electricity demand decreases (e.g., as a result of energy efficiency standards). 

Emissions will be far below the cap that would be established by CAIR, so it is unlikely that 

excess SO2 emissions allowances resulting from the lower electricity demand would be needed 

or used to permit offsetting increases in SO2 emissions by any regulated EGU. Therefore, DOE 

believes that efficiency standards will reduce SO2 emissions in 2015 and beyond. 

CAIR established a cap on NOx emissions in 28 eastern States and the District of 

Columbia. Energy conservation standards are expected to have little effect on NOx emissions in 

those States covered by CAIR because excess NOx emissions allowances resulting from the 

lower electricity demand could be used to permit offsetting increases in NOx emissions.

However, standards would be expected to reduce NOx emissions in the States not affected by the 

caps, so DOE estimated NOx emissions reductions from potential standards for those States. 

The MATS limit mercury emissions from power plants, but they do not include emissions 

caps and, as such, DOE’s energy conservation standards would likely reduce Hg emissions. DOE

b On July 20, 2012, EPA announced a partial stay, for a limited duration, of the effectiveness of national new source 

emission standards for hazardous air pollutants from coal- and oil-fired electric utility steam generating units. 

<www.epa.gov/airquality/powerplanttoxics/pdfs/20120727staynotice.pdf> 

13-2 

 
estimated mercury emissions reductions using the NEMS-BT based on AEO2013, which 

incorporates the MATS. 

13.3 POWER SECTOR EMISSIONS FACTORS

The analysis of power sector emissions uses marginal emissions intensity factors derived 

from runs of DOE’s NEMS-BT model, using the version updated to the AEO2013. To model the 

impact of a standard, DOE inputs a reduction to annual energy demand for the corresponding end 

use in the appropriate start year. The NEMS-BT model is run with the decremented energy 

demand to determine the modified build-out of capacity, fuel use, and power sector emissions. A 

marginal emissions intensity factor is defined by dividing the reduction in the total emissions of 

a given pollutant by the reduction in total generation (in billion kilowatt-hours). DOE uses the 

site energy savings multiplied by a transmission and distribution (T&D) loss factor to estimate 

the reduction in generation for each trial standard level (TSL). Details on the approach used may 

be found in Coughlin (2013).3 

Table 13.3.1 presents the average power plant emissions factors for selected years. These 

power plant emissions factors are derived from the emissions factors of the plant types used to 

supply electricity to buildings. DOE used the commercial refrigeration end use load shape. The 

average factors for each year take into account the projected shares of each of the sources in total 

electricity generation. 

The power plant emissions factor for NOx is an average for the entire U.S. The marginal 

calculation based on the NEMS-BT model accounts for the fact that NOx emissions are capped in 

some States. 

Table 13.3.1 Power Plant Emissions Factors 

Unit 2017 2020 2025 2030 2035 2040

CO2 kg/MWh 598 598 563 514 452 305

SO2 g/MWh 572 572 704 708 364 461

NOx g/MWh 394 394 394 303 215 191

Hg g/MWh 0.0014 0.0014 0.0005 0.0009 0.0005 0.0007

N2O g/MWh 7.0 7.2 7.2 7.1 7.1 6.9

CH4 g/MWh 49 50 50 50 49 48

13.4 UPSTREAM AND GREENHOUSE GAS EMISSIONS FACTORS

The upstream emissions accounting uses the same approach as the upstream energy 

accounting described in appendix 10B. See also Coughlin (2013).3 When demand for a particular 

fuel is reduced, there is a corresponding reduction in the emissions from combustion of that fuel 

at either the building site or the power plant. The associated reduction in energy use for upstream 

activities leads to further reductions in emissions. These upstream emissions are defined to 

include the combustion emissions from the fuel used upstream, the fugitive emissions associated 

with the fuel used upstream, and the fugitive emissions associated with the fuel used on site. 

Fugitive emissions of CO2 occur during oil and gas production, but are small relative to 

combustion emissions. They comprise about 2.5 percent of total CO2 emissions for natural gas 

and 1.7 percent for petroleum fuels. Fugitive emissions of methane occur during oil, gas, and 

13-3 
coal production. Combustion emissions of CH4 are very small, while fugitive emissions 

(particularly for gas production) may be relatively large. Hence, fugitive emissions make up over 

99 percent of total methane emissions for natural gas, about 95 percent for coal, and 93 percent

for petroleum fuels. 

Upstream emissions factors account for both fugitive emissions and combustion 

emissions in extraction, processing, and transport of primary fuels. For ease of application in its 

analysis, DOE developed all of the emissions factors using site (point of use) energy savings in 

the denominator. Table 13.4.1 presents the electricity upstream emissions factors for selected 

years. The caps that apply to power sector NOx emissions do not apply to upstream combustion 

sources. 

Table 13.4.1 Electricity Upstream Emissions Factors

Unit 2015 2020 2025 2030 2035 2040

CO2 kg/MWh 28.1 27.3 26.9 26.8 26.9 26.3

SO2 g/MWh 10.2 5.3 5.3 5.2 5.2 5.1

NOx g/MWh 355 340 334 333 336 329

Hg g/MWh 0.00006 0.00001 0.00001 0.00001 0.00001 0.00001

N2O g/MWh 0.26 0.25 0.25 0.25 0.24 0.24

CH4 g/MWh 2,083 2,025 2,008 2,025 2,057 1,999

13.5 EMISSIONS IMPACT RESULTS

Table 13.5.1 presents the estimated cumulative emissions reductions for the lifetime of 

equipment sold in 2017-2046 for each TSL. 

13-4 
Table 13.5.1 Cumulative Emissions Reduction for Potential Standards for Commercial 

Refrigeration Equipment

Trial Standard Level

1 2 3 4 5

Power Sector Emissions

 CO2 (million metric tons) 12.22 21.83 47.55 51.77 66.05

 NOx (thousand tons) 9.05 16.18 35.23 38.36 48.93

 Hg (tons) 0.03 0.05 0.10 0.11 0.14

 N2O (thousand tons) 0.26 0.47 1.02 1.11 1.42

 CH4 (thousand tons) 1.53 2.73 5.95 6.48 8.27

 SO2 (thousand tons) 16.39 29.28 63.78 69.43 88.58

Upstream Emissions

 CO2 (million metric tons) 0.73 1.31 2.85 3.10 3.96

 NOx (thousand tons) 10.08 18.01 39.23 42.71 54.49

 Hg (tons) 0.000 0.001 0.002 0.002 0.002

 N2O (thousand tons) 0.01 0.01 0.03 0.03 0.04

 CH4 (thousand tons) 61.23 109.39 238.27 259.41 330.92

 SO2 (thousand tons) 0.16 0.28 0.61 0.67 0.85

Total Emissions

 CO2 (million metric tons) 12.95 23.14 50.41 54.88 70.01

 NOx (thousand tons) 19.14 34.19 74.46 81.07 103.42

 Hg (tons) 0.03 0.05 0.10 0.11 0.14

 N2O (thousand tons) 0.27 0.48 1.05 1.15 1.46

 CH4 (thousand tons) 62.76 112.13 244.22 265.89 339.19

 SO2 (thousand tons) 16.55 29.56 64.39 70.10 89.43

Figure 13.5.1 through Figure 13.5.6 show the annual reductions for total emissions for 

each type of emission from each TSL. The reductions reflect the lifetime impacts of equipment 

sold in 2017-2046. 

Figure 13.5.1 Commercial Refrigeration Equipment: CO2 Total Emissions Reduction 

0.0

500.0

1000.0

1500.0

2000.0

2500.0

3000.0

3500.0

201720222027203220372042204720522057

kt

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

13-5 
Figure 13.5.2 Commercial Refrigeration Equipment: SO2 Total Emissions Reduction 

Figure 13.5.3 Commercial Refrigeration Equipment: NOx Total Emissions Reduction 

0.0

500.0

1000.0

1500.0

2000.0

2500.0

3000.0

3500.0

4000.0

201720222027203220372042204720522057

ton

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

0.0

500.0

1000.0

1500.0

2000.0

2500.0

3000.0

3500.0

4000.0

4500.0

5000.0

201720222027203220372042204720522057

ton

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

13-6 
Figure 13.5.4 Commercial Refrigeration Equipment: Hg Total Emissions Reduction 

Figure 13.5.5 Commercial Refrigeration Equipment: N2O Total Emissions Reduction 

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

201720222027203220372042204720522057

ton

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

201720222027203220372042204720522057

ton

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

13-7 
Figure 13.5.6 Commercial Refrigeration Equipment: CH4 Total Emissions Reduction 

0.0

2000.0

4000.0

6000.0

8000.0

10000.0

12000.0

14000.0

16000.0

201720222027203220372042204720522057

ton

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

13-8 
REFERENCES

1. U.S. Energy Information Administration. Annual Energy Outlook 2013 with Projections 

to 2040. 2013. <www.eia.gov/forecasts/aeo/> 

2. U.S. Environmental Protection Agency. Compilation of Air Pollutant Emission Factors, 

AP-42, Fifth Edition, Volume I: Stationary Point and Area Sources. 1998. 

<www.epa.gov/ttn/chief/ap42/index.html> 

3. Coughlin, K. Projections of Full-Fuel-Cycle Energy and Emissions Metrics. 2013. 

Lawrence Berkeley National Laboratory. Berkeley, CA. Report No. LBNL-6025E.

13-9 
CHAPTER 14. MONETIZATION OF EMISSION REDUCTIONS BENEFITS 

TABLE OF CONTENTS

14.1 INTRODUCTION ......................................................................................................... 14-1

14.2 MONETIZING CARBON DIOXIDE EMISSIONS ..................................................... 14-1

14.2.1 Social Cost of Carbon ........................................................................................ 14-1

14.2.2 Monetizing Carbon Dioxide Emissions ............................................................. 14-1

14.2.3 Current Approach and Key Assumptions .......................................................... 14-2

14.3 VALUATION OF OTHER EMMISIONS REDUCTIONS .......................................... 14-5

14.4 RESULTS ...................................................................................................................... 14-5

REFERENCES .......................................................................................................................... 14-8

LIST OF TABLES

Table 14.2.1 Annual SCC Values from 2010 Interagency Report, 2010–2050 (in 2007$ 

per metric ton) .................................................................................................... 14-4

Table 14.2.2 Annual SCC Values from 2013 Interagency Update, 2010–2050 (in 2007$ 

per metric ton CO2) ............................................................................................ 14-4

Table 14.4.1 Estimates of Global Present Value of CO2 Emissions Reduction under 

Commercial Refrigeration Equipment Trial Standard Levels ........................... 14-6

Table 14.4.2 Estimates of Domestic Present Value of CO2 Emissions Reduction under 

Commercial Refrigeration Equipment Trial Standard Levels ........................... 14-6

Table 14.4.3 Estimates of Present Value of NOx Emissions Reduction under Commercial 

Refrigeration Equipment Trial Standard Levels ................................................ 14-7

14-i 
CHAPTER 14. MONETIZATION OF EMISSION REDUCTIONS BENEFITS 

14.1 INTRODUCTION

As part of its assessment of energy conservation standards for commercial refrigeration 

equipment, the U.S. Department of Energy (DOE) estimated the monetary benefits likely to 

result from the reduced emissions of carbon dioxide (CO2) and nitrogen oxides (NOx) that are 

expected to result from each of the trial standard levels (TSLs) considered. This chapter 

summarizes the basis for the monetary values used for each of these emissions and presents the 

benefits estimates considered. 

14.2 MONETIZING CARBON DIOXIDE EMISSIONS

14.2.1 Social Cost of Carbon 

The social cost of carbon (SCC) is an estimate of the monetized damages associated with 

an incremental increase in carbon emissions in a given year. It is intended to include (but is not 

limited to) changes in net agricultural productivity, human health, property damages from 

increased flood risk, and the value of ecosystem services. Estimates of the SCC are provided in 

dollars per metric ton of CO2. A domestic SCC value is meant to reflect the value of damages in 

the United States resulting from a unit change in CO2 emissions, while a global SCC value is 

meant to reflect the value of damages worldwide.

Under section 1(b)(6) of Executive Order 12866,”Regulatory Planning and Review,” 58 

FR 51735 (Oct. 4, 1993), agencies must, to the extent permitted by law, “assess both the costs 

and the benefits of the intended regulation and, recognizing that some costs and benefits are 

difficult to quantify, propose or adopt a regulation only upon a reasoned determination that the 

benefits of the intended regulation justify its costs.” The purpose of the SCC estimates presented 

here is to allow agencies to incorporate the monetized social benefits of reducing CO2 emissions 

into cost-benefit analyses of regulatory actions that have small, or “marginal,” impacts on 

cumulative global emissions. The estimates are presented with an acknowledgement of the many 

uncertainties involved and with a clear understanding that they should be updated over time to 

reflect increasing knowledge of the science and economics of climate impacts.

As part of the interagency process that developed these SCC estimates, technical experts 

from numerous agencies met on a regular basis to explore the technical literature in relevant 

fields, discuss key model inputs and assumptions, and consider public comments. The main 

objective of this process was to develop a range of SCC values using a defensible set of input 

assumptions grounded in the existing scientific and economic literatures. In this way, key 

uncertainties and model differences transparently and consistently inform the range of SCC 

estimates used in the rulemaking process.

14.2.2 Monetizing Carbon Dioxide Emissions 

When attempting to assess the incremental economic impacts of CO2 emissions, the 

analyst faces a number of serious challenges. A report from the National Research Council1

points out that any assessment will suffer from uncertainty, speculation, and lack of information 

about (1) future emissions of greenhouse gases; (2) the effects of past and future emissions on 

14-1 
the climate system; (3) the impact of changes in climate on the physical and biological 

environment; and (4) the translation of these environmental impacts into economic damages. As 

a result, any effort to quantify and monetize the harms associated with climate change will raise 

serious questions of science, economics, and ethics and should be viewed as provisional. 

Despite the serious limits of both quantification and monetization, SCC estimates can be 

useful in estimating the social benefits of reducing CO2 emissions. Most Federal regulatory 

actions can be expected to have marginal impacts on global emissions. For such policies, the 

agency can estimate the benefits from reduced (or costs from increased) emissions in any future 

year by multiplying the change in emissions in that year by the SCC value appropriate for that 

year. The net present value of the benefits can then be calculated by multiplying each of these 

future benefits by an appropriate discount factor and summing across all affected years. This 

approach assumes that the marginal damages from increased emissions are constant for small 

departures from the baseline emissions path, an approximation that is reasonable for policies that 

have effects on emissions that are small relative to cumulative global CO2 emissions.

In 2009, an interagency process was initiated to offer a preliminary assessment of how 

best to quantify the benefits from reducing CO2 emissions. To ensure consistency in how 

benefits are evaluated across agencies, the Administration sought to develop a transparent and 

defensible method, specifically designed for the rulemaking process, to quantify avoided climate 

change damages from reduced CO2 emissions. The interagency group did not undertake any 

original analysis. Instead, it combined SCC estimates from the existing literature to use as 

interim values until a more comprehensive analysis could be conducted. The outcome of the 

preliminary assessment by the interagency group was a set of five interim values: global SCC 

estimates for 2007 (in 2006$) of $55, $33, $19, $10, and $5 per ton of CO2.

2 These interim 

values represented the first sustained interagency effort within the U.S. government to develop 

an SCC for use in regulatory analysis. The results of this preliminary effort were presented in 

several proposed and final rules. 

14.2.3 Current Approach and Key Assumptions

After the release of the interim values, the interagency group reconvened on a regular 

basis to generate improved SCC estimates, which were considered for this proposed rule. 

Specifically, the group considered public comments and further explored the technical literature 

in relevant fields. The interagency group relied on three integrated assessment models (IAMs) 

commonly used to estimate the SCC: the FUND, DICE, and PAGE models.a These models are 

frequently cited in the peer-reviewed literature and were used in the last assessment of the 

Intergovernmental Panel on Climate Change. Each model was given equal weight in the SCC 

values that were developed. 

Each model takes a slightly different approach to model how changes in emissions result 

in changes in economic damages. A key objective of the interagency process was to enable a 

consistent exploration of the three models while respecting the different approaches to 

quantifying damages taken by the key modelers in the field. An extensive review of the literature 

was conducted to select three sets of input parameters for these models: (1) climate sensitivity; 

a The models are described in appendix 14-A of the technical support document.

14-2 

 
(2) socio-economic and emissions trajectories; and (3) discount rates. A probability distribution 

for climate sensitivity was specified as an input into all three models. In addition, the interagency 

group used a range of scenarios for the socio-economic parameters and a range of values for the 

discount rate. All other model features were left unchanged, relying on the model developers’ 

best estimates and judgments.

The interagency group selected four SCC values for use in regulatory analyses. Three 

values are based on the average SCC from three integrated assessment models, at discount rates 

of 2.5, 3, and 5 percent. The fourth value, which represents the 95th percentile SCC estimate 

across all three models at a 3-percent discount rate, is included to represent higher-than-expected 

impacts from temperature change further out in the tails of the SCC distribution. The values 

grow in real terms over time. Additionally, the interagency group determined that a range of 

values from 7 percent to 23 percent should be used to adjust the global SCC to calculate 

domestic effects, although preference is given to consideration of the global benefits of reducing 

CO2 emissions. Table 14.2.1 presents the values in the 2010 interagency group report,b

 which is 

reproduced in appendix 14-A of the notice of proposed rulemaking technical support document 

(NOPR TSD). 

The SCC values used for this analysis were generated using the most recent versions of 

the three integrated assessment models that have been published in the peer-reviewed literature.

c

Table 14.2.2 shows the updated sets of SCC estimates in 5-year increments from 2010 to 2050. 

The full set of annual SCC estimates between 2010 and 2050 is reported in appendix 14B of the 

NOPR TSD. The central value that emerges is the average SCC across models at the 3-percent 

discount rate. However, for purposes of capturing the uncertainties involved in regulatory impact 

analysis, the interagency group emphasizes the importance of including all four sets of SCC 

values. For the years after 2050, DOE applied the average annual growth rate of the SCC 

estimates in 2040−2050 associated with each of the four sets of values.

b Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866. Interagency Working Group 

on Social Cost of Carbon, United States Government, February 2010. 

www.whitehouse.gov/sites/default/files/omb/inforeg/for-agencies/Social-Cost-of-Carbon-for-RIA.pdf. c Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866. 

Interagency Working Group on Social Cost of Carbon, United States Government. May 2013. 

www.whitehouse.gov/sites/default/files/omb/inforeg/social_cost_of_carbon_for_ria_2013_update.pdf

14-3 

 
Table 14.2.1 Annual SCC Values from 2010 Interagency Report, 2010–2050 (in 2007$ per 

metric ton)

Year

Discount Rate 

%

5 3 2.5 3

Average Average Average 95th Percentile

2010 4.7 21.4 35.1 64.9

2015 5.7 23.8 38.4 72.8

2020 6.8 26.3 41.7 80.7

2025 8.2 29.6 45.9 90.4

2030 9.7 32.8 50.0 100.0

2035 11.2 36.0 54.2 109.7

2040 12.7 39.2 58.4 119.3

2045 14.2 42.1 61.7 127.8

2050 15.7 44.9 65.0 136.2

Table 14.2.2 Annual SCC Values from 2013 Interagency Update, 2010–2050 (in 2007$ per 

metric ton CO2) 

Year

Discount Rate 

%

5 3 2.5 3

Average Average Average 95th Percentile

2010 11 33 52 90

2015 12 38 58 109

2020 12 43 65 129

2025 14 48 70 144

2030 16 52 76 159

2035 19 57 81 176

2040 21 62 87 192

2045 24 66 92 206

2050 27 71 98 221

It is important to recognize that a number of key uncertainties remain, and that current 

SCC estimates should be treated as provisional and revisable since they will evolve with 

improved scientific and economic understanding. The interagency group also recognizes that the 

existing models are imperfect and incomplete. The National Research Council report previously 

mentioned points out that there is tension between the goal of producing quantified estimates of 

the economic damages from an incremental ton of carbon and the limits of existing efforts to 

model these effects. There are a number of concerns and problems that should be addressed by 

the research community, including research programs housed in many of the agencies 

participating in the interagency process to estimate the SCC. The interagency group intends to 

periodically review and reconsider estimates of the SCC used for cost-benefit analyses to reflect 

increasing knowledge of the science and economics of climate impacts, as well as improvements 

in modeling. 

In summary, in considering the potential global benefits resulting from reduced CO2

emissions, DOE used the values from the 2013 interagency report, escalated to 2012$ using the 

gross domestic product (GDP) price deflator. For each of the four cases specified, the values 

used for emissions in 2015 are $12.9, $40.8, $62.2, and $117 per metric ton avoided.3

14-4 
DOE multiplied the CO2 emissions reduction estimated for each year by the SCC value 

for that year in each of the four cases. To calculate a present value of the stream of monetary 

values, the interagency report notes that damages from future emissions should be discounted at 

the same rate as that used to calculate the SCC estimates themselves to ensure internal 

consistency. Thus, DOE discounted the values in each of the four cases using the specific 

discount rate that had been used to obtain the SCC values in each case. 

14.3 VALUATION OF OTHER EMMISIONS REDUCTIONS

DOE considered the potential monetary benefit of reduced NOX emissions from the TSLs 

it considered. As noted in chapter 13, new or amended energy conservation standards would 

reduce NOx emissions in those States that are not affected by caps. DOE estimated the monetized 

value of NOx emissions reductions resulting from each of the TSLs considered based on 

environmental damage estimates found in the relevant scientific literature. Available estimates 

suggest a very wide range of monetary values, ranging from $468 to $4,809 per ton (in 2012$).4

In accordance with Office of Management and Budget (OMB) guidance, DOE calculated a range 

of monetary benefits using each of the economic values for NOx and real discount rates of 3 

percent and 7 percent.5 

DOE is still evaluating appropriate values to use to monetize avoided SO2 and Hg 

emissions. It did not monetize these emissions for this analysis. 

14.4 RESULTS

Table 14.4.1 presents the global values of CO2 emissions reductions for each considered 

TSL. DOE calculated domestic values as a range from 7 percent to 23 percent of the global 

values, and these results are presented in Table 14.4.2. 

14-5 
Table 14.4.1 Estimates of Global Present Value of CO2 Emissions Reduction under 

Commercial Refrigeration Equipment Trial Standard Levels

TSL

SCC Case*

5% discount 

rate, average

3% discount 

rate, average

2.5% discount 

rate, average

3% discount rate, 

95th percentile

Million 2012$

Primary Energy Emissions

1 68.6 335.1 546.1 1,013.7

2 122.6 598.7 975.6 1,811.1

3 266.9 1,304.1 2,124.9 3,944.8

4 290.6 1,419.8 2,313.4 4,294.8

5 370.7 1,811.2 2,951.2 5,478.8

Upstream Emissions

1 4.0 20.0 32.6 60.6

2 7.2 35.7 58.3 108.3

3 15.8 77.8 126.9 236.0

4 17.1 84.7 138.1 256.9

5 21.9 108.1 176.2 327.7

Total Emissions

1 73 355 579 1,074

2 130 634 1,034 1,919

3 283 1,382 2,252 4,181

4 308 1,504 2,452 4,552

5 393 1,919 3,127 5,807

* For each of the four cases, the corresponding SCC value for emissions in 2015 is $12.9, $40.8, 

$62.2, and $117.0 per metric ton (2012$).

Table 14.4.2 Estimates of Domestic Present Value of CO2 Emissions Reduction under 

Commercial Refrigeration Equipment Trial Standard Levels 

TSL

SCC Case*

5% discount 

rate, average

3% discount 

rate, average

2.5% discount 

rate, average

3% discount rate, 

95th percentile

Million 2012$

Primary Energy Emissions

1 4.8 to 15.8 23.5 to 77.1 38.2 to 125.6 71.0 to 233.2

2 8.6 to 28.2 41.9 to 137.7 68.3 to 224.4 126.8 to 416.6

3 18.7 to 61.4 91.3 to 299.9 148.7 to 488.7 276.1 to 907.3

4 20.3 to 66.8 99.4 to 326.5 161.9 to 532.1 300.6 to 987.8

5 26.0 to 85.3 126.8 to 416.6 206.6 to 678.8 383.5 to 1260.1

Upstream Emissions

1 0.3 to 0.9 1.4 to 4.6 2.3 to 7.5 4.2 to 13.9

2 0.5 to 1.7 2.5 to 8.2 4.1 to 13.4 7.6 to 24.9

3 1.1 to 3.6 5.4 to 17.9 8.9 to 29.2 16.5 to 54.3

4 1.2 to 3.9 5.9 to 19.5 9.7 to 31.8 18.0 to 59.1

5 1.5 to 5.0 7.6 to 24.9 12.3 to 40.5 22.9 to 75.4

Total Emissions

1 5.1 to 16.7 24.9 to 81.7 40.5 to 133.1 75.2 to 247.1

2 9.1 to 29.9 44.4 to 145.9 72.4 to 237.8 134.4 to 441.5

3 19.8 to 65.0 96.7 to 317.8 157.6 to 517.9 292.7 to 961.6

4 21.5 to 70.8 105.3 to 346.0 171.6 to 563.9 318.6 to 1046.9

5 27.5 to 90.3 134.3 to 441.4 218.9 to 719.3 406.5 to 1335.5

* For each of the four cases, the corresponding SCC value for emissions in 2015 is $12.9, $40.8, 

$62.2, and $117.0 per metric ton (2012$).

14-6 
Table 14.4.3 presents the present value of cumulative NOx emissions reductions for each 

TSL, calculated using the average dollar-per-ton values and 7-percent and 3-percent discount 

rates.

Table 14.4.3 Estimates of Present Value of NOx Emissions Reduction under Commercial 

Refrigeration Equipment Trial Standard Levels

TSL 3% discount rate 7% discount rate

Million 2012$

Power Sector Emissions

1 12.0 5.6

2 21.4 10.0

3 46.6 21.7

4 50.7 23.6

5 64.7 30.1

Upstream Emissions

1 13.4 6.2

2 24.0 11.0

3 52.3 24.0

4 56.9 26.1

5 72.6 33.3

Total Emissions

1 25.4 11.7

2 45.4 21.0

3 98.9 45.7

4 107.6 49.8

5 137.3 63.5

14-7 
REFERENCES

1. National Research Council, Hidden Costs of Energy: Unpriced Consequences of Energy 

Production and Use, 2009. National Academies Press. Washington, DC. 

<www.nap.edu/catalog.php?record_id=12794> 

2. Interagency Working Group on Social Cost of Carbon, Social Cost of Carbon for 

Regulatory Impact Analysis under Executive Order 12866, February, 2010. United States 

Government. <www.whitehouse.gov/sites/default/files/omb/inforeg/for-agencies/SocialCost-of-Carbon-for-RIA.pdf> 

3. Interagency Working Group on Social Cost of Carbon, Technical Update of the Social Cost 

of Carbon for Regulatory Impact Analysis Under Executive Order 12866. Interagency 

Working Group on Social Cost of Carbon, May, 2013. United States Government. 

<www.whitehouse.gov/sites/default/files/omb/inforeg/social_cost_of_carbon_for_ria_2013_

update.pdf> 

4. U.S. Office of Management and Budget (OMB), 2006 Report to Congress on the Costs and 

Benefits of Federal Regulations and Unfunded Mandates on State, Local, and Tribal 

Entities, 2006. Washington, DC. 

<www.whitehouse.gov/sites/default/files/omb/assets/omb/inforeg/2006_cb/2006_cb_final_r

eport.pdf> 

5. U.S. Office of Management and Budget (OMB), Circular A-4: Regulatory Analysis, 2003.

(Posted September 17, 2003) (Last accessed April 2013.) 

<www.whitehouse.gov/sites/default/files/omb/assets/regulatory_matters_pdf/a-4.pdf> 

14-8 
APPENDIX 14A. SOCIAL COST OF CARBON FOR REGULATORY IMPACT 

ANALYSIS UNDER EXECUTIVE ORDER 12866

TABLE OF CONTENTS

14A.1 EXECUTIVE SUMMARY ........................................................................................ 14A-1

14A.2 MONETIZING CARBON DIOXIDE EMISSIONS .................................................. 14A-2

14A.3 SOCIAL COST OF CARBON VALUES USED IN PAST REGULATORY 

ANALYSES ................................................................................................................ 14A-4

14A.4 APPROACH AND KEY ASSUMPTIONS ............................................................... 14A-5

14A.4.1 Integrated Assessment Models ................................................................. 14A-5

14A.4.2 Global versus Domestic Measures of SCC ............................................. 14A-11

14A.4.3 Valuing Non-CO2 Emissions .................................................................. 14A-12

14A.4.4 Equilibrium Climate Sensitivity ............................................................. 14A-13

14A.4.5 Socio-Economic and Emissions Trajectories.......................................... 14A-16

14A.4.6 Discount Rate .......................................................................................... 14A-18

14A.5 REVISED SCC ESTIMATES .................................................................................. 14A-25

14A.6 LIMITATIONS OF THE ANALYSIS ..................................................................... 14A-29

14A.7 A FURTHER DISCUSSION OF CATASTROPHIC IMPACTS AND DAMAGE 

FUNCTIONS ............................................................................................................ 14A-32

14A.7.1 Extrapolation of Climate Damages to High Levels of Warming ............ 14A-32

14A.7.2 Failure to Incorporate Inter-Sectoral and Inter-Regional Interactions .... 14A-33

14A.7.3 Imperfect Substitutability of Environmental Amenities ......................... 14A-34

14A.8 CONCLUSION ......................................................................................................... 14A-34

14A.9 REFERENCES ......................................................................................................... 14A-36

14A.10ANNEX..................................................................................................................... 14A-42

14A.10.1 Other (non-CO2) Gases ........................................................................... 14A-43

14A.10.2 Extrapolating Emissions Projections to 2300 ......................................... 14A-45

LIST OF TABLES

Table 14A.1.1 Social Cost of CO2, 2010–2050 (2007$) ........................................................ 14A-2

Table 14A.4.1 Summary Statistics for Four Calibrated Climate Sensitivity Distributions .. 14A-14

Table 14A.4.2 Socioeconomic and Emissions Projections from Select EMF-22 Reference 

Scenarios ....................................................................................................... 14A-17

Table 14A.5.1 Disaggregated Social Cost of CO2 Values by Model, Socio-Economic 

Trajectory, and Discount Rate for 2010 (2007$) .......................................... 14A-27

Table 14A.5.2 Social Cost of CO2, 2010–2050 (2007$) ...................................................... 14A-29

Table 14A.5.3 Changes in the Average Annual Growth Rates of SCC Estimates between 

2010 and 2050 ............................................................................................... 14A-29

Table 14A.7.1 Probabilities of Various Tipping Points from Expert Elicitation.................. 14A-33

Table 14A.9.1 Annual SCC Values: 2010–2050 (2007$) .................................................... 14A-42

Table 14A.9.2 2010 Global SCC Estimates at 2.5 Percent Discount Rate (2007$/ton CO2) 14A-50

Table 14A.9.3 2010 Global SCC Estimates at 3 Percent Discount Rate (2007$/ton CO2) .. 14A-50

14A-i 
Table 14A.9.4 2010 Global SCC Estimates at 5 Percent Discount Rate (2007$/ton CO2) .. 14A-51

Table 14A.9.5 Additional Summary Statistics of 2010 Global SCC Estimates ................... 14A-52

LIST OF FIGURES

Figure 14A.4.1 Annual Consumption Loss as a Fraction of Global GDP in 2100 Due to 

an Increase in Annual Global Temperature in the DICE, FUND, and 

PAGE Models ............................................................................................... 14A-10

Figure 14A.4.2 Annual Consumption Loss for Lower Temperature Changes in DICE, 

FUND, and PAGE ........................................................................................ 14A-10

Figure 14A.4.3 Estimates of the Probability Density Function for Equilibrium Climate 

Sensitivity ..................................................................................................... 14A-15

Figure 14A.5.1 Level of Global GDP Across EMF Scenarios ............................................. 14A-28

Figure 14A.9.1 Sulphur Dioxide Emission Scenarios .......................................................... 14A-45

Figure 14A.9.2 Global Population, 2000–2300 (post-2100 extrapolations assume the 

population growth rate changes linearly to reach a zero growth rate by 

2200) ............................................................................................................. 14A-47

Figure 14A.9.3 World GDP, 2000-2300 (post-2100 extrapolations assume GDP per 

capita growth declines linearly, reaching zero in 2300) ............................... 14A-47

Figure 14A.9.4 Global Fossil and Industrial CO2 Emissions, 2000-2300 (post-2100 

extrapolations assume growth rate of CO2 intensity (CO2/GDP) over 

2090–2100 is maintained through 2300) ...................................................... 14A-48

Figure 14A.9.5 Global Net Land Use CO2 Emissions, 2000–2300 (post-2100 

extrapolations assume emissions decline linearly, reaching zero in 2200) .. 14A-48

Figure 14A.9.6 Global Non-CO2 Radiative Forcing, 2000–2300 (post-2100 

extrapolations assume constant non-CO2 radiative forcing after 2100) ....... 14A-49

Figure 14A.9.7 Global CO2 Intensity (fossil & industrial CO2 emissions/GDP), 2000–

2300 (post-2100 extrapolations assume decline in CO2/GDP growth rate 

over 2090–2100 is maintained through 2300) .............................................. 14A-49

Figure 14A.9.8 Histogram of Global SCC Estimates in 2010 (2007$/ton CO2), by 

Discount Rate* .............................................................................................. 14A-51

14A-ii
APPENDIX 14A. SOCIAL COST OF CARBON FOR REGULATORY IMPACT 

ANALYSIS UNDER EXECUTIVE ORDER 12866

Prepared by

Interagency Working Group on Social Cost of Carbon, United States Government 

With participation by

Council of Economic Advisers 

Council on Environmental Quality 

Department of Agriculture

Department of Commerce

Department of Energy

Department of Transportation 

Environmental Protection Agency 

National Economic Council 

Office of Energy and Climate Change

Office of Management and Budget

Office of Science and Technology Policy 

Department of the Treasury

14A.1 EXECUTIVE SUMMARY

Under Executive Order (E.O.) 12866, agencies are required, to the extent permitted by 

law, “to assess both the costs and the benefits of the intended regulation and, recognizing that 

some costs and benefits are difficult to quantify, propose or adopt a regulation only upon a 

reasoned determination that the benefits of the intended regulation justify its costs.” The purpose 

of the “social cost of carbon” (SCC) estimates presented here is to allow agencies to incorporate 

the social benefits of reducing carbon dioxide (CO2) emissions into cost-benefit analyses of 

regulatory actions that have small, or “marginal,” impacts on cumulative global emissions. The 

estimates are presented with an acknowledgement of the many uncertainties involved and with a 

clear understanding that they should be updated over time to reflect increasing knowledge of the 

science and economics of climate impacts.

The SCC is an estimate of the monetized damages associated with an incremental 

increase in carbon emissions in a given year. It is intended to include but is not limited to 

changes in net agricultural productivity, human health, property damages from increased flood 

risk, and the value of ecosystem services due to climate change.

This document presents a summary of the interagency process that developed these SCC 

estimates. Technical experts from numerous agencies met on a regular basis to consider public 

comments, explore the technical literature in relevant fields, and discuss key model inputs and 

assumptions. The main objective of this process was to develop a range of SCC values using a 

defensible set of input assumptions grounded in the existing scientific and economic literatures. 

14A-1 
In this way, key uncertainties and model differences transparently and consistently inform the 

range of SCC estimates used in the rulemaking process.

The interagency group selected four SCC values for use in regulatory analyses (Table 

14A.1.1. Three values are based on the average SCC from three integrated assessment models, 

at discount rates of 2.5, 3, and 5 percent. The fourth value, which represents the 95th percentile 

SCC estimate across all three models at a 3 percent discount rate, is included to represent higherthan-expected impacts from temperature change further out in the tails of the SCC distribution.

 

Table 14A.1.1 Social Cost of CO2, 2010–2050 (2007$) 

Year Discount Rate

%

5 3 2.5 3

Avg Avg Avg 95th

2010 4.7 21.4 35.1 64.9

2015 5.7 23.8 38.4 72.8

2020 6.8 26.3 41.7 80.7

2025 8.2 29.6 45.9 90.4

2030 9.7 32.8 50.0 100.0

2035 11.2 36.0 54.2 109.7

2040 12.7 39.2 58.4 119.3

2045 14.2 42.1 61.7 127.8

2050 15.7 44.9 65.0 136.2

14A.2 MONETIZING CARBON DIOXIDE EMISSIONS

The “social cost of carbon” (SCC) is an estimate of the monetized damages associated 

with an incremental increase in carbon emissions in a given year. It is intended to include but is 

not limited to changes in net agricultural productivity, human health, property damages from 

increased flood risk, and the value of ecosystem services. We report estimates of the social cost 

of carbon in dollars per metric ton of CO2 throughout this document.a 

When attempting to assess the incremental economic impacts of CO2 emissions, the 

analyst faces a number of serious challenges. A recent report from the National Academies of 

Science (NRC 2009) points out that any assessment will suffer from uncertainty, speculation, 

and lack of information about (1) future emissions of greenhouse gases; (2) the effects of past 

and future emissions on the climate system; (3) the impact of changes in climate on the physical 

and biological environment; and (4) the translation of these environmental impacts into 

economic damages. As a result, any effort to quantify and monetize the harms associated with 

climate change will raise serious questions of science, economics, and ethics and should be 

viewed as provisional. 

Despite the serious limits of both quantification and monetization, SCC estimates can be 

useful in estimating the social benefits of reducing CO2 emissions. Under E.O. 12866, agencies 

a In this document, we present all values of the SCC as the cost per metric ton of CO2 emissions. Alternatively, one 

could report the SCC as the cost per metric ton of carbon emissions. The multiplier for translating between mass of 

CO2 and the mass of carbon is 3.67 (the molecular weight of CO2 divided by the molecular weight of carbon = 44/12 

= 3.67). 

14A-2 

 
are required, to the extent permitted by law, “to assess both the costs and the benefits of the 

intended regulation and, recognizing that some costs and benefits are difficult to quantify, 

propose or adopt a regulation only upon a reasoned determination that the benefits of the 

intended regulation justify its costs.” The purpose of the SCC estimates presented here is to make 

it possible for agencies to incorporate the social benefits from reducing CO2 emissions into costbenefit analyses of regulatory actions that have small or “marginal” impacts on cumulative 

global emissions. Most Federal regulatory actions can be expected to have marginal impacts on 

global emissions. 

For such policies, the benefits from reduced (or costs from increased) emissions in any 

future year can be estimated by multiplying the change in emissions in that year by the SCC 

value appropriate for that year. The net present value of the benefits can then be calculated by 

multiplying each of these future benefits by an appropriate discount factor and summing across 

all affected years. This approach assumes that the marginal damages from increased emissions 

are constant for small departures from the baseline emissions path, an approximation that is 

reasonable for policies that have effects on emissions that are small relative to cumulative global 

CO2 emissions. For policies that have a large (non-marginal) impact on global cumulative 

emissions, there is a separate question of whether the SCC is an appropriate tool for calculating 

the benefits of reduced emissions; we do not attempt to answer that question here. 

An interagency group convened on a regular basis to consider public comments, explore 

the technical literature in relevant fields, and discuss key inputs and assumptions in order to 

generate SCC estimates. Agencies that actively participated in the interagency process include 

the Environmental Protection Agency, and the Departments of Agriculture, Commerce, Energy, 

Transportation, and Treasury. This process was convened by the Council of Economic Advisers 

and the Office of Management and Budget, with active participation and regular input from the 

Council on Environmental Quality, National Economic Council, Office of Energy and Climate 

Change, and Office of Science and Technology Policy. The main objective of this process was to 

develop a range of SCC values using a defensible set of input assumptions that are grounded in 

the existing literature. In this way, key uncertainties and model differences can more 

transparently and consistently inform the range of SCC estimates used in the rulemaking process.

The interagency group selected four SCC estimates for use in regulatory analyses. For 

2010, these estimates are $4.7, $21.4, $35.1, and $64.9 (2007$). The first three estimates are 

based on the average SCC across models and socio-economic and emissions scenarios at the 5, 3, 

and 2.5 percent discount rates, respectively. The fourth value is included to represent the higherthan-expected impacts from temperature change further out in the tails of the SCC distribution. 

For this purpose, we use the SCC value for the 95th percentile at a 3 percent discount rate. The 

central value is the average SCC across models at the 3 percent discount rate. For purposes of 

capturing the uncertainties involved in regulatory impact analysis, we emphasize the importance 

and value of considering the full range. These SCC estimates also grow over time. For instance, 

the central value increases to $24 per ton of CO2 in 2015 and $26 per ton of CO2 in 2020. See 

Appendix A for the full range of annual SCC estimates from 2010 to 2050. 

It is important to emphasize that the interagency process is committed to updating these 

estimates as the science and economic understanding of climate change and its impacts on 

society improves over time. Specifically, we have set a preliminary goal of revisiting the SCC 

14A-3 
values within 2 years or at such time as substantially updated models become available, and to 

continue to support research in this area. In the meantime, we will continue to explore the issues 

raised in this document and consider public comments as part of the ongoing interagency 

process.

14A.3 SOCIAL COST OF CARBON VALUES USED IN PAST REGULATORY 

ANALYSES

To date, economic analyses for Federal regulations have used a wide range of values to 

estimate the benefits associated with reducing CO2 emissions. In the final model year 2011 

CAFE rule, the Department of Transportation (DOT) used both a “domestic” SCC value of $2 

per ton of CO2 and a “global” SCC value of $33 per ton of CO2 for 2007 emission reductions 

(2007$), increasing both values at 2.4 percent per year. It also included a sensitivity analysis at 

$80 per ton of CO2. A domestic SCC value is meant to reflect the value of damages in the United 

States resulting from a unit change in CO2 emissions, while a global SCC value is meant to 

reflect the value of damages worldwide.

A 2008 regulation proposed by DOT assumed a domestic SCC value of $7 per ton CO2

(in 2006 dollars) for 2011 emission reductions (with a range of $0-$14 for sensitivity analysis), 

also increasing at 2.4 percent per year. A regulation finalized by DOE in October of 2008 used a 

domestic SCC range of $0 to $20 per ton CO2 for 2007 emission reductions (2007$). In addition, 

EPA’s 2008 Advance Notice of Proposed Rulemaking for Greenhouse Gases identified what it 

described as “very preliminary” SCC estimates subject to revision. EPA’s global mean values 

were $68 and $40 per ton CO2 for discount rates of approximately 2 percent and 3 percent, 

respectively (2006$ for 2007 emissions). 

In 2009, an interagency process was initiated to offer a preliminary assessment of how 

best to quantify the benefits from reducing CO2 emissions. To ensure consistency in how 

benefits are evaluated across agencies, the Administration sought to develop a transparent and 

defensible method, specifically designed for the rulemaking process, to quantify avoided climate 

change damages from reduced CO2 emissions. The interagency group did not undertake any 

original analysis. Instead, it combined SCC estimates from the existing literature to use as 

interim values until a more comprehensive analysis could be conducted. 

The outcome of the preliminary assessment by the interagency group was a set of five 

interim values: global SCC estimates for 2007 (in 2006 dollars) of $55, $33, $19, $10, and $5 per 

ton of CO2. The $33 and $5 values represented model-weighted means of the published estimates 

produced from the most recently available versions of three integrated assessment models—

DICE, PAGE, and FUND—at approximately 3 and 5 percent discount rates. The $55 and $10 

values were derived by adjusting the published estimates for uncertainty in the discount rate 

(using factors developed by Newell and Pizer (2003)) at 3 and 5 percent discount rates, 

respectively. The $19 value was chosen as a central value between the $5 and $33 per ton 

estimates. All of these values were assumed to increase at 3 percent annually to represent growth 

in incremental damages over time as the magnitude of climate change increases.

These interim values represent the first sustained interagency effort within the U.S. 

government to develop an SCC for use in regulatory analysis. The results of this preliminary 

14A-4 
effort were presented in several proposed and final rules and were offered for public comment in 

connection with proposed rules, including the joint EPA-DOT fuel economy and CO2 tailpipe 

emission proposed rules. 

14A.4 APPROACH AND KEY ASSUMPTIONS

Since the release of the interim values, interagency group has reconvened on a regular 

basis to generate improved SCC estimates. Specifically, the group has considered public 

comments and further explored the technical literature in relevant fields. This section details the 

several choices and assumptions that underlie the resulting estimates of the SCC. 

It is important to recognize that a number of key uncertainties remain, and that current 

SCC estimates should be treated as provisional and revisable since they will evolve with 

improved scientific and economic understanding. The interagency group also recognizes that the 

existing models are imperfect and incomplete. The National Academy of Science (2009) points 

out that there is tension between the goal of producing quantified estimates of the economic 

damages from an incremental ton of carbon and the limits of existing efforts to model these 

effects. Throughout this document, we highlight a number of concerns and problems that should 

be addressed by the research community, including research programs housed in many of the 

agencies participating in the interagency process to estimate the SCC. 

The U.S. Government will periodically review and reconsider estimates of the SCC used 

for cost-benefit analyses to reflect increasing knowledge of the science and economics of climate 

impacts, as well as improvements in modeling. In this context, statements recognizing the 

limitations of the analysis and calling for further research take on exceptional significance. The 

interagency group offers the new SCC values with all due humility about the uncertainties 

embedded in them and with a sincere promise to continue work to improve them. 

14A.4.1 Integrated Assessment Models 

We rely on three integrated assessment models (IAMs) commonly used to estimate the 

SCC: the FUND, DICE, and PAGE models.b These models are frequently cited in the peerreviewed literature and used in the IPCC assessment. Each model is given equal weight in the 

SCC values developed through this process, bearing in mind their different limitations (discussed 

below). 

These models are useful because they combine climate processes, economic growth, and 

feedbacks between the climate and the global economy into a single modeling framework. At the 

same time, they gain this advantage at the expense of a more detailed representation of the 

underlying climatic and economic systems. DICE, PAGE, and FUND all take stylized, reducedform approaches (see NRC 2009 for a more detailed discussion; see Nordhaus 2008 on the 

b The DICE (Dynamic Integrated Climate and Economy) model by William Nordhaus evolved from a series of 

energy models and was first presented in 1990 (Nordhaus and Boyer 2000, Nordhaus 2008). The PAGE (Policy 

Analysis of the Greenhouse Effect) model was developed by Chris Hope in 1991 for use by European decisionmakers in assessing the marginal impact of carbon emissions (Hope 2006, Hope 2008). The FUND (Climate 

Framework for Uncertainty, Negotiation, and Distribution) model, developed by Richard Tol in the early 1990s, 

originally to study international capital transfers in climate policy. is now widely used to study climate impacts (e.g., 

Tol 2002a, Tol 2002b, Anthoff et al. 2009, Tol 2009).

14A-5 

 
possible advantages of this approach). Other IAMs may better reflect the complexity of the 

science in their modeling frameworks but do not link physical impacts to economic damages. 

There is currently a limited amount of research linking climate impacts to economic damages, 

which makes this exercise even more difficult. Underlying the three IAMs selected for this 

exercise are a number of simplifying assumptions and judgments reflecting the various modelers’ 

best attempts to synthesize the available scientific and economic research characterizing these 

relationships. 

The three IAMs translate emissions into changes in atmospheric greenhouse 

concentrations, atmospheric concentrations into changes in temperature, and changes in 

temperature into economic damages. The emissions projections used in the models are based on 

specified socio-economic (GDP and population) pathways. These emissions are translated into 

concentrations using the carbon cycle built into each model, and concentrations are translated 

into warming based on each model’s simplified representation of the climate and a key 

parameter, climate sensitivity. Each model uses a different approach to translate warming into 

damages. Finally, transforming the stream of economic damages over time into a single value 

requires judgments about how to discount them. 

Each model takes a slightly different approach to model how changes in emissions result 

in changes in economic damages. In PAGE, for example, the consumption-equivalent damages 

in each period are calculated as a fraction of GDP, depending on the temperature in that period 

relative to the pre-industrial average temperature in each region. In FUND, damages in each 

period also depend on the rate of temperature change from the prior period. In DICE, 

temperature affects both consumption and investment. We describe each model in greater detail 

here. In a later section, we discuss key gaps in how the models account for various scientific and 

economic processes (e.g., the probability of catastrophe, and the ability to adapt to climate 

change and the physical changes it causes).

The parameters and assumptions embedded in the three models vary widely. A key 

objective of the interagency process was to enable a consistent exploration of the three models 

while respecting the different approaches to quantifying damages taken by the key modelers in 

the field. An extensive review of the literature was conducted to select three sets of input 

parameters for these models: climate sensitivity, socio-economic and emissions trajectories, and 

discount rates. A probability distribution for climate sensitivity was specified as an input into all 

three models. In addition, the interagency group used a range of scenarios for the socio-economic 

parameters and a range of values for the discount rate. All other model features were left 

unchanged, relying on the model developers’ best estimates and judgments. In DICE, these 

parameters are handled deterministically and represented by fixed constants; in PAGE, most 

parameters are represented by probability distributions. FUND was also run in a mode in which 

parameters were treated probabilistically.

The sensitivity of the results to other aspects of the models (e.g., the carbon cycle or 

damage function) is also important to explore in the context of future revisions to the SCC but 

has not been incorporated into these estimates. Areas for future research are highlighted at the 

end of this document. 

14A-6 
14A.4.1.1 The DICE Model

The DICE model is an optimal growth model based on a global production function with 

an extra stock variable (atmospheric CO2 concentrations). Emission reductions are treated as 

analogous to investment in “natural capital.” By investing in natural capital today through 

reductions in emissions—implying reduced consumption—harmful effects of climate change can 

be avoided and future consumption thereby increased. 

For purposes of estimating the SCC, CO2 emissions are a function of global GDP and the 

carbon intensity of economic output, with the latter declining over time due to technological 

progress. The DICE damage function links global average temperature to the overall impact on 

the world economy. It varies quadratically with temperature change to capture the more rapid 

increase in damages expected to occur under more extreme climate change, and is calibrated to 

include the effects of warming on the production of market and nonmarket goods and services. It 

incorporates impacts on agriculture, coastal areas (due to sea level rise), “other vulnerable 

market sectors” (based primarily on changes in energy use), human health (based on climaterelated diseases, such as malaria and dengue fever, and pollution), non-market amenities (based 

on outdoor recreation), and human settlements and ecosystems. The DICE damage function also 

includes the expected value of damages associated with low probability, high impact 

“catastrophic” climate change. This last component is calibrated based on a survey of experts 

(Nordhaus 1994). The expected value of these impacts is then added to the other market and nonmarket impacts mentioned above. 

No structural components of the DICE model represent adaptation explicitly, though it is 

included implicitly through the choice of studies used to calibrate the aggregate damage function. 

For example, its agricultural impact estimates assume that farmers can adjust land use decisions 

in response to changing climate conditions, and its health impact estimates assume 

improvements in healthcare over time. In addition, the small impacts on forestry, water systems, 

construction, fisheries, and outdoor recreation imply optimistic and costless adaptation in these 

sectors (Nordhaus and Boyer, 2000; Warren et al., 2006). Costs of resettlement due to sea level 

rise are incorporated into damage estimates, but their magnitude is not clearly reported.

Mastrandrea’s (2009) review concludes that “in general, DICE assumes very effective 

adaptation, and largely ignores adaptation costs.” 

Note that the damage function in DICE has a somewhat different meaning from the 

damage functions in FUND and PAGE. Because GDP is endogenous in DICE and because 

damages in a given year reduce investment in that year, damages propagate forward in time and 

reduce GDP in future years. In contrast, GDP is exogenous in FUND and PAGE, so damages in 

any given year do not propagate forward.c

 

c Using the default assumptions in DICE 2007, this effect generates an approximately 25 percent increase in the 

SCC relative to damages calculated by fixing GDP. In DICE2007, the time path of GDP is 

endogenous. Specifically, the path of GDP depends on the rate of saving and level of abatement in each period 

chosen by the optimizing representative agent in the model. We made two modifications to DICE to make it 

consistent with EMF GDP trajectories (see next section): we assumed a fixed rate of savings of 20%, and we recalibrated the exogenous path of total factor productivity so that DICE would produce GDP projections in the 

absence of warming that exactly matched the EMF scenarios.

14A-7 

 
14A.4.1.2 The PAGE Model

PAGE2002 (version 1.4epm) treats GDP growth as exogenous. It divides impacts into 

economic, non-economic, and catastrophic categories and calculates these impacts separately for 

eight geographic regions. Damages in each region are expressed as a fraction of output, where 

the fraction lost depends on the temperature change in each region. Damages are expressed as 

power functions of temperature change. The exponents of the damage function are the same in 

all regions but are treated as uncertain, with values ranging from 1 to 3 (instead of being fixed at 

2 as in DICE). 

PAGE2002 includes the consequences of catastrophic events in a separate damage subfunction. Unlike DICE, PAGE2002 models these events probabilistically. The probability of a 

“discontinuity” (i.e., a catastrophic event) is assumed to increase with temperature above a 

specified threshold. The threshold temperature, the rate at which the probability of experiencing 

a discontinuity increases above the threshold, and the magnitude of the resulting catastrophe are 

all modeled probabilistically.

Adaptation is explicitly included in PAGE. Impacts are assumed to occur for temperature 

increases above some tolerable level (2 °C for developed countries and 0 °C for developing 

countries for economic impacts, and 0 °C for all regions for non-economic impacts), but 

adaptation is assumed to reduce these impacts. Default values in PAGE2002 assume that the 

developed countries can ultimately eliminate up to 90 percent of all economic impacts beyond 

the tolerable 2 °C increase and that developing countries can eventually eliminate 50 percent of 

their economic impacts. All regions are assumed to be able to mitigate 25 percent of the noneconomic impacts through adaptation (Hope 2006). 

14A.4.1.3 The FUND Model

Like PAGE, the FUND model treats GDP growth as exogenous. It includes separately 

calibrated damage functions for eight market and nonmarket sectors: agriculture, forestry, water, 

energy (based on heating and cooling demand), sea level rise (based on the value of land lost and 

the cost of protection), ecosystems, human health (diarrhea, vector-borne diseases, and 

cardiovascular and respiratory mortality), and extreme weather. Each impact sector has a 

different functional form, and is calculated separately for sixteen geographic regions. In some 

impact sectors, the fraction of output lost or gained due to climate change depends not only on 

the absolute temperature change but also on the rate of temperature change and level of regional 

income.d

 In the forestry and agricultural sectors, economic damages also depend on CO2

concentrations. 

Tol (2009) discusses impacts not included in FUND, noting that many are likely to have a 

relatively small effect on damage estimates (both positive and negative). However, he 

characterizes several omitted impacts as “big unknowns:” for instance, extreme climate 

scenarios, biodiversity loss, and effects on economic development and political violence. With 

regard to potentially catastrophic events, he notes, “Exactly what would cause these sorts of 

d In the deterministic version of FUND, the majority of damages are attributable to increased air conditioning 

demand, while reduced cold stress in Europe, North America, and Central and East Asia results in health benefits in 

those regions at low to moderate levels of warming (Warren et al. 2006).

14A-8 

 
changes or what effects they would have are not well-understood, although the chance of any one 

of them happening seems low. But they do have the potential to happen relatively quickly, and if 

they did, the costs could be substantial. Only a few studies of climate change have examined 

these issues.”

Adaptation is included both implicitly and explicitly in FUND. Explicit adaptation is seen 

in the agriculture and sea level rise sectors. Implicit adaptation is included in sectors such as 

energy and human health, where wealthier populations are assumed to be less vulnerable to 

climate impacts. For example, the damages to agriculture are the sum of three effects: (1) those 

due to the rate of temperature change (damages are always positive); (2) those due to the level of 

temperature change (damages can be positive or negative depending on region and temperature); 

and (3) those from CO2 fertilization (damages are generally negative but diminishing to zero).

Adaptation is incorporated into FUND by allowing damages to be smaller if climate 

change happens more slowly. The combined effect of CO2 fertilization in the agricultural sector, 

positive impacts to some regions from higher temperatures, and sufficiently slow increases in 

temperature across these sectors can result in negative economic damages from climate change.

14A.4.1.4 Damage Functions

To generate revised SCC values, we rely on the IAM modelers’ current best judgments of 

how to represent the effects of climate change (represented by the increase in global-average 

surface temperature) on the consumption-equivalent value of both market and non-market goods 

(represented as a fraction of global GDP). We recognize that these representations are 

incomplete and highly uncertain. Given the paucity of data linking the physical impacts to 

economic damages, we were not able to identify a better way to translate changes in climate into 

net economic damages, short of launching our own research program. 

The damage functions for the three IAMs are presented in Figure 14A.4.1 and Figure 

14A.4.2, using the modeler’s default scenarios and mean input assumptions. There are significant 

differences between the three models both at lower (Figure 14A.4.1) and higher (Figure 14A.4.2) 

increases in global-average temperature. 

14A-9 
Figure 14A.4.1 Annual Consumption Loss as a Fraction of Global GDP in 2100 Due to an 

Increase in Annual Global Temperature in the DICE, FUND, and PAGE Modelse

Figure 14A.4.2 Annual Consumption Loss for Lower Temperature Changes in DICE, 

FUND, and PAGE

e The x-axis represents increases in annual, rather than equilibrium, temperature, while the y-axis represents the 

annual stream of benefits as a share of global GDP. Each specific combination of climate sensitivity, socioeconomic, and emissions parameters will produce a different realization of damages for each IAM. The damage 

functions represented in Figure 17A.4.1 and Figure 17A.4.2are the outcome of default assumptions. For instance, 

under alternate assumptions, the damages from FUND may cross from negative to positive at less than or greater 

than 3 °C.

14A-10 

 
The lack of agreement among the models at lower temperature increases is underscored 

by the fact that the damages from FUND are well below the 5th percentile estimated by PAGE, 

while the damages estimated by DICE are roughly equal to the 95th percentile estimated by 

PAGE. This is significant because at higher discount rates we expect that a greater proportion of 

the SCC value is due to damages in years with lower temperature increases. For example, when 

the discount rate is 2.5 percent, about 45 percent of the 2010 SCC value in DICE is due to 

damages that occur in years when the temperature is less than or equal to 3 °C. This increases to 

approximately 55 percent and 80 percent at discount rates of 3 and 5 percent, respectively. 

These differences underscore the need for a thorough review of damage functions—in 

particular, how the models incorporate adaptation, technological change, and catastrophic 

damages. Gaps in the literature make modifying these aspects of the models challenging, which 

highlights the need for additional research. As knowledge improves, the Federal government is 

committed to exploring how these (and other) models can be modified to incorporate more 

accurate estimates of damages.

14A.4.2 Global versus Domestic Measures of SCC

Because of the distinctive nature of the climate change problem, we center our current 

attention on a global measure of SCC. This approach is the same as that taken for the interim 

values, but it otherwise represents a departure from past practices, which tended to put greater 

emphasis on a domestic measure of SCC (limited to impacts of climate change experienced 

within U.S. borders). As a matter of law, consideration of both global and domestic values is 

generally permissible; the relevant statutory provisions are usually ambiguous and allow 

selection of either measure.f 

14A.4.2.1 Global SCC 

Under current OMB guidance contained in Circular A-4, analysis of economically 

significant proposed and final regulations from the domestic perspective is required, while 

analysis from the international perspective is optional. However, the climate change problem is 

highly unusual in at least two respects. First, it involves a global externality: emissions of most 

greenhouse gases contribute to damages around the world even when they are emitted in the 

United States. Consequently, to address the global nature of the problem, the SCC must 

incorporate the full (global) damages caused by GHG emissions. Second, climate change 

presents a problem that the United States alone cannot solve. Even if the United States were to 

reduce its greenhouse gas emissions to zero, that step would be far from enough to avoid 

substantial climate change. Other countries would also need to take action to reduce emissions if 

significant changes in the global climate are to be avoided. Emphasizing the need for a global 

solution to a global problem, the United States has been actively involved in seeking 

international agreements to reduce emissions and in encouraging other nations, including 

emerging major economies, to take significant steps to reduce emissions. When these 

f It is true that Federal statutes are presumed not to have extraterritorial effect, in part to ensure that the laws of the 

United States respect the interests of foreign sovereigns. But use of a global measure for the SCC does not give 

extraterritorial effect to federal law and hence does not intrude on such interests.

14A-11 

 
considerations are taken as a whole, the interagency group concluded that a global measure of 

the benefits from reducing U.S. emissions is preferable. 

When quantifying the damages associated with a change in emissions, a number of 

analysts (e.g., Anthoff et al. 2009a) employ “equity weighting” to aggregate changes in 

consumption across regions. This weighting takes into account the relative reductions in wealth 

in different regions of the world. A per-capita loss of $500 in GDP, for instance, is weighted 

more heavily in a country with a per-capita GDP of $2,000 than in one with a per-capita GDP of 

$40,000. The main argument for this approach is that a loss of $500 in a poor country causes a 

greater reduction in utility or welfare than does the same loss in a wealthy nation.

Notwithstanding the theoretical claims on behalf of equity weighting, the interagency group 

concluded that this approach would not be appropriate for estimating a SCC value used in 

domestic regulatory analysis.g For this reason, the group concluded that using the global (rather 

than domestic) value, without equity weighting, is the appropriate approach. 

14A.4.2.2 Domestic SCC

As an empirical matter, the development of a domestic SCC is greatly complicated by the 

relatively few region- or country-specific estimates of the SCC in the literature. One potential 

source of estimates comes from the FUND model. The resulting estimates suggest that the ratio 

of domestic to global benefits of emission reductions varies with key parameter assumptions. For 

example, with a 2.5 or 3 percent discount rate, the U.S. benefit is about 7–10 percent of the 

global benefit, on average, across the scenarios analyzed. Alternatively, if the fraction of GDP 

lost due to climate change is assumed to be similar across countries, the domestic benefit would 

be proportional to the U.S. share of global GDP, which is currently about 23 percent.h

On the basis of this evidence, the interagency workgroup determined that a range of 

values from 7 to 23 percent should be used to adjust the global SCC to calculate domestic 

effects. Reported domestic values should use this range. It is recognized that these values are 

approximate, provisional, and highly speculative. There is no a priori reason why domestic 

benefits should be a constant fraction of net global damages over time. Further, FUND does not 

account for how damages in other regions could affect the United States (e.g., global migration, 

economic and political destabilization). If more accurate methods for calculating the domestic 

SCC become available, the Federal government will examine these to determine whether to 

update its approach. 

14A.4.3 Valuing Non-CO2 Emissions

While CO2 is the most prevalent greenhouse gas emitted into the atmosphere, the U.S. 

included five other greenhouse gases in its recent endangerment finding: methane, nitrous oxide, 

g It is plausible that a loss of $X inflicts more serious harm on a poor nation than on a wealthy one, but development 

of the appropriate “equity weight” is challenging. Emissions reductions also impose costs, and hence a full account 

would have to consider that a given cost of emissions reductions imposes a greater utility or welfare loss on a poor 

nation than on a wealthy one. Even if equity weighting—for both the costs and benefits of emissions reductions—is 

appropriate when considering the utility or welfare effects of international action, the interagency group concluded 

that it should not be used in developing an SCC for use in regulatory policy at this time. 

h Based on 2008 GDP (in current US dollars) from the World Bank Development Indicators Report. 

14A-12 

 
hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride. The climate impact of these 

gases is commonly discussed in terms of their 100-year global warming potential (GWP). GWP 

measures the ability of different gases to trap heat in the atmosphere (i.e., radiative forcing per 

unit of mass) over a particular timeframe relative to CO2. However, because these gases differ in 

both radiative forcing and atmospheric lifetimes, their relative damages are not constant over 

time. For example, because methane has a short lifetime, its impacts occur primarily in the near 

term and thus are not discounted as heavily as those caused by longer-lived gases. Impacts other 

than temperature change also vary across gases in ways that are not captured by GWP. For 

instance, CO2 emissions, unlike methane and other greenhouse gases, contribute to ocean 

acidification. Likewise, damages from methane emissions are not offset by the positive effect of 

CO2 fertilization. Thus, transforming gases into CO2-equivalents using GWP, and then 

multiplying the carbon-equivalents by the SCC, would not result in accurate estimates of the 

social costs of non-CO2 gases.

In light of these limitations, and the significant contributions of non-CO2 emissions to 

climate change, further research is required to link non-CO2 emissions to economic impacts.

Such work would feed into efforts to develop a monetized value of reductions in non-CO2

greenhouse gas emissions. As part of ongoing work to further improve the SCC estimates, the 

interagency group hopes to develop methods to value these other greenhouse gases. The goal is 

to develop these estimates by the time we issue revised SCC estimates for CO2 emissions.

14A.4.4 Equilibrium Climate Sensitivity

Equilibrium climate sensitivity (ECS) is a key input parameter for the DICE, PAGE, and 

FUND models.i It is defined as the long-term increase in the annual global-average surface 

temperature from a doubling of atmospheric CO2 concentration relative to pre-industrial levels 

(or stabilization at a concentration of approximately 550 parts per million (ppm)). Uncertainties 

in this important parameter have received substantial attention in the peer-reviewed literature.

The most authoritative statement about equilibrium climate sensitivity appears in the 

Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC):

Basing our assessment on a combination of several independent lines of evidence...including 

observed climate change and the strength of known feedbacks simulated in [global climate 

models], we conclude that the global mean equilibrium warming for doubling CO2, or 

‘equilibrium climate sensitivity,’ is likely to lie in the range 2 °C to 4.5 °C, with a most likely 

value of about 3 °C. Equilibrium climate sensitivity is very likely larger than 1.5 °C.j

For fundamental physical reasons as well as data limitations, values substantially higher than 

4.5 °C still cannot be excluded, but agreement with observations and proxy data is generally 

i The equilibrium climate sensitivity includes the response of the climate system to increased greenhouse gas 

concentrations over the short to medium term (up to 100–200 years), but it does not include long-term feedback 

effects due to possible large-scale changes in ice sheets or the biosphere, which occur on a time scale of many 

hundreds to thousands of years (e.g., Hansen et al. 2007).

j This is in accord with the judgment that it “is likely to lie in the range 2 °C to 4.5 °C” and the IPCC definition of 

“likely” as greater than 66 percent probability (Le Treut et al. 2007). “Very likely” indicates a greater than 90 

percent probability.

14A-13 

 
worse for those high values than for values in the 2 °C to 4.5 °C range. (Meehl et al. 2007, p. 

799) 

After consulting with several lead authors of this chapter of the IPCC report, the 

interagency workgroup selected four candidate probability distributions and calibrated them to 

be consistent with the above statement: Roe and Baker (2007), log-normal, gamma, and Weibull. 

Table 17A.4.1 gives summary statistics for the four calibrated distributions.

Table 14A.4.1 Summary Statistics for Four Calibrated Climate Sensitivity Distributions

Rank Roe & Baker Log-Normal Gamma Weibull

Pr(ECS < 1.5 °C) 0.013 0.050 0.070 0.102

Pr(2 °C < ECS < 4.5 °C) 0.667 0.667 0.667 0.667

5th Percentile 1.72 1.49 1.37 1.13

10th Percentile 1.91 1.74 1.65 1.48

Mode 2.34 2.52 2.65 2.90

Median (50th percentile) 3.00 3.00 3.00 3.00

Mean 3.50 3.28 3.19 3.07

90th Percentile 5.86 5.14 4.93 4.69

95th Percentile 7.14 5.97 5.59 5.17

Each distribution was calibrated by applying three constraints from the IPCC: 

(1) a median equal to 3 °C, to reflect the judgment of “a most likely value of about 3 °C;”k

(2) two-thirds probability that the equilibrium climate sensitivity lies between 2 and 4.5 °C; 

and

(3) zero probability that it is less than 0 °C or greater than 10 °C (Hegerl et al. 2006, p. 721). 

We selected the calibrated Roe and Baker distribution from the four candidates for two 

reasons. First, the Roe and Baker distribution is the only one of the four that is based on a 

theoretical understanding of the response of the climate system to increased greenhouse gas 

concentrations (Roe and Baker 2007; Roe 2008). In contrast, the other three distributions are 

mathematical functions that are arbitrarily chosen based on simplicity, convenience, and general 

shape. The Roe and Baker distribution results from three assumptions about climate response: 

(1) absent feedback effects, the equilibrium climate sensitivity is equal to 1.2 °C; (2) feedback 

factors are proportional to the change in surface temperature; and (3) uncertainties in feedback 

factors are normally distributed. There is widespread agreement on the first point and the second 

and third points are common assumptions. 

Second, the calibrated Roe and Baker distribution better reflects the IPCC judgment that 

“values substantially higher than 4.5°C still cannot be excluded.” Although the IPCC made no 

k Strictly speaking, “most likely” refers to the mode of a distribution rather than the median, but common usage 

would allow the mode, median, or mean to serve as candidates for the central or “most likely” value and the IPCC 

report is not specific on this point. For the distributions we considered, the median was between the mode and the 

mean. For the Roe and Baker distribution, setting the median equal to 3 °C, rather than the mode or mean, gave a 

95th percentile that is more consistent with IPCC judgments and the literature. For example, setting the mean and 

mode equal to 3 °C produced 95th percentiles of 5.6 and 8.6 °C, respectively, which are in the lower and upper end 

of the range in the literature. Finally, the median is closer to 3 °C than is the mode for the truncated distributions 

selected by the IPCC (Hegerl et al. 2006); the average median is 3.1 °C and the average mode is 2.3 °C, which is 

most consistent with a Roe and Baker distribution with the median set equal to 3 °C.

14A-14 

 
quantitative judgment, the 95th percentile of the calibrated Roe & Baker distribution (7.1 °C) is 

much closer to the mean and the median (7.2 °C) of the 95th percentiles of 21 previous studies 

summarized by Newbold and Daigneault (2009). It is also closer to the mean (7.5 °C) and 

median (7.9 °C) of the nine truncated distributions examined by the IPCC (Hegerl et al. 2006) 

than are the 95th percentiles of the three other calibrated distributions (5.2–6.0 °C). 

Finally, we note the IPCC judgment that the equilibrium climate sensitivity “is very 

likely larger than 1.5°C.” Although the calibrated Roe & Baker distribution, for which the 

probability of equilibrium climate sensitivity being greater than 1.5 °C is almost 99 percent, is 

not inconsistent with the IPCC definition of “very likely” as “greater than 90 percent 

probability,” it reflects a greater degree of certainty about very low values of ECS than was 

expressed by the IPCC. 

To show how the calibrated Roe and Baker distribution compares to different estimates 

of the probability distribution function of equilibrium climate sensitivity in the empirical 

literature, Figure 14A.4.3 overlays it on Figure 17A.9.2 from the IPCC Fourth Assessment 

Report. These functions are scaled to integrate to unity between 0 °C and 10 °C. The horizontal 

bars show the respective 5 percent to 95 percent ranges; dots indicate the median estimate.l

Figure 14A.4.3 Estimates of the Probability Density Function for Equilibrium Climate 

Sensitivity

l The estimates based on instrumental data are from Andronova and Schlesinger (2001), Forest et al. (2002; dashed 

line, anthropogenic forcings only), Forest et al. (2006; solid line, anthropogenic and natural forcings), Gregory et al. 

(2002), Knutti et al. (2002), Frame et al. (2005), and Forster and Gregory (2006). Hegerl et al. (2006) are based on 

multiple palaeoclimatic reconstructions of north hemisphere mean temperatures over the last 700 years. Also shown 

are the 5–95 percent approximate ranges for two estimates from the last glacial maximum (dashed, Annan et al. 

2005; solid, Schneider von Deimling et al. 2006), which are based on models with different structural properties.

14A-15 

 
14A.4.5 Socio-Economic and Emissions Trajectories

Another key issue considered by the interagency group is how to select the set of socioeconomic and emissions parameters for use in PAGE, DICE, and FUND. Socio-economic 

pathways are closely tied to climate damages because, all else equal, more and wealthier people 

tend to emit more greenhouse gases and also have a higher (absolute) willingness to pay to avoid 

climate disruptions. For this reason, we consider how to model several input parameters in 

tandem: GDP, population, CO2 emissions, and non-CO2 radiative forcing. A wide variety of 

scenarios have been developed and used for climate change policy simulations (e.g., SRES 2000, 

CCSP 2007, EMF 2009). In determining which scenarios are appropriate for inclusion, we aimed 

to select scenarios that span most of the plausible ranges of outcomes for these variables. 

To accomplish this task in a transparent way, we decided to rely on the recent Stanford 

Energy Modeling Forum exercise, EMF-22, which uses ten well-recognized models to evaluate 

substantial, coordinated global action to meet specific stabilization targets. A key advantage of 

relying on these data is that GDP, population, and emission trajectories are internally consistent 

for each model and scenario evaluated. The EMF-22 modeling effort also is preferable to the 

IPCC SRES due to their age (SRES were developed in 1997) and the fact that 3 of 4 of the SRES 

scenarios are now extreme outliers in one or more variables. Although the EMF-22 scenarios 

have not undergone the same level of scrutiny as the SRES scenarios, they are recent, peerreviewed, published, and publicly available. 

To estimate the SCC for use in evaluating domestic policies that will have a small effect 

on global cumulative emissions, we use socio-economic and emission trajectories that span a 

range of plausible scenarios. Five trajectories were selected from EMF-22 (Table 14A.4.2 ). Four 

of these represent potential business-as-usual (BAU) growth in population, wealth, and 

emissions and are associated with CO2 (only) concentrations ranging from 612 to 889 ppm in 

2100. One represents an emissions pathway that achieves stabilization at 550 ppm CO2e (i.e., 

CO2-only concentrations of 425–484 ppm or a radiative forcing of 3.7 W/m2) in 2100, a lowerthan-BAU trajectory.m Out of the 10 models included in the EMF-22 exercise, we selected the 

trajectories used by MiniCAM, MESSAGE, IMAGE, and the optimistic scenario from MERGE. 

For the BAU pathways, we used the GDP, population, and emission trajectories from each of 

these four models. For the 550 ppm CO2e scenario, we averaged the GDP, population, and 

emission trajectories implied by these same four models.

m Such an emissions path would be consistent with widespread action by countries to mitigate GHG emissions, 

though it could also result from technological advances. It was chosen because it represents the most stringent case 

analyzed by the EMF-22 where all the models converge: a 550 ppm, not to exceed, full participation scenario.

14A-16 

 
Table 14A.4.2 Socioeconomic and Emissions Projections from Select EMF-22 Reference 

Scenarios

Reference Fossil and Industrial CO2 Emissions

GtCO2/yr

EMF – 22 Based Scenarios 2000 2010 2020 2030 2050 2100

IMAGE 26.6 31.9 36.9 40.0 45.3 60.1

MERGE Optimistic 24.6 31.5 37.6 45.1 66.5 117.9

MESSAGE 26.8 29.2 37.6 42.1 43.5 42.7

MiniCAM 26.5 31.8 38.0 45.1 57.8 80.5

550 ppm average 26.2 31.1 33.2 32.4 20.0 12.8

Reference GDP

market exchange rates in trillion 2005$n

EMF – 22 Based Scenarios 2000 2010 2020 2030 2050 2100

IMAGE 38.6 53.0 73.5 97.2 156.3 396.6

MERGE Optimistic 36.3 45.9 59.7 76.8 122.7 268.0

MESSAGE 38.1 52.3 69.4 91.4 153.7 334.9

MiniCAM 36.1 47.4 60.8 78.9 125.7 369.5

550 ppm average 37.1 49.6 65.6 85.5 137.4 337.9

Global Population

billions

EMF – 22 Based Scenarios 2000 2010 2020 2030 2050 2100

IMAGE 6.1 6.9 7.6 8.2 9.0 9.1

MERGE Optimistic 6.0 6.8 7.5 8.2 9.0 9.7

MESSAGE 6.1 6.9 7.7 8.4 9.4 10.4

MiniCAM 6.0 6.8 7.5 8.1 8.8 8.7

550 ppm average 6.1 6.8 7.6 8.2 8.7 9.1

We explore how sensitive the SCC is to various assumptions about how the future will 

evolve without prejudging what is likely to occur. The interagency group considered formally 

assigning probability weights to different states of the world, but this proved challenging to do in 

an analytically rigorous way given the dearth of information on the likelihood of a full range of 

future socio-economic pathways. 

There are a number of caveats. First, EMF BAU scenarios represent the modelers’ 

judgment of the most likely pathway absent mitigation policies to reduce greenhouse gas 

emissions, rather than the wider range of possible outcomes. Nevertheless, these views of the 

n While the EMF-22 models used market exchange rates (MER) to calculate global GDP, it is also possible to use 

purchasing power parity (PPP), which takes into account the different price levels across countries, so it more 

accurately describes relative standards of living across countries. MERs tend to make low-income countries appear 

poorer than they actually are. Because many models assume convergence in per capita income over time, use of 

MER-adjusted GDP gives rise to projections of higher economic growth in low income countries. There is an 

ongoing debate about how much this will affect estimated climate impacts. Critics of the use of MER argue that it 

leads to overstated economic growth and hence a significant upward bias in projections of greenhouse gas 

emissions, and unrealistically high future temperatures (e.g., Castles and Henderson 2003). Others argue that 

convergence of the emissions-intensity gap across countries at least partially offset the overstated income gap so that 

differences in exchange rates have less of an effect on emissions (Holtsmark and Alfsen, 2005; Tol, 2006). 

Nordhaus (2007b) argues that the ideal approach is to use superlative PPP accounts (i.e., using cross-sectional PPP 

measures for relative incomes and outputs and national accounts price and quantity indexes for time-series 

extrapolations). However, he notes that it important to keep this debate in perspective; it is by no means clear that 

exchange-rate-conversion issues are as important as uncertainties about population, technological change, or the 

many geophysical uncertainties.

14A-17 

 
most likely outcome span a wide range, from the more optimistic (e.g., abundant low-cost, lowcarbon energy) to more pessimistic (e.g., constraints on the availability of nuclear and 

renewables).o

 Second, the socio-economic trajectories associated with a 550 ppm CO2e 

concentration scenario are not derived from an assessment of what policy is optimal from a 

benefit-cost standpoint. Rather, it is indicative of one possible future outcome. The emission 

trajectories underlying some BAU scenarios (e.g., MESSAGE’s 612 ppm) also are consistent 

with some modest policy action to address climate change.p

 We chose not to include socioeconomic trajectories that achieve even lower GHG concentrations at this time, given the 

difficulty many models had in converging to meet these targets.

For comparison purposes, the Energy Information Agency in its 2009 Annual Energy 

Outlook projected that global CO2 emissions will grow to 30.8, 35.6, and 40.4 gigatons in 2010, 

2020, and 2030, respectively, while world GDP is projected to be $51.8, $71.0 and $93.9 trillion 

(2005$ using market exchange rates) in 2010, 2020, and 2030, respectively. These projections 

are consistent with one or more EMF-22 scenarios. Likewise, the United Nations’ 2008 

Population Prospect projects population will grow from 6.1 billion people in 2000 to 9.1 billion 

people in 2050, which is close to the population trajectories for the IMAGE, MiniCAM, and 

MERGE models.

In addition to fossil and industrial CO2 emissions, each EMF scenario provides 

projections of methane, nitrous oxide, fluorinated greenhouse gases, and net land use CO2

emissions out to 2100. These assumptions also are used in the three models while retaining the 

default radiative forcings due to other factors (e.g., aerosols and other gases). See the Appendix 

for greater detail.

14A.4.6 Discount Rate

The choice of a discount rate, especially over long periods of time, raises highly 

contested and exceedingly difficult questions of science, economics, philosophy, and law. 

Although it is well understood that the discount rate has a large influence on the current value of 

future damages, there is no consensus about what rates to use in this context. Because CO2

emissions are long-lived, subsequent damages occur over many years. In calculating the SCC, 

we first estimate the future damages to agriculture, human health, and other market and nonmarket sectors from an additional unit of CO2 emitted in a particular year in terms of reduced 

consumption (or consumption equivalents) due to the impacts of elevated temperatures, as 

represented in each of the three IAMs. Then we discount the stream of future damages to its 

present value in the year when the additional unit of emissions was released using the selected 

discount rate, which is intended to reflect society’s marginal rate of substitution between 

consumption in different time periods. 

o For instance, in the MESSAGE model’s reference case total primary energy production from nuclear, biomass, and 

non-biomass renewables is projected to increase from about 15 percent of total primary energy in 2000 to 54 percent 

in 2100. In comparison, the MiniCAM reference case shows 10 percent in 2000 and 21 percent in 2100. 

p For example, MiniCAM projects if all non-US OECD countries reduce CO2 emissions to 83 percent below 2005 

levels by 2050 (per the G-8 agreement) but all other countries continue along a BAU path CO2 concentrations in 

2100 would drop from 794 ppmv in its reference case to 762 ppmv.

14A-18 

 
For rules with both intra- and intergenerational effects, agencies traditionally employ 

constant discount rates of both 3 percent and 7 percent in accordance with OMB Circular A-4. 

As Circular A-4 acknowledges, however, the choice of discount rate for intergenerational 

problems raises distinctive problems and presents considerable challenges. After reviewing those 

challenges, Circular A-4 states, “If your rule will have important intergenerational benefits or 

costs you might consider a further sensitivity analysis using a lower but positive discount rate in 

addition to calculating net benefits using discount rates of 3 and 7 percent.” For the specific 

purpose of developing the SCC, we adapt and revise that approach here. 

Arrow et al. (1996) outlined two main approaches to determine the discount rate for 

climate change analysis, which they labeled “descriptive” and “prescriptive.” The descriptive 

approach reflects a positive (non-normative) perspective based on observations of people’s 

actual choices—e.g., savings versus consumption decisions over time, and allocations of savings 

among more and less risky investments. Advocates of this approach generally call for inferring 

the discount rate from market rates of return “because of a lack of justification for choosing a 

social welfare function that is any different than what decision makers [individuals] actually use” 

(Arrow et al. 1996). 

One theoretical foundation for the cost-benefit analyses in which the social cost of carbon 

will be used—the Kaldor-Hicks potential-compensation test—also suggests that market rates 

should be used to discount future benefits and costs, because it is the market interest rate that 

would govern the returns potentially set aside today to compensate future individuals for climate 

damages that they bear (e.g., Just et al. 2004). As some have noted, the word “potentially” is an 

important qualification; there is no assurance that such returns will actually be set aside to 

provide compensation, and the very idea of compensation is difficult to define in the 

intergenerational context. On the other hand, societies provide compensation to future 

generations through investments in human capital and the resulting increase in knowledge, as 

well as infrastructure and other physical capital.

The prescriptive approach specifies a social welfare function that formalizes the 

normative judgments that the decision-maker wants explicitly to incorporate into the policy 

evaluation—e.g., how inter-personal comparisons of utility should be made, and how the welfare 

of future generations should be weighed against that of the present generation. Ramsey (1928), 

for example, has argued that it is “ethically indefensible” to apply a positive pure rate of time 

preference to discount values across generations, and many agree with this view. 

Other concerns also motivate making adjustments to descriptive discount rates. In 

particular, it has been noted that the preferences of future generations with regard to 

consumption versus environmental amenities may not be the same as those today, making the 

current market rate on consumption an inappropriate metric by which to discount future climaterelated damages. Others argue that the discount rate should be below market rates to correct for 

market distortions and uncertainties or inefficiencies in intergenerational transfers of wealth, 

which in the Kaldor-Hicks logic are presumed to compensate future generations for damage (a 

potentially controversial assumption, as noted above; Arrow et al. 1996, Weitzman 1999). 

Further, a legitimate concern about both descriptive and prescriptive approaches is that 

they tend to obscure important heterogeneity in the population. The utility function that underlies 

14A-19 
the prescriptive approach assumes a representative agent with perfect foresight and no credit 

constraints. This is an artificial rendering of the real world that misses many of the frictions that 

characterize individuals’ lives and indeed the available descriptive evidence supports this. For 

instance, many individuals smooth consumption by borrowing with credit cards that have 

relatively high rates. Some are unable to access traditional credit markets and rely on payday 

lending operations or other high cost forms of smoothing consumption. Whether one puts greater 

weight on the prescriptive or descriptive approach, the high interest rates that credit-constrained 

individuals accept suggest that some account should be given to the discount rates revealed by 

their behavior. 

We draw on both approaches but rely primarily on the descriptive approach to inform the 

choice of discount rate. With recognition of its limitations, we find this approach to be the most 

defensible and transparent given its consistency with the standard contemporary theoretical 

foundations of benefit-cost analysis and with the approach required by OMB’s existing guidance. 

The logic of this framework also suggests that market rates should be used for discounting future 

consumption-equivalent damages. Regardless of the theoretical approach used to derive the 

appropriate discount rate(s), we note the inherent conceptual and practical difficulties of 

adequately capturing consumption trade-offs over many decades or even centuries. While relying 

primarily on the descriptive approach in selecting specific discount rates, the interagency group 

has been keenly aware of the deeply normative dimensions of both the debate over discounting 

in the intergenerational context and the consequences of selecting one discount rate over another. 

14A.4.6.1 Historically Observed Interest Rates

In a market with no distortions, the return to savings would equal the private return on 

investment, and the market rate of interest would be the appropriate choice for the social 

discount rate. In the real world risk, taxes, and other market imperfections drive a wedge 

between the risk-free rate of return on capital and the consumption rate of interest. Thus, the 

literature recognizes two conceptual discount concepts—the consumption rate of interest and the 

opportunity cost of capital. 

According to OMB’s Circular A-4, it is appropriate to use the rate of return on capital 

when a regulation is expected to displace or alter the use of capital in the private sector. In this 

case, OMB recommends Agencies use a discount rate of 7 percent. When regulation is expected 

to primarily affect private consumption—for instance, via higher prices for goods and services—

a lower discount rate of 3 percent is appropriate to reflect how private individuals trade-off 

current and future consumption. 

The interagency group examined the economics literature and concluded that the 

consumption rate of interest is the correct concept to use in evaluating the benefits and costs of a 

marginal change in carbon emissions (Lind 1990, Arrow et al., 1996, Arrow 2000). The 

consumption rate of interest also is appropriate when the impacts of a regulation are measured in 

consumption (-equivalent) units, as is done in the three integrated assessment models used for 

estimating the SCC.

Individuals use a variety of savings instruments that vary with risk level, time horizon, 

and tax characteristics. The standard analytic framework used to develop intuition about the 

14A-20 
discount rate typically assumes a representative agent with perfect foresight and no credit 

constraints. The risk-free rate is appropriate for discounting certain future benefits or costs, but 

the benefits calculated by IAMs are uncertain. To use the risk-free rate to discount uncertain 

benefits, these benefits first must be transformed into “certainty equivalents,” i.e., the maximum 

certain amount that we would exchange for the uncertain amount. However, the calculation of 

the certainty-equivalent requires first estimating the correlation between the benefits of the 

policy and baseline consumption. 

If the IAM projections of future impacts represent expected values (not certaintyequivalent values), then the appropriate discount rate generally does not equal the risk-free rate. 

If the benefits of the policy tend to be high in those states of the world in which consumption is 

low, then the certainty-equivalent benefits will be higher than the expected benefits (and vice 

versa). Since many (though not necessarily all) of the important impacts of climate change will 

flow through market sectors such as agriculture and energy, and since willingness to pay for 

environmental protections typically increases with income, we might expect a positive (though 

not necessarily perfect) correlation between the net benefits from climate policies and market 

returns. This line of reasoning suggests that the proper discount rate would exceed the riskless 

rate. Alternatively, a negative correlation between the returns to climate policies and market 

returns would imply that a discount rate below the riskless rate is appropriate. 

This discussion suggests that both the post-tax riskless and risky rates can be used to 

capture individuals’ consumption-equivalent interest rate. As a measure of the post-tax riskless 

rate, we calculate the average real return from Treasury notes over the longest time period 

available (those from Newell and Pizer 2003) and adjust for Federal taxes (the average marginal 

rate from tax years 2003 through 2006 is around 27 percent).q This calculation produces a real 

interest rate of about 2.7 percent, which is roughly consistent with Circular A-4’s 

recommendation to use 3 percent to represent the consumption rate of interest.r A measure of the 

post-tax risky rate for investments whose returns are positively correlated with overall equity 

market returns can be obtained by adjusting pre-tax rates of household returns to risky 

investments (approximately 7 percent) for taxes yields a real rate of roughly 5 percent.s

14A.4.6.2 The Ramsey Equation 

Ramsey discounting also provides a useful framework to inform the choice of a discount 

rate. Under this approach, the analyst applies either positive or normative judgments in selecting 

values for the key parameters of the Ramsey equation: η (coefficient of relative risk aversion or 

q The literature argues for a risk-free rate on government bonds as an appropriate measure of the consumption rate of 

interest. Arrow (2000) suggests that it is roughly 3-4 percent. OMB cites evidence of a 3.1 percent pre-tax rate for 

10-year Treasury notes in the A-4 guidance. Newell and Pizer (2003) find real interest rates between 3.5 and 4 

percent for 30-year Treasury securities. r The positive approach reflects how individuals make allocation choices across time, but it is important to keep in 

mind that we wish to reflect preferences for society as a whole, which generally has a longer planning horizon. s Cambell et al. (2001) estimates that the annual real return from stocks for 1900-1995 was about 7 percent. The 

annual real rate of return for the S&P 500 from 1950–2008 was about 6.8 percent. In the absence of a better way to 

population-weight the tax rates, we use the middle of the 20–40 percent range to derive a post-tax interest rate 

(Kotlikoff and Rapson 2006).

14A-21 

 
elasticity of the marginal utility of consumption) and ρ (pure rate of time preference).t These are 

then combined with g (growth rate of per-capita consumption) to equal the interest rate at which 

future monetized damages are discounted: ρ + η∙g.

u

 In the simplest version of the Ramsey model, 

with an optimizing representative agent with perfect foresight, what we are calling the “Ramsey 

discount rate,” ρ + η∙g, will be equal to the rate of return to capital, i.e., the market interest rate.

A review of the literature provides some guidance on reasonable parameter values for the 

Ramsey discounting equation, based on both prescriptive and descriptive approaches. 

• η. Most papers in the climate change literature adopt values for η in the range of 0.5 to 3 

(Weitzman cites plausible values as those ranging from 1 to 4), although not all authors 

articulate whether their choice is based on prescriptive or descriptive reasoning.v

Dasgupta (2008) argues that η should be greater than 1 and may be as high as 3, since η

equal to 1 suggests savings rates that do not conform to observed behavior. 

• ρ. With respect to the pure rate of time preference, most papers in the climate change 

literature adopt values for ρ in the range of 0 to 3 percent per year. The very low rates 

tend to follow from moral judgments involving intergenerational neutrality. Some have 

argued that to use any value other than ρ = 0 would unjustly discriminate against future 

generations (e.g., Arrow et al. 1996, Stern 2006). However, even in an inter-generational 

setting, it may make sense to use a small positive pure rate of time preference because of 

the small probability of unforeseen cataclysmic events (Stern 2006). 

• g. A commonly accepted approximation is around 2 percent per year. For the socioeconomic scenarios used for this exercise, the EMF models assume that g is about 1.5–2 

percent to 2100. 

t The parameter ρ measures the pure rate of time preference: people’s behavior reveals a preference for an increase 

in utility today versus the future. Consequently, it is standard to place a lower weight on utility in the future. The 

parameter η captures diminishing marginal utility: consumption in the future is likely to be higher than consumption 

today, so diminishing marginal utility of consumption implies that the same monetary damage will cause a smaller 

reduction of utility for wealthier individuals, either in the future or in current generations. If η = 0, then a one dollar 

increase in income is equally valuable regardless of level of income; if η = 1, then a one percent increase in income 

is equally valuable no matter the level of income; and if η > 1, then a one percent increase in income is less valuable 

to wealthier individuals. u In this case, g could be taken from the selected EMF socioeconomic scenarios or alternative assumptions about the 

rate of consumption growth.

v Empirical estimates of η span a wide range of values. A benchmark value of 2 is near the middle of the range of 

values estimated or used by Szpiro (1986), Hall and Jones (2007), Arrow (2007), Dasgupta (2006, 2008), Weitzman 

(2007, 2009), and Nordhaus (2008). However, Chetty (2006) developed a method of estimating η using data on 

labor supply behavior. He shows that existing evidence of the effects of wage changes on labor supply imposes a 

tight upper bound on the curvature of utility over wealth (CRRA < 2) with the mean implied value of 0.71 and 

concludes that the standard expected utility model cannot generate high levels of risk aversion without contradicting 

established facts about labor supply. Recent work has jointly estimated the components of the Ramsey equation. 

Evans and Sezer (2005) estimate η = 1.49 for 22 OECD countries. They also estimate ρ = 1.08 percent per year 

using data on mortality rates. Anthoff et al. (2009b) estimate η = 1.18, and ρ = 1.4 percent. When they multiply the 

bivariate probability distributions from their work and Evans and Sezer (2005) together, they find η = 1.47, and ρ = 

1.07. 

14A-22 

 
Some economists and non-economists have argued for constant discount rates below 2 

percent based on the prescriptive approach. When grounded in the Ramsey framework, 

proponents of this approach have argued that a ρ of zero avoids giving preferential treatment to 

one generation over another. The choice of η has also been posed as an ethical choice linked to 

the value of an additional dollar in poorer countries compared to wealthier ones. Stern (2006) 

applies this perspective through his choice of ρ = 0.1 percent per year, η = 1 and g = 1.3 percent 

per year, which yields an annual discount rate of 1.4 percent. In the context of permanent income 

savings behavior, however, Stern’s assumptions suggest that individuals would save 93 percent 

of their income.w

Recently, Stern (2008) revisited the values used in Stern (2006), stating that there is a 

case to be made for raising η due to the amount of weight lower values place on damages far in 

the future (over 90 percent of expected damages occur after 2200 with η = 1). Using Stern’s 

assumption that ρ = 0.1 percent, combined with a η of 1.5 to 2 and his original growth rate, 

yields a discount rate greater 2 percent.

We conclude that arguments made under the prescriptive approach can be used to justify 

discount rates between roughly 1.4 and 3.1 percent. In light of concerns about the most 

appropriate value for η, we find it difficult to justify rates at the lower end of this range under the 

Ramsey framework.

14A.4.6.3 Accounting for Uncertainty in the Discount Rate

While the consumption rate of interest is an important driver of the benefits estimate, it is 

uncertain over time. Ideally, we would formally model this uncertainty, just as we do for climate 

sensitivity. Weitzman (1998, 2001) showed theoretically and Newell and Pizer (2003) and 

Panipoulou et al. (2004) confirm empirically that discount rate uncertainty can have a large 

effect on net present values. A main result from these studies is that if there is a persistent 

element to the uncertainty in the discount rate (e.g., the rate follows a random walk), then it will 

result in an effective (or certainty-equivalent) discount rate that declines over time. 

Consequently, lower discount rates tend to dominate over the very long term (Weitzman 1998, 

1999, 2001; Newell and Pizer 2003; Panipoulou et al. (2004); Gollier 2008; Summers and 

Zeckhauser 2008; and Gollier and Weitzman 2009). 

The proper way to model discount rate uncertainty remains an active area of research.

Newell and Pizer (2003) employ a model of how long-term interest rates change over time to 

forecast future discount rates. Their model incorporates some of the basic features of how 

interest rates move over time, and its parameters are estimated based on historical observations 

of long-term rates. Subsequent work on this topic, most notably Panipoulou et al. (2004), uses 

more general models of interest rate dynamics to allow for better forecasts. Specifically, the 

volatility of interest rates depends on whether rates are currently low or high and variation in the 

level of persistence over time. 

w Stern (2008) argues that building in a positive rate of exogenous technical change over time reduces the implied 

savings rate and that η at or above 2 are inconsistent with observed behavior with regard to equity. (At the same 

time, adding exogenous technical change—all else equal—would increase g as well.)

14A-23 

 
 While Newell and Pizer (2003) and Panipoulou et al. (2004) attempt formally to model 

uncertainty in the discount rate, others argue for a declining scale of discount rates applied over 

time (e.g., Weitzman 2001, and the UK’s “Green Book” for regulatory analysis). This approach 

uses a higher discount rate initially, but applies a graduated scale of lower discount rates further 

out in time.x A key question that has emerged with regard to both of these approaches is the 

trade-off between potential time inconsistency and giving greater weight to far future outcomes 

(see the EPA Science Advisory Board’s recent comments on this topic as part of its review of 

their Guidelines for Economic Analysis).y

14A.4.6.4 The Discount Rates Selected for Estimating SCC

In light of disagreement in the literature on the appropriate market interest rate to use in 

this context and uncertainty about how interest rates may change over time, we use three 

discount rates to span a plausible range of certainty-equivalent constant discount rates: 2.5, 3, 

and 5 percent per year. Based on the review in the previous sections, the interagency workgroup 

determined that these three rates reflect reasonable judgments under both descriptive and 

prescriptive approaches.

The central value (3 percent) is consistent with estimates provided in the economics 

literature and OMB’s Circular A-4 guidance for the consumption rate of interest. As previously 

mentioned, the consumption rate of interest is the correct discounting concept to use when future 

damages from elevated temperatures are estimated in consumption-equivalent units. Further, 3 

percent roughly corresponds to the after-tax riskless interest rate. The upper value of 5 percent is 

included to represent the possibility that climate damages are positively correlated with market 

returns. Additionally, this discount rate may be justified by the high interest rates that many 

consumers use to smooth consumption across periods. 

The low value (2.5 percent) is included to incorporate the concern that interest rates are 

highly uncertain over time. It represents the average certainty-equivalent rate using the meanreverting and random walk approaches from Newell and Pizer (2003) starting at a discount rate 

of 3 percent. Using this approach, the certainty equivalent is about 2.2 percent using the random 

walk model and 2.8 percent using the mean reverting approach.z

 Without giving preference to a 

particular model, the average of the two rates is 2.5 percent. Further, a rate below the riskless 

rate would be justified if climate investments are negatively correlated with the overall market 

rate of return. Use of this lower value also responds to certain judgments using the prescriptive 

or normative approach and to ethical objections that have been raised about rates of 3 percent or 

higher. 

x For instance, the UK applies a discount rate of 3.5 percent to the first 30 years; 3 percent for years 31–75; 2.5 

percent for years 76–125; 2 percent for years 126–200; 1.5 percent for years 201–300; and 1 percent after 300 years. 

As a sensitivity, it recommends a discount rate of 3 percent for the first 30 years, also decreasing over time. 

y Uncertainty in future damages is distinct from uncertainty in the discount rate. Weitzman (2008) argues that 

Stern’s choice of a low discount rate was “right for the wrong reasons.” He demonstrates how the damages from a 

low probability, catastrophic event far in the future dominate the effect of the discount rate in a present value 

calculation and result in an infinite willingness-to-pay for mitigation today. Newbold and Daigneault, (2009) and 

Nordhaus (2009) find that Weitzman’s result is sensitive to the functional forms chosen for climate sensitivity, 

utility, and consumption. Summers and Zeckhauser (2008) argue that uncertainty in future damages can also work in 

the other direction by increasing the benefits of waiting to learn the appropriate level of mitigation required. 

z Calculations done by Pizer et al. using the original simulation program from Newell and Pizer (2003).

14A-24 

 
14A.5 REVISED SCC ESTIMATES

Our general approach to estimating SCC values is to run the three integrated assessment 

models (FUND, DICE, and PAGE) using the following inputs agreed upon by the interagency 

group: 

• A Roe and Baker distribution for the climate sensitivity parameter bounded between 0 

and 10 with a median of 3 °C and a cumulative probability between 2 and 4.5 °C of twothirds. 

• Five sets of GDP, population and carbon emissions trajectories based on EMF-22. 

• Constant annual discount rates of 2.5, 3, and 5 percent. 

Because the climate sensitivity parameter is modeled probabilistically, and because 

PAGE and FUND incorporate uncertainty in other model parameters, the final output from each 

model run is a distribution over the SCC in year t. 

For each of the IAMS, the basic computational steps for calculating the SCC in a particular year t

are:

1. Input the path of emissions, GDP, and population from the selected EMF-22 scenarios, 

and the extrapolations based on these scenarios for post-2100 years.

2. Calculate the temperature effects and (consumption-equivalent) damages in each year 

resulting from the baseline path of emissions. 

a. In PAGE, the consumption-equivalent damages in each period are calculated as a 

fraction of the EMF GDP forecast, depending on the temperature in that period 

relative to the pre-industrial average temperature in each region.

b. In FUND, damages in each period depend on both the level and the rate of 

temperature change in that period. 

c. In DICE, temperature affects both consumption and investment, so we first adjust the 

EMF GDP paths as follows: Using the Cobb-Douglas production function with the 

DICE2007 parameters, we extract the path of exogenous technical change implied by 

the EMF GDP and population paths, then we recalculate the baseline GDP path 

taking into account climate damages resulting from the baseline emissions path.

3. Add an additional unit of carbon emissions in year t. (The exact unit varies by model.)

4. Recalculate the temperature effects and damages expected in all years beyond t resulting 

from this adjusted path of emissions, as in step 2. 

5. Subtract the damages computed in step 2 from those in step 4 in each year. (DICE is run 

in 10 year time steps, FUND in annual time steps, while the time steps in PAGE vary.)

6. Discount the resulting path of marginal damages back to the year of emissions using the 

agreed upon fixed discount rates. 

14A-25 
7. Calculate the SCC as the net present value of the discounted path of damages computed 

in step 6, divided by the unit of carbon emissions used to shock the models in step 3. 

8. Multiply by 12/44 to convert from dollars per ton of carbon to dollars per ton of CO2

(2007 dollars) in DICE and FUND. (All calculations are done in tons of CO2 in PAGE).

The steps above were repeated in each model for multiple future years to cover the time 

horizons anticipated for upcoming rulemaking analysis. To maintain consistency across the three 

IAMs, climate damages are calculated as lost consumption in each future year.

It is important to note that each of the three models has a different default end year. The 

default time horizon is 2200 for PAGE, 2595 for DICE, and 3000 for the latest version of FUND.

This is an issue for the multi-model approach because differences in SCC estimates may arise 

simply due to the model time horizon. Many consider 2200 too short a time horizon because it 

could miss a significant fraction of damages under certain assumptions about the growth of 

marginal damages and discounting, so each model is run here through 2300. This step required a 

small adjustment in the PAGE model only. This step also required assumptions about GDP, 

population, and greenhouse gas emission trajectories after 2100, the last year for which these 

data are available from the EMF-22 models. (A more detailed discussion of these assumptions is 

included in the Appendix.) 

This exercise produces 45 separate distributions of the SCC for a given year, the product 

of 3 models, 3 discount rates, and 5 socioeconomic scenarios. This is clearly too many separate 

distributions for consideration in a regulatory impact analysis. 

To produce a range of plausible estimates that still reflects the uncertainty in the 

estimation exercise, the distributions from each of the models and scenarios are equally weighed 

and combined to produce three separate probability distributions for SCC in a given year, one for 

each assumed discount rate. These distributions are then used to define a range of point estimates 

for the global SCC. In this way, no integrated assessment model or socioeconomic scenario is 

given greater weight than another. Because the literature shows that the SCC is quite sensitive to 

assumptions about the discount rate, and because no consensus exists on the appropriate rate to 

use in an intergenerational context, we present SCCs based on the average values across models 

and socioeconomic scenarios for each discount rate. 

The interagency group selected four SCC values for use in regulatory analyses. Three 

values are based on the average SCC across models and socio-economic and emissions scenarios 

at the 2.5, 3, and 5 percent discount rates. The fourth value is included to represent the higherthan-expected economic impacts from climate change further out in the tails of the SCC 

distribution. For this purpose, we use the SCC value for the 95th percentile at a 3 percent discount 

rate. (The full set of distributions by model and scenario combination is included in the 

Appendix.) As noted above, the 3 percent discount rate is the central value, and so the central 

value that emerges is the average SCC across models at the 3 percent discount rate. For purposes 

of capturing the uncertainties involved in regulatory impact analysis, we emphasize the 

importance and value of considering the full range. 

14A-26 
As previously discussed, low probability, high impact events are incorporated into the 

SCC values through explicit consideration of their effects in two of the three models as well as 

the use of a probability density function for equilibrium climate sensitivity. Treating climate 

sensitivity probabilistically results in more high temperature outcomes, which in turn lead to 

higher projections of damages. Although FUND does not include catastrophic damages (in 

contrast to the other two models), its probabilistic treatment of the equilibrium climate sensitivity 

parameter will directly affect the non-catastrophic damages that are a function of the rate of 

temperature change.

In Table 14A.5.1, we begin by presenting SCC estimates for 2010 by model, scenario, 

and discount rate to illustrate the variability in the SCC across each of these input parameters. As 

expected, higher discount rates consistently result in lower SCC values, while lower discount 

rates result in higher SCC values for each socioeconomic trajectory. It is also evident that there 

are differences in the SCC estimated across the three main models. For these estimates, FUND 

produces the lowest estimates, while PAGE generally produces the highest estimates. 

Table 14A.5.1 Disaggregated Social Cost of CO2 Values by Model, Socio-Economic 

Trajectory, and Discount Rate for 2010 (2007$) 

Discount rate: 5% 3% 2.5% 3%

Model Scenario Avg Avg Avg 95th

DICE IMAGE 10.8 35.8 54.2 70.8

MERGE 7.5 22.0 31.6 42.1

Message 9.8 29.8 43.5 58.6

MiniCAM 8.6 28.8 44.4 57.9

550 Average 8.2 24.9 37.4 50.8

PAGE IMAGE 8.3 39.5 65.5 142.4

MERGE 5.2 22.3 34.6 82.4

Message 7.2 30.3 49.2 115.6

MiniCAM 6.4 31.8 54.7 115.4

550 Average 5.5 25.4 42.9 104.7

FUND IMAGE -1.3 8.2 19.3 39.7

MERGE -0.3 8.0 14.8 41.3

Message -1.9 3.6 8.8 32.1

MiniCAM -0.6 10.2 22.2 42.6

550 Average -2.7 -0.2 3.0 19.4

These results are not surprising when compared to the estimates in the literature for the 

latest versions of each model. For example, adjusting the values from the literature that were 

used to develop interim SCC values to 2007 dollars for the year 2010 (assuming, as we did for 

the interim process, that SCC grows at 3 percent per year), FUND yields SCC estimates at or 

near zero for a 5 percent discount rate and around $9 per ton for a 3 percent discount rate. There 

are far fewer estimates using the latest versions of DICE and PAGE in the literature: Using 

similar adjustments to generate 2010 estimates, we calculate a SCC from DICE (based on 

Nordhaus 2008) of around $9 per ton for a 5 percent discount rate, and a SCC from PAGE 

(based on Hope 2006, 2008) close to $8 per ton for a 4 percent discount rate. Note that these 

14A-27 
comparisons are only approximate since the literature generally relies on Ramsey discounting, 

while we have assumed constant discount rates.aa

The SCC estimates from FUND are sensitive to differences in emissions paths but 

relatively insensitive to differences in GDP paths across scenarios, while the reverse is true for 

DICE and PAGE. This likely occurs because of several structural differences among the models. 

Specifically in DICE and PAGE, the fraction of economic output lost due to climate damages 

increases with the level of temperature alone, whereas in FUND the fractional loss also increases 

with the rate of temperature change. Further, in FUND increases in income over time decrease 

vulnerability to climate change (a form of adaptation), whereas this does not occur in DICE and 

PAGE. These structural differences among the models make FUND more sensitive to the path of 

emissions and less sensitive to GDP compared to DICE and PAGE. 

Figure 14A.5.1 shows that IMAGE has the highest GDP in 2100 while MERGE 

Optimistic has the lowest. The ordering of global GDP levels in 2100 directly corresponds to the 

rank ordering of SCC for PAGE and DICE. For FUND, the correspondence is less clear, a result 

that is to be expected given its less direct relationship between its damage function and GDP.

Figure 14A.5.1 Level of Global GDP Across EMF Scenarios

Table 14A.5.2 shows the four selected SCC values in 5-year increments from 2010 to 

2050. Values for 2010, 2020, 2040, and 2050 are calculated by first combining all outputs 

(10,000 estimates per model run) from all scenarios and models for a given discount rate. Values 

for the years in between are calculated using a simple linear interpolation.

aa Nordhaus (2008) runs DICE2007 with ρ = 1.5 and η = 2. The default approach in PAGE2002 (version 1.4epm) 

treats ρ and η as random parameters, specified using a triangular distribution such that the min, mode, and max = 

0.1, 1, and 2 for ρ, and 0.5, 1, and 2 for η, respectively. The FUND default value for η is 1, and Tol generates SCC 

estimates for values of ρ = 0, 1, and 3 in many recent papers (e.g., Anthoff et al. 2009). The path of per-capita 

consumption growth, g, varies over time but is treated deterministically in two of the three models. In DICE, g is 

endogenous. Under Ramsey discounting, as economic growth slows in the future, the large damages from climate 

change that occur far out in the future are discounted at a lower rate than impacts that occur in the nearer term.

0

50

100

150

200

250

300

350

400

450

2000 2010 2020 2030 2050 2100

Global 

GDP

(trillions

of U.S. 

dollars)

IMAGE

MERGE Optimistic

MESSAGE

MiniCAM

3.7 W/m2 radiative forcing

14A-28 

 
Table 14A.5.2 Social Cost of CO2, 2010–2050 (2007$) 

Discount Rate 5% 3% 2.5% 3%

Year Avg Avg Avg 95th

2010 4.7 21.4 35.1 64.9

2015 5.7 23.8 38.4 72.8

2020 6.8 26.3 41.7 80.7

2025 8.2 29.6 45.9 90.4

2030 9.7 32.8 50.0 100.0

2035 11.2 36.0 54.2 109.7

2040 12.7 39.2 58.4 119.3

2045 14.2 42.1 61.7 127.8

2050 15.7 44.9 65.0 136.2

The SCC increases over time because future emissions are expected to produce larger 

incremental damages as physical and economic systems become more stressed in response to 

greater climatic change. Note that this approach allows us to estimate the growth rate of the SCC 

directly using DICE, PAGE, and FUND rather than assuming a constant annual growth rate as 

was done for the interim estimates (using 3 percent). This helps to ensure that the estimates are 

internally consistent with other modeling assumptions. Table 14A.5.3 illustrates how the growth 

rate for these four SCC estimates varies over time. The full set of annual SCC estimates between 

2010 and 2050 is reported in the Appendix. 

Table 14A.5.3 Changes in the Average Annual Growth Rates of SCC Estimates between 

2010 and 2050 

Average Annual 

Growth Rate 

5% 3% 2.5% 3.0%

Year Range Avg Avg Avg 95th

2010–2020 3.6 2.1 1.7 2.2

2020–2030 3.7 2.2 1.8 2.2

2030–2040 2.7 1.8 1.6 1.8

2040–2050 2.1 1.4 1.1 1.3

While the SCC estimate grows over time, the future monetized value of emissions 

reductions in each year (the SCC in year t multiplied by the change in emissions in year t) must 

be discounted to the present to determine its total net present value for use in regulatory analysis. 

Damages from future emissions should be discounted at the same rate as that used to calculate 

the SCC estimates themselves to ensure internal consistency—i.e., future damages from climate 

change, whether they result from emissions today or emissions in a later year, should be 

discounted using the same rate. For example, climate damages in 2020 that are calculated using a 

SCC based on a 5 percent discount rate also should be discounted back to the analysis year using 

a 5 percent discount rate.bb 

14A.6 LIMITATIONS OF THE ANALYSIS

As noted, any estimate of the SCC must be taken as provisional and subject to further 

refinement (and possibly significant change) in accordance with evolving scientific, economic, 

and ethical understandings. During the course of our modeling, it became apparent that there are 

bb However, it is possible that other benefits or costs of proposed regulations unrelated to CO2 emissions will be 

discounted at rates that differ from those used to develop the SCC estimates. 

14A-29 

 
several areas in particular need of additional exploration and research. These caveats and 

additional observations in the following section are necessary to consider when interpreting and 

applying the SCC estimates.

Incomplete treatment of non-catastrophic damages. The impacts of climate change are 

expected to be widespread, diverse, and heterogeneous. In addition, the exact magnitude of these 

impacts is uncertain because of the inherent complexity of climate processes, the economic 

behavior of current and future populations, and our inability to accurately forecast technological 

change and adaptation. Current IAMs do not assign value to all of the important physical, 

ecological, and economic impacts of climate change recognized in the climate change literature 

(some of which are discussed above) because of lack of precise information on the nature of 

damages and because the science incorporated into these models understandably lags behind the 

most recent research. Our ability to quantify and monetize impacts will undoubtedly improve 

with time. It is also likely that even in future applications, a number of potentially significant 

damage categories will remain non-monetized. (Ocean acidification is one example of a 

potentially large damage from CO2 emissions not quantified by any of the three models. Species 

and wildlife loss is another example that is exceedingly difficult to monetize.) 

Incomplete treatment of potential catastrophic damages. There has been considerable 

recent discussion of the risk of catastrophic impacts and how best to account for extreme 

scenarios, such as the collapse of the Atlantic Meridional Overturning Circulation or the West 

Antarctic Ice Sheet, or large releases of methane from melting permafrost and warming oceans. 

Weitzman (2009) suggests that catastrophic damages are extremely large—so large, in fact, that 

the damages from a low probability, catastrophic event far in the future dominate the effect of 

the discount rate in a present value calculation and result in an infinite willingness-to-pay for 

mitigation today. However, Nordhaus (2009) concluded that the conditions under which 

Weitzman’s results hold “are limited and do not apply to a wide range of potential uncertain 

scenarios.” 

Using a simplified IAM, Newbold and Daigneault (2009) confirmed the potential for 

large catastrophe risk premiums but also showed that the aggregate benefit estimates can be 

highly sensitive to the shapes of both the climate sensitivity distribution and the damage function 

at high temperature changes. Pindyck (2009) also used a simplified IAM to examine high-impact 

low-probability risks, using a right-skewed gamma distribution for climate sensitivity as well as 

an uncertain damage coefficient, but in most cases found only a modest risk premium. Given this 

difference in opinion, further research in this area is needed before its practical significance can 

be fully understood and a reasonable approach developed to account for such risks in regulatory 

analysis. (The next section discusses the scientific evidence on catastrophic impacts in greater 

detail.)

Uncertainty in extrapolation of damages to high temperatures. The damage functions in 

these IAMs are typically calibrated by estimating damages at moderate temperature increases 

(e.g., DICE was calibrated at 2.5 °C) and extrapolated to far higher temperatures by assuming 

that damages increase as some power of the temperature change. Hence, estimated damages are 

far more uncertain under more extreme climate change scenarios. 

14A-30 
Incomplete treatment of adaptation and technological change. Each of the three 

integrated assessment models used here assumes a certain degree of low- or no-cost adaptation. 

For instance, Tol assumes a great deal of adaptation in FUND, including widespread reliance on 

air conditioning, so much so that the largest single benefit category in FUND is the reduced 

electricity costs from not having to run air conditioning as intensively (NRC 2009). 

Climate change also will increase returns on investment to develop technologies that 

allow individuals to cope with adverse climate conditions, and IAMs to do not adequately 

account for this directed technological change.cc For example, scientists may develop crops that 

are better able to withstand higher and more variable temperatures. Although DICE and FUND 

have both calibrated their agricultural sectors under the assumption that farmers will change land 

use practices in response to climate change (Mastrandrea 2009), they do not take into account 

technological changes that lower the cost of this adaptation over time. On the other hand, the 

calibrations do not account for increases in climate variability, pests, or diseases, which could 

make adaptation more difficult than assumed by the IAMs for a given temperature change.

Hence, models do not adequately account for potential adaptation or technical change that might 

alter the emissions pathway and resulting damages. In this respect, it is difficult to determine 

whether the incomplete treatment of adaptation and technological change in these IAMs under or 

overstate the likely damages.

Risk aversion. A key question unanswered during this interagency process is what to 

assume about relative risk aversion with regard to high-impact outcomes. These calculations do 

not take into account the possibility that individuals may have a higher willingness to pay to 

reduce the likelihood of low-probability, high-impact damages than they do to reduce the 

likelihood of higher-probability but lower-impact damages with the same expected cost. (The 

inclusion of the 95th percentile estimate in the final set of SCC values was largely motivated by 

this concern.) If individuals do show such a higher willingness to pay, a further question is 

whether that fact should be taken into account for regulatory policy. Even if individuals are not 

risk-averse for such scenarios, it is possible that regulatory policy should include a degree of 

risk-aversion. 

Assuming a risk-neutral representative agent is consistent with OMB’s Circular A-4, 

which advises that the estimates of benefits and costs used in regulatory analysis are usually 

based on the average or the expected value and that “emphasis on these expected values is 

appropriate as long as society is ‘risk neutral’ with respect to the regulatory alternatives. While 

this may not always be the case, [analysts] should in general assume ‘risk neutrality’ in [their] 

analysis.” 

Nordhaus (2008) points to the need to explore the relationship between risk and income 

in the context of climate change across models and to explore the role of uncertainty regarding 

various parameters in the results. Using FUND, Anthoff et al. (2009) explored the sensitivity of 

the SCC to Ramsey equation parameter assumptions based on observed behavior. They conclude 

that “the assumed rate of risk aversion is at least as important as the assumed rate of time 

preference in determining the social cost of carbon.” Since Circular A-4 allows for a different 

cc However these research dollars will be diverted from whatever their next best use would have been in the absence 

of climate change (so productivity/GDP would have been still higher).

14A-31 

 
assumption on risk preference in regulatory analysis if it is adequately justified, we plan to 

continue investigating this issue.

14A.7 A FURTHER DISCUSSION OF CATASTROPHIC IMPACTS AND DAMAGE 

FUNCTIONS

As noted above, the damage functions underlying the three IAMs used to estimate the 

SCC may not capture the economic effects of all possible adverse consequences of climate 

change and may therefore lead to underestimates of the SCC (Mastrandrea 2009). In particular, 

the models’ functional forms may not adequately capture: (1) potentially discontinuous “tipping 

point” behavior in Earth systems; (2) inter-sectoral and inter-regional interactions, including 

global security impacts of high-end warming; and (3) limited near-term substitutability between 

damage to natural systems and increased consumption. 

It is the hope of the interagency group that over time researchers and modelers will work 

to fill these gaps and that the SCC estimates used for regulatory analysis by the Federal 

government will continue to evolve with improvements in modeling. In the meantime, we 

discuss some of the available evidence.

14A.7.1 Extrapolation of Climate Damages to High Levels of Warming

The damage functions in the models are calibrated at moderate levels of warming and 

should therefore be viewed cautiously when extrapolated to the high temperatures found in the 

upper end of the distribution. Recent science suggests that there are a number of potential 

climatic “tipping points” at which the Earth system may exhibit discontinuous behavior with 

potentially severe social and economic consequences (e.g., Lenton et al. 2008, Kriegler et al.

2009). These tipping points include the disruption of the Indian Summer Monsoon, dieback of 

the Amazon Rainforest and boreal forests, collapse of the Greenland Ice Sheet and the West 

Antarctic Ice Sheet, reorganization of the Atlantic Meridional Overturning Circulation, 

strengthening of El Niño-Southern Oscillation, and the release of methane from melting 

permafrost. Many of these tipping points are estimated to have thresholds between about 3 °C 

and 5 °C (Lenton et al. 2008). Probabilities of several of these tipping points were assessed 

through expert elicitation in 2005–2006 by Kriegler et al. (2009); results from this study are 

highlighted in Table 14A.7.1. Ranges of probability are averaged across core experts on each 

topic. 

14A-32 
Table 14A.7.1 Probabilities of Various Tipping Points from Expert Elicitation

Possible Tipping Points Duration before 

effect is fully realized

years

Additional Warming by 2100

%

0.5–1.5 C 1.5–3.0 C 3–5 C

Reorganization of Atlantic Meridional 

Overturning Circulation

about 100 0–18 6–39 18–67

Greenland Ice Sheet Collapse at least 300 8–39 33–73 67–96

West Antarctic Ice Sheet Collapse at least 300 5–41 10–63 33–88

Dieback of Amazon rainforest about 50 2–46 14–84 41–94

Strengthening of El Niño-Southern 

Oscillation

about 100 1–13 6–32 19–49

Dieback of Boreal Forests about 50 13–43 20–81 34–91

Shift in Indian Summer Monsoon about 1 not formally assessed

Release of Methane from Melting 

Permafrost

less than 100 not formally assessed

As previously mentioned, FUND does not include potentially catastrophic effects. DICE 

assumes a small probability of catastrophic damages that increases with increased warming, but 

the damages from these risks are incorporated as expected values (i.e., ignoring potential risk 

aversion). PAGE models catastrophic impacts in a probabilistic framework (Figure 14-A.4.1), so 

the high-end output from PAGE potentially offers the best insight into the SCC if the world were 

to experience catastrophic climate change. For instance, at the 95th percentile and a 3 percent 

discount rate, the SCC estimated by PAGE across the five socio-economic and emission 

trajectories of $113 per ton of CO2 is almost double the value estimated by DICE, $58 per ton in 

2010. We cannot evaluate how well the three models account for catastrophic or noncatastrophic impacts, but this estimate highlights the sensitivity of SCC values in the tails of the 

distribution to the assumptions made about catastrophic impacts. 

PAGE treats the possibility of a catastrophic event probabilistically, while DICE treats it 

deterministically (i.e., by adding the expected value of the damage from a catastrophe to the 

aggregate damage function). In part, this results in different probabilities being assigned to a 

catastrophic event across the two models. For instance, PAGE places a probability near zero on a 

catastrophe at 2.5 °C warming, while DICE assumes a 4 percent probability of a catastrophe at 

2.5 °C. By comparison, Kriegler et al. (2009) estimate a probability of at least 16–36 percent of 

crossing at least one of their primary climatic tipping points in a scenario with temperatures 

about 2–4 °C warmer than pre-Industrial levels in 2100. 

It is important to note that crossing a climatic tipping point will not necessarily lead to an 

economic catastrophe in the sense used in the IAMs. A tipping point is a critical threshold across 

which some aspect of the Earth system starts to shifts into a qualitatively different state (for 

instance, one with dramatically reduced ice sheet volumes and higher sea levels). In the IAMs, a 

catastrophe is a low-probability environmental change with high economic impact. 

14A.7.2 Failure to Incorporate Inter-Sectoral and Inter-Regional Interactions 

The damage functions do not fully incorporate either inter-sectoral or inter-regional 

interactions. For instance, while damages to the agricultural sector are incorporated, the effects 

of changes in food supply on human health are not fully captured and depend on the modeler’s 

choice of studies used to calibrate the IAM. Likewise, the effects of climate damages in one 

14A-33 
region of the world on another region are not included in some of the models (FUND includes 

the effects of migration from sea level rise). These inter-regional interactions, though difficult to 

quantify, are the basis for climate-induced national and economic security concerns (e.g., 

Campbell et al. 2007; U.S. Department of Defense 2010) and are particularly worrisome at 

higher levels of warming. High-end warming scenarios, for instance, project water scarcity 

affecting 4.3–6.9 billion people by 2050, food scarcity affecting about 120 million additional 

people by 2080, and the creation of millions of climate refugees (Easterling et al. 2007; 

Campbell et al. 2007). 

14A.7.3 Imperfect Substitutability of Environmental Amenities

Data from the geological record of past climate changes suggests that 6 °C of warming 

may have severe consequences for natural systems. For instance, during the Paleocene-Eocene 

Thermal Maximum about 55.5 million years ago, when the Earth experienced a geologically 

rapid release of carbon associated with an approximately 5 °C increase in global mean 

temperatures, the effects included shifts of about 400–900 miles in the range of plants (Wing et 

al. 2005), and dwarfing of both land mammals (Gingerich 2006) and soil fauna (Smith et al.

2009). 

 The three IAMs used here assume that it is possible to compensate for the 

economic consequences of damages to natural systems through increased consumption of nonclimate goods, a common assumption in many economic models. In the context of climate 

change, however, it is possible that the damages to natural systems could become so great that no 

increase in consumption of non-climate goods would provide complete compensation (Levy et 

al. 2005). For instance, as water supplies become scarcer or ecosystems become more fragile and 

less bio-diverse, the services they provide may become increasingly more costly to replace. 

Uncalibrated attempts to incorporate the imperfect substitutability of such amenities into IAMs 

(Sterner and Persson 2008) indicate that the optimal degree of emissions abatement can be 

considerably greater than is commonly recognized. 

14A.8 CONCLUSION

The interagency group selected four SCC estimates for use in regulatory analyses. For 

2010, these estimates are $4.7, $21.4, $35.1, and $64.9 (2007$). The first three estimates are 

based on the average SCC across models and socio-economic and emissions scenarios at the 5, 3, 

and 2.5 percent discount rates, respectively. The fourth value is included to represent the higherthan-expected impacts from temperature change further out in the tails of the SCC distribution. 

For this purpose, we use the SCC value for the 95th percentile at a 3 percent discount rate. The 

central value is the average SCC across models at the 3 percent discount rate. For purposes of 

capturing the uncertainties involved in regulatory impact analysis, we emphasize the importance 

and value of considering the full range. These SCC estimates also grow over time. For instance, 

the central value increases to $24 per ton of CO2 in 2015 and $26 per ton of CO2 in 2020. 

 We noted a number of limitations to this analysis, including the incomplete way 

in which the integrated assessment models capture catastrophic and non-catastrophic impacts, 

14A-34 
their incomplete treatment of adaptation and technological change, uncertainty in the 

extrapolation of damages to high temperatures, and assumptions regarding risk aversion. The 

limited amount of research linking climate impacts to economic damages makes this modeling 

exercise even more difficult. It is the hope of the interagency group that over time researchers 

and modelers will work to fill these gaps and that the SCC estimates used for regulatory analysis 

by the Federal government will continue to evolve with improvements in modeling. 

14A-35 
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14A-41 
14A.10ANNEX

This Annex provides additional technical information about the non-CO2 emission 

projections used in the modeling and the method for extrapolating emissions forecasts through 

2300, and shows the full distribution of 2010 SCC estimates by model and scenario combination. 

Annual SCC values for the next 40 years are provided in Table 14A.9.1. 

Table 14A.9.1 Annual SCC Values: 2010–2050 (2007$) 

Discount Rate 5% 3% 2.5% 3%

Year Avg Avg Avg 95th

2010 4.7 21.4 35.1 64.9

2011 4.9 21.9 35.7 66.5

2012 5.1 22.4 36.4 68.1

2013 5.3 22.8 37.0 69.6

2014 5.5 23.3 37.7 71.2

2015 5.7 23.8 38.4 72.8

2016 5.9 24.3 39.0 74.4

2017 6.1 24.8 39.7 76.0

2018 6.3 25.3 40.4 77.5

2019 6.5 25.8 41.0 79.1

2020 6.8 26.3 41.7 80.7

2021 7.1 27.0 42.5 82.6

2022 7.4 27.6 43.4 84.6

2023 7.7 28.3 44.2 86.5

2024 7.9 28.9 45.0 88.4

2025 8.2 29.6 45.9 90.4

2026 8.5 30.2 46.7 92.3

2027 8.8 30.9 47.5 94.2

2028 9.1 31.5 48.4 96.2

2029 9.4 32.1 49.2 98.1

2030 9.7 32.8 50.0 100.0

2031 10.0 33.4 50.9 102.0

2032 10.3 34.1 51.7 103.9

2033 10.6 34.7 52.5 105.8

2034 10.9 35.4 53.4 107.8

2035 11.2 36.0 54.2 109.7

2036 11.5 36.7 55.0 111.6

2037 11.8 37.3 55.9 113.6

2038 12.1 37.9 56.7 115.5

2039 12.4 38.6 57.5 117.4

2040 12.7 39.2 58.4 119.3

2041 13.0 39.8 59.0 121.0

2042 13.3 40.4 59.7 122.7

2043 13.6 40.9 60.4 124.4

2044 13.9 41.5 61.0 126.1

2045 14.2 42.1 61.7 127.8

2046 14.5 42.6 62.4 129.4

2047 14.8 43.2 63.0 131.1

2048 15.1 43.8 63.7 132.8

2049 15.4 44.4 64.4 134.5

2050 15.7 44.9 65.0 136.2

14A-42 
14A.10.1 Other (non-CO2) Gases

In addition to fossil and industrial CO2 emissions, each EMF scenario provides 

projections of methane (CH4), nitrous oxide (N2O), fluorinated gases, and net land use CO2

emissions to 2100. These assumptions are used in all three IAMs while retaining each model’s 

default radiative forcings (RF) due to other factors (e.g., aerosols and other gases). Specifically, 

to obtain the RF associated with the non-CO2 EMF emissions only, we calculated the RF 

associated with the EMF atmospheric CO2 concentrations and subtracted them from the EMF 

total RF.dd This approach respects the EMF scenarios as much as possible and at the same time 

takes account of those components not included in the EMF projections. Since each model treats 

non-CO2 gases differently (e.g., DICE lumps all other gases into one composite exogenous 

input), this approach was applied slightly differently in each of the models. 

FUND: Rather than relying on RF for these gases, the actual emissions from each 

scenario were used in FUND. The model default trajectories for CH4, N2O, SF6, and the CO2

emissions from land were replaced with the EMF values. 

PAGE: PAGE models CO2, CH4, sulfur hexafluoride (SF6), and aerosols and contains an 

“excess forcing” vector that includes the RF for everything else. To include the EMF values, we 

removed the default CH4 and SF6 factors,

ee decomposed the excess forcing vector, and 

constructed a new excess forcing vector that includes the EMF RF for CH4, N2O, and fluorinated 

gases, as well as the model default values for aerosols and other factors. Net land use CO2

emissions were added to the fossil and industrial CO2 emissions pathway. 

DICE: DICE presents the greatest challenge because all forcing due to factors other than 

industrial CO2 emissions is embedded in an exogenous non-CO2 RF vector. To decompose this 

exogenous forcing path into EMF non-CO2 gases and other gases, we relied on the references in 

DICE2007 to the Intergovernmental Panel on Climate Change’s (IPCC) Fourth Assessment 

Report (AR4) and the discussion of aerosol forecasts in the IPCC’s Third Assessment Report 

(TAR) and in AR4, as explained below. In DICE2007, Nordhaus assumes that exogenous forcing 

from all non-CO2 sources is -0.06 W/m2

 in 2005, as reported in AR4, and increases linearly to 

0.3 W/m2

 in 2105, based on GISS projections, and then stays constant after that time. 

According to AR4, the RF in 2005 from CH4, N20, and halocarbons (approximately 

similar to the F-gases in the EMF-22 scenarios) was 0.48 + 0.16 + 0.34 = 0.98 W/m2

 and RF 

from total aerosols was -1.2 W/m2. Thus, the -.06 W/m2 non-CO2 forcing in DICE can be 

decomposed into: 0.98 W/m2 due to the EMF non-CO2 gases, -1.2 W/m2 due to aerosols, and the 

remainder, 0.16 W/m2

, due to other residual forcing. 

dd Note EMF did not provide CO2 concentrations for the IMAGE reference scenario. Thus, for this scenario, we fed 

the fossil, industrial and land CO2 emissions into MAGICC (considered a “neutral arbiter” model, which is tuned to 

emulate the major global climate models) and the resulting CO2 concentrations were used. Note also that MERGE 

assumes a neutral biosphere so net land CO2 emissions are set to zero for all years for the MERGE Optimistic 

reference scenario, and for the MERGE component of the average 550 scenario (i.e., we add up the land use 

emissions from the other three models and divide by 4).

ee Both the model default CH4 emissions and the initial atmospheric CH4 is set to zero to avoid double counting the 

effect of past CH4 emissions.

14A-43 

 
For subsequent years, we calculated the DICE default RF from aerosols and other nonCO2 gases based on the following two assumptions: 

(1) RF from aerosols declines linearly from 2005 to 2100 at the rate projected by the TAR 

and then stays constant thereafter, and 

(2) With respect to RF from non-CO2 gases not included in the EMF-22 scenarios, the share 

of non-aerosol RF matches the share implicit in the AR4 summary statistics cited above and 

remains constant over time. 

Assumption (1) means that the RF from aerosols in 2100 equals 66 percent of that in 

2000, which is the fraction of the TAR projection of total RF from aerosols (including sulfates, 

black carbon, and organic carbon) in 2100 vs. 2000 under the A1B SRES emissions scenario. 

Since the SRES marker scenarios were not updated for the AR4, the TAR provides the most 

recent IPCC projection of aerosol forcing. We rely on the A1B projection from the TAR because 

it provides one of the lower aerosol forecasts among the SRES marker scenarios and is more 

consistent with the AR4 discussion of the post-SRES literature on aerosols: 

Aerosols have a net cooling effect and the representation of aerosol and aerosol precursor 

emissions, including sulphur dioxide, black carbon and organic carbon, has improved in the 

post-SRES scenarios. Generally, these emissions are projected to be lower than reported in 

SRES. {WGIII 3.2, TS.3, SPM}.ff

Assuming a simple linear decline in aerosols from 2000 to 2100 also is more consistent 

with the recent literature on these emissions. For example, Figure 17A.9.1 shows that the sulfur 

dioxide emissions peak over the short-term of some SRES scenarios above the upper bound 

estimates of the more recent scenarios.gg Recent scenarios project sulfur emissions to peak earlier 

and at lower levels compared to the SRES in part because of new information about present and 

planned sulfur legislation in some developing countries, such as India and China.hh The lower 

bound projections of the recent literature have also shifted downward slightly compared to the 

SRES scenario (IPCC 2007). 

With these assumptions, the DICE aerosol forcing changes from -1.2 in 2005 to -0.792 in 

2105 W/m2

; forcing due to other non-CO2 gases not included in the EMF scenarios declines from 

0.160 to 0.153 W/m2

. 

ff AR4 Synthesis Report, p. 44, http://www.ipcc.ch/pdf/assessment-report/ar4/syr/ar4_syr.pdf gg See Smith, S.J., R. Andres, E. Conception, and J. Lurz. 2004. “Historical sulfur dioxide emissions, 1850-2000: 

methods and results.” Joint Global Research Institute, College Park, 14 pp. hh See Carmichael, G., D. Streets, G. Calori, M. Amann, M. Jacobson, J. Hansen, and H. Ueda. 2002. “Changing 

trends in sulphur emissions in Asia: implications for acid deposition, air pollution, and climate.” Environmental 

Science and Technology 36(22):4707- 4713; Streets, D., K. Jiang, X. Hu, J. Sinton, X.-Q. Zhang, D. Xu, M. 

Jacobson, and J. Hansen. 2001. “Recent reductions in China’s greenhouse gas emissions.” Science 294(5548):1835-

1837.

14A-44 

 
. 

Figure 14A.9.1 Sulphur Dioxide Emission Scenarios

Notes: Thick colored lines depict the four SRES marker scenarios and black dashed lines show the median, 

5th and 95th percentile of the frequency distribution for the full ensemble of 40 SRES scenarios. The blue 

area (and the thin dashed lines in blue) illustrates individual scenarios and the range of Smith et al. (2004). 

Dotted lines indicate the minimum and maximum of SO2 emissions scenarios developed pre-SRES.

Source: IPCC (2007), AR4 WGIII 3.2, http://www.ipcc.ch/publications_and_data/ar4/wg3/en/ch3-ens3-2-

2-4.html. 

Although other approaches to decomposing the DICE exogenous forcing vector are 

possible, initial sensitivity analysis suggests that the differences among reasonable alternative 

approaches are likely to be minor. For example, adjusting the TAR aerosol projection above to 

assume that aerosols will be maintained at 2000 levels through 2100 reduces average SCC values 

(for 2010) by approximately 3 percent (or less than $2); assuming all aerosols are phased out by 

2100 increases average 2010 SCC values by 6–7 percent (or $0.50–$3), depending on the 

discount rate. These differences increase slightly for SCC values in later years but are still well 

within 10 percent of each other as far out as 2050. 

Finally, as in PAGE, the EMF net land use CO2 emissions are added to the fossil and 

industrial CO2 emissions pathway. 

14A.10.2 Extrapolating Emissions Projections to 2300 

To run each model through 2300 requires assumptions about GDP, population, 

greenhouse gas emissions, and radiative forcing trajectories after 2100, the last year for which 

these projections are available from the EMF-22 models. These inputs were extrapolated from 

2100 to 2300 as follows: 

1. Population growth rate declines linearly, reaching zero in 2200. 

2. GDP/per capita growth rate declines linearly, reaching zero in 2300. 

3. The decline in the fossil and industrial carbon intensity (CO2/GDP) growth rate over 

2090-2100 is maintained from 2100 through 2300. 

14A-45 
4. Net land use CO2 emissions decline linearly, reaching zero in 2200. 

5. Non-CO2 radiative forcing remains constant after 2100. 

Long run stabilization of GDP per capita was viewed as a more realistic simplifying 

assumption than a linear or exponential extrapolation of the pre-2100 economic growth rate of 

each EMF scenario. This is based on the idea that increasing scarcity of natural resources and the 

degradation of environmental sinks available for assimilating pollution from economic 

production activities may eventually overtake the rate of technological progress. Thus, the 

overall rate of economic growth may slow over the very long run. The interagency group also 

considered allowing an exponential decline in the growth rate of GDP per capita. However, since 

this would require an additional assumption about how close to zero the growth rate would get 

by 2300, the group opted for the simpler and more transparent linear extrapolation to zero by 

2300. 

The population growth rate is also assumed to decline linearly, reaching zero by 2200. 

This assumption is reasonably consistent with the United Nations long run population forecast, 

which estimates global population to be fairly stable after 2150 in the medium scenario (UN 

2004).ii The resulting range of EMF population trajectories (Figure 14A.9.2) also encompass the 

UN medium scenario forecasts through 2300 – global population of 8.5 billion by 2200, and 9 

billion by 2300. 

Maintaining the decline in the 2090–2100 carbon intensity growth rate (i.e., CO2 per 

dollar of GDP) through 2300 assumes that technological improvements and innovations in the 

areas of energy efficiency and other carbon reducing technologies (possibly including currently 

unavailable methods) will continue to proceed at roughly the same pace that is projected to occur 

towards the end of the forecast period for each EMF scenario. This assumption implies that total 

cumulative emissions in 2300 will be between 5,000 and 12,000 GtC, which is within the range 

of the total potential global carbon stock estimated in the literature.

Net land use CO2 emissions are expected to stabilize in the long run, so in the absence of 

any post 2100 projections, the group assumed a linear decline to zero by 2200. Given no a priori 

reasons for assuming a long run increase or decline in non-CO2 radiative forcing, it is assumed to 

remain at the 2100 levels for each EMF scenario through 2300. 

Figure 14A.9.2 through Figure 14A.9.8 show the paths of global population, GDP, fossil 

and industrial CO2 emissions, net land CO2 emissions, non-CO2 radiative forcing, and CO2

intensity (fossil and industrial CO2 emissions/GDP) resulting from these assumptions. 

ii United Nations. 2004. World Population to 2300. 

http://www.un.org/esa/population/publications/longrange2/worldpop2300final.pdf. 

14A-46 

 
Figure 14A.9.2 Global Population, 2000–2300 (post-2100 extrapolations assume the 

population growth rate changes linearly to reach a zero growth rate by 2200) 

Note: In the fifth scenario, 2000–2100 population is equal to the average of the population under the 550 

ppm CO2e, full-participation, not-to-exceed scenarios considered by each of the four models. 

Figure 14A.9.3 World GDP, 2000-2300 (post-2100 extrapolations assume GDP per capita 

growth declines linearly, reaching zero in 2300)

Note: In the fifth scenario, 2000–2100 GDP is equal to the average of the GDP under the 550 ppm CO2e, 

full-participation, not-to-exceed scenarios considered by each of the four models. 

5.5

6.5

7.5

8.5

9.5

10.5

11.5

2000 2050 2100 2150 2200 2250 2300

IMAGE

MERGE

MESSAGE

MiniCAM

5th scenario

Extrapolations

Global Population [billion]

Year

0

500

1000

1500

2000

2000 2050 2100 2150 2200 2250 2300

IMAGE

MERGE

MESSAGE

MiniCAM

5th scenario

Extrapolations

Year

World GDP [$trillion]

14A-47 
Figure 14A.9.4 Global Fossil and Industrial CO2 Emissions, 2000-2300 (post-2100 

extrapolations assume growth rate of CO2 intensity (CO2/GDP) over 2090–2100 is 

maintained through 2300) 

Note: In the fifth scenario, 2000–2100 emissions are equal to the average of the emissions under the 550 

ppm CO2e, full-participation, not-to-exceed scenarios considered by each of the four models. 

Figure 14A.9.5 Global Net Land Use CO2 Emissions, 2000–2300 (post-2100 extrapolations 

assume emissions decline linearly, reaching zero in 2200)jj

Note: In the fifth scenario, 2000–2100 emissions are equal to the average of the emissions under the 550 

ppm CO2e, full-participation, not-to-exceed scenarios considered by each of the four models. 

jj MERGE assumes a neutral biosphere so net land CO2 emissions are set to zero for all years for the MERGE 

Optimistic reference scenario, and for the MERGE component of the average 550 scenario (i.e., we add up the land 

use emissions from the other three models and divide by 4).

0

50

100

150

200

2000 2050 2100 2150 2200 2250 2300

IMAGE

MERGE

MESSAGE

MiniCAM

5th scenario

Extrapolations

Fossil&Industrial CO2 Emissions [GtCO2/decade]

Year

-3.00

-2.00

-1.00

0.00

1.00

2.00

3.00

4.00

2000 2050 2100 2150 2200 2250 2300

IMAGE

MERGE

MESSAGE

MiniCAM

5th scneario

Extrapolations

Net land CO2 emissions [GtCO2/yr]

Year

z

14A-48 

 
Figure 14A.9.6 Global Non-CO2 Radiative Forcing, 2000–2300 (post-2100 extrapolations 

assume constant non-CO2 radiative forcing after 2100) 

Note: In the fifth scenario, 2000–2100 emissions are equal to the average of the emissions under the 550 

ppm CO2e, full-participation, not-to-exceed scenarios considered by each of the four models. 

Figure 14A.9.7 Global CO2 Intensity (fossil & industrial CO2 emissions/GDP), 2000–2300 

(post-2100 extrapolations assume decline in CO2/GDP growth rate over 2090–2100 is 

maintained through 2300) 

Note: In the fifth scenario, 2000–2100 emissions are equal to the average of the emissions under the 550 

ppm CO2e, full-participation, not-to-exceed scenarios considered by each of the four models. 

0.00

0.75

1.50

2.25

3.00

3.75

2000 2050 2100 2150 2200 2250 2300

IMAGE

MERGE

MESSAGE

MiniCAM

5th scenario

Extrapolations

nonCO2 RF [W/m^2]

Year

0

0

0

0

0

1

1

1

1

2000 2050 2100 2150 2200 2250 2300

IMAGE

MERGE

MESSAGE

MiniCAM

5th scenario

Extrapolations

Fossil & Industrial CO2 intensity [GtCO2/trillion $]

Year

14A-49 
Table 14A.9.2 2010 Global SCC Estimates at 2.5 Percent Discount Rate (2007$/ton CO2) 

Percentile 1st 5th 10th 25th 50th Avg 75th 90th 95th 99th

Scenario PAGE

IMAGE 3.3 5.9 8.1 13.9 28.8 65.5 68.2 147.9 239.6 563.8

MERGE optimistic 1.9 3.2 4.3 7.2 14.6 34.6 36.2 79.8 124.8 288.3

Message 2.4 4.3 5.8 9.8 20.3 49.2 50.7 114.9 181.7 428.4

MiniCAM base 2.7 4.6 6.4 11.2 22.8 54.7 55.7 120.5 195.3 482.3

5th scenario 2.0 3.5 4.7 8.1 16.3 42.9 41.5 103.9 176.3 371.9

Scenario DICE

IMAGE 16.4 21.4 25 33.3 46.8 54.2 69.7 96.3 111.1 130.0

MERGE optimistic 9.7 12.6 14.9 19.7 27.9 31.6 40.7 54.5 63.5 73.3

Message 13.5 17.2 20.1 27 38.5 43.5 55.1 75.8 87.9 103.0

MiniCAM base 13.1 16.7 19.8 26.7 38.6 44.4 56.8 79.5 92.8 109.3

5th scenario 10.8 14 16.7 22.2 32 37.4 47.7 67.8 80.2 96.8

Scenario FUND

IMAGE -33.1 -18.9 -13.3 -5.5 4.1 19.3 18.7 43.5 67.1 150.7

MERGE optimistic -33.1 -14.8 -10 -3 5.9 14.8 20.4 43.9 65.4 132.9

Message -32.5 -19.8 -14.6 -7.2 1.5 8.8 13.8 33.7 52.3 119.2

MiniCAM base -31.0 -15.9 -10.7 -3.4 6 22.2 21 46.4 70.4 152.9

5th scenario -32.2 -21.6 -16.7 -9.7 -2.3 3 6.7 20.5 34.2 96.8

Table 14A.9.3 2010 Global SCC Estimates at 3 Percent Discount Rate (2007$/ton CO2) 

Percentile 1st 5th 10th 25th 50th Avg 75th 90th 95th 99th

Scenario PAGE

IMAGE 2.0 3.5 4.8 8.1 16.5 39.5 41.6 90.3 142.4 327.4

MERGE optimistic 1.2 2.1 2.8 4.6 9.3 22.3 22.8 51.3 82.4 190.0

Message 1.6 2.7 3.6 6.2 12.5 30.3 31 71.4 115.6 263.0

MiniCAM base 1.7 2.8 3.8 6.5 13.2 31.8 32.4 72.6 115.4 287.0

5th scenario 1.3 2.3 3.1 5 9.6 25.4 23.6 62.1 104.7 222.5

Scenario DICE

IMAGE 11.0 14.5 17.2 22.8 31.6 35.8 45.4 61.9 70.8 82.1

MERGE optimistic 7.1 9.2 10.8 14.3 19.9 22 27.9 36.9 42.1 48.8

Message 9.7 12.5 14.7 19 26.6 29.8 37.8 51.1 58.6 67.4

MiniCAM base 8.8 11.5 13.6 18 25.2 28.8 36.9 50.4 57.9 67.8

5th scenario 7.9 10.1 11.8 15.6 21.6 24.9 31.8 43.7 50.8 60.6

Scenario FUND

IMAGE -25.2 -15.3 -11.2 -5.6 0.9 8.2 10.4 25.4 39.7 90.3

MERGE optimistic -24.0 -12.4 -8.7 -3.6 2.6 8 12.2 27 41.3 85.3

Message -25.3 -16.2 -12.2 -6.8 -0.5 3.6 7.7 20.1 32.1 72.5

MiniCAM base -23.1 -12.9 -9.3 -4 2.4 10.2 12.2 27.7 42.6 93.0

5th scenario -24.1 -16.6 -13.2 -8.3 -3 -0.2 2.9 11.2 19.4 53.6

14A-50 
Table 14A.9.4 2010 Global SCC Estimates at 5 Percent Discount Rate (2007$/ton CO2) 

Percentile 1st 5th 10th 25th 50th Avg 75th 90th 95th 99th

Scenario PAGE

IMAGE 0.5 0.8 1.1 1.8 3.5 8.3 8.5 19.5 31.4 67.2

MERGE optimistic 0.3 0.5 0.7 1.2 2.3 5.2 5.4 12.3 19.5 42.4

Message 0.4 0.7 0.9 1.6 3 7.2 7.2 17 28.2 60.8

MiniCAM base 0.3 0.6 0.8 1.4 2.7 6.4 6.6 15.9 24.9 52.6

5th scenario 0.3 0.6 0.8 1.3 2.3 5.5 5 12.9 22 48.7

Scenario DICE

IMAGE 4.2 5.4 6.2 7.6 10 10.8 13.4 16.8 18.7 21.1

MERGE optimistic 2.9 3.7 4.2 5.3 7 7.5 9.3 11.7 12.9 14.4

Message 3.9 4.9 5.5 7 9.2 9.8 12.2 15.4 17.1 18.8

MiniCAM base 3.4 4.2 4.7 6 7.9 8.6 10.7 13.5 15.1 16.9

5th scenario 3.2 4 4.6 5.7 7.6 8.2 10.2 12.8 14.3 16.0

Scenario FUND

IMAGE -11.7 -8.4 -6.9 -4.6 -2.2 -1.3 0.7 4.1 7.4 17.4

MERGE optimistic -10.6 -7.1 -5.6 -3.6 -1.3 -0.3 1.6 5.4 9.1 19.0

Message -12.2 -8.9 -7.3 -4.9 -2.5 -1.9 0.3 3.5 6.5 15.6

MiniCAM base -10.4 -7.2 -5.8 -3.8 -1.5 -0.6 1.3 4.8 8.2 18.0

5th scenario -10.9 -8.3 -7 -5 -2.9 -2.7 -0.8 1.4 3.2 9.2

Figure 14A.9.8 Histogram of Global SCC Estimates in 2010 (2007$/ton CO2), by Discount 

Rate*

* The distribution of SCC values ranges from -$5,192 to $66,116, but the X-axis has been truncated at 

approximately the 1st and 99th percentiles to better show the data.

 

0

2000

4000

6000

8000

10000

12000

14000

16000

-25-12

1

14274053667992

105118131144157170183196209222235248261274

All 2010, 5.0% All 2010, 3.0% All 2010, 2.5%

14A-51 
Table 14A.9.5 Additional Summary Statistics of 2010 Global SCC Estimates 

Discount 

Rate

5% 3% 2.5%

Scenario Mean Variance Skewness Kurtosis Mean Variance Skewness Kurtosis Mean Variance Skewness Kurtosis

DICE 9.0 13.1 0.8 0.2 28.3 209.8 1.1 0.9 42.2 534.9 1.2 1.1

PAGE 6.5 136.0 6.3 72.4 29.8 3,383.7 8.6 151.0 49.3 9,546.0 8.7 143.8

FUND -1.3 70.1 28.2 1,479.0 6.0 16,382.5 128.0 18,976.5 13.6 150,732.6 149.0 23,558.3

14A-52 
APPENDIX 14B. SOCIAL COST OF CARBON FOR REGULATORY IMPACT 

ANALYSIS UNDER EXECUTIVE ORDER 12866: TECHNICAL MODEL UPDATE

TABLE OF CONTENTS

14B.1 PREFACE ...................................................................................................................14B-1

14B.2 PURPOSE ...................................................................................................................14B-1

14B.3 SUMMARY OF MODEL UPDATES ........................................................................14B-2

14B.3.1 DICE .........................................................................................................14B-2

14B.3.1.1 Carbon Cycle Parameters ................................................................... 14B-2

14B.3.1.2 Sea Level Dynamics .......................................................................... 14B-3

14B.3.1.3 Re-calibrated Damage Function ........................................................ 14B-3

14B.3.2 FUND ........................................................................................................14B-4

14B.3.2.1 Space Heating .................................................................................... 14B-4

14B.3.2.2 Sea Level Rise and Land Loss ........................................................... 14B-5

14B.3.2.3 Agriculture ......................................................................................... 14B-5

14B.3.2.4 Temperature Response Model ........................................................... 14B-6

14B.3.2.5 Methane .............................................................................................. 14B-6

14B.3.3 PAGE ........................................................................................................14B-6

14B.3.3.1 Sea Level Rise .................................................................................... 14B-6

14B.3.3.2 Revised Damage Function to Account for Saturation ....................... 14B-7

14B.3.3.3 Regional Scaling Factors ................................................................... 14B-7

14B.3.3.4 Probability of a Discontinuity ............................................................ 14B-7

14B.3.3.5 Adaptation .......................................................................................... 14B-8

14B.3.3.6 Other Noteworthy Changes ................................................................ 14B-8

14B.4 REVISED SCC ESTIMATES ....................................................................................14B-8

14B.5 OTHER MODEL LIMITATIONS OR RESEARCH GAPS ...................................14B-11

LIST OF TABLES

Table 14B.4.1 Revised Social Cost of CO2, 2010 – 2050 (in 2007 dollars per ton of CO2) ...14B-9

Table 14B.4.2 Average Annual Growth Rates of SCC Estimates between 2010 and 2050 ..14B-10

Table 14B.5.1 Annual SCC Values: 2010-2050 (2007$/ton CO2) ........................................14B-14

Table 14B.5.2 202 Global SCC Estimates at 2.5 Percent Discount Rate (2007$/ton CO2) ..14B-15

Table 14B.5.3 SCC Estimates at 3 Percent Discount Rate (2007$/ton CO2)........................14B-15

Table 14B.5.4 2020 Global SCC Estimates at 5 Percent Discount Rate (2007$/ton CO2) ...14B-16

LIST OF FIGURES 

Figure 14B.4.1 Distribution of SCC Estimates for 2020 (in 2007$ per ton CO2) .................14B-10

14B-i
Appendix 14B. Social Cost of Carbon for Regulatory Impact Analysis Under Executive 

Order 12866: technical model update

14B.1 Preface

The following text is reproduced almost verbatim from the draft (Feb. 13, 2013) report of 

the Interagency Working Group on the Social Cost of Carbon of the United States Government, 

titled “Technical Model Update for the Social Cost of Carbon (SCC).” Minor changes were

made to the working group's report to make it more consistent with the rest of this technical 

support document. 

14B.2 Purpose

The purpose of this document is to update the schedule of social cost of carbon (SCC) a

estimates from the 2010 interagency technical support document (TSD) (Interagency Working 

Group on Social Cost of Carbon 2010).1 E.O. 13563 commits the Administration to regulatory 

decision making “based on the best available science.”b

 Additionally, the interagency group 

recommended in 2010 that the SCC estimates be revisited on a regular basis or as model updates 

that reflect the growing body of scientific and economic knowledge become available.c

 New 

versions of the three integrated assessment models used by the U.S. government to estimate the 

SCC (DICE, FUND, and PAGE), are now available and have been published in the peer 

reviewed literature. While acknowledging the continued limitations of the approach taken by the 

interagency group in 2010 (documented in the original 2010 TSD), this document provides an 

update of the SCC estimates based solely on the latest peer-reviewed version of the models, 

replacing model versions that were developed up to ten years ago in a rapidly evolving field. It 

does not revisit other assumptions with regard to the discount rate, reference case socioeconomic 

and emission scenarios, or equilibrium climate sensitivity. Improvements in the way damages are 

modeled are confined to those that have been incorporated into the latest versions of the models 

by the developers themselves in the peer-reviewed literature. The Environmental Protection 

Agency (EPA), in collaboration with other Federal agencies such as the Department of Energy 

(DOE), continues to investigate potential improvements to the way in which economic damages 

associated with changes in CO2 emissions are quantified. 

Section II summarizes the major updates relevant to SCC estimation that are contained in 

the new versions of the integrated assessment models released since the 2010 interagency report. 

Section III presents the updated schedule of SCC estimates for 2010 – 2050 based on these 

versions of the models. Section IV provides a discussion of recent workshops to support 

improvements in SCC estimation.

a

 In this document, we present all values of the SCC as the cost per metric ton of CO2 emissions. Alternatively, one 

could report the SCC as the cost per metric ton of carbon emissions. The multiplier for translating between mass of 

CO2 and the mass of carbon is 3.67. b http://www.whitehouse.gov/sites/default/files/omb/inforeg/eo12866/eo13563_01182011.pdf

c See p. 1, 3, 4, 29, and 33 (Interagency Working Group on Social Cost of Carbon 2010).1

14B-1 

 
14B.3 Summary of Model Updates 

This section briefly summarizes changes integrated into the most recent versions of the 

three integrated assessment models (IAMs) used by the interagency group in 2010. We focus on 

describing those model updates that are relevant to estimating the social cost of carbon. For 

example, both the DICE and PAGE models now include an explicit representation of sea level 

rise damages. Other revisions to PAGE include: updated adaptation assumptions, revisions to 

ensure damages are constrained GDP, updated regional scaling of damages, and a revised 

treatment of potentially abrupt shifts in climate damages. In the most recent version of DICE, 

the model’s simple carbon cycle has been updated to be more consistent with a relatively more 

complex climate model. The FUND model includes updated damage functions for sea level rise 

impacts, the agricultural sector, and reduced space heating requirements, as well as changes to 

the response of temperature to the buildup of GHG concentrations and the inclusion of indirect 

effects of methane emissions. Changes made to parts of the models that are superseded by the 

interagency working group’s modeling assumptions – regarding climate sensitivity, discounting, 

and socioeconomic variables – are not discussed. 

14B.3.1 DICE

Changes in the DICE model relevant for the SCC estimates developed by the interagency 

working group include: 1) updated parameter values for the carbon cycle model, 2) an explicit 

representation of sea level dynamics, and 3) a re-calibrated damage function that includes an 

explicit representation of economic damages from sea level rise. Changes were also made to 

other parts of the DICE model—including the equilibrium climate sensitivity parameter, the rate 

of change of total factor productivity, and the elasticity of the marginal utility of consumption—

but these components of DICE are superseded by the interagency working group’s assumptions 

and so will not be discussed here. More details on DICE2007 can be found in Nordhaus (2008)2

and on DICE2010 in Nordhaus (2010)3 and the associated on-line appendix containing 

supplemental information. 

14B.3.1.1 CARBON CYCLE PARAMETERS

DICE uses a three-box model of carbon stocks and flows to represent the accumulation 

and transfer of carbon among the atmosphere, the shallow ocean and terrestrial biosphere, and 

the deep ocean. These parameters are “calibrated to match the carbon cycle in the Model for the 

Assessment of Greenhouse Gas Induced Climate Change (MAGICC)” (Nordhaus 2008 p 44).2d

Carbon cycle transfer coefficient values in DICE2010 are based on re-calibration of the model to 

match the newer version of MAGICC (Nordhaus 2010 p 2).3 For example, in DICE2010 in each 

decade, 12 percent of the carbon in the atmosphere is transferred to the shallow ocean, 4.7 

percent of the carbon in the shallow ocean is transferred to the atmosphere, 94.8 percent remains 

in the shallow ocean, and 0.5 percent is transferred to the deep ocean. For comparison, in DICE 

2007, 18.9 percent of the carbon in the atmosphere is transferred to the shallow ocean each 

decade, 9.7 percent of the carbon in the shallow ocean is transferred to the atmosphere, 85.3 

percent remains in the shallow ocean, and 5 percent is transferred to the deep ocean. 

d MAGICC is a simple climate model initially developed within the U.S. National Center for Atmospheric Research 

that has been used heavily by the Intergovernmental Panel on Climate Change (IPCC) to emulate projections from 

much more sophisticated state of the art earth system simulation models (Randall et al. 2007).4

14B-2 

 
The implication of these changes for DICE2010 is in general a weakening of the ocean as 

a carbon sink and therefore a higher concentration of carbon in the atmosphere than in 

DICE2007, for a given path of emissions. All else equal, these changes will generally increase 

the level of warming and therefore the SCC estimates in DICE2010 relative to those from 

DICE2007. 

14B.3.1.2 SEA LEVEL DYNAMICS

A new feature of DICE2010 is an explicit representation of the dynamics of the global 

average sea level anomaly to be used in the updated damage function (discussed below). This 

section contains a brief description of the sea level rise (SLR) module; a more detailed 

description can be found on the model developer’s website.e The average global sea level 

anomaly is modeled as the sum of four terms that represent contributions from: 1) thermal 

expansion of the oceans, 2) melting of glaciers and small ice caps, 3) melting of the Greenland 

ice sheet, and 4) melting of the Antarctic ice sheet. 

The parameters of the four components of the SLR module are calibrated to match 

consensus results from the IPCC’s Fourth Assessment Report.4 f The rise in sea level from 

thermal expansion in each time period (decade) is 2 percent of the difference between the sea 

level in the previous period and the long run equilibrium sea level, which is 0.5 meters per 

degree Celsius (°C) above the average global temperature in 1900. The rise in sea level from the 

melting of glaciers and small ice caps occurs at a rate of 0.008 meters per decade per °C above 

the average global temperature in 1900. 

The contribution to sea level rise from melting of the Greenland ice sheet is more 

complex. The equilibrium contribution to SLR is 0 meters for temperature anomalies less than 

1 oC and increases linearly from 0 meters to a maximum of 7.3 meters. The contribution to SLR 

in each period is proportional to the difference between the previous period’s sea level anomaly 

and the equilibrium sea level anomaly, where the constant of proportionality increases with the 

temperature anomaly in the current period. 

The contribution to SLR from the melting of the Antarctic ice sheet is -0.001 meters per 

decade when the temperature anomaly is below 3 °C and increases linearly to a maximum rate of 

0.025 meters per decade at a temperature anomaly of 6 °C. 

14B.3.1.3 RE-CALIBRATED DAMAGE FUNCTION

Economic damages from climate change in the DICE model are represented by a 

fractional loss of gross economic output in each period. A portion of the remaining economic 

output in each period (net of climate change damages) is consumed and the remainder is invested 

in the physical capital stock to support future production, so each period’s climate damages will 

reduce consumption in that period and in all future periods due to the lost investment. The 

fraction of output in each period that is lost due to climate change impacts is represented as one 

e Documentation on the new sea level rise module of DICE is available on William Nordhaus’ website at: 

http://nordhaus.econ.yale.edu/documents/SLR_021910.pdf.

f For a review of post-IPCC AR4 research on sea level rise, see Nicholls et al. (2011)5 and NAS (2011).6

 

14B-3 

 
minus a fraction, which is one divided by a quadratic function of the temperature anomaly, 

producing a sigmoid (“S”-shaped) function. The loss function in DICE2010 has been expanded 

by adding a quadratic function of SLR to the quadratic function of temperature. In DICE2010 the 

temperature anomaly coefficients have been recalibrated to avoid double-counting damages from 

sea level rise that were implicitly included in these parameters in DICE2007. 

The aggregate damages in DICE2010 are illustrated by Nordhaus (2010 p 3),3 who notes 

that “...damages in the uncontrolled (baseline) [i.e., reference] case ... in 2095 are $12 trillion, 

or 2.8 percent of global output, for a global temperature increase of 3.4 o

C above 1900 levels.” 

This compares to a loss of 3.2 percent of global output at 3.4 o

C in DICE2007. However, in 

DICE2010 (as downloaded from the homepage of William Nordhaus), annual damages are lower 

in most of the early periods but higher in later periods of the time horizon than would be 

calculated using the DICE2007 damage function. Specifically, the percent difference between 

damages in the base run of DICE2010 and those that would be calculated using the DICE2007 

damage function starts at +7 percent in 2005, decreases to a low of -14 percent in 2065, then 

continuously increases to +20 percent by 2300 (the end of the interagency analysis time horizon), 

and to +160 percent by the end of the model time horizon in 2595. The large increases in the far 

future years of the time horizon are due to the permanence associated with damages from sea 

level rise, along with the assumption that the sea level is projected to continue to rise long after 

the global average temperature begins to decrease. The changes to the loss function generally 

decrease the interagency working group SCC estimates slightly, all else equal.

14B.3.2 FUND

FUND version 3.8 includes a number of changes over the previous version 3.5 used in 

the interagency report. Documentation supporting FUND and the model’s source code for all 

versions of the model is available from the model authors.g Notable changes, due to their impact 

on the estimates of expected SCC, are adjustments to the space heating, agriculture, and sea level 

rise damage functions in addition to changes to the temperature response function and the 

inclusion of indirect effects from methane emissions.h

 We discuss each of these in turn. 

14B.3.2.1 SPACE HEATING

In FUND, the damages associated with the change in energy needs for space heating are 

based on the estimated impact due to one degree of warming. These baseline damages are scaled 

based on the forecasted temperature anomaly’s deviation from the one degree benchmark and 

adjusted for changes in vulnerability due to economic and energy efficiency growth. In FUND 

3.5, the function that scales the base year damages adjusted for vulnerability allows for the 

possibility that in some simulations the benefits associated with reduced heating needs may be an 

g http://www.fund-model.org/. This report uses version 3.8 of the FUND model, which represents a modest update 

to the most recent version of the model to appear in the literature (version 3.7) (Anthoff and Tol, 2013).7 For the 

purpose of computing the SCC, the relevant changes are associated with improving consistency with IPCC AR4 by 

adjusting the atmospheric lifetimes of CH4 and N2O and incorporating the indirect forcing effects of CH4, along 

with making minor stability improvements in the sea wall construction algorithm.

h The other damage sectors (water resources, space cooling, land loss, migration, ecosystems, human health, and 

extreme weather) were not the subject of significant updates.

14B-4 

 
unbounded convex function of the temperature anomaly. In FUND 3.8, the form of the scaling 

has been modified to ensure that the function is everywhere concave, meaning that for every 

simulation there will exist an upper bound on the benefits a region may receive from reduced 

space heating needs. The new formulation approaches a value of two in the limit as the 

temperature anomaly increases, or in other words, assuming no decrease in vulnerability, the 

reduced expenditures on space heating at any level of warming will not exceed two times the 

reductions experienced at one degree of warming. Since the reduced need for space heating 

represents a benefit of climate change in the model, or a negative damage, this change will 

increase the estimated SCC. This update accounts for a significant portion of the difference in the 

expected SCC estimates reported by the two versions of the model when run probabilistically. 

14B.3.2.2 SEA LEVEL RISE AND LAND LOSS

The FUND model explicitly includes damages associated with the inundation of dry land 

due to sea level rise. The amount of land lost within a region is dependent upon the proportion of 

the coastline being protected by adequate sea walls and the amount of sea level rise. In FUND 

3.5 the function defining the potential land lost in a given year due to sea level rise is linear in 

the rate of sea level rise for that year. This assumption implicitly assumes that all regions are 

well represented by a homogeneous coastline in length and a constant uniform slope moving 

inland. In FUND 3.8 the function defining the potential land lost has been changed to be a nonlinear function of sea level rise, thereby assuming that the slope of the shore line is not constant 

moving inland, with a positive first derivative. The effect of this change is to typically reduce the 

vulnerability of some regions to sea level rise based land loss, therefore having an effect of 

lowering the expected SCC estimate. The model has also been updated to assume that the value

of dry land at risk of inundation is not uniform across a region but will be a decreasing function 

of protection measure, thereby implicitly assuming that the most valuable land will be protected 

first.

14B.3.2.3 AGRICULTURE

In FUND, the damages associated with the agricultural sector are measured as 

proportional to the sector’s value. The fraction is made up of three additively separable 

components that represent the effects from carbon fertilization, the rate of temperature change, 

and the level of the temperature anomaly. In both FUND 3.5 and FUND 3.8, the fraction of the 

sector’s value lost due to the level of the temperature anomaly is modeled as a quadratic function 

with an intercept of zero. In FUND 3.5, the linear and quadratic coefficients are modeled as the 

ratio of two normal distributions. Within this specification, as draws from the distribution in the 

denominator approached zero the share of the sector’s value “lost” approaches (+/-) infinity 

independent of the temperature anomaly itself. In FUND 3.8, the linear and quadratic 

coefficients are drawn directly from truncated normal distributions so that they remain in the 

range [0,∞) and (−∞,0], respectively, where the means for the new distributions are set equal to 

the ratio of the means from the normal distributions used in the previous version. In general the 

impact of this change has been to increase the likelihood that increases in the temperature level 

will have either larger positive or negative effects on the agricultural sector relative to the 

previous version (through eliminating simulations in which the “lost” value approached (+/-) 

infinity). The net effect of this change on the SCC estimates is difficult to predict. 

14B-5 
14B.3.2.4 TEMPERATURE RESPONSE MODEL

The temperature response model translates changes in global levels of radiative forcing 

into the current expected temperature anomaly. In FUND, a given year’s increase in the 

cumulative temperature anomaly is based on a mean reverting function where the mean equals 

the equilibrium temperature anomaly that would eventually be reached if that year’s level of 

radiative forcing were sustained. The rate of mean reversion defines the rate at which the 

transient temperature approaches the equilibrium. In FUND 3.5, the rate of temperature response 

is defined as a decreasing linear function of equilibrium climate sensitivity to capture the fact 

that the progressive heat uptake of the deep ocean causes the rate to slow at higher values of the 

equilibrium climate sensitivity. In FUND 3.8, the rate of temperature response has been updated 

to a quadratic function of the equilibrium climate sensitivity. This change reduces the sensitivity 

of the rate of temperature response to the level of the equilibrium climate sensitivity. Therefore 

in FUND 3.8, the temperature response will typically be faster than in the previous version. The 

overall effect of this change is likely to increase estimates of the SCC as higher temperatures are 

reached during the timeframe analyzed and as the same damages experienced in the previous 

version of the model are now experienced earlier and therefore discounted less. 

14B.3.2.5 METHANE

The IPCC notes a series of indirect effects of methane emissions, and has developed 

methods for proxying such effects when computing the global warming potential of methane 

(Forster et al. 2007).8

 FUND 3.8 now includes the same methods for incorporating the indirect 

effects of methane emissions. Specifically, the average atmospheric lifetime of methane has been 

set to 12 years to account for the feedback of CH4 emissions on its own lifetime. The radiative 

forcing associated with atmospheric methane has also been increase by 40% to account for its net 

impact on ozone production and increase in stratospheric water vapor. The general effect of this 

increased radiative forcing will be to increase the estimated SCC values, where the degree to 

which this occurs will be dependent upon the relative curvature of the damage functions with 

respect to the temperature anomaly.

14B.3.3 PAGE

PAGE09 (Hope 2012)9 includes a number of changes from PAGE2002, the version used 

in the 2009 SCC interagency report. The changes that most directly affect the SCC estimates 

include: explicitly modeling the impacts from sea level rise, revisions to the damage function to 

ensure damages are constrained by GDP, a change in the regional scaling of damages, a revised 

treatment for the probability of a discontinuity within the damage function, and revised 

assumptions on adaptation. The model also includes revisions to the carbon cycle feedback and 

the calculation of regional temperatures. More details on PAGE2009 can be found in three 

working papers (Hope 2011a, 2011b, 2011c).10, 11, 12 A description of PAGE2002 can be found 

in Hope (2006).13

14B.3.3.1 SEA LEVEL RISE

While PAGE2002 aggregates all damages into two categories – economic and noneconomic impacts - PAGE2009 adds a third explicit category: damages from sea level rise. In the 

14B-6 
previous version of the model, damages from sea level rise were subsumed by the other damage 

categories. PAGE09 models damages from sea level rise as increasing less than linearly with sea 

level based on the assumption that low-lying shoreline areas will be associated with higher 

damages than current inland areas. Damages from the economic and non-economic sector were 

adjusted to account for the introduction of this new category. 

14B.3.3.2 REVISED DAMAGE FUNCTION TO ACCOUNT FOR SATURATION

In PAGE09, small initial economic and non-economic benefits (negative damages) are 

modeled for small temperature increases, but all regions eventually experience positive economic 

damages from climate change, where damages are the sum of additively separable polynomial 

functions of temperature and sea level rise. Damages transition from this polynomial function to 

a logistic path once they exceed a certain proportion of remaining Gross Domestic Product 

(GDP) to ensure that damages do not exceed 100 percent of GDP. This differs from PAGE2002, 

which allowed Eastern Europe to potentially experience large benefits from temperature 

increases, and which also did not bound the possible damages that could be experienced. 

14B.3.3.3 REGIONAL SCALING FACTORS

As in the previous version of PAGE, the PAGE09 model calculates the damages for the 

European Union (EU) and then, assumes that damages for other regions are proportional based 

on a given scaling factor. The scaling factor in PAGE09 is based on the length of a region’s 

coastline relative to the EU (Hope 2011b).11 Because of the long coastline in the EU, other 

regions are, on average, less vulnerable than the EU for the same sea level and temperature 

increase, but all regions have a positive scaling factor. PAGE2002 based its scaling factors on 

four studies reported in the IPCC’s third assessment report, and allowed for benefits from 

temperature increase in Eastern Europe, smaller impacts in developing countries, and higher 

damages in developing countries. 

14B.3.3.4 PROBABILITY OF A DISCONTINUITY 

In PAGE2002, the damages associated with a “discontinuity” were modeled as an 

expected value. That is, additional damages from an extreme event, such as extreme melting of 

the Greenland ice sheet, were multiplied by the probability of the event occurring and added to 

the damage estimate. In PAGE09, the probability of “discontinuity” is treated as a discrete event 

for each year in the model. The damages for each model run are estimated either with or without 

a discontinuity occurring, rather than as an expected value. A large‐scale discontinuity becomes 

possible when the temperature rises beyond some threshold value between 2 and 4°C. The 

probability that a discontinuity will occur beyond this threshold then increases by between 10 

and 30 percent for every 1°C rise in temperature beyond the threshold. If a discontinuity occurs, 

the EU loses an additional 5 to 25 percent of its GDP (drawn from a triangular distribution with a 

mean of 15 percent) in addition to other damages, and other regions lose an amount determined 

by the regional scaling factor. The threshold value for a possible discontinuity is lower than in 

PAGE2002, while the rate at which the probability of a discontinuity increases with the 

temperature anomaly and the damages that result from a discontinuity are both higher than in 

PAGE2002. The model assumes that only one discontinuity can occur and that the impact is 

phased in over a period of time, but once it occurs, its effect is permanent.

14B-7 
14B.3.3.5 ADAPTATION

As in PAGE2002, adaptation is available to increase the tolerable level of temperature 

change and can help mitigate any climate change impacts that still occur. In PAGE this 

adaptation is the same regardless of the temperature change or sea level rise and is therefore akin 

to what is more commonly considered a reduction in vulnerability. It is modeled by modifying 

the temperature change and sea level rise used in the damage function or by reducing the 

damages by some percentage. PAGE09 assumes a smaller decrease in vulnerability than the 

previous version of the model and assumes that it will take longer for this change in vulnerability 

to be realized. In the aggregated economic sector, at the time of full implementation, this 

adaptation will mitigate all damages up to a temperature increase of 1°C, and for temperature 

anomalies between 1°C and 3°C, it will reduce damages by 15-30 percent (depending on the 

region). However, it takes 20 years to fully implement this adaptation. In PAGE2002, adaptation 

was assumed to reduce economic sector damages up to 3°C by 50-90 percent after 20 years. 

Beyond 3°C, no adaptation is assumed to be available to mitigate the impacts of climate change. 

For the non-economic sector, in PAGE09 adaptation is available to reduce 15 percent of the 

damages due to a temperature increase between 0°C and 2°C and is assumed to take 40 years to 

fully implement, instead of 25 percent of the damages over 20 years assumed in PAGE2002. 

Similarly, adaptation is assumed to alleviate 25-50 percent of the damages from the first 0.20 to 

0.25 meters of sea level rise but is assumed to be ineffective thereafter. Hope (2011c)12 estimates 

that the less optimistic assumptions regarding the ability to offset impacts of temperature and sea 

level rise via adaptation increase the SCC by approximately 30 percent. 

14B.3.3.6 OTHER NOTEWORTHY CHANGES

Two other changes in the model are worth noting. A revised carbon cycle feedback is 

introduced to simulate decreased CO2 absorption by the terrestrial biosphere and ocean as the 

temperature rises. This feedback is linear in the average global and annual temperature anomaly 

but is capped at a maximum value. In the previous version of PAGE, an additional amount was 

added to the CO2 emissions each period to account for a decrease in ocean absorption and a loss 

of soil carbon. Also updated is the method by which the average global and annual temperature 

anomaly is downscaled to determine annual average regional temperature anomalies to be used 

in the regional damage functions. In the previous version of PAGE, the scaling was determined 

solely based on regional difference in emissions of sulfate aerosols. In PAGE09, this regional 

temperature anomaly is further adjusted using an additive factor that is based on the average 

absolute latitude of a region relative to the area weighted average absolute latitude of the Earth’s 

landmass.

14B.4 Revised SCC Estimates

The updated versions of the three integrated assessment models were run using the same 

methodology detailed in the 2010 TSD.1

 The approach along with the inputs for the 

socioeconomic emissions scenarios, equilibrium climate sensitivity distribution, and discount 

rate remains the same. This includes the five reference scenarios based on the EMF-22 modeling 

exercise, the Roe and Baker equilibrium climate sensitivity distribution calibrated to the Fourth 

Assessment Report of the IPCC, and three constant discount rates of 2.5, 3, and 5 percent. 

14B-8 
As was previously the case, the use of three models, three discount rates, and five 

scenarios produces 45 separate distributions for the SCC. The approach laid out in the TSD 

applied equal weight to each model and socioeconomic scenario in order to reduce the 

dimensionality down to three separate distributions representative of the three discount rates. The 

interagency group selected four values from these distributions for use in regulatory analysis. 

Three values are based on the average SCC across models and socio-economic-emissions 

scenarios at the 2.5, 3, and 5 percent discount rates, respectively. The fourth value was chosen to 

represent the higher-than-expected economic impacts from climate change further out in the tails 

of the SCC distribution. For this purpose, the 95th percentile of the SCC estimates at a 3 percent 

discount rate was chosen. (A detailed set of percentiles by model and scenario combination is 

available in the Annex.) As noted in the original TSD, “the 3 percent discount rate is the central 

value, and so the central value that emerges is the average SCC across models at the 3 percent 

discount rate” (TSD, p. 25). However, for purposes of capturing the uncertainties involved in 

regulatory impact analysis, the interagency group emphasizes the importance and value of 

including all four SCC values. 

Table 14B.4.1 shows the four selected SCC estimates in five year increments from 2010 

to 2050. Values for 2010, 2020, 2030, 2040, and 2050 are calculated by first combining all 

outputs (10,000 estimates per model run) from all scenarios and models for a given discount rate. 

Values for the years in between are calculated using basic linear interpolation. The full set of 

annual SCC estimates between 2010 and 2050 is reported in the Annex. 

Table 14B.4.1 Revised Social Cost of CO2, 2010 – 2050 (in 2007 dollars per ton of CO2) 

Discount 5.0% 3.0% 2.5% 3.0%

Year Avg Avg Avg 95th

2010 11 33 52 90

2015 12 38 58 109

2020 12 43 65 129

2025 14 48 70 144

2030 16 52 76 159

2035 19 57 81 176

2040 21 62 87 192

2045 24 66 92 206

2050 27 71 98 221

The SCC estimates using the updated versions of the models are higher than those 

reported in the TSD due to the changes to the models outlined in the previous section. Figure 

14B.4.1 illustrates where the four SCC values for 2020 fall within the full distribution for each 

discount rate based on the combined set of runs for each model and scenario (150,000 estimates 

in total for each discount rate). In general, the distributions are skewed to the right and have long 

tails. The Figure also shows that the lower the discount rate, the longer the right tail of the 

distribution. 

14B-9 
Figure 14B.4.1 Distribution of SCC Estimates for 2020 (in 2007$ per ton CO2) 

As was the case in the original TSD, the SCC increases over time because future 

emissions are expected to produce larger incremental damages as physical and economic systems 

become more stressed in response to greater climatic change. The approach taken by the 

interagency group is to allow the growth rate to be determined endogenously by the models 

through running them for a set of perturbation years out to 2050. Table 14B.4.2 illustrates how 

the growth rate for these four SCC estimates varies over time.

Table 14B.4.2 Average Annual Growth Rates of SCC Estimates between 2010 and 2050 

Average Annual 5.0% 3.0% 2.5% 3.0%

Rate (%) Avg Avg Avg 95th

2010-2020 1.2% 3.2% 2.4% 4.3%

2020-2030 3.4% 2.1% 1.7% 2.4%

2030-2040 3.0% 1.8% 1.5% 2.0%

2040-2050 2.6% 1.6% 1.3% 1.5%

The future monetized value of emission reductions in each year (the SCC in year t 

multiplied by the change in emissions in year t) must be discounted to the present to determine 

its total net present value for use in regulatory analysis. As previously discussed in the original 

TSD, damages from future emissions should be discounted at the same rate as that used to 

calculate the SCC estimates themselves to ensure internal consistency – i.e., future damages from 

climate change, whether they result from emissions today or emissions in a later year, should be 

discounted using the same rate. 

14B-10
14B.5 Other Model Limitations or Research Gaps

The 2010 interagency SCC technical support report discusses a number of important 

limitations for which additional research is needed. In particular, the document highlights the 

need to improve the quantification of both non-catastrophic and catastrophic damages, the 

treatment of adaptation and technological change, and the way in which inter-regional and intersectoral linkages are modeled. It also discusses the need to more carefully assess the implications 

of risk aversion for SCC estimation as well as the inability to perfectly substitute between 

climate and non-climate goods at higher temperature increases, both of which have implications 

for the discount rate used. EPA, DOE, and other agencies continue to engage in long-term 

research work on modeling and valuation of climate impacts that we expect will inform 

improvements in SCC estimation in the future.

14B-11
REFERENCES

1. Interagency Working Group on Social Cost of Carbon, Social Cost of Carbon for 

Regulatory Impact Analysis under Executive Order 12866, February, 2010. United States 

Government. <http://www.whitehouse.gov/sites/default/files/omb/inforeg/foragencies/Social-Cost-of-Carbon-for-RIA.pdf> 

2. Nordhaus, W., A Question of Balance. 2008. Yale University Press: New Haven. 

3. Nordhaus, W., Economic aspects of global warming in a post-Copenhagen environment.

Proceedings of the National Academy of Sciences, 2010. 107(26): pp. 11721-11726. 

4. Randall, D. A., R.A. Wood, S. Bony, R. Colman, T. Fichefet, J. Fyfe, V. Kattsov, A. 

Pitman, J. Shukla, J. Srinivasan, R.J. Stouffer, A. Sumi and K.E. Taylor, Climate Models 

and Their Evaluation. In Climate Change 2007: The Physical Science Basis. 

Contribution of Working Group I to the Fourth Assessment Report of the 

Intergovernmental Panel on Climate Change, S. Solomon, D. Qin, M. Manning, Z. Chen, 

M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller, Editor. 2007. Cambridge University 

Press: Cambridge, United Kingdom and New York, NY, USA. 

5. Nicholls, R. J., N. Marinova, J.A. Lowe, S. Brown, P. Vellinga, D. de Gusmão, J. Hinkel 

and R.S.J. Tol, Sea-level rise and its possible impacts given a ‘beyond 4°C world’ in the 

twenty-first century. Phil. Trans. R. Soc. A 2011. 369(1934): pp. 161-181. 

6. National Academy of Sciences, Climate Stabilization Targets: Emissions, 

Concentrations, and Impacts over Decades to Millennia. 2011. National Academies 

Press, Inc: Washington, DC.

7. Anthoff, D. and R. S. J. Tol, The uncertainty about the social cost of carbon: a 

decomposition analysis using FUND. Climatic Change, 2013(Forthcoming). 

8. Forster, P., V. Ramaswamy, P. Artaxo, T. Berntsen, R. Betts, D.W. Fahey, J. Haywood, 

J. Lean, D.C. Lowe, G. Myhre, J. Nganga, R. Prinn, G. Raga, M. Schulz and R. Van 

Dorland, Changes in Atmospheric Constituents and in Radiative Forcing. In Climate 

Change 2007: The Physical Science Basis. Contribution of Working Group I to the 

Fourth Assessment Report of the Intergovernmental Panel on Climate Change S. 

Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. 

Miller Editor. 2007. Cambridge University Press: Cambridge, United Kingdom and New 

York, NY, USA. 

9. Hope, C., Critical issues for the calculation of the social cost of CO2: why the estimates 

from PAGE09 are higher than those from PAGE2002. Climatic Change, 

2012(Forthcoming). 

14B-12
10. Hope, C., The PAGE09 Integrated Assessment Model: A Technical Description. 2011, 

Cambridge Judge Business School. 

<http://www.jbs.cam.ac.uk/research/working_papers/2011/wp1104.pdf>

11. Hope, C., The Social Cost of CO2 from the PAGE09 Model. 2011, Cambridge Judge 

Business School. 

<http://www.jbs.cam.ac.uk/research/working_papers/2011/wp1105.pdf>

12. Hope, C., New Insights from the PAGE09 Model: The Social Cost of CO2. 2011, 

Cambridge Judge Business School. 

<http://www.jbs.cam.ac.uk/research/working_papers/2011/wp1108.pdf>

13. Hope, C., The Marginal Impact of CO2 from PAGE2002: An Integrated Assessment 

Model Incorporating the IPCC’s Five Reasons for Concern. The Integrated Assessment 

Journal, 2006. 6(1): pp. 19-56. 

14B-13
ANNEX

Table 14B.5.1 Annual SCC Values: 2010-2050 (2007$/ton CO2) 

Discount 5.0% 3.0% 2.5% 3.0%

Year Avg Avg Avg 95th

2010 11 33 52 90

2011 11 34 54 94

2012 11 35 55 98

2013 11 36 56 102

2014 11 37 57 106

2015 12 38 58 109

2016 12 39 60 113

2017 12 40 61 117

2018 12 41 62 121

2019 12 42 63 125

2020 12 43 65 129

2021 13 44 66 132

2022 13 45 67 135

2023 13 46 68 138

2024 14 47 69 141

2025 14 48 70 144

2026 15 49 71 147

2027 15 49 72 150

2028 15 50 73 153

2029 16 51 74 156

2030 16 52 76 159

2031 17 53 77 163

2032 17 54 78 166

2033 18 55 79 169

2034 18 56 80 172

2035 19 57 81 176

2036 19 58 82 179

2037 20 59 84 182

2038 20 60 85 185

2039 21 61 86 188

2040 21 62 87 192

2041 22 63 88 195

2042 22 64 89 198

2043 23 65 90 200

2044 23 65 91 203

2045 24 66 92 206

2046 24 67 94 209

2047 25 68 95 212

2048 25 69 96 215

2049 26 70 97 218

2050 27 71 98 221

14B-14
Table 14B.5.2 202 Global SCC Estimates at 2.5 Percent Discount Rate (2007$/ton CO2) 

Percentile 1st 5th 10th 25th 50th Avg 75th 90th 95th 99th

Scenario PAGE

IMAGE 6 11 15 27 58 129 139 327 515 991

MERGE 4 6 9 16 34 78 82 196 317 649

MESSAGE 4 8 11 20 42 108 107 278 483 918

MiniCAM Base 5 9 12 22 47 107 113 266 431 872

5th Scenario 2 4 6 11 25 85 68 200 387 955

Scenario DICE

IMAGE 25 31 37 47 64 72 92 123 139 161

MERGE 14 18 20 26 36 40 50 65 74 85

MESSAGE 20 24 28 37 51 58 71 95 109 221

MiniCAM Base 20 25 29 38 53 61 76 102 117 135

5th Scenario 17 22 25 33 45 52 65 91 106 126

Scenario FUND

IMAGE -17 -1 5 17 34 44 59 90 113 176

MERGE -7 2 7 16 30 35 49 72 91 146

MESSAGE -19 -4 2 12 27 32 46 70 87 135

MiniCAM Base -9 1 8 18 35 45 59 87 108 172

5th Scenario -30 -12 -5 6 19 24 35 57 72 108

Table 14B.5.3 SCC Estimates at 3 Percent Discount Rate (2007$/ton CO2) 

Percentile 1st 5th 10th 25th 50th Avg 75th 90th 95th 99th

Scenario PAGE

IMAGE 4 7 10 18 38 91 95 238 385 727

MERGE 2 4 6 11 23 56 58 142 232 481

MESSAGE 3 5 7 13 29 75 74 197 330 641

MiniCAM Base 3 5 8 14 30 73 75 184 300 623

5th Scenario 1 3 4 7 17 58 48 136 264 660

Scenario DICE

IMAGE 16 21 24 32 43 48 60 79 90 102

MERGE 10 13 15 19 25 28 35 44 50 58

MESSAGE 14 18 20 26 35 40 49 64 73 83

MiniCAM Base 13 17 20 26 35 39 49 65 73 85

5th Scenario 12 15 17 22 30 34 43 58 67 79

Scenario FUND

IMAGE -14 -3 1 9 20 25 35 54 69 111

MERGE -8 -1 3 9 18 22 31 47 60 97

MESSAGE -16 -5 -1 6 16 18 28 43 55 88

MiniCAM Base -9 -1 3 10 21 27 35 53 67 107

5th Scenario -22 -10 -5 2 10 13 20 33 42 63

14B-15
Table 14B.5.4 2020 Global SCC Estimates at 5 Percent Discount Rate (2007$/ton CO2) 

Percentile 1st 5th 10th 25th 50th Avg 75th 90th 95th 99th

Scenario PAGE

IMAGE 1 2 2 5 10 28 27 71 123 244

MERGE 1 1 2 3 7 17 17 45 75 153

MESSAGE 1 1 2 4 9 24 22 60 106 216

MiniCAM Base 1 1 2 3 8 21 21 54 94 190

5th Scenario 0 1 1 2 5 18 14 41 78 208

Scenario DICE

IMAGE 6 8 9 11 14 15 18 22 25 27

MERGE 4 5 6 7 9 10 12 15 16 18

MESSAGE 6 7 8 10 12 13 16 20 22 25

MiniCAM Base 5 6 7 8 11 12 14 18 20 22

5th Scenario 5 6 6 8 10 11 14 17 19 21

Scenario FUND

IMAGE -9 -5 -3 -1 2 3 6 11 15 25

MERGE -6 -3 -2 0 3 4 7 12 16 27

MESSAGE -10 -6 -4 -1 2 2 5 9 13 23

MiniCAM Base -7 -3 -2 0 3 4 7 11 15 26

5th Scenario -11 -7 -5 -2 0 0 3 6 8 14

14B-16
CHAPTER 15. UTILITY IMPACT ANALYSIS

TABLE OF CONTENTS

15.1 INTRODUCTION ......................................................................................................... 15-1

15.2 METHODOLOGY ........................................................................................................ 15-1

15.3 UTILITY IMPACT RESULTS ..................................................................................... 15-2

15.3.1 Installed Capacity............................................................................................... 15-2

15.3.2 Electricity Generation ........................................................................................ 15-6

15.3.3 Results Summary ............................................................................................... 15-9

REFERENCES ........................................................................................................................ 15-10

LIST OF FIGURES

Figure 15.3.1 Commercial Refrigeration Equipment: Total Capacity Reduction ..................... 15-3

Figure 15.3.2 Commercial Refrigeration Equipment: Coal Capacity Reduction ...................... 15-3

Figure 15.3.3 Commercial Refrigeration Equipment: Nuclear Capacity Reduction ................. 15-4

Figure 15.3.4 Commercial Refrigeration Equipment: Gas Combined Cycle Capacity Reduction

............................................................................................................................ 15-4

Figure 15.3.5 Commercial Refrigeration Equipment: Peaking Capacity Reduction ................. 15-5

Figure 15.3.6 Commercial Refrigeration Equipment: Renewables Capacity Reduction .......... 15-5

Figure 15.3.7 Commercial Refrigeration Equipment: Total Generation Reduction .................. 15-6

Figure 15.3.8 Commercial Refrigeration Equipment: Coal Generation Reduction ................... 15-6

Figure 15.3.9 Commercial Refrigeration Equipment: Nuclear Generation Reduction ............. 15-7

Figure 15.3.10 Commercial Refrigeration Equipment: Gas Combined Cycle Generation 

Reduction ........................................................................................................... 15-7

Figure 15.3.11 Commercial Refrigeration Equipment: Peaking Generation Reduction ........... 15-8

Figure 15.3.12 Commercial Refrigeration Equipment: Renewables Generation Reduction ..... 15-8

LIST OF TABLES

Table 15.3.1 CRE: Summary of Utility Impact Results ............................................................ 15-9

15-i 
CHAPTER 15. UTILITY IMPACT ANALYSIS

15.1 INTRODUCTION

In the utility impact analysis, U.S. Department of Energy (DOE) analyzes the changes in 

electric installed capacity and generation that result for each trial standard level (TSL). 

The utility impact analysis uses a variant of the DOE Energy Information 

Administration’s (EIA’s) National Energy Modeling System (NEMS).a NEMS is a public 

domain, multi-sectored, partial equilibrium model of the U.S. energy sector. Each year, 

DOE/EIA uses NEMS to produce an energy forecast for the United States, the Annual Energy 

Outlook (AEO). DOE uses a variant of this model, referred to as NEMS-BT,b to account for 

selected utility impacts of energy conservation standards. DOE’s analysis consists of a 

comparison between model results for the most recent AEO Reference Case and for cases in 

which energy use is decremented to reflect the impact of standards. For the analysis of standards 

on commercial refrigeration equipment, DOE used the version of NEMS based on AEO2013.

1

NEMS-BT has a number of advantages that have led to its use in the analysis of energy 

conservation standards: 

• NEMS-BT uses a set of assumptions that are well known and fairly transparent, due 

to the exposure and scrutiny each AEO receives. 

• NEMS-BT is updated each year, with each edition of the AEO, to reflect changes in 

energy prices, supply trends, regulations, etc. 

• The comprehensiveness of NEMS-BT permits the modeling of interactions among the 

various energy supply and demand sectors. 

15.2 METHODOLOGY 

DOE uses NEMS-BT to estimate the marginal impacts of reduction in energy demand on 

the energy supply sector. In principle, marginal values should provide a better estimate of the 

actual impact of energy conservation standards. In practice, the numerical differences between 

marginal and average values may turn out to be smaller than the intrinsic uncertainties in the 

AEO. 

NEMS uses predicted growth in demand for each end use to build up a projection of the 

total electric system load growth. The system load shapes are converted internally to load 

duration curves, which are then used to estimate the most cost-effective additions to capacity. 

When electricity demand deviates from the AEO reference case, in general there are three interrelated effects: the annual generation (terawatt-hours (TWh)) from the stock of electric 

a For more information on NEMS, refer to the U.S. Department of Energy, Energy Information Administration 

documentation. A useful summary is National Energy Modeling System: An Overview 2003, DOE/EIA-0581(2003), 

March, 2003. b DOE/EIA approves use of the name NEMS to describe only an official version of the model without any 

modification to code or data. Because this analysis entails some minor code modifications and the model is run 

under various policy scenarios that are variations on DOE/EIA assumptions, DOE refers to it by the name NEMSBT (BT is DOE’s Building Technologies Program, under whose aegis this work has been performed). 

15-1 

 
generating capacity changes, the total generation capacity itself (gigawatts (GW)) may change, 

and the mix of capacity by fuel type may change. Each of these effects can vary for different 

types of end use. The change in total generating capacity is sensitive to the degree to which the 

end-use is peak coincident, while the capacity mix is sensitive to the hourly load shape 

associated with the end use.

To model the impact of a standard, DOE inputs a reduction to annual energy demand for 

the corresponding end use in the appropriate start year. The NEMS-BT model is run with the 

decremented energy demand to determine the modified build-out of capacity and total 

generation. Regional effects of a standard can be accounted for by defining the energy demand 

decrement as a function of census division. 

The output of the NEMS-BT analysis includes the effective marginal heat rate (ratio of 

the change in fuel consumption in quadrillion British thermal units (quads) to the change in 

generation in TWh), and the capacity reduction by fuel type for a given reduction in total 

generation. DOE uses the site energy savings multiplied by a transmission and distribution loss 

factor to estimate the reduction in generation for each TSL. The relationship between a 

reductionc in electricity generation (TWh) and the reduction in capacity (GW) is estimated based 

on the output of NEMS-BT model runs using the end-use specific energy demand decrement. 

Details on the approach used may be found in Coughlin (2013).2

NEMS-BT provides output for the following capacity types: coal, nuclear, 

combined cycle (natural gas), renewable sources, oil and natural gas steam, 

combustion turbine/diesel, pumped storage, fuel cells, and distributed generation (natural gas). 

DOE grouped oil and natural gas steam and combustion turbine/diesel into a peaking category, 

and grouped pumped storage, fuel cells, and distributed generation (natural gas) into an “other” 

category.

In general, energy conservation standards impact primarily fossil combustion (coal, 

natural gas and diesel) and renewables. Pumped storage and nuclear power are very insensitive 

to small changes in demand, while fuel cells and distributed generation make up a very small 

fraction (less than 1 percent) of the generation capacity base.

15.3 UTILITY IMPACT RESULTS

This section presents results of the analysis for all of the capacity types except “Other,” 

for which the impacts are very small.

15.3.1 Installed Capacity 

The figures in this section show the changes in U.S. electricity installed capacity that 

result for each TSL by major plant type for selected years. Note that a negative number means an 

increase in capacity under a TSL. 

c These reductions are defined relative to the AEO Reference Case.

15-2 

 
Figure 15.3.1 Commercial Refrigeration Equipment: Total Capacity Reduction 

Figure 15.3.2 Commercial Refrigeration Equipment: Coal Capacity Reduction 

0

200

400

600

800

1000

1200

1400

1600

201720222027203220372042204720522057

MW

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

0

50

100

150

200

250

300

350

201720222027203220372042204720522057

MW

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

15-3 
Figure 15.3.3 Commercial Refrigeration Equipment: Nuclear Capacity Reduction

Figure 15.3.4 Commercial Refrigeration Equipment: Gas Combined Cycle Capacity 

Reduction

0

5

10

15

20

25

30

35

201720222027203220372042204720522057

MW

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

0

50

100

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200

250

300

350

400

450

500

201720222027203220372042204720522057

MW

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

15-4 
Figure 15.3.5 Commercial Refrigeration Equipment: Peaking Capacity Reduction 

Figure 15.3.6 Commercial Refrigeration Equipment: Renewables Capacity Reduction

-150

-100

-50

0

50

100

150

200

250

300

350

400

201720222027203220372042204720522057

MW

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

0

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600

800

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1200

201720222027203220372042204720522057

MW

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

15-5 
15.3.2 Electricity Generation

The figures in this section show the annual change in electricity generation that result for 

each TSL by plant type. Coal-fired power plants account for most of the generation reduction. 

Note that a negative number means an increase in generation under a TSL.

Figure 15.3.7 Commercial Refrigeration Equipment: Total Generation Reduction

Figure 15.3.8 Commercial Refrigeration Equipment: Coal Generation Reduction 

0

1000

2000

3000

4000

5000

6000

7000

201720222027203220372042204720522057

GWh

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

0

500

1000

1500

2000

2500

201720222027203220372042204720522057

GWh

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

15-6 
Figure 15.3.9 Commercial Refrigeration Equipment: Nuclear Generation Reduction

Figure 15.3.10 Commercial Refrigeration Equipment: Gas Combined Cycle Generation 

Reduction

0

50

100

150

200

250

300

201720222027203220372042204720522057

GWh

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

0

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1000

1500

2000

2500

3000

3500

201720222027203220372042204720522057

GWh

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

15-7 
Figure 15.3.11 Commercial Refrigeration Equipment: Peaking Generation Reduction

Figure 15.3.12 Commercial Refrigeration Equipment: Renewables Generation Reduction

-200

-150

-100

-50

0

50

100

150

GWh

201720222027203220372042204720522057

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

0

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201720222027203220372042204720522057

GWh

TSL 1 TSL 2 TSL 3 TSL 4 TSL 5

15-8 
15.3.3 Results Summary 

Table 15.3.1 presents a summary of the utility impact results for commercial refrigeration 

equipment. 

Table 15.3.1 CRE: Summary of Utility Impact Results

Year

TSL

1 2 3 4 5

Installed Capacity Reduction (MW)

2020 10.13 18.10 39.42 42.92 54.75 

2025 34.99 62.51 136.15 148.23 189.09 

2030 82.72 147.80 321.91 350.47 447.10 

2035 148.65 265.58 578.45 629.77 803.39 

2040 253.41 452.75 986.11 1,073.61 1,369.59 

Electricity Generation Reduction (GWh)

2020 279.06 498.57 1,085.92 1,182.27 1,508.21 

2025 607.33 1,085.07 2,363.35 2,573.04 3,282.41 

2030 852.78 1,523.61 3,318.51 3,612.96 4,609.02 

2035 921.64 1,646.63 3,586.45 3,904.67 4,981.15 

2040 996.24 1,779.91 3,876.76 4,220.74 5,384.36 

15-9 
REFERENCES

1. U.S. Department of Energy, Energy Information Administration, Annual Energy Outlook 

2013. 2013. Washington, DC. (Last accessed May 1, 2013.) 

<http://www.eia.gov/forecasts/aeo/>.

2. Coughlin, K. 2013. Projections of Full-Fuel-Cycle Energy and Emissions Metrics. 

Lawrence Berkeley National Laboratory, Report Number LBNL-6025E. 

<http://eetd.lbl.gov/publications/projections-of-full-fuel-cycle-energy-and-emissionsmetrics>.

15-10
CHAPTER 16. EMPLOYMENT IMPACT ANALYSIS

TABLE OF CONTENTS

16.1 INTRODUCTION ............................................................................................................ 16-1

16.2 ASSUMPTIONS ............................................................................................................... 16-1

16.3 METHODOLOGY ........................................................................................................... 16-1

16.4 SHORT-TERM RESULTS ............................................................................................... 16-2

16.5 LONG-TERM RESULTS ................................................................................................. 16-3

REFERENCES .......................................................................................................................... 16-5

LIST OF TABLES

Table 16.4.1 Net Short-Term Change in Employment .............................................................. 16-3

16-i
CHAPTER 16. EMPLOYMENT IMPACT ANALYSIS

16.1 INTRODUCTION

The U.S. Department of Energy’s (DOE) employment impact analysis is designed to 

estimate indirect national job creation or elimination resulting from proposed standards due to 

reallocation of associated expenditures for purchasing and operating commercial refrigeration 

equipment. Job increases or decreases reported in this chapter are separate from the direct 

commercial refrigeration equipment sector employment impacts reported in chapter 12, and 

reflect the employment impact of efficiency standards on all other sectors of the economy. DOE 

conducted this analysis as part of this notice of proposed rulemaking (NOPR). 

16.2 ASSUMPTIONS

DOE expects amended energy conservation standards to decrease energy use and

therefore reduce energy expenditures. The savings in energy expenditures may be spent on new 

investments, or not spent at all (i.e., they may remain “saved”). Amended standards may increase 

the purchase price of commercial refrigeration equipment, including the retail price plus sales 

tax, and could in some cases increase installation costs. 

Using an input/output econometric model of the U.S. economy, this analysis estimated 

the short-term effect of these expenditure impacts on net economic output and employment. 

DOE intends this analysis to quantify the indirect employment impacts of these expenditure 

changes. DOE evaluated direct employment impacts at manufacturers’ facilities in the 

manufacturer impact analysis (see chapter 12). 

DOE notes that the ImSET model (Impact of Sector Energy Technologies) is not a 

general equilibrium forecasting model, and understands the uncertainties involved in projecting 

employment impacts, especially changes in the later years of the analysis.1 Because ImSET does 

not incorporate price changes, the employment effects predicted by ImSET would overestimate 

the magnitude of actual job impacts over the long run for this rule. Since input/output models do 

not allow prices to bring markets into equilibrium, they are best used for short-run analysis. DOE 

therefore included a qualitative discussion of how labor markets are likely to respond in the 

longer term. In future rulemakings, DOE may consider the use of other modeling approaches for 

examining long-run employment impacts. 

16.3 METHODOLOGY

DOE based its analysis on an input/output model of the U.S. economy that estimates the 

effects of standards on major sectors of the economy related to buildings, and the net impact of 

standards on jobs. The Pacific Northwest National Laboratory (PNNL) developed the model 

using ImSET 3.1.12 as a successor to Impact of Building Energy Efficiency Programs

(ImBuild),3 a special purpose version of the Impact Analysis for Planning (IMPLAN)4 national 

input/output model. ImSET estimates the employment and income effects of building energy 

technologies. Compared with simple economic multiplier approaches, ImSET allows for more 

complete and automated analysis of the economic impacts of energy-efficiency investments in 

buildings. 

16-1
In an input/output model, the level of employment in an economy is determined by the 

relationships of different sectors of the economy and spending flows among them. Different 

sectors have different levels of labor intensity and so changes in the level of spending (e.g., due 

to the effects of an efficiency standard) in one sector of the economy will affect flows in other 

sectors, which affects the overall level of employment.

ImSET uses a 187-sector model of the national economy to predict the economic effects 

of residential and commercial buildings’ technologies. ImSET collects estimates of initial 

investments, energy savings, and economic activity associated with spending the savings 

resulting from standards (e.g., changes in final demand in personal consumption, business 

investment and spending, and government spending). It provides overall estimates of the change 

in national output for each input/output sector. The model applies estimates of employment and

wage income per dollar of economic output for each sector and calculates impacts on national 

employment and wage income.

Energy-efficiency technology primarily affects the U.S. economy along three spending 

pathways. First, general investment funds are diverted to sectors that manufacture, install, and 

maintain energy-efficient equipment. The increased cost of equipment leads to higher 

employment in the equipment manufacturing sectors and lower employment in other economic 

sectors. Second, commercial firm and residential spending are redirected from utilities toward 

firms that supply production inputs. Third, electric utility sector investment funds are released 

for use in other sectors of the economy. When customers use less energy, electric utilities 

experience relative reductions in demand, which leads to reductions in utility sector investment 

and employment. 

DOE also notes that the employment impacts estimated with ImSET for the entire 

economy differ from the employment impacts in the commercial refrigeration equipment 

manufacturing sector estimated in chapter 12 using the Government Regulatory Impact Model 

(GRIM). The methodologies used and the sectors analyzed in the ImSET and GRIM models are 

different. 

16.4 SHORT-TERM RESULTS

The results in this section refer to impacts of commercial refrigeration equipment 

standards relative to the base case. DOE disaggregated the impact of standards on employment 

into three component effects: increased capital investment costs, decreased energy costs, and 

changes in operations and maintenance costs. DOE anticipates no change in operations and 

maintenance costs for commercial refrigeration equipment. DOE presents the summary impact. 

Conceptually, one can consider the impact of the rule in its first year on three aggregate 

sectors: the commercial refrigeration equipment production sector, the energy generation sector, 

and the general consumer goods sector (as mentioned previously, ImSET’s calculations are made 

at a much more disaggregate level). By raising energy efficiency, the rule increases the purchase 

price of commercial refrigeration equipment; this increase in expenditures causes an increase in 

employment in this sector. At the same time, the improvements in energy efficiency reduce 

expenditures on electricity. The reduction in electricity demand causes a reduction in 

employment in that sector. Finally, based on the net impact of increased expenditures on 

16-2
commercial refrigeration equipment and reduced expenditures on electricity, expenditures on 

everything else are either positively or negatively affected, increasing or reducing jobs in that 

sector accordingly. The model also captures any indirect jobs created or lost by changes in 

consumption due to changes in employment (as more workers are hired they consume more 

goods, which generates more employment, the converse is true for workers laid off). 

Table 16.4.1 presents the modeled net employment impact from the rule in 2017 and 

2021. As mentioned in chapter 12, 90 percent of commercial refrigeration equipment is produced 

domestically and 10 percent is imported. The net employment impact estimate is sensitive to 

assumptions regarding the return to the U.S. economy of money spent on imported commercial 

refrigeration equipment. The two scenarios bounding the ranges presented in Table 16.4.1

represent situations in which none of the money spent on imported microwaves returns to the 

U.S. economy and all of the money spent on imported commercial refrigeration returns to the 

U.S. economy (low and high bounds, respectively). The U.S. trade deficit in recent years 

suggests that between 50 percent and 75 percent of the money spent on imported commercial 

refrigeration equipment is likely to return, with employment impacts falling within the ranges 

presented below.

Table 16.4.1 Net Short-Term Change in Employment 

Trial Standard Level 2017* 2021

1 35 to 38 198 to 201

2 53 to 61 345 to 354

3 74 to 108 719 to 749

4 60 to 105 760 to 801

5 (728) to (363)** 130 to 504

* Compliance date of standard levels is 2017.

** Values in parentheses are negative values.

16.5 LONG-TERM RESULTS

Due to the short payback period of energy-efficiency improvements mandated by this 

rule, over the long term DOE expects the energy savings to customers to increasingly dominate 

the increase in equipment costs, resulting in increased aggregate savings to customers. As a 

result, DOE expects demand for electricity to decrease over time and demand for other goods to 

increase. Since the electricity generation sector is relatively capital intensive compared to the 

consumer goods sector, the net effect will be an increase in labor demand. In equilibrium, this 

should lead to upward pressure on wages and a shift in employment away from electricity 

generation and toward consumer goods. Note that in long-run equilibrium there is no net effect 

on total employment because wages adjust to bring the labor market into equilibrium. For 

context, the Office of Management and Budget (OMB) currently assumes that the official

unemployment rate may decline to 6.9 percent in 2014 and drop further to 5.3 percent in 

2017.5

 The unemployment rate in 2017 is generally considered to be close to “full 

employment.” When an economy is at full employment, any effects on net employment are 

likely to be transitory as workers change jobs (e.g., some workers may need to be retrained or 

require time to search for new jobs) rather than enter or exit longer-term unemployment.

Nonetheless, even to the extent that markets are slow to adjust, DOE anticipates that net labor 

market impacts will be negligible over time due to the small magnitude of the short-term effects 

16-3
presented in Table 16.4.1. The ImSET model projections, assuming no price or wage effects until 

2021, are included in Table 16.4.1. 

16-4
REFERENCES

1. Scott, M., J.M. Roop, R.W. Schultz, D.M. Anderson, and K.A. Cort. The Impact of DOE 

Building Technology Energy Efficiency Programs on U.S. Employment, Income, and 

Investment. Energy Economics, 2008. 30(5): pp. 2283-2301. 

2. Scott M.J., O.V. Livingston, P.J. Balducci, J.M. Roop, and R.W. Schultz. ImSET: Impact 

of Sector Energy Technologies Model Description and User’s Guide. 2009. Pacific 

Northwest National Laboratory: Richland, WA. Report No. PNNL-18412. 

 

3. Scott, M.J., D.J. Hostick, and D.B. Belzer. ImBuild: Impact of Building Energy Efficiency 

Programs.1998. Pacific Northwest National Laboratory, Richland, WA. Report No. PNNL11884. 

4. Minnesota IMPLAN Group Inc. IMPLAN Professional: User’s Guide, Analysis Guide, 

Data Guide. 1997. Stillwater, MN. 

5. U.S. Office of Management and Budget. Fiscal Year 2012 Mid-Session Review. 2011. 

Washington, D.C. <www.whitehouse.gov/sites/default/files/omb/budget/fy2012/ 

assets/12msr.pdf> 

16-5
CHAPTER 17. REGULATORY IMPACT ANALYSIS 

TABLE OF CONTENTS

17.1 INTRODUCTION ......................................................................................................... 17-1

17.2 METHODOLOGY ........................................................................................................ 17-1

17.3 NON-REGULATORY POLICIES ................................................................................ 17-2

17.3.1 No New Regulatory Action ............................................................................... 17-2

17.3.2 Customer Rebates .............................................................................................. 17-2

17.3.3 Consumer Tax Credits ....................................................................................... 17-4

17.3.4 Voluntary Energy Efficiency Programs ............................................................. 17-5

17.3.5 Early Replacement ............................................................................................. 17-5

17.4 SUMMARY OF RESULTS FOR NON-REGULATORY ALTERNATIVES ............ 17-5

REFERENCES .......................................................................................................................... 17-7

LIST OF TABLES

Table 17.1.1 Non-Regulatory Alternatives to Standards ........................................................... 17-1

Table 17.3.1 Customer Rebate NES and NPV Comparison to TSL 4 ....................................... 17-3

Table 17.3.2 Tax Credit NES and NPV Comparison to TSL 4 ................................................. 17-5

Table 17.4.1 Cumulative NES of Non-Regulatory Alternatives Compared to the Proposed 

Standard ............................................................................................................. 17-6

Table 17.4.2 Cumulative NPV of Non-Regulatory Alternatives Compared to the Proposed 

Standard ............................................................................................................. 17-6

17-i 
CHAPTER 17. REGULATORY IMPACT ANALYSIS

17.1 INTRODUCTION

Under the Process Rule (Procedures for Consideration of New or Revised Energy 

Conservation Standards for Consumer Products, 61 FR 36974 (July 15, 1996)), the U.S.

Department of Energy (DOE) is committed to continually explore non-regulatory alternatives to 

standards. DOE will prepare a draft regulatory impact analysis pursuant to E.O. 12866, 

Regulatory Planning and Review, which will be subject to review under the Executive Order by 

the Office of Management and Budget’s Office of Information and Regulatory Affairs. 

58 FR 51735 (Sept. 30, 1993). 

DOE has identified five major alternatives to standards that represent feasible policy 

options to reduce commercial refrigeration equipment energy consumption. DOE evaluated each 

alternative’s ability to achieve significant energy savings at a reasonable cost, and compared the 

effectiveness of each one to the effectiveness of the proposed standards rule. 

The non-regulatory means of achieving energy savings that DOE proposes to analyze are 

listed in Table 17.1.1. In support of DOE’s notice of proposed rulemaking, DOE includes a 

quantitative analysis of each alternative, the methodology for which is discussed briefly in this 

technical support document (TSD). 

Table 17.1.1 Non-Regulatory Alternatives to Standards 

No new regulatory action

Consumer tax credits

Customer rebates

Voluntary energy efficiency targets

Early replacement

17.2 METHODOLOGY

DOE uses the national impact analysis (NIA) spreadsheet models to calculate the national 

energy savings (NES) and the net present value (NPV) corresponding to each non-regulatory 

alternative. The NIA model is discussed in chapter 10 of this TSD. To compare each alternative 

quantitatively to the proposed energy conservation standards, DOE quantifies the effect of each 

alternative on the purchase and use of energy efficient commercial refrigeration equipment. After 

quantifying each alternative, DOE makes the appropriate revisions to the inputs in the NIA 

models to estimate energy savings compared to the base-case scenario. Key inputs that DOE 

typically revises in these models include the following: 

• energy prices and escalation factors

• implicit market discount rates for trading off purchase price against operating expense 

when choosing product efficiency 

• business purchase prices and operating costs 

• purchase price-versus-efficiency relationships

• product stock data 

17-1 
The key measures of the impact of each alternative are the following: 

• Energy use reflects the cumulative energy use of the product from the effective date 

of the new standard to the year 2046. 

• National energy savings represents the cumulative national energy use from the basecase projection minus the alternative policy case projection, given in quadrillion 

British thermal units (quads). 

• Net present value represents the value in 2012$ (discounted to 2013) of net monetary 

savings from products bought during the period from the effective date of the policy 

(2017) through the end of the analysis period (2046).

17.3 NON-REGULATORY POLICIES

17.3.1 No New Regulatory Action 

The base-case scenario is the one in which no new regulatory action is taken with regard 

to the energy efficiency of commercial refrigeration equipment, as described in the NIA

(chapter 10 of this TSD). The base-case scenario provides the basis of comparison for all other 

non-regulatory alternatives. By definition, no new regulatory action yields zero energy savings 

and an NPV of zero dollars. 

17.3.2 Customer Rebates

Customer rebates cover a portion of the difference in incremental product price between 

products meeting baseline efficiency levels and those meeting higher efficiency levels, resulting 

in a higher percentage of consumers purchasing more efficacious models and decreased 

aggregated energy use compared to the base-case scenario. 

DOE surveyed the various rebate programs available in the United States in 2011. 

Typically, local utility companies offer rebates to grocery stores that retrofit their display cases 

with energy efficiency components, such as light-emitting diode (LED) lamps, electronically 

commutated motor (ECM) fan motors, night curtains, and higher efficiency doors. As an 

example, Eugene Water and Electric Board offers $16 per linear foot of LED when a 

refrigeration case is retrofit to replace T8 fluorescent lamps; $11 per linear foot for installing 

night covers on a vertical open refrigerator; $3 per lamp for installing a motion sensor control; 

and $35 per motor when a refrigerated display case is retrofitted with ECM fan motors.1

Examples of similar rebate programs on offer are from Pacific Gas and Electric Company as part 

of its EnergySmart Grocer Program2 and Santee Cooper Business as part of its 2010-2011 

Commercial Prescriptive Rebate Program.

3

 

DOE used the rebate amounts on offer and compared them to the manufacturer selling 

price (MSP) increments of the higher design option levels (chapter 5 of this TSD) of certain

equipment classes. Certain rebates on offer, such as rebates for retrofitting with ECM fan motors, 

were not applicable to this rulemaking because the commercial refrigeration equipment that is 

compliant to the 2009 final rule standards will most likely incorporate ECM fan motors. 

Therefore, the ECM fan motors are likely to be part of the base-case scenario for the current 

rulemaking. DOE calculated the rebate amounts a percentage of the MSP increments. An 

17-2 
approximate calculation of the rebate amount with respect to trial standard level (TSL) 4 for 

VOP.RC.M and VCT.RC.L equipment classes yielded a rebate percentage range from 50 to 

80 percent. 

Other types of rebates, on offer from a large number of utilities across the nation, are in 

the form of fixed rebate amounts for commercial customers who purchase refrigerators and 

freezers that are ENERGY STAR® compliant. DOE compared the typical rebate amounts to the 

MSP increments associated with TSL 4 for VCS.SC.M and VCT.SC.L equipment classes and 

found that the rebate amount as a percentage of MSP increments was approximately 50 percent 

in most cases.

Based on comparison with the incremental MSP values obtained from the engineering 

analysis, DOE chose to model a scenario where customers are offered, as rebates, 60 percent of 

the incremental installed cost of the commercial refrigeration equipment. The value of 60 percent 

is very high compared to most rebate programs and was chosen to approximate a high-rebate 

scenario.

DOE applied the 60-percent rebate to MSP increments at all efficiency levels for all the 

equipment classes and calculated the new installed costs of the equipment. These new installed 

costs were then used to recalculate the market shares of efficiency levels (see chapter 10 of this 

TSD). As the new equipment installed price of higher efficiency equipment is reduced, the 

market shares of efficiency levels shift towards higher efficiency levels resulting in savings 

compared to the base-case scenario.

Although the rebate program reduces the total installed cost to the customer, it is financed 

by tax revenues. Therefore, from a societal perspective, the installed cost at any efficiency level 

does not change with the rebate program; rather, part of the cost is transferred from the customer 

to taxpayers as a whole. Consequently, DOE assumed that equipment costs in the rebates 

scenario were identical to the NIA base-case scenario. 

DOE assumed that rebates would remain in effect for the duration of the analysis period. 

Table 17.3.1 presents the NES and NPV values for the 60-percent rebate scenario and compares 

them against the NES and NPV values at TSL 4 obtained from NIA (see TSD chapter 10). 

Table 17.3.1 Customer Rebate NES and NPV Comparison to TSL 4 

Policy Alternatives

Cumulative 

Energy Savings*

quads

Net Present Value**

billion 2012$

7%

Discount Rate

3%

Discount Rate

No New Regulatory Action 0 0 0

Customer Rebates (60% of MSP increments) 0.198 0.055 0.122

TSL 4 0.985 1.606 4.067

* Energy savings are in primary energy quads.

** Net present value is the value in the present of a time series of costs and savings.

17-3 
17.3.3 Consumer Tax Credits

Consumer tax credits are considered a viable non-regulatory market transformation 

program, as shown by the inclusion of Federal consumer tax credits in the Energy Policy Act of 

2005 (EPACT 2005; Pub L. 109-58, 119 Stat 1026 (2005)) for various residential appliances.

From a consumer perspective, the most important difference between rebate and tax credit 

programs is that a rebate can be obtained relatively quickly, whereas receipt of tax credits is 

delayed until income taxes are filed or a tax refund is provided by the Internal Revenue Service 

(IRS).

For the tax credits scenario, DOE did not find a suitable program for commercial 

customers to model the scenario. Therefore, DOE used a 5-percent/10-percent tax credit 

scenario. DOE first calculated the MSP increments over baseline for each TSL for each 

equipment class. For TSLs that had an increase in MSP between 10 and 15 percent over the 

baseline MSP, DOE applied a 5-percent tax credit, where the amount of tax credit is equal to 

5-percent of the MSP of the higher efficiency equipment. For TSLs that had increase of 

15 percent or more in MSP values over the baseline MSP, DOE applied a 10-percent tax credit. 

This type of tax credit scenario is an attempt to approximate a model where the tax credits are 

proportional to the magnitude of efficiency improvement with the implicit assumption being that 

the amount of MSP increase is proportional to the magnitude of increase in energy efficiency. 

DOE applied the 5-percent/10-percent tax credit to MSP increments at all efficiency 

levels, as described above, for all the equipment classes and calculated the new installed costs of 

the equipment. These new installed costs were then used to recalculate the market shares of 

efficiency levels. As the new equipment installed price of higher efficiency equipment is 

reduced, the market shares of efficiency levels shift towards higher efficiency levels, resulting in 

savings compared to the base-case scenario.

From a societal perspective, tax credits (like rebates) do not change the installed cost of 

the equipment, but rather transfer a portion of the cost from the consumer to taxpayers as a 

whole. DOE, therefore, assumed that equipment costs in the consumer tax credits scenario were 

identical to the NIA base case.

DOE assumed that tax credits would remain in effect for the duration of the analysis 

period. Table 17.3.2 presents the NES and NPV values for the 5-percent/10-percent tax credit 

scenario and compares them against the NES and NPV values at TSL 4 obtained from NIA (see 

TSD chapter 10). 

17-4 
Table 17.3.2 Tax Credit NES and NPV Comparison to TSL 4 

Policy Alternatives

Cumulative Energy 

Savings*

quads

Net Present Value**

billion 2012$

7%

Discount Rate

3%

Discount Rate

No New Regulatory Action 0 0 0

Customer Tax Credits 0.151 0.257 0.489

Today's Standards at TSL 4 0.985 1.606 4.067 * Energy savings are in primary energy quads. ** Net present value is the value in the present of a time series of costs and savings. 

17.3.4 Voluntary Energy Efficiency Programs

While it is possible that voluntary programs for equipment would be effective, DOE lacks 

a quantitative basis to determine how effective such a program might be. As previously noted, 

the economic and social considerations in play are broader than simple economic return to the 

equipment purchaser. DOE lacks the data necessary to quantitatively project the degree to which 

such voluntary programs for more expensive, higher efficiency equipment like commercial 

refrigeration equipment would modify the market. 

17.3.5 Early Replacement

Early replacement refers to the replacement of equipment before the end of its useful 

lives. The purpose of this policy is to retrofit or replace old, inefficient equipment with highefficiency units. DOE studied the feasibility of a Federal program to promote early replacement 

of appliances and equipment under EPACT 1992. In this study, DOE identified Federal policy

options for early replacement that include a direct national program, replacement of Federally 

owned equipment, promotion through equipment manufacturers, customer incentives, incentives 

to utilities, market behavior research, and building regulations. 

While cost-effective opportunities to install units that are more efficient exist, DOE 

determined that a Federal early replacement program is not economically justified because the 

market for commercial refrigeration equipment is relatively small, especially for federally owned 

equipment, and distributed across a broad set of customers; thus, the savings are not expected to 

be significant. 

17.4 SUMMARY OF RESULTS FOR NON-REGULATORY ALTERNATIVES

Table 17.4.1 and Table 17.4.2 show the NES and NPV for the non-regulatory alternatives 

analyzed. The case in which no regulatory action is taken constitutes the base-case scenario. 

Because this is the base case, NES and NPV are zero by definition. For comparison, the tables 

include the results of the NES and NPV at TSL 4 associated with the proposed energy 

conservation standard. 

17-5 
Table 17.4.1 Cumulative NES of Non-Regulatory Alternatives Compared to the Proposed 

Standard

Policy Alternatives Cumulative Primary NES

quads

No new regulatory action 0

Consumer tax credits 0.151

Customer rebates 0.198

Voluntary energy efficiency targets 0

Early replacement 0

Proposed standards (TSL 4) 0.985

Table 17.4.2 Cumulative NPV of Non-Regulatory Alternatives Compared to the Proposed 

Standard

Policy Alternatives

Cumulative Net Present Value

billion 2012$

7% Discount 3% Discount

No new regulatory action 0 0

Consumer tax credits 0.257 0.489

Customer rebates 0.055 0.122

Voluntary energy efficiency targets 0 0

Early replacement 0 0

Proposed standards (TSL 4) 1.606 4.067

As shown in Table 17.4.1 and Table 17.4.2, none of the policy alternatives DOE 

examined would achieve close to the amount of energy or monetary savings that could be 

realized under the proposed rule. In addition, implementing either tax credits or customer rebates 

would incur initial and/or administrative costs that were not considered in this analysis.

17-6 
REFERENCES

1. Eugene Water and Electric Board. Refrigeration Equipment Catalog. 2011. Eugene, OR. 

2. Pacific Gas and Electric Company. EnergySmart Grocer. 2011. (Last accessed October 26, 

2011.) <http://www.energysmartgrocer.org/grocers.php?u=1> 

3. Santee Cooper Business. Reduce the Use: Business – Rebates for Prescriptive Energy 

Efficient Equipment Installations and Upgrades. 2011. (Last accessed October 26, 2011.) 

<http://www.reducetheuse.com/ReduceTheUse/business_landingpage/business/pdfs/commer

cial_prescriptive_program_manual.pdf> 

17-7